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作 者:龙腾飞[1] 黄苗苗[1] 张英[1] 周家德[1] Long Tengfei;Huang Miaomiao;Zhang Ying;Zhou Jiade(Dept of Obstetrics and Gynecology,The First Affiliated Hospital of Anhui Medical University,Hefei 230022)
机构地区:[1]安徽医科大学第一附属医院妇产科,合肥230022
出 处:《安徽医科大学学报》2023年第6期1011-1015,共5页Acta Universitatis Medicinalis Anhui
基 金:安徽省高校科学研究项目(编号:201904a07020046);安徽省重点研究与开发计划项目(编号:KJ2019A0288)。
摘 要:目的探索子宫肌瘤患者全子宫切除术后发热的高危因素,并建立列线图预测模型,为临床诊治提供理论指导。方法收集因子宫肌瘤行全子宫切除的患者资料,6∶4随机拆分为训练组及验证组,用χ2检验及Logistic回归模型分析进行单因素及多因素分析。基于多因素分析,结果建立列线图,并采用校准曲线、受试者工作特征曲线评估列线图的预测能力及精准度,决策曲线反应该模型的临床应用价值。结果训练组264例患者,发热患者共33例,术后病率为12.50%。经单因素及多因素分析结果显示,贫血、术前诊刮、手术范围、手术时间是子宫肌瘤患者全子宫切除术后发热独立危险因素。基于多因素结果建立的列线图经过验证,内外部验证校准曲线与实际观测结果拟合性较好,平均误差分别为0.031、0.025。模型内外部验证的受试者工作特征曲线下面积分别为0.788、0.712,反映了模型较好的预测能力。决策曲线显示模型在一定阈值范围内有较好的临床获益。结论基于多因素分析结果得到的4个子宫肌瘤患者全子宫切除术后发热独立危险因素包括贫血、术前诊刮、手术范围、手术时间;该研究建立的列线图有助于临床医师对子宫肌瘤患者全子宫切除术后发热的及时管理,指导临床个体化治疗。Objective To explore the risk factors of fever after hysterectomy in patients with uterine fibroids,and establish a nomogram prediction model to provide theoretical guidance for clinical diagnosis and treatment.Methods The data of patients who underwent hysterectomy due to uterine fibroids were collected and randomly divided into training group and validation group at 6∶4.Univariate and multivariate analyses were performed byχ2 test and Logistic regression model analysis.The nomogram was established based on the results of multivariate analysis,the calibration curve and receiver operating characteristic,curve were used to evaluate the prediction ability and accuracy of the nomogram.The decision curve reflected the clinical application value of the model.Results Among 264 patients in the training group,33 patients had fever,and the postoperative disease rate was 12.5%.The results of univariate and multivariate analysis showed that anemia,preoperative curettage,operation scope and operation time were independent risk factors for fever after hysterectomy in patients with uterine fibroids.The internal and external calibration curves had a good fit with the actual observation results,with an average error of 0.031 and 0.025,respectively.The area under receiver operating characteristic curve of the internal and external verification of the nomogramare 0.788 and 0.712,respectively,reflecting the good predictive ability of the model.The decision curve showed that the model had good clinical benefit in a certain threshold range.Conclusion Based on multivariate analysis,the independent risk factors of fever after hysterectomy in patients with uterine fibroids,including anemia,preoperative curettage,operation scope and operation time.In addition,we established a nomogram with good predictive ability and accuracy,which is helpful for clinicians to timely manage fever after hysterectomy in patients with uterine fibroids and guide clinical individualized treatment.
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