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Establishment of risk model for elderly CAP at different age stages: a single-center retrospective observational study.
Lv, Chunxin; Pan, Teng; Shi, Wen; Peng, Weixiong; Gao, Yue; Muhith, Abdul; Mu, Yang; Xu, Jiayi; Deng, Jinhai; Wei, Wei.
Afiliación
  • Lv C; Oncology Department, Shanghai Punan Hospital of Pudong New District, No 279, Linyi Road, Pudong, Shanghai, China.
  • Pan T; Longgang District Maternity & Child Healthcare Hospital of Shenzhen City, Shenzhen, China.
  • Shi W; Faculty of Life Sciences and Medicine, School of Cancer and Pharmaceutical Sciences, King's College London, London, UK.
  • Peng W; Department of Dermatology, Shanghai Punan Hospital of Pudong New District, No 279, Linyi Road, Shanghai, China.
  • Gao Y; Hunan Zixing Artificial Intelligence Technology Group Co., Ltd., Hunan Province, Changsha City, China.
  • Muhith A; Hunan Zixing Artificial Intelligence Technology Group Co., Ltd., Hunan Province, Changsha City, China.
  • Mu Y; Department of Oncology, Royal Marsden Hospital, London, UK.
  • Xu J; Hunan Zixing Artificial Intelligence Technology Group Co., Ltd., Hunan Province, Changsha City, China.
  • Deng J; Geriatric Department, Minhang Hospital, Fudan University, No 170, Xinsong Road, Shanghai, China.
  • Wei W; Hunan Zixing Artificial Intelligence Technology Group Co., Ltd., Hunan Province, Changsha City, China. jinhai.deng@kcl.ac.uk.
Sci Rep ; 13(1): 12432, 2023 08 01.
Article en En | MEDLINE | ID: mdl-37528213
Community-acquired pneumonia (CAP) is one of the main reasons of mortality and morbidity in elderly population, causing substantial clinical and economic impacts. However, clinically available score systems have been shown to demonstrate poor prediction of mortality for patients aged over 65. Especially, no existing clinical model can predict morbidity and mortality for CAP patients among different age stages. Here, we aimed to understand the impact of age variable on the establishment of assessment model and explored prognostic factors and new biomarkers in predicting mortality. We retrospectively analyzed elderly patients with CAP in Minhang Hospital, Fudan University. We used univariate and multiple logistic regression analyses to study the prognostic factors of mortality in each age-based subgroup. The prediction accuracy of the prognostic factors was determined by the Receiver Operating Characteristic curves and the area under the curves. Combination models were established using several logistic regressions to save the predicted probabilities. Four factors with independently prognostic significance were shared among all the groups, namely Albumin, BUN, NLR and Pulse, using univariate analysis and multiple logistic regression analysis. Then we built a model with these 4 variables (as ABNP model) to predict the in-hospital mortality in all three groups. The AUC value of the ABNP model were 0.888 (95% CI 0.854-0.917, p < 0.000), 0.912 (95% CI 0.880-0.938, p < 0.000) and 0.872 (95% CI 0.833-0.905, p < 0.000) in group 1, 2 and 3, respectively. We established a predictive model for mortality based on an age variable -specific study of elderly patients with CAP, with higher AUC value than PSI, CURB-65 and qSOFA in predicting mortality in different age groups (66-75/ 76-85/ over 85 years).
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neumonía / Infecciones Comunitarias Adquiridas Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Aged / Aged80 / Humans Idioma: En Revista: Sci Rep Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neumonía / Infecciones Comunitarias Adquiridas Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Aged / Aged80 / Humans Idioma: En Revista: Sci Rep Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Reino Unido