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首页> 外文期刊>Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine >The predictive value of variables measurable in the ambulance and the development of the Predict Sepsis screening tools: a prospective cohort study
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The predictive value of variables measurable in the ambulance and the development of the Predict Sepsis screening tools: a prospective cohort study

机译:救护车中可测量的变量的预测值和预测败血症筛查工具的开发:一个潜在的队列研究

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摘要

Despite sepsis being a time critical condition with a high mortality, it is often not identified in a timely fashion. The aim of the current study was to create a screening tool based on bedside measurable variables predictive of sepsis among ambulance patients with infection according to clinical judgment by ambulance personnel. Prospective cohort study of 551 adult patients presenting with suspected infection, performed in the ambulance setting of Stockholm during 2017–2018. 18 variables were measured in the ambulance (8 keywords related to medical history, 6 vital signs, 4 point-of-care blood tests, in addition to age, gender, and comorbidity. Logistic regression, area under the curve (AUC) and classification trees were used to study the association with sepsis. The AUC, sensitivity, specificity, predictive values and likelihood ratios were used to evaluate the predictive ability of sepsis screening models. The six variables with the strongest association with sepsis were: systolic blood pressure?≤?100?mmHg, temperature??38.5?°C, GCS 4?mmol/L, gastrointestinal symptoms, and a history of acute altered mental status. These were combined into the Predict Sepsis screening tool 1, with a sensitivity of 0.90, specificity 0.41, AUC 0.77; 95% confidence interval [CI] 0.73–0.81, PPV 0.52, and NPV 0.86. Combining a history of acute altered mental status with GCS 38.5?°C, GCS 4?mmol/L, gastrointestinal symptoms, and a history of acute altered mental status demonstrated the strongest association with sepsis. We present three screening tools to predict sepsis with similar sensitivity. The results indicated no noticeable increase of predictive ability by including symptom-variables and blood tests to a sepsis screening tool in the current study population. NCT03249597.
机译:尽管败血症是一种患有高死亡率的时间关键条件,但它通常不会及时识别。目前研究的目的是根据救护车人员根据临床判断,基于床头患者的床侧可测量变量预测败血症患者的筛选工具。 551例患有疑似感染患者的前瞻性队列研究,2017 - 2018年斯德哥尔摩救护车设置。在救护车中测量了18个变量(与病史有关的8个关键词,6个生命体征,除了年龄,性别和合并症外,还有4个护理验血。物流回归,曲线下的面积(AUC)和分类树木用于研究与败血症的关联。使用AUC,敏感性,特异性,预测值和似然比来评估败血症筛查模型的预测能力。与败血症最强关联的六个变量是:收缩压?≤ ?100?mmHg,温度?>?38.5?°C,GCS 4?mmol / L,胃肠道症状和急性改变精神状态的历史。将它们组合到预测败血症筛选工具1中,灵敏度为0.90,特异性0.41,AUC 0.77; 95%置信区间[CI] 0.73-0.81,PPV 0.52和NPV 0.86。将急性改变的精神状态的历史与GCS 38.5℃,GCS 4?Mmol / L,胃肠道症状组合急性改变的心理状况证明的历史与败血症的最强烈关联。我们提出了三种筛选工具,以预测具有相似敏感性的败血症。结果表明,通过将症状变量和血液检测到目前的研究人群中的败血症筛查工具,没有明显增加预测能力。 nct03249597。

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