Article

Predictive accuracy of the pneumonia severity index vs CRB-65 for time to clinical stability: Results from the Community-Acquired Pneumonia Organization (CAPO) International Cohort Study

University of Louisville, School of Medicine, Department of Medicine, Division of Infectious Diseases, Louisville, KY 40202, USA.
Respiratory medicine (Impact Factor: 2.92). 11/2010; 104(11):1736-43. DOI: 10.1016/j.rmed.2010.05.022
Source: PubMed

ABSTRACT The Pneumonia Severity Index (PSI) and CRB-65 are scores used to predict mortality in patients with community-acquired pneumonia (CAP). It is unknown how well either score predicts time to clinical stability in hospitalized patients with CAP. Thus, it is also not known which score predicts time to clinical stability better.
A secondary analysis of 3087 patients from the Community-Acquired Pneumonia Organization (CAPO) database was performed. Time-dependent receiver-operator characteristic (ROC) curves for time to clinical stability were calculated for the PSI and CRB-65 scores at day seven of hospitalization. Secondary outcomes were to assess the relationship of the PSI and CRB-65 to in-hospital mortality and length of stay (LOS). ROC curves for LOS and mortality were calculated.
The area under the ROC curve (AUC) for time to clinical stability by day seven was 0.638 (95% CI 0.613, 0.660) when using the PSI, and 0.647 (95% CI 0.619, 0.670) while using the CRB-65. The difference in AUC values was not statistically significant (95% CI for difference of -0.03 to 0.01). However, the difference in the AUC values for discharge within 14 days (0.651 for PSI vs 0.63 for CRB-65, 95% CI for difference 0.001-0.049), and 28-day in-hospital mortality (0.738 for PSI vs 0.69 for CRB-65, 95% CI for difference 0.02-0.082) were both statistically significant.
This study demonstrates a moderate ability of both the PSI and CRB-65 scores to predict time to clinical stability, and found that the predictive accuracy of the PSI was equivalent to that of the CRB-65 for this outcome.

Download full-text

Full-text

Available from: Guy N Brock, Aug 23, 2015
0 Followers
 · 
88 Views
  • Heart, Lung and Circulation 01/2003; 12(2). DOI:10.1046/j.1443-9506.2003.03349.x · 1.17 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Adverse outcomes after discharge in patients hospitalized for community-acquired pneumonia (CAP) might be associated with the inflammatory response during hospitalization, recognized by the length of time needed for the patient to reach clinical stability (time to clinical stability [TCS]). The objective of this study was to assess the association between TCS and outcomes after discharge in hospitalized patients with CAP. A retrospective cohort study of consecutive patients discharged alive after an episode of CAP was conducted at the Veterans Hospital of Louisville, Kentucky, between 2001 and 2006. Among the 464 patients enrolled in the study, 82 (18%) experienced an adverse outcome within 30 days after discharge, leading to either readmission or death. Patients with a TCS > 3 days showed a significantly higher rate of adverse outcomes after discharge compared with those with a TCS ≤ 3 days (26% vs 15%, respectively; OR, 1.98; 95% CI, 1.19-3.3; P = .008) as well as adverse outcomes after discharge related to pneumonia (16% vs 4.6%, respectively; OR, 4.07; 95% CI, 2-8.2; P < .001). The propensity-adjusted analysis showed that delay in reaching TCS during hospitalization was associated with a significant increased risk of adverse outcomes. Adjusted ORs comparing patients who reached TCS at days 2, 3, 4, and 5 to those who reached TCS at day 1 were 1.06, 1.54, 2.40, and 10.53, respectively. Patients with CAP who experienced a delay in reaching clinical stability during hospitalization are at high risk of adverse outcomes after discharge and should receive close observation and an early follow-up.
    Chest 02/2011; 140(2):482-8. DOI:10.1378/chest.10-2895 · 7.13 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: A large pneumonia database can be defined as one containing more than 1000 patients. Important strengths of large databases include the ability to evaluate infrequent predictor or outcome variables, and increased generalizability. Beyond analysis of the database core study, large databases facilitate secondary analysis, expansion with ancillary studies, and concurrent analysis with other databases. Computer technology is now available that is able to merge sizable databases with the objective to generate a very large database. Construction of a global, very large pneumonia database is an achievable goal that can move clinical research in pneumonia to a higher level.
    Clinics in chest medicine 09/2011; 32(3):481-9. DOI:10.1016/j.ccm.2011.05.007 · 2.17 Impact Factor
Show more