Healthcare-Associated Pneumonia: Refining the HCAP Criteria

Transcription

Healthcare-Associated Pneumonia: Refining the HCAP Criteria
Healthcare-Associated Pneumonia:
Refining the HCAP Criteria
Pharmacotherapy Conference
November 20, 2009
Russell T. Attridge, Pharm.D.
Master’s Candidate / Specialty Resident in Pharmacotherapy
The University of Texas at Austin College of Pharmacy
The University of Texas Health Science Center at San Antonio
OBJECTIVES
 At the end of this presentation, audience members will be able to:
 Define healthcare-associated pneumonia (HCAP).
 Describe the origin of the term “healthcare-associated infection.”
 Briefly summarize the findings of current HCAP evidence.
 Discuss the published evidence regarding individual HCAP risk factors.
 Further specify the population of pneumonia patients that should be considered HCAP.
INTRODUCTION

Table 1: Definitions1, 2
Pneumonia Type
“Signs, symptoms, and radiologic evidence of pneumonia . . .”
Community-acquired pneumonia (CAP)
Healthcare-associated pneumonia (HCAP)
Hospital-acquired pneumonia (HAP)
Ventilator-associated pneumonia (VAP)
In the first 48 hours of hospital admission
In CAP patients with recent contact with the health system
48-72 hours after hospital admission
48-72 hours after endotracheal intubation
Adapted from: Guidelines for the management of adults with hospital-acquired, ventilator-associated, and healthcare-associated
pneumonia. Am J Respir Crit Care Med 2005;171:388-416.

Epidemiology – pneumonia is…
 The leading cause of infectious disease-related death globally and in the United States3-5
 WHO (2004)  4.2 million deaths worldwide (7.1% of total global death)3
 CDC (2006)  more than 56,000 deaths in the United States4
 Responsible for 1.2 million of the 35 million annual U.S. hospitalizations 5
 Community-acquired pneumonia (CAP)6, 7
 Incidence: 4 million cases annually in the United States
o 80% outpatient: low risk of mortality
o 18% non-ICU inpatient: 5-7% mortality
o 2% ICU inpatient: 10-15% mortality
 U.S. expenditures: greater than $8 billion annually
 Table 2: Expected CAP Pathogen Distribution, By Site of Care8
Outpatient
Inpatient, non-ICU
Inpatient, ICU
S pneumoniae
M pneumoniae
H influenzae
C pneumoniae
Resp viruses
S pneumoniae
M pneumoniae
C pneumoniae
H influenzae
Legionella sp
Aspiration / respiratory viruses
S pneumoniae
S aureus
Legionella sp
Gram-negative bacilli (GNB)
H influenzae
Adapted from: File TM. Community-acquired pneumonia. Lancet 2003;362:1991-2001.
2
†Healthcare-associated infections:9
Hospitalization within past 12 months
Peritoneal/hemodialysis within 12 months
Indwelling bladder/vascular device at home immediately prior to admission
NOTE: long-term care facilities were not included in these criteria
Morin and Hadler 2001
‡Healthcare-associated bloodstream infection:10
Friedman et al 2002
Positive blood culture w/in 48 hours of admission with . . .
Intravenous (IV) therapy/wound care at home in the past 30 days
Hospital/hemodialysis (HD) clinic or IV chemotherapy in the past 30 days
Hospitalized ≥ 2 days in the past 90 days
Transfer from a nursing home or long-term care facility
§Healthcare-associated bacteremia:11
Tacconelli et al 2004
Patients with MRSA in ≥ 1 blood culture within 24 hours of hospital admission with . . .
IV therapy, chemotherapy, specialized nursing/wound care at home
Ambulatory visit within past 30 days
Chronic HD
Hospitalized ≥ 2 days in past 6 months
Nursing home or long-term care facility
ψ Healthcare-associated pneumonia:2
ATS/IDSA Guidelines 2005
Hospitalization for 2 days or more in the preceding 90 days
Residence in a nursing home or extended care facility
Home infusion therapy (including antibiotics)
Chronic dialysis within 30 days
Home wound care
Family member with multidrug-resistant pathogen
Figure 1: The Origins of HCAP
† This is largely considered the first definition of a healthcare-associated infection. The objective of the study was
to determine the epidemiology of community-onset S. aureus bloodstream infections (BSIs) and the extent to
which they are caused by MRSA. Three mutually exclusive cohorts were created; patients with “healthcareassociated infections” and patients “with underlying comorbidities” were more likely to have MRSA BSIs than
patients “without underlying comorbidities” (MRSA rates as a % of S. aureus: 16% vs. 16% vs. 0%, respectively).
‡ Extrapolating from Morin and Hadler, Friedman and colleagues set out to further develop a classification scheme
for BSIs that differentiated among community-acquired, healthcare-associated, and nosocomial infections. Results
of their study led them to conclude that healthcare-associated BSIs are similar to nosocomial infections (e.g.,
pathogens and susceptibility patterns, mortality) and should be a separate category of infection. This definition is
very similar to the definition in pneumonia set forth by the 2005 ATS/IDSA guidelines.
§ Tacconelli and colleagues performed a case-control study to further characterize patients found to have MRSA
bacteremia within 24 hours of admission. All patients had healthcare-associated BSI risk factors (no “true”
community-acquired MRSA BSIs). In the discussion, the authors emphasize the importance of using the
“heathcare-associated” term when it applies to avoid confusion with any true community-acquired infections.
ψ Historical healthcare-associated infection risk factors were applied to pneumonia in the 2005 ATS/IDSA
guidelines for the management of HAP, VAP, and HCAP.
3
HCAP AS A DISTINCT CLINICAL ENTITY
 HCAP is a large, heterogeneous patient population with a poorly-defined conglomeration of risk
factors that may increase the risk for infection with drug-resistant pathogens
Risk Factor
Hosp. in past 30d
Hosp. in past 90d
1
2
3
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4
5
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
Hosp. in past 12 months
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

Transfer from other health facility


Home infusion / IV therapy

Chronic dialysis



Family with MDR pathogen


8
1.
Friedman et al 2002

2.
ATS/IDSA
Guidelines 2005
3.
Kollef et al 2005
4.
Carratalà et al 2007

5.
Micek et al 2007

6.
Shorr et al 2008
7.
Venditti et al 2009
8.
Shindo et al 2009
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Home wound care
7
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Hosp./surgery in past 180d
Nursing home / ext. care facility
6
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Attended hosp./HD clinic past 30d
Regular clinic visits (HD, PD, infusions)
IV chemotherapy past 30 days
Immunocompromised state


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

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Figure 2: HCAP Definitions, By Study
QUANTIFYING THE MAGNITUDE OF THE HCAP POPULATION
Cohorts altered significantly by study site and selected HCAP inclusion criteria
HCAP
Kollef '05
CAP
30.8%
69.2%
Micek '07 & Shorr '08
67.4%
Carratala '07
32.6%
17.3%
Venditti '09
82.7%
28.8%
Shindo '09
71.2%
38.0%
Average
62.0%
36.5%
0%
10%
20%
30%
63.9%
40%
50%
60%
70%
80%
90%
100%
% HCAP of Community-Dwelling Adults Hospitalized for Pneumonia
Figure 3: CAP vs. HCAP, By Study
4
 Comparison of Etiology and Outcomes, HCAP vs. CAP
12
2005 Kollef et al – multicenter retrospective cohort analysis (U.S., 59 hospitals), 2002-03
Variable
Pathogen (%, culture-positive)
 S. aureus [% MRSA]
 P. aeruginosa
 S. pneumoniae
 H. influenzae
Hospital length of stay, days (mean ± SD)
In-hospital mortality (%)
2007
46.7 [56.8]
25.3
5.5
5.8
8.8 ± 7.8
19.8
25.5 [34.8]
17.1
16.6
16.6
7.5 ± 7.2
10.0
<0.01 [<0.01]
<0.01
<0.01
<0.01
<0.0001
<0.0001
HCAP (n=126)
CAP (n=601)
27.8
11.9
2.4
1.6
2.4 [0]
32.5
10.4 ± 3.4
10.3
33.9
6.0
8.8
0.5
0 [0]
43.9
10.4 ± 4.7
4.3
P-value
* = not provided
0.18
0.02
0.01
0.18*
0.005
0.02
0.94
0.007
HCAP (n=431)
CAP (n=208)
44.5 [68.8]
10.4
25.5
4.2
0.2
Not provided
24.6
25.5 [47.1]
40.9
4.8
17.3
3.4
Not provided
9.1
P-value
* = not provided
0.001* [0.001]
<0.001
<0.001
<0.001
0.017
-<0.001
Venditti et al15 – multicenter prospective observational study (Italy, 55 hospitals), 2007
Variable [no pathogen data]
Hosp. length of stay, days (mean, 95% CI)
In-hospital mortality (%)
2009
P-value
Micek et al14 – single-center retrospective cohort analysis (U.S.), 2003-05
Variable
Pathogen, (%, culture-positive)
 S. aureus [% MRSA]
 S. pneumoniae
 P. aeruginosa
 H. influenzae
 Legionella sp
Hospital Length of stay, days (mean ± SD)
In-hospital mortality (%)
2009
CAP (n=2,221)
Carratalà et al13 – single-center prospective observational analysis (Spain), 2001-04
Variable
Pathogen, (%, culture-pos. and neg.)
 S. pneumoniae
 H. influenzae
 L. pneumophila
 P. aeruginosa
 S. aureus [% MRSA]
 No pathogen identified
Hospital length of stay, days (mean ± SD)
30-day mortality (%)
2007
HCAP (n=988)
HCAP (n=90)
18.7 (15.9-21.5)
17.8
CAP (n=49)
14.7 (13.4-15.9)
6.7
P-value
<0.05
<0.05
Shindo et al16 – single-center retrospective observation study (Japan), 2005-07
Variable
Pathogen, (%, culture-pos. and neg.)
 S. pneumoniae
 S. aureus [% MRSA]
 Pseudomonas sp
 Atypical pathogens
 No pathogen identified
Previous antibiotics, past 90d (%)
In-hospital mortality (%)
HCAP (n=141)
CAP (n=230)
13.5
9.9 [35.7]
5.7
0.7
45.4
63.1
21.3
19.1
6.1 [14.3]
1.7
7.0
52.6
20.9
7.4
P-value
* = not provided
0.132*
0.235* [0.066]*
0.038*
0.004*
0.194*
<0.001
<0.001
5
THE BIGGER ISSUE: HCAP or DRUG-RESISTANT PNEUMONIA?
Shorr AF, Zilberberg MD, Micek ST, et al. Predictors of infection due to antibiotic-resistant bacteria by select risk
17
factors for health care-associated pneumonia. Arch Intern Med 2008;168(20):2205-10.
14
Design
Single-center retrospective review (same cohort as Micek et al 2007 )
Primary endpoint – presence of infection with a resistant pathogen
o MRSA, P.aeruginosa, extended-spectrum β-lactamase-producing (ESBL) Klebsiella sp,
and other non-fermenting gram-negative rods (GNRS)
Population
n=639 pts (HCAP, n=431; CAP, n=208)
Resistant pathogen (45.2%) vs. no resistant pathogen (54.8%)  see figure below
Results
Pathogen Distribution (not provided for HCAP and CAP individually)
Resistant Pathogen
No Resistant Pathogen
MRSA: 54.3%
S. pneumoniae: 37.1%
P.aeruginosa: 41.5%
ESBL Klebsiella sp/other nonfermenting GNRs: 16.3%
HCAP definition specificity for resistant pathogen – 48.6%
Four variables independently associated with a resistant pathogen (basis for scoring system)
o OR 4.21 – recent hospitalization (4 points)
o OR 2.75 – nursing home resident (3 points)
o OR 2.11 – long-term hemodialysis (2 points)
o OR 1.62 – ICU admission (1 point)
Scoring system (out of 10 points)  AUC under ROC curve = 0.75 (95% CI, 0.65-0.80)
o Likelihood of Infection with a resistant pathogens
 Low-risk (<3 points): <20%
 Intermediate-risk (3-5 points): 55%
 High-risk (≥6 points): >75%
Author’s
As is, HCAP risk factors have limited value in predicting patients with resistant infections.
Comments
The use of simple of risk stratification tools can improve the likelihood of appropriate initial
coverage without exposure to unnecessarily broad-spectrum agents.
Resistant Pathogen
No Resistant Pathogen
100%
80%
60%
40%
20%
0%
Figure 4: Resistant Pathogens, By Risk Factor (Shorr et al 200817, all p<0.05)
6
INDIVIDUAL HCAP CRITERIA: WHAT IS THE RISK OF A RESISTANT PNEUMONIA PATHOGEN?
 Recent Hospitalization
 Proportion of the HCAP Cohort, By Study
Study
Previous Hospitalization
12
Kollef 2005 (HCAP, n=988)
13
Carratalà 2007 (HCAP, n=126)
14
17
Micek 2007 / Shorr 2008 (HCAP, n=431)
15
Venditti 2009 (HCAP, n=90)
16
Shindo 2009 (HCAP, n=141)
Not provided
Within 90 days: 55 (43.7%)
Within 365 days: 402 (93.3%)
Within 180 days: 384 (89.1%)
Within 90 days: 297 (68.9%)
Within 180 days: 72 (80.0%)
Within 90 days: 55 (39.0%)
 Key Points
 One of the most prevalent HCAP risk factors – extremely heterogeneous group
 No published literature specifically on recent hospitalization
 Emphasis in literature on risk factors for drug-resistant pathogens
o Previous hospitalization – consistently an identified risk factor
 In HCAP patients, primary pathogens of concern are MRSA and Pseudomonas sp
 Evidence for Pseudomonas and MRSA in community-dwelling patients (see below)
Group
Pseudomonas
pneumonia
MRSA
pneumonia
MRSA
Colonization
Publication
Independent Risk Factors (OR, 95% CI)
18
Arancibia 2002
(n=559, CAP patients; n=60,
Pseudomonas pneumonia)
19
Garcia-Vidal 2009
[abstract, ICAAC 2009]
(n=4426, community-onset
pneumonia; n=44,
Pseudomonas pneumonia)
20
Lescure 2006
(n=198, MRSA case patients;
n=198, MSSA control patients;
27.3% of infections in
respiratory tract)
17
Shorr 2008
(n=639, CAP and HCAP patients;
n=157, MRSA pneumonia)
See Table 1, Appendix A
Pulmonary comorbidity (5.8, 2.2-15.3)
Previous hospital admission, 1 mo. (3.8, 1.8-8.3)
COPD (5.5, 2.7-11.2)
Prior use of steroids (3.9, 1.8-8.4)
ICU admission (3.3, 1.4-8.1)
Note: “Community-onset” not defined – may not
have included patients with previous hospitalization.
Prior hospitalization, past 3y (3.8, 1.8-7.9)
Home nursing care (3.7, 2.0-6.7)
Home care or hosp. for surgery, past 3y (3.1, 1.2-8.0)
Referral [other hospital, nursing home] (2.3, 1.2-4.3)
Age >65y (1.6, 1.1-2.5)
Recent hospitalization, 3 mos. (2.35, 1.52-3.64)
Nursing home resident (1.88, 1.21-2.90)
ICU admission (1.75, 1.20-2.55)
See Table 1, Appendix A
 The Bottom Line
 Previous hospitalization needs to be considered with the additional knowledge of
reason for previous admission, duration of hospitalization, and receipt of antibiotic
therapy, all of which may play a role in a patient’s risk for a drug-resistant pathogen.
 The search for drug-resistant pathogen-specific risk factors is complicated by issues
of statistical power, selection bias, and limitations of the case-control study design.
o For community-dwelling patients, there is limited evidence.
7
 Residence in a Nursing Home / Long-Term Care Facility (LTCF)
 Size of Cohort
Study
Nursing Home / LTCF Patients
12
Kollef 2005 (HCAP, n=988)
13
Carratalà 2007 (HCAP, n=126)
14
17
Micek 2007 / Shorr 2008 (HCAP, n=431)
15
Venditti 2009 (HCAP, n=90)
16
Shindo 2009 (HCAP, n=141)
490 (49.6%)
32 (25.4%)
121 (28.1%)
6 (6.7%)
86 (61.0%)
 Key Points
 Nursing home-acquired pneumonia (NHAP): most evidence among the HCAP criteria
 Adults over age 85 are the fastest growing demographic in the U.S.21
 Pneumonia  second most common infection in nursing home residents22
o Highest mortality (15-60%) and common cause for hospital transfer22-24
 Lack of standard “nursing home” definition  major differences in scope of care25
 NHAP is often managed in-house w/oral therapy (e.g., fluoroquinolones)22, 26
o Remember: HCAP focuses on hospitalized patients
 Evidence-based review of hospitalized NHAP publications containing pathogen data
Lim WS, Macfarlane JT. A prospective comparison of nursing home acquired pneumonia with
27
community acquired pneumonia. Eur Respir J 2001;18:362-8.
Design
 Single-center prospective cohort study (United Kingdom), 1998-2001
Population  n=437 CAP patients; 40 (9%) admitted from nursing homes
 Excluded patients hospitalized in previous 10 days, HIV patients, and
immunosuppressed patients (recent chemotherapy, recent daily corticosteroid therapy)
 For etiology, each NHAP “case” matched with 2 “control” CAP patients from 1998-1999
Characteristic
NHAP (n=40)
CAP (n=397)
P-value
Age, years
80.6 ± 9.6
65.5 ± 19.4
<0.001
Prior antibiotics
18 (45%)
145 (37%)
0.6
ECOG (1-4)
3±1
1.2 ± 1.2
<0.001
Barthel Index (0-20)
8.9 ± 6.7
17 ± 5.1
<0.001
PSI score
144 ± 26
90 ± 39
<0.001
Results
 Pathogen(s) were detected in 50 (77%) of 66 patients
Pathogen
NHAP (n=22)
CAP (n=44)
P-value
(% cx-pos. and neg.)
* = not provided
S. pneumoniae
12 (55%)
19 (43%)
0.342*
S. aureus
0
1 (2%)
0.481*
H. influenzae
0
5 (11%)
0.104*
Atypicals
4 (18%)
9 (20%)
0.860*
No pathogen identified
7 (32%)
9 (20%)
0.287*
Outcome
NHAP (n=40)
CAP (n=397)
P-value
LOS, days (survivors)
6 (median)
7 (median)
-In-hospital mortality
21 (53%)
53 (13%)
<0.001
 No enteric gram-negative bacteria reported in either cohort
 Independent risk factor of mortality: functional status (ECOG) – OR 4.0, 95% CI, 1.3-12.0
Author’s
 Compared to CAP patients, NHAP patients have more severe disease but a similar
Conclusions
pathogen distribution.
 Choice of empiric antibiotics for hospitalized NHAP patients should not be any different
than for older CAP patients.
 Functional status is the main factor in the higher mortality of NHAP patients.
8
El Solh AA, Sikka P, Ramadan F, Davies J. Etiology of severe pneumonia in the very elderly. Am J Respir
28
Crit Care Med 2001;163:645-51.
Design
 Multi-center prospective cohort study (2 hospitals); June 1996 – September 1999
Population  n=104 pts >75 years of age with severe CAP and NHAP (all mechanically-ventilated)
 Excluded if transferred to ICU after 24h of initial admission, recent hospitalization (30d)
 Patients assigned Activities of Daily Living (ADL) score as marker of functional status
 ADL scores from 6 (best) to 18 (worst); divided into 3 arbitrary classes
o ADL I – 6-8 points; ADL II – 9-13 points; ADL III – 14-18 points
Results
 Microbial etiology determined in 55 (53%) patients *“n” per cohort not provided+
Variable
Nursing Home (n=47) Home (n=57)
P-value
Pathogens (% cx-pos. and neg.)
 S. pneumoniae
4 (9%)
8 (14%)
0.380*
 S. aureus
14 (29%)
4 (7%)
0.002*
o % MRSA
3 (21%)
0
0.053*
 P. aeruginosa
2 (4%)
1 (2%)
0.448*
 L. pneumonphila
0
5 (9%)
0.037*
APACHE II score
28.4 ± 5.7
25.8 ± 5.4
0.04
In-hospital mortality
27 (57.4%)
30 (52.6%)
0.8
 Poor functional status associated with higher rates of:
o S. aureus: ADL III (56%) vs. ADL I (9%), p=0.0034
o GNB and P. aeruginosa: ADL III (39%) vs. ADL I (17%), p=0.16
 Independent predictors of hospital mortality (multivariable regression) were multilobar
involvement, septic shock, 24-h urine output, and inadequate antimicrobial therapy
o In this patient group, no impact of functional status on mortality
Author’s
 Respiratory pathogens differ based on residence prior to admission.
Conclusions  Functional status may factor into pneumonia due to S. aureus and Pseudomonas.
El Solh AA, Pietrantoni C, Bhat A, et al. Indicators of potentially drug-resistant bacteria in severe
29
nursing-home acquired pneumonia. Clin Infect Dis 2004;39:474-80.
Design
 Single-center ICU retrospective cohort study (12-bed ICU, average 650 admissions/yr)
 Derived from a prospective database – patient data collected between 1998-2003
Population  n=135 mechanically-ventilated patients from a long-term care facility
o Excluded if transferred to ICU >48h after admission, hospitalized >48 hours in
previous 6 months, immunocompromised, or receiving antibiotic therapy
within 72h of enrollment
 Utilized 2 cohorts (derivation cohort, n=88; validation cohort, n=47) to derive and
validate a classification tree that predicts the risk of a drug-resistant pathogen
Results
 In both cohorts, patients with pneumonia secondary to drug-resistant pathogens had:
o Higher ADL scores (higher=↑ dependence) [p<0.05]
o Higher Charlson Index scores (higher=↑ risk of 1-year mortality) [p<0.05]
o Higher rates of previous antibiotic use [p<0.001]
 Microbial etiology determined for 93 (68%) of 135 patients
Gram-Positive Cocci (% culture-positive) Gram-Negative Bacilli (% culture-positive)
S. pneumoniae: 25 (25.3%)
P. aeruginosa: 9 (9.1%)
MRSA: 20 (20.2%)
E. coli: 9 (9.1%)
MSSA: 11 (11.1%)
K. pneumoniae: 6 (6.1%)
 Stratifying patients by previous antibiotic exposure and a cut-off ADL score of 12.5, the
classification tree selected patients with drug-resistant pathogens with sensitivities of
100% and 100% and specificities of 53.5% and 69.4% in the derivation and validation
cohorts, respectively.
Author’s
 Functional status and previous antibiotic use are predictors of pneumonias due to drugConclusions
resistant pathogens and may be considered when choosing therapy for severe NHAP.
9
Martínez-Moragόn E, Garcia Ferrer L, Serra Sanchos B, et al. Community-acquired pneumonia among the
elderly: differences between patients living at home and in nursing homes. Arch Bronconeumol
30
2004;140(12):547-52.
Design
 Single-center prospective cohort study (Spain), 2002-2003
Population  n=91 CAP pts; all patients >65 years old; 25/91 (27.5%) admitted from nursing homes
 Excluded patients hospitalized in prior 10 days or w/o primary diagnosis of pneumonia
Results
 Microbiologic diagnosis, n=22 (24%)  nursing home, n=6 (24%); home, n=16 (24%)
Variable
Nursing Home (n=25)
Home (n=66)
P-value
Age, years
82 ± 4
73 ± 5
0.0001
ECOG score
2.09 ± 0.9
0.93 ± 11
0.0001
Karnofsky Index
51 ±17
78 ± 23
0.0001
Barthel Index
19 ± 33
77 ± 35
0.0001
PSI score
134 ± 26
95 ± 28
0.0001
Pathogen (n)
- S. pneumoniae
2
4
 S. aureus
3
4
 Enteric GNB
1
0
 Atypicals
0
5
LOS, days
8 ± 7.87
8.54 ± 4.97
NS
In-hospital mortality, n (%)
7 (28%)
3 (4.5%)
0.005
 Univariable analysis: age, residence, Barthel Index, respiratory rate, hemoglobin, urea,
creatinine, arterial pH, and PSI score associated with mortality (all p<0.05)
2
 Stepwise linear regression  only predictor of mortality was serum urea (adj. r =0.452)
Author’s
 High mortality rate of nursing home patients consistent with other published data.
Conclusions  Pneumonia etiology was similar between CAP patients from home and nursing homes.
 Given their prognosis value, general condition scales should be standardized.
Kothe H, Bauer T, Marre R, et al. Outcome of community-acquired pneumonia: influence of age,
31
residence status and antimicrobial treatment. Eur Respir J 2008;32:139-46.
Design
 Prospective observational study; consecutive CAP patients, March 2003 – October 2005
 Data from the CAPNETZ group [based in Germany: >670 practitioners, >30 hospitals]
Population  n=2,647; 74.8% hospitalized, 25.2% outpatient
 Excluded patients with acquisition of pneumonia after admission, immunosuppression
 Microbial etiology determined in 539 (20.4%) of cases
 Subgroup analysis performed for those ≥65 in nursing homes *i.e., NHAP patients+
Results
 Multivariable model (elderly patients): age, CURB score, residence status [nursing
home], cerebrovascular/chronic liver disease, and treatment failure predictive of death
 Subgroup analysis: n=1,349 patients ≥65; 15.2% resided in a nursing home
Variable
NHAP (n=205)
Home (n=1,144) P-value
Age, years
82.3 ± 7.9
76.1 ± 7.0
<0.001
CURB score
1.52 ± 1.01
0.93 ± 0.83
<0.001
Pathogens (% cx-pos. and neg.)
 GNB
18.8%
5.5%
0.02
 S. aureus
2.3%
1.0%
NS
 P. aeruginosa
1.0%
0.3%
NS
Change in treatment
 Ineffective
14.1%
11.2%
0.233
 Resistance
2.0%
1.6%
0.560
30-day mortality
28.8%
6.9%
<0.001
Author’s
 Age and residence in a nursing home are associated with 30-day mortality after
Conclusions
controlling for comorbid conditions and disease severity.
 Mortality was significantly higher in nursing home patients despite similar rates of drugresistant pathogens and ineffective antibiotic therapy.
10
Maruyama T, Niederman MS, Kobayashi T, et al. A prospective comparison of nursing home-acquired
32
pneumonia with hospital-acquired pneumonia in non-intubated elderly. Respir Med 2008;102:1287-95.
Design
 Single-center prospective cohort study (Japan), June 2004 – May 2005
Population  n=108 patients; HAP, n=33; NHAP, n=75
 Excluded early-onset HAP/NHAP, hemodialysis, malignant disease, immunosuppression
Variable
HAP (n=33)
NHAP (n=75)
P-value
Age, years
79.0 ± 7.2
87.3 ± 8.9
<0.0001
ECOG, grade 1-4
3.4 ± 0.5
3.0 ± 0.5
<0.0001
Prior antibiotics
14 (42.4%)
26 (34.7%)
0.4419
CURB-65
2.54 ± 1.37
1.95 ± 1.03
0.0343
ICU admission
4 (12.1%)
6 (8.0%)
0.483*
Results
 Pneumonia etiology; microbiologic diagnosis in 26 (78.8%) HAP pts; 54 (72%) NHAP pts
Variable
HAP (n=33)
NHAP (n=75)
P-value
Pathogen
 S. pneumoniae
4 (12.1%)
25 (33.3%)
0.031
 S. aureus
9 (27.2%)
3 (4.0%)
0.006
 P. aeruginosa
4 (12.1%)
3 (4.0%)
0.075
 Atypicals
10 (30.3%)
28 (37.3%)
0.730
Presence of MDR pathogen
8 (24.2%)
7 (9.3%)
0.036*
In-hospital mortality
17 (51.5%)
28 (37.3%)
0.0213
 Results of logistic regression determined ECOG status to be an indicator of prognosis in
all patients and a subgroup of only NHAP patients.
Author’s
 Causative pathogens and outcomes differ for elderly non-intubated patients
Conclusions
hospitalized for the treatment of pneumonia.
 Findings do not support treating NHAP patients the same as late-onset HAP patients, as
outlined in the 2005 ATS/IDSA pneumonia guidelines.
Attridge RT, Frei CR. Etiology and outcomes for pneumonia patients admitted from skilled-nursing
facilities (SNFs): implications for empiric antibiotic therapy. In: Meeting guide and abstracts of the 2009
ACCP/ESCP International Congress on Clinical Pharmacy (Orlando). Lenexa, Kansas: American College of
24
Clinical Pharmacy, 2009:257-8.
Design
 Multicenter retrospective cohort study (U.S.), 1996-2006
 Data from the CDC National Hospital Discharge Survey (NHDS)
Population  n=5,477,504 patients (weighted data); SNF patients, n=130,081 (2.4%)
 Pneumonia diagnosis and pathogen data extracted from ICD-9-CM codes
Results
 Culture-positive patients: SNF vs. home, 15.4% vs. 12.7%, p<0.0001
Variable
SNF (n=130,081)
Home (n=5,477,504)
P-value
Age, years (mean)
80.1
70.2
<0.0001
Pathogen (cx-positive)
 S. aureus (%)
44.8
22.0
<0.0001
 P. aeruginosa (%)
22.1
14.4
<0.0001
 S. pneumoniae (%)
5.6
20.7
<0.0001
 H. influenzae (%)
1.4
7.1
<0.0001
LOS ≥7 days (%)
40
28
<0.0001
Death, at discharge (%)
13
5
<0.0001
 No data available on antibiotic therapy or drug-resistance (e.g., S. aureus resistance)
Author’s
Conclusions


Compared to patients admitted from home, SNF patients present with different
bacterial pathogens, utilize more healthcare resources, and suffer increased mortality.
These results support the inclusion of SNF patients in the HCAP population and are
similar to other recent U.S. data on pneumonia in SNF patients (Kollef et al 2005).
11
El Solh AAA, Akinnusi ME, Alfarah Z, Patel A. Effect of antibiotic guidelines on outcomes of hospitalized
33
patients with nursing home-acquired pneumonia. J Am Geriatr Soc 2009;57:1030-5.
Design
 Retrospective cohort study (3 northeastern U.S. hospitals), January 2006 – August 2008
 Compared time to clinical stability (TTCS), time to switch therapy (TTST), length of
hospital stay (LOS), and mortality in hospitalized NHAP patients when treated according
to the 2003 CAP or the 2005 HCAP guidelines
Population  n=337; consecutive adult patients admitted to hospital with principal diagnosis of
pneumonia and residence in a nursing home
 Excluded patients with HIV, previous hospitalization (30 days), ICU admission, outside
hospital transfer, active chemotherapy, or those receiving more than 1 dose of
antibiotics prior to ER presentation
Variable
2003 CAP (n=258)
2005 HCAP (n=76)
P-value
Age, years
73.5 ± 13.8
76.7 ± 13.1
0.08
ADL score, median
14 (11-16)
14.5 (11-17)
0.32
PSI score, mean
127 ± 31
135 ± 35
0.11
Results
 Clinical endpoints, based on guideline-concordant treatment
Outcome
2003 CAP (n=258)
2005 HCAP (n=76)
P-value
TTCS, days
3.6 ± 0.7
3.9 ± 0.8
0.38
TTST, days
4.1 ± 1.6
5.8 ± 2.2
<0.001
LOS, days
5.7 ± 1.7
6.9 ± 2.8
<0.001
Hospital mortality
34 (13.2%)
13 (17.1%)
0.49
30-day mortality
39 (15.1%)
17 (22.4%)
0.19
Author’s
 Treatment of hospitalized NHAP patients according to either the 2003 CAP guidelines or
Conclusions
the 2005 HCAP guidelines led to comparable outcomes in time to clinical stability and
mortality.
 The Bottom Line
 There are wide variations among the NHAP evidence in study populations, disease
severity, functional status, and pathogen distribution.
 Functional status may play an important role in both:
o Mortality27, 34
o Risk of a drug-resistant pathogen28, 29, 35-37
 Initial evidence suggests that guideline-concordant CAP and HCAP therapy have
comparable outcomes in NHAP patients.
 Chronic Hemodialysis
 Size of Cohort
Study
Dialysis Patients
12
Kollef 2005 (HCAP, n=988)
13
Carratalà 2007 (HCAP, n=126)
14
17
Micek 2007 / Shorr 2008 (HCAP, n=431)
15
Venditti 2009 (HCAP, n=90)
16
Shindo 2009 (HCAP, n=141)
Not provided
40 (31.7%)
43 (10.0%)
3 (3.3%)
10 (7.1%)
12
From: U.S. Renal Data System, USRDS 2009 Annual Data Report: Atlas of Chronic Kidney Disease and End-Stage Renal Disease in the
United States, National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, 2009.
Figure 5: Infectious-disease related admissions (per 1,000 patient years) [dialysis patients]
 Key Points
 Infections in hemodialysis patients – 2nd most common cause of death38
 Infectious disease mortality rates (2004-2006 combined data) in dialysis patients38
o Septicemia  19.5 deaths/1,000 patient-years (72% of infectious deaths)
o Pulmonary infection  4.4 deaths/1,000 patient-years (16% of inf. deaths)
 Pulmonary infectious mortality 14- to 16-fold higher than general population39
 Evidence-based review of pneumonia etiology in dialysis patients
Slinin Y, Foley RN, Collins AJ. Clinical epidemiology of pneumonia in hemodialysis patients: the USRDS
40
waves 1, 3, and 4 study. Kidney Int 2006;70:1135-41.
Design
 Retrospective cohort study (Waves 1, 3, and 4 Dialysis Morbidity & Mortality Study set)
 Random sample: 1 of every 5 US dialysis pts alive on 12/31/1993 (>1300 dialysis units)
Population  n=10,635  linked to Medicare claims to identify hospitalizations with pneumonia
 mean age: 60.3 years
 mean duration of ESRD: 3.8 years
 Pneumococcal vaccination: 8.7% in 5-years preceding study
 Influenza vaccination: 31.6% in 4 months preceding study
Results
 Average follow-up interval: 3.3 years
 28.9% of population hospitalized with pneumonia
o Primary discharge diagnosis: 57.1% of hospitalizations involving pneumonia
 Organism identified in 18.2% of cases
 Gram-negative vs. gram-positive bacteria (% overall): 11.1% vs. 4.8%, respectively
Gram-negatives (%overall, % cx-positive) Gram-positives (% overall, % cx-positive)
P. aeruginosa: 2.8% (15.4%)
S. pneumoniae: 3.4% (26.4%)
K. pneumoniae: 1.6% (8.8%)
Other Streptococcus: 1.0% (5.5%)
H. influenzae: 1.5% (8.2%)
Staphylococcus sp: 0.4% (2.2%)
 In-hospital mortality: 384 (12.4%) died with pneumonia diagnosis
o 134 (4.3%) – primary discharge diagnosis
o 250 (8.1%) – secondary discharge diagnosis
Author’s
 There was a noteworthy burden of disease and associated mortality. The mortality rate
Comments
of 12.4% is similar to the 11% in-hospital mortality rate found in a study of the general
41
U.S. Medicare population.
 Pneumonia was identified through administrative claims, meaning that a substantial
number of pneumonias may have occurred after admission for another serious illness.
o This may affect the spectrum of pathogens and the ability to show a direct causal
link between pneumonia and death.
13
Guo H, Liu J, Collins AJ, Foley RN. Pneumonia in incident dialysis patients – the United States Renal Data
42
System. Nephrol Dial Transplant 2008;23:680-6.
Design
 Retrospective cohort study using the Renal Beneficiary Utilization System files and the
CMS Institutional Inpatient Analytic Files
Population  n=289,210 patients initiating maintenance dialysis (use of dialysis for 90 days) between
1996-2001; followed until the end of 2003
 Medicare claims used to define pneumonia and cardiovascular events
 Mean age: 63.8 years
 Hemodialysis: 90.4%; peritoneal dialysis: 9.6%
Results
 Out- and inpatient pneumonia assessed – 42% of pneumonia patients hospitalized
 Within one year of dialysis, 60,610 patients (21.0%) developed pneumonia
o Overall event rate: 27.9/100 patient-years
o Hospitalized for treatment: 11.8/100 patient-years
o ↑ rates in hemo- vs. peritoneal dialysis (29.0 vs. 18.2/100 patient-years)
 Organism identified in 15.6% of cases: 4.01% gram-negative, 4.73% gram-positive
Gram-Negatives (% of culture-positive)
Gram-Positives (% of culture-positive)
P. aeruginosa: 1.19% (7.6%)
S. pneumoniae: 2.56% (16.4%)
K. pneumoniae: 1.06% (6.8%)
Staphylococcus sp: 1.73% (11.1%)
H. influenzae: 0.47% (3.0%)
Other Streptococcus: 0.43% (2.8%)
E. coli: 0.23% (1.5%)
Author’s
 The disease burden and mortality of pneumonia in dialysis patients should encourage
Comments
practitioners to ensure preventative measures in patients (vaccinations).
 Pneumonia was identified through administrative claims, meaning that a substantial
number of pneumonias may have occurred after admission for another serious illness.
o This may affect the spectrum of pathogens and the ability to show a direct
causal link between pneumonia and death.
 D’Agata et al 200043 – hospital-acquired infections among chronic hemodialysis patients
 Single-center matched case-control study of dialysis and non-dialysis patients
 N=47 nosocomial infections (from 578 dialysis patient admissions)
 Most common infection site/type: 1) urinary tract; 2) bloodstream; 3) pneumonia
 Dialysis patients with identified pneumonia pathogen, n=5  too small to consider
 What about MRSA?
 No studies of pneumonia in dialysis provide information on S. aureus resistance
 Dialysis patients  higher risk of invasive MRSA infection vs. general population44
o 2005 data – 45.2/1,000 vs. 0.2-0.4/1,000, dialysis vs. general pop., respectively
 Surveillance data from the Active Bacterial Core (ABC) system (2005 data)44
o Dialysis patients  15.6% of invasive MRSA infections (813/5,287 isolates)
 MRSA colonization rates in dialysis patients – variable, ranging from 2-22%45-48
 The Bottom Line
 Considering the frequency of pneumonia and its associated mortality in dialysis
patients, there is little data regarding epidemiology, risk factors, and pathogens.
 Bacterial etiology is crudely-defined with no information on MRSA, making it difficult
to make any meaningful conclusions that might influence therapy.
 As HCAP criteria, dialysis seems to be included more by convention than evidence.
14
 Home Healthcare
 Size of cohort
Study
Home Healthcare Patients
12
Kollef 2005 (HCAP, n=988)
13
Carratalà 2007 (HCAP, n=126)
14
17
Micek 2007 / Shorr 2008 (HCAP, n=431)
15
Venditti 2009 (HCAP, n=90)
16
Shindo 2009 (HCAP, n=141)
Not included
18 (14.3%)
Not included
Not included
3 (2.1%)
 Key Points
 Home healthcare includes processes such as the receipt of home intravenous
therapy, home wound care, or specialized nursing care (e.g., catheter changes)
 No epidemiological data specifically on pneumonia risk factors/pathogens/outcomes
 Evidence-based review – one study of MRSA infections in home nursing care patients
Lescure F, Locher G, Eveillard M, et al. Community-acquired infection with healthcare-associated
methicillin-resistant Staphylococcus aureus: the role of home nursing care. Infect Control Hosp
20
Epidemiol 2006;27(11):1213-18.
Design
 Single-center prospective case-control study (France), April 2002 – July 2003
Population  n=396  cases, n=198; controls, n=198; included patients with positive sample for
S. aureus w/in 48h of admission (cases = MRSA infection; controls = MSSA infection)
 Sites of infection  1) skin/soft tissue (38.5%), 2) respiratory tract (27.3%),
3) urinary tract (17.2%), 4) blood (9.8%), 5) other (7.2%)
Results
Characteristic
Cases (n=175) Controls (n=173) P-value
Age, years; mean ± SD
67 ± 18
57 ± 20
<0.001
Prior hospitalization, 3y (%)
85.1
67.6
<0.001
Home nursing care, 3y (%)
65.1
42.2
<0.001
Nursing procedures, 3y (mean ± SD)
192 ± 302
102 ± 2332
0.002
Healthcare worker in family (%)
8.1
7.0
0.70
Transfer from another facility (%)
24.6
11.6
0.002
Antibiotic use, 6 mos. (%)
52.6
42.8
0.07
 Positive relationship between home nursing procedures and MRSA infection
 Independent risk factors for MRSA infection on hospital admission (OR, 95% CI)
o Prior hospitalization (3.8, 1.8-7.9)
o Home nursing care (3.7, 2.0-6.7)
o Home care or hosp. for surgery, past 3y (3.1, 1.2-8.0)
o Referral [other hospital, nursing home] (2.3, 1.2-4.3)
o Age >65y (1.6, 1.1-2.5)
Author’s
 Recognized risk factors (prior hosp, nursing home) are confirmed for MRSA in this study.
Comments  Presence and duration of home nursing care are associated with S. aureus resistance;
indirect contact with healthcare workers (e.g., a family member) is not.
 Infection control procedures (e.g., hand washing) should be reinforced among
community healthcare workers.
 The Bottom Line
 Home healthcare accounts for a small subset of the studied HCAP cohorts, and there
is little information on its epidemiology in pneumonia.
 Limited evidence demonstrates an association between home healthcare and the
risk of MRSA infection/carriage, potentially related to the number of procedures by
and/or carriage among community healthcare worker.20, 49
15
 Immunosuppression
 Size of cohort
Study
Kollef 2005 (HCAP, n=988)
Carratalà 2007 (HCAP, n=126)
Micek 2007 / Shorr 2008 (HCAP, n=431)
Venditti 2009 (HCAP, n=90)
Shindo 2009 (HCAP, n=141)
Immunosuppressed Patients
Not included
Not included
169 (39.2%)
Not included
Not included
 Diverse group of patients in HCAP studies14, 17  includes:
 Seropositivity for human immunodeficiency virus (HIV)
 Radiation or chemotherapy for underlying malignancy within 6 months
 Receipt of either solid organ transplant or bone marrow transplant
 Daily administration of corticosteroids (≥5mg/day of prednisone or equivalent)
 Use of other immunosuppressive agent (e.g., cyclosporine)
 Acquired immune deficiency disorders
 Seropositivity for HIV
 Increased incidence of bacterial pneumonia among HIV-positive patients50
o HIV pts vs. non-HIV pts, 5.5 vs. 0.9 episodes per 100 person-years (p<0.001)
 Similar to non-HIV patients with regards to most common pathogens and treatment
o S. pneumoniae and Haemophilus sp. are most common51-58
o Treatment in accordance with 2007 ATS/IDSA CAP guidelines58
 In contrast to non-HIV population, increased incidence of pneumonia due to
community-acquired P. aeruginosa and S. aureus54, 56, 59-61
o Pseudomonas pneumonia: 2-18% in HIV-infected patients51, 53-56, 59, 60, 62, 63
 Often associated with low CD4 count51, 54, 60, 61, 63
o Lack of data on MRSA pneumonia in HIV-infected patients
 Active Malignancy / Chemotherapy
 Multiple groups within this population:
o Host factors: non-neutropenic vs. neutropenic w/o fever vs. febrile neutropenia
o Disease factors: type of malignancy, active/recent chemotherapy
 Where is the data?25
o No evidence in non-neutropenic cancer patients on the potential effect of
chemotherapy, increased healthcare contact, or simply cancer itself on
pneumonia epidemiology
 Reasonable to treat as CAP according to 2007 ATS/IDSA guidelines 1, 64
o Febrile neutropenia – treat according to established National Comprehensive
Cancer Network (NCCN) guidelines64
 Pseudomonas coverage recommended65, 66
16
 The Bottom Line
 Immunosuppression is not part of the HCAP criteria set forth by the ATS/IDSA in the
2005 HCAP/HAP/VAP guidelines; however, it has been included as HCAP criteria in
some studies.
 Two of the groups, HIV-positive patients and patients with active malignancies, are
diverse groups within themselves. Disease-specific characteristics (e.g., CD4 count in
HIV, febrile neutropenia in cancer) should be considered before making treatment
decisions.
REFINING THE HCAP CRITERIA
Based on the available evidence, should ________ be part
of the HCAP criteria?
Previous hospitalization
 Previous 3 months
 Previous 6 months
 Previous 12 months
Residence in a nursing home / long-term care facility:
 Poor functional status
Chronic hemodialysis
Home healthcare
Immunosuppression:
 HIV seropositivity
 Active malignancy / chemotherapy
*ICU admission
*Prior antibiotic therapy (any)
 Broad-spectrum antibiotic therapy, 3 months
Yes
No
Unclear
X
X
X
X
X
X
X
X
X
X
X
X
X
X
* Not covered explicitly in presentation – extrapolated from data.
The BIRP Criteria – Patients at high risk for drug-resistant pneumonia:
 Broad-spectrum antibiotic therapy, 3 months
 Intensive care unit (ICU) admission
 Residence in a nursing home/LTCF and poor functional status
 Prior hospitalization, 3 months
17
CONCLUSIONS
 The current evidence in HCAP is limited; however, these data have influenced practice
guidelines and have major implications for empiric antibiotic therapy.
 Current HCAP criteria are broad and may be imprecise in predicting the risk of an infection
with a drug-resistant pathogen.
 Aside from nursing home-acquired pneumonia, evidence is scarce for pneumonia patients
with each individual risk factor.
 Evidence that further defines the relationship between treatment strategies and outcomes
is essential to improve the care of HCAP patients.
 The difficulty of refining the HCAP criteria is in making the criteria simple yet specific
enough that a clinician can gather the required information and develop an appropriate
treatment plan in a timely manner.
18
ABBREVIATIONS





























ACCP: American College of Clinical Pharmacy
ADL: Activities of daily living
APACHE: Acute Physiologic and Chronic Health Evaluation
ATS: American Thoracic Society
CAP: Community-acquired pneumonia
CDC: Centers for Disease Control and Prevention
COPD: Chronic obstructive pulmonary disease
CURB: Confusion – urea – respiration – blood pressure
ECOG: Eastern Cooperative Oncology Group
ESBL: Extended-spectrum beta-lactamase
ESCP: European Society of Clinical Pharmacy
GNR: Gram-negative rod
GNB: Gram-negative bacilli
HAP: Hospital-acquired pneumonia
HD: Hemodialysis
HIV: Human Immunodeficiency Virus
ICAAC: International Conference on Antimicrobial Agents and Chemotherapy
IDSA: Infectious Diseases Society of America
LOS: Length of stay
MDR: Multi-drug resistant
MRSA: Methicillin-resistant Staphylococcus aureus
NHAP: Nursing home-acquired pneumonia
PD: Peritoneal dialysis
PDR: Potentially drug resistant
PSI: Pneumonia Severity Index
TTCS: Time to clinical stability
TTST: Time to switch therapy
USRDS: United States Renal Data System
WHO: World Health Organization
19
APPENDIX A: RISK FACTORS FOR MRSA COLONIZATION
Table 1: Previous Hospitalization as a Risk Factor for MRSA Colonization, by Study
Study
Warshawsky 2000
(n=331)
68
Hori 2002
(n=342)
Hidron 2005
(n=726)
Outcome Measure
Independent Risk Factors (OR, 95% CI)
Colonization (nares, groin);
Infection (urinary tract,
surgical wound, skin ulcer,
lower resp tract)
Inpatient or outpatient contact with healthcare facility:
Previous month: 90.6%
Previous 3 months: 96.7%
Previous 6 months: 97.0%
Previous 12 months: 98.2%
*Note: Logistic regression not performed.
Exposure to ciprofloxacin (17.06, 2.91- 99.90)
Exposure to ampicillin (4.10, 1.28-13.14)
Prior hospitalization, 1 mo. (1.82, 0.62-5.38) [p=0.278]
HIV (+) w/o antibiotics in past 3 mos. (13.81, 4.34-43.04)
Hospitalization, past year (4.01, 1.97-8.15)
Skin or soft-tissue infection at admission (3.40, 1.46-7.90)
HIV (-) w/anitibiotic use in past 3 mos. (2.46, 1.20-5.03)
Alternative housing (2.03, 0.97-4.27)
Recent hospitalization, 3 mos. (5.4, 1.53-19.03)
Gastrointestinal diseases (2.74, 1.32-5.70)
LTCF admission, past year (6.47, 1.97-21.18)
Hospitalization, past year (4.06, 1.13-14.61)
Mean age (1.04, 1.00-1.08)
Malignancy (6.4, 2.5-16.4)
≥3 antibiotic treatments, 12 mos. (4.0 (1.7-9.9)
Recent hospitalization, 12 mos. (2.2, 1.0-4.4)
Presence of household members <age 7 (2.24, 1.53-3.29)
Antibiotic use, past year (2.05, 1.35-3.11)
Hospitalization, past year (1.46, p=0.3609)
Colonization;
Nasal swabs
69
Colonization;
Nasal swab
70
Lu 2005
(n=2,231)
71
Casas 2007
(n=1,127)
Brugnaro 2009
(n=551)
Wang 2009
(n=3,098)
67
73
Colonization;
Nasal swab
Colonization;
Nasal swab
72
Colonization
(long-term care patients);
Nasal swab
Colonization with MRSA or
MSSA;
Nasal swab
20
APPENDIX B: MEASURES OF FUNCTIONAL STATUS
Table 1: Eastern Cooperative Oncology Group (ECOG) Performance Status74
Grade
0
1
2
3
4
5
ECOG













Fully active
Able to carry on all pre-disease performance without restriction
Restricted in physically strenuous activity
Ambulatory and able to carry out work of a light or sedentary nature (light house work, office work)
Ambulatory and capable of all self-care
Unable to carry out any work activities
Up and about more than 50% of waking hours
Capable of only limited self-care
Confined to bed or chair >50% of waking hours
Completely disabled
Cannot carry on any self-care
Totally confined to bed or chair
Dead
Table 2: The Barthel Index (BI)75
Activity
Feeding
Bathing
Grooming
Dressing
Bowels
Bladder
Toilet Use
Transfers (Bed to Chair)
Mobility (level surfaces)
Stairs
Score
0
5
10
0
5
0
5
0
5
10
0
5
10
0
5
10
0
5
10
0
5
10
15
0
5
10
15
0
5
10
Index Description
Unable
Needs help cutting, spreading butter, etc., or requires modified diet
Independent
Dependent
Independent (or in shower)
Needs help with personal care
Independent face/hair/teeth/shaving (implements provided)
Dependent
Needs help but can do about half unaided
Independent (including buttons, zips, laces, etc.)
Incontinent (or needs to be given enemas)
Occasional accident
Continent
Incontinent, or catheterized and unable to manage alone
Occasional accident
Continent
Dependent
Needs some help, but can do something alone
Independent (on and off, dressing, wiping)
Dependent
Major help (one or two people, physical), can sit
Minor help (verbal or physical)
Independent
Immobile or <50 yards
Wheelchair independent, including corners, >50 yards
Walks with help of one person (verbal or physical) >50 yards
Independent (but may use any aid; for example, stick) >50 yards
Unable
Needs help (verbal, physical, carrying aid)
Independent
21
Table 3: Karnofsky Performance Status76, 77
Definition
Scale
Able to carry on normal activity and
to work. No special care is needed.
100
Normal; no complaints; no evidence of disease.
90
Able to carry on normal activity; minor signs or symptoms of
disease.
Normal activity with effort; some signs or symptoms of disease.
80
Unable to work. Able to live at
home, care for most personal
needs. A varying amount of
assistance is needed.
Unable to care for self. Requires
equivalent of institutional or
hospital care. Disease may be
progressing rapidly.
70
Index Description
50
Cares for self. Unable to carry on normal activity or do active
work.
Requires occasional assistance, but is able to care for most of his
needs.
Requires considerable assistance and frequent medical care.
40
Disable; requires special care and assistance.
30
10
Severely disabled; hospitalization indicated although death not
imminent.
Very sick; hospitalization necessary; active supportive treatment
necessary.
Moribund; fatal processes progressing rapidly.
0
Dead.
60
20
Table 4: Activities of Daily Living (ADL) score (from New York State Dept of Health)28, 78
Area of Activity
Eating
Toileting
Feeding
Bathing
Mobility
Continence
Score
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
Index Description
Fully independent
Partially independent
Completely dependent
Fully independent
Partially independent
Completely dependent
Fully independent
Partially independent
Completely dependent
Fully independent
Partially independent
Completely dependent
Fully independent
Partially independent
Completely dependent
Fully independent
Partially independent
Completely dependent
ADL Class (Score): ADL I (6-8); ADL II (9-13); ADL III (14-18)
22
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