首页> 外文期刊>JAMA: the Journal of the American Medical Association >Prediction of critical illness during out-of-hospital emergency care.
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Prediction of critical illness during out-of-hospital emergency care.

机译:院外急救期间重大疾病的预测。

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CONTEXT: Early identification of nontrauma patients in need of critical care services in the emergency setting may improve triage decisions and facilitate regionalization of critical care. OBJECTIVES: To determine the out-of-hospital clinical predictors of critical illness and to characterize the performance of a simple score for out-of-hospital prediction of development of critical illness during hospitalization. DESIGN AND SETTING: Population-based cohort study of an emergency medical services (EMS) system in greater King County, Washington (excluding metropolitan Seattle), that transports to 16 receiving facilities. PATIENTS: Nontrauma, non-cardiac arrest adult patients transported to a hospital by King County EMS from 2002 through 2006. Eligible records with complete data (N = 144,913) were linked to hospital discharge data and randomly split into development (n = 87,266 [60%]) and validation (n = 57,647 [40%]) cohorts. MAIN OUTCOME MEASURE: Development of critical illness, defined as severe sepsis, delivery of mechanical ventilation, or death during hospitalization. RESULTS: Critical illness occurred during hospitalization in 5% of the development (n = 4835) and validation (n = 3121) cohorts. Multivariable predictors of critical illness included older age, lower systolic blood pressure, abnormal respiratory rate, lower Glasgow Coma Scale score, lower pulse oximetry, and nursing home residence during out-of-hospital care (P < .01 for all). When applying a summary critical illness prediction score to the validation cohort (range, 0-8), the area under the receiver operating characteristic curve was 0.77 (95% confidence interval [CI], 0.76-0.78), with satisfactory calibration slope (1.0). Using a score threshold of 4 or higher, sensitivity was 0.22 (95% CI, 0.20-0.23), specificity was 0.98 (95% CI, 0.98-0.98), positive likelihood ratio was 9.8 (95% CI, 8.9-10.6), and negative likelihood ratio was 0.80 (95% CI, 0.79- 0.82). A threshold of 1 or greater for critical illness improved sensitivity (0.98; 95% CI, 0.97-0.98) but reduced specificity (0.17; 95% CI, 0.17-0.17). CONCLUSIONS: In a population-based cohort, the score on a prediction rule using out-of-hospital factors was significantly associated with the development of critical illness during hospitalization. This score requires external validation in an independent population.
机译:背景:在紧急情况下及早发现需要重症监护服务的非创伤性患者,可能会改善分诊决策并促进重症监护的区域化。目的:确定危重病的院外临床预测指标,并表征住院期间危重病发展的院外预测的简单评分的表现。设计与地点:华盛顿大金县(不包括西雅图市)的紧急医疗服务(EMS)系统的人口队列研究,该系统运送到16个接收设施。患者:2002年至2006年间由金县EMS运送到医院的非创伤,非心脏骤停的成年患者。具有完整数据(N = 144,913)的合格记录与医院出院数据相关,并随机分为发展阶段(n = 87,266 [60 %]和验证(n = 57,647 [40%])队列。主要观察指标:严重疾病的发展,定义为严重败血症,机械通气或住院期间死亡。结果:在住院期间,有5%的发育严重性疾病(n = 4835)和确诊(n = 3121)队列发生。重大疾病的多变量预测因素包括年龄较大,收缩压降低,呼吸频率异常,格拉斯哥昏迷量表评分降低,脉搏血氧饱和度降低以及院外护理期间的疗养院住所(全部P <0.01)。将汇总的重大疾病预测得分应用于验证队列(范围0-8)时,接收器工作特征曲线下的面积为0.77(95%置信区间[CI],0.76-0.78),校准斜率令人满意(1.0) )。使用4分或更高的得分阈值,敏感性为0.22(95%CI,0.90-0.23),特异性为0.98(95%CI,0.98-0.98),阳性可能性比为9.8(95%CI,8.9-10.6),负似然比为0.80(95%CI,0.79-0.82)。严重疾病的阈值1或更高可提高敏感性(0.98; 95%CI,0.97-0.98),但特异性降低(0.17; 95%CI,0.17-0.17)。结论:在以人群为基础的队列中,使用医院外因素的预测规则得分与住院期间危重疾病的发生显着相关。此分数需要在独立人群中进行外部验证。

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