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WHAT HAPPENED TO HCAP? APPROACHES TO APPROPRIATE THERAPY FOR PNEUMONIA ORIGINATING FROM THE COMMUNITY Karl Madaras-Kelly, Pharm.D., M.P.H.Professor, Idaho State University and Clinical Pharmacist, Boise Veterans Affairs Medical Center

OBJECTIVES

• Review the history of healthcare associated pneumonia (HCAP) as a definition and the implications on use of broad-spectrum antibiotics in the United States

• Discuss recent literature contradicting the utility of the HCAP definition as a predictor of multidrug resistant organisms in patients presenting to the hospital with pneumonia

• Outline alternative strategies to selection of empiric therapy in pneumonia based on pathogen-specific risk factors and the impact these may have on broad-spectrum antibiotic use

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BACKGROUND

“Some of the key recommendations and principles in this new, evidence-based guideline: HCAP is included in the spectrum of HAP and VAP, and patients with HCAP need therapy for MDR pathogens.”

Table 2(adapted): Presence of risk factors for HCAP:

Hospitalization for > 2 d in preceding 90 dNursing home or extended care residencyHome infusion therapy (including antibiotics)Chronic dialysis within 30 dHome wound care

Other MDR Risk Factors: 

Prior antibiotic use < 90 daysFamily member with MDRImmunosuppressive disease and/or therapy

“Most of the studies have focused on patients with VAP, but the committee extrapolated the relationship between risk factors and bacteriology to all patients with HAP, including those with HCAP.”

“Risk factors for colonization and infection with MDR pathogens are summarized in Table 2 (21, 43)”

Am J Respir Crit Care Med Vol 171. pp 388–416, 2005

BACKGROUND

Evidence:• “MDR pathogens are more commonly

isolated from patients with severe, chronic underlying disease, those with risk factors for HCAP, and patients with late-onset HAP or VAP (Level II) (9, 21, 22, 30, 31, 39, 40, 91).”

• “Elderly residents of long-term care facilities have been found to have a spectrum of pathogens that more closely resemble late-onset HAP and VAP (30, 31).”

• “In the United States, more than 50% of the ICU infections caused by S. aureus are with methicillin-resistant organisms (16, 33)”

Select References: 9. Ventilator-associated pneumonia. Am J Respir Crit Care Med 2002;165:867–903.

12. Nosocomial pneumonia: a multivariate analysis of risk and prognosis. Chest 1988;93:318–324.

16. Nosocomial infections in medical ICUs in the United States: National Nosocomial Infections Surveillance System. Crit Care Med 1999;27:887–892.

21. Ventilator-associated pneumonia caused by potentially drug-resistant bacteria. Am J Respir Crit Care Med 1998;157:531–539.

22. Impact of previous antimicrobial therapy on the etiology and outcome of ventilator associated pneumonia. Chest 1993;104:1230–1235.

30. Etiology of severe pneumonia in the very elderly. Am J Respir CritCare Med 2001;163:645–651.31. Impact of invasive strategy on management of antimicrobial treatment failure in institutionalized older people with severe pneumonia. Am J Respir Crit Care Med 2002;166:1038–1043.43. Health-care associated bloodstream infections: a change in thinking. Ann Intern Med 2002;137:850–851.

Am J Respir Crit Care Med Vol 171. pp 388–416, 2005

Unique guidelines: Levels of evidence, but no strength of recommendations

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BACKGROUND

• “This guideline is not meant to replace clinical judgment, but rather to give an organizational framework to patient management.”

Initial Empiric Therapy RecommendationsAntipseudomonal cephalosporin(ceftazidime, cefepime) ORAntipseudomonal carbapenem (imipenem, meropenem, doripenem) ORB-lactam/B-lactamase inhibitor( Pip./Taz , Ticarc/Clav) PLUSAntipseudomonal fluoroquinolone (Ciproflox, Levoflox)ORAminoglycoside ( Gentamicin, Tobramycin, Amikacin)PLUSLinezolid or vancomycin Consider addition of macrolide if Legionella suspected

“Patients with healthcare-related pneumonia should be treated for potentially drug-resistant organisms, regardless of when during the hospital stay the pneumonia begins (Level II) (43).”

Am J Respir Crit Care Med Vol 171. pp 388–416, 2005

CONSEQUENCES

The beginning (of the end)• Prospective observational analysis of

303 patients in 4 US based academic medical centers

• Educational campaign to implement 2005 ATS HAP/VAP/HCAP guidelines

Lancet Infect. Dis. 2011 Mar;11(3):181-9

Point: Despite increasing compliance w/ guideline concordant therapy mortality increased in the guideline concordant therapy group composed to those with non-compliant therapy.

Treatment outcomes, grouped by empirical treatment complianceCompliant Treatment

(n-129)Non-Compliant

Treatment (n=174)P value

Survival through day 28 (total population) 65% (3) 79% (4) 0.004

Baseline CPIS <7 68% (6) 80% (4) 0.063

Baseline CPIS > 63% (6) 78% (5) 0.037

Survival through day 28 (patients with Pseudomonas spp infection *)

55% (4) 82% (9) 0.064

Resource use, after pneumonia (days)

Mechanic ventilation support (total pop.) 8 (3-15) 9 (2‐18) 0.44

Length of stay in ICU (total pop.) 12 (7-22) 13 (5‐20) 0.57

Length of stay in hospital (total pop.) 16 (9-28) 17 (10‐26) 0.52

Mechanical ventilation support (survivors to day 14)

8 (2-18) 9 (2‐18) 0.81

Length of stay in ICU (survivors to day 14) 14 (7-23) 13 (5‐21) 0.15

Length of stay in hospital (survivors to day 14) 18 (11-32) 18 (10‐28 0.55

Data are Kaplan-Meler % (SE) estimates of survival or median (IQR, unless otherwise stated. ICU-Intensive-care unit. * We isolated Pseudomonas spp for 50 patients (33 patients in the compliant group and 17 in the non-compliant group)/

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CONSEQUENCES

The end…..

• Meta‐analysis of 24 studies (n= 22,456) only 4 quality studies

• MDR prevalence in HCAP: 2‐46%

• AUROC High quality studies 0.66 (0.62‐0.70)

• Mortality OR (+ 95% CI)  1.2 (0.9, 1.7)  

• NNT dependent on MDR prevalence (MRSA 4‐444, PSA 5‐330)

Clin. Inf. Dis, 2014;58(3):330-9

Organism PLR (+95% CI)

NLR (+95%CI)

Sens(+95% CI)

Spec(+95% CI)

AUROC(+95% CI)

All MDR 1.9 1.7,2.2)

0.6(0.5, 0.7)

54(52, 55)

71 (71, 77)

0.70 (0.69,0.71)

MRSA 2.0(1.7,2.2)

0.4(0.4, 0.6)

69(66, 72)

66 (65, 66)

0.74 (0.72,0.76)

PSA 1.4(1.3,1.5)

0.8(0.7,0.8)

43(41, 45)

66 (62, 67)

0.60 (0.58,0.62)

Enterobacteriaceae 1.7(1.5 ,1.8)

0.6(0.5,0.7)

52(49, 55)

68 (67, 68)

0.68 (0.66,0.70)

Key Point: The HCAP criteria have poor discriminatory ability to predict CAP-resistant organisms and heterogeneous populations are at risk for CAP-resistant organisms

CONSEQUENCES

2006-2010: 95,511 pneumonia hospitalizations

• 2006: Vancomycin and Pip/Tz. Both RXd 16%

• 2010: Vancomycin 31% Pip/Tz. 27 %

• MDR: MRSA reduced, PSA unchanged

• LRTI admit cultures: 34% unchanged

Key Point: Broad-spectrum antibiotic use doubled with no change in culturing rates or recovery of MDR

Clin. Inf. Dis. 2015 Nov 1;61(9):1403-10

Proportion of Admissions With MDR Cultured

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CONSEQUENCES

Other Implications:

• IDSA Guidelines committee changed guideline process

• Broad representation of interests• Structured PICO questions• Librarians create search

strategies and pull literature• Use GRADE criteria• Initial and subsequent grading• Consensus approach

Guideline Development and GRADE, CDC.gov

CONSEQUENCES

• “In light of the more recent data regarding the HCAP population, the panel anticipated that recommendations regarding coverage for MDR pathogens among community-dwelling patients who develop pneumonia would likely be based on validated risk factors for MDR pathogens, not solely on whether or not the patient had previous contacts with the healthcare system”

HCAP removed from HAP/VAP guidelines

“There is increasing evidence from a growing number of studies that many patients defined as havingHCAP are not at high risk for MDR pathogens [15–19]. Furthermore,although interaction with the healthcare system is potentially a risk for MDR pathogens, underlying patient characteristics are also important independent determinantsof risk for MDR pathogens”

Clin. Infect Dis., 2016;63:361-111

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CONSEQUENCES

Anticipation………

• Changes in practice based on primary literature have been ongoing for several years

• Release of new CAP guidelines have been significantly delayed

• National guidelines provide a organizational framework but all implementation is local

• What are considerations in selecting a path forward?

ALTERNATIVES

Consider:What is your patient population and how does it relate to existing literature?

• Severity of illness • What’s your community-onset pneumonia MDR prevalence?• Availability of prior colonization or infection microbiology results• Availability and timeliness of rapid diagnostics• Ability to influence empirical antibiotic choice • Ability to influence antibiotic change (de-escalation)

Options

Revert to old CAP Guideline

recommendations Make a diagnosis

Alternative epidemiological

models

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ALTERNATIVES

Revert to old CAP Guideline recommendations and wait it out

What do the CAP guidelines say?• “Pneumonia in non-ambulatory

residents of nursing homes and other long-term care facilities epidemiologically mirrors hospital-acquired pneumonia and should be treated according to the HCAP guidelines. However, certain other patients whose conditions are included in the designation of HCAP are better served by management in accordance with CAP guidelines with concern for specific pathogens.”

Clin. Infect. Dis, , 2007:44, S27-72

Guideline recommend obtaining LRTI cultures in a number of patient presentations where MDRO are possible (not all patients)

Anti-Pseudomonal Therapy

Patients with GNB on Gram Stain or structural lung disease (bronchiectasis or severe COPD w/ frequent exacerbations >> steroids / antibiotics)

Anti-MRSA Therapy

Gram positive cocci on Gram Stain, Lung abscess with Staph risk factors, chronic hemodialysis, recent influenza, antecedent antibiotics (especially FQ)

“The committee chose not to address CAP occurring in immunocompromised patients, including solid organ, bone marrow, or stem cell transplant recipients; patients receiving cancer chemotherapy or long-term (130 days) high-dose corticosteroid treatment; and patients with congenital or acquired immunodeficiency or those infected with HIV who have CD4 cell counts 350 cells/mm3, although many of these patients may be infected with the same microorganisms.”

ALTERNATIVES

About those Gram Stains……• Study to measure de-escalation rates and

determine variables associated with de-escalation in 119 VAMCs

• De-escalation rate 28.7% by day 4

Odds (95% CI) of de-escalation by day 4Culture positive admission 1.8 (1.4, 2.1)Obtaining blood cx 1.0 (0.9, 1.2)Obtaining LRTI cx 1.1 (1.0,1.2)

J. Antimicrob. Chemoth, 2016:71;539-46

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ALTERNATIVES

Clin. Microb. Infect, 2013;19:187-192; Clin. Infect. Dis, , 2007:44, S27-72

Potential risk factors

Anti-Pseudomonal Therapy

Patients with GNB on Gram Stain or structural lung disease (bronchiectasis or severe COPD w/ frequent exacerbations >> steroids / antibiotics)

Anti-MRSA Therapy

Gram positive cocci on Gram Stain, Lung abscess with Staph risk factors, chronic hemodialysis, recent influenza, antecedent antibiotics (especially FQ)

Key Point: Know your patient population and how it relates to guidelines (and/or prediction models)

How many patients have structural lung disease? -My facility ~ 46% COPD

Lung abscess with Staph risk factors -My facility ~ 3.4% complicated PNA

Chronic Hemodialysis - My facility ~1%

Recent influenza -My facility ~6%

Antecedent antibiotics - My facility ~34%

Question: What major Pseudomonas risk factor is missing? 2007 CAP guidelines likely not sufficient

ALTERNATIVES

Prospective observational cohort of 239 adults with CAP

• Nasopharyngeal swabs inferior to LRTI for identifying bacteria in CAP

• Excluded HAP patients• ED culture protocol: Blood, sputum,

urine antigens PLUS oropharyngeal swab

• rtPCR for Streptococcus pneumoniaeand Haemophilus influenzae

Key Points: • Increased yield compared to traditional cultures

• Sensitivity 75%, specificity 80%, PPV 65%, NPV 94%

• Great for bacteria and viruses in oropharynyx, potential for over-interpreting results (especially viral), MAY reduce dependence on obtaining LRTI culture

Eur J Clin Microbiol Infect Dis (2017) 36:529

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ALTERNATIVES

320 Patients admitted with CAP to two U.K. tertiary hospitals• Excluded HCAP, 12% admitted

to ICU• Mucopurulent sputum (96%),

endotracheal aspirates (4%)• Quantitative (10^5 cfu/ml)

MALDI TOF methods and real-time multiplex PCR for 26 pathogens

Clin Infect Dis, 2016; 62(7):817-23

• ID’d a pathogen in 87% compared ot 39% for culture

• PCR detected pathogens in 77.6 vs 32.1% if antibiotic received first

Key Points: Increased yield compared to prior studies

Still have to obtain sputumSensitivity vs specificity

Similar prospective studies need to be conducted WO exclusions

Pathogen N (%)Bacteria

Any bacteria 262 (81.1)

With ≥105 CFU/mL cutoff where quantified 231 (71.5)

Haemophilus influenzae 130 (40.2)Streptococcus pneumoniae 115 (35.6)Moraxella catarrhalis 44 (13.6)Escherichia coli 37 (11.5)Staphylococcus aureus 33 (10.2)Klebsiella pneumoniae 13 (4.0)Pseudomonas aeruginosa 9 (2.8)Mycoplasma pneumoniae 6 (1.9)Acinetobacter baumannii 3 (0.9)Legionella pneumophila 3 (0.9)Non-pneumophila Legionella spp. 3 (0.9)Chlamydophila psittaci 2 (0.6)Chlamydophila pneumoniae 0 (0)

VirusAny virus 98 (30.3)Rhinovirus 41 (12.7)Influenza 23 (7.1)

A 16 (5.0)B 7 (2.2)

Parainfluenza virus 11 (3.4)PIV-1 3 (0.9)PIV-2 6 (1.9)PIV-3 2 (0.6)

Coronavirus 9 (2.8)HCoV-OC43 6 (1.9)HCoV-NL63 2 (0.6)HCoV-229E 1 (0.3)HCoV-HKU1 0 (0)

Adenovirus 7 (2.2)Respiratory syncytial virus 4 (1.2)Human metapneumovirus 3 (0.9)

Any pathogena 280 (86.7)With ≥105 CFU/mL cutoff for bacteria where quantified 263 (81.1)

Table 2. Pathogen Detection in Patients with Community-Aquired Pneumonia Using Molecular Methods (n=323)

ALTERNATIVESSo why do I keep showing you diagnostic studies conducted in patients with CAP?

• Lack of existing studies in community-onset pneumonia beyond CAP populations

• Several commercial LRTI panels in development (LRTI sampling is a difficult nut to crack)

• May need a combination of sampling strategies (Blood + LRTI +/-oropharyngeal/nasopharyngeal)

• May need to combine epidemiological risk factors with upper airway sampling to target populations at risk for MDRO

• New technologies will be adopted by clinicians when it makes their life easier!

• Key Point: Embrace improvements in rapid diagnostics and strive to implement practices that facilitate determining an etiology of infection to improve antimicrobial selection

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ALTERNATIVESSo many prediction papers so little time to

discuss

Focus

• U.S. based studies• Cumulative risk instead of single predictor • Improved prediction over HCAP• Models with validation

Respiratory Medicine, 2015; 109:1-10

ALTERNATIVES

Background: Retrospective single-center (large urban tertiary care) analysis of 639 patients admitted with pneumonia (2003-5)

Methods: ICD-9 discharge diagnosis plus confirmation of S/S, chest x-ray. Required positive LRTI or blood culture. CAP-resistance endpoint, MRSA sub-model

Logistic regression with internal validation, Prediction score based on conversion of β- coefficients, optimal scoring assessed with AUROC

Results: ICU admit 45.4%, MDR prevalence 45.2%, MRSA 24.6%, Pseudomonas 18.8%, ESBL 7.3%

MDR Prediction model (AUROC=0.74)

Variable OR LCL UCLPrior Hospitalization 4.2 2.9 6.2Nursing Home 2.8 1.7 4.3LT Hemodialysis 2.1 2.1 4.3ICU admission 1.6 1.6 2.3

Arch Int Med, 2008; 168(20):2205-10

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ALTERNATIVES

Results (cont.)Points: Prior Hosp. = 4, NH admit = 3, LT.hemodialysis = 2, ICU admit =1

MRSA Prediction model Variable OR LCL UCLPrior Hospitalization 2.4 1.5 3.1Nursing Home 1.9 1.2 2.9ICU admission 1.8 1.2 2.6

Arch Int Med, 2008; 168(20):2205-10Only 33 patients had MDR and score <5

Points:

• Improvement over HCAP definition• Model worked well in this population

(high ICU, MDR rate)• Limited in scope to validating existing

HCAP criteria

ALTERNATIVES

Background: Retrospective single-center (same center) analysis of 977 patients admitted with pneumonia (2010)

Methods: ICD-9 discharge diagnosis plus confirmation of S/S, chest x-ray. Required positive LRTI or blood culture. Tested prior 10 point model

Results: ICU admit 53.1%, MDR prevalence 46.7%, MRSA 22.7%, Pseudomonas 19.1%,

MDR Prediction model (AUROC=0.71)Sens 88.6, Spec. 54.5, PPV 63.0, NPV 89.5, Accuracy 70.4

Clin. Infect. Dis., 2012;59(2:193-8

Key Points:

• Model worked well in this population again (high ICU, MDR rate)

• Limited number of exploratory variables

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ALTERNATIVESShorr et. Al. out-predicts HCAP criteria in different populations but no better than regionally developed scoring criteria

Aliberti et. Al.

Alberti score AUROC 0.89 (0.83, 0.96)Shorr score AUROC 0.89 (0.82, 0.96)HCAP criteria AUROC 0.66 (0.59, 0.73)

Am J Respir Crit Care Med, 2013;188(8), 985–995, Thorax, 2013;68(11):997-9

Variable PointsNo risk fx 0Comorbidity(COPD, abx<90d, immunosuppression, wound/IV care

0.5

Residence in long term care 3ICU admission 4LT Hemodialysis 5

Variable OR LCL UCLPrior Hospitalization 2.1 1.2 3.4Immunosuppression 2.3 1.1 5.1Abx < 90 d 2.7 1.5 4.0Acid suppression 2.2 1.4 3.6Tube feeding 2.4 1.2 5.0Non-ambulatory 2.5 1.4 4.3

Shindo et. Al.

Shindo score AUROC 0.79 (0.74, 0.84)Shorr score AUROC 0.71 (0.66, 0.77)Albert score AUROC 0.66 (0.61, 0.71)

ALTERNATIVES

Background: VA retrospective cohort of 375 culture-positive patients with HCAP. Developed MDR, MRSA, Pseudomonas models, compared to HCAP criteria

AUROC vs HCAP criteria

Cohort-derived (0.71 vs. 0.63)Cohort-derived MRSA (0.77 vs. 0.64)Cohort-derived Pseudomonas (0.77 vs. 0.68)

Key Points: Prior microbiology data improves models and pathogen specific models may be warranted. J Hosp.Med., 2012; 7(3):195-202

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ALTERNATIVES

Background: VA retrospective cohort of 38,473 admissions for pneumonia in 128 medical centers. Estimated adjusted probabilities from patient and hospital factors predicting coverage and detection of MRSA and Pseudomonas

Empiric antibiotics: MRSA (8-42%), PSA (13.9-44.0)Admit cultures: MRSA (0.5-3.6%), PSA (0.6-3.7%)Prior cultures: MRSA > 7.9%, PSA 11.9%

Key Points: Providing prior microbiology history at the time of antibiotic selection may better align coverage for resistant pathogens.

Infect Control Hosp Epidemiol 2017;38:937-944

ALTERNATIVES

Background: Retrospective 7 center derivation cohort in 200 culture-positive cases followed by prospective observational prediction cohort in 4 geographically distinct centers (200 cases each).

Methods: Review of literature to determine potential risk factors for evaluation. Logistic regression, probalistic score developed, optimal scoring assessed with AUROC, compared to other models

Results: MDR prevalence 25.0%, MRSA 11.7, Pseudomonas 6.1%

Respiratory Medicine, 2015; 109:1-10Antimicrob.Agents Chemoth., 2016;60(5):2652-63

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ALTERNATIVES

DRIP Score (14 points possible) Results ( cont.)

Drip Score >4 in Derivation Cohort

Sensitivity 0.76Specificity 0.91PPV 0.73NPV 0.92Accuracy 0.87Under-treatment 6.0%Overtreatment 7.0%

Antimicrob.Agents Chemoth., 2016;60(5):2652-63

Characteristic Number of Points

Major Risk Factors

Antibiotic use last 60 d 2

Residence in LTC 2

Tube Feeding 2

Prior infection with DRP 2

Minor Risk Factors

Prior hosp.<60 days 1

Chronic pulm disease 1

Poor functional status 1

Gastric acid suppres. 1

Wound care 1

MRSA colonization 1

ALTERNATIVES

DRIP Score Performance in Prospective Validation Cohort

Antimicrob.Agents Chemoth., 2016;60(5):2652-63

Points:

• Appears to be most accurate and validated prediction model to date

• Also performed better than Shorr or ShindoMRSA models

• What to do with DRIP scores of >0 but < 4 in severely ill patients?

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ALTERNATIVESMDR rate and predominant MDR organism

• HCAP developed from patient populations with high MDR prevalence

• High MDR rate: better PPV, lower NPV, less overtreatment with broad spectrum antibiotics

• Low MDR rate: poor PPV, good NPV resulting in overtreatment with broad spectrum antibiotics

Respiratory Medicine (2015) 109, 1e10

Key Point: Heterogeneous populations are at risk for CAP-resistant organisms and resistance rates vary substantially between facilities and regions

ALTERNATIVESExample: • In my facility we replaced HCAP order

menus in 2015-16

• Menus based on severity of illness AND specific risk factors for MRSA and Pseudomonas aeruginosa based in part on CAP guidelines

• Lower threshold for selecting BS therapy in ICU patients (sepsis) than non-ICU patients

• Menus facilitated obtaining diagnostics, assessing MDR factors, and selecting right antibiotics

• Retrospectively evaluated 105 consecutive Community-onset pneumonia cases with quality LRTI and positive blood cultures

• Collected data on menu risk factor criteria, drip score criteria, and provider practice

• Calculated predictive performance

Key Point: All implementation is local!

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ALTERNATIVES

• Actual prescribing during evaluation• Accuracy 56% (95% CI 47,66)• Unnecessary spectrum 39% (95% CI 30, 48)• Inadequate spectrum 5% (95% CI 1,9)

Example: Local predictive performance of DRIP score

Action:

• Replaced existing menus with DRIP score based menus and added a DRIP score calculator with predicative performance findings to menus

• For DRIP score >0 but <4 consider individual risk and severity of illness

Key Point: If adopting an existing prediction model, select model applicable to your population and validate the model in your patients

Table 5. Predictive performance of tools to identify MDR pathogens

Prediction Model

Cut-off Score

Sensitivity (95% CI)

Specificity(95% CI)

PPV(95% CI)

NPV(95% CI)

AUROC (95% CI)

Inadequate

Spectrum(95% CI)

Overall Accuracy(95% CI)

Unnecessary Spectrum(95% CI)

DRIP 4 0.70 (0.42, 0.98)

0.71 (0.61, 0.80)

0.20 (0.07, 0.33)

0.96 (0.91, 1.00)

0.84 (0.72, 0.96)

0.03 (0.00, 0.06)

0.70 (0.62, 0.79)

0.27 (0.18, 0.35)

CPRS, broad-

spectrum1 1.00 (1.00,

1.00)0.22 (0.14,

0.30)0.12 (0.05,

0.19)1.00 (1.00,

1.00)0.81 (0.68,

0.95)0.00 (0.00,

0.00)0.30 (0.21,

0.38)0.70 (0.62,

0.79)

ALTERNATIVES• Internal validation of external risk models may not be feasible in every practice setting

• In lieu of internal validation determine pneumonia‐specific % positive MDR and where (ICU versus non‐ICU) MDR coverage is prescribed

• Compare facility aggregate numbers to  those reported in risk scores and determine what adopting an existing risk score would do if applied to the local patient population

• Want to know if adopting an existing risk score model will improve ability to cover patients with MDR and not cover patients without

• Consider application of model to specific patients based on risk for poor outcome (severity of illness)

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KEY POINTSSummary

• HCAP criteria have poor discriminatory ability to predict CAP-resistant organisms except in patient populations with very high CAP-resistance rates

• Heterogeneous populations are at risk for CAP-resistant organisms and resistance rates vary substantially between facilities and regions

• Strive to implement practices that facilitate making a diagnosis to improve antimicrobial selection

• If adopting an existing prediction model, select one that is applicable to your population and validate the model in your patients if possible

• Guidelines provide a conceptual framework, but all implementation is local

DISCLAIMER

• The author has no conflicts of interest to disclose

• The views expressed in this presentation are solely those of the author and do not necessarily reflect the position or policy of Idaho State University or the United States Department of Veterans Affairs

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