达芬奇机器人辅助泌尿外科肿瘤切除术中老年患者术中低温预测图的开发和验证:一项回顾性队列研究。

IF 1 4区 医学 Q4 CRITICAL CARE MEDICINE
Xiaoyan Song, Siyu Jin, Minghui Ma, Haiwen Zheng, Liang Xin, Liu Tiantian
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引用次数: 0

摘要

本研究旨在构建机器人辅助泌尿外科肿瘤切除术(RAUTR)老年患者术中低温(IH)的Nomogram,并通过内外验证对模型的效果进行评价。采用方便的抽样方法,将2022年2月至2024年7月在某大型医院就诊的患者作为建模和验证队列。通过单因素和多因素logistic回归分析确定IH的独立危险因素,并利用R软件制作Nomogram。采用受试者工作特征(ROC)曲线和Hosmer-Lemeshow (H-L)检验检验Nomogram辨别性和准确性,用1000个Bootstrap样本和校准曲线进行内部验证。采用ROC曲线和H-L检验对验证队列进行外部评价。建模队列包括420例患者,IH率为39.8%。单因素和多因素logistic回归分析显示,基线温度(优势比[OR] = 0.087)、术前心理评分(OR = 1.114)、体重指数(BMI) (OR = 0.820)和麻醉时间(OR = 1.013)是IH的独立危险因素。Nomogram ROC曲线的曲线下面积为0.844(95%可信区间[CI]: 0.807-0.881),最大约登指数为0.563,最佳截断值为0.383,敏感性为0.772,特异性为0.791。H-L检验的卡方值为10.173,p值为0.253。1000个Bootstrap样本的内部验证一致性系数为0.844,校准曲线拟合良好。验证队列共纳入120例患者,包括45例低温患者(37.5%)。外部验证队列预测IH的ROC曲线下面积为0.854 (95% CI: 0.781-0.927), H-L检验的卡方值为5.207,p值为0.735。老年RAUTR患者的IH率较高。基线体温、术前心理评分、BMI、麻醉时间为独立危险因素。Nomogram可以用来预测IH。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development and Validation of a Predictive Nomogram for Intraoperative Hypothermia in Elderly Patients Undergoing Da Vinci Robot-Assisted Urological Tumor Resection: A Retrospective Cohort Study.

This study aims to construct a Nomogram for intraoperative hypothermia (IH) in elderly patients undergoing robot-assisted urological tumor resection (RAUTR) and to evaluate the effect of the model by internal and external validation. Using convenient sampling to enroll patients in a large hospital from February 2022 to July 2024 as the modeling and validation cohort. Identifying the independent risk factors for IH by univariate and multivariate logistic regression, and developing a Nomogram by the R software. The Nomogram's discrimination and accuracy were tested by receiver operating characteristic (ROC) curves and the Hosmer-Lemeshow (H-L) test, internal validation was performed with 1000 Bootstrap resamples and calibration curves. External evaluation was conducted on a validation cohort using ROC curves and H-L tests. The modeling cohort included 420 patients, with an IH rate of 39.8%. Univariate and multivariate logistic regression showed that baseline temperature (odds ratio [OR] = 0.087), preoperative psychological score (OR = 1.114), body mass index (BMI) (OR = 0.820), and anesthesia time (OR = 1.013) were independent risk factors for IH. The ROC curve of the Nomogram had an area under the curve of 0.844 (95% confidence interval [CI]: 0.807-0.881), a maximum Youden index of 0.563, a best cutoff value of 0.383, a sensitivity of 0.772, and a specificity of 0.791. The H-L test yielded a chi-square value of 10.173 and a p-value of 0.253. Internal validation with 1000 Bootstrap resamples showed a consistency coefficient of 0.844, the calibration curve fits well. A total of 120 patients were included in the validation cohort, including 45 with hypothermia (37.5%). The area under the ROC curve for the prediction of IH in the external validation cohort was 0.854 (95% CI: 0.781-0.927), and the H-L test yielded a chi-square value of 5.207 and a p-value of 0.735. The IH rate is high in elderly patients undergoing RAUTR. Baseline temperature, preoperative psychological score, BMI, and anesthesia time are independent risk factors. And the Nomogram could be used to predict IH.

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来源期刊
CiteScore
2.50
自引率
8.30%
发文量
35
期刊介绍: Therapeutic Hypothermia and Temperature Management is the first and only journal to cover all aspects of hypothermia and temperature considerations relevant to this exciting field, including its application in cardiac arrest, spinal cord and traumatic brain injury, stroke, burns, and much more. The Journal provides a strong multidisciplinary forum to ensure that research advances are well disseminated, and that therapeutic hypothermia is well understood and used effectively to enhance patient outcomes. Novel findings from translational preclinical investigations as well as clinical studies and trials are featured in original articles, state-of-the-art review articles, protocols and best practices. Therapeutic Hypothermia and Temperature Management coverage includes: Temperature mechanisms and cooling strategies Protocols, risk factors, and drug interventions Intraoperative considerations Post-resuscitation cooling ICU management.
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