A Lecture by Dr. Charmian Hufano, MD FPCP FPSMID during the 22nd PHICS Annual Convention

1. It More Fun Doing the Antibiogram:
Proper Analysis and Optimization of
Antibiotic Use using the Antibiogram
Ma. Charmian M. Hufano, MD, FPCP, FPSMID
Infectious Disease Specialist

2. Lecture Outline
• The importance of a hospital antibiogram
• How to create your hospital antibiogram
• How to translate the science of your hospital antibiogram in action

5. 5

6. 6
22 Sentinel sites in14 regions
of the Philippines
Antimicrobial Resistance
Surveillance Reference
Laboratory
ANNUAL REPORT
ANTIMICROBIAL RESISTANCE SURVEILLANCE PROGRAM
2013 DATA SUMMARY REPORT
ANTIMCROBIAL RESISTANCE SURVEILLANCE REFERENCE LABORATORY

7. Yearly resistance rates of
Staphylococcus aureus, ARSP, 2005-2014
7
http://www.ritm.gov.ph
33.5 37 35.6 36.1
46
54.3 52.7
56.6 53.2
60.3
0
20
40
60
80
100
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
%Resistance
Penicillin
Oxacillin
Vancomycin

8. Percent Resistance of Pseudomonas aeruginosa, ARSP,
2014
14.5 15.6
13.4 13.2
17.5
15.8
9.5
16.3 15.6
0
5
10
15
20
25
30
Pip/Tazobactam Ceftazidime Cefepime Aztreonam Imipenem Meropenem Amikacin Gentamin Ciprofloxacin
%Resistance
Antibiotics
n=3706 n=4108 n=3861 n=3119 n=3997 n=3725 n=3971 n=3892 n=3926

9. Pseudomonas aeruginosa MDR and possible XDR rates,
ARSP, 2014
Acinetobacter
baumannii
No. of Organisms % MDR % possible XDR
All isolates 4286 23% 18%
Blood culture isolates 259 35% 26%
2013 MDR Pseudomonas = 22%
2013 XDR Pseudomonas = 13%

10. Percentage resistance of urinary Escherichia coli from
outpatient versus inpatient, ARSP, 2014
Antimicrobial Outpatient Inpatient
Oral Agents N %R N %R
Ampicillin 971 79.8 1936 82.3
Co-amoxiclav 1084 18.5 2226 24.2
Cefuroxime 535 24.3 949 35.2
Ciprofloxacin 979 50.7 2073 43.1
Cotrimoxazole 1012 65.8 1966 68
Nitrofurantoin 945 6.6 1757 5.5

11. Percentage resistance of urinary Escherichia coli from
outpatient versus inpatient, ARSP, 2014
Antimicrobial Outpatient Inpatient
Intravenous Agents N %R N %R
Piperacillin/Tazobactam 1037 3.1 2078 6
Ceftriaxone 917 27.5 2007 38.2
Ertapenem 554 1.3 1300 2.8
Amikacin 941 2.2 1897 3.9
Legend: N=number tested; %R=percentage resistance; Outpatient=specimen taken from patients at the outpatient
Department or emergency room; Inpatient=specimen taken from patient admitted or hospitalized

12. MRSA Rates by Site, ARSP
2014
29
hicillin- resistant Staphylococcus aureus
SA)
e were 2,004 M RSA isolates report ed from the
P sentinel sit es for 2014. M ost of these iso-
were isolat ed from cutaneous and blood cul-
isolates. The overall cumulat ive M RSA rate
014 was at 60.3%. Sentinel sit e M RSA rat es
ed from as low as 24.8% (NKI, n= 137) to as
as 74.5% (LCP, n= 31). FIGURE 36 shows the
A rates by region.
hese 2014 M RSA isolates, 85% were from
mens taken from patients in the outpatient
rtment, emergency room and admissions
n t heir 1st
2 hospital days. When M RSA rates
analyzed by specimen type, 60% of all blood
es (n= 570) and 64.7% of all skin and soft tis-
solat es (n= 1,535) were methicillin-resist ant .
tance rat e of the M RSA isolates against avail-
agents for treat ment showed variable suscep-
y to available antimicrobial agent s as seen in
RE 35. Resistance rat es have increased signifi-
y for most of the antibiotics t est ed when
pared to 2013 rates: rifampin from 4% in 2013
% in 2014 (p value 0.0339); ciprofloxacin from
n 2013 to 10.5% in 2014 (p value 0.0017); co-
xazole from 18% in 2013 to 26.1% in 2014 (p
0.0001); clindamycin from 12% in 2013 to
% in 2014 (p value 0.0353); and tetracycline
8% in 2013 to 10.9% in 2014 (p value 0.0103).
2014 M RSA isolat es rat es of resistance did not
significantly against erythromycin, linezolid
vancomycin from reported rat es in 2013 (p
> 0.05).
Figure 36. M RSA rates by sentinel sit e region
MRSA rates by site, ARSP 2014

13. s. [7]
een-
iso-
pect).
test-
duc-
iso-
were
ESBL-
512
o the
d by
siella
from
, re-
FIGURE 50. Percentage of ESBL-suspect
(ceftazidime-resistant) Klebsiella species, ARSP,
2014
ARSP 2014

14. Why do we need hospital antibiograms?
• With increasing antimicrobial resistance worldwide, it is crucial to monitor
emerging trends in drug resistance at the local level to support clinical
decision making, infection-control interventions, and antimicrobial-resistance
containment strategies
• Several distinct approaches can be used in summarizing results from a
database of clinical isolates, but, unfortunately, results obtained using
different calculation algorithms may not necessarily be comparable.

15. Clinical Laboratory Standards Institute

16. Antibiogram
• Cumulative antimicrobial susceptibility test data summary.
• Report generated by analysis of results on insolates from a particular
institution(s) in a defined period of time that reflects the percentage of first
isolates (per patient) of a given species that is susceptible to each of the
antimicrobial agents routinely tested.
• Guide clinicians in the selection of initial empiric antimicrobial therapy for
infection

17. CLSI Recommendations
• Information System Design- computer application to analyze cumulative
AST data
• Integrated into LIS or system must have the capability to send data through a real-time
interface or to periodically export results to an analysis program
• Software must be versatile and flexible and have the ability to analyze data for a defined
period to generate cumulative statistics and line listings; and rem

18. WHONET is a free
Windows-based
database software
developed for the
management and
analysis of
microbiology
laboratory data with a
special focus on the
analysis of AST
results..

19. CLSI Recommendations
DATA VERIFICATION
• Only final, verified results should be included.
-Viridans streptococci resistant to penicillin
-Vancomycin-resistant Staphylococcus aureus

20. CLSI Recommendations
FACILITY
• Antibiogram reports should be institute specific.
FREQUENCY
• Analyze and report antibiogram data at least once a year.

21. CLSI Recommendations
ISOLATES
• Include only species with testing data for at least 30 isolates.
• Include only the 1st isolate of a given species per patient per
analysis period irrespective of body site, AST profile or other
phenotypic characteristics.
• Include diagnostic, not surveillance isolates.

22. CLSI Recommendations
ANTIMICROBIAL AGENTS
• Include results only for drugs that are routinely tested.
• AST results for antimicrobials tested against drug-resistant
strains are generally biased towards higher rates of AMR
• Results of supplemental drugs tested only from drug-resistant
pathogens are not included in to the antibiogram report.

23. CLSI Recommendations
CALCULATIONS
• Calculate percentage susceptibility. Do not include the
percentage of isolates with intermediate susceptibility.
• Perform calculations using the interpretive breakpoints and rules
current at the time of analysis. Analysis of historical data require
the storage of quantitative test measurements with reinterpretation
of results using interpretive criteria or breakpoints current at the
time of analysis.

24. Supplemental Analysis
• Streptococcus pneumoniae and reporting of meningitis and non-meningitis
breakpoints
FIGURE7. S. pneumoniae penicillin-resistance rates
by specimen type, ARSP, 2014
FIGURE8. Yearly resistance rates of S. pneumoniae,
isolates sen
for confirma
monest sero
were serogr
ing 64% o
serogroup/s
with penicill
trast, most
isolates we
comprising
seen in FIG
non-invasiv
FIGURE 9. D
isolates by s
CLSI M100; 2015
ARSP 2014 Annual Report. S. pneumoniae %R to penicillin

26. Supplemental Analysis
• Staphylococcus aureus- List %S for ALL and MRSA subset
11
22
9.1
14.6
26.1
10.9
0
5
10
15
20
25
30
Clindamycin Co-trimoxazole Tetracycline
Staphylococcus aureus and MRSA %R, ARSP 2014
S. aureus MRSA
ARSP Annual Report, 2014

27. Additional Data Stratification
By nursing unit or site of care
By organism’s resistance characteristics
By specimen type or infection site
By clinical service or patient population

28. Additional Data Stratification
By nursing unit or site of care
By organism’s resistance characteristics
By specimen type or infection site
By clinical service or patient population
-by patient location at time
that infection is suspected or
diagnosed
-e.g. ICU versus wards versus
OPD
-Antibiogram for specific data
set maybe used to develop
treatment algorithms specific
for patients at that particular
unit or site of infection

29. Staphylococcus aureus by Patient Location
CLSI M39-A3

30. Comparison of unit –specific and hospital-wide
antibiograms: potential implications for selection of
empirical antimicrobial therapy
SETTING: A 625-bed tertiary care medical center.
METHODS: Antimicrobial susceptibility results were collected
for all inpatient clinical bacterial isolates recovered over a 3-
year period; isolates were categorized by the hospital location of the patient
at the time of sampling and by the anatomic site from which the isolate was
recovered. Antibiograms from each unit were compiled for the most
commonly isolated organisms and were compared to the hospital-
wide antibiogram.
Binkley S etal. Infec Control Hosp Epidemiol 2006 Jul;27(7):682-7.

31. Comparison of unit –specific and hospital-wide
antibiograms: potential implications for selection of
empirical antimicrobial therapy
RESULTS: A total of 9,970 bacterial isolates were evaluated in this study,
including 2,646 enterococcal isolates, 2,806 S. aureus isolates, 2,795 E. coli isolates,
and 1,723 Pseudomonas aeruginosa isolates. The percentages of bacterial
isolates resistant to antimicrobials were significantly higher in the medical
ICU and surgical ICU than the hospital-wide antibiogram would have
predicted, whereas the percentages of isolates susceptible to antimicrobials
were significantly higher in the non-ICU units, compared with the hospital
overall. However, on general medicine units, the prevalence of susceptibility to
levofloxacin was significantly lower than that for the hospital overall.
Binkley S etal. Infec Control Hosp Epidemiol 2006 Jul;27(7):682-7.

32. Comparison of unit –specific and hospital-wide
antibiograms: potential implications for selection of
empirical antimicrobial therapy
CONCLUSIONS: Unit-specific antibiograms are important for making informed
decisions about empirical antimicrobial therapy, because the hospital-wide antibiogram
may mask important differences in susceptibility rates across different units. These
differences may have important implications for selecting the optimal empirical
antimicrobial therapy.
Binkley S etal. Infec Control Hosp Epidemiol 2006 Jul;27(7):682-7.

33. Additional Data Stratification
By nursing unit or site of care
By organism’s resistance characteristics
By specimen type or infection site
By clinical service or patient population
-data are segregated by
resistance characteristics of a
given organism
-Useful for MDROs

34. Staphylococcus aureus %S, CLSI M39-A3

35. Klebsiella pneumoniae %S, CLSI M39-A3

36. Additional Data Stratification
By nursing unit or site of care
By organism’s resistance characteristics
By specimen type or infection site
By clinical service or patient population
-by specimen type or infection
site (e.g. urine isolates, blood
isolates)

37. Urine Isolates from Inpatients and Outpatients
for Selected Uropathogens
CLSI M39-A3

38. Urine Isolates from Inpatients and Outpatients
for Selected Uropathogens
CLSI M39-A3

39. Additional Data Stratification
By nursing unit or site of care
By organism’s resistance characteristics
By specimen type or infection site
By clinical service or patient population
-by clinical service, medical or
surgical specialty or specific
patient population (e.g.
transplant, burn, pediatrics)

40. Isolates from All Sites for Selected Pathogens
for Burn Patients
CLSI M39-A3

41. Examining Percent Susceptible for
Combinations of Antimicrobial Agents
• For guiding empiric therapy of infections where the likely causative agent are
best treated with a combination of antimicrobial agents, it maybe useful to
examine the percentage of isolates susceptible to 1 or both drugs in relevant
combinations.
CLSI M39-A3

42. % SUSCEPTIBLE
No of
strains
CIP CTZ IPM TOB CTZ
&/
CIP
IMP
&/
CIP
CTZ
&/
TOB
IMP
&/
TOB
PAE 814 69 80 79 86 86 84 91 91
Pseudomonas aeruginosa susceptibility rates for monotherapy and select combination
drug therapy
CIP- ciprofloxacin; CTZ- ceftazidime; IPM- imipenem; TOB- tobramycin
CLSI M39-A3

43. Utility of a Combination Antibiogram for
Treating Pseudomonas aeruginosa
• A retrospective observational study at a Veterans Affairs (VA) hospital in the
Southwestern region of the U.S. was conducted.
• P. aeruginosa isolates were collected between January 2008 and February 2012
in hospitalized veterans.
• A total of 374 isolates were included, of which 61 (16%) were obtained from
the ICU.
Thurman L etal. Am Journal of Infec Ds 10(2):88-94,2014

44. Utility of a Combination Antibiogram for
Treating Pseudomonas aeruginosa
Susceptibility rates for monotherapy with a beta-lactam ranged from 83.7 to 90.6%.
Collectively, all P. aeruginosa isolates benefited in coverage with the addition of a
fluoroquinolone or an aminoglycoside to one of the beta-lactams considered for monotherapy
(p<0.01 for each comparison).
Monotherapy with a beta-lactam could be considered for mild to moderate wound infections
which had beta-lactam susceptibility rates greater than 90% and the addition of a
fluoroquinolone did not significantly extend the spectrum.
Combination susceptibility rates ranged from 89.0 to 99.2%. Dual therapy of a beta-lactam
with amikacin or tobramycin resulted in significantly better coverage than with a
fluoroquinolone (p<0.03 for all combinations).
Thurman L etal. Am Journal of Infec Ds 10(2):88-94,2014

45. Utility of a Combination Antibiogram for
Treating Pseudomonas aeruginosa
For severe infections dual therapy with tobramycin or amikacin may be preferred over
fluoroquinolones, but the risks versus benefits of aminoglycoside therapy must be weighed for
each patient.
In conclusion, combination antibiograms are useful for evaluating the treatment of P.
aeruginosa. Choosing the ideal antibiotic regimen ultimately deals with many factors and results
of this combination antibiogram are only specific to this institution.
Thurman L etal. Am Journal of Infec Ds 10(2):88-94,2014

46. CLSI M39-A3
Inclusive dates of
report
Name of Laboratory
Comments on Methods
List organisms
alphabetically, by
organism group and by
prevalence
Separate table for gram
+ and gram –
Number of organisms-
30 or more
Antibiotic names
spelled out or
abbreviations listed
%S; use dash (-) no
tested

47. Use of Antibiogram
• Only be used as a general guide for empirical therapy until such time that
specific antimicrobial susceptibility test results on a given patient’s isolates
become available.
• Other factors: the organism, the antimicrobial agent and the clinical context
• Distribution of the Report
• Pocket Guides
• Website application or PDF
• Educational lectures

48. CLSI: Limitations of Data, Data Analysis and
Data Presentation
• Culturing practices
• Biased by more frequent sampling of patients with treatment failure following prior
antibiotic therapy; and or prolonged medical histories or recent hospitalization
• Influence of small number of isolates
• Ways to improve guidance for antimicrobial therapy when # tested isolates is small:
• Combine data on organism from data collected over more than 12 months
• Combine data, when applicable, for more than1 species within a genus
• Combine data from several comparable institutions in a geographic area
• Providing data from published summaries and guides

49. CLSI: Limitations of Data, Data Analysis and
Data Presentation
• Comparing results of individual antimicrobial agent results
• Comparing antibiotic susceptibility tested against all specimens versus that tested only
for urine isolates
• Identification of new patterns of resistance
• When 1st isolate per patient is used in summaries, changes related to emergence of new
patterns of resistance maybe missed

50. Implementing an Antibiotic Stewardship Program:
Guidelines by the IDSA and the SHEA
• We suggest development of stratified antibiograms over solely relying on
non-stratified antibiograms to assist ASPs in developing guidelines for
empiric therapy (weak recommendation, low-quality evidence)
CID; Feb 2016

51. Summary
• Hospital antibiograms are useful tools that clinicians can use to guide empiric
antibiotic therapy.
• Guidelines to improve representation of true susceptibility rates of common
pathogens causing infections are provided by the CLSI.
• Translating and communicating the antibiogram data remains one of the key
strategies in improving rational antibiotic use.

52. • No declarations of competing interests
• Acknowledgement to the Antimicrobial Resistance Surveillance Reference
Laboratory and our partner sentinel sites