Abstract：
BACKGROUND: Although the relationships between paraspinal muscles and lumbar degenerative disorders have been acknowledged, paraspinal muscle evaluation has not been incorporated into clinical therapies.
OBJECTIVE: We aimed to establish a novel paraspinal muscle endurance and morphology (PMEM) score to better predict mechanical complications after lumbar fusion.
METHODS: Prospective cohort study.
METHODS: A total of 212 patients undergoing posterior lumbar interbody fusion with at least 1 year of follow-up were finally included.
METHODS: Mechanical complications including screw loosening, pseudarthrosis and other complications like cage subsidence, and patient-reported outcomes were evaluated at last follow-up.
METHODS: The PMEM score comprised 1 functional muscular parameter (the performance time of the endurance test) and 2 imaging muscular parameters (relative functional cross-sectional area [rFCSA] of paraspinal extensor muscles [PEM] and psoas major [PS] on magnetic resonance imaging). The score was established based on a weighted scoring system created by rounding β regression coefficients to the nearest integer in univariate logistic regression. The diagnostic performance of the PMEM score was determined by binary logistic regression model and receiver operating characteristic (ROC) curve with the area under the curve (AUC). Additionally, pairwise comparisons of ROC curves were conducted to compare the diagnostic performance of the PMEM score with conventional methods based on a single muscular parameter. Moreover, differences of mechanical complications and patient-reported outcomes among the PMEM categories were analyzed using Chi-square test with Bonferroni correction.
RESULTS: The PMEM score, calculated by adding the scores for each parameter, ranges from 0 to 5 points. Patients with higher PMEM scores exhibited higher rates of mechanical complications (p<.001). Binary logistic regression revealed that the PMEM score was an independent factor of mechanical complications (p<.001, OR=2.002). Moreover, the AUC of the PMEM score (AUC=0.756) was significantly greater than those of the conventional methods including the endurance test (AUC=0.691, Z=2.036, p<.05), PEM rFCSA (AUC=.690, Z=2.016, p<.05) and PS rFCSA (AUC=0.640, Z=2.771, p<.01). In terms of the PMEM categories, a score of 0-1 was categorized as low-risk muscular state of mechanical complications; 2-3, as moderate; and 4-5, as high-risk state. Moving from the low-risk state to the high-risk state, there was a progressive increase in the rates of mechanical complications (13.8% vs. 32.1% vs. 72.7%; p<.001), and a decrease in the rates of clinically significant improvement of patient-reported outcomes (all p<.05).
CONCLUSIONS: The PMEM score might comprehensively evaluate paraspinal muscle degeneration and exhibit greater ability in predicting mechanical complications than the conventional evaluations after lumbar fusion. Surgeons might develop individualized treatment strategy tailored to different muscle degeneration statuses reflected by the PMEM score for decreasing the risk of mechanical complications.
OBJECTIVE: We aimed to establish a novel paraspinal muscle endurance and morphology (PMEM) score to better predict mechanical complications after lumbar fusion.
METHODS: Prospective cohort study.
METHODS: A total of 212 patients undergoing posterior lumbar interbody fusion with at least 1 year of follow-up were finally included.
METHODS: Mechanical complications including screw loosening, pseudarthrosis and other complications like cage subsidence, and patient-reported outcomes were evaluated at last follow-up.
METHODS: The PMEM score comprised 1 functional muscular parameter (the performance time of the endurance test) and 2 imaging muscular parameters (relative functional cross-sectional area [rFCSA] of paraspinal extensor muscles [PEM] and psoas major [PS] on magnetic resonance imaging). The score was established based on a weighted scoring system created by rounding β regression coefficients to the nearest integer in univariate logistic regression. The diagnostic performance of the PMEM score was determined by binary logistic regression model and receiver operating characteristic (ROC) curve with the area under the curve (AUC). Additionally, pairwise comparisons of ROC curves were conducted to compare the diagnostic performance of the PMEM score with conventional methods based on a single muscular parameter. Moreover, differences of mechanical complications and patient-reported outcomes among the PMEM categories were analyzed using Chi-square test with Bonferroni correction.
RESULTS: The PMEM score, calculated by adding the scores for each parameter, ranges from 0 to 5 points. Patients with higher PMEM scores exhibited higher rates of mechanical complications (p<.001). Binary logistic regression revealed that the PMEM score was an independent factor of mechanical complications (p<.001, OR=2.002). Moreover, the AUC of the PMEM score (AUC=0.756) was significantly greater than those of the conventional methods including the endurance test (AUC=0.691, Z=2.036, p<.05), PEM rFCSA (AUC=.690, Z=2.016, p<.05) and PS rFCSA (AUC=0.640, Z=2.771, p<.01). In terms of the PMEM categories, a score of 0-1 was categorized as low-risk muscular state of mechanical complications; 2-3, as moderate; and 4-5, as high-risk state. Moving from the low-risk state to the high-risk state, there was a progressive increase in the rates of mechanical complications (13.8% vs. 32.1% vs. 72.7%; p<.001), and a decrease in the rates of clinically significant improvement of patient-reported outcomes (all p<.05).
CONCLUSIONS: The PMEM score might comprehensively evaluate paraspinal muscle degeneration and exhibit greater ability in predicting mechanical complications than the conventional evaluations after lumbar fusion. Surgeons might develop individualized treatment strategy tailored to different muscle degeneration statuses reflected by the PMEM score for decreasing the risk of mechanical complications.
摘要：
背景：虽然椎旁肌与腰椎退行性疾病之间的关系已被确认，椎旁肌评价尚未纳入临床治疗.
目的：我们旨在建立一种新的椎旁肌耐力和形态学（PMEM）评分，以更好地预测腰椎融合术后的机械并发症。
方法：前瞻性队列研究。
方法：最终纳入212例接受腰椎后路椎间融合术的患者，随访至少一年。
方法：机械性并发症，包括螺钉松动，假关节和其他并发症，如笼子下沉，和患者报告的结局在最后一次随访时进行评估.
方法：PMEM评分包括一个功能性肌肉参数（耐力测试的表现时间）和两个成像肌肉参数（磁共振成像的椎旁伸肌[PEM]和腰大肌[PS]的相对功能横截面积[rFCSA]）。评分是基于通过将β回归系数舍入到单变量逻辑回归中的最接近的整数而创建的加权评分系统来建立的。通过二元逻辑回归模型和具有曲线下面积（AUC）的受试者工作特征（ROC）曲线确定PMEM评分的诊断性能。此外,进行ROC曲线的成对比较,以比较PMEM评分与基于单个肌肉参数的常规方法的诊断性能。此外，使用卡方检验和Bonferroni校正分析了PMEM类别中机械性并发症和患者报告结局的差异.
结果：PMEM评分，通过添加每个参数的分数来计算，范围从0到5点。PMEM评分较高的患者表现出更高的机械性并发症发生率(p<0.001)。二元logistic回归分析显示,PMEM评分是机械性并发症的独立影响因素(p<0.001,OR=2.002)。此外，PMEM评分的AUC（AUC=0.756）明显大于包括耐力测试在内的常规方法（AUC=0.691，Z=2.036，p<0.05），PEMrFCSA(AUC=0.690,Z=2.016,p<0.05)和PSrFCSA(AUC=0.640,Z=2.771,p<0.01)。就PMEM类别而言，0~1分被归类为机械并发症的低危肌肉状态;2~3分被归类为中度;4~5分被归类为高危状态.从低风险状态到高风险状态，机械并发症的发生率逐渐增加（13.8％vs32.1％vs72.7％；p<0.001），患者报告结局的临床显着改善率下降（所有p<0.05）。
结论：在腰椎融合术后，PMEM评分可以综合评价椎旁肌退变，在预测机械并发症方面表现出比常规评价更高的能力。外科医生可能会制定针对PMEM评分反映的不同肌肉变性状态的个性化治疗策略，以降低机械并发症的风险。
目的：我们旨在建立一种新的椎旁肌耐力和形态学（PMEM）评分，以更好地预测腰椎融合术后的机械并发症。
方法：前瞻性队列研究。
方法：最终纳入212例接受腰椎后路椎间融合术的患者，随访至少一年。
方法：机械性并发症，包括螺钉松动，假关节和其他并发症，如笼子下沉，和患者报告的结局在最后一次随访时进行评估.
方法：PMEM评分包括一个功能性肌肉参数（耐力测试的表现时间）和两个成像肌肉参数（磁共振成像的椎旁伸肌[PEM]和腰大肌[PS]的相对功能横截面积[rFCSA]）。评分是基于通过将β回归系数舍入到单变量逻辑回归中的最接近的整数而创建的加权评分系统来建立的。通过二元逻辑回归模型和具有曲线下面积（AUC）的受试者工作特征（ROC）曲线确定PMEM评分的诊断性能。此外,进行ROC曲线的成对比较,以比较PMEM评分与基于单个肌肉参数的常规方法的诊断性能。此外，使用卡方检验和Bonferroni校正分析了PMEM类别中机械性并发症和患者报告结局的差异.
结果：PMEM评分，通过添加每个参数的分数来计算，范围从0到5点。PMEM评分较高的患者表现出更高的机械性并发症发生率(p<0.001)。二元logistic回归分析显示,PMEM评分是机械性并发症的独立影响因素(p<0.001,OR=2.002)。此外，PMEM评分的AUC（AUC=0.756）明显大于包括耐力测试在内的常规方法（AUC=0.691，Z=2.036，p<0.05），PEMrFCSA(AUC=0.690,Z=2.016,p<0.05)和PSrFCSA(AUC=0.640,Z=2.771,p<0.01)。就PMEM类别而言，0~1分被归类为机械并发症的低危肌肉状态;2~3分被归类为中度;4~5分被归类为高危状态.从低风险状态到高风险状态，机械并发症的发生率逐渐增加（13.8％vs32.1％vs72.7％；p<0.001），患者报告结局的临床显着改善率下降（所有p<0.05）。
结论：在腰椎融合术后，PMEM评分可以综合评价椎旁肌退变，在预测机械并发症方面表现出比常规评价更高的能力。外科医生可能会制定针对PMEM评分反映的不同肌肉变性状态的个性化治疗策略，以降低机械并发症的风险。
