Copenhagen Spine Research Unit (CSRU), Section of Spine Surgery, Department of Rheumatology and Spine Diseases, Rigshospitalet-Glostrup, Denmark.
Copenhagen Spine Research Unit (CSRU), Section of Spine Surgery, Department of Rheumatology and Spine Diseases, Rigshospitalet-Glostrup, Denmark.
Clin Neurol Neurosurg. 2023 May;228:107698. doi: 10.1016/j.clineuro.2023.107698. Epub 2023 Mar 27.
To compare Modified Frailty Index (mFI), Modified Charlson Comorbidity (mCCI) and ASA with demographic data such as age, BMI and gender in the prediction of AEs obtained using a validated systematic reporting system in a prospective cohort undergoing cervical spine surgery.
All adult patients undergoing spine surgery for cervical degenerative disease at our academic tertiary referral center from February 1, 2016, to January 31, 2017, were included. Morbidity and mortality were determined according to the predefined adverse event (AE) variables using the Spinal Adverse Events Severity (SAVES) System. Area under the curve (AUC) analyses from receiver operating characteristics (ROC) curves were used to assess the discriminative ability in predicting AEs for the comorbidity indices mFI, mCCI, ASA and for BMI, age and gender.
A total of 288 consecutive cervical cases were included. BMI was the most predictive demographic factor for an AE (AUC = 0.58), the most predictive comorbidity index was mCCI (AUC = 0.52). No combination of comorbidity indices or demographic factors reached a threshold of AUC ≥ 0.7 for AEs. As predictor of extended length of stay: age (AUC = 0.77), mFI (AUC = 0.70) and ASA (AUC = 0.70) were similar and fair.
Age and BMI equal mFI, mCCI and ASA in predicting postoperative AEs, amongst patients operated for cervical degenerative disease. No significant difference was found between mFI, mCCI and ASA in the discriminative abilities in predicting morbidity, based on prospectively collected AEs according to the SAVES grading system.
比较改良衰弱指数（mFI）、改良 Charlson 共病指数（mCCI）和 ASA 与年龄、BMI 和性别等人口统计学数据在预测前瞻性队列接受颈椎手术患者使用验证后的系统报告系统获得的不良事件（AE）中的作用。
纳入 2016 年 2 月 1 日至 2017 年 1 月 31 日期间在我们学术性三级转诊中心接受颈椎退行性疾病脊柱手术的所有成年患者。根据预先确定的不良事件（AE）变量，使用脊柱不良事件严重程度（SAVES）系统确定发病率和死亡率。利用接受者操作特性（ROC）曲线下的面积（AUC）分析来评估共病指数 mFI、mCCI、ASA 以及 BMI、年龄和性别预测 AE 的鉴别能力。
共纳入 288 例连续颈椎病例。BMI 是预测 AE 的最具预测性的人口统计学因素（AUC=0.58），最具预测性的共病指数是 mCCI（AUC=0.52）。没有任何共病指数或人口统计学因素的组合达到 AE 的 AUC≥0.7 的阈值。作为延长住院时间的预测因素：年龄（AUC=0.77）、mFI（AUC=0.70）和 ASA（AUC=0.70）相似，均为中等。
在预测颈椎退行性疾病患者术后 AE 方面，年龄和 BMI 与 mFI、mCCI 和 ASA 相当。根据 SAVES 分级系统前瞻性收集的 AE 发现，mFI、mCCI 和 ASA 在预测发病率方面的鉴别能力无显著差异。
