The value of shock index, modified shock index and age shock index to predict mortality and hospitalisation in a district level emergency centre

休克指数、改良休克指数和年龄休克指数在预测区级急诊中心死亡率和住院率方面的价值

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Abstract

INTRODUCTION: Triage is the most important step in patients' journey through an Emergency Centre (EC) and directly impacts time to critical actions. Triage tools, like the South African Triage Scale, are however not designed to predict patient outcomes. The shock index (SI), modified shock index (MSI) and age shock index (ASI) are clinical markers derived from vital signs and correlate with tissue perfusion in critically ill patients. This study aimed to assess the value of SI, MSI and ASI to predict mortality and the need for hospitalisation in all adult patients presenting to a district level emergency centre in South Africa. METHODS: This diagnostic study was performed as a retrospective observational study, using data from an existing electronic registry at a district level hospital emergency centre over a period of 24 months. All adult patients who presented to Mitchells Plain Hospital were eligible for inclusion. Sensitivity, specificity and likelihood ratios were calculated for each variable as a predictor of mortality and hospitalisation with pre-determined thresholds. RESULTS: During the study period of 24 months, a total of 61 329 patients ≥ 18 years old presented to the EC with 60 599 included in the final sample. A red SATS triage category (+LR = 7.2) and SI ≥1.3 (+LR = 4.9) were the only two predictors with any significant clinical value. The same two markers performed well for both patients with and without trauma and specifically for patients who died while under the care of the emergency centre. DISCUSSION: The study demonstrated that patients with a SI≥1.3 at triage have a significantly higher likelihood to die or require hospitalisation, whether the presenting complaint is trauma related or not, especially to predict mortality while under the care of the EC. Incorporating this marker as a triage alert could expedite the identification of patients requiring time critical interventions and improve patient throughput in the emergency centre.

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