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Assessment of MDR risk: Focus on ESBL
Nuno Rocha Pereira
➤ Travel, accomodation and registatrion in meetings, workshops and congress
• MSD, Pfizer, ViiV Healthcare, Janssen
➤ Invited talks
• Pfizer
CONFLICTS OF INTEREST
BACKGROUND
➤ Antimicrobial resistance is a worldwide concern
➤ Burden among gram negatives increasing
➤ Most common mechanism of resistance among Gram
negatives is the production of β-lactamases
• ESBLs among the most important and are mostly
expressed by Enterobacteriaceae.
• ESBLs confer resistance to all β-lactams with the
exception of carbapenems and, in some selected
cases, beta-lactam/beta-lactamase inhibitors
• Commonly other resistance mechanisms coexist
Bassetti M et al. Expert Review of Anti-Infective Therapy 2016
http://dx.doi.org/10.1080/14787210.2017.1251840
BACKGROUND
BACKGROUND
ESBL IMPACT
➤ Increased likelihood of inadequate empirical coverage
➤ Independent predictor of impaired survival (higher mortality)
➤ Higher LOS
➤ Increased carbapenem exposure
➤ ESBL-EB bacteremia associated with higher mortality
• Inadequate empirical therapy
Freeman JT et al. International Journal of Infectious Diseases 2012 ; 16: e371-e374
Peralta et al. BMC Infectious Diseases 2012; 12:245
Barbier et al. J Antimicrob Chemother 2016; 71: 1088–1097
A VICIOUS CYCLE
Increasing resistance
(ESBL)
Broad spectrum antibiotics)
(Carbapenems)
Increasing resistance
(Carbapenemases)
Limited therapeutic options
CARBAPENEM RESISTANCE
A CLINICAL DILEMMA
Effective
antimicrobial therapy
Good use of
antimicrobials
A CLINICAL DILEMMA
Effective antimicrobial
therapy
Good use of
antimicrobials
Risk assessment Better outcomes
ESBL RISK ASSESSMENT
➤ Prior colonization/infection and risk of infection
➤ “Traditional” risk factors
➤ Risk scores and prediction rules
PRIOR COLONIZATION/INFECTION
➤ Utility of prior cultures in predicting antibiotic resistance of bloodstream
infections due to Gram-negative pathogens: a multicentre observational
cohort study
• 04/2010 – 03/2015; USA and Canada
• Inpatients with monomicrobial gram negative bacteremia
• Predict resistance with prior isolates:
MacFadden DR et al. Clinical Microbiology and Infection 2017;
http://dx.doi.org/10.1016/j.cmi.2017.07.032
ESBL COLONIZATION AND INFECTION
➤ Significance of Prior Digestive Colonization With ESBL Enterobacteriaceae in
Patients With VAP
• Retrospective cohort study (January 2006 – October 2013)
• Included patients with suspected VAP (clinical judgement)
• ESBL-EB rectal swab at admission and every week thereafter
Bruyère R et al. Critical Care Medicine 2016; 44(4):699–706
ESBL COLONIZATION AND INFECTION
➤ Significance of Prior Digestive Colonization With ESBL Enterobacteriaceae in
Patients With VAP
• ESBL-EB digestive colonization prior to VAP episode found in 40 cases (6,8%)
• ESBL-EB VAP: 40,0% (ESBL+) vs 0,7% (ESBL-) p < 0,01
• ESBL-EB rectal carriage can predict subsequent ESBL-EB infection
Sensitivity (%)
[95% CI]
Specificity (%)
[95% CI]
Positive
Predictive Value
(%)
[95% CI]
Negative
Predictive Value
(%)
[95% CI]
Positive LR
[95% CI]
Negative LR
[95% CI]
All VAP 85,0%
[62,1-96,8]
95,7%
[93,7-97,3]
41,5%
[26,3-57,9]
99,4%
[98,4-99,9]
19,8
[9,8-35,4]
0,15
[0,0-0,4]
Bruyère R et al. Critical Care Medicine 2016; 44(4):699–706
ESBL COLONIZATION AND INFECTION
➤ ICU Acquisition Rate, Risk Factors, and Clinical Significance of Digestive Tract
Colonization With ESBL Enterobacteriaceae: A Systematic Review and Meta-
Analysis
• 13 studies included >> 15 045 ICU patients
Detsis M et al. Critical Care Medicine 2017; 45(4):705–714
ESBL COLONIZATION AND INFECTION
➤ ICU Acquisition Rate, Risk Factors, and Clinical Significance of Digestive Tract
Colonization With ESBL Enterobacteriaceae: A Systematic Review and Meta-
Analysis
Detsis M et al. Critical Care Medicine 2017; 45(4):705–714
Sensitivity (%)
[95% CI]
Specificity (%)
[95% CI]
Positive LR
[95% CI]
Negative LR
[95% CI]
Studies
combined
95,1%
[54,7,1-99,7]
89,2%
[77,2-95,3]
8,80
[4,15-18,67]
0,055
[0,004-0,75]
ESBL COLONIZATION AND INFECTION
➤ Colonisation with ESBL Enterobacteriaceae and risk for infection among
patients with solid or haematological malignancy: a systematic review and
meta-analysis
• 10 studies included >> 2211 patients
Alevizakos M et al. International Journal of Antimicrobial Agents 2016; 48: 647–654
RISK FACTORS
Bassetti M et al. Expert Review of Anti-Infective Therapy 2016
http://dx.doi.org/10.1080/14787210.2017.1251840
RISK FACTORS
➤ Bloodstream infection with ESBL Enterobacteriaceae at a tertiary care hospital
in New Zealand: risk factors and outcome
• 01/05/2003 – 31/03/2007
• ESBL-EB bacteremia cases (n=44) / EB bacteremia controls (n=44)
• Risk factors (multivariate analysis):
o Known colonization with an ESBL-EB (OR 46,2)
o Exposure to 1st-generation cephalosporins (OR 12,3)
o Exposure to fluoroquinolones (OR 6,56
o Total inpatient days (OR 1,033 per admission day)
Freeman JT et al. International Journal of Infectious Diseases 2012 ; 16: e371-e374
RISK FACTORS ➤ Risk factors for bloodstream infection caused by ESBL producing Escherichia
coli and Klebsiella pneumoniae: A focus on antimicrobials including cefepime
➤ Retrospective case control study
➤ 12/2004 – 08/2009
• ESBL-E.coli or K.pneumoniae bacteremia cases (n=103) / E.coli or K.pneumoniae
bacteremia controls (n=103)
• Risk factors (multivariate analysis):
o Any tumor in the prior 5 years (OR 3,6); History of a cerebrovascular accident (OR
2,4)
o Dementia (OR 3,4); Low albumin (OR 9,5); Prior hospitalization (OR 3,2)
o Presence of an indwelling CVC (OR 8,0) or urinary catheter (OR 4,4)
o Exposure to antimicrobials (cefepime OR 15,3; Pip/taz OR 5,3; Linezolid OR 5,5)
Chopra T et al. American Journal of Infection Control 2015 ; 1-5
RISK SCORES
➤ Identifying Patients Harboring ESBL Enterobacteriaceae on Hospital
Admission: Derivation and Validation of a Scoring System
• Derivation cohort:
o 01/01/2008 – 31/12/2008; Catholic University Hospital, Rome
o Cases: Inpatients with at least one culture with ESBL-EB within 48h of
admission
o Two controls for each case (without culture positive for EB; matching by hospital
ward and admission month)
o 113 cases included (total number of patients included 339)
Tumbarello M et al. Antimicrobial Agents and Chemotherapy 2011; 55(7):3485–3490
RISK SCORES
➤ Identifying Patients Harboring ESBL Enterobacteriaceae on Hospital
Admission: Derivation and Validation of a Scoring System
• Validation cohort:
o 01/06/2009 – 31/12/2009; San Martino University Hospital (Genoa) or San
Giovanni Battista-Molinette Hospital (Turin)
o Four controls for each case
o 102 cases included (total number of patients included 510)
Tumbarello M et al. Antimicrobial Agents and Chemotherapy 2011; 55(7):3485–3490
RISK SCORES
➤ Identifying Patients Harboring ESBL Enterobacteriaceae on Hospital
Admission: Derivation and Validation of a Scoring System
Tumbarello M et al. Antimicrobial Agents and Chemotherapy 2011; 55(7):3485–3490
RISK SCORES
➤ Identifying Patients Harboring ESBL Enterobacteriaceae on Hospital
Admission: Derivation and Validation of a Scoring System
Tumbarello M et al. Antimicrobial Agents and Chemotherapy 2011; 55(7):3485–3490
RISK SCORES
➤ Identifying Patients Harboring ESBL Enterobacteriaceae on Hospital
Admission: Derivation and Validation of a Scoring System
• Limitations:
o Not applicable to other locations
o Needs validation against a different type of control population, i.e., hospitalized
patients suspected of infection
Combined
cohort Sensitivity (%) Specificity (%)
Positive
preditive value
(%)
Negative
preditive value
(%)
Score > 3 93% 62% 45% 97%
Score > 6 63% 95% 80% 88%
Tumbarello M et al. Antimicrobial Agents and Chemotherapy 2011; 55(7):3485–3490
RISK SCORES
➤ Utility of a Clinical Risk Factor Scoring Model in Predicting Infection with ESBL
Enterobacteriaceae on Hospital Admission
• Duke University Hospital
• 01/01/2008 – 31/12/2010
• Cases: Inpatients with at least one culture with ESBL-EB within 48h of admission
and clinical signs of active infection
• Three controls for each case (without culture positive for EB; matching by hospital
ward and admission month)
• 110 cases included (338 controls)
Johnson M et al. Infect Control Hosp Epidemiol 2013; 34(4): 385–392
RISK SCORES
➤ Utility of a Clinical Risk Factor Scoring Model in Predicting Infection with ESBL
Enterobacteriaceae on Hospital Admission
• Using Italian model: AUC ROC 0,88
• Using Duke model: AUC ROC 0,89
Johnson M et al. Infect Control Hosp Epidemiol 2013; 34(4): 385–392
RISK SCORES
➤ Utility of a Clinical Risk Factor Scoring Model in Predicting Infection with ESBL
Enterobacteriaceae on Hospital Admission
Johnson M et al. Infect Control Hosp Epidemiol 2013; 34(4): 385–392
Duke Score Sensitivity (%) Specificity (%)
Positive
preditive value
(%)
Negative
preditive value
(%)
Score > 4 87% 69% 48% 94%
Score > 8 58% 95% 79% 87%
RISK SCORES
➤ Clinical risk scoring system for predicting extended-spectrum β-lactamase-
producing Escherichia coli infection in hospitalized patients
• 01/2011 – 12/2014, Thailand
• Inpatients with positive cultures for E. coli
• Cases ESBL-EC (n=443); Controls non-ESBL-EC (n=367)
Kengkla K et al. Journal of Hospital Infection 2016, doi: 10.1016/j.jhin.2016.01.0072013
RISK SCORES
➤ Clinical risk scoring system for predicting extended-spectrum β-lactamase-
producing Escherichia coli infection in hospitalized patients
• AUC ROC 0,77
• Limitations: Only for E.coli, single centre.
Kengkla K et al. Journal of Hospital Infection 2016, doi: 10.1016/j.jhin.2016.01.0072013
Thailand Score Sensitivity (%) Specificity (%)
Positive
preditive value
(%)
Negative
preditive value
(%)
Score > 9 74% 66% 73% 68%
Score > 12 53% 90% 86% 61%
RISK SCORES ➤ Development and validation of the INCREMENT-ESBL predictive score for
mortality in patients with bloodstream infections due to ESBL
Enterobacteriaceae
• Large multinational cohort (37 hospitals in 11 countries)
• 01/2004 – 12/2013
• Included patients with ESBL-EB bacteremia
Palacios-Baena ZR et al. J Antimicrob Chemother 2017; doi:10.1093/jac/dkw513
RISK SCORES
➤ Development and validation of the INCREMENT-ESBL predictive score for
mortality in patients with bloodstream infections due to ESBL
Enterobacteriaceae
Palacios-Baena ZR et al. J Antimicrob Chemother 2017; doi:10.1093/jac/dkw513
RISK SCORES
➤ PREDICT
• Ongoing multinational study (aiming 20 000 participants)
• Validation of prediction rules to detect 3G cephalosporins resistance in bacteremic
patients
• Prediction rule to use at the beginning of empirical therapy
• Separate prediction rules for hospital and community acquired bacteremia
• Preliminary results in ECCMID 2018
Deelens JWT et al. PREDICT study protocol
DECISION TREE
➤ A Clinical Decision Tree to Predict Whether a Bacteremic Patient Is Infected
With an ESBL–Producing Organism
• 10/2008 – 03/2015
• Included 1288 patiens with bacteremia due to E.coli, K. pneumoniae or K. oxytoca
• 194 (15%) patients with ESBL + bacteremia
• 5 predictors for decision tree:
• Prior history of ESBL colonization or infection
• Presence of chronic indwelling vascular hardware
• Age (model-derived dichotomization at 43 years)
• Recent hospitalization in an ESBL high-burden region
• Total antibiotic exposure in the prior 6 months (model-derived dichotomization at 6 days)
Goodman KE et al. Clinical Infectious Diseases 2016;63(7):896–903
DECISION TREE
➤ A Clinical Decision Tree to Predict Whether a Bacteremic Patient Is Infected
With an ESBL–Producing Organism
Sensitivity (%) Specificity (%)
Positive
preditive value
(%)
Negative
preditive value
(%)
Decision
Tree 51% 99,1% 90,8% 91,9%
Goodman KE et al. Clinical Infectious Diseases 2016;63(7):896–903
RISK ASSESSMENT
➤ Several strategies available:
• Probabilities related to patient characteristics (comorbidities)
• Past culture results / information about colonizations
• Known risk factors for different bacteria and resistance
• Risk scores
• Decision support systems
➤ All strategies have limitations and pitfalls
CLINICAL JUDGEMENT
Clinical judgement
Comorbidities
Local epidemiology
“Individual epidemiology”
Illness severity
Risk factors
Risk scores
Decision support systems
Guidelines
Medicine is a science of
uncertainty and an art of
probability
Sir William Osler (1849-1919)
Thank you.
Nuno Rocha Pereira