Design and clinical application of a risk prediction model for diabetic foot.

OBJECTIVE: To construct and evaluate a nomogram prediction model for the risk of diabetic foot in patients with type 2 diabetes based on their clinical data, and to assist clinical healthcare professionals in identifying high-risk factors and developing targeted intervention measures. METHODS: We retrospectively collected clinical data from 478 hospitalized patients with type 2 diabetes at the First Affiliated Hospital of Shantou University Medical College from January 2019 to December 2021. The patients were divided into a diabetic foot group (n=312) and a non-diabetic foot group (n=166) based on whether they had diabetic foot. The baseline data of both groups were collected. Univariate and multivariate analyses as well as logistic regression analysis were conducted to explore the risk factors for diabetic foot. A nomogram prediction model was established using the package "rms" version 4.3. The model was internally validated using the area under the receiver operating characteristic curve (AUC). Additionally, the decision curve analysis (DCA) was performed to evaluate the performance of the nomogram model. RESULTS: The results from the logistic regression analysis revealed that being male, smoking, duration of diabetes, glycated hemoglobin, hyperlipidemia, and atherosclerosis were influencing factors for diabetic foot (all P<0.05). The AUC of the model in predicting diabetic foot was 0.804, with a sensitivity of 75.3% and specificity of 74.4%. Harrell's C-index of the nomogram prediction model for diabetic foot was 0.804 (95% CI: 0.762-0.844), with a threshold value of >0.675. The DCA findings demonstrated that the nomogram model provided a net clinical benefit. CONCLUSION: The nomogram prediction model constructed in this study showed good predictive performance and can provide a basis for clinical workers to prevent and intervene in diabetic foot, thereby improving the overall diagnosis and treatment.

Establishment and Reliability Evaluation of Prognostic Models in Diabetic Foot.

Purpose: To study the risk factors affecting amputation and survival in patients with diabetic foot (DF) and to construct a predictive model using the machine learning technique for DF foot amputation and survival and evaluate its effectiveness. Materials and Methods: A total of 200 patients with DF hospitalized in the First Affiliated Hospital of Shantou University Medical College in China were selected via cluster analysis screening, Kaplan-Meier survival calculation, amputation rate and Cox proportional hazards model investigation of risk factors associated with amputation and death. In addition, we constructed various models, including Cox proportional hazards regression analysis, the deep learning method convolution neural network (CNN) model, backpropagation (BP) neural network model, and backpropagation neural network prediction model after optimizing the genetic algorithm. The accuracy of the 4 prediction models for survival and amputation was assessed, and we evaluated the reliability of these computational models based on the size of the area under the ROC curve (AUC), sensitivity and specificity. Results: We found that the 1-year survival rate in patients with DF was 88.5%, and the 1-year amputation rate was 12.5%. Wagner's Classification of Diabetic Foot Ulcers grade, ankle-brachial index (ABI), low-density lipoprotein (LDL), and percutaneous oxygen partial pressure (TcPO2) were independent risk factors for amputation in patients with DF, while cerebrovascular disease, Sudoscan sweat gland function score, glycated hemoglobin (HbA1c) and peripheral artery disease (PAD) were independent risk factors for death in patients with DF. In addition, our results showed that in the case of amputation, the COX regression predictive model revealed an AUC of 0.788, sensitivity of 74.1% and specificity of 83.6%. The BP neural network predictive model identified an AUC of 0.874, sensitivity of 87.0% and specificity of 87.7%. An AUC of 0.909, sensitivity of 90.7% and specificity of 91.1% were found after optimizing the BP neural network prediction model via genetic algorithm. In the deep learning CNN model, the AUC, sensitivity and specificity were 0.939, 92.6%, and 95.2%, respectively. In the analysis of risk factors for death, the COX regression predictive model identified the AUC, sensitivity and specificity as 0.800, 74.1% and 85.9%, respectively. The BP neural network predictive model revealed an AUC, sensitivity and specificity of 0.937, 93.1% and 94.4%, respectively. Genetic algorithm-based optimization of the BP neural network predictive model identified an AUC, sensitivity and specificity of 0.932, 91.4% and 95.1%, respectively. The deep learning CNN model found the AUC, sensitivity and specificity to be 0.861, 82.8% and 89.4%, respectively. Conclusion: To identify risk factors for death, the BP neural network predictive model and genetic algorithm-based optimizing BP neural network predictive model have higher sensitivity and specificity than the deep learning method CNN predictive model and COX regression analysis.

Reduced stress-associated FKBP5 DNA methylation together with gut microbiota dysbiosis is linked with the progression of obese PCOS patients.

Polycystic ovary syndrome (PCOS) is a common endocrine disease in females that is characterized by hyperandrogenemia, chronic anovulation, and polycystic ovaries. However, the exact etiology and pathogenesis of PCOS are still unknown. The aim of this study was to clarify the bacterial, stress status, and metabolic differences in the gut microbiomes of healthy individuals and patients with high body mass index (BMI) PCOS (PCOS-HB) and normal BMI PCOS (PCOS-LB), respectively. Here, we compared the gut microbiota characteristics of PCOS-HB, PCOS-LB, and healthy controls by 16S rRNA gene sequencing, FK506-binding protein 5 (FKBP5) DNA methylation and plasma metabolite determination. Clinical parameter comparisons indicated that PCOS patients had higher concentrations of total testosterone, androstenedione, dehydroepiandrosterone sulfate, luteinizing hormone, and HOMA-IR while lower FKBP5 DNA methylation. Significant differences in bacterial diversity and community were observed between the PCOS and healthy groups but not between the PCOS-HB and PCOS-LB groups. Bacterial species number was negatively correlated with insulin concentrations (both under fasting status and 120 min after glucose load) and HOMA-IR but positively related to FKBP5 DNA methylation. Compared to the healthy group, both PCOS groups had significant changes in bacterial genera, including Prevotella_9, Dorea, Maihella, and Slackia, and plasma metabolites, including estrone sulfate, lysophosphatidyl choline 18:2, and phosphatidylcholine (22:6e/19:1). The correlation network revealed the complicated interaction of the clinical index, bacterial genus, stress indices, and metabolites. Our work links the stress responses and gut microbiota characteristics of PCOS disease, which might afford perspectives to understand the progression of PCOS.

Comparison of the efficacy of different androgens measured by LC-MS/MS in representing hyperandrogenemia and an evaluation of adrenal-origin androgens with a dexamethasone suppression test in patients with PCOS.

BACKGROUND: The aims of this study were to compare the efficacy of different androgens measured by liquid chromatography-mass spectrometry (LC-MS/MS) in representing hyperandrogenemia and to evaluate adrenal-origin androgens with a dexamethasone suppression test in patients with polycystic ovary syndrome (PCOS). METHODS: One hundred and two patients with PCOS and 41 healthy volunteers were recruited and total serum testosterone (TT), androstenedione (AD), dehydroepiandrosterone (DHEA) and dehydroepiandrosterone sulfate (DHEA-S) were measured by LC-MS/MS. ROC analysis was performed to compare the efficacy of different androgens in representing hyperandrogenemia. Dexamethasone suppression test was performed in 51 patients with PCOS and above indicators were measured after dexamethasone administration. The prediction efficacy of DHEA and DHEA-S at baseline in the dexamethasone suppression test was evaluated with ROC analysis. RESULTS: The AUCs of TT, AD, free androgen index (FAI) and DHEA-S in ROC analysis for representing hyperandrogenemia were 0.816, 0.842, 0.937 and 0.678, respectively. The optimal cutoff value of TT was 0.337 ng/ml, with a sensitivity of 72.0% and specificity of 82.93%. The optimal cutoff value for AD was 1.309 ng/ml, with a sensitivity of 81.0% and specificity of 73.17%. The optimal cutoff value of the FAI was 2.50, with a sensitivity of 87.0% and specificity of 92.68%. Alternatively, AD or FAI more than the optimal cutoff values as evidence of hyperandrogenemia had the highest sensitivity of 91.18%. The levels of cortisol, DHEA and DHEA-S were all suppressed to narrow ranges after dexamethasone administration. Nine and 8 of 51 patients with PCOS had significant decreases in TT and AD, respectively. DHEA can be used as a indicator for predicting significant decrease of TT in dexamethasone suppression test with cutoff value of 13.28 ng/ml. A total of 27.5% (14/51) of patients had DHEA-S excess, but only 1 of 9 patients who had a significant decrease in TT had elevated level of DHEA-S at baseline. CONCLUSIONS: AD measured by LC-MS/MS can represent hyperandrogenemia in PCOS patients and, combined with TT or FAI, can improve the screening efficiency of hyperandrogenemia. Seventeen percent of PCOS patients had adrenal-origin androgen dominance, with TT significantly decreasing after 2 days of dexamethasone administration. Adrenal-origin androgen dominance was not parallel with DHEA-S excess in patients with PCOS.

The amputation and survival of patients with diabetic foot based on establishment of prediction model.

OBJECTIVE: The objective of this paper is to study the establishment of predictive models and the amputation and survival of patients with diabetic foot. METHODS: A total of 200 inpatients with diabetic foot were selected as the research subject in this study. The amputation and survival status of diabetic foot patients were followed up by telephone. The relevant indicators were screened by cluster analysis. The predictive model was established respectively based on proportional hazard regression analysis, back propagation neural network (BPNN) and BPNN based on genetic algorithm optimization, and the reliability of the three prediction models (PM) was evaluated and compared. RESULTS: The risk factors for amputation were severe ulcer disease, glycosylated hemoglobin and low-density lipoprotein cholesterol. The risk factors for death were cerebrovascular disease, severe ulcer disease and peripheral arterial disease. In case that the outcome was amputation, the PM of BPNN and the PM of BPNN based on genetic algorithm optimization have obviously higher AUC (area under the receiver operating characteristic curve) than the PM of proportional hazard regression analysis, and the difference was statistically significant (P < 0.05). Among the three PMs, the PM based on BPNN had the highest AUC, sensitivity and specificity (SAS). In case that the outcome was death, the PM of BPNN and the PM of BPNN based on genetic algorithm optimization had almost the same AUC, and were obviously higher than the PM based on proportional hazard regression analysis. The difference was statistically significant (P < 0.05). The PM based on BPNN and the BPNN based on genetic algorithm optimization had higher SAS than the PM based on COX regression analysis. CONCLUSION: The PM of BPNN and BPNN based on genetic algorithm optimization have better prediction effect than the PM based on proportional hazard regression analysis. It can be used for amputation and survival analysis of diabetic foot patients.

Impact of disease-management programs on metabolic control in patients with type 1 diabetes mellitus: A cohort study in Shantou, China.

The aim of this study is to evaluate the effect of diabetes disease management program (DMP) on glycemic control in type 1 diabetes mellitus (T1DM) patients in Shantou China.A sample of 240 participants recruited from 3C study Shantou subgroup was followed up in DMP for 3 years. The DMP provided self-management education, individualized therapy plan, diabetes complications screening, and laboratory examination periodical according to clinical practice guidelines. Primary outcomes were changes in hemoglobin A1C (HbA1c).Two hundred one of the participants completed the follow-up. There was a significant decrease in the HbA1c levels after DMP implemented. The mean (± SD) pre- and post-intervention HbA1c levels were 10.26% ±â€Š3.30% and 8.57% ±â€Š1.57% respectively with a P value <0.001. General linear mixed model analyse demonstrated that changes in glycemic control were associated with insulin treatment regimen, frequency of Self-Monitoring of Blood Glucose (SMBG), diabetes diet adherence, physical activity, and duration of diabetes.DMP helped to improve glycemic control and should be general implemented in China's T1DM. Individuals with basal-bolus regimen (multiple daily injections or pump therapy), more frequency of SMBG, following a diabetes diet, more physical activity, shorter diabetes duration may derive greater benefits from DMP.

Different effect of handle region peptide on ß-cell function in different sexes of rats neonatally treated with sodium L-glutamate.

BACKGROUND The (pro)renin receptor ((P)RR) was reported to be expressed in various tissues including the pancreas, and handle region peptide (HRP) is believed to block the function of (P)RR. This study aimed to investigate the effect of HRP on the glucose tolerance status and ß-cell function of female rats, neonatally treated with sodium L-glutamate (MSG) and to compare with the previously reported HRP effect on male rats. MATERIAL AND METHODS Female MSG rats aged 8 weeks were divided into MSG control group and HRP treated group and the normal SD rats served as control. The MSG rats were treated with HRP by osmotic minipumps with dose of 1 mg/kg per day for total 28 days. Glucose tolerance status was evaluated at the end of the study. Islets α-cell and ß-cell were marked with insulin antibody and glucagon antibody respectively. The proliferation of islet cells and expression of subunit of NADPH oxidase P22phox were marked by PCNA and P22phox antibody. Picrosirius red staining was performed for evaluating fibrosis of islets. RESULTS HRP improved the glucose status tolerance with decreasing α-cell mass, islets PCNA-positive cells, expression of P22phox and picrosirius red stained areas, and increasing ß-cell mass in female MSG rats. The indexes with obviously interacted effect of sexes and HRP for the MSG rats were the AUC of blood glucose concentration (P<0.01), α-cell mass (P<0.05), proliferation of islet cells (P<0.01) and area of picrosirius red staining (P<0.01). CONCLUSIONS HRP improved the glucose tolerance status in the females although it was previously reported to worsen the glucose tolerance in male MSG rats. Different levels of sex hormones may partly account for the disparate effects observed for HRP in different sexes.

Handle Region Peptide Ameliorating Insulin Resistance but Not ß Cell Functions in Male Rats Neonatally Treated with Sodium L-Glutamate.

Handle region peptide (HRP), which was recognized as a blocker of (pro)renin receptor ((P)RR), may block the function of (P)RR. The aim of this study was to investigate the effect of HRP with a large dose of 1 mg/kg/d on glucose status in the rats treated neonatally with monosodium L-glutamate (MSG). At the age of 8 weeks, the MSG rats were randomly divided into MSG control group, HRP treated group with minipump (MSG-HRP group), losartan treated group (MSG-L group), and HRP and losartan cotreated group (MSG-HRP-L group) and fed with high-fat diet for 4 weeks. Losartan but not HRP increased the levels of insulin releasing and ameliorate glucose status although both losartan and HRP improved insulin sensitivity. On the one hand, both losartan and HRP decreased levels of pancreatic local Ang-II and NADPH oxidase activity as well as its subunits P(22phox). On the other hand, losartan but not HRP decreased α -cell mass and number of PCNA-positive cells located periphery of the islets and decreased picrosirius red stained area in islets. HRP ameliorating insulin resistance but not ß -cell functions leads to hyperglycemia in the end in male MSG rats, and the dual characters of HRP may partly account for the phenomenon.

[Effects of glucagon on plasma ghrelin level in type 2 diabetes mellitus].

OBJECTIVE: To investigate the effect of glucagon on ghrelin secretion in type 2 diabetes mellitus (T2DM) patients. METHODS: Circulating ghrelin and C-peptide were measured during glucagon stimulation test in 38 cases with T2DM and 30 cases in normal controls (NC) at the 1st Affiliated Hospital of Shantou University from May 2006 to December 2007. RESULTS: (1) There was no significant difference in the fasting C-peptide and fasting ghrelin levels of the NC group were (1.3 +/- 0.6) microg/L and (3.0 +/- 1.0) ng/ml respectively, both not significantly different from those of the T2DM group [(1.2 +/- 0.4) microg/L and (2.7 +/- 0.8) microg/L respectively, P > 0.05 and P > 0.05]; six minutes after the injection of glucagon, the C-peptide level of the T2DM group increased to (2.0 +/- 0.8) microg/L (P < 0.01), and that of the NC group increased to (3.0 +/- 0.8) microg/L (P < 0.01), and the C-peptide level 6 min after of the T2DM group was significantly lower than that of the NC group (P < 0.01). The ghrelin level 6 min after the injection of glucagon of the NC group was (2.3 +/- 0.7) microg/L, significantly lower than that before the injection (P < 0.01). But the ghrelin level 6 min after the injection of glucagon of the T2DM group was (2.9 +/- 0.9) microg/L, NOT significantly different from that before the injection (P > 0.05). (2) Fasting ghrelin level was significantly negatively correlated with the waist circumference (r = -0.343, P < 0.05). CONCLUSION: In healthy subjects exogenous glucagon decreases the ghrelin level. Ghrelin may be associated with the beta-cell hypofunction and first-phase insulin secretion defects in T2DM. Insulin, glucagon, and ghrelin secreted influence each other to regulate glucose homeostasis.

[A multicenter survey on the diabetic foot and its neuropathy in China].

OBJECTIVE: To investigate the characteristics of diabetic foot with neuropathy and its related factors. METHODS: 530 out- and in-patients in 14 grade A class 3 comprehensive hospitals in China with foot problems were surveyed. 337 of the 500 patients (63.58%) suffered from neuropathy, 172 (32.45%) with diabetic foot with simple neuropathy and 165 (31.13%) with simple neuropathy combined with peripheral artery disease (PAD). 193 of the 500 patients (36.42%) suffered from peripheral artery disease (PAD). 77.7% of ulcer were caused by physical factors. Questionnaire survey was conducted to collect the demographic data, present and past history, history of the hyperglycemia and lipid disorders, classification and phases of the foot ulcers based on Wagner' system and Texas system, characteristics of neuropathy and other diabetic complications, and relative risk factors. Detailed physical examination was performed, including 10 g nylon filament sensation examination. RESULTS: The duration of diabetic foot of the patients with simple neuropathy was 3 (1, 60) months, significantly shorter than that of the diabetic foot patients with PAD [5 (1, 96) months, P < 0.001]. The Wagner degree of ulcer was related to the duration of diabetes, economic income, foot deformity, nerve reflection, diapason vibration sensation of foot, sensation point of 10 g nylon filament, ankle/brachial index (ABI), foot artery pulse, fasting blood sugar (FBS) and glycated hemoglobin (HbA1c). Stepwise regression analysis revealed that ABI of left posterior tibial artery, vibration detection threshold and economic income were the most significant influencing factors of the degree of ulcer. CONCLUSION: Neuropathy ulcer is common in diabetic foot patients. The prognosis of healing in diabetic foot with neuropathy is prior to that of diabetic foot with PAD. The neuropathy and PAD of foot influence each other and aggravate the condition of diabetic foot. The examinations of diapason vibration sensation of foot, sensation point of 10 g nylon filament, and Achilles tendon reflex are simple and practical, and are worth recommending.