A Comparison between Type-2 Diabetics and Non-Diabetics in Terms of Papillary Bleeding Index (PBI)

OBJECTIVES: The purpose of this study was to compare the Type 2 diabetes mellitus patients and non-diabetics in terms of Papillary bleeding index (PBI) of periodontal disease. METHODOLOGY: This comparative cross-sectional study was conducted during the period of November 2020 to February 2021 in three (3) tertiary care hospitals of Peshawar. The sampling technique was purposive sampling. The sample comprised 105 individuals, 56 participants in Type–2 diabetes group and 49 in non-diabetes group. Male and females, having age between 40-65 years were recruited. Each diabetic and non-diabetic were clinically examined for periodontitis. Age and sex-matched participants suffering from periodontitis without a history of diabetes as well as with good glycemic control (HbA1c) were considered as controls subjects. Glycated hemoglobulin (HbA1c) was carried out for all the participants free of cost by using Human Gmbh-Max-Planck-Ring 21-65205 Wiesbaden-Germany kit. The study was approved by the ethical committee of the Peshawar Medical College. Data was analyzed using software package SPSS version 20. RESULTS: Out of 56 diabetics, 24 subjects brushed once daily, 15 brushed twice daily, 11 brushed occasionally and 6 didn’t brush whereas in 49 non diabetics, 20 subjects brushed once daily, 13 brushed twice daily, 11 brushed occasionally and 5 didn’t brush. The clinical parameter mean (PBI) was recorded in our study. Score was 2.09 (±0.82) in diabetics and 1.02 (±0.47) in non-diabetics. P-value measured by the chi square test was significant. Spearman correlation test was performed to explore the association between the type 2 diabetes and Papillary bleeding index (PBI). CONCLUSION: We concluded that a significant difference exists between the mean PBI scores of Type 2 diabetics and non-diabetics.

Diabetes Treatment Is Associated With Better Cognitive Function: The Age Disparity

Background: Diabetes mellitus (DM) is a recognised risk factor for cognitive dysfunction. The purpose of this study was to explore the relationship between active treatment for DM and cognitive function in middle-aged (< 60 years) and older adults (≥60 years), respectively.Methods: A total of 13,691 participants (58.55 ± 9.64 years, 47.40% of men) from the Chinese Health and Retirement Longitudinal Study (CHARLS) were included. The participants were classified into three groups according to whether or not they have diabetes and to their diabetes treatment status: diabetes-free, treated-diabetes and untreated-diabetes, in which the diabetes-free group was regarded as reference specially. Cognitive function was assessed by two interview-based measurements for mental intactness and episodic memory.Results: Compared with the participants in the diabetes-free group, the older participants in the treated-diabetes group had better performance in terms of mental intactness (β = 0.37, 95% CI = 0.04–0.70). No significant association was observed in the middle-aged participants. In the subgroup analyses, the lower cognitive score was only observed in people without depression, who had never smoked and drunk, and with a normal weight (body mass index: 18.5–23.9 kg/m2).Conclusion: The cognitive function of actively treated diabetic patients was better than that of patients without diabetes, but the improvement was significant only in elderly people. Depression, smoking, drinking, and an abnormal weight may attenuate this effect.

Comparison of sleep and health behaviors among diabetic patients and non-diabetics in Phitsanulok, Thailand: a cross-sectional study

Background: Type 2 diabetes mellitus (T2DM) is a global public health problem. To avoid disease complications, diabetic patients have to control their blood glucose and maintain a healthy lifestyle including a healthy diet, weight control, moderate exercise, and smoking cessation. Methods: This study aimed to survey sleep, eating, and exercise behaviors of diabetic patients in Bang Rakam district, a rural community in Phitsanulok province, Thailand. The data on sleep and other health behaviors were taken from 1,385 T2DM patients and 1,394 non-T2DM controls, who were aged 30 - 85 years and were free from other chronic diseases. The data were collected using a structured questionnaire. Results: Compared to the control group, the diabetes group had a significantly higher body mass index (BMI). However, fewer of them were found to smoke cigarettes and drink alcohol. Most of the participants were ‘morning people’ who slept 7-9 hours per day. It was found that sleep ≥8 hours increased the risk of diabetes among women (OR = 1.27, 95% CI 1.03 - 1.56). The diabetes group reported eating chicken and vegetables more than the control group. They also avoided eating beef and eating more than a cup of rice per meal. However, the T2DM group did fewer physical activities, such as walking, biking, or playing sports, during their leisure time. Conclusions: Compared to the control group, diabetic patients in a rural community of Thailand had healthier sleep, lifestyle, and eating behaviors but not healthier exercise behaviors, especially among obese women. Diabetes prevention programs should emphasize and promote weight control and increasing levels of exercise.

High Fasting Blood Glucose Level With Unknown Prior History of Diabetes Is Associated With High Risk of Severe Adverse COVID-19 Outcome

BackgroundWe aimed to understand how glycaemic levels among COVID-19 patients impact their disease progression and clinical complications.MethodsWe enrolled 2,366 COVID-19 patients from Huoshenshan hospital in Wuhan. We stratified the COVID-19 patients into four subgroups by current fasting blood glucose (FBG) levels and their awareness of prior diabetic status, including patients with FBG<6.1mmol/L with no history of diabetes (group 1), patients with FBG<6.1mmol/L with a history of diabetes diagnosed (group 2), patients with FBG≥6.1mmol/L with no history of diabetes (group 3) and patients with FBG≥6.1mmol/L with a history of diabetes diagnosed (group 4). A multivariate cause-specific Cox proportional hazard model was used to assess the associations between FBG levels or prior diabetic status and clinical adversities in COVID-19 patients.ResultsCOVID-19 patients with higher FBG and unknown diabetes in the past (group 3) are more likely to progress to the severe or critical stage than patients in other groups (severe: 38.46% vs 23.46%-30.70%; critical 7.69% vs 0.61%-3.96%). These patients also have the highest abnormal level of inflammatory parameters, complications, and clinical adversities among all four groups (all p<0.05). On day 21 of hospitalisation, group 3 had a significantly higher risk of ICU admission [14.1% (9.6%-18.6%)] than group 4 [7.0% (3.7%-10.3%)], group 2 [4.0% (0.2%-7.8%)] and group 1 [2.1% (1.4%-2.8%)], (P<0.001). Compared with group 1 who had low FBG, group 3 demonstrated 5 times higher risk of ICU admission events during hospitalisation (HR=5.38, 3.46-8.35, P<0.001), while group 4, where the patients had high FBG and prior diabetes diagnosed, also showed a significantly higher risk (HR=1.99, 1.12-3.52, P=0.019), but to a much lesser extent than in group 3.ConclusionOur study shows that COVID-19 patients with current high FBG levels but unaware of pre-existing diabetes, or possibly new onset diabetes as a result of COVID-19 infection, have a higher risk of more severe adverse outcomes than those aware of prior diagnosis of diabetes and those with low current FBG levels.

The Role of Serum Angiopoietin-Like Protein 4 (ANGPTL-4) and its Gene in Iraq Patients with Type2 Diabetes Mellitus: Case-Control Study

Background Type 2 Diabetes Mellitus is produced by cell failure of pancreatic cells and insulin resistance and is a disorder in which the amount of sugar in the blood is elevated. Angiopoietin-like protein 4 (ANGPTL4) functions as an inhibitor of lipoprotein lipase, a critical enzyme in lipid metabolism. The aim of this study was to explore if the ANGPTL4 gene's E40K variant and ANGPTL4 serum levels are related to the Body mass index, fasting glucose levels, lipid levels, and glycated hemoglobin.Method75 people were enrolled in this case-control study, 25 of whom had type 2 diabetes mellitus while the other 50 were healthy control subjects. Fasting blood glucose, Lipid profile, Glycated hemoglobin were estimated by Cobas 111 analyzer, BMI (weight, height) was calculated, angiopoietin-like protein 4by anenzyme-linked immune sorbent test kit and TaqMan genotyping-based real-time PCR was used to ascertain ANGPTL4 genotypes. The variant was linked to the risk of Type 2 Diabetes Mellitus and parameters used to quantify the variant were identified. Result Patients in the 30-50 age range with type 2 diabetes and those in the same age group who serve as controls. The control group had a lower level of angiopoietin-like protein 4 (ANGPTL4) than the diabetes group. Patients with T2DM had a substantially (p< 0.0001) greater fasting serum Angiopoietin-like protein 4 level than the control group (135.1±6.70) ng/ml and (62.35±6.4) ng/ml, respectively. The diabetes group has significantly higher fasting serum glucose, lipid profile, and glycated hemoglobin compared with non-diabetics. Serum Angiopoietin-like protein 4 was correlated positively with body mass index. (CC,CT,TT) genotypes of the rs2010871 polymorphism There was a significant difference in frequency of the control group (p =0.0477); however, there was no significant difference in its level of (diabetics, newly diagnosed type 2 diabetic before treatment)p-value (0.7066, 0.5555) respectively Conclusion Serum Angiopoietin-like protein 4 levels are negatively correlated to cholesterol, positively correlated to triglyceride, negatively correlated to HDL, positively correlated to HbA1c, negatively correlated to LDL, negatively correlated to VLDL, negatively correlated to FBS, negatively correlated to BMI. The C>T allele at the ANGPTL4 gene's rs2010871polymorphic locus was linked to a decreased prevalence of Type 2 diabetes.

The relationship of platelet-to-lymphocyte ratio with cognitive decline in T2DM

Purpose We aimed to investigate the role of platelet-to-lymphocyte ratio (PLR) in cognitive decline in patients with type 2 diabetes mellitus (T2DM). Methods A total number of 261 T2DM patients were enrolled in this study. The T2DM patients were divided into two groups according to the median of PLR (PLR < 96.5, n = 130; PLR ≥ 96.5, n = 131). Cognitive impairment was defined as Mini-mental State Examination score ≤ 26. Student’s t test and Chi-square test were used to test the difference between the groups, and logistics regression analysis were performed to verify whether high PLR was an independent factor for cognitive impairment. Results T2DM patients with cognitive impairment had significantly higher PLR level when compared with the simple diabetes group (p = 0.003). Incidence of cognitive impairment was higher in the high PLR group, compared to low PLR group (p = 0.040). Multivariate logistic regression analysis suggested that PLR was a risk biomarker of cognitive decline in T2DM patients (odds ratio [OR] = 1.010, 95% CI: 1.001–1.018, p = 0.013). Conclusions We demonstrated that a higher PLR was associated with cognitive decline in T2DM patients. The PLR may help to identify high-risk patients in time and provide clues for further prevention of cognitive dysfunction in T2DM patients.

Mortality, Cardiovascular and Limb Events in Patients With Symptomatic Lower Extremity Artery Disease and Diabetes

The aim of this study was to compare the prognosis of patients according to diabetes status, during a 1-year follow-up after hospital admission for lower extremity artery disease, in the prospective COPART (COhorte de Patients ARTériopathes) registry. Inclusion criteria were intermittent claudication, ischemic rest pain, tissue loss, or acute limb ischemia, with radiological and hemodynamic confirmation. Among 2494 patients, 1235 (49.5%) had diabetes. Incidence rates for major adverse cardiovascular events (MACE) were 18.0/100 person-years (95% confidence interval [CI], 15.4–21.0) for the diabetes group and 11.1/100 person-years (95% CI, 9.2–13.4) for the non-diabetes group. Incidence rates of all-cause mortality were 29.8/100 person-years (95% CI, 26.5–33.4) for the diabetes group and 19.7/100 person-years (95% CI, 17.2–22.7) for the non-diabetes group. Incidence rates of major limb amputation were 24.2/100 person-years (95% CI, 21.1–27.8) for the diabetes group and 11.6/100 person-years (95% CI, 9.6–14.0) for the non-diabetes group. Diabetes was associated with MACE, adjusted hazard ratio 1.60 (95% CI, 1.16–2.22), and all-cause mortality, unadjusted HR 1.49 (95% CI, 1.24–1.78). In the multivariate analysis, diabetes was no longer associated with major amputation, adjusted HR 1.15 (95% CI, .87–1.51). Patients hospitalized for LEAD with diabetes had a higher risk of MACE than those without diabetes.

Humoral immune response to Covid-19 vaccination in diabetes: age-dependent but independent of type of diabetes and glycaemic control-the prospective COVAC-DM cohort study

Aims: Immune response to COVID-19 vaccination and a potential impact of glycaemia on antibody levels in people with diabetes remains unclear. We investigated the seroconversion following first and second COVID-19 vaccination in people with type 1 and type 2 diabetes in relation to glycaemic control prior to vaccination and analysed the response in comparison to individuals without diabetes. Materials and Methods: This prospective, multicenter cohort study analysed people with type 1 and type 2 diabetes, well (HbA1c<7.5% or <58 mmol/mol) or insufficiently (HbA1c≥7.5% or ≥58 mmol/mol) controlled and healthy controls. Roche's Elecsys anti-SARS-CoV-2 S was used to quantify anti-spike protein antibodies 7-14 days after the first and 14-21 days after the second vaccination. Results: 86 healthy controls and 161 participants with diabetes were enrolled, 150 (75 with type 1 diabetes and 75 with type 2 diabetes) were eligible for the analysis. After the first vaccination, only 52.7% in the type 1 diabetes group and 48.0% in the type 2 diabetes group showed antibody levels above the cut-off for positivity. Antibody levels after the second vaccination were similar in people with type1, type 2 diabetes and healthy controls if adjusted for age, sex and multiple testing (p>0.05). Age (r=-0.45, p<0.001) and glomerular filtration rate (r=0.28, p=0.001) were significantly associated with antibody response. Conclusions: Anti-SARS-CoV-2 S antibody levels after the second vaccination were comparable in healthy controls, people with type 1 and type 2 diabetes, irrespective of glycaemic control. Age and renal function correlated significantly with the extent of antibody levels.

Correlations between Salivary Immuno-Biochemical Markers and HbA1c in Type 2 Diabetes Subjects before and after Dental Extraction

Dental extraction can trigger certain sequences of complex processes that involve both hard (alveolar bone) and soft tissue (periodontal ligament, gingiva) remodeling. Type 2 diabetes is a serious risk factor for many oral pathologies, both in terms of progression and severity, but also regarding subsequent rehabilitation possibilities. The aim of this study was to establish whether certain molecules: osteoprotegerin (OPG), kappa B nuclear factor receptor activator ligand (RANKL), hepatocyte growth factor (HGF), tumor necrosis factor-α (TNF-α), interleukin 18 (IL-18), matrix metalloproteinase 9 (MMP-9) and oxidative stress markers—total oxidant status (TOS), total antioxidant capacity (TAC)—evaluated in saliva are modified post-extraction in type 2 diabetes mellitus subjects and whether there is a correlation with HbA1c levels. The aforementioned markers plus HbA1c were investigated in a group of systemically healthy subjects (n = 45) and in a type 2 diabetes mellitus group (n = 41) before and three months after a tooth extraction. Diabetes patients’ recorded increased levels of OPG, RANKL, TNF-α, MMP-9, IL-18 and TOS compared to controls both pre- and post-extraction. In both study groups, the average OPG, HGF and TAC level recorded an upward trend three months post-extraction. TNF-α registered a statistically significant decrease only in the diabetes group after dental extraction, together with a decrement of mean HbA1c levels in the diabetes group. By plotting the ROC (receiver operating characteristic) curve, at baseline RANKL, TNF-α, IL-18, MMP-9, TOS and OPG were good predictors of HbA1c levels. Post-extraction, there was a significant correlation between HbA1c and oxidative status biomarkers, however the linear regression model indicated the influence of all studied salivary markers in HbA1c determinism, in a considerable proportion. In conclusion, our study demonstrated that several oxidative status markers and proinflammatory biomarkers are modified in the saliva of diabetic patients and they correlate to HbA1c levels, thus being potential indicators of the post-extraction healing status in the oral cavity.

Characterization of the Oral Microbiome Among Children With Type 1 Diabetes Compared With Healthy Children

Aim: Current microbiome profiling of type 1 diabetes mellitus (T1D) patients is mostly limited to gut microbiome. We characterized the oral microbiome associated with T1D in children after the onset of the disease and explored its relationship with oral physiological factors and dental status.Methods: This cohort study comprised 37 children aged 5–15 years with T1D and 29 healthy children matched in age and gender. Unstimulated whole saliva was collected from diabetic and non-diabetic children, in the morning after brushing their teeth and a fasting period of at least 1 h before sampling. 16S rRNA gene-based analysis was performed by Powersoil Pro kit by Qiagen and Phusion High-Fidelity PCR Master Mix. Oral physiological and dental parameters studied included decayed, missing, and filled teeth index, salivary flow rate, and salivary pH, glucose, calcium, phosphate, and urea levels.Results: Of the identified 105 different genera and 211 different species, the most abundant genera were Streptococcus, Prevotella, Veillonella, Haemophilus, and Neisseria. Streptococcus was more abundant in T1D children. The diabetes group had 22 taxa at the genus level and 33 taxa at the species level that were not present in the control group and the control group exhibited 6 taxa at the genus level and 9 taxa at the species level that did not exist in the diabetes group. In addition, Catonella, Fusobacterium, and Mogibacterium differed between healthy and T1D subjects. Eight species and eight subspecies were significantly more abundant among healthy children than in T1D children. Porphyromonas and Mogibacterium genera were significantly correlated with salivary parameters. We found similarities between taxa revealed in the present study and those found in gut microbiome in type 1 diabetes mellitus according to gutMDisorder database.Conclusions: Salivary microbiome analysis revealed unique microbial taxa that differed between T1D children and healthy subjects. Several genera found in the saliva of T1D children were associated with gut microbiome in T1D individuals.