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1.
Diabetol Metab Syndr ; 13(1): 92, 2021 Aug 31.
Article in English | MEDLINE | ID: mdl-34465375

ABSTRACT

BACKGROUND: Diabetic foot ulcer (DFU) is a serious chronic complication of diabetes. This study aimed to establish weighted risk models for determining DFU occurrence and severity in diabetic patients. METHODS: This was a multi-center hospital-based cross-sectional study. A total of 1488 diabetic patients with or without an ulcer from three tertiary hospitals were included in the study. Random forest method was used to develop weighted risk models for assessing DFU risk and severity. Receiver operating characteristic curves were used to validate the models and calculate the optimal cut-off values of the important risk factors. RESULTS: We developed potent weighted risk models for evaluating DFU occurrence and severity. The top eight important risk factors for DFU onset were plasma fibrinogen, neutrophil percentage and hemoglobin levels in whole blood, stroke, estimated glomerular filtration rate, age, duration of diabetes, and serum albumin levels. The top 10 important risk factors for DFU severity were serum albumin, neutrophil percentage and hemoglobin levels in whole blood, plasma fibrinogen, hemoglobin A1c, estimated glomerular filtration rate, hypertension, serum uric acid, diabetic retinopathy, and sex. Furthermore, the area under curve values in the models using plasma fibrinogen as a single risk factor for determining DFU risk and severity were 0.86 (sensitivity 0.74, specificity 0.87) and 0.73 (sensitivity 0.76, specificity 0.58), respectively. The optimal cut-off values of plasma fibrinogen for determining DFU risk and severity were 3.88 g/L and 4.74 g/L, respectively. CONCLUSIONS: We have established potent weighted risk models for DFU onset and severity, based on which precise prevention strategies can be formulated. Modification of important risk factors may help reduce the incidence and progression of DFUs in diabetic patients.

2.
Acta Diabetol ; 57(6): 705-713, 2020 Jun.
Article in English | MEDLINE | ID: mdl-32008161

ABSTRACT

AIMS: Type 2 diabetes mellitus (T2DM) is now very prevalent in China. Due to the lower rate of controlled diabetes in China compared to that in developed countries, there is a higher incidence of serious cardiovascular complications, especially acute coronary syndrome (ACS). The aim of this study was to establish a potent risk predictive model in the economically disadvantaged northwest region of China, which could predict the probability of new-onset ACS in patients with T2DM. METHODS: Of 456 patients with T2DM admitted to the First Affiliated Hospital of Xi'an Jiaotong University from January 2018 to January 2019 and included in this study, 270 had no ACS, while 186 had newly diagnosed ACS. Overall, 32 demographic characteristics and serum biomarkers of the study patients were analysed. The least absolute shrinkage and selection operator regression was used to select variables, while the multivariate logistic regression was used to establish the predictive model that was presented using a nomogram. The area under the receiver operating characteristics curve (AUC) was used to evaluate the discriminatory capacity of the model. A calibration plot and Hosmer-Lemeshow test were used for the calibration of the predictive model, while the decision curve analysis (DCA) was used to evaluate its clinical validity. RESULTS: After random sampling, 319 and 137 T2DM patients were included in the training and validation sets, respectively. The predictive model included age, body mass index, diabetes duration, systolic blood pressure (SBP), diastolic blood pressure (DBP), low-density lipoprotein cholesterol, serum uric acid, lipoprotein(a), hypertension history and alcohol drinking status as predictors. The AUC of the predictive model and that of the internal validation set was 0.830 [95% confidence interval (CI) 0.786-0.874] and 0.827 (95% CI 0.756-0.899), respectively. The predictive model showed very good fitting degree, and DCA demonstrated a clinically effective predictive model. CONCLUSIONS: A potent risk predictive model was established, which is of great value for the secondary prevention of diabetes. Weight loss, lowering of SBP and blood uric acid levels and appropriate control for DBP may significantly reduce the risk of new-onset ACS in T2DM patients in Northwest China.


Subject(s)
Acute Coronary Syndrome/diagnosis , Acute Coronary Syndrome/etiology , Diabetes Mellitus, Type 2/complications , Diabetic Angiopathies/diagnosis , Models, Statistical , Acute Coronary Syndrome/blood , Acute Coronary Syndrome/epidemiology , Aged , Biomarkers/blood , Blood Pressure/physiology , Body Mass Index , China/epidemiology , Cholesterol, LDL/blood , Diabetes Mellitus, Type 2/blood , Diabetes Mellitus, Type 2/diagnosis , Diabetes Mellitus, Type 2/epidemiology , Diabetic Angiopathies/blood , Diabetic Angiopathies/epidemiology , Female , Humans , Incidence , Male , Middle Aged , Predictive Value of Tests , Prevalence , Prognosis , Risk Factors , Uric Acid/blood
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