ArticleJournal of cellular and molecular medicine2022
Genetic prediction of ICU hospitalization and mortality in COVID-19 patients using artificial neural networks.
Article in Journal of cellular and molecular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Mixture of experts extra tree-based sEMG hand gesture recognition.Scientific reports · 2026Article
- Predicting the severity of COVID-19 using machine learning methods.BMC medical informatics and decision making · 2026Article
- Research on predicting risk factors for re-bleeding in the acute phase of intracerebral hemorrhage using machine learning algorithms.Frontiers in medicine · 2026Article
- Magnetic Resonance Imaging Radiomics-Driven Artificial Neural Network Model for Advanced Glioma Grading Assessment.Medicina (Kaunas, Lithuania) · 2025Article
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- Common Genetic Variants in Rare Disorders: Hematology and Beyond.Current issues in molecular biology · 2025Article
- Unraveling the pathogenic interplay between SARS-CoV-2 and polycystic ovary syndrome using bioinformatics and experimental validation.Scientific reports · 2024Article
- Prediction of optical properties of rare-earth doped phosphate glasses using gene expression programming.Scientific reports · 2024Article
- Correlation between Genomic Variants and Worldwide COVID-19 Epidemiology.Journal of personalized medicine · 2024Article
- Next-generation sequencing of host genetics risk factors associated with COVID-19 severity and long-COVID in Colombian population.Scientific reports · 2024Article
- Association between loss of hypercoagulable phenotype, clinical features and complement pathway consumption in COVID-19.Frontiers in immunology · 2024Observational
- Artificial intelligence for diagnosis of mild-moderate COVID-19 using haematological markers.Annals of medicine · 2023Article
- Development of a population-level prediction model for intensive care unit (ICU) survivorship and mortality in older adults: A population-based cohort study.Health science reports · 2023Article
- Predicting intensive care need for COVID-19 patients using deep learning on chest radiography.Journal of medical imaging (Bellingham, Wash.) · 2023Article
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- Accurate prediction of dynamic viscosity of polyalpha-olefin boron nitride nanofluids using machine learning.Heliyon · 2023Article
- Multi-omic Profiling Reveals Early Immunological Indicators for Identifying COVID-19 Progressors.bioRxiv : the preprint server for biology · 2023Article
- Complement and COVID-19: Three years on, what we know, what we don't know, and what we ought to know.Immunobiology · 2023Review
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- Hybridizing five neural-metaheuristic paradigms to predict the pillar stress in bord and pillar method.Frontiers in public health · 2023Article
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Authors and funding
41 authors.
Funding
Abstract
There is an unmet need of models for early prediction of morbidity and mortality of Coronavirus disease-19 (COVID-19). We aimed to a) identify complement-related genetic variants associated with the clinical outcomes of ICU hospitalization and death, b) develop an artificial neural network (ANN) predicting these outcomes and c) validate whether complement-related variants are associated with an impaired complement phenotype. We prospectively recruited consecutive adult patients of Caucasian origin, hospitalized due to COVID-19. Through targeted next-generation sequencing, we identified variants in complement factor H/CFH, CFB, CFH-related, CFD, CD55, C3, C5, CFI, CD46, thrombomodulin/THBD, and A Disintegrin and Metalloproteinase with Thrombospondin motifs (ADAMTS13). Among 381 variants in 133 patients, we identified 5 critical variants associated with severe COVID-19: rs2547438 (C3), rs2250656 (C3), rs1042580 (THBD), rs800292 (CFH) and rs414628 (CFHR1). Using age, gender and presence or absence of each variant, we developed an ANN predicting morbidity and mortality in 89.47% of the examined population. Furthermore, THBD and C3a levels were significantly increased in severe COVID-19 patients and those harbouring relevant variants. Thus, we reveal for the first time an ANN accurately predicting ICU hospitalization and death in COVID-19 patients, based on genetic variants in complement genes, age and gender. Importantly, we confirm that genetic dysregulation is associated with impaired complement phenotype.
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