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创伤性颈脊髓损伤后急性住院并发症的临床预测模型:来自急性脊髓损伤手术时机研究的亚分析。

Clinical prediction model for acute inpatient complications after traumatic cervical spinal cord injury: a subanalysis from the Surgical Timing in Acute Spinal Cord Injury Study.

机构信息

Department of Surgery, Division of Neurosurgery, University of Toronto, Ontario, Canada

出版信息

J Neurosurg Spine. 2012 Sep;17(1 Suppl):46-51. doi: 10.3171/2012.4.AOSPINE1246.

DOI:10.3171/2012.4.AOSPINE1246
PMID:22985370
Abstract

OBJECT

While the majority of existing reports focus on complications sustained during the chronic stages after traumatic spinal cord injury (SCI), the objective in the current study was to characterize and quantify acute inpatient complications. In addition, the authors sought to create a prediction model using clinical variables documented at hospital admission to predict acute complication development.

METHODS

Analyses were based on data from the Surgical Timing in Acute Spinal Cord Injury Study (STASCIS) data registry, which contains prospective information on adult patients with cervical SCIs who were enrolled at 6 North American centers over a 7-year period. All patients who underwent a standardized American Spinal Injury Association (ASIA) neurological examination within 24 hours of injury and whose follow-up information was available at the acute hospital discharge were included in the study. For purposes of classification, complications were divided into 5 major categories: 1) cardiopulmonary, 2) surgical, 3) thrombotic, 4) infectious, and 5) decubitus ulcer development. Univariate statistical analyses were performed to determine the relationship between complication occurrence and individual demographic, injury, and treatment variables. Multivariate logistic regression was subsequently performed to create a complication prediction model. Model discrimination was judged according to the area under the receiver operating characteristic curve.

RESULTS

Complete complication information was available for 411 patients at the acute care discharge. One hundred sixty patients (38.9%) experienced 240 complications. The mean age among those who experienced at least one complication was 45.9 years, as compared with 43.5 years among those who did not have a complication (p = 0.18). In the univariate analysis, patients with complications were less likely to receive steroids at admission (p = 0.01), had a greater severity of neurological injury as indicated by the ASIA Impairment Scale (AIS) grade at presentation (p < 0.01), and a higher frequency of significant comorbidity (p = 0.04). In a multivariate logistic regression model, a severe initial AIS grade (p < 0.01), a high-energy injury mechanism (p = 0.07), an older age (p = 0.05), the absence of steroid administration (p = 0.02), and the presence of comorbid illness (p = 0.02) were associated with a greater likelihood of complication development during the period of acute hospitalization. The area under the curve value for the full model was 0.75, indicating acceptable predictive discrimination.

CONCLUSIONS

These results will help clinicians to identify patients with cervical SCIs at greatest risk for complication development and thus allowing for the institution of aggressive complication prevention measures.

摘要

目的

虽然大多数现有报告都集中在创伤性脊髓损伤 (SCI) 慢性阶段所发生的并发症,但本研究的目的是描述和量化急性住院并发症,并创建一个使用入院时记录的临床变量预测急性并发症发生的预测模型。

方法

分析基于 Surgical Timing in Acute Spinal Cord Injury Study (STASCIS) 数据登记处的数据,该登记处包含了 6 个北美中心在 7 年期间纳入的患有颈 SCI 的成年患者的前瞻性信息。所有患者在受伤后 24 小时内接受了标准化的美国脊髓损伤协会 (ASIA) 神经学检查,并且在急性医院出院时可获得随访信息,均纳入本研究。为了便于分类,并发症分为 5 大类别:1)心肺,2)手术,3)血栓形成,4)感染,5)褥疮发展。进行单变量统计分析以确定并发症发生与个体人口统计学、损伤和治疗变量之间的关系。随后进行多变量逻辑回归以创建并发症预测模型。根据接收者操作特征曲线下的面积判断模型区分度。

结果

在急性护理出院时,411 名患者可获得完整的并发症信息。160 名患者(38.9%)经历了 240 次并发症。经历至少一次并发症的患者的平均年龄为 45.9 岁,而没有并发症的患者的平均年龄为 43.5 岁(p=0.18)。在单变量分析中,患有并发症的患者在入院时接受类固醇治疗的可能性较低(p=0.01),入院时 ASIA 损伤量表(AIS)分级所示的神经损伤严重程度更高(p<0.01),且合并症的发生率更高(p=0.04)。在多变量逻辑回归模型中,初始 AIS 严重程度较高(p<0.01)、高能损伤机制(p=0.07)、年龄较大(p=0.05)、未给予类固醇治疗(p=0.02)和存在合并症(p=0.02)与急性住院期间并发症发生的可能性增加相关。全模型的曲线下面积值为 0.75,表明具有可接受的预测区分度。

结论

这些结果将帮助临床医生识别颈椎 SCI 患者中并发症发生风险最高的患者,从而可以采取积极的并发症预防措施。

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