ArticleAnnals of medicine2024
Establishment and validation of a prognostic model based on common laboratory indicators for SARS-CoV-2 infection in Chinese population.
Article in Annals of medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Construction of a risk prediction model for severe community-acquired pneumonia in children in Qinghai region.BMJ paediatrics open · 2026Review
- Algorithms for appropriate patient stratification in the face of a new SARS-CoV-2 pandemic.Immunity & ageing : I & A · 2025Article
- In-depth analysis of the risk factors for persistent severe acute respiratory syndrome coronavirus 2 infection and construction of predictive models: an exploratory research study.BMC infectious diseases · 2025Article
- Nomogram-based model to predict prognosis in anisometropic amblyopia.Frontiers in medicine · 2025Article
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7 authors.
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Abstract
backgroundAt the beginning of December 2022, the Chinese government made major adjustments to the epidemic prevention and control measures. The epidemic infection data and laboratory makers for infected patients based on this period may help with the management and prognostication of COVID-19 patients.
methodsThe COVID-19 patients hospitalized during December 2022 were enrolled. Logistic regression analysis was used to screen significant factors associated with mortality in patients with COVID-19. Candidate variables were screened by LASSO and stepwise logistic regression methods and were used to construct logistic regression as the prognostic model. The performance of the models was evaluated by discrimination, calibration, and net benefit.
results888 patients were eligible, consisting of 715 survivors and 173 all-cause deaths. Factors significantly associated with mortality in COVID-19 patients were: lactate dehydrogenase (LDH), albumin (ALB), procalcitonin (PCT), age, smoking history, malignancy history, high density lipoprotein cholesterol (HDL-C), lactate, vaccine status and urea. 335 of the 888 eligible patients were defined as ICU cases. Seven predictors, including neutrophil to lymphocyte ratio, D-dimer, PCT, C-reactive protein, ALB, bicarbonate, and LDH, were finally selected to establish the prognostic model and generate a nomogram. The area under the curve of the receiver operating curve in the training and validation cohorts were respectively 0.842 and 0.853. In terms of calibration, predicted probabilities and observed proportions displayed high agreements. Decision curve analysis showed high clinical net benefit in the risk threshold of 0.10-0.85. A cutoff value of 81.220 was determined to predict the outcome of COVID-19 patients
conclusionsThe laboratory model established in this study showed high discrimination, calibration, and net benefit. It may be used for early identification of severe patients with COVID-19.
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