Predictive Model for Emergence Agitation in Patients Awakening From General Anaesthesia After Transurethral Resection of the Prostate

IF 2 4区医学 Q2 NURSING

International Journal of Nursing Practice Pub Date : 2025-08-22 DOI:10.1111/ijn.70041

Qinqin Cao, Haihong Meng, Shuling Bai, Hemin Dong, Shouxin Zhang, Chengjuan Fan

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引用次数: 0

Abstract

Aims

The aim of this study was to develop and verify a new emergence agitation risk prediction model based on the electronic medical records of patients undergoing transurethral resection of the prostate.

Background

The incidence of prostate disease in elderly men is high, and the harm caused by emergence agitation in patients after transurethral resection of the prostate is serious. It is necessary to develop a predictive model for emergence agitation in patients undergoing transurethral resection of the prostate.

Design

This was a retrospective cohort study. Patients who underwent transurethral resection of the prostate from January 2016 to December 2020 formed the study population.

Methods

The multivariate logistic backward stepwise method was used to further evaluate the variables with p-values of less than 0.1 in the univariate analysis. A receiver operating characteristic curve was used to analyse the discrimination of models, and the Hosmer–Lemeshow test was used to evaluate calibration.

Results

A total of 956 patients undergoing transurethral resection of the prostate were included in the study. The incidence of emergence agitation in the deduction data set and the verification data set were 24.6% and 23.2%, respectively. Multiple logistic regression analysis showed that age (OR = 1.05, 95% CI, 1.02–1.09), urea (OR = 1.14, 95% CI, 1.05–1.29), postoperative pain (OR = 3.74, 95% CI, 1.99–7.03) and catheter-related bladder discomfort (OR = 2.26, 95% CI, 1.80–2.84) were independent predictors of emergence agitation in patients with transurethral resection of the prostate. The prediction model showed good discrimination in both the derivation dataset and the verification dataset (the area under the curve was 0.737 and 0.804, respectively) and calibration (Hosmer–Lemeshow test p = 0.895 and 0.418, respectively).

Conclusion

This low-cost low-risk clinical prediction model based on electronic medical records is simple and practical, easy to generalize, and contributes to health care providers identifying individuals at high risk of emergence agitation in patients undergoing transurethral resection of the prostate.

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经尿道前列腺切除术后全麻苏醒患者出现躁动的预测模型

目的基于经尿道前列腺切除术患者的电子病历，建立并验证一种新的出现躁动风险预测模型。背景老年男性前列腺疾病发病率高，经尿道前列腺切除术后患者出现躁动造成的危害严重。因此，有必要建立一个预测经尿道前列腺切除术患者出现躁动的模型。设计本研究为回顾性队列研究。2016年1月至2020年12月接受经尿道前列腺切除术的患者构成研究人群。方法采用多元logistic逐步回归法对单因素分析中p值小于0.1的变量进行进一步评价。采用受试者工作特征曲线分析模型的判别性，采用Hosmer-Lemeshow检验评价模型的校准。结果共纳入956例经尿道前列腺切除术患者。推演数据集和验证数据集的紧急搅拌发生率分别为24.6%和23.2%。多元logistic回归分析显示，年龄（OR = 1.05, 95% CI, 1.02-1.09）、尿素（OR = 1.14, 95% CI, 1.05 - 1.29）、术后疼痛（OR = 3.74, 95% CI, 1.99-7.03）和导管相关性膀胱不适（OR = 2.26, 95% CI, 1.80-2.84）是经尿道前列腺切除术患者出现躁动的独立预测因素。该预测模型在衍生数据集和验证数据集（曲线下面积分别为0.737和0.804）和校准数据集（Hosmer-Lemeshow检验p分别= 0.895和0.418）上均表现出良好的判别性。结论基于电子病历的低成本低风险临床预测模型简单实用，易于推广，有助于卫生保健人员识别经尿道前列腺切除术患者出现躁动的高危个体。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Nursing Practice NURSING-

CiteScore

4.10

自引率

0.00%

发文量

审稿时长

3 months

期刊介绍： International Journal of Nursing Practice is a fully refereed journal that publishes original scholarly work that advances the international understanding and development of nursing, both as a profession and as an academic discipline. The Journal focuses on research papers and professional discussion papers that have a sound scientific, theoretical or philosophical base. Preference is given to high-quality papers written in a way that renders them accessible to a wide audience without compromising quality. The primary criteria for acceptance are excellence, relevance and clarity. All articles are peer-reviewed by at least two researchers expert in the field of the submitted paper.