ArticlePeerJ2020
Identification of risk factors for mortality associated with COVID-19.
Article in PeerJ, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Serum hydroxybutyrate dehydrogenase and COVID-19 severity and mortality: a systematic review and meta-analysis with meta-regression.Clinical and experimental medicine · 2022Pooled it
- Role of Galanin system and insulin resistance parameters as predictive tools for diagnosis of Long-COVID patients.Biochemistry and biophysics reports · 2025Article
- A new parallel multi-objective Harris hawk algorithm for predicting the mortality of COVID-19 patients.PeerJ. Computer science · 2023Article
- A bibliometric analysis of the application of artificial intelligence to advance individualized diagnosis and treatment of critical illness.Annals of translational medicine · 2022Article
- Interleukin-29 profiles in COVID-19 patients: Survival is associated with IL-29 levels.Health science reports · 2022Article
- Associations of pre-existing cardiovascular morbidity with severity and the fatality rate in COVID-19 patients: a systematic review and meta-analysis.Osong public health and research perspectives · 2022Article
- Retrospective Study of Aging and Sex-Specific Risk Factors of COVID-19 with Hypertension in China.Cardiovascular therapeutics · 2022Article
- Estimated pulse wave velocity (ePWV) as a potential gatekeeper for MRI-assessed PWV: a linear and deep neural network based approach in 2254 participants of the Netherlands Epidemiology of Obesity study.The international journal of cardiovascular imaging · 2022Article
- A simple nomogram for predicting infectious diseases in adult kidney transplantation recipients.Frontiers in public health · 2022Article
- SARS-CoV-2 and COVID-19: A Narrative Review.British journal of biomedical science · 2022Review
- Risk profiles for negative and positive COVID-19 hospitalized patients.Computers in biology and medicine · 2021Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesCoronavirus Disease 2019 (COVID-19) has become a pandemic outbreak. Risk stratification at hospital admission is of vital importance for medical decision making and resource allocation. There is no sophisticated tool for this purpose. This study aimed to develop neural network models with predictors selected by genetic algorithms (GA).
methodsThis study was conducted in Wuhan Third Hospital from January 2020 to March 2020. Predictors were collected on day 1 of hospital admission. The primary outcome was the vital status at hospital discharge. Predictors were selected by using GA, and neural network models were built with the cross-validation method. The final neural network models were compared with conventional logistic regression models.
resultsA total of 246 patients with COVID-19 were included for analysis. The mortality rate was 17.1% (42/246). Non-survivors were significantly older (median (IQR): 69 (57, 77) vs. 55 (41, 63) years;
conclusionsOur study included a cohort of COVID-19 patients. Several risk factors were identified considering both clinical and statistical significance. We further developed two neural network models, with the variables selected by using GA. The model performs much better than the conventional generalized linear models.
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Registered trials
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