Incidence and risk factors of chronic post-thoracic surgery pain: A retrospective study.

H Rivera-Ramos, L Larrañaga-Altuna, M García-Olivera, M Armengol-Gay, M Soldevilla-García, S Bermejo-Martínez
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Abstract

Background: Chronic post-thoracic surgery pain (CPTSP) is a common complication that affects a patient's quality of life. Thoracotomy is associated with a high risk of chronic pain. Video-assisted thoracoscopy surgery (VATS) is a less traumatic option, but its role in the development of CPTSP is unclear. Regardless of the approach, there is evidence that demographic, psychosocial, or clinical factors also contribute to pain. The primary objective of this study is to determine the incidence of CPTSP in our hospital. The secondary objective is to identify possible risk factors related to CPTSP.

Method: Retrospective, single-centre observational study. The medical records of patients that underwent thoracic surgery between January 2016 and January 2020 were reviewed. The diagnosis of CPTSP was made by reviewing the postoperative visits 6 months after surgery. We analysed the relationship between CPTSP and a series of variables, and then constructed a multivariate binary logistic regression model with a significance level of p < 0.05.

Results: A total of 259 patients were analysed, 46.7% underwent VATS and 53.3% underwent thoracotomy. The overall incidence of CPTSP was 12%; 4.1% in VATS and 18.8% in thoracotomies. The multivariate model revealed that acute postoperative pain severe and a greater number of chest tubes were risk factors for CPTSP.

Conclusion: The incidence of CPTSP was 12% in our hospital. Patients with higher acute postoperative pain severe and several chest tubes were more likely to develop CPTSP.

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胸外科手术后慢性疼痛的发生率和风险因素:回顾性研究
背景:胸外科手术后慢性疼痛(CPTSP)是影响患者生活质量的常见并发症。胸廓切开术与慢性疼痛的高风险相关。视频辅助胸腔镜手术(VATS)创伤较小,但其在 CPTSP 发生中的作用尚不清楚。无论采用哪种方法,有证据表明人口、社会心理或临床因素也会导致疼痛。本研究的主要目的是确定 CPTSP 在我院的发病率。次要目的是确定与 CPTSP 相关的可能风险因素:方法:回顾性单中心观察研究。方法:回顾性单中心观察研究,回顾 2016 年 1 月至 2020 年 1 月期间接受胸外科手术患者的病历。CPTSP 的诊断是通过回顾术后 6 个月的就诊情况得出的。我们分析了 CPTSP 与一系列变量之间的关系,然后构建了一个多变量二元逻辑回归模型,显著性水平为 p
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