Development and validation of a predictive model for hospital mortality in patients with community-acquired pneumonia admitted to the intensive care unit
Objective This retrospective cohort study aimed to develop and validate a nomogram for predicting in-hospital mortality among patients with community-acquired pneumonia admitted to the intensive care unit. Methods Data of patients meeting the inclusion criteria were extracted from the Medical Inform...
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SAGE Publishing
2025-05-01
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| Series: | Journal of International Medical Research |
| Online Access: | https://doi.org/10.1177/03000605251340304 |
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| author | Xuefeng Song Qiang Zhang Zhijiang Qi Bo Liu |
| author_facet | Xuefeng Song Qiang Zhang Zhijiang Qi Bo Liu |
| author_sort | Xuefeng Song |
| collection | DOAJ |
| description | Objective This retrospective cohort study aimed to develop and validate a nomogram for predicting in-hospital mortality among patients with community-acquired pneumonia admitted to the intensive care unit. Methods Data of patients meeting the inclusion criteria were extracted from the Medical Information Mart for Intensive Care-IV database, and the patients were randomly allocated into training (n = 3798, 70%) and validation (n = 1629, 30%) cohorts. First-day intensive care unit admission parameters were averaged. Least Absolute Shrinkage and Selection Operator regression and multivariate logistic regression analyses were used to identify mortality risk factors in the training cohort, followed by nomogram construction. Model performance was evaluated based on discrimination (area under the curve), calibration (Hosmer–Lemeshow test and bootstrap resampling), and clinical utility (decision curve analysis). Data from emergency intensive care unit were used to perform external validation of the value of the model. Results In total, 5427 patients were included. Age, red cell distribution width, Sequential Organ Failure Assessment, Acute Physiology Score-III, blood urea nitrogen-to-serum creatinine ratio, anion gap, osmolarity, and sepsis were identified as independent risk factors for hospital mortality. The nomogram demonstrated superior discrimination compared with Sequential Organ Failure Assessment and Acute Physiology Score-III in the validation (area under the curve: 0.772 vs. 0.685–0.724) and training (area under the curve: 0.787 vs. 0.708–0.740; p < 0.05) sets. Calibration and decision curve analyses confirmed robust performance (Hosmer–Lemeshow p = 0.11; net benefit threshold: 20%–80%). In both cohorts, calibration and decision curve analyses showed that the nomogram had good calibration degree, discriminative ability, and clinical benefits. Data from emergency intensive care unit showed that the area under the curve of the model was 0.7864 (95% confidence interval, 0.76–0.81), area under the curve of Sequential Organ Failure Assessment was 0.7217 (95% confidence interval, 0.69–0.75), and area under the curve of Acute Physiology Score-III was 0.7055 (95% confidence interval, 0.68–0.73). Conclusions This nomogram provides moderate predictive accuracy for hospital mortality in critically ill patients with community-acquired pneumonia and may aid prognosis assessment. |
| format | Article |
| id | doaj-art-cb4b62c03d0d40168fd78886eeb7b96f |
| institution | DOAJ |
| issn | 1473-2300 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Journal of International Medical Research |
| spelling | doaj-art-cb4b62c03d0d40168fd78886eeb7b96f2025-08-20T03:13:36ZengSAGE PublishingJournal of International Medical Research1473-23002025-05-015310.1177/03000605251340304Development and validation of a predictive model for hospital mortality in patients with community-acquired pneumonia admitted to the intensive care unitXuefeng SongQiang ZhangZhijiang QiBo LiuObjective This retrospective cohort study aimed to develop and validate a nomogram for predicting in-hospital mortality among patients with community-acquired pneumonia admitted to the intensive care unit. Methods Data of patients meeting the inclusion criteria were extracted from the Medical Information Mart for Intensive Care-IV database, and the patients were randomly allocated into training (n = 3798, 70%) and validation (n = 1629, 30%) cohorts. First-day intensive care unit admission parameters were averaged. Least Absolute Shrinkage and Selection Operator regression and multivariate logistic regression analyses were used to identify mortality risk factors in the training cohort, followed by nomogram construction. Model performance was evaluated based on discrimination (area under the curve), calibration (Hosmer–Lemeshow test and bootstrap resampling), and clinical utility (decision curve analysis). Data from emergency intensive care unit were used to perform external validation of the value of the model. Results In total, 5427 patients were included. Age, red cell distribution width, Sequential Organ Failure Assessment, Acute Physiology Score-III, blood urea nitrogen-to-serum creatinine ratio, anion gap, osmolarity, and sepsis were identified as independent risk factors for hospital mortality. The nomogram demonstrated superior discrimination compared with Sequential Organ Failure Assessment and Acute Physiology Score-III in the validation (area under the curve: 0.772 vs. 0.685–0.724) and training (area under the curve: 0.787 vs. 0.708–0.740; p < 0.05) sets. Calibration and decision curve analyses confirmed robust performance (Hosmer–Lemeshow p = 0.11; net benefit threshold: 20%–80%). In both cohorts, calibration and decision curve analyses showed that the nomogram had good calibration degree, discriminative ability, and clinical benefits. Data from emergency intensive care unit showed that the area under the curve of the model was 0.7864 (95% confidence interval, 0.76–0.81), area under the curve of Sequential Organ Failure Assessment was 0.7217 (95% confidence interval, 0.69–0.75), and area under the curve of Acute Physiology Score-III was 0.7055 (95% confidence interval, 0.68–0.73). Conclusions This nomogram provides moderate predictive accuracy for hospital mortality in critically ill patients with community-acquired pneumonia and may aid prognosis assessment.https://doi.org/10.1177/03000605251340304 |
| spellingShingle | Xuefeng Song Qiang Zhang Zhijiang Qi Bo Liu Development and validation of a predictive model for hospital mortality in patients with community-acquired pneumonia admitted to the intensive care unit Journal of International Medical Research |
| title | Development and validation of a predictive model for hospital mortality in patients with community-acquired pneumonia admitted to the intensive care unit |
| title_full | Development and validation of a predictive model for hospital mortality in patients with community-acquired pneumonia admitted to the intensive care unit |
| title_fullStr | Development and validation of a predictive model for hospital mortality in patients with community-acquired pneumonia admitted to the intensive care unit |
| title_full_unstemmed | Development and validation of a predictive model for hospital mortality in patients with community-acquired pneumonia admitted to the intensive care unit |
| title_short | Development and validation of a predictive model for hospital mortality in patients with community-acquired pneumonia admitted to the intensive care unit |
| title_sort | development and validation of a predictive model for hospital mortality in patients with community acquired pneumonia admitted to the intensive care unit |
| url | https://doi.org/10.1177/03000605251340304 |
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