Dataset Information

HbA1c - A predictor of dyslipidemia in type 2 Diabetes Mellitus.

ABSTRACT: Objective:This study was aimed to determine the predictive value of HbA1c in detecting dyslipidemia in patients with Type-2 Diabetes Mellitus. Methods:A total of 142 consecutive patients of Type-2 diabetes mellitus were recruited in this study after informed consent. The study was conducted for 6 months from January 2019 - June 2019 in Creek General Hospital, Korangi, Creek, Karachi. Demographic data and detailed history was taken. A complete systemic examination was done for any complications or co-morbids present and related investigations were performed including Fasting lipid profile (CHO, TG's, HDL, LDL, CHO/HDL), serum HbA1c, Creatinine and ECG. Data is analyzed on SPSS 16 for mean, frequencies and correlations. Pearsons Chi square test is used for analyses of Correlation. Results:In a total of 142 Type-2 diabetic patients 39(27.5%) were Males and 103(72.5%) were females with a male to female ratio of 1: 2.6. Mean age was 54.9yrs ± 10.7SD. Mean duration of diabetes was 7.37yrs ±5.64 SD years. Mean BMI is 26.8 ± 3.67kg/m2. 27(19.01%) patients had HbA1c ? 7% whereas 115(80.9%) had >7%. 81(57.04%) patients had dyslipidemia. HbA1c exhibited direct correlations with BMI, cholesterol, TG's and LDL and inverse correlation with HDL with significant P value of <.05. TG's were found significantly higher in females when compared with male patients. In addition, Metabolic syndrome also showed a strong correlation with increasing HbA1c levels especially in female gender (P0.001). Conclusion:The results of our study indicates that HbA1c can be used not only as a useful biomarker of long-term glycaemic control but also a good predictor of lipid profile.

SUBMITTER: Kidwai SS

PROVIDER: S-EPMC7501047 | biostudies-literature | 2020 Sep-Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

HbA1c - A predictor of dyslipidemia in type 2 Diabetes Mellitus.

Kidwai Saera Suhail SS Nageen Ayesha A Bashir Farhat F Ara Jamal J

Pakistan journal of medical sciences 20200901 6

<h4>Objective</h4>This study was aimed to determine the predictive value of HbA1c in detecting dyslipidemia in patients with Type-2 Diabetes Mellitus.<h4>Methods</h4>A total of 142 consecutive patients of Type-2 diabetes mellitus were recruited in this study after informed consent. The study was conducted for 6 months from January 2019 - June 2019 in Creek General Hospital, Korangi, Creek, Karachi. Demographic data and detailed history was taken. A complete systemic examination was done for any ...[more]

PMID: 32968405

Similar Datasets

Project description:Type 2 diabetes mellitus (T2DM), dyslipidemia and periodontitis are frequently associated pathologies; however, there are no studies showing the peripheral blood transcript profile of these combined diseases. Here we identified the differentially expressed genes (DEGs) of circulating lymphocytes and monocytes to reveal potential biomarkers that may be used as molecular targets for future diagnosis of each combination of these pathologies (compared to healthy patients) and give insights into the underlying molecular mechanisms of these diseases. Study participants (n?=?150) were divided into groups: (H) systemically and periodontal healthy (control group); (P) with periodontitis, but systemically healthy; (DL-P) with dyslipidemia and periodontitis; (T2DMwell-DL-P) well-controlled type 2 diabetes mellitus with dyslipidemia and periodontitis; and (T2DMpoorly-DL-P) poorly-controlled type 2 diabetes mellitus with dyslipidemia and periodontitis. We preprocessed the microarray data using the Robust Multichip Average (RMA) strategy, followed by the RankProd method to identify candidates for DEGs. Furthermore, we performed functional enrichment analysis using Ingenuity Pathway Analysis and Gene Set Enrichment Analysis. DEGs were submitted to pairwise comparisons, and selected DEGs were validated by quantitative polymerase chain reaction. Validated DEGs verified from T2DMpoorly-DL-P versus H were: TGFB1I1, VNN1, HLADRB4 and CXCL8; T2DMwell-DL-P versus H: FN1, BPTF and PDE3B; DL-P versus H: DAB2, CD47 and HLADRB4; P versus H: IGHDL-P, ITGB2 and HLADRB4. In conclusion, we identified that circulating lymphocytes and monocytes of individuals simultaneously affected by T2DM, dyslipidemia and periodontitis, showed an altered molecular profile mainly associated to inflammatory response, immune cell trafficking, and infectious disease pathways. Altogether, these results shed light on novel potential targets for future diagnosis, monitoring or development of targeted therapies for patients sharing these conditions.

Project description:Background Metabolic dyslipidemia (high triglyceride) and low high-density lipoprotein cholesterol (HDL-C) is highly prevalent in type 2 diabetes mellitus (T2DM). The extent to which diabetes mellitus-related abnormalities in the triglyceride-HDL-C profile associates with cardiovascular disease (CVD) risk is incompletely understood. We evaluated the associations of triglyceride and HDL-C status with CVD outcomes in individuals with T2DM. Methods and Results We analyzed data from 4199 overweight/obese adults with T2DM free of CVD with available data on triglyceride and HDL-C at baseline (2001-2004) in the Look AHEAD (Action for Health in Diabetes) study. We used Cox proportional models to estimate hazard ratios (HRs) and 95% CIs of: (1) composite CVD outcome (myocardial infarction, stroke, hospitalization for angina, and/or death from cardiovascular causes); (2) coronary artery disease events; and (3) cerebrovascular accidents (stroke). Of the 4199 participants, 62% (n=2600) were women, with a mean age of 58 years (SD, 7), and 40% (n=1659) had metabolic dyslipidemia at baseline. Over a median follow-up of 9.5 years (interquartile range, 8.7-10.3), 500 participants experienced the composite CVD outcome, 396 experienced coronary artery disease events, and 100 experienced stroke. Low HDL-C was associated with higher hazards of the composite CVD outcome (HR, 1.36; 95% CI, 1.12-1.64 [P=0.002]) and coronary artery disease events (HR, 1.46; 95% CI, 1.18-1.81 [P=0.001]) but not stroke (HR, 1.38; 95% CI, 0.90-2.11 [P=0.140]). Compared with patients with normal triglyceride and normal HDL, participants with metabolic dyslipidemia had higher risks of the composite CVD outcome (HR, 1.30; 95% CI, 1.03-1.63 [P=0.025]) and coronary artery disease events (HR, 1.48; 95% CI, 1.14-1.93 [P=0.003]) but not stroke (HR, 1.23; 95% CI, 0.74-2.05 [P=0.420]). Conclusions In a large sample of overweight/obese individuals with T2DM, metabolic dyslipidemia was associated with higher risks of CVD outcomes. Our findings highlight the necessity to account for metabolic dyslipidemia in CVD risk stratification among patients with T2DM. Registration URL: https://www.lookaheadtrial.org; Unique identifier: NCT00017953.

Dataset Information

HbA1c - A predictor of dyslipidemia in type 2 Diabetes Mellitus.

Publications

HbA1c - A predictor of dyslipidemia in type 2 Diabetes Mellitus.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure