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PREDICTION OF OUTCOME IN PATIENTS ADMITTED TOICU IN SEPSIS USING APACHE III SCORING SYSTEM
By
DR. VISHWAJEETH K PAI MBBS
Dissertation submitted to the Rajiv Gandhi University of Health Sciences,Karnataka, Bangalore in partial fulfillment of the requirements for the
degree of
DOCTOR OF MEDICINE IN GENERAL MEDICINE
Under the guidance of
DR. VIJAYLAXMI P.B MD
Professor
KARNATAKA INSTITUTE OF MEDICAL SCIENCES
HUBLI
2015
ACKNOWLEDGEMENTS
Though the acknowledgements are written at the end of dissertation completion, there
is a reason why it is put up initially. Only towards the end do we realize that there
were so many people who helped us in every possible way to accomplish this
phenomenal feat.
Foremost, I would like to pay my deep sense of gratitude and respect to my guide, Dr.
Vijaylaxmi P.B. Her patience, concern for the well being towards all post graduate
students is worth mentioning. I am very thankful to madam for guiding me all way
along.
I would also like to thank Dr. H Mallikarjuna Swamy, the Medical Superintendent
and Dr. Ishwar S Hasabi, Head of the department of Medicine for having guided me
over the past 3 years and I am immensely grateful to have worked in their esteemed
presence.
I would also like to thank all the Associate and Assistant Professors in the department,
specially would like to mention Dr. Chandrashekhar K and Dr. Kalinga B.E who
has guided me and encouraged me in every possible way.
It gives me tremendous pleasure in thanking Dr. K Sreedhara Ranganath Pai,
Professor and Head, Dr. N. Gopalan Kutty, Professor in the Department of
Pharmacology, Manipal College of Pharmaceutical Sciences, Manipal University and
their research scholar Mr. Pawan G. Nayak who are instrumental in deducing the
statistical results for the study and making it extremely simple and uncomplicated.
I
LIST OF ABBREVIATIONS
AaDO2 → Arterial- Alveolar Oxygen Diffusion Gradient
ACCP → American College of Chest Physicians
AIDS → Acquired Immuno Deficiency Syndrome
AKI → Acute Kidney Injury
APACHE-III → Acute Physiology and Chronic Health Evaluation III
APS → Acute Physiology Score
ARDS → Acute Respiratory Distress Syndrome
ATS → American Thoracic Society
AUC → Area Under Curve
BUN → Blood Urea Nitrogen
CD4+ → Cluster of Differentiation
CNS → Central Nervous System
COPD → Chronic Obstructive Pulmonary Disease
DBP → Diastolic Blood Pressure
DNA → Deoxyribose Nucleic Acid
ESICM → European Society of Intensive Care Medicine
ESRD → End Stage Renal Disease
II
FiO2 → Fraction of Inspired Oxygen
GCS → Glasgow Coma Scale
HIV → Human Immunodeficiency Virus
HLA → Human Leucocyte Antigen
ICU → Intensive Care Unit
ITU → Intensive Therapy Units
MAP → Mean Arterial Pressure
MELD → Model for End stage Liver Disease
MICU → Medical Intensive Care Unit
MODS → Multi Organ Dysfunction Syndrome
MPM → Mortality Prediction Model
NLF → Non Lactose Fermenting
PaCO2 → Partial pressure of Arterial Carbon Dioxide
pH → Power of Hydrogen
p-value → Probability value
RBS → Random Blood Sugar
RNA → Ribose Nucleic Acid
ROC → Receiver Operating Characteristic
RR → Respiratory Rate
III
SAPS → Simplified Acute Physiology Score
SBP → Systolic Blood Pressure
SCCM → Society for Critical Care Medicine
SD → Standard Deviation
SIRS → Systemic Inflammatory Response Syndrome
SIS → Surgical Infection Society
SOFA → Sepsis Related Organ Failure Assessment
Spp → Species
SVC → Superior Vena Cava
TISS → Therapeutic Intervention Scoring System
WBC → White Blood Cell
IV
ABSTRACT
BACKGROUND: Sepsis is the Intensive Care Units (ICU) is one of the biggest
challenges faced in clinical practice today. More hurdles are being faced with the
advent of multi-drug resistant organisms and increased use of invasive procedures in
the ICUs in the recent times. Scoring systems to assess the disease severity and
possible outcomes have been used over the past 3 decades. Conflicting evidences
have emerged regarding the reliability and the accuracy of such scoring systems.
Hence we would like to assess one such scoring system- Acute Physiology and
Chronic Health Evaluation (APACHE III) in predicting the outcome in patients
admitted to ICU with sepsis.
OBJECTIVES: To study the predictive efficacy of the APACHE III score calculated
on admission in the prediction of outcome in patients with sepsis.
MATERIALS AND METHODS: The study was carried out in the period of 1st
January 2014 - 31st December 2014. 50 patients fulfilling the inclusion and exclusion
criteria were included in the study. After a thorough clinical examination, the
APACHE III score was assessed and calculated as per the guidelines. The study
population was divided into two groups: Survivor group- those patients who
recovered and were successfully discharged and the Non-Survivor group- those
patients who succumbed to sepsis.
RESULTS: In the study population, 28 patients were males and 22 patients were
females. The mean age of the study population was 42.84 ± 17.34. Respiratory
infection was the most common cause of sepsis. Of the 50 patients studied, 33 patients
(66%) survived and 17 patients (34%) died of sepsis. Mortality rate was 34% with a
V
high incidence of MODS. The mean duration of ICU stay was 7.21 days. Among the
parameters considered in the APACHE III score, the Heart rate, Respiratory rate, S.
Creatinine, S.Bilirubin, Urine output, AaDO2and Glasgow Coma Scale showed
significant differences among the two groups. The mean APACHE III score was
higher among Non-survivor (mean 97.18 v/s 41.12, p < 0.01) and showed good
Discrimination among the two groups by ROC with Area Under the Curve of 0.9742
(standard error of 0.018, 95% CI: 0.9383 to 1.010)
CONCLUSION: APACHE III scoring system is an excellent tool to predict the
mortality in ICU patients with sepsis.
KEYWORDS: Sepsis; APACHE III; Scoring system in ICU; Prediction; Outcome.
VI
TABLE OF CONTENTS
Sl.No Content Page No
1. INTRODUCTION 01
2. AIM&OBJECTIVES 02
3. REVIEW OF LITERATURE 03
4. METHODOLOGY 34
5. RESULTS 36
6. DISCUSSION 65
7. CONCLUSION 74
8. SUMMARY 75
9. BIBLIOGRAPHY 77
10. ANNEXURES 84
PROFORMA
MASTER CHART
VII
LIST OF TABLES
Sl.No Table Page No
1 Definition of sepsis 04
2 Points for the co-morbid conditions in APACHE- III Score 31
3 Age points in APACHE- III 31
4 Age distribution of patients studied 36
5 Gender distribution 37
6 Prior treatment location 38
7 Past known medical illness 39
8 Co-morbidities listed in APACHE III scoring system. 40
9 Chief Presenting Complaints 41
10 Etiology of sepsis 42
11 Interventions that patients underwent 43
12 Microbiological profile of the study population 45
13 Duration of ICU Stay 46
14 Distribution of Survivors and Non-survivors 47
15 Comparison of Temperature among Survivors and Non-
Survivors
48
16 Comparison of Pulse Rate among Survivors and Non-Survivors 49
17 Comparison of Mean Arterial Pressure among Survivors and
Non-Survivors
50
18 Comparison of Respiratory Rate among Survivors and Non-
Survivors
51
19 Comparison of WBC count among Survivors and Non-
Survivors
52
20 Comparison of Hematocrit among Survivors and Non-Survivors 53
21 Comparison of Serum Creatinine among Survivors and Non-
Survivors
54
22 Comparison of Serum Sodium among Survivors and Non-
Survivors
55
VIII
23 Comparison of Serum Albumin among Survivors and Non-
Survivors
56
24 Comparison of Serum Bilirubin among Survivors and Non-
Survivors
57
25 Comparison of RBS among Survivors and Non-Survivors 58
26 Comparison of pH among the survivors and Non-survivors 59
27 Comparison of AaDO2 among Survivors and Non-survivors 60
28 Comparison of GCS Score among the Survivors and Non-
Survivors
61
29 Comparison of Total APACHE scores among Survivors and
Non-Survivors.
62
30 Discrimination of APACHE III scoring system 63
IX
LIST OF FIGURES
Sl.No Figure
PageNo.
1 Pathogenesis of Sepsis 15
2 Mechanism of Organ Dysfunction in sepsis 18
3 The APACHE –III scoring system 34
4 Age distribution of patients studied 36
5 Gender distribution 37
6 Prior treatment location 38
7 Past known medical illness 39
8 Co-morbidities listed in APACHE III scoring system. 40
9 Chief Presenting Complaints 41
10 Etiology of sepsis 42
11 Need for Ventilator Support 43
12 Need for Ionotropic support 44
13 Need for Dialysis 44
14 Need for Surgery 44
15 Duration of ICU stay 46
16 Distribution of Survivors and Non-survivors 47
17 Comparison of Temperature among Survivors and Non-Survivors 48
18 Comparison of Pulse Rate among Survivors and Non-Survivors 49
19 Comparison of Mean Arterial Pressure among Survivors and Non-
Survivors
50
20 Comparison of Respiratory Rate among Survivors and Non-
Survivors
51
21 Comparison of WBC count among Survivors and Non-Survivors 52
22 Comparison of Hematocrit among Survivors and Non-Survivors 53
23 Comparison of Serum Creatinine among Survivors and Non-
Survivors
54
24 Comparison of Serum Sodium among Survivors and Non-Survivors 55
X
25 Comparison of Serum Albumin among Survivors and Non-
Survivors
56
26 Comparison of Serum Bilirubin among Survivors and Non-
Survivors
57
27 Comparison of RBS among Survivors and Non-Survivors 58
28 Comparison of pH among the survivors and Non-survivors 59
29 Comparison of AaDO2 among Survivors and Non-survivors 60
30 Comparison of GCS Score among the Survivors and Non-Survivors 61
31 Comparison of Total APACHE scores among Survivors and Non-
Survivors.
62
32 ROC Curve 64
1
INTRODUCTION
The understanding of sepsis has undergone a tremendous change from ancient times
where it was attributed to spirits and bad air to present day understanding of the
immunological basis of host-organism inter-relationship. The outcome of sepsis has
also improved over the years from being a near 100% fatal disease in the past to the
present day statistics suggesting an improvement in the outcome in majority of the
patients. This has been possible because of the better insight into the pathogenesis
and, the advances in the pharmacotherapy using antimicrobials. However, a lot more
needs to be explored in the years to come. A consensus in the form of Surviving
Sepsis Campaign has also added to the prognostic improvement. India, being a
tropical country, has the additional burden of diseases like Malaria, Leptospirosis,
Typhoid, etc., which need special attention. The ability to objectively estimate patient
risk for mortality or other important outcomes is a new undertaking for clinical
research. Knowledge of risk faced by patient on day of ICU admission could provide
an empiric basis for quality assurance and utilization activities. Development of Acute
Physiology and Chronic Health Evaluation (APACHE-III) was based on association
between acute changes in patient’s physiological balance and short-term risk of death.
In this study we intend to predict the outcome in patients with sepsis by calculating
the APACHE-III score on the day of admission and corroborate the score with the
final outcome of the patient.
2
AIM & OBJECTIVES
1. To study the predictive efficacy of the APACHE III score calculated on
admission in the prediction of outcome in patients with sepsis
3
REVIEW OF LITERATURE
HISTORY
Sepsis is one of the oldest and most elusive syndromes in Medicine.
Hippocrates claimed that sepsis was the process by which flesh rots, swamps generate
foul airs and wounds fester. 1
Documents of sepsis have been made in ancient Egyptian literature.
Particularly one Papyrus manuscript dated about 3000 BC explains case series of
about 48 patients with traumatic wounds, who developed fever as a secondary
phenomenon once the wound had pus and flesh started to turn black.2
However, the origin of the word sepsis seems to have come from the Greek
word ‘sepien’ which means ‘make rotten’.3
The need for anti-sepsis was noted by ancient Indian surgeons. Sushruta
Samhita mentions the application of Matured clarified butter (ghee), breast milk,
Saindhava Salts and linen-soaked bandages for preventing infections in patients who
were operated upon for cataract.4
Puerperal fever was a major infectious complication in the medieval times.
The causes and preventive measures baffled obstetricians. Hungarian doctor Ignaz
Semmelweiss in 1847 made it compulsory for students to wash hands with antiseptic
chloride solution before examining patients. This measure led to the drop in the
incidence of puerperal sepsis from 18% to less than 1%.5
With the confirmation of germ theory by Pasteur and others, Sepsis was recast
as a systemic infection, often termed as ‘Blood poisoning’. However with the modern
4
advances, Germ theory did not fully explain the pathogenesis of sepsis. Thus,
researchers suggested it was host, not the germ, that drove the pathogenesis of sepsis.6
DEFINITION OF SEPSIS
In 1992, an international consensus panel defined sepsis as a systemic inflammatory
response to infection, noting that sepsis could arise in response to multiple infectious
causes and also defined various terminologies like bacteremia, infection and sepsis as
follows.7
Table 1: Definition of sepsis
Infection A microbial phenomenon characterized by
an inflammatory response to the presence
of microorganisms or the invasion of
normally sterile part of the body
Bacteremia Presence of bacteria in blood as evidenced
by positive blood cultures
Systemic Inflammatory Response
Syndrome (SIRS)
Two or more of the following conditions:
1. Fever ( oral temperature >39 ºC)
or hypothermia (<36 ºC)
2. Tachypnea (RR>24 breaths/min)
3. Tachycardia( HR >90 beats/min)
4. Leukocytosis (>12,000/µL),
Leukopenia (<4,000/µL) or > 10%
band forms.
Sepsis SIRS that has proven or suspected
microbial etiology
5
Severe sepsis Sepsis with one or more signs of organ
dysfunction-
1. Cardiovascular: Arterial Systolic
blood pressure ≤90mmHg or
MAP≤70 mmHg
2. Renal: Urine output <0.5mL/kg/hr
despite adequate fluid
resuscitation
3. Respiratory: PaO2/FiO2 ≤ 200
4. Hematological: Platelet count
<80,000 or 50% decrease in the
platelet count from the highest
value recorded over previous 3
days
5. Metabolic acidosis: pH 7.30 or a
base deficit 5.0mEq/L and a
plasma lactate >1.5 times upper
limit of normal
Septic shock Sepsis with hypotension (arterial blood
pressure <90 mmHg systolic or 40mm of
Hg less than patient’s normal blood
pressure) for at least 1 hour despite
adequate fluid resuscitation; or need for
vasopressors to maintain SBP ≥ 90 mmHg
or MAP ≥ 70 mmHg
6
Refractory septic shock Septic shock that lasts for >1 hour and
does not respond to fluid or pressor
administration
In 2003, a second consensus panel endorsed most of these concepts, with the caveat
that signs of a systemic inflammatory response, such as tachycardia or an elevated
white-cell count, occur in many infectious and noninfectious conditions and therefore
are not helpful in distinguishing sepsis from other conditions. Thus, “severe sepsis”
and “sepsis” are sometimes used interchangeably to describe the syndrome of
infection complicated by acute organ dysfunction. 8
Thus, the Society of Critical Care Medicine (SCCM), The European Society of
Intensive Care Medicine (ESICM), The American College of Chest Physicians
(ACCP), the American Thoracic Society (ATS), and the Surgical Infection Society
(SIS) came forward with the consensus regarding various terms at the International
Sepsis Definition Conference held in 2011 in Rhode Island Hospital, USA. They are
as follows:
7
Sepsis (documented or suspected infection plus ≥1 of the following)
General variables
Fever (core temperature, >38.3°C)
Hypothermia (core temperature, <36°C)
Elevated heart rate (>90 beats per min or >2 SD above the upper limit of the
normal range for age)
Tachypnea
Altered mental status
Substantial edema or positive fluid balance (>20 ml/kg of body weight over a
24-hr period)
Hyperglycemia (plasma glucose, >120 mg/dl [6.7 mmol/liter]) in the absence
of diabetes
Inflammatory variables
Leukocytosis (white-cell count, >12,000/mm3)
Leukopenia (white-cell count, <4000/mm3)
Normal white-cell count with >10% immature forms
Elevated plasma C-reactive protein (>2 SD above the upper limit of the
normal range)
Elevated plasma procalcitonin (>2 SD above the upper limit of the normal
range)
Hemodynamic variables
Arterial hypotension (systolic pressure, <90 mm Hg; mean arterial pressure,
<70 mm Hg; or decrease in systolic pressure of >40 mm Hg in adults or to >2
SD below the lower limit of the normal range for age)
8
Elevated mixed venous oxygen saturation (>70%)
Elevated cardiac index (>3.5 liters/min/square meter of body-surface area)
Organ-dysfunction variables
Arterial hypoxemia (ratio of the partial pressure of arterial oxygen to the
fraction of inspired oxygen, <300)
Acute oliguria (urine output, <0.5 ml/kg/hr or 45 ml/hr for at least 2 hr)
Increase in creatinine level of >0.5 mg/dl (>44 μmol/liter)
Coagulation abnormalities (international normalized ratio, >1.5; or activated
partial-thromboplastin time, >60 sec)
Paralytic ileus (absence of bowel sounds)
Thrombocytopenia (platelet count, <100,000/mm3)
Hyperbilirubinemia (plasma total bilirubin, >4 mg/dl [68 μmol/liter])
Tissue-perfusion variables
Hyperlactatemia (lactate, >1 mmol/liter)
Decreased capillary refill or mottling
Severe sepsis (sepsis plus organ dysfunction)
Septic shock (sepsis plus either hypotension [refractory to intravenous fluids] or
hyperlactatemia)
9
EPIDEMIOLOGY
An analysis of a large sample from major US medical centers reported the incidence
of severe sepsis as 3 per 1000 population. Of these patients, 51.1% were admitted to
an intensive care unit. Mortality was 28.6% overall, ranging from 10% in children to
38.4% in the elderly. 9
As per another study, sepsis accounted for about 10% of all ICU admissions.10
There is a lack of statistical data on sepsis in Indian ICU. A multicentre, prospective,
observational study was conducted across four intensive therapy units (ITUs) in India
from June 2006 to June 2009 to determine the incidence and outcome of severe sepsis
among adult patients. A total of 5,478 patients were studied. Sepsis was the main
reason for admission in 901 patients, of which 397 patients succumbed to sepsis 11
As per another prospective study conducted in a rural setup MICU, the mortality was
48% with an alarming 78% of those patients had developed MODS. The most
common organ involved was Lung and most common organism causing sepsis was
Klebsiella pneumonia.12
Though sepsis occurs at all ages, a strong correlation exists between advanced age and
incidence of septic shock, with a sharp increase in the number of cases in patients
older than 50 years.13
The age adjusted incidence and mortality of septic shock are consistently greater in
men. It is not clear whether this difference can be attributed to an underlying higher
prevalence of comorbid conditions and higher incidence of lung infections among
men, or whether women are inherently protected against inflammatory injury that
occurs in severe sepsis.14
10
With regard to ethnicity, incidence of septic shock in the nonwhite population is
almost twice that in the white population.15
The incidence of sepsis has been growing over the decades, for reasons that likely
include the following:
An increasingly elderly population
Increased recognition of the disease
Increased performance of invasive procedures and organ transplantation
Increased use of immunosuppressive drugs and chemotherapy
Increased use of indwelling lines and devices
A rise in chronic diseases such as end-stage renal disease (ESRD) and HIV
infection.
ETIOLOGY OF SEPSIS
Before the introduction of antibiotics, gram positive bacteria were the principal
organisms that caused sepsis. Subsequently, gram negative bacteria became the key
pathogens causing severe sepsis and septic shock. Currently, however, the rates of
severe sepsis and septic shock due to gram positive organisms are rising again
because of more frequent use of invasive procedures and central venous lines in
critically ill patients. As a result gram positive and gram negative microorganisms are
now about equally likely to be causative pathogens in septic shock.16
Respiratory tract and abdominal infections are the most frequent causes of sepsis
followed by urinary tract and skin-soft tissue infections. Each organ system tends to
be infected by a particular set of pathogens as mentioned below:
11
Lower respiratory tract infections are the cause for septic shock in 35-50% patients.16-
19 The following are the common pathogens.
Streptococcus pneumonia
Klebsiella pneumoniae
Escherichia coli
Legionella spp
Hemophilus spp
Staphylococcus aureus
Pseudomonas spp
Anaerobes
Gram negative bacteria
Fungi
Abdominal and GI tract infections are the cause for septic shock in 20-40% of
patients.16-19. The following are the common pathogens.
Escherichia coli
Enterococcus spp
Bacteroides fragilis
Acinetobacter spp
Pseudomonas spp
Enterobacter spp
Salmonella spp
Klebsiella spp
Anaerobes
12
Urinary tract infections are the cause for septic shock in 10-30% of patients. 16-19 The
following are the common pathogens
Escherichia coli
Klebsiella spp
Pseudomonas spp
Enterobacter spp
Serratia spp
Enterococcus spp
Candida
Infections of the male and female reproductive systems are the cause for septic shock
in 1-5% of patients.16-19 The following are the common pathogens
Neisseria gonorrhoeae
Gram negative bacteria
Streptococci
Anaerobes
Soft-tissue infections are the cause for sepsis in 5-10% patients 16-19 The following are
the common pathogens:
Staphylococcus aureus
Staphylococcus epidermis
Streptococci
Clostridium spp
Gram negative bacteria
Anaerobes
13
Fungi
Miscellaneous infections, such as CNS infections, also cause septic shock in 1-5% of
patients. Neisseria meningitides is a common cause of such infections.16-19.
Infections due to foreign bodies cause septic shock in 1-5% of patients.
Staphylococcus aureus, Staphylococcus epidermis and fungi are the common
pathogens.16-19
PATHOPHYSIOLOGY
Host Response
As the concept of the host theory emerged, it was first assumed that the clinical
features of sepsis were the result of overly exuberant inflammation. Later, Bone
et.al.20 advanced the idea that the initial inflammatory response gave way to a
subsequent “compensatory anti-inflammatory response syndrome.” However, it has
become apparent that infection triggers a much more complex, variable, and
prolonged host response, in which both pro-inflammatory and anti-inflammatory
mechanisms can contribute to clearance of infection and tissue recovery on the one
hand and organ injury and secondary infections on the other.21 The specific response
in any patient depends on the causative pathogen (load and virulence) and the host
(genetic characteristics and coexisting illnesses), with differential responses at local,
regional, and systemic levels (Fig. 1). The composition and direction of the host
response probably change over time in parallel with the clinical course. In general,
pro-inflammatory reactions (directed at eliminating invading pathogens) are thought
to be responsible for collateral tissue damage in severe sepsis, whereas anti-
14
inflammatory responses (important for limiting local and systemic tissue injury) are
implicated in the enhanced susceptibility to secondary infections.
Innate Immunity
Knowledge of pathogen recognition has increased tremendously in the past decade.
Pathogens activate immune cells through an interaction with pattern-recognition
receptors, of which four main classes — toll-like receptors, C-type lectin receptors,
retinoic acid inducible gene 1–like receptors, and nucleotide-binding oligomerization
domain–like receptors — have been identified, with the last group partially acting in
protein complexes called inflammasomes (Fig. 1)22. These receptors recognize
structures that are conserved among microbial species, so-called pathogen-associated
molecular patterns, resulting in the up-regulation of inflammatory gene transcription
and initiation of innate immunity. The same receptors also sense endogenous
molecules released from injured cells, so-called damage-associated molecular
patterns, or alarmins, such as high-mobility group protein B1, S100 proteins, and
extracellular RNA, DNA, and histones23 Alarmins are also released during sterile
injury such as trauma, giving rise to the concept that the pathogenesis of multiple
organ failure in sepsis is not fundamentally different from that in noninfectious
critical illness.23
15
Figure 1: Pathogenesis of Sepsis (N Engl J Med 2013;369:844.)
Coagulation Abnormalities
Severe sepsis is almost invariably associated with altered coagulation, frequently
leading to disseminated intravascular coagulation.24 Excess fibrin deposition is driven
by coagulation through the action of tissue factor, a transmembrane glycoprotein
expressed by various cell types; by impaired anticoagulant mechanisms, including the
protein C system and antithrombin; and by compromised fibrin removal owing to
depression of the fibrinolytic system (Fig. 2) 24. Protease-activated receptors (PARs)
form the molecular link between coagulation and inflammation. Among the four
subtypes that have been identified, PAR1 in particular is implicated in sepsis (24).
PAR1 exerts cytoprotective effects when stimulated by activated protein C or low-
dose thrombin, but exerts disruptive effects on endothelial- cell barrier function when
16
activated by high-dose thrombin.25. The protective effect of activated protein C in
animal models of sepsis is dependent on its capacity to activate PAR1 and not on its
anticoagulant properties.25.
Anti-inflammatory Mechanisms and Immunosuppression
The immune system harbors humoral, cellular, and neural mechanisms that attenuate
the potentially harmful effects of the pro-inflammatory response (Fig. 1)21.
Phagocytes can switch to an anti-inflammatory phenotype that promotes tissue repair,
and regulatory T cells and myeloid-derived suppressor cells further reduce
inflammation. In addition, neural mechanisms can inhibit inflammation.26. In the so-
called neuroinflammatory reflex, sensory input is relayed through the afferent vagus
nerve to the brain stem, from which the efferent vagus nerve activates the splenic
nerve in the celiac plexus, resulting in norepinephrine release in the spleen and
acetylcholine secretion by a subset of CD4+ T cells. The acetylcholine release targets
α7 cholinergic receptors on macrophages, suppressing the release of pro-
inflammatory cytokines.27 In animal models of sepsis26 disruption of this neural-based
system by vagotomy increases susceptibility to endotoxin shock, whereas stimulation
of the efferent vagus nerve or α7 cholinergic receptors attenuates systemic
inflammation.
Patients who survive early sepsis but remain dependent on intensive care have
evidence of immunosuppression, in part reflected by reduced expression of HLA-DR
on myeloid cells.28 These patients frequently have ongoing infectious foci, despite
antimicrobial therapy, or reactivation of latent viral infection.29-30. Multiple studies
have documented reduced responsiveness of blood leukocytes to pathogens in patients
with sepsis21, findings that were recently corroborated by postmortem studies
revealing strong functional impairments of splenocytes obtained from patients who
17
had died of sepsis in the ICU.28. Besides the spleen, the lungs also showed evidence of
immunosuppression; both organs had enhanced expression of ligands for T-cell
inhibitory receptors on parenchymal cells.28. Enhanced apoptosis, especially of B
cells, CD4+ T cells, and follicular dendritic cells, has been implicated in sepsis-
associated immunosuppression and death.31, 32. Epigenetic regulation of gene
expression may also contribute to sepsis-associated immunosuppression.33
Organ Dysfunction
Although the mechanisms that underlie organ failure in sepsis have been only
partially elucidated, impaired tissue oxygenation plays a key role (Fig. 2). Several
factors including hypotension, reduced red-cell deformability, and microvascular
thrombosis contribute to diminished oxygen delivery in septic shock. Inflammation
can cause dysfunction of the vascular endothelium, accompanied by cell death and
loss of barrier integrity, giving rise to subcutaneous and body-cavity edema.34. In
addition, mitochondrial damage caused by oxidative stress and other mechanisms
impairs cellular oxygen use.35. Moreover, injured mitochondria release alarmins into
the extracellular environment, including mitochondrial DNA and formyl peptides,
which can activate neutrophils and cause further tissue injury.36.
18
Figure 2: Mechanism of Organ Dysfunction in sepsis (N Engl J Med 2013;369:845)
PROGNOSIS
Mortality figures for severe sepsis and septic shock have commonly been quoted as
ranging from 20% to 50%. Clinical trials from the past decade have found the
mortality associated with septic shock range from 24% to 41%.18 Mortality has been
found to vary according to degree of illness. The following clinical characteristics are
related to the severity of sepsis:
Abnormal host response to infection
Site and type of infection
Timing and type of anti microbial therapy
Offending organism
Development of shock
19
An underlying disease
Patient’s long-term health condition
Location of patient at the time of septic shock onset
Host immunologic variation.15
In one epidemiologic study, reported mortality figures were 7% for SIRS, 16% for
sepsis, 20% for severe sepsis and 46% for septic shock .37.
As per another study, 27% of all deaths occurring in sepsis happened within 2 days of
the onset of severe sepsis and 77% occurring within the first 14 days. The risk factors
for early mortality in his study were as follows:
Higher severity of illness score
Acute failure of 2 or more organ systems at the time of sepsis
Shock
Low blood pH(<7.3) (38)
TREATMENT OF SEPSIS
The ‘SURVIVING SEPSIS CAMPAIGN’39 was a landmark study for the treatment of
sepsis which provided treatment guidelines. The last update of the Surviving Sepsis
campaign has made major changes in the treatment. The recommendations are as
follows:
Initial resuscitation
1. Protocolized, quantitative resuscitation of patients with sepsis- induced
tissue hypoperfusion with the Goals during the first 6 hours
a) Central venous pressure 8–12 mm Hg
20
b) Mean arterial pressure (MAP) ≥ 65 mm Hg
c) Urine output ≥ 0.5 mL/kg/h
d) Central venous (SVC) or mixed venous oxygen saturation 70% or
65%, respectively
2. In patients with elevated lactate levels targeting resuscitation to
normalize lactate
Diagnosis
1. Clinically appropriate culture samples are to be collected before the start
of antimicrobial therapy. At least 2 sets of blood cultures (both aerobic and
anaerobic bottles) be obtained before antimicrobial therapy with at least 1
drawn percutaneously and 1 drawn through each vascular access device,
unless the device was recently (<48 hrs) inserted.
2. Imaging studies performed promptly to confirm a potential source of
infection
Antimicrobial Therapy
1. Administration of effective intravenous antimicrobials within the first hour
of recognition of septic shock and severe sepsis without septic shock.
2. Initial empiric anti-infective therapy of one or more drugs that have
activity against all likely pathogens (bacterial and/or fungal or viral) and
that penetrate in adequate concentrations into tissues presumed to be the
source of sepsis.
3. Antimicrobial regimen should be reassessed daily for potential de-
escalation
4. Use of low procalcitonin levels or similar biomarkers to assist the
clinician in the discontinuation of empiric antibiotics.
21
5. Empiric combination therapy should not be administered for more than 3–
5 days. De-escalation to the most appropriate single therapy should be
performed as soon as the susceptibility profile is known
6. Duration of therapy typically 7–10 days
Source Control
1. A specific anatomical diagnosis of infection requiring consideration for
emergent source control be sought and diagnosed or excluded as rapidly as
possible, and intervention be undertaken for source control within the first
12 hr after the diagnosis is made.
2. When source control in a severely septic patient is required, the effective
intervention associated with the least physiologic insult should be used
(e.g., percutaneous rather than surgical drainage of an abscess)
3. If intravascular access devices are a possible source of severe sepsis or
septic shock, they should be removed promptly after other vascular access
has been established.
Infection Prevention
1. Selective oral decontamination and selective digestive decontamination
should be introduced and investigated as a method to reduce the incidence
of ventilator-associated pneumonia.
2. Frequent wash of hands by standard procedure by health care providers.
Fluid Therapy of Severe Sepsis
1. Crystalloids as the initial fluid of choice in the resuscitation of severe
sepsis and septic shock
22
2. Albumin in the fluid resuscitation of severe sepsis and septic shock when
patients require substantial amounts of crystalloids
3. The guidelines were Against the use of hydroxyethyl starches for fluid
resuscitation of severe sepsis and septic shock
4. Initial fluid challenge in patients with sepsis-induced tissue hypoperfusion
with suspicion of hypovolemia to achieve a minimum of 30 mL/kg of
crystalloids
Vasopressors
1. Vasopressor therapy initially to target a mean arterial pressure (MAP)
of 65 mm Hg
2. Norepinephrine as the first choice vasopressor
3. Vasopressin 0.03 units/minute can be added to norepinephrine (NE)
with intent of either raising MAP or decreasing NE dosage
4. Dopamine as an alternative vasopressor agent to norepinephrine only
in highly selected patients (e.g., patients with low risk of
tachyarrhythmias and absolute or relative bradycardia
5. Low-dose dopamine should not be used for renal protection
6. Phenylephrine is not recommended in the treatment of septic shock
except in circumstances where (a) norepinephrine is associated with
serious arrhythmias, (b) cardiac output is known to be high and blood
pressure persistently low or (c) as salvage therapy when combined
inotrope/vasopressor drugs and low dose vasopressin have failed to
achieve MAP target
Inotropic Therapy
23
A trial of dobutamine infusion up to 20 micrograms/kg/min be administered or
added to vasopressor (if in use) in the presence of (a) myocardial dysfunction
as suggested by elevated cardiac filling pressures and low cardiac output, or
(b) ongoing signs of hypoperfusion, despite achieving adequate intravascular
volume and adequate MAP.
Corticosteroids
1. Not using intravenous hydrocortisone to treat adult septic shock patients if
adequate fluid resuscitation and vasopressor therapy are able to restore
hemodynamic stability
2. In case this is not achievable, we suggest intravenous hydrocortisone alone at
a dose of 200 mg per day
3. Corticosteroids not be administered for the treatment of sepsis in the absence
of shock.
SCORING SYSTEMS
Scoring systems for use in intensive care unit (ICU) patients have been introduced
and developed over the last 30 years. They allow the assessment of the severity of
disease and provide an estimate of in-hospital mortality. A weighting is applied to
each variable, and the sum of the weighted individual scores produces the severity
score. Various factors have been shown to increase the risk of in-hospital mortality
after admission to ICU, including increasing age and severity of acute illness, certain
pre-existing medical conditions (e.g. malignancy, immunosuppression, and
requirement for renal replacement therapy), and emergency admission to ICU. Before
the 1980s, there were no scoring systems applicable to critical care populations which
would allow outcomes from different critical care units to be compared. Since then,
many scoring systems have been developed, though only a small minority is used.40.
24
The assessment of quality of care in the practice of medicine has become increasingly
important.41 The practice of critical care medicine has been especially scrutinized, at
least in part, because of the enormous costs of providing critical care services.42, 43
Prognostic scoring systems have been developed by the critical care community in an
effort to quantify the severity of illness of a given patient or group of patients. It also
enables monitoring of the performance of an ICU over time and for comparison of
ICUs in the same or different hospitals. It is imperative that such severity adjustments
be as accurate as possible.44
Scoring systems essentially consists of two parts: a severity score, which is a number
(generally the higher this is, the more severe the condition) and a calculated
probability of mortality. Most commonly, this is the risk of in-hospital mortality,
though other outcome measures (e.g. survival to 28 days post-hospital discharge) can
also be considered.45.
Many prognostic models exist, suggesting that the optimum model has not been
established. The three most commonly used adult-ICU prognostic scoring systems are
APACHE (Acute Physiology and Chronic Health Evaluation), the Simplified Acute
Physiology Score (SAPS), and the Mortality Probability Model (MPM).46
The applied variables can be grouped into five categories: age, co-morbidities,
physiological abnormalities, acute diagnosis, and interventions.
25
CLASSIFICATION OF SCORING SYSTEMS
There is no agreed classification of the scoring systems that are used in critically ill
patients. Scores can be applied either to a single set of data or repeated over time. The
available methods include:
1. Anatomical scoring: These depend on the anatomical area involved.
Anatomical scoring systems are mainly used for trauma patients [e.g.
abbreviated injury score (AIS) and injury severity score (ISS)].
2. Therapeutic weighted scores: These are based on the assumption that very ill
patients require a greater number of interventions and procedures that are
more complex than patients who are less ill. Examples include the therapeutic
intervention scoring system (TISS).
3. Organ-specific scoring: This is similar to therapeutic scoring; the underlying
premise is the sicker a patient the more organ systems will be involved,
ranging from organ dysfunction to failure [e.g. sepsis related organ failure
assessment (SOFA)].
4. Physiological assessment: It is based on the degree of derangement of
routinely measured physiological variables [e.g. acute physiology and chronic
health evaluation (APACHE) and simplified acute physiology score (SAPS)].
5. Simple scales: It is based on clinical judgement (e.g. survive or die).
6. Disease specific [e.g. Ranson’s criteria for acute pancreatitis, subarachnoid
haemorrhage assessment using the World Federation of Neurosurgeons score,
and liver failure assessment using Child-Pugh or model for end stage liver
disease (MELD) scoring].
26
IDEAL SCORING SYSTEM
The ideal scoring system would have the following characteristics:
1. On the basis of easily/routinely recordable variables
2. Well calibrated
3. A high level of discrimination
4. Applicable to all patient populations
5. Can be used in different countries
6. The ability to predict functional status or quality of life after ICU discharge.
No scoring system currently incorporates all these features.
TYPES OF SCORING SYSTEM
First day scoring system: Most critical care severity scores are calculated from
the data obtained on the first day of ICU admission.
Examples: the APACHE, the SAPS and the mortality prediction model
(MPM)
Repetitive scoring systems: these scoring systems are repetitive and collect
data sequentially throughout the duration of ICU stay or over the first few
days.
Examples: the SOFA and Multiple Organ Dysfunction Score (MODS).
27
MODEL CALIBRATION
Calibration assesses the degree of correspondence between the estimated probability
of mortality and that actually observed. This can be tested using a goodness of fit test,
most commonly the Hosmer–Lemeshow C statistic. Over the range of probabilities,
the expected and observed mortality are compared and a P-value derived. Calibration
is considered to be good if the predicted mortality is close to the observed mortality.48
If a scoring model predicts that a patient has a probability of in-hospital mortality of
0.25, it means that, in a sample population of 100 patients, 25 would be expected to
die and 75 patients would survive. When the number of deaths in the actual
population is near to that predicted by the scoring system, the model is considered
well calibrated.
MODEL DISCRIMINATION
Model discrimination reviews the ability of the scoring model to discriminate between
patients who die from those who survive, based on the predicted mortalities. Methods
include calculation of the area under the receiver operating characteristic (ROC) curve
or using a classification matrix. The two most important parts of the classification
matrix are the specificity and sensitivity. In MPMs, these are not absolute levels, and
a huge grey area exists between those who die and those who survive. Therefore, a
number of classification matrices are constructed with sensitivity and specificity
values across the range.48
A pair of sensitivity–specificity values produces the ROC curve across the range of
mortality prediction scores. The area under the resultant curve (AUC) represents the
number of patients who died. The curve is analysed using complex computerized
statistical processes to assess the discrimination. Clearly, if this AUC is around 0.50,
28
the performance of the scoring system is no better than a coin toss. Typically, model
developers require an AUC of the ROC curve to be .0.70.45.
APACHE SCORING SYSTEMS
History
A conceptual model for the APACHE prognostic scoring system was formulated in
1979. The APACHE (acute physiology and chronic health evaluation) prognostic
scoring system was developed in 1981 at the George Washington University Medical
Center as a way to measure disease severity.49
Development of APACHE
The original APACHE consisted of two parts: the APS (acute physiology score)
representing the degree of acute illness and CHE (chronic health evaluation)
indicating physiological reserve before the acute illness. The APS variables were
developed by a panel of physicians from medicine, surgery and anaesthesia. Thirty-
four variables were selected and relative weights (0-4) were assigned according to the
clinicians' clinical experience and a review of the literature. The greatest degree of
abnormality (worst value) of each variable within the first 32 h after admission was
used. The CHE consisted of a questionnaire inquiring about the number of recent
physician visits, activities of daily living and the presence of carcinoma. Patients were
then classified into A for excellent health to D for severely failing health. The final
score consisted of an APS and a CHE (e.g., 25-D). Probability calculations were not
part of the original APACHE system. Results from the initial study group indicated a
direct relationship between the APS score and the probability of death. Criticisms of
29
the APACHE included the large number of variables and the 32 h allowed for data
collection. Further analysis and modifications led to the development of the APACHE
II.50.
APACHE II, which was introduced in 1985, incorporated a number of important
changes. First, the number of APS variables was reduced from 34 to 12. This was
accomplished by eliminating infrequently measured variables (e.g., serum lactate,
osmolality) and redundant variables (e.g., BUN). In addition, the threshold and
weights of variables were modified according to their statistical correlation to hospital
mortality. Particularly, the Glasgow Coma Scale was given an increased weight of 12
and acute renal failure was double-weighted with a maximum score of 8. The most
abnormal APS values within the first 24 hr of ICU admission were used. With these
modifications, APACHE II then consisted of three parts: APS (12 variables;
creatinine: 0-8 points, Glasgow Coma Scale: 0-12 points, other 10 variables: 0-4
points each; maximum 60 points), age points (0-6) and chronic health points (0-5) for
a maximum total score of 71.50
The APACHE II system was extensively evaluated in an initial study population of
5815 patients from 13 medical centres.51.
There was a direct correlation between the APACHE 11 score and hospital mortality.
Each three-point increase in APACHE II was associated with an increase in hospital
mortality (P < 0.05). APACHE thus fulfilled its original objectives of providing an
accurate measure of the severity of illness and the ability to predict mortality in an
individual or groups in a wide variety of disease categories.
30
APACHE III
APACHE is a severity-adjusted methodology that predicts outcomes for critically ill
adult patients. In order to predict these outcomes, the APACHE methodology looks at
27 variables for each patient. These variables include the patient's diagnosis, age, vital
signs, and laboratory values. This data, in conjunction with a few other pieces of
information about the patient's history, is combined and used to mathematically
formulate predictions for each individual patient. These predictions are made for
mortality (both ICU and hospital), length of stay (both ICU and hospital), the need for
active treatment and predicted ventilator days. The APACHE Foundations solution
includes the APACHE IV hospital mortality risk prediction and the APACHE IV
expected ICU LOS prediction.
The APACHE III score consists of a cardinal index risk number varying from 0-299
points. Points are tabulated from weights assigned to the following:
• Physiology: Physiology is the largest component of the APACHE III score. The
Acute Physiology Score (APS) is the total number of points that the patient is
assigned due to acute physiologic derangements alone. The total score can range
from 0 to 252.
• Chronic Health: Chronic Health includes only significant co-morbidities
influencing a patient's immunologic status. More than 30 chronic health items
were collected in the APACHE III study, but only those that were found to impact
outcomes are included in the methodology. The total score derived from chronic
health information can range from 0 to 23.
31
Table 2: Points for the co-morbid conditions in APACHE- III Score
Comorbid condition Points
AIDS 23
Hepatic failure 16
Lymphoma 13
Metastatic cancer 11
Leukemia/multiple myeloma 10
Immunosuppression 10
Cirrhosis 4
• Age: The patient’s chronological age can contribute 0-24 points.
Table 3: Age points in APACHE-III system
Age (in years) Points
≤44 0
45-59 5
60-64 11
65-69 13
70-74 16
75-74 16
75-84 17
≥85 24
Chronic Health and Age points combined equal the physiological reserve points- an
indicator of the patient's ability to recover from illness. The patient’s APS + Chronic
Health + Age = APACHE III Score. The score is calculated using the value furthest
32
from a predetermined midpoint, over the course of the patient’s first ICU day. In
APACHE Foundations, the evaluation period for the first ICU day is the first 24
hours in the ICU following admission. The APACHE III score provides relative risk
stratification for acutely ill hospitalized adults only when used within a single medical or
surgical diagnostic category
STATISTICAL ANALYSIS
Descriptive and inferential statistical analysis had been carried out in our
study. The continuous variable such as age, BP, etc were expressed in terms of
average ± standard deviation. The categorical measurements were expressed in
Number (percentage). Significance was assessed at 5 % level of significance. (p
<0.05)
Unpaired t-test has been used to find the significance of study parameters on
continuous scale between two groups (Inter group analysis) on metric parameters.
Chi-square/ Fisher Exact test has been used to find the significance of study
parameters on categorical scale between two or more groups.
Significant figures
+ Suggestive significance (P value: 0.05<P<0.10)
* Moderately significant (P value:0.01<P 0.05)
** Strongly significant (P value : P0.01)
Statistical software: Chi-square statistical software52 and GraphPad Prism 6.05 were
used for the analysis of the data. Microsoft Word and Excel were used to generate
graphs, tables, etc.
33
Figure 3: The APACHE –III scoring system
34
METHODOLOGY
A prospective study entitled "PREDICTION OF OUTCOME IN
PATIENTS ADMITTED TO ICU IN SEPSIS USING APACHE III SCORING
SYSTEM" was undertaken in the Karnataka Institute of Medical Sciences, Hubli
after the approval from the Ethics Committee.
The study was carried out in the period of 1st January 2014 - 31st December
2014 and 50 patients were included in the study.
The patients with sepsis as defined by the 2001
SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference were
included in the study.
The detailed history, Clinical examination and all relevant laboratory
investigations were done. In the present study, the conditions were defined according
to the standard practice and based on relevant literature.
All the patients of sepsis admitted to ICU were being prognosticated on the
basis of APACHE III score.
APACHE III is calculated on the day on admission. The predicted mortality
rate was calculated on the basis of this score.
The minimum APACHE III score was 0 and maximum 399.
We are analyzing various profiles between two groups; survivor group which
included the patients who were successfully discharged after the recovery and the
Non- survivor group which included the patients who died.
35
INCLUSION CRITERIA
Patients admitted to the ICU and who remain for a minimum of 4 hours
with evidence of sepsis fulfilled by at least 2 of the 4 criteria mentioned
below
Oral Temperature greater than 38 ºC(100.4 ºF) or less than 36C(96.8 ºF)
Heart Rate greater than 90 beats per minute
Respiratory Rate(RR) greater than 20 breaths per minute or Arterial Carbon
Dioxide tension(PaCO2) lower than 32mm of Hg.
White blood cell (WBC) count greater than 12,000/µL or less than 4000/µL
EXCLUSION CRITERIA
Age<18 years
Patients admitted with burn injuries
Patient admitted with or suspicion of Acute Myocardial Ischemia.
Patients with Acute gastroenteritis.
36
RESULTS
50 patients fulfilling the inclusion criteria admitted in the Intensive Care Unit of
Karnataka Institute of Medical Sciences, Hubli, were enrolled in the study.
Table 4: Age distribution of patients studied
Age in years Number of patients Percentage
18-20 6 12
21-30 8 16
31-40 7 14
41-50 13 26
51-60 11 22
61-70 2 4
>70 3 6
Mean: 42.84 ± 17.34
The mean age of the study population was 42.84 ± 17.34 years. The maximum
number of patients were in the age group of 41-50 years. The youngest patient was 18
years old and the oldest patient was 95 years old.
0
5
10
15
20
25
30
18-20 21-30 31-40 41-50 51-60 61-70 >70
12
1614
26
22
46Pe
rcen
tage
Age in years
Figure 4: Age Distribution of Patients Studied
37
Table 5: Gender distribution
Gender Number of patients Percentage
Male 28 56
Female 22 44
Total 50 100
Out of the 50 patients, selected for the study, 28 were males and 22 were females.
Male56%
Female44%
Figure 5: Gender distribution
38
Table 6: Prior treatment location
Prior Treatment Location Number of patients Percentage
Emergency department 34 68
Another hospital 6 12
Another ICU 5 10
Operation theatre 2 4
Wards 3 6
Most patients were admitted to the ICU from the Emergency department (68%). Other
prior treatment locations were Another hospital (12%), Another ICU (10%), Hospital
wards (6%) and Operation theatre (4%).
0
10
20
30
40
50
60
70
Emergencydepartment
Anotherhospital
Another ICU Operationtheatre
Wards
68
12 104 6
Perc
enta
ge
Prior treatment location
Figure 6: Prior Treatment Location
39
Table 7: Past known medical illness
Past medical history No. of Patients Percentage
Type 2 Diabetes 13 26
Asthma/COPD 4 8
Hypertension 4 8
Ischemic Heart Disease 3 6
Hypothyroidism 1 2
Leprosy 1 2
Pulmonary Tuberculosis 1 2
Chronic Kidney Disease 1 2
Type 2 Diabetes Mellitus was the most common known medical illness in the study
group, present in 26% of the patients. Followed by Hypertension (8%),
Asthma/COPD (8%) and Ischemic Heart Disease (6%). Leprosy, Pulmonary
tuberculosis, chronic Kidney Disease, Hypothyroidism each was present in 2% of the
patients.
05
1015202530354045
26
8 8 62 2 2 2
44
Perc
enta
ge
Past medical history
Figure 7: Past known medical illness
40
Table 8: Co-morbidities listed in APACHE III scoring system.
Co-morbidities No. of Patients Percentage
None 43 86
Immune suppression 2 4
Leukemia 2 4
Metastatic Cancer 2 4
Liver Cirrhosis 1 2
Among the 7 conditions listed in the APACHE III which carry specific points have
been listed separately. 2 patients had Immune suppression due to AIDS, 2 patients had
Leukemia, 2 patients had metastatic cancer and 1 patient had liver cirrhosis.
0102030405060708090
None Immunesuppression
Leukemia MetastaticCancer
Liver Cirrhosis
86
4 4 4 2
Perc
enta
ge
Co-morbidities
Figure 8: Comorbidities listed in APACHE III
41
Table 9: Chief Presenting Complaints
Presenting complaints No. of patients Percentage
Fever 50 100
Cough with expectoration 22 44
Breathlessness 21 42
Altered sensorium 15 30
Pain abdomen 15 30
Decreased urine output 14 28
Wheeze 5 10
Convulsions 5 10
Headache 3 6
Rashes 4 8
Jaundice 7 14
Fever was the most common presenting complaint, present in all patients. Followed
by Cough (44%), Breathlessness (42%). Other symptoms were pain abdomen and
altered sensorium in 30% each and Decreased urine out in 28%.
0102030405060708090
100100
44 4230 30 28
10 10 6 8 14
Perc
enta
ge
Presenting complaints
Figure 9: Chief Presenting complaints
42
Table 10: Etiology of sepsis
Etiology for sepsis No of patients Percentage
Respiratory infection 23 46
Intra-abdominal sepsis 8 16
Urosepsis 5 10
Skin-soft tissue infection 4 8
Puerperal 3 6
Malaria 3 6
Leptospirosis 2 4
Brucellosis 1 2
Neuroinfection 1 2
Total 50 100
Respiratory infection was the most identified cause of sepsis which was seen in 46%
of patients. Other causes were Intra-abdominal (16%), Urosepsis (10%), Skin-soft
tissue infections (8%) etc.
Respiratory46%
Urosepsis10%
Puerperal6%
Skin-soft tissue8%
Intra-abdominal16%
Malaria6%
Leptospirosis4%
Brucellosis2%
Neuroinfection2%
Figure 10: Etiology for sepsis
43
Table 11: Interventions that patients underwent
Number of patients
(n=50) Percentage
Ventilator support
Yes 27 54
No 23 46
Ionotropic support
Yes 23 46
No 27 54
Dialysis
Yes 12 24
No 38 76
Surgery
Yes 10 20
No 40 80
Of the 50 patients, Ventilator support was necessary in 54% of patients, Inotropic
support in 46%, Dialysis in 12% and Surgical intervention in 20% of the patients.
Yes54%
No46%
Figure 11: Need for Ventilator support
44
Yes46%
No54%
Figure 12: Need for Ionotropic support
Yes24%
No76%
Figure 13: Need for Dialysis
Yes20%
No80%
Figure 14: Need for Surgery
45
Table 12: Microbiological profile of the study population
Number of
patients
(n=50) Percentage
Respiratory
Streptococcus pneumoniae 8 16
Klebsiella 3 6
Pseudomonas 5 10
Non Lactose Fermenting 2 4
Staphylococcus. aureus 1 2
Urogenital sepsis
E. coli 7 14
Klebsiella 1 2
Intra-abdominal
E.coli 6 12
Mixed 1 2
Skin-soft tissue
Staphylcoccus. aureus 3 6
No Growth 1 2
The most common organism isolated from Respiratory secretions was Streptococcus
pneumonia (16%) followed by Pseudomonas (10%), Klebsiella (6%), NLF organisms
(4%). Among patients with Urogenital sepsis, E.coli was the most common organism.
The Most common organism isolated in patients with Intra-abdominal sepsis was
E.coli and in patients with Skin-soft tissue infections was Staphylococcus aureus.
Intra-abdominal sepsis included bowel perforation peritonitis in 4 patients, Liver
abscess in 2 patients. Ruptured Psoas abscess and Acute Cholecystitis was found in 1
patient each.
46
Table 13: Duration of ICU Stay
Duration of ICU stay No of patients Percentage
<7 days 40 80
>7 days 10 20
80% of patients had duration of ICU stay <7 days and 20% of patients had a duration
>7 days.
80%
20%
Figure 15 : Duration of ICU stay
<7 days >7 days
47
Table 14: Distribution of Survivors and Non-survivors
Survival Number of patients Percentage
Yes 33 66
No 17 34
Among the study group of 50 patients, 33 patients (66%) survived and 17 patients
(34%) did not survive and succumbed to sepsis.
Yes66%
No34%
Figure 16: Distribution of Survivors and Non-Survivors
48
Table 15: Comparison of body Temperature among Survivors and Non-
Survivors
Temperature
(0F)
Survivors Non-survivors Total
No. of
Patients Percentage
No. of
Patients Percentage
No. of
Patients Percentage
98 2 6.06 0 0.00 2 4
99 5 15.15 6 35.29 11 22
100 8 24.24 1 5.88 9 18
101 9 27.27 4 23.53 13 26
102 5 15.15 4 23.53 9 18
103 3 9.09 1 5.88 4 8
104 1 3.03 1 5.88 2 4
Total 33 100.00 17 100.00 50 100
p-value: 0.8247
All patients had Body temperature >98º F. We did not encounter any patient with
hypothermia. The mean temperature in the Survivor group was 100.7 ± 1.40 and the
mean temperature in the Non- Survivor group was 100.8 ± 1.60. The p-value was
0.8247. This suggested that the body temperature does not affect the prognosis much.
05
10152025303540
98 99 100 101 102 103 104
6.06
%
15.1
5%
24.2
4%
27.2
7%
15.1
5%
9.09
%
3.03
%
0%
35.2
9%
5.88
%
23.5
3%
23.5
3%
5.88
%
5.88
%Perc
enta
ge
Temperature (0F)
Figure 17: Comparison of body Temperature among Survivors andNon-Survivors
Survivors
Non-Survivors
49
Table 16: Comparison of Pulse Rate among Survivors and Non-Survivors
Pulse
Survivors Non-survivors Total
No. of
Patients Percentage
No. of
Patients Percentage
No. of
Patients Percentage
≤90 4 12.12 1 5.88 5 10
91-100 8 24.24 3 17.65 11 22
101-120 14 42.42 4 23.53 18 36
>120 7 21.21 9 52.94 16 32
Total 33 100.00 17 100.00 50 100
All patients had pulse above 90. The mean pulse rate in the Survivor group was 108.5
± 13.71 and the mean pulse rate in the Non-Survivor group was 119.2 ± 16.26. The p
value was 0.0170, which is statistically significant. This showed that Heart rate was
higher in the Non-Survivor group than in the Survivor group.
0
10
20
30
40
50
60
<=90 91-100 101-120 >120
12.1
2%
24.2
4%
42.4
2%
21.2
2%
5.88
%
17.6
5% 23.5
3%
52.9
4%
Perc
enta
ge
Pulse
Figure 18: Comparison of Pulse among Survivors and Non-Survivors
Survivors
Non-Survivors
50
Table 17: Comparison of MAP among Survivors and Non Survivors
MAP
Survivors Non-survivors Total
No. of
Patients Percentage
No. of
Patients Percentage
No. of
Patients Percentage
<39 0 0.00 0 0.00 0 0.00
40-80 25 75.76 10 58.82 35 70.00
81-100 8 24.24 6 35.29 14 28.00
101-120 0 0.00 0 0.00 0 0.00
>120 0 0.00 1 5.88 1 2.00
Total 33 100.00 17 100.00 50 100.00
P-value=0.3089
The Mean Arterial Pressure was calculated using the formula MAP= DBP+ 1/3(Pulse
Pressure). The mean MAP in the Survivor group was 72.94 ± 12.88 and the mean
MAP in the Non-Survivor group was 77.81 ± 20.54. The p value was 0.3089 which is
not statistically significant. This suggests that there is no significant difference in the
MAP between the two study groups.
0
10
20
30
40
50
60
70
80
<39 40-80 81-100 101-120 >120
0%
75.7
6%
24.2
4%
0% 0%0%
58.8
3%
35.2
9%
0%
5.88
%
Perc
enta
ge
MAP (mmHg)
Figure 19: Comparison of MAP among Survivors and Non-Survivors
Survivors
Non-Survivors
51
Table 18: Comparison of Respiratory Rate among Survivors and Non-Survivors
Respiratory
Rate
Survivors Non-survivors Total
No. of
Patients Percentage
No. of
Patients Percentage
No. of
Patients Percentage
<20 6 18.18 1 5.88 7 14
20-40 24 72.73 12 70.59 36 72
>40 3 9.09 4 23.53 7 14
Total 33 100.00 17 100.00 50 100
p-value: 0.0081
Majority of patients had Tachypnea (RR>20). Severe tachypnea i.e, Respiratory rate
>40 was seen in 30% of patients. The mean Respiratory rate among Survivors was
26.6 ± 9.20 and the mean Respiratory rate among Non-survivors was 34.06 ± 8.47.
The p-value was 0.0081 which is statistically significant. This shows that Non-
survivors had a higher respiratory rate than the survivors.
0
10
20
30
40
50
60
70
80
<20 20-40 >40
18.1
8%
72.7
3%
9.09
%
5.88
%
70.5
9%
23.5
3%
Perc
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ge
Respiratory Rate
Figure 20: Comparison of Respiratory rate among Survivors andNon-Survivors
Survivors
Non-Survivors
52
Table 19: Comparison of WBC count among Survivors and Non-Survivors
WBC
Survivors Non-survivors Total
No. of
Patients Percentage
No. of
Patients Percentage
No. of
Patients Percentage
<1 0 0.00 0 0.00 0 0
1.0-3.9 3 9.09 3 17.65 6 12
4.0-12.0 3 9.09 3 17.65 6 12
12.0-19.9 12 36.36 2 11.76 14 28
≥20 15 45.45 9 52.94 24 48
Total 33 100.00 17 100.00 50 100
p-value: 0.3340
Most patients had leucocytosis (37%) that is Leucocyte count over 12,000. Normal
Total count was seen in 6% of patients. Leucopenia was observed in 7% of the
patients. The highest WBC count observed was 32,800 cells/cu mm and the lowest
was 1200 cells/cu. mm. The mean WBC count among Survivors was 17.94 ± 9.21 and
the mean WBC count among Non-survivors was 22 ± 20.33. The p-value was 0.3340
which is statistically not significant. This shows that degree of increase in the WBC
count did not affect the outcome in patients.
0102030405060
<1 1.0-3.9 1.0-12.0 12.0-19.9 >=20
0%
9.09
%
9.09
%
36.3
7% 45.4
5%
0%
17.6
5%
17.6
5%
11.7
6%
52.9
4%
Perc
enta
ge
WBC ( (cu/mm)*1000 )
Figure 21: Comparison of WBC count among Survivors andNon-Survivors
Survivors
Non-Survivors
53
Table 20: Comparison of Hematocrit among Survivors and Non-Survivors
Hematocrit
Survivors Non-survivors Total
No. of
Patients Percentage
No. of
Patients Percentage
No. of
Patients Percentage
<25 4 12.12 7 41.18 11 22
25-40 23 69.70 6 35.29 29 58
>40 6 18.18 4 23.53 10 20
Total 33 100.00 17 100.00 50 100
p-value: 0.3077
Degree of anemia was assessed using the Hematocrit. Majority of patients (60%) had
normal hematocrit. Anemia with hematocrit was present in 20% of the patients. The
percentage Anemic patients in the Non- Survivor group (41.1%) was more than in the
survivor group (12.1%). The mean Hematocrit in the survivor and the Non-survivor
groups were 34.35 ± 7.35 and 31.60 ± 11.43. The p-value was 0.3077 which is not
statistically significant.
0
10
20
30
40
50
60
70
<25 25-40 >40
12.1
2%
69.7
%
18.1
8%
41.1
8%
35.2
9%
23.5
3%
Perc
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ge
Hematocrit (%)
Figure 22: Comparison of Hematocrit
Survivors
Non-Survivors
54
Table 21: Comparison of Serum Creatinine among Survivors and Non-Survivors
Serum
Creatinine
Survivors Non-survivors Total
No. of
Patients Percentage
No. of
Patients Percentage
No. of
Patients Percentage
≤1 11 33.33 2 11.76 13 26
1.1-1.5 8 24.24 4 23.53 12 24
1.6-2.5 7 21.21 1 5.88 8 16
2.6-5.9 4 12.12 8 47.06 12 24
6.0-10.0 3 9.09 2 11.76 5 10
>10 0 0.00 0 0.00 0 0
Total 33 100.00 17 100.00 50 100
p-value: 0.0013
66% of the patients had Normal Serum Creatinine (<1.5mEq/l) and elevated
Creatinine was found in 44% of patients. The highest serum Creatinine observed was
4.4mg/dl. The Mean Serum Creatinine was 1.66 ± 1.41 among the survivor group and
the mean Serum Creatinine among the Non-Survivor group was 3.35 ± 2.08. The p-
value is 0.0013 which is statistically significant. This shows Non-Survivors had
higher elevated creatinine and Acute Kidney Injury had an adverse outcome in the
prediction of prognosis.
05
101520253035404550
<=1 1.1-1.5 1.6-2.5 2.6-5.9 6.0-10.0 >10
33.3
3%
24.2
4%
21.2
1%
12.1
2%
9.1%
0%
11.7
6%
23.5
3%
5.88
%
47.0
7%
11.7
6%
0%
Perc
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ge
Serum creatinine (mg/dl)
Figure 23: Comparison of S. Creatinine
Survivors
Non-Survivors
55
Table 22: Comparison of Serum Sodium among Survivors and Non-Survivors
Sodium
Survivors Non-survivors Total
No. of
Patients Percentage
No. of
Patients Percentage
No. of
Patients Percentage
≤119 0 0.00 2 11.76 2 4
120-134 16 48.48 8 47.06 24 48
135-145 15 45.45 4 23.53 19 38
146-154 1 3.03 3 17.65 4 8
≥155 1 3.03 0 0.00 1 2
Total 33 100.00 17 100.00 50 100
p-value: 0.3451
Normal Serum Sodium was seen in 40% of patients. Hyponatremia (Serum Na<
135mEq/l) was seen in 52% of patients. Of which 4% patients had severe
Hyponatremia (<120). Hypernatremia was observed in 8% of patients. The mean
Serum Sodium among Survivors was 134.1 ± 5.08 and the mean Serum Sodium
among Non-survivors was 131.8 ± 11.98. The p-value was 0.3451 which is
statistically not significant. This shows that hyponatremia can occur equally among
the two groups.
05
101520253035404550
<=119 120-134 135-145 146-154 >=155
0%
48.4
8%
45.4
6%
3.03
%
3.03
%
11.7
6%
47.0
6%
23.5
3%
17.6
5%
0%
Perc
enta
ge
Sodium (mEq/L)
Figure 24: Comparison of Serum Sodium
Survivors
Non-Survivors
56
Table 23: Comparison of Serum Albumin among Survivors and Non-Survivors
Albumin
Survivors Non-survivors Total
No. of
Patients Percentage
No. of
Patients Percentage
No. of
Patients Percentage
≤1.9 1 3.03 0 0.00 1 2
2.0-2.4 5 15.15 4 23.53 9 18
2.4-4.4 27 81.82 13 76.47 40 80
>4.5 0 0.00 0 0.00 0 0
Total 33 100.00 17 100.00 50 100
p-value: 0.2638
Majority of patients had normal serum albumin (82%). Hypoalbuminemia was
observed in 18% of patients. The mean Serum Albumin among the survivor and the
Non-survivor groups were 3.09 ± 0.58 and 2.88 ± 0.70 respectively. The p-value was
0.2638 which is not statistically significant.
0102030405060708090
<=1.9 2.0-2.4 2.4-4.4 >4.5
3.03
% 15.1
5%
81.8
2%
0%0%
23.5
3%
76.4
7%
0%
Perc
enta
ge
Albumin (g/dl)
Figure 25: Comparison of Serum Albumin
Survivors
Non-Survivors
57
Table 24: Comparison of Serum Bilirubin among Survivors and Non-Survivors
Bilirubin
Survivors Non-survivors Total
No. of
Patients Percentage
No. of
Patients Percentage
No. of
Patients Percentage
≤1.5 25 75.76 10 58.82 35 70
1.6-3.5 6 18.18 2 11.76 8 16
3.6-8 2 6.06 1 5.88 3 6
>8 0 0.00 4 23.53 4 8
Total 33 100.00 17 100.00 50 100
p-value: 0.0214
Majority of the patients (76%) had normal Serum Bilirubin. The highest S. Bilirubin
that was recorded was 12.3mg/dl. The Mean S. Bilirubin among the survivors and
Non-survivors were 1.6 ± 1.63 and 3.72 ± 4.64. The p-value was 0.0214 which is
statistically significant. This suggests that occurrence of Liver dysfunction in sepsis
patients was higher in the Non-survivor group.
0
10
20
30
40
50
60
70
80
<=1.5 1.6-3.5 3.6-8 >8
75.7
6%
18.1
8%
6.06
%
0%
58.8
3%
11.7
6%
5.88
%
23.5
3%
Perc
enta
ge
Bilirubin (mg/dl)
Figure 26: Comparison of S. Bilirubin
Survivors
Non-Survivors
58
Table 25: Comparison of RBS among Survivors and Non-Survivors
Glucose
Survivors Non-survivors Total
No. of
Patients Percentage
No. of
Patients Percentage
No. of
Patients Percentage
<39 0 0.00 0 0.00 0 0
40-59 0 0.00 0 0.00 0 0
60-199 29 87.88 14 82.35 43 86
200-349 3 9.09 3 17.65 6 12
>350 1 3.03 0 0.00 1 2
Total 33 100.00 17 100.00 50 100
Random Blood glucose was done in all patients at admission. Majority (86%) had a
normal RBS at admission. Hyperglycemia (>200mg/dl) was observed in 14% of the
patients. No patient had hypoglycemia. No statistically significant differences in the
serum Glucose at admission was observed in the two groups.
0102030405060708090
<39 40-59 60-199 200-349 >350
0% 0%
87.8
8%
9.09
%
3.03
%
0% 0%
82.3
5%
17.6
5%
0%
Perc
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ge
Glucose (mg/dl)
Figure 27: Comparison of RBS
Survivors
Non-Survivors
59
Table 26: Comparison of pH among the survivors and Non-survivors
pH
Survivors Non-survivors Total
No. of
Patients Percentage
No. of
Patients Percentage
No. of
Patients Percentage
<7 0 0.00 2 11.76 2 4
7.0-7.34 16 48.48 9 52.94 25 50
7.35-7.45 12 36.36 2 11.76 14 28
>7.45 5 15.15 4 23.53 9 18
Total 33 100.00 17 100.00 50 100
p-value: 0.0789
The pH of Arterial blood was analysed. 54% of the patients had Metabolic Acidosis.
28% of patients had Normal pH and 18% had alkalosis. Of which 2 patients (4%) had
severe Metabolic Acidosis i.e., p H <7.0. Both patients did not survive. Suggesting
that severe Metabolic acidosis in sepsis patients had unfavorable prognosis.
0
10
20
30
40
50
60
<7 7.0-7.34 7.35-7.45 >7.45
0%
48.4
9%
36.3
6%
15.1
5%
11.7
6%
52.9
4%
11.7
6%
23.5
4%
Perc
enta
ge
pH
Figure 28: Comparison of pH
Survivors
Non-Survivors
60
Table 27: Comparison of AaDO2 among Survivors and Non-survivors
AaDO2
Survivors Non-survivors Total
No. of
Patients Percentage
No. of
Patients Percentage
No. of
Patients Percentage
<50 11 33.33 1 5.88 12 24
50-100 5 15.15 0 0.00 5 10
101-249 7 21.21 1 5.88 8 16
250-349 8 24.24 9 52.94 17 34
>=350 2 6.06 6 35.29 8 16
Total 33 100.00 17 100.00 50 100
p-value: 0.0001
The degree of Oxygenation was assessed using the Arterial- Alveolar Oxygen
Gradient. The mean AaDO2 among the survivors was 158.8 ± 133.1 and among the
non-survivors was 326.2 ± 116.6. The p-value was 0.0001 which is statistically highly
significant. This showed adequate oxygenation was necessary for better outcome in
patients.
0
10
20
30
40
50
60
<50 50-100 101-249 250-349 >=350
33.3
3%
15.1
5% 21.2
1%
24.2
4%
6.07
%
5.88
%
0%
5.88
%
52.9
5%
35.2
9%
Perc
enta
ge
AaDO2 (mmHg)
Figure 29: Comparison of AaDO2
Survivors
Non-Survivors
61
Table 28: Comparison of GCS Score among the Survivors and Non-Survivors
GCS
Survivors Non-survivors Total
No. of
Patients Percentage
No. of
Patients Percentage
No. of
Patients Percentage
3 0 0.00 0 0.00 0 0
4-7 0 0.00 5 29.41 5 10
8-11 0 0.00 5 29.41 5 10
>12 33 100.00 7 41.18 40 80
Total 33 100.00 17 100.00 50 100
p-value: 0.000005
The Glasgow Coma Scale was assessed in all patients at admission. All survivors had
GCS> 12 at admission. 10% of Non-Survivors had GCS 8-11, 10% had GCS between
4-7. Rest of the Non-survivors had GCS >12. This shows that presentation of sepsis
patients with a low GCS score at admission was associated with a poor prognosis. P-
value= 0.000005 which is statistically significant.
0102030405060708090
100
3 4-7 8-11 >12
0% 0% 0%
100%
0%
10%
10%
80%
Perc
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ge
GCS
Figure 30: Comparison of GCS
Survivors
Non-Survivors
62
Table 29: Comparison of Total APACHE scores among Survivors and Non-
Survivors.
APACHE
Survivors Non-survivors Total
No. of
Patients Percentage
No. of
Patients Percentage
No. of
Patients Percentage
≤20 2 6.06 0 0.00 2 4
21-50 24 72.73 0 0.00 24 48
51-80 6 18.18 5 29.41 11 22
80-100 2 6.06 3 17.65 5 10
>100 0 0.00 9 52.94 9 18
Total 33 100.00 17 100.00 50 100
p-value: 0.000001
Of the 50 patients, studied, 4% of the patients had APACHE III score <20, 48%
patients had score of 21-50. 22% patients had score of 51-80. 10% between 80-100
and 18% patients had score>100. The Mean APACHE III score among survivors was
41.12 ± 15.02 and the Mean APACHE III score among Non-Survivors was 97.18 ±
25.07 which was significantly higher. The p-value was 0.000001 which is statistically
highly significant. This shows that higher APACHE III score at admission was
associated with bad outcome.
0
20
40
60
80
<=20 21-50 51-80 80-100 >100
Figure 31: Comparison of APACHE III score
Survivors Non-Survivors
63
Table 30: Discrimination of APACHE III scoring system
The Discrimination power of APACHE III was assessed using the Receiver-Operator
Curve (ROC) curve which involves plotting a graph of Sensitivity v/s 1-Specificity.
The Area under the curve (AUC) represents the number of patients who died. Ideally
the AUC should be >0.7. which indicates that the scoring system is successfully able
to discriminate between the Survivors and Non-survivors. The results are as follows
Area under the ROC curve
Area 0.9742
Std. Error 0.01827
95% confidence interval 0.9383 to 1.010
P value < 0.0001
Data
Controls (Non-survival) 17
Patients (Survival) 33
Missing Controls 0
Missing Patients 0
APACHE III significantly discriminates the Survivors from the Non-Survivors as
demonstrated in the ROC. P-value <0.0001.
64
Figure 32: ROC Curve
65
DISCUSSION
A short prospective study to analyze the clinical profile of sepsis patients in ICU and
to predict the usefulness of Acute Physiology and Chronic Health Evaluation III score
to predict the mortality in such patients was studied. 50 patients satisfying the
Inclusion and the Exclusion criteria were enrolled into the study over a period of 1
year.
Age distribution
The study group had patients of varying age group. Age of patients varied from 18
years to 96 years. Most patients were in the age group of 41-50 years. The mean age
of the study group was 42.84 ± 17.34. No statistically significant difference in the
mortality was observed in the study groups. Compared to other studies done at various
centers, our study had a younger population
Ihnsook et al53 Carneiro et al54 Present study
Mean Age (in
years)
54.8 56.9 42.8
Gender Distribution
Of the 50 patients studied, 56% patients were Male and 44% patients were females.
The male preponderance was also observed in other previous Indian studies and also
in studies done abroad.
Ihnsook et al53 Carneiro et al54 Abrahamsen et al55 Present study
Male: Female(%)
59/41 70/30 61/39 56/44
66
Length of stay in ICU
The duration of stay in the ICU can have multitude of influence on the final outcome.
Longer stay in the ICU is associated with more Nosocomial infections like Ventilator
Acquired pneumonia, Central Line sepsis etc which can prolong the stay and can even
increase the mortality.56 The mean duration of stay in the ICU was 7.21 days. But no
significant difference was noted in the duration of stay in the ICU in our study among
the survivors and Non-Survivors. Compared to other studies, the mean duration in our
study was less. The results in other similar studies as follows
Ihnsook et al53 Carneiro et al54 Present study
Duration in days 10.7 9.4 7.21
Etiology of Sepsis
The study was intended to identify the source of sepsis and threat the same
effectively. The most common source of sepsis identified in our study was
Respiratory (46%) followed by Urogenital (16%) and Intra-abdominal (16%). Skin-
soft tissue, Neuroinfection and tropical infections like Malaria constituted a smaller
percentage. This profile of source of sepsis has been validated in multiple studies. (16-
19)
Microbiological spectrum
Streptococcus pneumonia was the most common organism isolated from Respiratory
secretions and Escheirechia coli from specimen collected from patients with
Urogenital and intra-abdominal sepsis. This is on par with the bacteriological profile
studied in sepsis patients in multiple studies. (16-19)
67
Effect of co-morbid illness
The most common pre-existing medical illness identified in our study was Diabetes
Mellitus. Though a higher incidence of co-morbidities of diseases like immune-
suppression, leukemias, metastatic cancer have been proven to have poor outcome; no
statistically significant association was established in our study. This could be
explained by the low incidence of such diseases in the study group and the small
sample size. A larger study on such group of patients may be necessary to establish an
association.
Mortality
Gaiski et.al.reported an In-hospital mortality rate ranging from 14.7% to 29.9% after
their multicentric study across Pennsylvania USA. The study noted a wide range in
the difference in the incidence of mortality in severe sepsis. 57
Of the 50 patients studied, 33 patients (66%) survived and 17 patients (34%)
succumbed to sepsis. The Mortality rate was 34%. Though the mortality rate is
alarmingly high, similar results have been obtained from studies in India.
Ihnsook etal53
(n=284)
Carneiro etal54
(n= 220)
Desaiet.al.58
(n=50)
Todi et.al.59
(n=1,344)
Presentstudy(n=50)
Mortality 30.9% 15% 48% 54.1% 34%
68
Incidence of Multi Organ Dysfunction Syndrome
The Incidence of MODS was high in the study. Occurrence was MODS was one of
the major cause of Mortality. A Total of 50% patients had MODS. Acute Kidney
Injury was observed in 46% of patients, Hepatic dysfunction in 24%, Neurological
dysfunction in 20%, ARDS in 12% and severe coagulopathy in 4% of the patients.
Todi et al59 Desai et al58 Present study
Incidence 17.1% 78% 50%
Clinical features
Fever was the presenting complaint in all 100% patients followed by Cough (44%),
Breathlessness (42%)
Clinical Predictors of Mortality
All patients had temperature above 98ºF. Hypothermia was not observed in any
patient. There was n statistical differences among the mean Temperature among
Survivors and Non-survivors (p=0.8247).
The mean pulse rate was much higher among Non-survivors (119.2 v/s 108,
p=0.0170). There was also significant difference in the mean Respiratory rate. It was
higher in Non-survivor group (34.06 v/s 26.6, p=0.0081). This shows that
Tachycardia and Tachypnea could be useful markers to assess the severity of infection
and outcome prediction.
69
Among the hematological parameters, though the mean Hematocrit was higher (34.35
v/s 31.60) and the mean WBC count was lower (17.94 v/s 22.0) among Survivors, no
statistically significant difference was established.
Onset of Renal dysfunction is known to change the clinical course of a patient in
sepsis. Our study showed statistically significant differences in the serum Creatinine
among the two groups. The mean serum creatinine was higher in the Non-survivor
group (3.35 v/s 1.66, p= 0.0013) which is statistically significant. The deteriorating
renal parameters could be assessed by clinically assessing and monitoring the Urine
output. Fall in the urine output can precede biochemical parameters. The difference in
the mean Urine output was highly significant. Survivor (1835 ± 560.8) and Non-
survivor (747.1 ± 731.3), the p-value being 0.0001.
Neveu et.al.in 1996, after a multicentric study in France concluded that septic acute
renal failure occurred more commonly in older patients (mean age: 62.2 versus 57.9
years, P<0.02) and had on inclusion a higher APACHE II (29.6 versus 24.3,
P<0.001), than patients with non-septic acute renal failure. They had a higher need for
mechanical ventilation (69.1% versus 47.3%, P<0.001), Hospital mortality was higher
in patients with septic acute renal failure (74.5%) than in those whose renal failure did
not result from sepsis (45.2%, P<0.001). 60
Oppert et.al.in 2008 after their study with 415 patients with septic Renal failure
concluded that Acute renal failure was an independent risk factor for mortality in
severe sepsis and septic shock. 61
As it is clear from the above discussion, the findings from our study concurs with the
study by Oppert et.al.and Naevu et.al. So we strongly conclude that presence of AKI
is a significant risk for mortality in septic shock patients.
70
Acute Hepatic dysfunction occurs in septic shock patients in previous normal liver
functions and can be exacerbated in patients with pre-existing cirrhosis. The Mean S.
Bilirubin among the survivors and Non-survivors were 1.6 ± 1.63 and 3.72 ± 4.64.
The p-value was 0.0214 which is statistically significant. This suggests that
occurrence of Liver dysfunction in sepsis patients was higher in the Non-survivor
group.
Gimson et.al.in their article state that the hepatic dysfunction in sepsis is
multifactorial due to combination of hypoxic hepatitis, congestion, cholestasis and
toxin mediated liver injury. The outcome of such patients was poor if it was
associated with other organ dysfunction like coagulopathy, renal and cardiac
dysfunction. 62
Serum Sodium, Serum Albumin, Serum glucose at admission did not show significant
differences among the 2 groups. Our study is in contradiction to the NICE study
which recommends a strict glycemic control for critically ill patients.63
The Glasgow Coma Scale was assessed in all patients at admission. All survivors had
GCS> 12 at admission. 10% of Non-Survivors had GCS 8-11, 10% had GCS 4-7.
Rest of the Non-survivors (80%) had GCS >12. This shows that presentation of sepsis
patients with a low GCS score at admission was associated with a poor prognosis. P-
value= 0.000005 which is statistically significant.
Bastos et.al.studied GCS along with APACHE III score in 15,973 patients admitted
with septic shock across 40 ICUs in the United States. The relationship between
the Glasgow Coma Scale score and outcome for sepsis patients were examined and
compared. The Glasgow Coma Scale score on ICU admission had a highly significant
(r2 = .922, p < .0001) but nonlinear relationship with subsequent outcome in ICU
71
patients. Discrimination of patients into high- or low-risk prognostic groups was
good, but discrimination in the intermediate levels (Glasgow Coma Scale score of 7 to
11) was reduced. The study concluded that the Glasgow Coma Scale may be used to
stratify risks and mortality in ICU patients. 64
Total APACHE III Score.
The Mean APACHE III score was significantly higher among Non-Survivors (mean
97.18 v/s 41.12, p=0.000001) which is highly statistically significant. Score >80 was
associated with significant mortality. In the 28 % patients who had score >80, only
7% were survivors. In patients with score >100, there were no survivors.
Mean APACHE III
score
Ihnsook et al53 Zhang et al65 Present study
Survivors 34.1± 2.6 88.42±26.86 41.12 ± 15.02
Non- Survivors 81.0± 30.2 106.72±27.30 97.18 ± 25.07
Area Under ROC
curve
0.905 0.68 0.9742
As it is clear from the studies shown above which assessed the APACHE III score in
the prediction of outcome in patients with sepsis, the Mean APACHE III score was
significantly higher among Non- Survivors compared to Survivors. p-value was <0.01
in all the studies. This shows that the difference is statistically significant.
The discrimination power of the APACHE III scoring system was assessed using the
Receiver-Operating Charactertic (ROC) curve which involves plotting a graph of
Sensitivity v/s 1-Specificity. The Area under the curve (AUC) represents the number
of patients who died. Ideally the AUC should be >0.7. Our study had a AUC of
72
0.9742. Similar studies have been observed with studies by Ihnsok et al53 and Zhang
et.al.65
Utility of APACHE III in postoperative surgical patients
The utility of APACHE III system was assessed in surgical patients following major
thoracoabdominal surgeries. Loay et.al.in 2010, assessed the APACHE III score
among patients undergoing Aortic Aneurysm repair. In a study with 450 patients, they
found a mortality rate of 4.9% with the APACHE III score being significantly higher
among Non-survivors (79 vs. 45, p < 0.0001) and an excellent discriminator by ROC
(AUC 0.92 standard error of 0.05, 95% CI: 0.83-1.0). 66
Keegan et.al.conducted a similar study to assess the utility of APACHE III among
post pneumonectomy patients (N=281). The mortality rate was 8.2% and the mean
APACHE III score was also found to be higher among Non-survivors (p<0.01) and
concluded the APACHE III discriminates moderately well between survivors and
Non-survivors.
Thus the utility of APACHE III can be well utilized in post operative surgical patients
too.67
Thus, we concur with earlier studies done elsewhere in the world and are of the
opinion that APACHE III score can be used to predict mortality in sepsis with a good
discrimination power to distinguish the two study groups.
73
LIMITATIONS OF THE STUDY
The sample size was small
Nosocomial complications could adversely change the outcome which cannot
be predicted only by the APACHE score calculated at admission. Serial
APACHE III score done everyday thus might be of significance.
Socio-economic constraints in few patients may also hinder the treatment
options which cannot be assessed by the scoring system.
74
CONCLUSIONS
Acute Physiology and Chronic Health Evaluation Score III estimated on the
day of admission is significantly higher among Non-Survivors compared to
Survivors and has a good discrimination to differentiate the two groups.
Serial APACHE III score if calculated everyday may increase the reliability of
the score in predicting the outcome.
75
SUMMARY
ICU scoring systems have been designed since past 30 years to assess the
severity of the disease and to assess the In-hospital mortality rates. Such
scoring systems help in prognosticating and predicting the final outcome
The total number of patients enrolled in the study was 50.
Majority of the patients in the study group were 41-50 years. The mean age of
the study group was 42.84 ± 17.34.
In the study group, 56% patients were Male and 44% patients were females.
Of the 50 patients studied, 33 patients (66%) survived and 17 patients (34%)
were non- Survivors.
No significant age difference noted among the two groups.
No significant difference was noted in the duration of stay in the ICU among
the two groups
The most common source of sepsis identified was Respiratory infection (46%)
followed by Urogenital (16%) and Intra-abdominal (16%).
Streptococcus pneumonia was the most common isolated in respiratory
infections and E.coli in Urogenital and intra-abdominal sepsis.
Diabetes Mellitus was the most common associated co-morbid condition.
Incidence of Multiorgan Dysfunction was high. Acute Kidney Injury was the
most common, observed in 46% of patients,
Fever was most common symptom seen in all 50 patients
Serum Creatinine, Serum Bilirubin, Urine output, Glasgow Coma Scale,
AaDo2 were the parameters from the APACHE III panel with high statistical
significance.
76
APACHE III score was significantly higher among Non-Survivor (mean
97.18) as compared to Survivors (41.12)
The discrimination of APACHE III score is good.
77
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84
ANNEXURES
PROFORMA
Name of the patient:
Date of admission:
Age: Gender:
Address:
Occupation:
Travel History: IP No.:
2. HISTORY (Symptoms at the time of presentation)
Fever Myalgia
Dyspnea Artharlgia
Cough and expectoration Abdomen pain
Wheeze Nausea/vomiting
Hemoptysis Loose stools
Chest pain Upper/lower GI bleed
Altered Sensorium Abdomen distension
Head Ache Jaundice
Convulsions Lower limb swelling
Dysuria Decreased urine output
Rash Limb Weakness
85
3. PRIOR TREATMENT LOCATION:
Emergency Dept Transfer from another hospital
Medicine ward Transfer from another ICU
Direct to ICU Operation Theatre
4. PRE-EXISTING COMORBIDITIES-(I)
Diabetes Mellitus Chronic Renal failure
Ischemic Heart disease COPD/Asthma
Chronic liver disease Alcoholism
Smoking Others
Hypertension
5. COMORBID CONDITION – II (APACHE-III POINT)
AIDS Leukemia / Multiple Myeloma
Hepatic Failure Immunosuppression
Lymphoma Cirrhosis
Metastatic Cancer
6. GENERAL PHYSICAL EXAMINATION
Pulse BP RR Temp.
Pallor
Icterus
Cyanosis
Clubbing
Edema
Any Other Specific Finding:
7. RESPIRATORY
Breath sounds
86
Crackles / creps
Ronchi
8. CARDIOVASCULAR SYSTEM
Heart sound
Murmers
9. ABDOMEN
Hepatomegaly
Splenomegaly
Ascitis
Tenderness
10. CENTRAL NERVOUS SYSTEM
GCS
Motor System
Reflexes
Signs of meningeal irritation
Fundus
87
11. APACHE-III SCORING
Sl.
No.
Variable Observed Value Score
(a) Pulse
(b) Mean BP (mm Hg)
(c) Temperature (oC)
(d) Respiratory Rate
(e) PaO2 (mm Hg)
(f) AaDO2 (mm Hg)
(g) Hemotocrit (%)
(h) WBC Count ( /ml)
(i) S. Creatinine (mg/dl) without ARF
(j) S. Creatinine (mg/dl) with ARF
(k) Urine output (ml/day)
(l) Serum Bun (mg/dl)
(m) Serum Na+ (mg/dl)
(n) Serum Albumin (mg/dl)
(o) Serum Bilirubin (mg/dl)
(p) Serum glucose (mg/dl)
12. GLASGOW COMA SCALE
Sl. No. Observed
Component
Score
(a) Eye Opening
(b) Motor Response
(c) Verbal Response
88
13. ACUTE PHYSIOLOGY SCORE
PH
PaO2
Acute physiology score
14. MICROBIOLOGICAL STUDIES
Specimen
Bacteria Cultured
Sensitivity pattern
15. OTHER INVESTIGATIONS
Malarial Parasite
Urine routine / micro
Chest X-ray
ECG
2D-Echo
Serology
USC Abdomen
Other imaging studies
16. INTERVENTIONS
YES NO
Need for Ventilatory support
Need for Isotropic support
Need for Dialysis
Surgery
89
17. DURATION OF ICU STAY
18. OTHER SIGNIFICANT EVENTS
19. OUTCOME OF PATIENT
Improved
Status quo
MODS
Mortality
20. CONCLUSION
Sl No.Name Age Sex IP no. Fever Breathlessness Cough &
Expectoration Wheeze Headache Convulsions Painabdomen
Alteredsensorium Jaundice Decreased urine
output Rashes Priortreatment
Past Medicalhistory
1 Basappa 74 M 37669 Y N N N N N N Y N Y N ED T2DM2 Raju 17 M 37568 Y N N N Y Y N Y N N N ICU -3 Sudha 28 F 38606 Y Y Y Y N N N N N N N HOSP -4 Mallika 21 F 46328 Y N N N Y N Y N N N N ED -5 Sumitramma 38 F 6421 Y N N N N N Y N Y N N ED -6 Girija 35 F 41217 Y Y Y N N N N N N N N ED -7 Maktumsab 60 M 39532 Y Y Y N N N N N N N N ED T2DM8 Samuel 19 M 38827 Y N N N N N N N N Y Y WARD -9 Gopal 42 M 6589 Y Y Y N N N Y Y N Y N ED T2DM
10 Parvatamma 95 F 7526 Y Y Y N N N N Y N N N ED ASTHMA11 Yallappa 70 M 10822 Y Y Y Y N N N Y N Y N ED COPD12 Paravva 25 F 9089 Y N N N N N N Y Y Y N ED -13 Basavaraj 42 M 38716 Y N N N N N N Y Y Y Y ED14 Shankar 38 M 10213 Y N N N N N Y N N Y N WARD AIDS15 Gowramma 44 F 19211 Y N N N N Y N N N N N OT -16 Moulasab 52 M 6571 Y N N N N N Y N N N N OT -17 Lakshmi 22 F 8264 Y Y Y N N N N N N N N ED -18 Siddamma 47 F 14525 Y N N N N N Y N N Y N ED T2DM19 Venkatesh 48 M 5979 Y Y Y Y N N N N N N N ED -20 Uma 20 F 7555 Y Y Y N N N N N N N N HOSP -21 Hasinabanu 24 F 1009 Y N N N N N N Y N N N HOSP None22 Vijaylakshmi 34 F 21403 Y Y Y N N N N N N N N ICU AIDS23 Ashwini 24 F 10855 Y N N N N N N Y N N N HOSP -24 Bharatesh 45 M 11234 Y Y Y N N N N Y N N N ICU T2DM25 Gopal Joshi 69 M 38654 Y Y Y N N N N N N Y N ICU IHD
CKD26 Kallappa 45 M 9031 Y N Y N N N Y N N Y N WARD CML
27 Akbarsab 72 M 41501 Y Y Y N N N N Y N N N ED T2DMIHD
28 Sumitrabai 55 F 7634 Y Y N N N N N Y N Y N ED T2DMIHD
29 Deepak 32 M 3210 Y N N N N Y N N N N N ED Alcohol30 Nagavva 55 F 37508 Y N Y N N N N Y N N N ED T2DM31 Noorjanbi 50 F 5992 Y N N N N N N N Y N N ED T2DM32 Shankarappa 53 M 12899 Y Y Y N N N N N N N N ED HTN33 Laxmidevi 45 F 40674 Y Y Y N N N N N N N N HOSP -34 Ishwar 28 M 40039 Y N N N N Y N Y N N N ICU Leprosy35 Rajeshwari 18 F 20321 Y Y N N N N N N N N Y ED36 Basamma 48 F 33124 Y Y Y N N N N N N N N ED None37 Drakshayini 52 F 3098 Y N N N N N Y N N Y N ED T2DM38 Shankargouda 60 M 42409 Y Y Y Y N N N N N N N ED PTB COPD39 Hasansab 44 M 13081 Y N N N N N Y N N Y N ED None40 Ningappa 57 M 43120 Y N N N N N N N N N N ED T2DM41 Shivaji 60 M 10014 Y N N N Y Y N Y N N Y HOSP HTN42 Devendrappa 50 M 20123 Y N N N N N Y N Y N N ED None43 Mehboob 38 M 19132 Y Y Y N N N N N N N N ED None44 Parvati 24 M 32146 Y N N N N N Y N Y N N ED Cholelithiasis45 Ishaq 18 M 12177 Y N Y N N N N N N N N ED None46 Shantavva 45 F 12340 Y N N N N N Y N N Y N ED T2DM47 Manjappa 34 M 12970 Y N N N N N Y N N N N ED None48 Ramappa 53 M 24567 Y N N N N N Y N Y N N ED None49 Suresh 19 M 9371 Y Y Y Y N N N N N N N ED None50 Fakiravva 54 F 34561 Y N N N N N Y N N N N ED HTN
Sl No.123456789
1011121314151617181920212223242526
272829303132333435363738394041424344454647484950
Comorbidconditions Physical Exam Respiratory CVS Per abdomen CNS
- - NAD NAD NAD comatose- Normal NAD NAD Splenomegely Pappiledema
AML - ARDS NAD Gravid uterus NAD- NAD NAD NAD Hepato Splenomegely Pappiledema- NAD NAD NAD Hepatomegely NAD- NAD ARDS NAD NAD NAD- NAD L. Pleural effusion NAD NAD NAD- pustular rashes NAD NAD NAD NAD- Pallor R. consolidation NAD NAD NAD- Pallor L. consolidation NAD NAD drowsy- Cyanosis L. consolidation NAD NAD drowsy- Pallor NAD NAD NAD drowsy
Liver Cirrhosis Icterus NAD NAD ascitis tenderness drowsyAIDS - NAD NAD Renal angle tenderness NAD
- - NAD NAD mass in LIF NAD- - NAD NAD Guarding rigidity NAD- B/l creps NAD NAD NAD- - NAD NAD Renal angle tenderness NAD- - Left consolidation NAD NAD NAD- - B/l creps NAD NAD NAD - Pallor NAD NAD NAD NAD
AIDS pallor, candidiasis B/l creps NAD NAD neck stiffness - Pallor edema NAD NAD NAD - Pallor B/l creps NAD NAD comatose
Carcinoma Penis _ B/l creps NAD NAD L. Hemiplegia - Pallor R. consolidation NAD Splenomegely NAD
Bladder cancer clubbing B/l creps NAD ascitis tenderness drowsy - Anasarca B/l creps NAD ascitis tenderness drowsy - Icterus NAD NAD Splenomegely NAD - Cyanosis Cavernous breath sounds NAD NAD NAD - Edema NAD NAD flank tenderness NAD - Cyanosis R. consolidation NAD NAD Drowsy - Cyanosis B/l creps NAD NAD NAD - Leonine facies B/l creps NAD Splenomegely Pappiledema
TGA Pallor NAD VSD NAD NADNone NAD L. consolidation NAD NAD NADNone NAD NAD NAD Renal angle tenderness NADNone Pallor b/l creps and ronchi NAD NAD NADNone NAD NAD NAD Guarding rigidity NADNone R. Limb edema NAD NAD NAD NADNone pethechial rashes NAD NAD NAD drowsyNone Icterus R. Pleural effusion NAD Tender hepatomegaly NADNone NAD R. consolidation NAD NAD NADNone icterus NAD NAD Murphy's sign + NADnone NAD B/l creps NAD NAD NADNone NAD NAD NAD Hypogastric tenderness NADNone NAD NAD NAD Guarding rigidity NADNone Icterus NAD NAD Splenomegely NADNone NAD B/l creps NAD NAD NADNone NAD NAD NAD Guarding rigidity NAD
SlNo Name Pulse
MeanArterial
PressureTemp Respiratory
Rate PaO2 AaDO2 Hematocrit WBC count S.Creat ARF Urine
output BUN SerumNa+ S.Albumin S.Bilirubin S.Glucose GCS ABG Ventilatory
support
1 Basappa 98 76 99 18 64 331 20.3 29 2.3 Y 350 60 131 2.1 0.6 140 E1V1M2 7.12/26 Y2 Raju 130 80 101 24 172 184 30.8 22.1 0.8 N 1400 44 137 2.6 2.5 130 E4V5M6 7.45/26 Y3 Sudha 136 90 102 45 52 481 33 32 1.2 N 1100 21 121 3.9 0.9 134 E3V4M5 7.46/52 Y4 Mallika 112 70 103 28 82 286 22.3 14.9 1.3 N 2000 40 128 2.9 0.7 92 E3V3M4 7.21/48 Y5 Sumitramma 128 70 101 26 92 292 38.7 27 0.6 N 2000 10 131 2.1 7.8 121 E4V5M6 7.21/35 N6 Girija 100 83 101 50 50 461 37.1 3000 0.6 N 2500 16 125 2.6 1.5 78 E4V5M6 7.39/23.5 Y7 Maktumsab 76 83 101 30 82 24 34.1 21.2 0.9 N 2000 11 139 2.7 0.7 159 E4V5M6 7.35/35 N8 Samuel 120 53 101 14 117 8 21.9 33.2 2 Y 800 34 131 2.1 0.9 99 E4V5M6 7.52/19.7 N9 Gopal 112 60 99 32 60 315 36.1 22.1 4.1 Y 2300 138 124 3.5 0.9 512 E4V5M6 7.23/42 N
10 Parvatamma 98 76 101 26 75 313 44.2 17.9 3.2 Y NIL 174 135 2.8 0.8 82 E2V1M4 7.64/32 Y11 Yallappa 118 130 99 38 121 289 36.5 23 7.4 Y 150 136 143 2.5 0.9 136 E4V5M6 6.9/13.9 Y12 Paravva 130 53 99 32 88 370 16.6 26.8 6.4 Y 200 132 144 2.7 12.2 118 E2V2M3 7.25/19.4 Y13 Basavaraj 120 70 102 28 105 360 21.1 21.1 4.5 Y 200 80 131 2.5 12.3 92 E2V4M5 7.29/21.4 Y14 Shankar 112 73 101 24 73 33 37.1 19.2 1.8 Y 1500 60 135 3.3 0.9 124 E4V5M6 7.35/35 N15 Gowramma 110 90 102 20 159 238 14.1 9.9 0.8 N 2000 13 136 3 1.6 80 E4V5M6 7.42/24.7 Y16 Moulasab 100 76 102 18 89 296 32.2 17.6 1.2 N 1900 30 143 2.5 1 105 E4V5M6 7.42/33.9 Y17 Lakshmi 108 80 102 35 93 22 35.4 12.9 0.8 N 2000 11 131 2.2 1 86 E4V5M6 7.50/28.9 N18 Siddamma 124 60 103 28 85 16 44.4 36 1.4 N 1800 22 128 3.4 1.2 155 E4V5M6 7.33/39 N19 Venkatesh 116 70 103 32 66 323 36.8 21.2 0.6 Y 1700 72 139 3.9 1.2 134 E4V5M6 7.31/31 Y20 Uma 136 86 104 48 49 613 38.4 7.5 1.4 N 1500 30 146 3.1 0.8 113 E4V5M6 7.16/41.2 Y21 Hasinabanu 130 70 100 24 98 285 10.6 3.5 1.2 N 1500 57 131 3.7 2.3 220 E4V5M6 7.38/36 N22 Vijaylakshmi 128 80 99 42 159 245 18.8 8.1 0.8 N 1500 9 112 3.7 0.9 114 E4V5M6 7.50/19.3 Y23 Ashwini 140 46.7 101 36 60 347 20.5 27.8 3.8 Y 1600 60 121 2.6 12.1 120 E4V5M6 7.19/17 Y24 Bharatesh 130 100 99 44 68 319 27 3.3 0.8 N 2100 12 115 4.3 0.3 295 E4V1M1 7.4/32.9 Y25 Gopal Joshi 98 93 99 40 371 26 34.7 2.9 5.1 Y 200 125 153 2.7 0.4 322 E2V3M3 7.31/24.8 Y26 Kallappa 130 90 101 40 65 313 53 90 2.9 Y 900 74 125 2.1 1.4 115 E3V5M6 7.01/40 Y27 Akbarsab 131 63 102 30 36 353 42 23 4.1 Y 300 102 124 2.1 1.8 256 E4V5M6 7.40/30.9 Y28 Sumitrabai 130 53 102 34 162 251 39.8 32.8 5.9 Y NIL 75 125 4 3.2 117 E3V1M5 6.84/11.5 Y29 Deepak 112 70 101 20 63 321 42.2 3.7 2 Y 1400 26 146 2.2 7.2 73 E4V5M6 7.31/35.2 Y30 Nagavva 106 56 102 26 88 67 32.2 17.2 1.4 N 2500 24 139 2.8 0.9 185 E4V5M6 7.46/28 N31 Noorjanbi 122 40 103 28 72 317 40.2 26.8 6.6 Y 300 94 128 3.2 1 172 E4V5M6 7.21/31 Y32 Shankarappa 124 73 103 34 78 312 42.4 34.3 0.8 N 2000 54 132 3.5 1.2 134 E4V5M6 7.22/38 Y33 Laxmidevi 130 90 102 45 104 423 33.4 33 0.8 N 2300 10 135 3.6 0.8 112 E4V5M6 7.27/39 Y34 Ishwar 90 86 101 26 86 298 21.4 3.5 1.5 Y 400 21 139 2.1 4.2 134 E4V1M1 7.47/86 Y35 Rajeshwari 120 85 99 34 95 78 28.3 18.5 6 Y 2500 79 135 2.8 1 142 E4V5M6 7.45/ 35 N36 Basamma 88 78 100 28 88 96 30.2 14.2 1.2 N 2000 20 140 3.1 1.3 167 E4V5M6 7.31/40 N37 Drakshayini 100 90 101 19 99 74 41.8 18.4 2.1 Y 1000 74 131 3.5 0.9 201 E4V5M6 7.38/48 N38 Shankargouda 96 73 98 18 100 90 33.3 4.3 0.8 N 1200 25 129 4.4 0.4 121 E4V5M6 7.53/32.4 N39 Hasansab 102 56 98 20 80 125 39.2 21.5 3.1 Y 1350 100 139 3.1 1.1 102 E4V5M6 7.29/29 Y40 Ningappa 97 73 100 15 99 122 38.7 14.5 1.8 N 1600 78 135 3.2 1.1 286 E4V5M6 7.32/40 N41 Shivaji 102 60 100 24 58 350 47.6 10.4 4.5 Y 200 120 147 2.8 9.8 119 E3V3M5 7.07/57.6 Y42 Devendrappa 110 78 99 24 90 24 40.1 23.4 2.1 Y 3000 92 134 3 3.1 124 E4V5M6 7.35/48.2 N43 Mehboob 108 53 101 38 74 140 39.4 19.1 1.1 N 2400 45 138 3.5 1.2 110 E4V5M6 7.29/42 N44 Parvati 100 53 100 20 99 20 38.1 14.2 0.9 N 1600 32 130 3.1 1.5 119 E4V5M6 7.31/45 N45 Ishaq 90 80 100 30 157 104 34.2 6.7 0.9 N 2600 28 130 3.7 0.4 179 E4V5M6 7.41/36.5 N46 Shantavva 102 90 99 14 82 46 34 1.4 1.8 Y 1400 70 129 2.9 1.1 178 E4V5M6 7.52/ 40.1 N47 Manjappa 100 78 100 20 90 60 39.2 15.2 1.3 N 1800 45 132 3.5 1 123 E4V5M6 7.23/39 N48 Ramappa 98 90 100 22 88 30 33 14.2 1.1 N 2000 36 135 3.8 2.2 90 E4V5M6 7.29/32 N49 Suresh 120 80 100 48 80 220 34.1 22.5 1 N 2000 45 137 2 0.7 129 E4V5M6 7.42/39.2 N50 Fakiravva 88 73 99 20 78 74 30.1 20 1.2 N 2200 37 140 3.4 1.2 111 E4V5M6 7.21/31 N
Inotropes Dialysis Duration(in days) Micro Sample Growth Diagnosis Total
APACHE Survival
Y Y 7 Pus S. Aureus Septic arthritis 143 NN N 7 CSF NG Pyogenic meningitis 37 YN N 2 blood NG Bronchpneumonia + ARDS 59 NY N 3 blood Mixed Malaria Complicated Malaria 62 NY N 2 Liver Abscess E. Coli Pyogenic Liver abscess 49 YN N 21 Sputum NLF Bronchopneumonia + ARDS 40 YN N 7 Pleural fluid Klebsiella L. Empyema thoracis 21 YY N 6 Pus S. Aureus Pyoderma 62 YN Y 21 Sputum Klebsiella R. lower lobe Pneumonia 56 YY Y 10 Sputum Pneumococci L. lower lobe Pneumonia 111 NN Y 7 Sputum Pneumococci L. lower lobe Pneumonia 106 NY Y 2 Vaginal swab E. Coli Puerperal sepsis 133 NY Y 3 Serum Leptospira Leptospirosis 110 NY N 5 Urine E. Coli Acute Pyelonephritis 58 YN N 4 Pus E. Coli Psoas abscess 13 YY N 14 Ascitic fluid NLF Perforation Peritonitis 26 YY N 4 Sputum Pneumococci Bronchpneumonia + ARDS 24 YY N 4 Urine E. Coli Acute Pyelonephritis 43 YN N 5 Sputum Pseudomonas L. lobar Pneumonia 50 YN N 4 Sputum NLF Bronchpneumonia + ARDS 62 NY N 7 Vaginal swab E. Coli Puerperal sepsis 41 YN N 5 Sputum PCP AIDS+ PCP 65 NY Y 7 Vaginal swab Bacteroids, E. Coli Puerperal sepsis 108 NN N 28 Tracheal suction Pseudomonas Aspiration Pneumonia 76 NY Y 9 Tracheal suction Pseudomonas Aspiration Pneumonia 102 NY Y 3 Sputum Pneumococci R. lower lobe Pneumonia 93 NY N 1 Sputum NLF bronchpneumonia 107 NY N 1 Urine Klebsiella Bronchopneumonia 121 NY N 7 blood Leptospira Leptospirosis 53 YY N 7 Sputum S. Aureus R. Lung abscess 42 YY Y 4 Urine Klebsiella UTI + Sepsis 95 YN N 5 Sputum Pneumococci R. lower lobe Pneumonia 57 YN N 30 Sputum Pseudomonas Bronchopneumonia+ ARDS 46 YN Y 7 blood Vivax Malaria Complicated Malaria 96 NN N 10 Pus S. Aureus Impetigo contagiosa 36 YN N 4 Sputum Klebsiella L. lower lobe Pneumonia 27 YN N 3 Urine E. Coli Acute Pyelonephritis 27 YN N 8 Sputum E. coli bronchopneumonia 37 YY N 3 Intraop fluid E. Coli Perforation Peritonitis 62 YN N 2 blood NG R. lower limb cellulitis 36 YY Y 3 Blood Brucella Brucellosis 98 NN N 3 Pus E. Coli Pyogenic Liver abscess 48 YN N 5 Sputum Pseudomonas Lobar pneumonia 44 YY N 6 blood NG Acute Cholecystitis 33 YN N 6 Sputum Pneumococci Bronchopneumonia + ARDS 18 YN N 4 Urine E. Coli UTI + Sepsis 48 YN N 4 Intraop fluid E. Coli Perforation Peritonitis 33 YN N 2 blood Falciparum malaria Complicated Malaria 26 YN N 14 Sputum Klebsiella Bronchopneumonia 39 YN N 4 Intraop fluid E. Coli Perforation Peritonitis 30 Y
