SynthesisBioMed research international2013
Risk prediction models for mortality in community-acquired pneumonia: a systematic review.
Synthesis in BioMed research international, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Predicting the Risk of Readmission in Pneumonia. A Systematic Review of Model Performance.Annals of the American Thoracic Society · 2016Pooled it
- HALP score and 30-day mortality: an observational analysis of clinical associations in Pneumonia.PeerJ · 2026Observational
- Long-term prognosis following cytomegalovirus respiratory infection in immunocompromised and immunocompetent patients: a retrospective single-centre study.BMC infectious diseases · 2025Observational
- CRB-65 for Risk Stratification and Prediction of Prognosis in Pulmonary Embolism.Journal of clinical medicine · 2023Article
- Development and validation of a new scoring system for prognostic prediction of community-acquired pneumonia in older adults.Scientific reports · 2021Article
- Clinical characteristics and in-hospital mortality of patients with COVID-19 in Chile: A prospective cohort study.International journal of clinical practice · 2021Article
- Clinical characteristics and prognostic risk factors of mortality in patients with interstitial lung diseases and viral infection: a retrospective cohort study.Journal of medical microbiology · 2021Article
- Artificial Intelligence Is Reshaping Healthcare amid COVID-19: A Review in the Context of Diagnosis & Prognosis.Diagnostics (Basel, Switzerland) · 2021Article
- Computerized Mortality Prediction for Community-acquired Pneumonia at 117 Veterans Affairs Medical Centers.Annals of the American Thoracic Society · 2021Article
- Charlson Comorbidity Index and other predictors of in-hospital mortality among adults with community-acquired pneumonia.Jornal brasileiro de pneumologia : publicacao oficial da Sociedade Brasileira de Pneumologia e Tisilogia · 2021Article
- Artificial Intelligence for clinical decision support in Critical Care, required and accelerated by COVID-19.Anaesthesia, critical care & pain medicine · 2020Article
- Article
- Comparison of pneumonia severity scores for patients diagnosed with pneumonia in emergency department.The Indian journal of medical research · 2020Article
- Six underlying health conditions strongly influence mortality based on pneumonia severity in an ageing population of Japan: a prospective cohort study.BMC pulmonary medicine · 2018Article
- Predicting 30-Day Pneumonia Readmissions Using Electronic Health Record Data.Journal of hospital medicine · 2017Observational
- Risk Prediction of One-Year Mortality in Patients with Cardiac Arrhythmias Using Random Survival Forest.Computational and mathematical methods in medicine · 2015Article
- Development of a risk-adjusted in-hospital mortality prediction model for community-acquired pneumonia: a retrospective analysis using a Japanese administrative database.BMC pulmonary medicine · 2014Article
- Review
- The Use of Guidelines for Lower Respiratory Tract Infections in Tanzania: A Lesson from Kilimanjaro Clinicians.Annals of medical and health sciences researchArticle
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSeveral models have been developed to predict the risk of mortality in community-acquired pneumonia (CAP). This study aims to systematically identify and evaluate the performance of published risk prediction models for CAP.
methodsWe searched MEDLINE, EMBASE, and Cochrane library in November 2011 for initial derivation and validation studies for models which predict pneumonia mortality. We aimed to present the comparative usefulness of their mortality prediction.
resultsWe identified 20 different published risk prediction models for mortality in CAP. Four models relied on clinical variables that could be assessed in community settings, with the two validated models BTS1 and CRB-65 showing fairly similar balanced accuracy levels (0.77 and 0.72, resp.), while CRB-65 had AUROC of 0.78. Nine models required laboratory tests in addition to clinical variables, and the best performance levels amongst the validated models were those of CURB and CURB-65 (balanced accuracy 0.73 and 0.71, resp.), with CURB-65 having an AUROC of 0.79. The PSI (AUROC 0.82) was the only validated model with good discriminative ability among the four that relied on clinical, laboratorial, and radiological variables.
conclusionsThere is no convincing evidence that other risk prediction models improve upon the well-established CURB-65 and PSI models.
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