Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

S1 to S18: All supplementary material.

Domaine:

healthcare

Type de record:

papermodel
Créateur:
CarPetDavGor
Hôte:avatar

Background

Uneven vaccination and less resilient health care systems mean hospitals in LMICs are at risk of being overwhelmed during periods of increased COVID-19 infection. Risk-scores proposed for rapid triage of need for admission from the emergency department (ED) have been developed in higher-income settings during initial waves of the pandemic.

Methods

Routinely collected data for public hospitals in the Western Cape, South Africa from the 27th August 2020 to 11th March 2022 were used to derive a cohort of 446,084 ED patients with suspected COVID-19. The primary outcome was death or ICU admission at 30 days. The cohort was divided into derivation and Omicron variant validation sets. We developed the LMIC-PRIEST score based on the coefficients from multivariable analysis in the derivation cohort and existing triage practices. We externally validated accuracy in the Omicron period and a UK cohort.

Results

We analysed 305,564 derivation, 140,520 Omicron and 12,610 UK validation cases. Over 100 events per predictor parameter were modelled. Multivariable analyses identified eight predictor variables retained across models. We used these findings and clinical judgement to develop a score based on South African Triage Early Warning Scores and also included age, sex, oxygen saturation, inspired oxygen, diabetes and heart disease. The LMIC-PRIEST score achieved C-statistics: 0.82 (95% CI: 0.82 to 0.83) development cohort; 0.79 (95% CI: 0.78 to 0.80) Omicron cohort; and 0.79 (95% CI: 0.79 to 0.80) UK cohort. Differences in prevalence of outcomes led to imperfect calibration in external validation. However, use of the score at thresholds of three or less would allow identification of very low-risk patients (NPV ≥0.99) who could be rapidly discharged using information collected at initial assessment.

Conclusion

The LMIC-PRIEST score shows good discrimination and high sensitivity at lower thresholds and can be used to rapidly identify low-risk patients in LMIC ED settings.

Visit

figshare.com

Tags

MedicineBiotechnologyDevelopmental BiologyScience PolicyInfectious DiseasesVirologyroutinely collected datanpv &# 8805externally validated accuracyalso included age+35

Licenses

CC BY 4.0

Similaires

Supplementary Material S1 - Seroprevalence of Pertussis in Senegal: A Prospective StudySupplementary Data S1: 1000 Hotels<p>Supplementary material.</p>Supplementary Material for NOTA GuidelinesSupplementary Material SM 1-7Supplementary Material S1 - The Impact of the New WHO Antiretroviral Treatment Guidelines on HIV Epidemic Dynamics and Cost in South Africa

Supplementary Material S1 - Seroprevalence of Pertussis in Senegal: A Prospective Study

Individual changes in anti-PT IgG responses over time according to age at first visit in all v

Supplementary Data S1: 1000 Hotels

The dataset for this study comprises detailed records from 1,000 economy hotel chain projects across

<p>Supplementary material.</p>

Background

High incidence rates of HIV, sexually transmitted infections (STIs), and te

Supplementary Material for NOTA Guidelines

These are supplementary information about the NOTA Guidelines, a set of rules for transcribing Tunis

Supplementary Material SM 1-7

SM 1 FATE : CapEx Learning Case Series Feminisation, agricultural transition and rural employment

Supplementary Material S1 - The Impact of the New WHO Antiretroviral Treatment Guidelines on HIV Epidemic Dynamics and Cost in South Africa

Detailed description of model and quantification.

(DOC)