Department of Internal Medicine, Victoria Hospital, Candos, Mauritius.
Chin J Traumatol. 2024 Mar;27(2):77-82. doi: 10.1016/j.cjtee.2023.09.001. Epub 2023 Sep 4.
To investigate which scoring system is the most accurate tool in predicting mortality among the infected patients who present to the emergency department in a middle-income country, and to validate a new scoring system to predict bacterial infections.
This was a retrospective, single-center study among patients who were admitted via the emergency department of a public hospital. All patients who were started on antibiotics were included in the study, while patients aged < 18 years were excluded. Data collected includeding patients' demographics, vital signs and basic laboratory parameters like white blood cell count and creatinine. The sensitivity and specificity of different scoring systems were calculated as well as their negative and positive predictive values. Logistic regression was used to derive a novel early warning system for bacterial infections. The area under the receiver operating characteristic (AUROC) was computed for each scoring model.
In total, 109 patients were included in this study. The quick sequential organ failure assessment (qSOFA), search out severity and rapid acute physiology score had the highest AUROC (≥ 0.89) for predicting mortality, while qSOFA and universal vital assessment were the simplest scoring systems with an AUROC > 0.85; however, these scoring systems failed to predict whether patients were truly infected. The INFECTIONS (short for impaired mental status, not conscious, fast heart rate, elevated creatinine, high temperature, on inotrope, low oxygen, high neutrophils and high sugar) model reached an AUROC of 0.88 to more accurately predict the infectious state of a patient.
Middle-income countries should use the qSOFA or universal vital assessment score to identify the sickest patients in emergency department. The INFECTIONS score may help recognize patients with bacterial infections, but it should be further validated in multiple countries prior to widely use.
研究在中低收入国家的急诊科就诊的感染患者中,哪种评分系统是预测死亡率最准确的工具,并验证一种新的评分系统来预测细菌感染。
这是一项回顾性、单中心研究,纳入了一家公立医院急诊科收治的患者。所有接受抗生素治疗的患者均纳入研究,而年龄<18 岁的患者被排除在外。收集的数据包括患者的人口统计学特征、生命体征和基本实验室参数,如白细胞计数和肌酐。计算了不同评分系统的敏感性和特异性及其阴性和阳性预测值。使用逻辑回归得出一种新的细菌感染预警系统。计算了每个评分模型的接收者操作特征曲线下面积(AUROC)。
共有 109 例患者纳入本研究。快速序贯器官衰竭评估(qSOFA)、搜索严重程度和快速急性生理学评分(RAPS)对预测死亡率的 AUROC 最高(≥0.89),而 qSOFA 和通用生命评估是最简单的评分系统,AUROC>0.85;然而,这些评分系统无法预测患者是否真正感染。感染(IMPACTED,代表精神状态受损、无意识、心率快、肌酐升高、体温高、使用正性肌力药、氧合不足、中性粒细胞高、血糖高)评分模型的 AUROC 达到 0.88,可更准确地预测患者的感染状态。
中低收入国家应使用 qSOFA 或通用生命评估评分来识别急诊科最病重的患者。感染评分可能有助于识别细菌感染患者,但在广泛应用之前,应在多个国家进一步验证。