[Construction and preliminary validation of a risk prediction model for the recurrence of diabetic foot ulcer in diabetic patients].

Objective: To develop a risk prediction model for the recurrence of diabetic foot ulcer (DFU) in diabetic patients and primarily validate its predictive value. Methods: Meta-analysis combined with retrospective cohort study was conducted. The Chinese and English papers on risk factors related to DFU recurrence publicly published in China Biology Medicine disc, China National Knowledge Infrastructure, Wanfang Database, VIP Database, and PubMed, Embase, Cochrane Library, and Web of Science, and the search time was from the establishment date of each database until March 31st, 2022. The papers were screened and evaluated, the data were extracted, a meta-analysis was performed using RevMan 5.4.1 statistical software to screen risk factors for DFU recurrence, and Egger's linear regression was used to assess the publication bias of the study results. Risk factors for DFU recurrence mentioned in ≥3 studies and with statistically significant differences in the meta-analysis were selected as the independent variables to develop a logistic regression model for risk prediction of DFU recurrence. The medical records of 101 patients with DFU who met the inclusion criteria and were admitted to Affiliated Hospital of Guizhou Medical University from January 2019 to June 2022 were collected. There were 69 males and 32 females, aged (63±14) years. The receiver operating characteristic (ROC) curve of the predictive performance of the above constructed predictive model for DFU recurrence was drawn, and the area under the ROC curve, maximum Youden index, and sensitivity and specificity at the point were calculated. Dataset including data of 8 risk factors for DFU recurrence and the DFU recurrence rates of 10 000 cases was simulated using RStudio software and a scatter plot was drawn to determine two probabilities for risk division of DFU recurrence. Using the β coefficients corresponding to 8 DFU recurrence risk factors ×10 and taking the integer as the score of coefficient weight of each risk factor, the total score was obtained by summing up, and the cutoff scores for risk level division were calculated based on the total score × two probabilities for risk division of DFU recurrence. Results: Finally, 20 papers were included, including 3 case-control studies and 17 cohort studies, with a total of 4 238 cases and DFU recurrence rate of 22.7% to 71.2%. Meta-analysis showed that glycosylated hemoglobin >7.5% and with plantar ulcer, diabetic peripheral neuropathy, diabetic peripheral vascular disease, smoking, osteomyelitis, history of amputation/toe amputation, and multidrug-resistant bacterial infection were risk factors for the recurrence of DFU (with odds ratios of 3.27, 3.66, 4.05, 3.94, 1.98, 7.17, 11.96, 3.61, 95% confidence intervals of 2.79-3.84, 2.06-6.50, 2.50-6.58, 2.65-5.84, 1.65-2.38, 2.29-22.47, 4.60-31.14, 3.13-4.17, respectively, P<0.05). There were no statistically significant differences in publication biases of diabetic peripheral neuropathy, diabetic peripheral vascular disease, glycosylated hemoglobin >7.5%, plantar ulcer, smoking, multidrug-resistant bacterial infection, or osteomyelitis (P>0.05), but there was a statistically significant difference in the publication bias of amputation/toe amputation (t=-30.39, P<0.05). The area under the ROC curve of the predictive model was 0.81 (with 95% confidence interval of 0.71-0.91) and the maximum Youden index was 0.59, at which the sensitivity was 72% and the specificity was 86%. Ultimately, 29.0% and 44.8% were identified respectively as the cutoff for dividing the probability of low risk and medium risk, and medium risk and high risk for DFU recurrence, while the corresponding total scores of low, medium, and high risks of DFU recurrence were <37, 37-57, and 58-118, respectively. Conclusions: Eight risk factors for DFU recurrence are screened through meta-analysis and the risk prediction model for DFU recurrence is developed, which has moderate predictive accuracy and can provide guidance for healthcare workers to take interventions for patient with DFU recurrence risk.目的： 构建糖尿病患者糖尿病足溃疡（DFU）复发风险预测模型并初步验证其预测价值。 方法： 采用荟萃分析联合回顾性队列研究方法。检索中国生物医学文献数据库、中国知网、万方数据库、维普数据库及PubMed、Embase、Cochrane Library、Web of Science中公开发表的有关DFU复发危险因素的中英文文献，检索时限为各数据库建立之日至2022年3月31日；筛选、评价文献并提取资料，用RevMan 5.4.1统计软件进行荟萃分析，筛选DFU复发的危险因素；采用Egger线性回归法评估研究结果的发表偏倚情况。将≥3篇文献均提到的且荟萃分析中具有统计学意义的DFU复发危险因素作为自变量，构建DFU复发的logistic回归风险预测模型。收集2019年1月—2022年6月贵州医科大学附属医院收治的符合入选标准的101例DFU患者的病历资料，患者中男69例、女32例，年龄（63±14）岁；绘制前述构建的DFU复发预测模型预测效果的受试者操作特征（ROC）曲线，并计算ROC曲线下面积、最大约登指数及此时的敏感度、特异度。用RStudio软件模拟生成包含10 000例患者8个DFU复发危险因素的数据和DFU复发率的数据集并绘制散点分布图，确定划分DFU复发风险的2个概率。用8个DFU复发危险因素对应的β系数×10并取整数作为各因素系数权重的分值并求和得到总分，按总分×用于DFU复发风险划分的2个概率计算风险等级划分节点分值。 结果： 最终纳入20篇文献，包括3篇病例对照研究和17篇队列研究，总病例数4 238例，DFU复发率为22.7%~71.2%。荟萃分析结果显示，糖化血红蛋白>7.5%、足底溃疡、伴有糖尿病周围神经病变、伴有糖尿病周围血管病变、吸烟、伴有骨髓炎、截肢/截趾、伴有多重耐药菌感染均是DFU复发的危险因素（比值比分别为3.27、3.66、4.05、3.94、1.98、7.17、11.96、3.61，95%置信区间分别为2.79~3.84、2.06~6.50、2.50~6.58、2.65~5.84、1.65~2.38、2.29~22.47、4.60~31.14、3.13~4.17，P<0.05）。糖尿病周围神经病变、糖尿病周围血管病变、糖化血红蛋白>7.5%、足底溃疡、吸烟、多重耐药菌感染、骨髓炎发表偏倚均不具有统计学意义（P>0.05），截肢/截趾发表偏倚具有统计学意义（t=-30.39，P<0.05）。预测模型ROC曲线下面积为0.81（95%置信区间为0.71~0.91），最大约登指数为0.59，此时的敏感度为72%、特异度为86%。最终将29.0%、44.8%分别作为DFU复发低风险和中风险、中风险和高风险概率划分节点，DFU复发低、中、高风险对应总分分别是<37分、37~57分、58~118分。 结论： 通过荟萃分析筛选出8个DFU复发的危险因素并建立DFU复发风险预测模型，该模型预测准确性适中，能够为医护人员针对DFU复发风险人群采取干预措施提供指导。.