Dr Neeraj Goel Sr. Consultant Department of Clinical Microbiology. Sir Ganga Ram Hospital

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Transcription:

Dr Neeraj Goel Sr. Consultant Department of Clinical Microbiology Sir Ganga Ram Hospital

Resistance profile of MDROs in ICU: Quinolone: 80% Amikacin: 75% Cefaperazone sulbactum: 79% Carbapenems: 79%

Super BUGs MDR/Nosocomial Gm + MRSA Gm Klebsiella E.Coli Pseudomonas Acinetobacter ESBLs Adapted from Infectious Diseases Society of American (IDSA). Available at http://www.idsociety.org/pa/idsa_paper4_final_web.pdf. Accessed July 2005; Cosgrove SE et al Arch Intern Med 2002;162:185 190; Ben-David D, Rubenstein E Curr Opin Infect Dis 2002;15:151 156; Colodner R et al Eur J Clin Microbiol Infect Dis 2004;23:163 167.

Association b/w antibiotic use and AMR

Autoregressive Integrated Moving Average Model

Significant correlation between carbapenem use and its resistance in A. baumannii

Campaign to Prevent Antimicrobial Resistance in Healthcare Settings 12 Steps to Prevent Antimicrobial Resistance: Hospitalized Adults 12 Break the chain 11 Isolate the pathogen 10 Stop treatment when cured 9 Know when to say no to vanco 8 Treat infection, not colonization 7 Treat infection, not contamination 6 Using Antibiogram 5 Practice antimicrobial control 4 Access the experts 3 Target the pathogen 2 Get the catheters out 1 Vaccinate Prevent Transmission Use Antimicrobials Wisely Diagnose & Treat Effectively Prevent Infections Fact: The prevalence of resistance can vary by locale, patient population, hospital unit & length of stay Actions: Know your local ABGM Know your patient population

Guidelines CDC - Campaign to Prevent Antimicrobial Resistance in Healthcare Settings IDSA/SHEA guidelines on Antimicrobial Stewardship (2007) JCI standards (IM.4/ IM.8) The hospital collects and analyzes aggregate data to support patient care and operations Recommends providing Antibiogram to the clinicians as mandatory to control the spread of MDRO

Definition Report generated by analysis of isolates from a particular institute in a defined period of time that reflects the percentage susceptibility to each of the antimicrobial agents routinely tested

Pre-2000: No consistent guidelines - Diversity in calculation algorithims - Poor comparability of data b/w institutes First version released in 2000 (M-39P)

CLSI. Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data. M39-2A, 2005

Data should be analyzed annually If there are large number of isolates then it can be done 6 monthly.

Number of Isolates Minimum no of isolates: 30 Adequate numbers is required for statistically meaningful data. N= 10 Sensitivity= 90% 95% CI= 55%-100% N= 100 Sensitivity= 90% 95% CI= 88%-92% If < 30 isolates: Acceptable to include isolates over a longer period. Report only % susceptibility Clinicians: focus on likelihood of a successful response Microbiologists: % R is more important Focus on changing trends of resistance IS results should be reported as R

Location: OPD, WARD, ICU OPD data excludes the community data Sensitivity of A. baumannii in blood to IMP is 20% ICU vs 43% in wards Specimen type Blood, urine, respiratory tract, pus and fluids Organism type GPC GNB

Surveillance/ screening cultures eg., MRSA, VRE screening. Repeat isolates Lowers the % susceptibility as MDROs are more often from: Patients with longer hospital stays Patients on multiple antibiotics Examples: - 6 year period study on S. aureus 1 MRSA contributed 39% duplicate (1.90 mean ratio). MSSA contributed 23% duplicates (1.35 mean ratio) - 4 years study on P. aeruginosa % sensitivity 2 All isolates included Repeat isolates excluded Imipenem 70% 80% Ceftazidime 56% 69% Ciprofloxacin 67% 74% Gentamicin 72% 84% 1. Horvat RTet al. J Clin Microbiol 2003;41:4611-16 2. Wilkinson ST et al. Presented at the annual meeting of the American College of Clinical Pharmacy, San Francisco, CA, October 23-26, 2005

Patient based (recommended by M 39,CLSI) First isolate per patient irrespective of the site. Fewer assumptions Simpler calculations Eliminates maximum number of isolates

Description of exact collection period Use of Generic names of antimicrobials Utilization of dash to describe susceptibility data not reported

1. Vancomycin susceptibility <100% for S. aureus / Strept. pneumoniae 2. Isolates of Enterococcus spp. tested against cephalosporin or cotrimoxazole 3. Imipenem susceptibility for Stenotrophomonas maltophilia 4. Ampicillin susceptibility in Kleb. pneumoniae 5. Sudden changes in the sensitivity patterns. JCM. Nationwide ABGM analysis using NCCLS M39-A Guidelines. Jun2005:43(6);2629-33

Prescribers, Infection Control, pharmacy & microbiology personnel Format Pocket guides Laminated cards Printed newsletters Website CLSI M39-A2

Online from May 2002 http://www.sgrh.com Publication Microbiology NL

Data of your own hospital is needed

Drug E. coli Pseud. aeruginosa Kleb. pnuemo. Proteus mirabilis Enterob. cloacae Serratia marcescens Enterob. aerogenes Ampicillin 63 49 Amp-Sul 64 75 Pip-Tzp 59 83 Ceftriaxone 65 Ceftazidime 71 68 89 Cefipime 62 Levofloxacin 85 34 46 75 Cipro 85 56 46 75 Gentamicin 57 62 Tobramycin 58 87 86 Cotrimoxazole 57 Imipenem 77 Green = susceptibility increased by greater than 10% during the study period Red = susceptibility decreased by greater than 10%, Yellow = change less than 10% but clinically significant resistance exist

% Resistance - S. aureus -- IPD 100 90 80 70 Penicillin Oxacillin 60 Clindamycin 50 40 Gentamicin 30 Vancomycin 20 10 0

% Vancomycin Resistance Enterococci spp. (IPD) 100 90 80 Ward 70 60 ICU 50 40 30 20 10 0 2010 2011 2012 2013 2014 2015 2016

% Resisance - E.coli - Blood Isolates - IPD 100 90 Ampicillin 80 70 60 Ceftriaxone Gentamicin 50 Amikacin 40 30 Ciprofloxacin Piperacillin + Tazobactum 20 10 0 Cefaperazone + Sulbactum Imipenem

% Resistance - Klebsiella - Blood Isolates - IPD 100 90 80 70 60 50 40 30 20 10 Ceftriaxone Gentamicin Amikacin Ciprofloxacin Piperacillin + Tazobactum Cefaperazone + Sulbactum Imipenem Colistin 0

100 90 80 70 Ampicillin Ceftriaxone Ceftazidime Gentamicin 60 Amikacin 50 40 Ciprofloxacin Piperacillin + Tazobactum Cefaperazone + Sulbactum 30 20 Imipenem Tigecycline 10 Colistin 0 1999 2000 2001 2002 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

% Resistance - Pseudomonas - Blood Isolates - IPD 100 90 Ceftazidime 80 Gentamicin 70 60 50 40 30 20 Netilmicin/Amikacin Ciprofloxacin Piperacillin + Tazobactum Cefaperazone + Sulbactum Imipenem 10 Colistin 0

Antibiotic trend analysis at SGRH 1999-2008

Antibiogram: In formulating empirical antibiotic policy Incorporates local microbiology and resistance patterns.

- Optimum Empirical Antibiotic Therapy If appropriate antibiotic therapy in the 1 st hr: survival rates of 80 % Each of hour of delay in institution of appropriate therapy decreases survival by 7% Crit Care Med, 34: 1589-1596, 2006.

Blood Steam Infections (ICU) Identify the Five most common pathogens Burkholderia cepacia 5% Enterobacter spp. 5% Staph aureus 6% Pseudomonas aeruginosa 7% Others 17% E.coli 13% Klebsiella spp. 30% Acinetobacter spp. 17% Klebsiella spp. Acinetobacter spp. E.coli Pseudomonas aeruginosa Staph aureus Enterobacter spp. Burkholderia cepacia Others Identify the Five most sensitive antibiotics Ampi Cefurox Ceftriax Ceftaz Cefep Aztreo Ampi+s Pipera+ Cefo+sul Quin Genta Amik Netil Erta Imi Coli ulbactutazobac bctum m tum Klebsiella spp. 10 11 19 12 18 21 21 22 25 22 21 21 87 Acinetobacter spp. 2 8 0 18 8 12 16 10 21 50 14 96 E.coli 12 12 12 29 12 50 50 12 48 76 72 64 63 98 P. aeruginosa 71 71 38 67 75 74 71 71 73 67 100 Enterobacter spp. 20 41 47 47 53 65 63 71 82 92 71 72 88

S. No Most common pathogens Tool Kit for Blood culture- ICU % prevalence Hospital surveillance data Most sensitive antibiotics 1 Klebsiella spp. 30% Colistin (87%), Amikacin(25%), Imipenem (22%), Netilmicin (22%), Cefoperazone+sulbactum (21%) 2 Acineobacter spp. 16% Colistin (96%), Netilmicin (50%), Amikacin (21%), Ampicillin+sulbactum (18%),Imipenem(14%) 3 E.coli 12% Colistin (98%), Amikacin (76%), Netilmicin (72%), Ertapenem (64%), Imipenem / Meropenem (63%) 4 P. aeruginosa 7% Colistin (100%), Imipenem (75%), Quinolones (74%), Netilmicin (73%), Ceftazidime (71%) 5 Staph aureus 6% Glycopeptide (100%), Linezolid (100%), Daptomycin (100%), Clindamycin (44%), Gentamicin (44%) Note: Cut off value to be used as empiric antibiotic is 80% *Choices written in red have sensitivity less than 80% Preferably Use Colistin as reserved drug, not as empiric

In the same way Tool kit can be made for : BSI (Ward and ICU) UTI (Ward and ICU) SSTI (Ward and ICU) Pneumonia (Ward and ICU) IAI (Ward and ICU)

The risk stratification is based on 3 factors: 1) Contact with Health Care System 2) Prior use of antibiotic 3) Patient Characteristics

Type 1 Type 2 Type 3 Health Care Contact No +ve Prolonged Antibiotic Rx History No in last 90 days +ve in last 90 days Repeat multiple antibiotics. Patients Characteristics Young No comorbid conditions. Elderly Few Co-morbid conditions. Immunocompromised, or with many comorbid conditions. Causative Pathogen could be ESBL+/- Susceptible to Common narrow spectrum antibiotics ESBLs +/MRSA CRE / MDR Pseudomonas /Acinetobacter+/- VRE

Antimicrobial resistance? (MRSA, VRE, ESBL, CRE) Antimicrobial survellance? Antimicrobial use? If the answer is NO ----- Information systems are not available to retrieve the data automatically.

Software developed by Thomas O Brien, Boston John Stelling, WHO Goals Enhanced local use of lab data and analysis Promote collaboration through exchange of data between national and international networks

A Microbiology Data Management Tool

In-built mechanism for expert analysis of antimicrobial agents Customise locations OPD / hospital wards / ICUs >2000 pathogens >85 specimens Methods of AST Disk Diffusion / Etest / MIC Windows version; 18 languages

Comp Software Excel Access EpiInfo Lab Systems Mysis MEDITECH ADBakt Lab Instruments MIC systems Disk diffusion readers BacLink Data Conversion WHONET Data analysis

Hospital Information system Infection Control LIS Server Pharmacy INFORMATION MANAGEMENT WORKFLOW WORKFLOW Purchase CONNECTIVITY VITEK 2 BacT/ALERT PREVI Isola Vitek-MS VITEK 2 VITEK 2

Prodigious software Manual Entry, retrieval and calculation

Speedminer Automated entry and retrieval Manual calculation

SGRH is publishing microbiology newsletter since: 1995 1998: Manual software (Foxpro) Manual data entry, retrieval, calculations > 2000 sheets of paper > 1000 manhours Chances of error in entry, retrieval and calculation 2008: Speedminer Data entry and retrieval automated, manual calculation Electronic data: No paper 50 manhours to compile the data Manual calculations of data Chances of error due to calculations 2010: SGRH Protech software No paper 0 manhours Data entry and retrieval automated No errors

Increasing prevalence of AMR Antibiotics should be conserved Antibiogram Prepared according to CLSI document Helps in Formulating in antibiotic policy AMR surveillance Detection of new AMR IT support is essential for making ABG

If you cannot measure, you cannot manage. If you cannot manage, you can not improve. We measure what we value. Let us value our data and start measuring it

Paradigm for empiric therapy: In Early, Hit Hard, Out Early

Total # New Antibacterial Agents 16 14 12 10 8 6 4 2 0 '83-'87 '88-'92 '93-'97 '98-'02 '03-'07 '08-'12 83-87

1. Annual reporting of results 2. Report results in percent susceptible (Pen & Strept. pneumo) 3. Only results from first isolates/patient; duplicate isolate notification 4. Exclude surveillance isolates 5. Number of isolates for each organism Best to report for bacteria with >30 isolates (earlier 10 isolates) Organisms morphological grouping 6. Description of exact collection period 7. Use of Generic names of antimicrobials CLSI. Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data. M39-2A, 2005

PAN RESISTANT BACTERIA