Assessing the prognostic impact of body composition phenotypes on surgical outcomes and survival in patients with spinal metastasis: a deep learning approach to preoperative CT analysis.

IF 2.9 2区 医学 Q2 CLINICAL NEUROLOGY Journal of neurosurgery. Spine Pub Date : 2024-12-20 DOI:10.3171/2024.8.SPINE24722
Syed I Khalid, Elie Massaad, John H Shin
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Abstract

Objective: The prognostic significance of body composition phenotypes for survival in patients undergoing surgical intervention for spinal metastases has not yet been elucidated. This study aimed to elucidate the impact of body composition phenotypes on surgical outcomes and 5-year survival.

Methods: The records of patients treated surgically for spinal metastases between 2010 and 2020 were retrospectively evaluated. A deep learning pipeline assessed preoperative CT scans obtained within 3 months of surgery and identified muscle and fat content and composition. These data were used to categorize patients into 4 body composition phenotypic groups: 1) not sarcopenic, not obese; 2) sarcopenia alone; 3) obesity alone; and 4) sarcopenic obesity (SO). The groups were matched using a comprehensive propensity-matching procedure. Rates of postoperative outcomes and survival were evaluated. Cox proportional hazard models were used to evaluate the influence of body composition phenotypes on 5-year survival. Kaplan-Meier plots were used to evaluate survival probability further.

Results: Following a propensity-matching procedure, 102 matched patient records were identified (not sarcopenic, not obese, n = 24; sarcopenia alone, n = 27; obesity alone, n = 37; and SO, n = 14). SO was found to be associated with a significantly increased mortality risk within 60 months (HR 3.27, 95% CI 1.43-7.48). Kaplan-Meier plots demonstrate evident divergence in survival probability within 5 years among patients in the SO group compared to the others (log-rank test, p = 0.022). Additionally, time to death was also lower in patients with SO (p = 0.018). Significant differences in postoperative ambulation rates were noted among patients with SO (p = 0.048), whereas no preoperative difference existed (p = 0.12). No significant differences in postoperative disposition, length of hospital stay, wound-related complications, or inpatient medical complications were otherwise noted (p > 0.05).

Conclusions: This study identifies SO as a distinct prognostic factor for increased mortality risk in patients undergoing surgery for spinal metastases, highlighting the complex interplay between body composition and patient outcomes. These findings advocate for integrating body composition analysis into preoperative assessment and tailored postoperative care strategies, promoting personalized treatment plans to improve survival and quality of life for this vulnerable patient population.

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目的:身体成分表型对脊柱转移瘤手术治疗患者生存率的预后意义尚未阐明。本研究旨在阐明身体成分表型对手术结果和 5 年生存率的影响:方法:对2010年至2020年间接受脊柱转移手术治疗的患者记录进行了回顾性评估。深度学习管道评估了手术后3个月内获得的术前CT扫描结果,并确定了肌肉和脂肪含量及组成。这些数据被用来将患者分为 4 个身体成分表型组:1)非肌肉疏松,非肥胖;2)单纯肌肉疏松;3)单纯肥胖;4)肌肉疏松性肥胖(SO)。各组采用综合倾向匹配程序进行匹配。对术后结果和存活率进行了评估。采用 Cox 比例危险模型评估身体成分表型对 5 年生存率的影响。采用 Kaplan-Meier 图进一步评估生存概率:经过倾向匹配程序,确定了102份匹配的患者记录(非肌无力、非肥胖,n = 24;单纯肌无力,n = 27;单纯肥胖,n = 37;SO,n = 14)。研究发现,SO 与 60 个月内的死亡风险显著增加有关(HR 3.27,95% CI 1.43-7.48)。Kaplan-Meier 图显示,与其他组别相比,SO 组患者在 5 年内的生存概率存在明显差异(对数秩检验,P = 0.022)。此外,SO 组患者的死亡时间也较短(p = 0.018)。SO患者的术后行走率存在显著差异(p = 0.048),而术前则不存在差异(p = 0.12)。在术后处置、住院时间、伤口相关并发症或住院医疗并发症等方面均无明显差异(P > 0.05):本研究发现,SO 是导致脊柱转移手术患者死亡风险增加的一个独特预后因素,凸显了身体成分与患者预后之间复杂的相互作用。这些研究结果主张将身体成分分析纳入术前评估和量身定制的术后护理策略中,促进个性化治疗方案的制定,以提高这一弱势患者群体的生存率和生活质量。
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来源期刊
Journal of neurosurgery. Spine
Journal of neurosurgery. Spine 医学-临床神经学
CiteScore
5.10
自引率
10.70%
发文量
396
审稿时长
6 months
期刊介绍: Primarily publish original works in neurosurgery but also include studies in clinical neurophysiology, organic neurology, ophthalmology, radiology, pathology, and molecular biology.
期刊最新文献
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