BACKGROUND: The association of hospitalization because of community-acquired pneumonia (CAP) and long-term survival has not been fully examined. We measured the long-term survival of hospitalized patients with CAP adjusted for the effects of comorbidities. METHODS: A cohort of adult patients admitted to the medical services of the Veterans Affairs Medical Center, Louisville, Kentucky, was retrospectively examined. A Kaplan-Meier survival curve was constructed to assess the effect of CAP admission status on patient survival. A Cox proportional hazards regression model included comorbidities as predictors and time to death as the outcome in the construction of a modified Charlson Comorbidity Index (mCCI). The mCCI was internally validated to evaluate the predictability of patient survival. The mCCI and age > 65 years were included as potential confounders in a final Cox proportional hazards regression model with CAP admission status as the main predictor and time to death as the outcome. RESULTS: CAP was identified in 624 (9%) out of 6,971 patients. The Kaplan-Meier survival curve showed a significantly shorter survival among patients with CAP than those without CAP (P < .0001). The internal validation of the mCCI showed that patients were more likely to die as the mCCI increased (P < .0001). The Cox proportional hazards regression modeling the association between time to death and CAP admission after adjusting for elderly age and the mCCI showed that hospitalization due to CAP was a statistically significant predictor of decreased survival (hazard ratio, 1.4; 95% CI, 1.2-1.5; P < .0001). CONCLUSION: There is a decreased long-term survival among hospitalized patients with CAP after adjusting for comorbidities and aging. Future research to understand the pathophysiology of the long-term CAP outcomes is necessary to develop treatment strategies.
BACKGROUND: The association of hospitalization because of community-acquired pneumonia (CAP) and long-term survival has not been fully examined. We measured the long-term survival of hospitalized patients with CAP adjusted for the effects of comorbidities. METHODS: A cohort of adult patients admitted to the medical services of the Veterans Affairs Medical Center, Louisville, Kentucky, was retrospectively examined. A Kaplan-Meier survival curve was constructed to assess the effect of CAP admission status on patient survival. A Cox proportional hazards regression model included comorbidities as predictors and time to death as the outcome in the construction of a modified Charlson Comorbidity Index (mCCI). The mCCI was internally validated to evaluate the predictability of patient survival. The mCCI and age > 65 years were included as potential confounders in a final Cox proportional hazards regression model with CAP admission status as the main predictor and time to death as the outcome. RESULTS:CAP was identified in 624 (9%) out of 6,971 patients. The Kaplan-Meier survival curve showed a significantly shorter survival among patients with CAP than those without CAP (P < .0001). The internal validation of the mCCI showed that patients were more likely to die as the mCCI increased (P < .0001). The Cox proportional hazards regression modeling the association between time to death and CAP admission after adjusting for elderly age and the mCCI showed that hospitalization due to CAP was a statistically significant predictor of decreased survival (hazard ratio, 1.4; 95% CI, 1.2-1.5; P < .0001). CONCLUSION: There is a decreased long-term survival among hospitalized patients with CAP after adjusting for comorbidities and aging. Future research to understand the pathophysiology of the long-term CAP outcomes is necessary to develop treatment strategies.
Authors: Grèce Saba; Luiz Flavio Andrade; Jacques Gaillat; Pierre Bonnin; Christian Chidiac; Hajnal-Gabriela Illes; Henri Laurichesse; Jonathan Messika; Jean-Damien Ricard; Bruno Detournay; Patrick Petitpretz; Gérard de Pouvourville Journal: Eur J Health Econ Date: 2017-05-25
Authors: Timothy L Wiemken; Ruth M Carrico; Stephen P Furmanek; Brian E Guinn; William A Mattingly; Paula Peyrani; Julio A Ramirez Journal: Public Health Rep Date: 2020-03-31 Impact factor: 2.792