ArticleInternal and emergency medicine2018
Predictive modeling of inpatient mortality in departments of internal medicine.
Article in Internal and emergency medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Postoperative Hypoalbuminemia as a Predictor of Early Mortality After Cementless Hemiarthroplasty for Hip Fractures.Medicina (Kaunas, Lithuania) · 2025Article
- Comparing Single-Hospital and National Models to Predict 30-Day Inpatient Mortality.Journal of general internal medicine · 2025Article
- Concurrent prediction of in-hospital mortality and length of stay using single-task, multiclass and multitask machine learning.BMJ digital health & AI · 2025Article
- Machine Learning for Targeted Advance Care Planning in Cancer Patients: A Quality Improvement Study.Journal of pain and symptom management · 2024Article
- Article
- Risk Prediction Models for Hospital Mortality in General Medical Patients: A Systematic Review.American journal of medicine open · 2023Article
- Do prior neurological comorbidities predict COVID-19 severity and death? A 25-month cross-sectional multicenter study on 7370 patients.Acta neurologica Belgica · 2023Article
- The Norton scale is an important predictor of in-hospital mortality in internal medicine patients.Irish journal of medical science · 2023Article
- Rate and risk factors of in-hospital and early post-discharge mortality in patients admitted to an internal medicine ward.Clinical medicine (London, England) · 2023Article
- Comparing Outcomes of Critically Ill Patients in Intensive Care Units and General Wards: A Comprehensive Analysis.International journal of general medicine · 2023Article
- Relevant vs non-relevant subspecialist for patients hospitalised in internal medicine at a local hospital: which is better? A retrospective cohort study.BMC health services research · 2022Article
- Palliative Care Exposure Relative to Predicted Risk of Six-Month Mortality in Hospitalized Adults.Journal of pain and symptom management · 2022Article
- Towards accurate prediction of patient length of stay at emergency department: a GAN-driven deep learning framework.Journal of ambient intelligence and humanized computing · 2022Article
- An Optimized Machine Learning Model Accurately Predicts In-Hospital Outcomes at Admission to a Cardiac Unit.Diagnostics (Basel, Switzerland) · 2022Article
- Hypoalbuminemia as Surrogate and Culprit of Infections.International journal of molecular sciences · 2021Review
- Factors Associated with In-Hospital Mortality in Acute Care Hospital Settings: A Prospective Observational Study.International journal of environmental research and public health · 2020Observational
- Development and validation of a machine learning-based prediction model for near-term in-hospital mortality among patients with COVID-19.BMJ supportive & palliative care · 2020Article
- Padua prediction score and IMPROVE score do predict in-hospital mortality in Internal Medicine patients.Internal and emergency medicine · 2020Article
- Prediction of general medical admission length of stay with natural language processing and deep learning: a pilot study.Internal and emergency medicine · 2020Article
- Prospective and External Evaluation of a Machine Learning Model to Predict In-Hospital Mortality of Adults at Time of Admission.JAMA network open · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite overwhelming data on predictors of inpatient mortality, it is unclear which variables are the most instructive in predicting mortality of patients in departments of internal medicine. This study aims to identify the most informative predictors of inpatient mortality, and builds a prediction model on an individual level, given a constellation of patient characteristics. We use a penalized method for developing the prediction model by applying the least-absolute-shrinkage and selection-operator regression. We utilize a cohort of adult patients admitted to any of 5 departments of internal medicine during 3.5 years. We integrated data from electronic health records that included clinical, epidemiological, administrative, and laboratory variables. The prediction model was evaluated using the validation sample. Of 10,788 patients hospitalized during the study period, 874 (8.1%) died during admission. We find that the strongest predictors of inpatient mortality are prior admission within 3 months, malignant morbidity, serum creatinine levels, and hypoalbuminemia at hospital admission, and an admitting diagnosis of sepsis, pneumonia, malignant neoplastic disease, or cerebrovascular disease. The C-statistic of the risk prediction model is 89.4% (95% CI 88.4-90.4%). The predictive performance of this model is better than a multivariate stepwise logistic regression model. By utilizing the prediction model, the AUC for the independent (validation) data set is 85.7% (95% CI 84.1-87.3%). Using penalized regression, this prediction model identifies the most informative predictors of inpatient mortality. The model illustrates the potential value and feasibility of a tool that can aid physicians in decision-making.
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