Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, USA.
McKenna EpiLog Fellowship in Population Health, at the University of Pennsylvania, Philadelphia, USA.
World Neurosurg. 2023 Dec;180:e84-e90. doi: 10.1016/j.wneu.2023.08.044. Epub 2023 Aug 18.
Preoperative management requires the identification and optimization of modifiable medical comorbidities, though few studies isolate comorbid status from related patient-level variables. This study evaluates Charlson Comorbidity Index (CCI)-an easily derived measure of aggregate medical comorbidity-to predict outcomes from spinal fusion surgery. Coarsened exact matching is employed to control for key patient characteristics and isolate CCI.
We retrospectively assessed 4680 consecutive patients undergoing single-level, posterior-only lumbar fusion at a single academic center. Logistic regression evaluated the univariate relationship between CCI and patient outcomes. Coarsened exact matching generated exact demographic matches between patients with high comorbid status (CCI >6) or no medical comorbidities (matched n = 524). Patients were matched 1:1 on factors associated with surgical outcomes, and outcomes were compared between matched cohorts. Primary outcomes included surgical complications, discharge status, 30- and 90-day risk of readmission, emergency department (ED) visits, reoperation, and mortality.
Univariate regression of increasing CCI was significantly associated with non-home discharge, as well as 30- and 90-day readmission, ED visits, and mortality (all P < 0.05). Subsequent isolation of comorbidity between otherwise exact-matched cohorts found comorbid status did not affect readmissions, reoperations, or mortality; high CCI score was significantly associated with non-home discharge (OR = 2.50, P < 0.001) and 30-day (OR = 2.44, P = 0.02) and 90-day (OR = 2.29, P = 0.008) ED evaluation.
Comorbidity, measured by CCI, did not increase the risk of readmission, reoperation, or mortality. Single-level, posterior lumbar fusions may be safe in appropriately selected patients regardless of comorbid status. Future studies should determine whether CCI can guide discharge planning and postoperative optimization.
术前管理需要识别和优化可改变的医疗合并症，尽管很少有研究将合并症与相关的患者水平变量分开。本研究评估 Charlson 合并症指数（CCI）——一种简单的总体医疗合并症衡量标准——以预测脊柱融合手术的结果。粗糙精确匹配用于控制关键患者特征并分离 CCI。
我们回顾性评估了在一个学术中心接受单节段后路腰椎融合术的 4680 名连续患者。逻辑回归评估了 CCI 与患者结局的单变量关系。粗糙精确匹配在具有高合并症状态（CCI>6）或无医疗合并症的患者之间生成了精确的人口统计学匹配（匹配 n=524）。根据与手术结果相关的因素对患者进行 1:1 匹配，并比较匹配队列之间的结果。主要结局包括手术并发症、出院状态、30 天和 90 天再入院风险、急诊就诊、再次手术和死亡率。
CCI 增加的单变量回归与非家庭出院以及 30 天和 90 天再入院、急诊就诊和死亡率显著相关（均 P<0.05）。随后在其他方面精确匹配的队列中分离出合并症发现，合并症状态并不影响再入院、再次手术或死亡率；高 CCI 评分与非家庭出院显著相关（OR=2.50，P<0.001）以及 30 天（OR=2.44，P=0.02）和 90 天（OR=2.29，P=0.008）急诊评估。
CCI 测量的合并症不会增加再入院、再次手术或死亡率的风险。单节段后路腰椎融合术可能在适当选择的患者中是安全的，无论合并症状态如何。未来的研究应确定 CCI 是否可以指导出院计划和术后优化。
