Long-Term Postoperative Pain Prediction Using Higher-Order Singular Value Decomposition of Intraoperative Physiological Responses: Prospective Cohort Study.

Raheleh Baharloo, Jose Principe, Parisa Rashidi, Patrick Tighe
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Abstract

Background: Long-term postoperative pain (POP) and patient responses to pain relief medications are not yet fully understood. Although recent studies have developed an index for the nociception level of patients under general anesthesia based on multiple physiological parameters, it remains unclear whether these parameters correlate with long-term POP outcomes.

Objective: This study aims to extract unbiased and interpretable descriptions of how the dynamics of physiological parameters change over time and across patients in response to surgical procedures and intraoperative medications using a multivariate-temporal analysis. We demonstrated that there is an association (correlation) between the main features of intraoperative physiological responses and long-term POP, which has a predictive value, even without claiming causality.

Methods: We proposed a complex higher-order singular value decomposition method to accurately decompose patients' physiological responses into multivariate structures evolving over time. We used intraoperative vital signs of 175 patients from a mixed surgical cohort to extract three interconnected, low-dimensional, complex-valued descriptions of patients' physiological responses: multivariate factors, reflecting subphysiological parameters; temporal factors, reflecting common intrasurgery temporal dynamics; and patients' factors, describing interpatient changes in physiological responses.

Results: Adoption of the complex higher-order singular value decomposition method allowed us to clarify the dynamic correlation structure included in the intraoperative physiological responses. Instantaneous phases of the complex-valued physiological responses of 242 patients within the subspace of principal descriptors enabled us to discriminate between mild and not-mild (moderate-severe) levels of pain at postoperative days 30 and 90. Following rotation of physiological responses before projection to align with the common multivariate-temporal dynamic, the method achieved an area under curve for postoperative day 30 and 90 outcomes of 0.81 and 0.89 for thoracic surgery, 0.87 and 0.83 for orthopedic surgery, 0.87 and 0.88 for urological surgery, 0.86 and 1 for colorectal surgery, 1 and 1 for transplant surgery, and 0.83 and 0.92 for pancreatic surgery, respectively.

Conclusions: By categorizing patients into different surgical groups, we identified significant surgery-related principal descriptors. Each of them potentially encodes different surgical stimulation. The dynamics of patients' physiological responses to these surgical events were linked to long-term POP development.

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利用术中生理反应的高阶奇异值分解预测术后长期疼痛:前瞻性队列研究。
背景:长期术后疼痛(POP)和患者对止痛药物的反应尚未完全了解。尽管最近的研究基于多种生理参数建立了全麻患者伤害感觉水平的指数,但这些参数是否与长期POP结果相关尚不清楚。目的:本研究旨在通过多变量-时间分析,提取无偏倚和可解释的生理参数动态如何随时间和患者对外科手术和术中药物的反应而变化的描述。我们证明术中生理反应的主要特征与长期POP之间存在关联,即使没有因果关系,也具有预测价值。方法:提出一种复杂的高阶奇异值分解方法,将患者的生理反应准确分解为随时间变化的多元结构。我们使用175例混合手术队列患者的术中生命体征来提取患者生理反应的三个相互关联、低维、复杂值描述:反映亚生理参数的多变量因素;时间因素,反映常见的术中时间动态;以及患者因素,描述了患者间生理反应的变化。结果:采用复杂高阶奇异值分解方法,明确了术中生理反应的动态相关结构。242例患者在主要描述符子空间内的复杂值生理反应的瞬时阶段使我们能够区分术后30天和90天的轻度和非轻度(中度-重度)疼痛水平。在投影前对生理反应进行旋转,以与常见的多变量-时间动态相一致,该方法在术后第30天和第90天的结果曲线下面积分别为0.81和0.89,胸外科为0.87和0.83,泌尿外科为0.87和0.88,结肠直肠手术为0.86和1,移植手术为1和1,胰腺手术为0.83和0.92。结论:通过将患者分为不同的手术组,我们确定了与手术相关的重要主要描述符。每一个都可能编码不同的手术刺激。患者对这些手术事件的生理反应动态与长期的POP发展有关。
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