OBJECTIVE: To develop a new paediatric illness severity score, called inpatient triage, assessment and treatment (ITAT), for resource-limited settings to identify hospitalised patients at highest risk of death and facilitate urgent clinical re-evaluation. METHODS: We performed a nested case-control study at a Malawian referral hospital. The ITAT score was derived from four equally weighted variables, yielding a cumulative score between 0 and 8. Variables included oxygen saturation, temperature, and age-adjusted heart and respiratory rates. We compared the ITAT score between cases (deaths) and controls (discharges) in predicting death within 2 days. Our analysis includes predictive statistics, bivariable and multivariable logistic regression, and calculation of data-driven scores. RESULTS: A total of 54 cases and 161 controls were included in the analysis. The area under the receiver operating characteristic curve was 0.76. At an ITAT cut-off of 4, the sensitivity, specificity and likelihood ratio were 0.44, 0.86 and 1.70, respectively. A cumulative ITAT score of 4 or higher was associated with increased odds of death (OR 4.80; 95% CI 2.39-9.64). A score of 2 for all individual vital signs was a statistically significant independent predictor of death. CONCLUSIONS: We developed an inpatient triage tool (ITAT) appropriate for resource-constrained hospitals that identifies high-risk children after hospital admission. Further research is needed to study how best to operationalise ITAT in developing countries.
OBJECTIVE: To develop a new paediatric illness severity score, called inpatient triage, assessment and treatment (ITAT), for resource-limited settings to identify hospitalised patients at highest risk of death and facilitate urgent clinical re-evaluation. METHODS: We performed a nested case-control study at a Malawian referral hospital. The ITAT score was derived from four equally weighted variables, yielding a cumulative score between 0 and 8. Variables included oxygen saturation, temperature, and age-adjusted heart and respiratory rates. We compared the ITAT score between cases (deaths) and controls (discharges) in predicting death within 2 days. Our analysis includes predictive statistics, bivariable and multivariable logistic regression, and calculation of data-driven scores. RESULTS: A total of 54 cases and 161 controls were included in the analysis. The area under the receiver operating characteristic curve was 0.76. At an ITAT cut-off of 4, the sensitivity, specificity and likelihood ratio were 0.44, 0.86 and 1.70, respectively. A cumulative ITAT score of 4 or higher was associated with increased odds of death (OR 4.80; 95% CI 2.39-9.64). A score of 2 for all individual vital signs was a statistically significant independent predictor of death. CONCLUSIONS: We developed an inpatient triage tool (ITAT) appropriate for resource-constrained hospitals that identifies high-risk children after hospital admission. Further research is needed to study how best to operationalise ITAT in developing countries.
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