This paper is in the following e-collection/theme issue:

Non-Randomized Studies (funded, eHealth) (105) JMIR Theme Issue: COVID-19 Special Issue (2452) Electronic Health Records (1053) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1517) Clinical Information and Decision Making (1407) Outbreak and Pandemic Preparedness and Management (1727) Infectious Diseases (non-STD/STI) (1575) Theme Issue: Medical Informatics and COVID-19 (107) Development and Evaluation of Research Methods, Instruments and Tools (481)

Published on in Vol 10, No 5 (2021): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/29072, first published .
Predicting Risk of Hospital Admission in Patients With Suspected COVID-19 in a Community Setting: Protocol for Development and Validation of a Multivariate Risk Prediction Tool

Predicting Risk of Hospital Admission in Patients With Suspected COVID-19 in a Community Setting: Protocol for Development and Validation of a Multivariate Risk Prediction Tool

Predicting Risk of Hospital Admission in Patients With Suspected COVID-19 in a Community Setting: Protocol for Development and Validation of a Multivariate Risk Prediction Tool

Authors of this article:

Ana Belen Espinosa-Gonzalez1 Author Orcid Image ;   Ana Luisa Neves2, 3 Author Orcid Image ;   Francesca Fiorentino1 Author Orcid Image ;   Denys Prociuk1 Author Orcid Image ;   Laiba Husain4 Author Orcid Image ;   Sonny Christian Ramtale1 Author Orcid Image ;   Emma Mi1 Author Orcid Image ;   Ella Mi1 Author Orcid Image ;   Jack Macartney4 Author Orcid Image ;   Sneha N Anand4 Author Orcid Image ;   Julian Sherlock4 Author Orcid Image ;   Kavitha Saravanakumar5 Author Orcid Image ;   Erik Mayer1 Author Orcid Image ;   Simon de Lusignan4 Author Orcid Image ;   Trisha Greenhalgh4 Author Orcid Image ;   Brendan C Delaney1 Author Orcid Image
Article Authors Cited by (8) Tweetations (86) Metrics

Journals

  1. Fiorentino F, Prociuk D, Espinosa Gonzalez A, Neves A, Husain L, Ramtale S, Mi E, Mi E, Macartney J, Anand S, Sherlock J, Saravanakumar K, Mayer E, de Lusignan S, Greenhalgh T, Delaney B. An Early Warning Risk Prediction Tool (RECAP-V1) for Patients Diagnosed With COVID-19: Protocol for a Statistical Analysis Plan. JMIR Research Protocols 2021;10(10):e30083 View
  2. Knight S, Harrison E. Risk stratification of patients with COVID-19 in the community. The Lancet Digital Health 2022;4(9):e628 View
  3. Campbell T, Wilson M, Roder H, MaWhinney S, Georgantas R, Maguire L, Roder J, Erlandson K. Predicting prognosis in COVID-19 patients using machine learning and readily available clinical data. International Journal of Medical Informatics 2021;155:104594 View
  4. Espinosa-Gonzalez A, Prociuk D, Fiorentino F, Ramtale C, Mi E, Mi E, Glampson B, Neves A, Okusi C, Husain L, Macartney J, Brown M, Browne B, Warren C, Chowla R, Heaversedge J, Greenhalgh T, de Lusignan S, Mayer E, Delaney B. Remote COVID-19 Assessment in Primary Care (RECAP) risk prediction tool: derivation and real-world validation studies. The Lancet Digital Health 2022;4(9):e646 View
  5. Meza-Torres B, Delanerolle G, Okusi C, Mayor N, Anand S, Macartney J, Gatenby P, Glampson B, Chapman M, Curcin V, Mayer E, Joy M, Greenhalgh T, Delaney B, de Lusignan S. Differences in Clinical Presentation With Long COVID After Community and Hospital Infection and Associations With All-Cause Mortality: English Sentinel Network Database Study. JMIR Public Health and Surveillance 2022;8(8):e37668 View
  6. Mayor N, Meza-Torres B, Okusi C, Delanerolle G, Chapman M, Wang W, Anand S, Feher M, Macartney J, Byford R, Joy M, Gatenby P, Curcin V, Greenhalgh T, Delaney B, de Lusignan S. Developing a Long COVID Phenotype for Postacute COVID-19 in a National Primary Care Sentinel Cohort: Observational Retrospective Database Analysis. JMIR Public Health and Surveillance 2022;8(8):e36989 View
  7. Le Thi T, Tran T, Phan T. Deep Learning Using Context Vectors to Identify Implicit Aspects. IEEE Access 2023;11:39385 View
  8. Oh T, Song I. Deterioration in Quality of Life among COVID-19 Survivors: Population-Based Cohort Study. Journal of Personalized Medicine 2024;14(6):569 View