ArticleNPJ digital medicine2020
A validated, real-time prediction model for favorable outcomes in hospitalized COVID-19 patients.
Article in NPJ digital medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.
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Who cites it
37 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Comprehensive Review of Artificial Intelligence in Prevention and Treatment of COVID-19 Pandemic.Frontiers in genetics · 2022Pooled it
- Evaluating the Effect of a COVID-19 Predictive Model to Facilitate Discharge: A Randomized Controlled Trial.Applied clinical informatics · 2022Trial
- Electronic Phenotype for Detection, Staging, and Subtyping of Acute Kidney Injury.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2026Article
- Predicting post-liver transplant outcomes in patients with acute-on-chronic liver failure using Expert-Augmented Machine Learning.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2023Article
- Development and validation of the COVID-19 Hospitalized Patient Deterioration Index.The American journal of managed care · 2023Observational
- Development and validation of a parsimonious prediction model for positive urine cultures in outpatient visits.PLOS digital health · 2023Article
- MultiCOVID: a multi modal deep learning approach for COVID-19 diagnosis.Scientific reports · 2023Article
- A Survey of COVID-19 Diagnosis Using Routine Blood Tests with the Aid of Artificial Intelligence Techniques.Diagnostics (Basel, Switzerland) · 2023Review
- DIET: Conditional independence testing with marginal dependence measures of residual information.Proceedings of machine learning research · 2023Article
- Entering the new digital era of intensive care medicine: an overview of interdisciplinary approaches to use artificial intelligence for patients' benefit.European journal of anaesthesiology and intensive care · 2023Article
- Unraveling complex relationships between COVID-19 risk factors using machine learning based models for predicting mortality of hospitalized patients and identification of high-risk group: a large retrospective study.Frontiers in medicine · 2023Article
- A Multifaceted benchmarking of synthetic electronic health record generation models.Nature communications · 2022Article
- Development and validation of self-monitoring auto-updating prognostic models of survival for hospitalized COVID-19 patients.Nature communications · 2022Article
- COVID-19 machine learning model predicts outcomes in older patients from various European countries, between pandemic waves, and in a cohort of Asian, African, and American patients.PLOS digital health · 2022Article
- Using EHR data to identify coronavirus infections in hospitalized patients: Impact of case definitions on disease surveillance.International journal of medical informatics · 2022Article
- Preparing for the next pandemic via transfer learning from existing diseases with hierarchical multi-modal BERT: a study on COVID-19 outcome prediction.Scientific reports · 2022Article
- A Scalable Risk-Scoring System Based on Consumer-Grade Wearables for Inpatients With COVID-19: Statistical Analysis and Model Development.JMIR formative research · 2022Article
- Recurrent neural network models (CovRNN) for predicting outcomes of patients with COVID-19 on admission to hospital: model development and validation using electronic health record data.The Lancet. Digital health · 2022Article
- A multicenter evaluation of computable phenotyping approaches for SARS-CoV-2 infection and COVID-19 hospitalizations.NPJ digital medicine · 2022Article
- Early identification of patients admitted to hospital for covid-19 at risk of clinical deterioration: model development and multisite external validation study.BMJ (Clinical research ed.) · 2022Article
Corrections and comments
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Authors and funding
24 authors.
Funding
Abstract
The COVID-19 pandemic has challenged front-line clinical decision-making, leading to numerous published prognostic tools. However, few models have been prospectively validated and none report implementation in practice. Here, we use 3345 retrospective and 474 prospective hospitalizations to develop and validate a parsimonious model to identify patients with favorable outcomes within 96 h of a prediction, based on real-time lab values, vital signs, and oxygen support variables. In retrospective and prospective validation, the model achieves high average precision (88.6% 95% CI: [88.4-88.7] and 90.8% [90.8-90.8]) and discrimination (95.1% [95.1-95.2] and 86.8% [86.8-86.9]) respectively. We implemented and integrated the model into the EHR, achieving a positive predictive value of 93.3% with 41% sensitivity. Preliminary results suggest clinicians are adopting these scores into their clinical workflows.
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