Two simple replacements for the Triage Early Warning Score to facilitate the South African Triage Scale in low resource settings
Background: The South African Triage Scale (SATS) requires the calculation of the Triage Early Warning Score (TEWS), which takes time and is prone to error. Aim: to derive and validate triage scores from a clinical database collected in a low-resource hospital in sub-Saharan Africa over four years a...
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doaj-0f331a395a77401a9939eb35909202132021-02-21T04:33:25ZengElsevierAfrican Journal of Emergency Medicine2211-419X2021-03-011115359Two simple replacements for the Triage Early Warning Score to facilitate the South African Triage Scale in low resource settingsLucien Wasingya-Kasereka0Pauline Nabatanzi1Immaculate Nakitende2Joan Nabiryo3Teopista Namujwiga4John Kellett5Kitovu Hospital, Masaka, UgandaKitovu Hospital, Masaka, UgandaDepartment of Medicine, Kitovu Hospital, Masaka, UgandaDepartment of Medicine, Kitovu Hospital, Masaka, UgandaDepartment of Medicine, Kitovu Hospital, Masaka, UgandaDepartment of Emergency Medicine, Hospital of South West Jutland, Esbjerg, Denmark; Corresponding author at: Ballinaclough, Nenagh, County Tipperary, Ireland.Background: The South African Triage Scale (SATS) requires the calculation of the Triage Early Warning Score (TEWS), which takes time and is prone to error. Aim: to derive and validate triage scores from a clinical database collected in a low-resource hospital in sub-Saharan Africa over four years and compare them with the ability of TEWS to triage patients. Methods: A retrospective observational study carried out in Kitovu Hospital, Masaka, Uganda as part of an ongoing quality improvement project. Data collected on 4482 patients was divided into two equal cohorts: one for the derivation of scores by logistic regression and the other for their validation. Results: Two scores identified the largest number of patients with the lowest in-hospital mortality. A score based on oxygen saturation, mental status and mobility had a c statistic for discrimination of 0.83 (95% CI 0.079–0.87) in the derivation, and 0.81 (95% CI 0.77–0.86) in the validation cohort. Another score based on respiratory rate, mental status and mobility had a c statistic of 0.82 (95% CI 0.078–0.87) in the derivation, and 0.81 (95% CI 0.77–0.86) in the validation cohort. The oxygen saturation-based score of zero points identified 51% of patients in the derivation cohort who had in-hospital mortality rate of 0.5%, and 49% of patients in the validation cohort who had in-hospital mortality of 1.0%. A respiratory rate-based score of zero points identified 45% in the derivation cohort who had in-hospital mortality rate of 0.5%, and 44% of patients in the validation cohort who had in-hospital mortality of 0.8%. Both scores had comparable performance to TEWS. Conclusion: Two easy to calculate scores have comparable performance to TEWS and, therefore, could replace it to facilitate the adoption of SATS in low-resource settings.http://www.sciencedirect.com/science/article/pii/S2211419X20301440TriageLow resource settingPredictive scoresEmergency department |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Lucien Wasingya-Kasereka Pauline Nabatanzi Immaculate Nakitende Joan Nabiryo Teopista Namujwiga John Kellett |
spellingShingle |
Lucien Wasingya-Kasereka Pauline Nabatanzi Immaculate Nakitende Joan Nabiryo Teopista Namujwiga John Kellett Two simple replacements for the Triage Early Warning Score to facilitate the South African Triage Scale in low resource settings African Journal of Emergency Medicine Triage Low resource setting Predictive scores Emergency department |
author_facet |
Lucien Wasingya-Kasereka Pauline Nabatanzi Immaculate Nakitende Joan Nabiryo Teopista Namujwiga John Kellett |
author_sort |
Lucien Wasingya-Kasereka |
title |
Two simple replacements for the Triage Early Warning Score to facilitate the South African Triage Scale in low resource settings |
title_short |
Two simple replacements for the Triage Early Warning Score to facilitate the South African Triage Scale in low resource settings |
title_full |
Two simple replacements for the Triage Early Warning Score to facilitate the South African Triage Scale in low resource settings |
title_fullStr |
Two simple replacements for the Triage Early Warning Score to facilitate the South African Triage Scale in low resource settings |
title_full_unstemmed |
Two simple replacements for the Triage Early Warning Score to facilitate the South African Triage Scale in low resource settings |
title_sort |
two simple replacements for the triage early warning score to facilitate the south african triage scale in low resource settings |
publisher |
Elsevier |
series |
African Journal of Emergency Medicine |
issn |
2211-419X |
publishDate |
2021-03-01 |
description |
Background: The South African Triage Scale (SATS) requires the calculation of the Triage Early Warning Score (TEWS), which takes time and is prone to error. Aim: to derive and validate triage scores from a clinical database collected in a low-resource hospital in sub-Saharan Africa over four years and compare them with the ability of TEWS to triage patients. Methods: A retrospective observational study carried out in Kitovu Hospital, Masaka, Uganda as part of an ongoing quality improvement project. Data collected on 4482 patients was divided into two equal cohorts: one for the derivation of scores by logistic regression and the other for their validation. Results: Two scores identified the largest number of patients with the lowest in-hospital mortality. A score based on oxygen saturation, mental status and mobility had a c statistic for discrimination of 0.83 (95% CI 0.079–0.87) in the derivation, and 0.81 (95% CI 0.77–0.86) in the validation cohort. Another score based on respiratory rate, mental status and mobility had a c statistic of 0.82 (95% CI 0.078–0.87) in the derivation, and 0.81 (95% CI 0.77–0.86) in the validation cohort. The oxygen saturation-based score of zero points identified 51% of patients in the derivation cohort who had in-hospital mortality rate of 0.5%, and 49% of patients in the validation cohort who had in-hospital mortality of 1.0%. A respiratory rate-based score of zero points identified 45% in the derivation cohort who had in-hospital mortality rate of 0.5%, and 44% of patients in the validation cohort who had in-hospital mortality of 0.8%. Both scores had comparable performance to TEWS. Conclusion: Two easy to calculate scores have comparable performance to TEWS and, therefore, could replace it to facilitate the adoption of SATS in low-resource settings. |
topic |
Triage Low resource setting Predictive scores Emergency department |
url |
http://www.sciencedirect.com/science/article/pii/S2211419X20301440 |
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