Dr Neeraj Goel

Sr. Consultant

Department of Clinical MicrobiologySir Ganga Ram Hospital

Resistance profile of MDROs in ICU:Quinolone: 80%

Amikacin: 75%

Cefaperazone sulbactum: 79%

Carbapenems: 79%

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.

Super BUGsMDR/Nosocomial

Gm +MRSA

Gm –Klebsiella

E.ColiPseudomonas

Acinetobacter

ESBLs

Association b/w antibiotic use and AMR

Autoregressive Integrated Moving Average Model

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

12 Steps to Prevent Antimicrobial

Resistance: Hospitalized Adults

Campaign to Prevent Antimicrobial Resistance in Healthcare Settings

12 Break the chain11 Isolate the pathogen

10 Stop treatment when cured9 Know when to say “no” to vanco

8 Treat infection, not colonization7 Treat infection, not contamination

6 Using Antibiogram5 Practice antimicrobial control

4 Access the experts3 Target the pathogen

2 Get the catheters out1 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 cultureseg., MRSA, VRE screening.

Repeat isolatesLowers 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

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

Drug E. coliPseud.

aeruginosaKleb. 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 62Levofloxacin 85 34 46 75

Cipro 85 56 46 75

Gentamicin 57 62

Tobramycin 58 87 86

Cotrimoxazole 57

Imipenem 77

0

10

20

30

40

50

60

70

80

90

100

Penicillin

Oxacillin

Clindamycin

Gentamicin

Vancomycin

% Resistance - S. aureus -- IPD

0

10

20

30

40

50

60

70

80

90

100

2010 2011 2012 2013 2014 2015 2016

Ward

ICU

% Vancomycin Resistance Enterococci spp. (IPD)

0

10

20

30

40

50

60

70

80

90

100

Ampicillin

Ceftriaxone

Gentamicin

Amikacin

Ciprofloxacin

Piperacillin + Tazobactum

Cefaperazone + Sulbactum

Imipenem

% Resisance - E.coli - Blood Isolates - IPD

0

10

20

30

40

50

60

70

80

90

100

Ceftriaxone

Gentamicin

Amikacin

Ciprofloxacin

Piperacillin + Tazobactum

Cefaperazone + Sulbactum

Imipenem

Colistin

% Resistance - Klebsiella - Blood Isolates - IPD

0

10

20

30

40

50

60

70

80

90

100

1999 2000 2001 2002 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Ampicillin

Ceftriaxone

Ceftazidime

Gentamicin

Amikacin

Ciprofloxacin

Piperacillin + Tazobactum

Cefaperazone + Sulbactum

Imipenem

Tigecycline

Colistin

0

10

20

30

40

50

60

70

80

90

100

Ceftazidime

Gentamicin

Netilmicin/Amikacin

Ciprofloxacin

Piperacillin +Tazobactum

Cefaperazone +Sulbactum

Imipenem

Colistin

% Resistance - Pseudomonas - Blood Isolates - IPD

Antibiotic trend analysis at SGRH 1999-2008

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

patterns.

Crit Care Med, 34: 1589-1596, 2006.

- Optimum Empirical Antibiotic Therapy

•If appropriate antibiotic

therapy in the 1st hr:

survival rates of 80 %

• Each of hour of delay in

institution of appropriate

therapy decreases

survival by 7%

Ampi Cefurox Ceftriax Ceftaz Cefep Aztreo Ampi+sulbactum

Pipera+tazobactum

Cefo+sulbctum

Quin Genta Amik Netil Erta Imi Coli

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

Identify the Five most sensitive antibiotics

Klebsiella spp.30%

Acinetobacter spp.17%

E.coli13%

Pseudomonas aeruginosa7%

Staph aureus6%

Enterobacter spp.5%

Burkholderia cepacia5%

Others17%

Klebsiella spp.

Acinetobacter spp.

E.coli

Pseudomonas aeruginosa

Staph aureus

Enterobacter spp.

Burkholderia cepacia

Others

Identify the Five most common pathogens

Blo

od S

team

Infe

cti

ons

(IC

U)

Hospital surveillance data

S. No Most common

pathogens

%

prevalence

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%)

Tool Kit for Blood culture- ICU

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

Health Care

Contact

Antibiotic Rx

History

Patients

Characteristics

No

No in last 90 days

Young – No co-

morbid conditions.

+ve

+ve in last 90 days

Elderly

Few Co-morbid

conditions.

Prolonged

Repeat multiple

antibiotics.

Immunocompromised,

or with many co-

morbid conditions.

Type 1 Type 2 Type 3

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 Lab Systems

WHONET

BacLink

Excel

Access

EpiInfo

Lab Instruments

Mysis

MEDITECH

ADBakt

MIC systems

Disk diffusion

readers

Data analysis

Data Conversion

LIS Server

Hospital

Information

systemInfection Control

Pharmacy

CONNECTIVITY

WORKFLOWWORKFLOW

INFORMATION

MANAGEMENT

PREVI Isola™BacT/ALERT®

VITEK® 2

VITEK® 2

VITEK® 2

Vitek-MS

Purchase

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 manhoursChances of error in entry, retrieval and calculation

2008: Speedminer Data entry and retrieval automated, manual calculation

Electronic data: No paper50 manhours to compile the dataManual calculations of dataChances of error due to calculations

2010: SGRH Protech software –No paper

0 manhoursData entry and retrieval automatedNo 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”

0

2

4

6

8

10

12

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16

'83-'87 '88-'92 '93-'97 '98-'02 '03-'07 '08-'12

To

tal

# N

ew

An

tib

acte

ria

l A

gen

ts

’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