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Measurement of pediatric illness severity using simple pretransport variables.

机译:使用简单的运输前变量测量小儿疾病的严重程度。

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OBJECTIVE: To test the hypothesis that pretransport variables can predict in-hospital mortality that will correlate with major interventions and unplanned events during interfacility transport. METHODS: A cohort of children (n = 2,253) transported by a specialized pediatric team to a children's hospital were studied. At the time of referral, data collected included age (months), heart rate, systolic blood pressure, respiratory rate, retractions, stridor or wheezing, seizures, skin perfusion, oxygen requirement, and mental status. Using univariate and stepwise logistic regression, variables predictive of in-hospital mortality were selected from a training set (n = 1,111) and assigned integers based on their computed coefficients. Probability of in-hospital mortality was calculated using the total integer score and age. The risk of mortality derived from the training set was validated in the remaining patients (n = 1,142) by comparing the observed and predicted mortalities. Major interventions performed and unplanned events were determined for each of five predetermined mortality risk groups. RESULTS: Variables (integers) predicting in-hospital mortality included systolic blood pressure (11), respiratory rate (6), oxygen requirement (11), and altered mental status (11). Observed mortality was similar to predicted mortality in all risk categories for the validation sample. As risk of mortality increased, so did the performance of major interventions and the occurrence of unplanned events. CONCLUSION: Four pretransport variables predicted in-hospital mortality. Risk of mortality correlated with the incidence of major patient interventions, and the occurrence of unplanned events increased as well. This model might be useful in comparing different transport systems using severity-adjusted assessment of children requiring interfacility transport.
机译:目的:检验运输前变量可以预测院内死亡率的假说,该死亡率将与设施间运输期间的主要干预措施和计划外事件相关。方法:研究了一组由专门的儿科小组运送到儿童医院的儿童(n = 2,253)。转诊时,收集的数据包括年龄(月),心率,收缩压,呼吸频率,收缩,喘鸣或喘息,癫痫发作,皮肤灌注,需氧量和精神状态。使用单变量和逐步逻辑回归,从训练集(n = 1,111)中选择预测院内死亡率的变量,并根据其计算的系数分配整数。使用总整数评分和年龄计算住院死亡率的概率。通过比较观察到的和预测的死亡率,在其余患者(n = 1,142)中验证了来自训练集的死亡风险。确定了五个预定的死亡风险组中的每一个的主要干预措施和计划外事件。结果:预测院内死亡率的变量(整数)包括收缩压(11),呼吸频率(6),需氧量(11)和精神状态改变(11)。在验证样本的所有风险类别中,观察到的死亡率与预期死亡率相似。随着死亡风险的增加,主要干预措施的执行和计划外事件的发生也随之增加。结论:四个运输前变量可预测住院死亡率。死亡风险与主要患者干预措施的发生率相关,并且计划外事件的发生率也增加了。通过对需要跨设施运输的儿童进行严重程度调整后的评估,该模型可能有助于比较不同的运输系统。

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