ArticleBMC pulmonary medicine2018
Six underlying health conditions strongly influence mortality based on pneumonia severity in an ageing population of Japan: a prospective cohort study.
Article in BMC pulmonary medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Utility of pneumonia severity assessment tools for mortality prediction in healthcare-associated pneumonia: a systematic review and meta-analysis.Scientific reports · 2024Pooled it
- Prognostic factors of poor outcomes in pneumonia in older adults: aspiration or frailty?European geriatric medicine · 2024Article
- Microbiological Profile of Patients with Aspiration Pneumonia Identified by Combined Detection Methods.Infection and drug resistance · 2024Article
- Poor Social Functioning: A Potentially Modifiable Risk Factor for Pneumonia in the Elderly.Cureus · 2023Article
- Prognostic value of geriatric nutritional risk index for aspiration pneumonia: a retrospective observational cohort study.Aging clinical and experimental research · 2022Observational
- A literature review of severity scores for adults with influenza or community-acquired pneumonia - implications for influenza vaccines and therapeutics.Human vaccines & immunotherapeutics · 2021Review
- Prognostic value of chest computed tomography in community-acquired pneumonia patients.ERJ open research · 2020Article
- Prognostic Prediction Value of qSOFA, SOFA, and Admission Lactate in Septic Patients with Community-Acquired Pneumonia in Emergency Department.Emergency medicine international · 2020Article
- Observational
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14 authors.
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Abstract
backgroundMortality prediction of pneumonia by severity scores in patients with multiple underlying health conditions has not fully been investigated. This prospective cohort study is to identify mortality-associated underlying health conditions and to analyse their influence on severity-based pneumonia mortality prediction.
methodsAdult patients with community-acquired pneumonia or healthcare-associated pneumonia (HCAP) who visited four community hospitals between September 2011 and January 2013 were enrolled. Candidate underlying health conditions, including demographic and clinical characteristics, were incorporated into the logistic regression models, along with CURB (confusion, elevated urea nitrogen, tachypnoea, and hypotension) score as a measure of disease severity. The areas under the receiver operating characteristic curves (AUROC) of the predictive index based on significant underlying health conditions was compared to that of CURB65 (CURB and age ≥ 65) score or Pneumonia severity index (PSI). Mortality association between disease severity and the number of underlying health conditions was analysed.
resultsIn total 1772 patients were eligible for analysis, of which 140 (7.9%) died within 30 days. Six underlying health conditions were independently associated: home care (adjusted odds ratio, 5.84; 95% confidence interval, CI, 2.28-14.99), recent hospitalization (2.21; 1.36-3.60), age ≥ 85 years (2.15; 1.08-4.28), low body mass index (1.99, 1.25-3.16), neoplastic disease (1.82; 1.17-2.85), and male gender (1.78; 1.16-2.75). The predictive index based on these conditions alone had a significantly or marginally higher AUROC than that based on CURB65 score (0.78 vs 0.66, p = 0.02) or PSI (0.78 vs 0.71, p = 0.05), respectively. Compared to this index, the AUROC of the total score consisting of six underlying health conditions and CURB score (range 0-10) did not improve mortality predictions (p = 0.3). In patients with one or less underlying health conditions, the mortality was discretely associated with severe pneumonia (CURB65 ≥ 3) (risk ratio: 7.24, 95%CI: 3.08-25.13), whereas in patients with 2 or more underlying health conditions, the mortality association with severe pneumonia was not detected (risk ratio: 1.53, 95% CI: 0.94-2.50).
conclusionsMortality prediction based on pneumonia severity scores is highly influenced by the accumulating number of underlying health conditions in an ageing society. The validation using a different cohort is necessary to generalise the conclusion.
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