预测头颈部手术并发症:计算器与外科医生的比较。

Kelly C Landeen, Kelly L Vittetoe, Miriam Smetak, Wu Gong, Christopher J Lindsell, Carey Burton Wood, Marc Bennett
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引用次数: 0

摘要

目的:手术效果决定着国家排名、声誉和资金,通常使用客观的手术风险计算器(SRC)进行评估。外科医生的评估不在考虑之列。本研究旨在确定是外科医生还是 SRC 在预测结果方面更准确。方法:这项前瞻性队列研究确定了外科医生对患者术前风险的评估。患者的风险也是通过 SRC 计算得出的。将预测结果与患者预后进行比较,并相互比较,以评估是外科医生更准确还是 SRC 更准确。结果:在纳入的 101 名患者中,37 人(36.6%)出现了任何类型的并发症,18 人(17.8%)出现了严重并发症。吸烟导致总并发症发生率高出 2.49 倍(P = .04)。与接受游离皮瓣重建手术的患者相比,喉切除术患者的并发症发生率最高(P = .02)[几率比 (OR) 0.9] 或其他任何手术(OR 0.26)。外科医生和美国外科医生学会(ACS)的工具在预测任何并发症的结果方面都表现不佳,曲线下接收器操作特征(ROC)面积(AUC)分别为 0.51 [95% 置信区间 (CI):0.39-0.62] 和 0.58 (95% CI:0.47-0.70),无统计学意义(P = .34)。在预测严重并发症结果方面,外科医生和 ACS 工具的 AUC 分别为 0.55(95% CI:0.41-0.69)和 0.60(95% CI:0.46-0.74),差异无统计学意义(P = .58)。结论经过验证的风险计算器和外科医生都不能准确预测围手术期风险。唯一有助于改善并发症预测的风险因素是术前吸烟,尽管年龄和手术类型也是重要的预测因素。因此,风险计算器可能不是评估医院绩效的合适指标。这些发现有助于指导术前咨询,并可能有助于开发更准确的预测工具,因为医疗保健领域将继续把人工智能纳入手术规划。
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Predicting Complications in Head and Neck Surgery: Comparing Calculators to Surgeons.

Objectives: Surgical outcomes determine national ranking, reputation, and funding, and are often assessed with objective surgical risk calculators (SRCs). Surgeons' assessments are not considered. This study aims to determine if surgeons or SRCs are more accurate in predicting outcomes. Methods: This prospective cohort study identified a surgeon's assessment on a patient's risk preoperatively. The patient's risk was also calculated using the SRC. Predictions were compared to patient outcomes and to each other to assess whether surgeons or the SRC were more accurate. Results: Of the 101 patients included, 37 (36.6%) experienced a complication of any kind and 18 (17.8%) experienced a serious complication. Smoking resulted in a 2.49 times higher overall complication rate (P = .04). Laryngectomy patients experienced the highest rate of complications (P = .02) compared to those undergoing free flap reconstruction [odds ratio (OR) 0.9] or any other surgery (OR 0.26). Both surgeons and the American College of Surgeons (ACS) tool performed poorly on the prediction of the outcome of any complication, with a receiver operating characteristic (ROC) area under the curve (AUC) of 0.51 [95% confidence interval (CI): 0.39-0.62] and 0.58 (95% CI: 0.47-0.70), respectively, which was not statistically significant (P = .34). For the prediction of the outcome of serious complication, the AUC for surgeons and the ACS tool were 0.55 (95% CI: 0.41-0.69) and 0.60 (95% CI: 0.46-0.74), respectively, which was not statistically significant (P = .58). Conclusions: Neither validated risk calculators nor surgeons are accurate in predicting perioperative risk. The only risk factor that contributes to improving predictions for complications is preoperative smoking, although age and type of surgery are also significant predictors. Risk calculators may therefore not be appropriate metrics for assessing hospital performance. These findings can help guide preoperative counseling and may help in the development of more accurate predictive tools as the healthcare field continues to incorporate artificial intelligence into surgical planning.

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