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 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.

Oxygen use in low-resource settings: An intervention still triggered by intuition.

BACKGROUND: Although hypoxic patients attending low-resource hospitals have a high mortality, many are not given supplemental oxygen. If oximetry is not available, then the decision to provide oxygen must be based on other factors. METHODS: The variables associated with the decision to provide supplemental oxygen made by an emergency department staff, without access to oximetry, in a low resource Ugandan hospital were determined from data collected within 16 h of admission to the hospital's medical and surgical wards. RESULTS: Of 2,599 patients, 731 (28.1%) had an oxygen saturation <95%, and 164 (6.3%) an oxygen saturation <90%. Of the 731 patients with oxygen levels below 95% 573 (83%) were not given oxygen; oxygen was only given to 63 (38%) of the 164 patients with oxygen saturation <90%. On average, a patient given oxygen was more likely to die than one not given oxygen, regardless of their oxygen saturation (odds ratio 13.4, 95%CI 9.1-19.6). After multivariate analysis weakness, dyspnoea, low oxygen saturation, high heart rate, high respiratory rate, low temperature, alertness, gait, and a medical illness were all significantly associated with the use of supplemental oxygen and in-hospital mortality. Logistic regression modelling of these variables had comparable discrimination for both oxygen use (c statistic 0.88 SE 0.02) and in-hospital mortality (c statistic 0.84 SE 0.02). CONCLUSION: The intuitive decision to provide oxygen was strongly associated with in-hospital mortality, suggesting that oxygen was given to those considered the sickest patients. In the future, oximetry may guide oxygen therapy more efficiently.

Do different patient populations need different early warning scores? The performance of nine different early warning scores used on acutely ill patients admitted to a low-resource hospital in sub-Saharan Africa.

BACKGROUND: Early warning scores (EWS) generated in a developed healthcare setting may not perform as well in low-resource settings in sub-Saharan Africa. METHOD: The performance of EWS used in developed world was compared with those generated in low-resource settings in sub-Saharan Africa. RESULTS: When tested on 1,266 acutely ill patients consecutively admitted to a low-resource Ugandan hospital there was no statistical difference in the performance of any of the EWS tested. The performance of all the scores appeared to be improved by the addition of mobility assessment. Although statistically insignificant, the National Early Warning Score with extra points added for impaired mobility had the highest discrimination and sensitivity. CONCLUSION: There were only marginal and no statistical differences in the performance of EWS generated in low- and high-resource healthcare settings in a cohort of unselected acutely ill medical patients admitted to a low-resource hospital in sub-Saharan Africa.

Mobility Identifies Acutely Ill Patients at Low Risk of In-Hospital Mortality: A Prospective Multicenter Study.

BACKGROUND: A retrospective study has reported that impaired mobility on presentation (IMOP) enhanced the ability of vital signs to predict mortality in acutely ill patients. This study was designed to further examine the association between IMOP and in-hospital mortality. METHODS: Prospective observational study of three different cohorts of acutely ill patients admitted to hospitals in Esbjerg, Denmark (998 patients), Basel, Switzerland (743 patients), and Kitovu, Uganda (1,622 patients). RESULTS: There were significant differences in age, sex, length of stay, proportion of medical and surgical patients, and in-hospital mortality between the three cohorts. Yet in all three cohorts a National Early Warning Score (NEWS) ≥ 3 when first recorded and IMOP increased the risk of in-hospital mortality to approximately the same extent. IMOP and NEWS ≥ 3 when first recorded were, therefore, used for risk categorization: patients with a NEWS < 3 when first recorded and normal mobility on presentation had the lowest in-hospital mortality risk and those with NEWS ≥ 3 when first recorded and IMOP had the highest risk. The number of these low risk patients ranged from 26% in Kitovu to 42% in Esbjerg, and their in-hospital mortality rates did not significantly differ in all three cohorts, ranging from 0.2% in Esbjerg to 0.4% in Basel. CONCLUSIONS: In this prospective multicenter study IMOP enhanced the risk categorization of acutely ill patients from very different clinical settings. The combination normal mobility on presentation and first recorded NEWS identified a substantial proportion of patients in all cohorts with a low risk of dying while in hospital. TRIAL REGISTRY: The Esbjerg data were collected as part of a trial registered with the US National Library of Medicine (ClinicalTrials.gov; No.: NCT03108807; URL: www.clinicaltrials.gov).

Are changes in objective observations or the patient's subjective feelings the day after admission the best predictors of in-hospital mortality? An observational study in a low-resource sub-Saharan hospital.

BACKGROUND: The first clinical re-assessment after admission to hospital probably provides the best opportunity to detect clinical deterioration or failure to improve, and decide if care should be intensified. AIM: Compare changes the day after admission in the patient's subjective feelings and objective findings that included age, gender, the National Early Warning Score (NEWS) on admission, gait stability and mid-upper arm circumference (MUAC) on admission, and changes in NEWS, gait stability and mental alertness. SETTING: Acutely ill medical patients admitted to a low-resource sub-Saharan hospital. METHODS: Prospective observational study. RESULTS: 1810 patients were reassessed 18 h after hospital admission. Logistic regression identified NEWS and gait stability on admission, a subjective feeling of improvement, the change in NEWS, and MUAC as clinically significant predictors of in-hospital mortality. Stratifying patients according to their NEWS on admission altered the predictive value of the four other predictors: for patients with an admission NEWS < 3 a subjective feeling of improvement is the most powerful predictor of a good outcome. For patients with an admission NEWS > = 3 the change in NEWS, gait stability on admission and MUAC provide additional prognostic information. CONCLUSION: NEWS and gait stability on admission, MUAC, a subjective feeling of improvement, and change in NEWS the day after admission are all clinically significant predictors of in-hospital mortality.