{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T09:03:28Z","timestamp":1785488608537,"version":"3.56.0"},"reference-count":26,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T00:00:00Z","timestamp":1785456000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Medicina"],"abstract":"<jats:p>Background and Objectives: Early identification of patients at high risk of death after COVID-19 hospitalization may support monitoring, follow-up planning and resource allocation. We aimed to develop and internally validate a parsimonious admission laboratory-based model for six-month all-cause mortality and derive a simplified risk score. Materials and Methods: This retrospective single-center cohort included 1827 consecutive adults hospitalized with COVID-19 between 3 March and 6 November 2020. The primary model was developed in 1559 patients with complete predictor data after data-quality review. Prespecified predictors were age, albumin, neutrophil-to-lymphocyte ratio, blood urea nitrogen, lactate dehydrogenase, troponin I and sodium. Model performance was assessed using discrimination and calibration measures, 500-sample bootstrap internal validation and a chronological split-sample assessment in later admissions from the same center; this was internal\u2013temporal rather than external validation. The simplified score was derived exclusively in the chronological development cohort and applied unchanged to the later cohort. Results: Among 1827 eligible patients, 437 died within six months (23.9%). The primary complete-case modeling cohort included 1559 patients, of whom 386 died. Older age, lower albumin and higher neutrophil-to-lymphocyte ratio, blood urea nitrogen, lactate dehydrogenase, troponin I and sodium were independently associated with mortality. The model achieved an apparent AUC of 0.936 (95% CI 0.919\u20130.954) and an optimism-corrected AUC of 0.933. The later same-center cohort yielded an AUC of 0.908 (95% CI 0.871\u20130.939). The development-derived simplified score had an AUC of 0.927 (95% CI 0.909\u20130.943) in the development cohort and 0.916 (95% CI 0.885\u20130.944) when applied unchanged to the later cohort. Conclusions: A model combining age with six routinely available admission laboratory variables showed strong discrimination for six-month all-cause mortality after COVID-19 hospitalization and retained good discrimination in single-center temporal assessment. However, calibration drift was observed, and the model and simplified score should currently be considered supportive risk-stratification frameworks rather than deployable stand-alone clinical calculators. External validation, contemporary recalibration and prospective assessment of clinical utility are required before implementation.<\/jats:p>","DOI":"10.3390\/medicina62081478","type":"journal-article","created":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T08:46:41Z","timestamp":1785487601000},"page":"1478","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Admission Laboratory-Based Prediction of Six-Month Mortality After COVID-19 Hospitalization: Model Development, Bootstrap Internal Validation, and Single-Center Temporal Validation"],"prefix":"10.3390","volume":"62","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9000-4851","authenticated-orcid":false,"given":"Onur","family":"\u00c7elik","sequence":"first","affiliation":[{"name":"Department of Pulmonary Medicine, Erzurum Faculty of Medicine, University of Health Sciences, 25240 Erzurum, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Oktay","family":"G\u00fclc\u00fc","sequence":"additional","affiliation":[{"name":"Department of Cardiology, Faculty of Medicine, Atat\u00fcrk University, 25240 Erzurum, T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,7,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1054","DOI":"10.1016\/S0140-6736(20)30566-3","article-title":"Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: A retrospective cohort study","volume":"395","author":"Zhou","year":"2020","journal-title":"Lancet"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1239","DOI":"10.1001\/jama.2020.2648","article-title":"Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China","volume":"323","author":"Wu","year":"2020","journal-title":"JAMA"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2052","DOI":"10.1001\/jama.2020.6775","article-title":"Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area","volume":"323","author":"Richardson","year":"2020","journal-title":"JAMA"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"106433","DOI":"10.1016\/j.rmed.2021.106433","article-title":"The predictors of COVID-19 mortality in a nationwide cohort of Turkish patients","volume":"183","author":"Kul","year":"2021","journal-title":"Respir. 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