1 25th eccmid - 2007, munich, germany magnitude of bacteremia predicts one-year mortality kim o....
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25th ECCMID - 2007, Munich, Germany 1
Magnitude of bacteremia predicts one-year mortality
Kim O. Gradel1, Henrik C. Schønheyder1,2, Mette Søgaard1, Claus Dethlefsen1, Henrik Nielsen1
1Aalborg Hospital, Aarhus University Hospital, Denmark2Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA
25th ECCMID - 2007, Munich, Germany 2
Prognostic bacteremia studies with magnitude of bacteremia
8 studies:– Old (range 1952-1995)– Few patients (range 20-464)– Often selected patient groups and bacteria– No multivariable analyses used– Only in-hospital mortality reported– Prognosis generally worsened with higher
magnitude of bacteremia
25th ECCMID - 2007, Munich, Germany 3
Study type
• One-year follow-up study
• Population based
• Registry study:– Registries linked via the personal
identification number (unique number given to all Danish residents)
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Setting
• North Jutland County, Denmark
• Background population: ~500,000 residents (~9% of Denmark’s population)
• All acutely ill patients admitted to the nearest hospital in their county
• Centralized clinical microbiology service
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Registries
• North Jutland Bacteremia Registry– Microbiological and clinical data
• Hospital Discharge Registry– Discharge diagnoses, coded by physicians
• Civil Registration System– Vital status, incl. date of emigration and
death
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Inclusion criteria
• Study period: 1996-2004
• Adults (16 years and older)
• Mono-microbial bacteremias
• First-time bacteremias
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Blood culture system, I
• BacT/Alert®
• Automatic colometric detection of CO2 produced by growing micro-organisms
• Incubation up till 7 days
• ~30 mL blood in each specimen, distributed equally in 3 bottles (2 aerobic, 1 anaerobic)
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Blood culture system, II
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Blood culture system, III
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Aims
1. Is ”Magnitude of bacteremia” (bacterial growth in 1, 2, or 3 blood culture bottles) associated with short-term and long-term all-cause mortality?
2. Is this consistent within strata:– Age– Comorbidity– Speciality (medical, surgical)
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Variables
• Primary exposure: 1, 2, or 3 bacteria positive blood culture bottles in the patient’s initial blood culture (BC) set (BC index 1 [ref.], 2, or 3)
• Outcome: All-cause mortality
• Covariates:– Age– Gender– Charlson comorbidity score– Speciality– Acquisition of infection – Focus
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6Tumor, metastaticAIDS
3Moderate/severe liver disease
2HemiplegiaDiabetes (type 1 and 2), with complicationsAny tumorLeukaemiaLymphoma
1Myocardial infarctionCongestive heart failurePeripheral vascular diseaseCerebrovascular diseaseDementiaChronic pulmonary diseaseConnective tissue diseaseUlcer diseaseMild liver diseaseDiabetes (type 1 and 2), without complications
ScoreDisease category
Charlson comorbidity index
Overall score: 1Overall score: 0Overall score: 2Overall score: 4
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Methods
• BC index distribution, overall and stratified
• Kaplan-Meier survival curve estimates, overall and stratified
• Cumulative mortality, standardized to the age and comorbidity distribution in the BC index 1 group
• Cox-regression analyses:– Crude– Adjusted, overall – Adjusted, stratified
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Study population
• 6406 patients
• 53.6% males
• Median age: 72 years
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BC index distribution
• The overall BC index distribution was U-shaped:– BC index 1: 1993 (31.1%)– BC index 2: 1174 (18.3%)– BC index 3: 3239 (50.6%)
• Generally few deviations from the overall BC index distribution within strata
• 92.5% were facultatively anaerobic
0
10
20
30
40
50
60
1 2 3
BC index
% B
C bo
ttles
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Kaplan-Meier mortality curves, all
BC index 3BC index 2BC index 1
0
10
20
30
40
50
% m
orta
lity
07 30 365Days after first-time bacteremia
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Kaplan-Meier mortality curves, medical patients (n = 3842)
BC index 3BC index 2BC index 1
0
10
20
30
40
50
% m
orta
lity
07 30 365Days after first-time bacteremia
25th ECCMID - 2007, Munich, Germany 18
Kaplan-Meier mortality curves, surgical patients (n = 1691)
BC index 3BC index 2BC index 1
0
10
20
30
40
50
% m
orta
lity
07 30 365Days after first-time bacteremia
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365-day cumulative mortality, standardized to age or
comorbidity distribution as in the BC index 1 group
All 16-64 65-80 >80 0 1-2 >20
10
20
30
40
50
60
70 BC index 1BC index 2BC index 3
Age (years) Charlson score
% m
ort
alit
y
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Cox-regression, overall results
1.4 (1.2-1.7)
1.3 (1.1-1.6)
1.3 (1.1-1.6)
0-7 days
Mortality rate ratios (95% CIs) for BC index 3 (BC index 1 = reference)
1.5 (1.2-1.8)
1.4 (1.1-1.7)
1.4 (1.1-1.7)
8-30 Days 31-365 days
1.1 (1.0-1.3)
BC index, age, gender, comorbidity, speciality, acquisition of infection, focus
1.1 (0.9-1.2)BC index, age, comorbidity
1.1 (0.9-1.2)BC index (crude)
Covariates
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Cox-regression, age groups
1.1 (0.9-1.4)1.4 (1.0-1.9)1.1 (0.8-1.4)>80
1.0 (0.8-1.2)1.6 (1.2-2.2)1.4 (1.1-1.9)65-80
1.3 (1.0-1.7)1.0 (0.6-1.5)1.5 (1.1-2.2)16-64
31-365 days8-30 Days0-7 days
Mortality rate ratios (95% CIs) for BC index 3 (BC index 1 = reference)
Age, years
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Cox-regression, comorbidity
1.0 (0.8-1.2)1.1 (0.7-1.6)1.1 (0.8-1.5)0
1.0 (0.8-1.3)1.7 (1.2-2.5)1.5 (1.1-2.0)>2
1.2 (1.0-1.5)1.4 (1.0-1.8)1.4 (1.1-1.8)1-2
31-365 days8-30 Days0-7 days
Mortality rate ratios (95% CIs) for BC index 3 (BC index 1 = reference)
Charlson score
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Strengths of the study
• Population-based
• High statistical precision
• Complete follow-up
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Limitations of the study
• “Magnitude of bacteremia” assessed by indirect (i.e., semi-quantitative) method
• Secondary data sources
• No information on severity of bacteremia (e.g., as described in the APACHE score system) or blood biochemistry parameters
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Conclusions, I
• In general, BC index 3 patients had ~4% higher one-year mortality compared to BC index 1 patients
• For medical patients, BC index 3 was a marker of short-term mortality (~0-30 days)
• For surgical patients, BC index 3 was a marker of long-term mortality (beyond ~30 days)
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Conclusions, II
• BC index was also associated with the cumulative mortality, but baseline patient characteristics (age, comorbidity) were more important
• The overall trends differed between some strata.
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Thank you!Danke!
Tak!