Current Issue : April-June Volume : 2023 Issue Number : 2 Articles : 5 Articles
Background: The role of the Endocannabinoids (ECs) in insulin resistance, and their association with visceral obesity and metabolic profile have been studied extensively. Since the association between ECs and metabolic factors in Gestational Diabetes Mellitus (GDM) are not clear, we aimed to evaluate the levels of N-Arachidonoylethanolamide (AEA) and 2-Arachidonoylglycerol (2-AG) and their association with C-reactive protein (CRP), glycemic indices, blood pressure, and anthropometric indices in pregnant women with GDM. Methods: The present case–control study was conducted among 96 singleton pregnant women aged 18–40 years, including 48 healthy pregnant women (control group) and 48 women with a positive diagnosis of GDM (case group). Odds Ratios (ORs) and 95% Confidence Intervals (CIs) for GDM were checked according to endocannabinoids and anthropometric indices using Multivariable Logistic Regression. Results: AEA was significantly associated with increased risk of GDM in models 1, 2 and 3 (OR = 1.22, 95% CI: 1.06– 1.41; OR = 1.54, 95% CI: 1.19–1.97; OR = 1.46, 95% CI:1.11–1.91). A positive but no significant association was found for AEA in model 4 (OR = 1.38,95% CI: 0.99–1.92). Similar to AEA, 2-AG was also positively associated with the likelihood of GDM in Models 1, 2, and 3 but the association attenuated to null in model 4 (OR = 1.25; 95% CI: 0.94- 1.65). Conclusions: Our findings showed that levels of ECs were significantly higher in pregnant women with GDM compared to healthy ones. Also, ECs levels were associated with the likelihood of GDM, independent of BMI and weight gain....
Background: Machine learning was a highly effective tool in model construction. We aim to establish a machine learning-based predictive model for predicting the cervical lymph node metastasis (LNM) in papillary thyroid microcarcinoma (PTMC). Methods: We obtained data on PTMC from the SEER database, including 10 demographic and clinicopathological characteristics. Univariate and multivariate logistic regression (LR) analyses were applied to screen the risk factors for cervical LNM in PTMC. Risk factors with P < 0.05 in multivariate LR analysis were used as modeling variables. Five different machine learning (ML) algorithms including extreme gradient boosting (XGBoost), random forest (RF), adaptive boosting (AdaBoost), gaussian naive bayes (GNB) and multi-layer perceptron (MLP) and traditional regression analysis were used to construct the prediction model. Finally, the area under the receiver operating characteristic (AUROC) curve was used to compare the model performance. Results: Through univariate and multivariate LR analysis, we screened out 9 independent risk factors most closely associated with cervical LNM in PTMC, including age, sex, race, marital status, region, histology, tumor size, and extrathyroidal extension (ETE) and multifocality. We used these risk factors to build an ML prediction model, in which the AUROC value of the XGBoost algorithm was higher than the other 4 ML algorithms and was the best ML model. We optimized the XGBoost algorithm through 10-fold cross-validation, and its best performance on the training set (AUROC: 0.809, 95%CI 0.800–0.818) was better than traditional LR analysis (AUROC: 0.780, 95%CI 0.772–0.787). Conclusions: ML algorithms have good predictive performance, especially the XGBoost algorithm. With the continuous development of artificial intelligence, ML algorithms have broad prospects in clinical prognosis prediction....
Introduction: The health related quality of life (HRQoL) has an important role in adults suffering from diabetes. Objective: To assess the health related quality of life in adult with type 2 diabetes mellitus. Materials and methods: A cross-sectional study was conducted to assess diabetic patient’s HRQoL on 119 purposively selected type-2 DM patients (aged ≥ 18 years and duration of diabetes ≥ 1 year). Data were collected by face-to-face interview and by medical record review through a Bangle version of SF-36 semi-structured questionnaire and a checklist. Place and period of study: The study was conducted at outpatient department in Gopalganj 50 bedded diabetic hospital from 1st January, 2018 to 31st December 2018. Results: The mean age of the respondents was 52.34 (SD ± 10.19) years. Age group shows a significant difference associated with all domains of quality of life except role emotion (>0.05), gender shows the significant in social and pain domain (<0.05). Physical functioning and role physical also show the significant associated with education. Duration of diabetes and use of oral hypoglycemic agent shows the significant difference (<0.05) associated with all domains of quality of life except role physical and role emotion (>0.05) respectively co-morbidity shows the significant difference with all domains expect pain (>0.05). Physical functioning, emotional, pain and general health of the quality of life show the significant difference associated with use of insulin (<0.05). Conclusion: The overall QoL of type-2 DM patients was poor and had lower score of health related quality of life....
Thyroglobulin antibody (TgAb) has been used as a surrogate tumor marker of differentiated thyroid carcinoma (DTC) patients. Preoperative TgAb (PreopTgAb) is thought to affect the prevalence, disease severity, and outcome of DTC. The objective of the present study was to retrospectively analyze the prevalence of PreopTgAb in patients diagnosed with DTC and its relation to thyroid cancer characteristics, staging, and disease outcome. A retrospective analysis of 109 DTC patients with reports of PreopTgAb was carried out. Clinicopathological parameters, including patient demographics (age and gender), TNM staging, histopathologic characteristics (type of pathology, vascular invasion, extrathyroid extension, carcinoma variant, multifocality), treatment (surgery, radioactive iodine), and outcome were recorded. The association of PreopTgAb was compared with the study variables and outcome of the disease using the Chi-square test and Mann-Whitney tests. The prevalence of PreopTgAb was 59.6%. Among the 54 PreopTgAb positive patients, 34 patients had an excellent response and 15 patients had an indeterminate response, while biochemically and structurally incomplete response was observed in 3 and 2 patients, respectively. PreopTgAb was not significantly associated with age (p = 0.919), sex (p = 0.650), pathology (p = 0.079), stage at diagnosis (p = 0.513), vascular invasion (p = 0.211), extra thyroid extension (p = 0.734), histologic variant (p = 0.877), multifocality (p = 0.361), and outcome (p = 0.360). Although we did not find a significant association between positive PreopTgAb and clinical characteristics and outcome of DTC, it can still be considered as a surrogate marker of DTC during follow-up....
Background: Research suggests that fibrinogen (Fib) is related to mild cognitive impairment (MCI) and diabetic peripheral neuropathy (DPN) and the risk of MCI in patients with DPN is greatly increased, although no studies have evaluated the predictive value of Fib for the risk of MCI in patients with DPN. Methods: This prospective observational clinical study enrolled 207 type 2 diabetes mellitus (T2DM) patients, who were divided into diabetes with no neuropathy (102 cases) and diabetes with neuropathy (105 cases) groups. Meanwhile, 90 healthy unrelated subjects were recruited as controls. The incidence of MCI in the DPN patients was followed up for 2 years. Divide patients in the DPN group into subgroups according to whether MCI occur, use multivariate logistic regression to analyze independent factors of MCIs in DPN patients within 2 years, and use ROC curve to analyze the predictive value of Fib for MCI in DPN patients. Results: Fib levels were significantly higher in diabetic subjects with neuropathy compared with those without (P < 0.001). In further subgroup analysis of DPN patients who were divided according to the occurrence of MCI, baseline data of the MCI subgroup showed Fib levels were higher than that in the non-MCI group while education levels declined (P < 0.001). The education level and increased Fib levels were independent factors for the occurrence of MCI within 2 years after the onset of DPN (OR = 0.769, 95% CI: 0.605 ~ 0.968, P = 0.037; OR = 2.674, 95% CI: 1.094 ~ 3.168, P = 0.002). The ROC curve indicated that the predictive value of Fib was (AUC = 0.764, 95% CI: 0.671 ~ 0.842, P < 0.001). Conclusions: Fib may function as a predictor for assessing the risk of MCI in DPN patients....
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