目的:探讨脊髓损伤住院患者尿路感染的影响因素。并构建和验证了列线图预测模型。
方法:本研究为回顾性队列研究。2017年1月至2022年3月,安徽省某三甲医院康复医学科收治的558例脊髓损伤患者,选择中国作为研究对象,按7:3的比例随机分为训练组(n=390)和验证组(n=168),临床资料包括社会人口学特征,收集疾病相关数据和实验室检查数据.采用单因素分析和多因素Logistic回归分析脊髓损伤住院患者尿路感染的影响因素。基于此,利用R软件构建了列线图预测模型,并通过受试者工作特性(ROC)曲线和校准曲线验证了列线图模型的风险预测效率。
结果:Logistic回归分析显示,ASIA-E级(与ASIA-A级比较)是脊髓损伤住院患者尿路感染的独立保护因素(OR<1,P<0.05),白细胞计数和留置尿管是脊髓损伤住院患者尿路感染的独立危险因素(OR>1,P<0.05)。基于此,建立了预测脊髓损伤住院康复患者尿路感染的列线图风险预测模型,被证明具有良好的预测效率。在培训组和验证组中,列线图模型的ROC曲线下面积(AUC)为0.808和0.767,训练组和验证组的列线图AUC的95CI为0.760〜0.856和0.688〜0.845,表明列线图模型具有良好的区分度。根据校正曲线,训练组和验证组的列线图模型预测概率与实际尿路感染频率一致性较好,Hosmer-Lemeshow偏倚检验的结果也表明,列线图模型在训练组和验证组中都具有良好的校准度(P=0.329,0.067)。
结论:ASIA分类水平,白细胞计数和留置尿管是脊髓损伤住院患者尿路感染的独立影响因素。基于上述因素的列线图预测模型可以简单有效地预测住院脊髓损伤患者尿路感染风险,有利于临床医务人员及早发现高危人群并实施预防,及时的治疗和护理策略。
OBJECTIVE: To explore the influencing factors of urinary tract infection (UTI) in hospitalized patients with spinal cord injury and to construct and verify the nomogram prediction model.
METHODS: This study is a retrospective cohort study. From January 2017 to March 2022, 558 patients with spinal cord injury admitted to the Department of Rehabilitation Medicine of a tertiary hospital in Anhui Province,
China, were selected as the research objects, and they were randomly divided into training group (n = 390) and verification group (n = 168) according to the ratio of 7:3, and clinical data including socio-demographic characteristics, disease-related data, and laboratory examination data were collected. Univariate analysis and multivariate logistic regression were used to analyze the influencing factors of UTI in hospitalized patients with spinal cord injuries. Based on this, a nomogram prediction model was constructed with the use of R software, and the risk prediction efficiency of the nomogram model was verified by the receiver operating characteristic curve and calibration curve.
RESULTS: Logistic regression analysis showed that the American Spinal Cord Injury Association (ASIA)-E grade (compared with ASIA-A grade) was an independent protective factor for UTI in hospitalized patients with spinal cord injury (odds ratio < 1, P < 0.05), while white blood cell count and indwelling catheter were independent risk factors for UTI in hospitalized patients with spinal cord injury (odds ratio > 1, P < 0.05). Based on this, a nomogram risk predictive model for predicting UTI in hospitalized rehabilitation patients with spinal cord injury was constructed, which proved to have good predictive efficiency. In the training group and the verification group, the area under the receiver operating characteristic curve of the nomogram model is 0.808 and 0.767, and the 95% confidence interval of the area under the receiver operating characteristic curve of the nomogram in the training group and the verification group is 0.760∼0.856 and 0.688∼0.845, respectively, indicating the nomogram model has good discrimination. According to the calibration curve, the prediction probability of the nomogram model and the actual frequency of UTI in the training group and the verification group are in good consistency, and the results of the Hosmer-Lemeshow bias test also suggest that the nomogram model has a good calibration degree in both the training group and the verification group (P = 0.329, 0.067).
CONCLUSIONS: ASIA classification level, white blood cell count, and indwelling catheter are independent influencing factors of UTI in hospitalized patients with spinal cord injury. The nomogram prediction model based on the above factors can simply and effectively predict the risk of UTI in hospitalized patients with spinal cord injury, which is helpful for clinical medical staff to identify high-risk groups early and implement prevention, treatment, and nursing strategies in time.