中国口腔颌面外科杂志

中国口腔颌面外科杂志 ›› 2023, Vol. 21 ›› Issue (2): 131-136.doi: 10.19438/j.cjoms.2023.02.005

• 论著 • 上一篇    下一篇

头颈癌游离皮瓣患者术后谵妄危险因素及NLR的临床价值分析

沈梦圆1, 张雪莹1, 赵姗1, 徐欣晨2, 李晓东2,*, 孟箭1,2,*   

  1. 1.蚌埠医学院,安徽 蚌埠 233000;
    2.徐州市中心医院 口腔科,江苏 徐州 221000
  • 收稿日期:2022-07-27 修回日期:2022-10-04 出版日期:2023-03-20 发布日期:2023-06-12
  • 通讯作者: 孟箭,E-mail: mrocket@126.com;李晓东,E-mail: 863303398@qq.com。*共同通信作者
  • 作者简介:沈梦圆（1998-）,男,在读硕士研究生,E-mail: 1737790093@qq.com
  • 基金资助:
    国家口腔疾病临床医学研究中心开放课题（NCRCO-202101）; 徐州市科技计划项目（KC21187）; 徐州市中心医院优秀人才基金项目（XYFY2020035）

Risk factors and clinical value of neutrophil-to-lymphocyte ratio in prediction of delirium after free flap surgery for head and neck cancer

SHEN Meng-yuan1, ZHANG Xue-ying1, ZHAO Shan1, XU Xin-chen2, LI Xiao-dong2, MENG Jian1,2   

  1. 1. Bengbu Medical College. Bengbu 233000, Anhui Province;
    2. Department of Stomatology, Xuzhou Central Hospital. Xuzhou 221000, Jiangsu Province, China
  • Received:2022-07-27 Revised:2022-10-04 Online:2023-03-20 Published:2023-06-12

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摘要： 目的： 研究头颈癌患者游离皮瓣重建术后谵妄（POD）发生率和危险因素,构建风险预测模型,探讨中性粒细胞/淋巴细胞比值（NLR）是否具有成为头颈癌患者游离皮瓣重建术后谵妄生物标志物的潜力。方法： 收集徐州市中心医院2016年1月—2022年3月行游离皮瓣重建的头颈恶性肿瘤住院患者128例,术后至出院每天根据《谵妄评估量表》评估患者是否谵妄并分为谵妄组和非谵妄组。采用SPSS 26.0软件包分析患者POD相关危险因素并用Logistic建立预测模型,以ROC曲线下面积检验模型预测效果及最佳截断值下的敏感度和特异度。结果： POD发生率为13.3%(17/128)。单因素分析显示,年龄≥65岁、术前NLR、术前总蛋白、手术时间、术中输血、术后ICU观察时间、术后睡眠紊乱、术后VAS评分具有统计学意义(P<0.05)。多因素Logistic回归分析显示,年龄≥65岁(OR=5.253;95%CI：1.146~24.074)、术前高NLR（OR=1.891;95%CI：1.050~3.405）、术中输血（OR=6.108;95%CI：1.109~33.644）、术后睡眠紊乱（OR=9.292;95%CI：1.441~59.914）、术后疼痛（OR=1.807;95%CI：1.018~3.206）是POD的独立危险因素。NLR-预测模型ROC曲线AUC=0.913,约登指数为0.522,NLR最佳截断值为2.540,灵敏度为0.765,特异度为0.757。结论： NLR-预测模型对头颈癌游离皮瓣重建患者POD预测价值良好,NLR具有生物标志物的潜力,可用于临床指导早期干预与治疗。

关键词: 头颈癌, 中性粒细胞与淋巴细胞比值, 术后谵妄, 危险因素预测模型

Abstract: PURPOSE: To investigate the incidence and risk factors of postoperative delirium (POD) after free flap reconstruction in patients with head and neck cancer, and then establish the risk prediction model and investigate whether neutrophil-to-lymphocyte ratio (NLR) has potential to be a biomarker for prediction of delirium. METHODS: A retrospective analysis of 128 patients who underwent free flap surgery for head and neck cancer in Xuzhou Central Hospital between January 2016 to March 2022 were performed. The patients were evaluated daily after surgery until discharge for delirium with Confusion Assessment Method (CAM), and they were divided into delirium group and non-delirium group. The related risk factors of delirium were analyzed using SPSS 26.0 software package. Logistic regression was used to screen clinical indicators and develop a risk prediction model. The predictive power of the model was verified by the area under the receiver operating characteristic curve(AUC) of the prediction model and the sensitivity and specificity under the optimal threshold. RESULTS: A total of 17(13.3%) patients had POD. Single factor analysis results indicated that POD was associated with age≥65, preoperative NLR, preoperative total protein, time of operation, intraoperative blood transfusion, postoperative ICU observation time, postoperative sleep disorder and postoperative pain. Multiple logistic regression analysis showed that the independent risk factors of POD included age≥65(OR=5.253; 95%CI: 1.146-24.074), preoperative NLR(OR=1.891; 95%CI: 1.050-3.405), intraoperative blood transfusion(OR=6.108; 95%CI: 1.109-33.644), postoperative sleep disorder (OR=9.292; 95%CI: 1.441-59.914) and postoperative pain(OR=1.807; 95%CI: 1.018-3.206). The receiver operating characteristic curve of the NLR-predictive model constructed using these risk factors was AUC=0.913, the Youden's index was 0.522, the best cutoff for NLR was 2.540, the sensitivity was 0.765 and the specificity was 0.757. CONCLUSIONS: NLR predictive model has good predictive value for POD in patients with head and neck cancer after free flap reconstruction. NLR has the potential as a biomarker, which can be used to guide early intervention and treatment in clinical practice.

Key words: Head and neck cancer, Neutrophil-to-lymphocyte ratio, Postoperative delirium, Risk factor Prediction model

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