ArticlePloS one2021
Can predicting COVID-19 mortality in a European cohort using only demographic and comorbidity data surpass age-based prediction: An externally validated study.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Article
- Is there still hesitancy towards SARS-CoV-2 vaccination among people with neurological disease- a survey of the NeuroCOVID-19 task force of the European Academy of Neurology.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025Article
- Using artificial intelligence and predictive modelling to enable learning healthcare systems (LHS) for pandemic preparedness.Computational and structural biotechnology journal · 2024Review
- Predicting the COVID-19 mortality among Iranian patients using tree-based models: A cross-sectional study.Health science reports · 2023Article
- Factors associated with covid-19 deaths in the city of Recife, Pernambuco, Brazil, 2020: a cross-sectional study with "Notifique Aqui" system data.Epidemiologia e servicos de saude : revista do Sistema Unico de Saude do Brasil · 2023Article
- A predictive model for hospitalization and survival to COVID-19 in a retrospective population-based study.Scientific reports · 2022Article
- COVID-19: Clinical features, case fatality, and the effect of symptoms on mortality in hospitalized cases in Iran.Journal of Taibah University Medical Sciences · 2022Article
- Predictive Value of Sequential Organ Failure Assessment, Quick Sequential Organ Failure Assessment, Acute Physiology and Chronic Health Evaluation II, and New Early Warning Signs Scores Estimate Mortality of COVID-19 Patients Requiring Intensive Care Unit.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2022Article
- Long-term clinical follow-up of patients suffering from moderate-to-severe COVID-19 infection: a monocentric prospective observational cohort study.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2021Observational
- Age differences in the association of comorbid burden with adverse outcomes in SARS-CoV-2.BMC geriatrics · 2021Article
- Association of Frailty with Adverse Outcomes in Patients with Suspected COVID-19 Infection.Journal of clinical medicine · 2021Article
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24 authors.
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No grant is acknowledged in the PubMed record.
Abstract
objectiveTo establish whether one can build a mortality prediction model for COVID-19 patients based solely on demographics and comorbidity data that outperforms age alone. Such a model could be a precursor to implementing smart lockdowns and vaccine distribution strategies.
methodsThe training cohort comprised 2337 COVID-19 inpatients from nine hospitals in The Netherlands. The clinical outcome was death within 21 days of being discharged. The features were derived from electronic health records collected during admission. Three feature selection methods were used: LASSO, univariate using a novel metric, and pairwise (age being half of each pair). 478 patients from Belgium were used to test the model. All modeling attempts were compared against an age-only model.
resultsIn the training cohort, the mortality group's median age was 77 years (interquartile range = 70-83), higher than the non-mortality group (median = 65, IQR = 55-75). The incidence of former/active smokers, male gender, hypertension, diabetes, dementia, cancer, chronic obstructive pulmonary disease, chronic cardiac disease, chronic neurological disease, and chronic kidney disease was higher in the mortality group. All stated differences were statistically significant after Bonferroni correction. LASSO selected eight features, novel univariate chose five, and pairwise chose none. No model was able to surpass an age-only model in the external validation set, where age had an AUC of 0.85 and a balanced accuracy of 0.77.
conclusionWhen applied to an external validation set, we found that an age-only mortality model outperformed all modeling attempts (curated on www.covid19risk.ai) using three feature selection methods on 22 demographic and comorbid features.
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