BMC Endocrine Disorders

Sleep disorders are common and associated with multiple metabolic and psychological derangements. Obstructive sleep apnoea (OSA) is among the most common sleep disorders and an inter-relationship between OSA, insulin resistance, obesity, type 2 diabetes (T2DM) and cardiovascular diseases has been established. Prevalence of sleep disorders in Kenyans, particularly in individuals with T2DM is unknown. We thus aimed to determine prevalence of poor quality of sleep (QOS) and high risk for OSA, among persons with T2DM and determine their associations with socio-demographic and anthropometric variables. Utilising a Cross- Sectional Descriptive design, QOS and risk for OSA were determined in a randomly selected sample of patients with T2DM (cases) and an age and sex matched comparison group. The validated Pittsburgh Sleep Quality Index (PSQI) and Berlin Questionnaire (BQ) were used to measure QOS and risk for OSA respectively. Associations between poor QOS, high risk for OSA, and socio-demographic and anthropometric variables in cases were evaluated. From 245 randomly selected persons with T2DM attending outpatient clinics, aged over 18 years, 22 were excluded due to ineligibility thus 223 were included in the analysis; 53.8% were females, mean age was 56.8 (SD 12.2) years and mean BMI was 28.8 kg/m2 (SD 4.4). Among them, 119 (53%, CI 95% 46.5–60.2) had poor QOS and 99 (44% CI 95% 37.8–50.9) were at high risk for OSA. Among 112 individuals in comparison group, 33 (29.5%, CI 95% 20.9–38.3) had poor QOS and 9 (8%, CI 95% 3.3–13.4) had high risk for OSA. Cases had a significantly higher probability for poor QOS [OR 2.76 (95% CI 1.7–4.4))] and high risk for OSA [OR 9.1 (95% CI 4.4–19.0)]. Higher waist circumference was independently associated with a high risk for OSA in cases. We demonstrate a high burden of sleep disturbances in patients with T2DM. Our findings may have implications for clinicians to screen for sleep disorders when assessing patients with T2DM and warranting further attention by practitioners and researches in this field.

In subjects with hypothyroidism, edema is often observed, and pleural effusion and pericardial fluid could be also observed. The color of such fluid retention is usually yellow. Here we show a very rare case with hypothyroidism who had bloody pleural effusion and bloody pericardial fluid. A 42-year-old male noticed chest pain and the aggravation of exertional dyspnea, and he was transported to our institution by emergency. He had Graves’ disease and underwent total thyroidectomy about 4 years before. After then, he had been treated with 200 μg/day of levothyroxine sodium for the maintenance of thyroid function. However, he self-interrupted such medication about 2 years before. Thyroid function on admission was reduced as follows: free triiodothyronine, 1.60 pg/mL; free thyroxine < 0.40 ng/dL; thyroid-stimulating hormone 25.50 μU/mL. Inflammation markers were increased: white blood cells 25,280 /μL; C-reactive protein 18.66 mg/dL. A large amount of pericardial fluid and pleural effusion were observed in chest and abdominal computer tomography and echocardiography. In addition, we performed pleural effusion and pericardial fluid collection. Pleural effusion in this subject showed bloody color, but not yellow. In cell block specimen of pleural effusion and pericardial fluid, red blood cells, neutrophils and lymphocyte component were observed. In this subject, however, we were unable to find any obvious background disease causing bloody pericardial effusion. Finally, we concluded that bloody pleural effusion and bloody pericardial fluid were brought about in a subject with untreated known hypothyroidism after total thyroidectomy, triggered by pneumonia. In subjects with hypothyroidism, fluid and mucopolysaccharide are stored in interstitial space and protein osmolality is increased, thus leading to edema and fluid retention. It is noted here that pleural effusion and pericardial fluid in this subject showed bloody color and included red blood cells. There are no reports of bloody pericardial fluid with hypothyroidism. Therefore, it is important to keep in mind that a subject with some trigger, such as infection, may have a hematologic fluid retention that is not seen when hypothyroidism is present alone, as observed in this subject.

Rosiglitazone not only improves insulin-sensitivity, but also exerts anti-inflammatory effects. We have now examined in type 2 diabetic patients if these effects are reflected by changes in mRNA expression in peripheral blood mononuclear cells (PBMCs) to see if these cells can be used to study these anti-inflammatory effects at the molecular level in vivo. Eleven obese type 2 diabetic patients received rosiglitazone (2 × 4 mg/d) for 8 weeks. Fasting blood samples were obtained before and after treatment. Ten obese control subjects served as reference group. The expression of NFκB-related genes and PPARγ target genes in PBMCs, plasma TNFα, IL6, MCP1 and hsCRP concentrations were measured. In addition, blood samples were obtained after a hyperinsulinemic-euglycemic clamp. Rosiglitazone reduced plasma MCP1 and hsCRP concentrations in diabetic patients (-9.5 ± 5.3 pg/mL, p = 0.043 and -1.1 ± 0.3 mg/L p = 0.003), respectively). For hsCRP, the concentration became comparable with the non-diabetic reference group. However, of the 84 NFκB-related genes that were measured in PBMCs from type 2 diabetic subjects, only RELA, SLC20A1, INFγ and IL1R1 changed significantly (p < 0.05). In addition, PPARγ and its target genes (CD36 and LPL) did not change. During the clamp, insulin reduced plasma MCP1 concentration in the diabetic and reference groups (-9.1 ± 1.8%, p = 0.001 and -11.1 ± 4.1%, p = 0.023, respectively) and increased IL6 concentration in the reference group only (23.5 ± 9.0%, p = 0.028). In type 2 diabetic patients, the anti-inflammatory effect of rosiglitazone is not reflected by changes in NFκB and PPARγ target genes in PBMCs in vivo. Furthermore, our results do not support that high insulin concentrations contribute to the pro-inflammatory profile in type 2 diabetic patients.

Several studies have assessed the relationship between type 2 diabetes (T2D) and tooth loss; however, results have been inconsistent. Therefore, the present systematic review and meta-analysis of observational studies was designed to examine the association between T2D and tooth loss. This systematic review and meta-analysis was conducted based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Guideline. We searched all the relevant studies in international databases of Scopus, PubMed, ProQuest, Web of Science, Cochrane Library, and Google scholar search engine until February 2022. The heterogeneity of the studies was calculated using the I2 index. Measure of effect and 95% confidence interval (CI) were extracted from each study. The results of the study were analyzed using the random effects model. In the present study, 22 eligible studies were included. Meta-analysis of unadjusted and adjusted results showed that T2D significantly increased the risk of tooth loss, and Odds Ratio (OR) unadjusted was 1.87 (95% CI: 1.62–2.13, p < 0.001), and OR adjusted was 1.20 (95% CI: 1.10–1.30, p < 0.001), respectively. Subgroup analysis based on study design for adjusted OR indicated that in the cohort study (OR: 1.29, 95% CI: 1.07–1.51), in the cross-sectional study (OR: 1.15, 95% CI: 1.06–1.23), and in the case-control study (OR: 5.10, 95% CI: 1.01–9.18) there was a significant association between T2D and tooth loss. Other subgroups analyses showed consistent results and no publication bias existed. The findings suggest that T2D is associated with increased risk of tooth loss. This conclusion may provide useful evidence for correlated clinical researches.

The transition from paediatric to adult care for young adults with type 1 diabetes poses unique challenges. Virtual diabetes clinics using smartphone applications offer a promising approach to support self-management and enhance communication with healthcare providers. The primary objective of this study was to evaluate the effects of a virtual diabetes clinic on glycaemic control, treatment satisfaction, and quality of life among young adults diagnosed with type 1. 79 participants with type 1 diabetes aged 18–25 years were included in a prospective, single-centre, randomised, wait-list controlled trial. Participants were randomly assigned to either the intervention group or the wait-list control group. The intervention group received instant access to a virtual care platform called Vista Dialog, which facilitated real-time communication between patients and healthcare providers. Glycosylated haemoglobin (HbA1c) levels, time in range (TIR), time below range (TBR), diabetes treatment satisfaction, and quality of life were assessed at baseline and after 6 months. Baseline characteristics were similar between the intervention and control groups, except for education level, where there was a skewed distribution between the groups (the intervention group had a lower education level). At the 6-month follow-up, there were no significant differences in HbA1c levels, TIR, TBR, or diabetes treatment satisfaction between the two groups. However, the intervention group demonstrated a significant decrease in the burden on physical health compared with the control group, indicating an improved quality of life. The implementation of a virtual diabetes clinic using the Vista Dialog platform did not result in significant improvements in glycaemic control or treatment satisfaction compared with usual care. However, it did show potential benefits in terms of reducing the burden on physical health and improving quality of life in young adults with type 1 diabetes. Further research is needed to explore the long-term effects and optimal use of virtual clinics in diabetes management. ISRCTN number: 73,435,627 (registration date: 23/10/2019): https://doi.org/10.1186/ISRCTN73435627 . The performance and results of this trial adhere to the guidelines outlined in the CONSORT 2010 (Consolidated Standards of Reporting Trials) recommendations.

Several studies on various bariatric surgeries involving patients with type 2 diabetes mellitus (T2DM) showed an overall rate of remission of hyperglycemia. However, there is little known about predictive factors on remission after different types of surgeries. The aim of this study was to identify the T2DM remission rate and to determine the effects of preoperative factors characteristics of remission of type 2 diabetes in Iran. We conducted a retrospective analysis of 1351 patients with T2DM operated by three different types of surgeries (Roux-en-Y gastric bypass (RYGB), sleeve gastrectomy (SG), and One Anastomosis Gastric Bypass (OAGB)). Diabetes remission was defined according to the American Diabetes Association (ADA) criteria. Binary logistic regression analyses were employed. A total of 1351 patients, 675 patients (50.0%) undergoing OAGB, 475 (35.2%) RYGB, and 201 (14.9%) SG. 80.6%, 84.2% of OAGB, 81.7%, 82.6% of RYGB, and 77.1%, 81.5% of SG participants were in T2DM remission after 1 and 3 years, respectively. 1- and 3-year remission were associated with preoperative age, duration of T2DM, FBS and HbA1c, BMI, insulin therapy, and a family history of obesity (p < 0.05). The remission of T2DM after RYGB, SG, and OAGB surgery is dependent on various preoperative factors. Patients with younger age, shorter duration of T2DM, lower preoperative HbA1c and FBS, higher BMI, who were not on insulin therapy, and not having a family history of obesity were the best candidates to achieve a prolonged diabetes remission.

Adolescents with polycystic ovary syndrome (PCOS) are at increased risk of impaired glucose tolerance (IGT) and type 2 diabetes mellitus. The aim of this study is to evaluate dysglycemia and biochemical differences based on BMI status and assess the prognostic ability of elevated hemoglobin A1c (HbA1c) in predicting an abnormal 2 hour oral glucose tolerance test (OGTT). Retrospective cohort of female patients aged 11-18 years who underwent 75-g OGTT and were evaluated for PCOS at an urban tertiary care hospital between January 2002 to December 2017. In 106 adolescents with PCOS who had OGTT results available, IGT was markedly pronounced in the ≥95th percentile BMI group (17 out of 72; 23.6%) compared with <95th percentile BMI group (4 out of 34; 11.7%). One patient with obesity met the criteria for type 2 diabetes. Patients with obesity had significantly higher homeostasis model assessment (HOMA-IR) and lower whole body insulin sensitivity index (WBISI) (p < 0.001) compared to patients without obesity. Free testosterone levels were also higher in patients with obesity (p< 0.03) and were significantly associated with HOMA-IR when controlling for body mass index (BMI). HbA1c did not demonstrate a strong ability to predict abnormal OGTT on receiver operating characteristic (ROC) curve analysis [Area under the curve (AUC) = 0.572, 95% CI: 0.428, 0.939]). In a study to assess glucose abnormalities in adolescents with PCOS, IGT was found to be markedly increased in patients with obesity, with abnormal glucose metabolism identified in over one-fifth of the patients. HbA1c alone may be a poor test to assess IGT and we recommend that adolescents diagnosed with PCOS and obesity undergo formal oral glucose tolerance testing.

To assess the factors associated with antihyperglycaemic medication initiation in UK patients with newly diagnosed type 2 diabetes.

In a retrospective cohort study, patients with newly diagnosed type 2 diabetes were identified during the index period of 2003-2005. Eligible patients were ≥ 30 years old at the date of the first observed diabetes diagnosis (referred to as index date) and had at least 2 years of follow-up medical history (N = 9,158). Initiation of antihyperglycaemic medication (i.e., treatment) was assessed in the 2-year period following the index date. Adjusted Cox regression models were used to examine the association between time to medication initiation and patient age and other factors.

Mean (SD) HbA_1c at diagnosis was 8.1% (2.3). Overall, 51% of patients initiated antihyperglycaemic medication within 2 years (65%, 55%, 46% and 40% for patients in the 30- < 45, 45- < 65, 65- < 75, 75+ age groups, respectively). Among the treated patients, median (25^th, 75^th percentile) time to treatment initiation was 63 (8, 257) days. Of the patients with HbA_1c ≥ 7.5% at diagnosis, 87% initiated treatment within 2 years. These patients with a higher HbA_1c also had shorter time to treatment initiation (adjusted hazard ratio (HR) = 2.44 [95% confidence interval (CI): 1.61, 3.70]; p < 0.0001). Increasing age (in years) was negatively associated with time to treatment initiation (HR = 0.98 [95% CI: 0.97, 0.99]; p < 0.001). Factors significantly associated with shorter time to treatment initiation included female gender and use of cardiovascular medications at baseline or initiated during follow up.

In this UK cohort of patients with newly diagnosed type 2 diabetes, only 51% had antihyperglycaemic medication initiated over a 2-year period following diagnosis. Older patients were significantly less likely to have been prescribed antihyperglycaemic medications. Elevated HbA_1c was the strongest factor associated with initiating antihyperglycaemic medication in these patients.

Many studies indicated that mean platelet volume (MPV) and platelet distribution width (PDW) may be valuable in the diagnosis and management of clinical disorders; also, serum butyrylcholinesterase activity (BChE) was suggested to be linked to systemic inflammation and oxidative stress. Limited studies measured these readily available markers in children with diabetic ketoacidosis (DKA). Our objectives were to measure MPV, PDW and BChE in children with DKA; and to assess if any of these markers reflects the severity of DKA. Our study included: 30 children with DKA (DKA group), 30 diabetic children (Non-DKA group) and 30 apparently healthy children (control group). MPV, PDW and BChE were measured in all children. Additional blood samples were withdrawn from the DKA group to assess these markers at discharge from hospital. MPV, PDW and BChE were significantly altered in the DKA group than the other two groups; and their levels improved significantly at discharge of the DKA group (p < 0.05). The three markers were found to equally to predict the presence of DKA, but MPV was the most suitable risk marker for DKA diagnosis (OR = 4.251, CI 95% =1.463–12.351, p = 0.003). Regarding their relation with DKA severity, they did not correlate significantly with arterial PH or serum HCO3- (p > 0.05). DKA in children is associated with changes in MPV, PDW and BChE activity, which improve after resolution of the condition. Elevated MPV can be a suitable risk marker for DKA. None of the studied markers correlated with the severity of DKA.

To study the bacteriological characteristics, risk factors, and treatment of multi-drug resistance (MDR) organisms in patients with diabetic foot infection. Patients with diabetic foot ulcer admitted to hospital from June 2018 to December 2019 (n = 180) were selected as clinical subjects. Demographic information, routine blood test, wound culture and sensitivity were collected. Risk factors of MDR bacteria were analyzed. Among 180 patients with diabetic foot ulcer, 146 were positive in bacterial culture, with 84 positive in MDR bacteria. A total of 182 strains were isolated, with 104 strains being multi-drug resistant. Body mass index, glycosylated hemoglobin, fasting blood glucose, triglyceride, course of ulcer, size of ulcer, peripheral neuropathy, peripheral vascular disease, osteomyelitis, peripheral blood leukocyte count, percentage of neutrophils, and previous use of antibiotics were the related factors of infection of MDR bacteria in diabetic foot ulcer patients (P < 0.05). The leukocyte count and neutrophil ratio of MDR-bacilli were lower than those of non MDR-bacilli (P < 0.05). The risk of MDR bacteria in diabetic foot infection is high. It is necessary to evaluate the risk of multidrug-resistant bacteria by characterizing the course of disease, metabolic control, local ulcer and other aspects in order to formulate an effective treatment plan. The decrease of leukocyte count and neutrophil ratio may be related to damage of the host immune response.