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心脏大血管手术患者术后恢复质量的影响因素及预测模型的建立

Influencing factors of the quality of postoperative rehabilitation of patients after cardiac large vessels surgery and establishment of prediction model

    摘要
  • 摘要:
    目的 通过15项恢复质量评分量表（QoR-15）评分评估心脏大血管手术患者术后恢复质量，回顾性分析围术期多项因素对患者术后恢复质量的影响，并建立预测模型。
    方法 通过电子病历系统收集并整理2020年3月—2022年9月实施心脏大血管手术患者的临床资料，对患者行术后QoR-15评分。收集患者性别、年龄、术后随访时间、美国麻醉医师协会（ASA）分级、术前乳酸水平、是否有合并症、是否急诊及术中是否建立体外循环等资料，并计算改良衰弱指数（mFI）。记录手术方式、手术时间、体外循环时间、主动脉阻断时间、复跳类型、围术期液体治疗、转流温度等手术资料及术后ICU停留时间、总住院时间及QoR-15评分等术后资料。采用单因素及多因素Logistic回归分析构建预测模型并予以验证。
    结果 本研究共纳入213例患者，剔除15例患者，共回收术后QoR-15评分198份。性别、ASA分级、术前乳酸水平、术后随访时间及mFI是影响心脏大血管手术患者恢复质量的影响因素，以此建立预测模型ln（p/1-p）=-5.571+0.862×性别+3.844×ASA分级+3.143×术前乳酸水平+2.001×术后随访时间+3.712×mFI。该模型具有良好的预测效果及分类效果。
    结论 性别、ASA分级、术前乳酸水平、术后随访时间及mFI是心脏大血管手术患者恢复质量的影响因素。

     

    Abstract:
    Objective To evaluate the quality of postoperative recovery of patients undergoing cardiac great vessels surgery by 15-item Recovery Quality Score Scale (QoR-15), to retrospectively analyze the influence of perioperative multi-factors on postoperative recovery quality, and to establish the predictive model.
    Methods Clinical data of patients who underwent cardiac great vascularsurgery from March 2020 to September 2022 were collected through electronic medical record system and the postoperative QoR-15 score were evaluated. The data including gender, age, postoperative follow-up time, American Society of Anesthesiologists (ASA) classification, preoperative lactate level, comorbidities, emergency or not, extracorporeal circulation or not, etc. were collected. The modified frailty index (mFI) was also calculated. Surgical patterns, operation time, extracorporeal circulation time, aortic block time, type of heart recurrence, perioperative fluid therapy, extracorporeal circulation temperature, and other postoperative data as well as postoperative data including ICU retention time after surgery, total length of stay and QoR-15 score were recorded. The univariate and multivariate Logistic regression analysis were then applied to construct a prediction model, and its accuracy was validated.
    Results A total of 213 patients were included, in which 15 patients were excluded, and 198 postoperative QoR-15 score sheets were received. Gender, ASA classification, preoperative lactate level, postoperative follow-up time, and mFI were significant influencing factors on the quality of rehabilitation of patients undergoing cardiac or great vascular surgery. The prediction model of ln(p/1-p)=-5.571+0.862×gender+3.844×ASA classification+3.143×preoperative lactate level+2.001×postoperative follow-up time+3.712×mFI, which had good predictive and classification effects.
    Conclusion Gender, ASA classification, preoperative lactate level, postoperative follow-up time and mFI are influencing factors on the recovery quality of patients after cardiac great vascular surgery.

     

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