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Development and validation of a risk prediction model for tracheostomy in acute traumatic cervical spinal cord injury patients

机译:急性外伤性颈脊髓损伤患者气管切开术风险预测模型的建立和验证

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PurposeTracheostomy may become indispensable for patients with acute traumatic cervical spinal cord injuries. However, the early prediction of a tracheostomy is often difficult. Previous prediction models using the pulmonary function test (PFT) have limitations because some severely injured patients could not provide acceptable PFT results. We aim to develop an alternative model for predicting tracheostomy using accessible data obtained from the bedside.MethodClinical, neurological and radiological data from 345 consecutive patients with acute tetraplegia were retrospectively reviewed. We applied multiple logistic regression analysis (MLRA) and classification and regression tree (CART) analysis to develop the prediction model for tracheostomy. By train-test cross-validation, we used the sensitivity, specificity, area under the receiver operating characteristics curve (AUC) and correction rate to evaluate the performance of these models.ResultsAccording to the American Spinal Injury Association (ASIA) standards, an admission ASIA motor score (AAMS)?≤?22, ASIA grade A and presence of respiratory complications were identified as independent predictors of tracheostomy by both models. The model derived by CART suggested that the highest signal change (HSC) in the spinal cord on magnetic resonance imaging (MRI) also affected a patient’s requirement for a tracheostomy, while MLRA demonstrated that tracheostomy was also influenced by the presence of an ASIA grade B injury. The CART model had a sensitivity of 73.7?%, specificity of 89.7?%, AUC of 0.909 and overall correction rate of 87.3?%. The sensitivity, specificity, AUC and correction rate of the MLRA model were 81.8, 86.4, 0.889 and 85.7?%, respectively.ConclusionsWe suggest using the CART model in clinical applications. Patients with AAMS?≤?1 exhibit an increased likelihood of requiring a tracheostomy. For patients with an AAMS in the range of 2–22, surgeons should consider giving these patients a tracheostomy once respiratory complications occur. Surgeons should be cautious to give a tracheostomy to patients with an AAMS?≥?23, if the patient experiences an incomplete spinal cord injury and the HSC in the spinal cord is at C3 level or lower based on MRI. For other patients, close observation is necessary; generally, patients with complete SCI might require a tracheostomy more frequently...
机译:目的气管切开术对于急性创伤性颈脊髓损伤的患者可能是必不可少的。但是,气管切开术的早期预测通常很困难。先前使用肺功能测试(PFT)的预测模型存在局限性,因为一些严重受伤的患者无法提供可接受的PFT结果。我们的目标是使用可从床旁获得的数据来开发另一种预测气管切开术的模型。方法回顾性分析345例连续的急性四肢瘫痪患者的临床,神经和放射学数据。我们应用多元逻辑回归分析(MLRA)和分类与回归树(CART)分析来开发气管切开术的预测模型。通过火车测试交叉验证,我们使用敏感性,特异性,受体工作特征曲线下的面积(AUC)和校正率来评估这些模型的性能。结果根据美国脊髓损伤协会(ASIA)的标准,可以接受两种模型均将ASIA运动评分(AAMS)≤22,ASIA A级和是否存在呼吸系统并发症作为气管造口术的独立预测因素。由CART得出的模型表明,磁共振成像(MRI)上脊髓中最高的信号变化(HSC)也影响了患者对气管切开术的需求,而MLRA表明,气管切开术也受到ASIA B级的影响受伤。 CART模型的灵敏度为73.7%,特异性为89.7%,AUC为0.909,总校正率为87.3%。 MLRA模型的敏感性,特异性,AUC和校正率分别为81.8、86.4、0.889和85.7%。结论我们建议在临床应用中使用CART模型。 AAMS≤≤1的患者表现出需要气管切开术的可能性增加。对于AAMS在2-22之间的患者,一旦发生呼吸系统并发症,外科医生应考虑给予这些患者气管切开术。如果患者的脊髓损伤不完全并且根据MRI的结果,脊髓中的HSC处于C3或更低水平,则外科医生应谨慎行AAMS≥23的患者进行气管切开术。对于其他患者,必须进行密切观察。通常,具有完整SCI的患者可能需要更频繁地进行气管切开术...

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