Transcript Document

Emergence of Antimicrobial
Resistance
Ebbing Lautenbach, MD, MPH
Assistant Professor of Medicine and Epidemiology
Associate Hospital Epidemiologist, Hospital of the
University of Pennsylvania
Center for Clinical Epidemiology & Biostatistics
University of Pennsylvania School of Medicine
PENN
Outline
• Recent trends in emerging antibiotic
resistance
• Epidemiology of resistance
• Clinical Impact on resistance
• Strategies to curb further emergence of
resistance
Outline
• Recent trends in emerging antibiotic
resistance
• Epidemiology of resistance
• Clinical Impact on resistance
• Strategies to curb further emergence of
resistance
Emergence of Gram + Resistance: US
100
1980 to 1999
Percent of Pathogens Resistant to Antibiotics
90
80
70
MRSE
60
MRSA
50
40
NPSP
30
VRE
20
10
0
1975
VISA VTSP LRSA VRSA
1980
1985
1990
1995
1997
Adapted from Thronsberry C. et al. 38th ICAAC, 1998; San Diego, Calif. Abstract E22
MMWR Morb Mortal Wkly Rep. 1997;46(27):624-636
2000
2002
Emergence of Gram - Resistance
25
% organisms resistant
20
FQ-R P. aeruginosa
15
10
Ceftaz-R K. pneumoniae
FQ-R E. coli
5
0
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000
New Agents with Expanded in Vitro
Gram-Positive Activity
[Glycopeptides
– Balhimycin
– HelvecardinA
– HelvecardinB
– MDL62208
– MDL62211
– MDL62476 (A40926)
– MDL63042
– MDL63166
– MDL63246
– LY333328
[Quinolones
– Trovafloxacin
– Clinafloxacin
– Gatifloxacin
– Moxifloxacin
– DU 6859
– ABT 719
[Lipoglycopeptides
– Ramoplanin
[Lipopeptides
– Daptomycin
[Everninomycins
– SCH27899
[Streptogramins
– Quinupristin/Dalfopristin
[Ketolides
– RU64004
– RU66647
[Oxazolidinones
– U100592
– Linezolid
[Glycylcyclines
– DMG-DMDOT
– DMG-MINO
New Agents with Expanded
Gram Negative Activity
Trends in Development of New Antibacterials
Total # New Antibacterial Agents
18
*R2 = 0.99
16
14
12
10
8
6
4
2
0
1983-1987
1988-1992
1993-1997
1998-2002
*p = 0.007 by linear regression
New antibacterial agent  new molecular entity (NME)
with antimicrobial properties, administered for systemic
infection; topical agents, immunomodulators excluded
Edwards J, ICAAC, 2003
Potential Reasons for Pharmaceutical Company Shifts
Away From Anti-infective Development
•Shift in demographics of population to elderly
•Need for treatment of chronic diseases
•Antibiotics become auto-obsolete
•Thought leaders advocating conservative use
•Increasing standards for efficacy and safety evaluation
•Increasingly complex patients in clinical trials
•Significantly increased costs in clinical trials
•Attractive to develop agents used for life of patients
Edwards J, ICAAC, 2003
Pharmaceutical R&D : 15 largest by revenue
Table 5. Anti-bacterial NMEs vs. Others
Indication
#NME
Lifestyle Drugs
Anxiety/Depression
Bladder Hyperactivity
GERD/Irritable Bowel Syndrome
Obesity
Impotence
Smoking Cessation
Insomnia
Migraine
Restless Leg Syndrome
42
12
8
7
4
4
2
2
1
1
Osteoporosis
8
Dementia
7
Anti-bacterials
5
Outline
• Recent trends in emerging antibiotic
resistance
• Epidemiology of resistance
• Clinical Impact on resistance
• Strategies to curb further emergence of
resistance
Outline
• Recent trends in emerging antibiotic resistance
• Epidemiology of resistance
– 2 examples
• Fluoroquinolone resistance
• Vancomycin-resistant enterococci
• Clinical Impact on resistance
• Strategies to curb further emergence of
resistance
Importance of FQ Resistance
•One of the most commonly used antibiotic classes1,2
•Most common antibiotic used in nursing homes3
•
•
•
•
Broad spectrum
Oral bioavailability
Long half-life
Well tolerated
1. Thomson, J Antimicrob Chemother, 1994
2. Lee, Am J Infect Control, 1998
3. Steinman, Ann Intern Med, 2003
Quinolones
• DNA Gyrase
–Supercoiling
–4 subunits
• 2 A subunits (gyrA gene)
• 2 B subunits (gyrB gene)
DNA gyrase (B subunit)
• Topoisomerase IV
–Acts in terminal stages of DNA replication
–Separates newly replicated daughter strands
–2 subunits
• ParC (GrlA in S. aureus)
• ParE (GrlB in S. aureus)
Trends in FQ Resistance
Surveillance study
GN bacilli
ICUs from 43 states
1994 – 2000
35,790 isolates
Cipro susceptibility
decreased from
86% to 76%
No difference across:
teaching vs non-teaching
>500 beds vs < 500 beds
Neuhauser MM, JAMA 2003;289:885
FQ Resistance vs FQ Use
PA (r=0.976; p<0.001)
GNB (r=0.891; p<0.001)
Neuhauser MM, JAMA 2003;289:885
FQR-EC and FQ Use
7
100
90
6
E. coli (r = 0.79; p = 0.002)
% FQ Resistance
5
70
60
4
50
3
40
30
2
DDD/1000 patient-days
80
20
1
10
0
0
1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
Lautenbach, SHEA, 2002
FQR-EC and the Dow Jones IA
7
6
12000
E. coli (r=.96; p<.001)
10000
8000
4
6000
3
4000
2
2000
1
0
0
1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
DJIA
% FQ Resistance
5
Risk Factors for Nosocomial FQ
Resistance in E. coli and K. pneumoniae
• Case-control study (1/1/98 – 6/30/99)
• Sites
– Hospital of the Univ. of Penn (HUP)
– Presbyterian Medical Center (PMC)
• Subjects identified through Clinical Micro Lab at HUP
• Study subjects
– 123 cases (FQ-resistant)
– 70 controls (FQ-susceptible)
• Review of inpatient medical records
Lautenbach, Arch Intern Med 2002;162:2469
Multivariable Model
Variable
Unadj OR
Adj OR (95%CI)
FQ Use
4.24
5.25 (1.81, 15.26)
LTCF
4.71
3.65 (1.64, 8.15)
Aminoglycoside Use
5.08
8.86 (1.71, 45.99)
Age
1.03 (1.01, 1.06)
Sex
1.83
2.11 (0.97, 4.56)
Hospital
0.33
0.52 (0.24, 1.13)
Organism (KP)
0.77
0.65 (0.27, 1.57)
Lautenbach, Arch Intern Med 2002;162:2469
Outline
• Recent trends in emerging antibiotic resistance
• Epidemiology of resistance
– 2 examples
• Fluoroquinolone resistance
• Vancomycin-resistant enterococci
• Clinical Impact on resistance
• Strategies to curb further emergence of
resistance
Importance of Enterococci
• 3rd most common hospital pathogen
– 10-12% of all nosocomial infections
• 3rd most common cause of BSI
– 3-4 per 10,000 discharges
• 1980s: incidence of enterococcal
bacteremia in teaching hospitals
increased up to 197% 1
1. NNIS, Am J Med 1991;91(suppl 3B):86S
Emergence of VRE
• First isolated in vitro in 1969 1
• Described clinically in 1988 2,3
• Mechanism of resistance
– Alteration of cell wall precursors
– Several resistance phenotypes
• VanA and VanB most clinically
significant
1. Toala, Am J Med Sci 1969;258:416
2. Leclercq, NEJM 1988;319:157
3. Uttley, Lancet 1988;1:57
Progression of Vancomycin
Resistance: Enterococci
Resistant isolates (%)
30
25
20
Non-ICU
15
ICU
10
5
0
1989
90
91
92
93
94
95
96
97
98
99*
Martone WJ. Infect Control Hosp Epidemiol. 1998;19:539-545.
NNIS Antimicrobial Resistance Surveillance Report. 1999.
*through June 1999
(www.cdCgov/ncidod/hip/NNIS/AR_Surv1198.htm).
Risk Factors:
An Exhaustive (ing) List
•
•
•
•
•
•
•
•
•
•
•
Age
Duration of hospitalization
ICU admission
Renal insufficiency
Immunosuppression
Neutropenia
Hematologic malignancy
Solid organ transplant
Bone marrow transplant
AIDS
Prior Surgery
• Antibiotics - General
– Number / Duration
• Antibiotics - Specific
– Almost all implicated
• Diarrhea / C. difficile
• Central venous catheter
• Urinary catheter
• Prior Colonization
• Exposure to VRE source
– VRE-infected patient
– Inanimate Object
– Health Care Worker
Risk factors for VRE (HUP)
• Case control study (1/1/93 - 12/31/95); HUP
• 260 cases enterococcal bacteremia
– 72 VRE
Risk factor
Vancomycin use
Renal insufficiency
Neutropenia
OR (95%CI)
3.0 (1.4,6.4)
4.4 (2.0,9.7)
6.3 (1.5,26.7)
p value
.005
<.001
.013
Lautenbach, Infect Control Hosp Epidemiol, 1999;20:318
VRE Risk Factors
Author/Year
Journal
Population
#VRE
pts
Cont
grp
Edmond ‘95
CID
Morris ’95
Ann Int Med
Shay ‘95
JID
Papanicolaou ’96
CID
Linden ‘96
CID
Dahms ‘98
Arch Surg
Lucas ‘98
CID
Stosor ‘98
Arch Int Med
Lautenbach ‘99
ICHE
Bhavnani ’00
Diag Micro Inf Dis
Oncology
11
SICU
20
Hosp-wide
46
Liver txp
32
Liver txp
Inf
Site
MV
Anal
Risk Factors
Onc pts BSI
no
SICU
pts
VSE
Mult
yes
BSI
yes
Mult
yes
54
OLT
pts
VSE
BSI
no
Anaerobic agent use,
VRE GI colonization
Vanc use, Cipro use,
APACHE, abx-days
APACHE, Vanc use,
Heme malignancy
Surgical re-exploration,
Prolonged ICU stay
Length of stay
Surgery
32
VSE
Mult
yes
Hosp-wide
93
VSE
BSI
yes
Hosp-wide
21
VSE
BSI
no
Hosp-wide
72
VSE
BSI
yes
Hosp-Wide
150
VSE
BSI
yes
3rd Gen Ceph use,
Vanc use
Length of stay, CVC,
White race, Surgery
Vanc use, Urine cath,
Length of stay, AG use
Abx-days, Renal insuff
Vanc use, Neutropenia
AIDS, Drug abuse, Vanc
use, Liver Transplant
Risk Factors:
Modifiable Variables
•
•
•
•
•
•
•
•
•
•
•
Age
Duration of hospitalization
ICU admission
Renal insufficiency
Immunosuppression
Neutropenia
Hematologic malignancy
Solid organ transplant
Bone marrow transplant
AIDS
Prior Surgery
• Antibiotics - General
– Number / Duration
• Antibiotics - Specific
– Almost all implicated
• Diarrhea / C. difficile
• Central venous catheter
• Urinary catheter
• Prior Colonization
• Exposure to VRE source
– VRE-infected patient
– Inanimate Object
– Health Care Worker
Exposure to VRE Source
• To develop VRE infection, one must first
be exposed to the organism
• Extent of exposure is related to other
risk factors:
– Duration of hospitalization
– ICU admission
– Age
– Greater severity of illness
– Indwelling devices
Sources of VRE Acquisition
• VRE-infected patients
• “Colonization pressure” 1
• Inanimate objects
Gowns, Bed linens, Cabinets, ECG wires,
Floors, etc.
• Room contamination
• > 50% of rooms may become contaminated
• May remain viable up to several months
• Healthcare workers?
1. Bonten, Arch Intern Med 1998;158:1127
Outline
• Recent trends in emerging antibiotic
resistance
• Epidemiology of resistance
• Clinical impact on resistance
• Strategies to curb further emergence of
resistance
Impact of Antimicrobial Resistance
• Increased morbidity / mortality 1,2
• Increased cost
– Estimated annual excess hospital
costs in the United States = $100
million - $30 billion3
1. Patton, Med Clin North Am, 1991
2. Cohen, Science, 1992
3. Phelps, Med Care, 1989
Impact of Resistance on
Antibiotic Use
• Increased complexity of empiric
antibiotic coverage
• Greater empiric use of antibiotics
• Increased use of broad spectrum
antibiotics
• Perpetuates the cycle of resistance
Impact of FQ Resistance on
Clinical Outcome
• Retrospective cohort design
• All patients with clinical E. coli or K. pneumoniae
isolates
– 123 patients with FQ-resistant isolate
– 70 patients with FQ-susceptible isolate
• January 1, 1998 - June 30, 1999
• Sites
– Hospital of the Univ. of Penn (HUP)
• 725-bed academic medical center
– Presbyterian Medical Center (PMC)
• 344-bed urban community hospital
Lautenbach et al, SHEA, 2002
% Mortality
Results: Mortality
10
9
8
7
6
5
4
3
2
1
0
P=0.05
8.1%
1.4%
Infection-Related Mortality
FQ-susceptible (n=70)
FQ-Resistant (n=123)
Lautenbach, SHEA, 2002
Multivariable Model: Risk
Factors for Mortality
Variable
Unadj OR
Adj OR (95%CI)
P value
FQ Resistance
6.61
8.83 (0.97, 80.59)
0.054
Bloodstream Involvement
4.87
4.89 (1.23, 19.42)
0.024
1.13 (1.01, 1.26)
0.033
4.30 (1.03, 17.94)
0.045
APACHE II Score
ICU Location
4.34
Lautenbach, SHEA, 2002
% Patients Receiving Appropriate
Therapy
Time to Effective Therapy
80
70
FQ Resistant
FQ Susceptible
60
50
40
30
20
10
0
Within 24 hours
Within 48 hours
Time after Culture
Lautenbach et al, SHEA, 2002
Impact of VRE on Emergence of
Other Resistance Patterns
• Resistance transferable to S. aureus in vitro 1
• 8-month prospective study of S. aureus and
VRE co-colonization in the GI tract 2
– Of 37 patients colonized with VRE, 23 (62%)
had S. aureus recovered from stool
• Of these, 20 (87%) had MRSA
– 25% of stools with S. aureus contained
>1,000,000 organisms/gram of stool
1. Noble WC, FEMS Microbiol Lett 1992 72:195
2. Ray AJ, Clin Infect Dis 2003 37:875
Glycopeptide Resistance in
S. aureus
VISA Isolates: PFGE Analysis
Lane 1-S. Aureus
Lane 2-MRSA
Lane 3-VISA (pt#1)
Lane 4-MRSA (pt#1)
Lane 5-VISA (pt#2)
Smith, NEJM 1999;340:493
VRSA - 2002
VanA +
Chang S, N Engl J Med 2003;348:1342
Outline
• Recent trends in emerging antibiotic
resistance
• Epidemiology of resistance
• Clinical impact on resistance
• Strategies to curb further emergence of
resistance
Prevention of Spread: VRE
• How do findings relate to infection risk?
• Only a minority of patients become colonized when
cared for in a contaminated room 1
• Elucidation of mechanisms of VRE acquisition
• Implement more effective infection control
interventions
• Enhanced surveillance
• Patients infected or colonized with VRE have equal
potential for transmission
• Patient transfer between facilities
1. Bonten, Lancet 1996;348:1615
Antibiotic Use: Is There Room for
Improvement?
“The desire to ingest medicines is
one of the principal features which
distinguish man from the animals”
Osler W. Aecquanimitas,1920
Implications: Addressing FQ
Overuse / Misuse
• On whom/Where are they being
used?
–Inpatient
–Outpatient
–Emergency Departments
• Why/How are they being used?
–Indications
–Dose/duration
How are FQs Used:
Appropriateness in Inpatients
None
1%
First line
35%
Alternative
59%
Experimental
5%
Ena, Diagn Microbiol Infect Dis 1998
Appropriateness of FQ Use: EDs
• FQ Drug Use Evaluation (DUE)
• Sites: 2 Academic Medical Center
Emergency Departments (EDs)
• Subjects: 100 patients seen in EDs, then
discharged
• Appropriateness (of indication) of therapy
judged by existing institutional guidelines
–www.med.upenn.edu/bugdrug
–3 independent ID reviewers
Lautenbach, Arch Intern Med 2003;163:601
Appropriateness of ED FQ Use
81% of courses inappropriate
No Infection
(n=27)
33%
Other Agent
First Line
(n=43)
53%
Insufficient
Information
(n=11)
14%
Lautenbach, Arch Intern Med 2003;163:601
Appropriateness by Site of Infection
50
Appropriate
Inappropriate
40
p=0.76
30
20
10
0
Ur
l
t
t
e
a
a
c
u
a
n
o
r
r
ti
ss
T
h
s
i
r
l
i
T
e
T
ta
e/
i
ft
sp
int
s
n
e
o
o
o
e
S
R
/
tr
N
/
G
s
n
r
i
Ga
Ea
Sk
ry
a
n
i
ry
o
t
a
O
r
e
h
t
Lautenbach, Arch Intern Med 2003;163:601
Appropriateness of FQ Use: EDs
• 19/100 (19%) patients received appropriate FQ
therapy (judged by indication)
–14 received both an incorrect dose & duration
–4 received either an incorrect dose or duration
–1 received the correct dose and duration
• Variation of FQ use by ED
–ED#1 (training program): 74% inappropriate
–ED#2 (no training program): 86% inappropriate
• OR (95%CI) = 0.39 (0.14, 1.09)
Lautenbach, Arch Intern Med 2003;163:601
Potential Strategies
• Guidelines
• Antibiotic cycling
• Antimicrobial optimization
Potential Strategies
• Guidelines
• Antibiotic cycling
• Antimicrobial optimization
Awareness and Use of CAP Guidelines
• Survey study of 621 physicians
– ATS CAP guidelines / local CAP guidelines
• 7 Pittsburgh area hospitals
– 1 University
– 3 community teaching
– 3 community non-teaching
• 345/621 (56%) responded
– Generalists (79%)
– ID (6%)
– Pulmonologist (5%)
Switzer GE, J Gen Intern Med 2003;18:816
Awareness and Use of CAP Guidelines
Used guideline
(20%)
Not at all
familiar (21%)
n=345
Read guideline
(30%)
Have seen
guideline (29%)
Switzer GE, J Gen Intern Med 2003;18:816
Predictors of Use of ATS
Guidelines
Variable
Adj OR (95%CI)
Practicing as pulmonary or ID
specialist
4.51 (1.71, 11.90)
Spending more time in non-patient
related activities
1.02 (1.00, 1.05)
Higher “intellect” score*
2.18 (1.07, 4.40)
* Goldberg Personality Scale
Switzer GE, J Gen Intern Med 2003;18:816
Awareness and Use of CAP Guidelines
• 6 of 7 study hospitals had local guidelines for CAP
• 290 respondents from the 6 hospitals
– 41% reported that no local guidelines existed
– 30% of respondents reported they used the
guideline more than half of the time in CAP therapy
• 48 respondents from the hospital without a guideline,
– 14% said it their hospital did have a guideline
• Local CAP guideline use was associated with:
– Practicing as a generalist: OR=0.10; 95%CI (0.01-0.89)
– Positive attitude toward guidelines: OR=1.05 95%CI (0.99-1.11)
Switzer GE, J Gen Intern Med 2003;18:816
Limitations of Guidelines
• Discrepancies across guidelines
• Lack of RCT data to support
recommendations
• Little regional/local susceptibility data
• Poor correlation between in vitro
resistance and clinical response
• Failure to consider future emergence of
resistance
Luh JY, Arch Intern Med 2003;163:1617
Potential Strategies
• Guidelines
• Antibiotic cycling
• Antimicrobial optimization
Antibiotic Cycling
• Periodic removal of certain agents / classes
• Goals:
– Prevention of VAP
– Curb emergence of antibiotic resistance
– Optimize empiric antibiotic selection
• Assumptions
–
–
–
–
–
Resistance emerges through selective pressure
Strict antibiotic control
Closed population
No patient to patient transmission
No co-selection of resistance
Antibiotic Cycling
• Prospective cohort study conducted in ICU
– University of Virginia
• General, trauma, or transplant surgery
patients
• 2 year study
– 1 year non-protocol driven antibiotic use
– 1 year of rotating empirical antibiotic
assignment
• November 1997 – October 1999
Raymond DP, Crit Care Med 2001;29:1101
Antibiotic Cycling
Quarter
Pneumonia
Jan-Mar
Ciprofloxacin +
Clindamycina
Piperacillin /
tazobactam
Carbapenemb
Apr-Jun
Jul-Sep
Oct-Dec
Cefepime +
Clindamycina
Peritonitis / Sepsis
of ? Etiology
Carbapenemb
Cefepime +
Metronidazolec
Ciprofloxacin +
Clindamycina
Piperacillin /
tazobactam
a - add clindamycin for pneumonia if aspiration suspected
b – imipenem or meropenem
c- add ampicillin or vancomycin if Enterococcus is suspected
Raymond DP, Crit Care Med 2001;29:1101
Antibiotic Cycling
Variable *
Year 1
Year 2
p value
Resistant GPC Infections 14.6
Resistant GNB Infections 7.7
Infection-related mortality 9.6
7.8
2.5
2.9
<0.001
<0.001
<0.001
Liver disease
Transplantation
8 (5.6%)
6 (4.2%)
<0.001
0.001
19 (10.8%)
27 (15.3%)
* All variables per 100 admissions
Limitations
Concurrent ceftazidime to cefepime formulary switch
Concurrent infection control interventions
Raymond DP, Crit Care Med 2001;29:1101
Potential Strategies
• Guidelines
• Antibiotic cycling
• Antimicrobial optimization
Antimicrobial Optimization
• Decrease unnecessary antibiotic use
• Develop / apply guidelines for antibiotic use
• Tailor empiric antibiotic selection to particular
situation
– Patient specific
• Maintain broad choice of agents
• Several approaches
– Human
– Computer
Antimicrobial Optimization
• Decrease unnecessary antibiotic use
• Develop / apply guidelines for antibiotic use
• Tailor empiric antibiotic selection to particular
situation
– Patient specific
• Maintain broad choice of agents
• Several approaches
– Human
– Computer
Antibiotic Management Programs
• University of Pennsylvania
• 1993 - Antibiotic management
program (AMP)
– Formulary redesigned
– Guidelines developed
– AMT team
• Approval of restricted agents
• Streamlining of therapy
Gross R, Clin Infect Dis 2001;33:289
Antibiotic Management Programs
Outcome
P value
Appropriate
AMT ID Fellows Adjusted OR
(n=87) (n=93
(95%CI
76
44
7.7 (3.7, 16.2)
Cure
49
0.03
35
2.4 (1.3, 4.5)
<0.001
Gross R, Clin Infect Dis 2001;33:289
Antimicrobial Optimization
• Decrease unnecessary antibiotic use
• Develop / apply guidelines for antibiotic use
• Tailor empiric antibiotic selection to particular
situation
– Patient specific
• Maintain broad choice of agents
• Several approaches
– Human
– Computer
Computer Support
Computer Decision Support
• Prospective before-after study of a
computerized anti-infectives
management program
• 12-bed ICU
• LDS Hospital, Salt Lake City
• June 1992 – June 1995
– 2 year “before” period
– 1 year “after” period
Evans RS, NEJM 1998;338:232
Computer Decision Support
• Computer system
– Data incorporated
• Patient information: admission diagnosis,
WBC count, temperature, surgical data,
chest radiograph, microbiology data,
pathology data, serologic data, allergies,
past infection
• Institution information: 5-year antibiogram
– Output
• Suggest antibiotic regimen that would cover
the identified and potential pathogens
Evans RS, NEJM 1998;338:232
Computer Decision Support
Variable
Before (n=766)
After (n=203)* p value
# different abx ordered
Duration of abx (hrs)
# abx doses
ICU Length of stay (ds)
Total Length of stay
Total hospital cost
2.0 (1.9, 2.1)
214 (177-251)
23.6 (20.3–26.9)
4.9 (4.1-5.8)
12.9 (11.5-14.4)
$35K (31K-39K)
1.5 (1.3, 1.7)
<0.001
103 (45-160) <0.001
11.4 (6.2-16.7) <0.001
2.7 (1.5-4.0)
<0.001
10.0 (7.7-12.3) <0.001
$26K (20K-32K)<0.001
* Includes only those patients for whom computer regimen was followed
Values are means per patient and 95%CIs
Evans RS, NEJM 1998;338:232
Trends in Antimicrobial Prescribing
•Cross sectional survey
•National Ambulatory
Medical Care Survey
(NCAMS)
Overall abx use
Adults 13% 10% (p<0.001)
Peds 33% 22% (p<0.001)
Broad Spectrum abx use
Adults 24% 48% (p<0.001)
Peds 23% 40% (p<0.001)
Steinman MA, Ann Intern Med 2003;138:525
Trends in Antimicrobial Prescribing
Steinman MA, Ann Intern Med 2003;138:525
Conclusions
• Antimicrobial resistance increasing
• Negative impact of resistance on clinical
outcomes
• Many potential interventions
– All require more study
• Judicious use of current agents critical to
preserve future use
Emergence of Antimicrobial
Resistance
Ebbing Lautenbach, MD, MPH
Assistant Professor of Medicine and Epidemiology
Associate Hospital Epidemiologist, Hospital of the
University of Pennsylvania
Center for Clinical Epidemiology & Biostatistics
University of Pennsylvania School of Medicine
PENN