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重大创伤性损伤患者出院去向的预测因素:俄克拉荷马创伤登记处分析。

Predictors of discharge destination in patients with major traumatic injury: Analysis of Oklahoma Trauma Registry.

机构信息

Department of Surgery, The University of Oklahoma, College of Medicine, Tulsa, OK, USA.

Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Tulsa, OK, USA.

出版信息

Am J Surg. 2019 Sep;218(3):496-500. doi: 10.1016/j.amjsurg.2018.11.045. Epub 2018 Dec 10.

Abstract

BACKGROUND

The ability to predict the need for discharge of trauma patients to a facility may help shorten hospital stay. This study aimed to determine the predictors of discharge to a facility and develop and validate a predictive scoring model, utilizing the Oklahoma Trauma Registry (OTR).

METHODS

A multivariate analysis of the OTR 2005-2013 determined independent predictors of discharge to a facility. A scoring model was developed, and positive and negative predictive values (PPV and NPV) were evaluated for 2014 patients.

RESULTS

101,656 patients were analyzed. The scoring model included age≥50 years, lower extremity fracture, ICU stay≥5 days, pelvic fracture, intracranial hemorrhage, congestive heart failure, cardiac dysrhythmia, history of CVA or TIA, and ISS≥15, spine fracture, diabetes mellitus, hypertension, ischemic heart disease, and chronic obstructive pulmonary disease. Applying the model to 2014 patients, PPV for predicting discharge to a facility was 84.9% for scores≥15, and NPV was 90.5% for scores<8.

CONCLUSION

A scoring model including age, trauma severity, types of injury, and comorbidities could predict discharge of trauma patients to a facility. Further studies are needed to refine the efficacy of the model.

摘要

背景

能够预测创伤患者需要转至医疗机构,可能有助于缩短住院时间。本研究旨在利用俄克拉荷马州创伤登记处(OTR)确定转至医疗机构的预测因素,并开发和验证预测评分模型。

方法

对 OTR 2005-2013 年的数据进行多变量分析,确定转至医疗机构的独立预测因素。开发了评分模型,并对 2014 年的患者评估了阳性和阴性预测值(PPV 和 NPV)。

结果

分析了 101656 名患者。评分模型包括年龄≥50 岁、下肢骨折、入住 ICU≥5 天、骨盆骨折、颅内出血、充血性心力衰竭、心律失常、中风或 TIA 病史、ISS≥15、脊柱骨折、糖尿病、高血压、缺血性心脏病和慢性阻塞性肺疾病。将该模型应用于 2014 年的患者,对于预测转至医疗机构的评分≥15 的患者,PPV 为 84.9%,评分<8 的患者,NPV 为 90.5%。

结论

包括年龄、创伤严重程度、损伤类型和合并症的评分模型可以预测创伤患者转至医疗机构。需要进一步的研究来完善该模型的疗效。

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