[Summary of the best evidence on exercise for the prevention and treatment of diabetic foot].

Objective: To summarize the best evidence on exercise for the prevention and treatment of diabetic foot. Methods: A bibliometric approach was used. Systematic searches were carried out to retrieve all the publicly published evidences till July 2022 on exercise for the prevention and treatment of diabetic foot, including guidelines, evidence summary, recommended practices, expert consensus, systematic review, and original research, from foreign language databases including BMJ Best Practice, UpToDate, Joanna Briggs Institute Evidence-Based Practice Database, Cochrane Library, Embase, PubMed, Guideline International Network, National Guideline Clearinghouse, Chinese databases including China National Knowledge Infrastructure, Wanfang Database, VIP Database, China Biology Medicine disc, China Clinical Guidelines Library, and the official websites of relevant academic organizations including National Institute for Health and Care Excellence of the United Kingdom, Registered Nurses' Association of Ontario of Canada, the International Working Group on the Diabetic Foot, International Diabetes Federation, American College of Sports Medicine, American Diabetes Association, and Chinese Diabetes Society. The literature was screened and evaluated for the quality, from which the evidences were extracted and evaluated to summarize the best evidences. Results: Nine guidelines, three expert consensuses, one evidence summary (with two systematic reviews being traced), two systematic reviews, 6 randomized controlled trials were retrieved and included, with good quality of literature. Totally 33 pieces of best evidences on exercise for the prevention and treatment of diabetic foot were summarized from the aspects of appropriate exercise prevention of diabetic foot, exercise therapy of diabetic foot, precautions for exercise, health education, and establishment of a multidisciplinary limb salvage team. Conclusions: Totally 33 pieces of best evidences on exercise for the prevention and treatment of diabetic foot were summarized from 5 aspects, providing decision-making basis for clinical guidance on exercise practice for patients with diabetic foot.

[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 ß 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.