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Predictors of nontransport of older fallers who receive ambulance care

机译:接受救护车的较大跌倒者的不预测因素

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Objectives. To identify patient, clinical, and operational factors associated with nontransport of older people who have fallen and received ambulance care; and to develop a nontransport prediction tool that could be utilized during the dispatch process to rationalize allocation of emergency ambulance resources. Methods. The study was a planned subanalysis using data collected during a prospective observational cohort study of nonconsecutive emergency responses to older people aged 65 years or more who had fallen between October 1, 2010 and June 30, 2011. The data consisted of routinely collected ambulance dispatch and clinical records, combined with prospectively collected fall-specific information. Missing data were managed using multiple imputation. Multivariate logistic regression modeling was undertaken to identify predictors of nontransport. Results are described for original and imputated data sets, presented as odds ratios (OR) with 95%CI (confidence interval). Receiver operating curve (ROC) statistics were generated, with model discrimination determined by the area under the curve (AUC). Results. There were 1,484 cases eligible for this subanalysis of which 419 (28.2%) were recorded as nontransport. Multivariate regression including dispatch and clinical variables identified a 6-item final model. Younger age group, nonurgent response priority, and presence of a personal alarm were predictors of nontransport, along with clinical variables, including normal vital signs, absence of injury, and unchanged functional status post-fall. The AUC was 0.88 (95% CI 0.86-0.90; p < 0.0001) (imputed data AUC 0.86 (95% CI 0.84-0.88)). Multivariate modeling of dispatch variables only identified a 3-item final model, which included response nonurgent response priority, younger age, and the presence of a personal alarm. The AUC was 0.68 (95% CI 0.64-0.71; p < 0.0001) (imputed data AUC 0.69 (95% CI 0.66-0.72)). Conclusion. In this population of confirmed older fallers attended to by paramedics, determination of the prehospital transport outcome is greatly influenced by on-scene findings resulting from paramedic assessment. The presence of new pain, abnormal physiology, and altered function post-fall were strongly associated with increased odds of transport. Conversely the presence of a personal alarm and allocation of a nonurgent dispatch priority increased the odds of nontransport. Accurate discrimination between older fallers who were and were not transported using dispatch data only was not possible.
机译:目标。识别与跌倒并接受救护车的老年人不转运相关的患者,临床和操作因素;并开发可在派遣过程中使用的非运输预测工具,以合理分配紧急救护车资源。方法。这项研究是一项计划内的子分析,使用的是一项前瞻性观察性队列研究收集的数据,该研究对2010年10月1日至2011年6月30日之间摔倒的65岁或65岁以上的老年人进行了非连续性紧急应对。这些数据包括常规收集的救护车分发和临床记录,以及前瞻性收集的秋季特定信息。丢失的数据使用多重插补进行管理。进行多元逻辑回归建模以识别非运输的预测因素。描述了原始数据和推定数据集的结果,以具有95%CI(置信区间)的优势比(OR)表示。生成接收器工作曲线(ROC)统计信息,并根据曲线下的面积(AUC)确定模型辨别力。结果。有1,484例符合该子分析条件的案例,其中419例(28.2%)被记录为非运输。包括派遣和临床变量在内的多元回归确定了6个项目的最终模型。较年轻的年龄组,非紧急反应优先级和出现个人警报是非运输的预测因素,包括临床变量,包括正常生命体征,无损伤和跌倒后功能状态不变。 AUC为0.88(95%CI 0.86-0.90; p <0.0001)(估算数据AUC 0.86(95%CI 0.84-0.88))。调度变量的多变量建模仅确定了3个项目的最终模型,其中包括响应非紧急响应优先级,较年轻的年龄以及个人警报的存在。 AUC为0.68(95%CI 0.64-0.71; p <0.0001)(估算数据AUC 0.69(95%CI 0.66-0.72))。结论。在这批经过确认的,由医护人员陪同的老年摔跤者中,院前运输结果的确定在很大程度上取决于医护人员评估的现场发现。出现新的疼痛,生理异常和跌倒后功能改变与运输机率增加密切相关。相反,个人警报的出现和非紧急调度优先级的分配增加了非运输的几率。仅使用派遣数据无法准确地区分是否曾与未运送过的老年跌倒者。

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