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Abstract：
BACKGROUND: We aimed to determine whether systemic immune-inflammation index (SII) combined with prealbumin can provide better predictive power for postoperative pneumonia in patients undergoing lung resection surgery.
METHODS: We identified eligible patients undergoing lung resection surgery at the Affiliated Hospital of Nantong University from March 2021 to March 2022. Demographic characteristics, clinical data, and laboratory information were collected and reviewed from the electronic medical records of the patients. To test the effect of the combined detection of SII and prealbumin, we made an equation using logistic regression analysis. The receiver operating characteristic curve (ROC) was plotted to evaluate the predictive powers, sensitivity, and specificity of prealbumin, SII, and SII combined with prealbumin. Decision curve analysis (DCA) was used to determine the clinical validity and net benefit of different methods of detection.
RESULTS: Totally 386 eligible patients were included with a median age of 62.0 years (IQR: 55.0, 68.0), and 57 (14.8%) patients presented with postoperative pneumonia within 7 days after surgery. The multivariate regression analysis showed that preoperative SII as continuous variable was associated with an increased risk of postoperative pneumonia (OR: 1.38, 95% CI: 1.19-2.83, P = 0.011), whereas the prealbumin as continuous variable remained as an independent protective predictor of postoperative pneumonia in the adjusted analysis (OR: 0.80, 95% CI: 0.37-0.89, P = 0.023). Compared to SII or prealbumin, the combined detection of preoperative SII and prealbumin showed a higher predictive power with area under curve of 0.79 (95% CI: 0.71-0.86, P < 0.05 for all). Additionally, DCA indicated that the combined detection was superior over preoperative SII or prealbumin alone in clinical validity and net benefit.
CONCLUSIONS: Both preoperative SII and prealbumin are independent influencing factors for postoperative pneumonia after lung resection surgery. The combined detection of preoperative SII and prealbumin can significantly improve prediction capability to identify potential postoperative pneumonia-susceptible patients, facilitating early interventions to improve postoperative quality of life for surgical lung resection patients.
METHODS: We identified eligible patients undergoing lung resection surgery at the Affiliated Hospital of Nantong University from March 2021 to March 2022. Demographic characteristics, clinical data, and laboratory information were collected and reviewed from the electronic medical records of the patients. To test the effect of the combined detection of SII and prealbumin, we made an equation using logistic regression analysis. The receiver operating characteristic curve (ROC) was plotted to evaluate the predictive powers, sensitivity, and specificity of prealbumin, SII, and SII combined with prealbumin. Decision curve analysis (DCA) was used to determine the clinical validity and net benefit of different methods of detection.
RESULTS: Totally 386 eligible patients were included with a median age of 62.0 years (IQR: 55.0, 68.0), and 57 (14.8%) patients presented with postoperative pneumonia within 7 days after surgery. The multivariate regression analysis showed that preoperative SII as continuous variable was associated with an increased risk of postoperative pneumonia (OR: 1.38, 95% CI: 1.19-2.83, P = 0.011), whereas the prealbumin as continuous variable remained as an independent protective predictor of postoperative pneumonia in the adjusted analysis (OR: 0.80, 95% CI: 0.37-0.89, P = 0.023). Compared to SII or prealbumin, the combined detection of preoperative SII and prealbumin showed a higher predictive power with area under curve of 0.79 (95% CI: 0.71-0.86, P < 0.05 for all). Additionally, DCA indicated that the combined detection was superior over preoperative SII or prealbumin alone in clinical validity and net benefit.
CONCLUSIONS: Both preoperative SII and prealbumin are independent influencing factors for postoperative pneumonia after lung resection surgery. The combined detection of preoperative SII and prealbumin can significantly improve prediction capability to identify potential postoperative pneumonia-susceptible patients, facilitating early interventions to improve postoperative quality of life for surgical lung resection patients.
摘要：
背景：我们旨在确定全身免疫炎症指数（SII）联合前白蛋白是否可以为接受肺切除术的患者术后肺炎提供更好的预测能力。
方法：我们确定了2021年3月至2022年3月在南通大学附属医院接受肺切除手术的合格患者。人口特征，临床资料,以及从患者的电子病历中收集和审查实验室信息。为了测试联合检测SII和前白蛋白的效果，我们用逻辑回归分析建立了一个方程。绘制受试者工作特性曲线（ROC）以评估预测能力，灵敏度,和前白蛋白的特异性，SII,和SII结合前白蛋白。使用决策曲线分析（DCA）来确定不同检测方法的临床有效性和净收益。
结果：共纳入386名符合条件的患者，中位年龄为62.0岁（IQR：55.0、68.0）。57例(14.8%)患者在术后7天内出现术后肺炎。多因素回归分析显示,术前SII作为连续变量与术后肺炎风险增加相关(OR:1.38,95%CI:1.19~2.83,P=0.011),而在校正分析中,前白蛋白作为连续变量仍然是术后肺炎的独立保护性预测因子(OR:0.80,95%CI:0.37-0.89,P=0.023).与SII或前白蛋白相比，术前联合检测SII和前白蛋白显示出更高的预测能力，曲线下面积为0.79（95％CI：0.71-0.86，P<0.05）。此外,DCA表明，联合检测在临床有效性和净收益方面优于术前SII或单独的前白蛋白。
结论：术前SII和前白蛋白均是肺切除术后肺炎的独立影响因素。术前联合检测SII和前白蛋白可显著提高对潜在术后肺炎易感患者的预测能力。促进早期干预，以提高外科肺切除术患者的术后生活质量。
方法：我们确定了2021年3月至2022年3月在南通大学附属医院接受肺切除手术的合格患者。人口特征，临床资料,以及从患者的电子病历中收集和审查实验室信息。为了测试联合检测SII和前白蛋白的效果，我们用逻辑回归分析建立了一个方程。绘制受试者工作特性曲线（ROC）以评估预测能力，灵敏度,和前白蛋白的特异性，SII,和SII结合前白蛋白。使用决策曲线分析（DCA）来确定不同检测方法的临床有效性和净收益。
结果：共纳入386名符合条件的患者，中位年龄为62.0岁（IQR：55.0、68.0）。57例(14.8%)患者在术后7天内出现术后肺炎。多因素回归分析显示,术前SII作为连续变量与术后肺炎风险增加相关(OR:1.38,95%CI:1.19~2.83,P=0.011),而在校正分析中,前白蛋白作为连续变量仍然是术后肺炎的独立保护性预测因子(OR:0.80,95%CI:0.37-0.89,P=0.023).与SII或前白蛋白相比，术前联合检测SII和前白蛋白显示出更高的预测能力，曲线下面积为0.79（95％CI：0.71-0.86，P<0.05）。此外,DCA表明，联合检测在临床有效性和净收益方面优于术前SII或单独的前白蛋白。
结论：术前SII和前白蛋白均是肺切除术后肺炎的独立影响因素。术前联合检测SII和前白蛋白可显著提高对潜在术后肺炎易感患者的预测能力。促进早期干预，以提高外科肺切除术患者的术后生活质量。
