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2,801 results for “diabetes mellitus”
Awareness, treatment, and control among adults living with arterial hypertension or diabetes mellitus in two rural districts in Lesotho
<p>These are pseudo-anonymised data from the ComBaCaL survey and belong to the manuscript "Awareness, treatment, and control among adults living with arterial hypertension or diabetes mellitus in two rural districts in Lesotho". </p> <p>The data dictionary explains the critical data available in the dataset. Between November 2021 and August 2022 , 6061 participants over 18 years old were visited in their households in two districts of Lesotho. Of these, data from those who were diagnosed with either hypertension or diabetes were further analysed and are documented here.</p>
Fetal exposure to the Ukraine famine of 1932-1933 and adult Type 2 Diabetes Mellitus (Public data and analytical code)
<p><strong>Abstract</strong></p> <p>The short-term impact of famines on death and disease is well documented but it is difficult to estimate their potential long-term impact. We used the setting of the man-made Ukrainian Holodomor famine of 1932-1933 to examine the relationship between prenatal famine and adult Type 2 diabetes mellitus (T2DM). This ecological study included 128,225 T2DM cases diagnosed between 2000-2008 among 10,186,016 male and female Ukrainians born between 1930 and 1938. Individuals who were born in the first half-year of 1934, and hence exposed in early gestation to the mid-1933 peak famine period, had a larger than two-fold likelihood of T2DM (OR 2.21; 95% CI 2.00-2.45) compared to unexposed controls. There was a dose-response relationship between severity of famine exposure and adult T2DM risk comparing individuals born in regions with severe, very severe, and extreme famine to births in the no-famine region.</p> <p> </p> <p><strong>Description of the data and analytical code</strong></p> <p>In exploratory analyses we first examined whether the odds for T2DM were elevated for any month of birth in the period January 1930 to December 1938 in any of the four regions of varying famine intensity. This was achieved by comparing, within each region, the T2DM odds for births in any month and year of birth relative to the T2DM odds for births in the same month combining all other years of birth. The analysis served to identify potential relations of famine with specific months and years of birth, controlling for month of birth effects. We observed increased T2DM odds ratios for births between January and June 1934 in famine-exposed oblasts, with smaller increases for births in 1935 and 1936 in these months. Our findings suggested that in multivariate modelling statistical control for month of birth effects could be accomplished by adjusting for the January-June period. Our findings are presented in the data file '01 Odds Ratio for T2DM Over Time' and show the odds ratios (ORs) for Type 2 Diabetes Mellitus (T2DM) comparing the region-specific T2DM odds for each birth year and month relative to births in the same months but combining all other years of birth. The R syntax file '01 Odds of T2DM Over Time Figure' provides the code necessary to reproduce the figure.</p> <p> </p> <p>For confirmatory analyses we employed a Difference-in-Differences approach to quantify associations between prenatal exposure to famine and T2DM, taking into account year of birth, half-year of birth (Jan-Jun vs Jul-Dec), region, and their interactions. This analysis was conducted initially for each gender separately and then for both genders combined, adjusting for We carried out sensitivity analyses to assess potential changes in T2DM odds arising from the use of pre-famine births vs post-famine births as controls. Our findings are presented in the data file '02 Ukraine Famine 1932-33 Main Data'. Information on the number of T2DM cases by gender, region of residence, and year and month of birth 1930-1938 in Ukraine was collected by the national Ukraine Diabetes Register (Komisarenko Institute of Endocrinology and Metabolism, Kyiv) between 2000-2008. The number of births in the same subgroups, representing the populations at risk for T2DM, was estimated by demographic population reconstruction methods as reported in the publication. We classified the birth counts by year of birth, the semi-annual birth period (January-June vs. July-December), region of birth, and gender. The SPSS syntax file titled '02 Ukraine Famine 1932-33 Main Analysis' provides the code to replicate our main findings as presented in the publication.</p> <p> </p> <p>In a separate analysis we visualized by a meta-regression approach the relation between famine intensity at the oblast level in 1933 and the odds for adult T2DM. The data required for the replication of our findings are included in the file '03 Odds Ratio for T2DM and Famine Intensity at Oblast Level'. The R syntax file titled '03 Ukraine Famine 1932-33 Meta-regression' provides details on conducting the meta-regression using the R package ‘metafor’.</p> <p> </p> <p><strong>Funding</strong></p> <p>Ukraine State complex program Diabetes Mellitus, project number 0106U000844 (M.K.). Holodomor Research and Education Consortium in Canada (L.H.L., O.W.). NIDI-NIAS Fellowship of the Royal Netherlands Academy of Sciences (L.H.L.). National Institute of Aging R01 AG028593 (L.H.L.). National Institute of Aging R01 AG06687 (L.H.L.).</p> <p> </p> <p><strong>Sharing/Access information</strong></p> <p>Data sharing and use are unrestricted with acknowledgement of the original publication and listing of the funding sources as per the above. Researchers are encouraged to contact the Principal Investigators (PIs) for consultations on data structure and use as needed (L.H. Lumey, <a href="mailto:lumey@columbia.edu">lumey@columbia.edu</a>; Oleh Wolowyna, <a href="mailto:olehw@aol.com">olehw@aol.com</a>).</p>
Supplemental data for: Mapping lifestyle factors in blood glucose variability in adolescents with Type 1 Diabetes Mellitus- A pilot study
<div> <p>The dataset was used in the paper “Mapping lifestyle factors in blood glucose variability in adolescents with Type 1 Diabetes Mellitus- A pilot study”. The article is currently under review for publication. DOI to be inserted.</p> </div> <div> <p>A data-in-brief article is to be published to give in-depth information about the data collected to improve reproducibility "Dataset for: Lifestyle Factors and Blood Glucose Variability in Adolescents with Type 1 Diabetes Mellitus". DOI to be inserted. </p> <p> </p> <p>The aim of the study was to assess whether adolescents with T1D in Ireland meet current nutrition and physical activity (PA) guidelines and to explore the impact of nutrition and PA on glycaemic variability (GV). The dataset includes continuous glucose monitoring (CGM) data, dietary intake records, and PA metrics, providing a comprehensive view of the participants' glucose levels and associated lifestyle behaviours.</p> </div>
Cessation of anti-diabetic medications by 'Daily 2-Only Meals-and- Exercise' lifestyle modification and remission of Type-2 Diabetes Mellitus
<p>This is the dataset describing details of the patient's age, gender, weight, waist circumference, HBA1C levels and Fasting Insulin levels from the date of enrolment in the study and subsequent changes at monthly intervals. </p>
ADIPOQ Gene Variants (rs266729, rs2241766, rs1501299) and Acute Myocardial Infarction in Vietnamese Patients with Type 2 Diabetes Mellitus
<p>This data is from a study project about ADIPOQ Gene Variants (rs266729, rs2241766, rs1501299) and Acute Myocardial Infarction in Vietnamese Patients with Type 2 Diabetes Mellitus. The data contains information from 550 patients with their identification removed to ensure confidentiality.</p>
Incidence and predictor of diabetic foot ulcer and its association with change in fasting blood sugar among diabetes mellitus patients at referral hospitals in Northwest Ethiopia, 2021
<p>Abstract</p> <p> </p> <p><strong>Background</strong></p> <p>Diabetes mellitus is one of the global public health problems and fasting blood sugar is an important indicator of diabetes management. Uncontrolled diabetes can lead to diabetic foot ulcers, which is a common and disabling complication. The association between fasting blood glucose level and the incidence of diabetic foot ulcers is rarely considered, and knowing its predictors is good for clinical decision-making. Therefore, the aim of this study was to determine the incidence and predictors of diabetic foot ulcers and its association with changes in fasting blood sugar among diabetes mellitus patients at referral hospitals in Northwest Ethiopia.</p> <p><strong>Methods</strong></p> <p>A multicenter retrospective follow-up study was conducted at a referral hospital in Northwest Ethiopia. A total of 539 newly diagnosed DM patients who had follow-up from 2010 to 2020 were selected using a computer-generated simple random sampling technique. Data was entered using Epi-Data 4.6 and analyzed in R software version 4.1. A Cox proportional hazard with a linear mixed effect model was jointly modeled and 95% Cl was used to select significant variables. AIC and BIC were used for model comparison.</p> <p><strong>Result</strong></p> <p>A total of 539 diabetes patients were followed for a total of 28727.53 person-month observations. Overall, 65 (12.1%) patients developed diabetic foot ulcers with incidence rate of 2.26/1000-person month observation with a 95% CI of [1.77, 2.88]. Being rural (AHR= 2.30, 95%CI: [1.23, 4.29]), being a DM patient with Diabetic Neuropathy (AHR= 2.61, 95%CI: [1.12, 6.06]), and having peripheral arterial disease(PAD) (AHR= 2.96, 95%CI: [1.37, 6.40]) were significant predictors of DFU. The time-dependent lagged value of fasting blood sugar change was significantly associated to the incident of DFU (α = 1.85, AHR=6.35, 95%CI [2.40, 16.79]).</p> <p><strong>Conclusion and recommendation</strong></p> <p>In this study, the incidence of DFU was higher than in previous studies and was influenced by multiple factors like rural residence, having neuropathy, and PAD were significant predictors of the incidence of DFU. In addition, longitudinal changes in fasting blood sugar were associated with an increased risk of DFU. Health professionals and DM patients should give greater attention to the identified risk factors for DFU were recommended.</p>
Structural Homology of Epitope Pair Candidates for Molecular Mimicry Trigger of Type 1 Diabetes Mellitus
<p><strong><em><span>Background:</span></em></strong><span> </span><span>Molecular mimicry, where foreign and self-peptides contain similar epitopes, can induce autoimmune responses. Identifying potential molecular mimics and studying their properties is key to understanding the onset of autoimmune diseases such as type 1 diabetes mellitus (T1DM). Previous work identified pairs of infectious epitopes (E<sub>INF</sub>) and T1DM epitopes (E<sub>T1D</sub>) that demonstrated sequence homology; however, structural homology was not considered. Correlating sequence homology with structural properties is important for streamlining translational investigation of potential molecular mimics. Therefore, the purpose of this work is to compare sequence homology with structural homology by calculating the structures and electrostatic potential surfaces of the epitope pairs identified in previous work from our laboratory. </span></p> <p><strong><span> </span></strong><strong><em><span>Results:</span></em></strong><span> </span><span> For each epitope pair the root mean square deviation (RMSD) was calculated between their predicted structures and their electrostatic potentials were compared. Structures were predicted using the AlphaFold software program. </span><span>Of the 52 epitope pairs considered here only 10 do not exhibit any matching (i.e. less than 3 residues overlap). When considering all residues the RMSD ranges from 0.33 Å to 11.66 Å with an average of 2.68 Å. Twenty-two pairs (42%) have RMSD of less than 1.5 Å and 30 (58%) less than 3 Å. Even some of the matching pairs show some electrostatic similarities that need to be considered. In general there is good agreement between the folding predicted for the isolated </span><span>E<sub>INF</sub></span><span> and E<sub>T1D</sub> epitopes and the folding of the corresponding amino acid sequence in the parent antigen, but in some cases there are deviation that need to be considered, even when the RMDS is small.</span></p> <p><span> </span><strong><em><span>Conclusions:</span></em></strong><span> </span><span>Despite differences, most of the E<sub>INF</sub><span>/</span>E<sub>T1D </sub>pairs selected by sequence homology show similar structural and electrostatic distributions, indicating that the E<sub>INF</sub> may bind to the same protein targets, the major histocompatibility complex molecules, for T1DM, leading to molecular mimicry onset of the disease. These findings suggest that searching for epitope pairs using sequence homology, a much less computationally demanding approach, leads to strong candidates for molecular mimicry that should be considered for further study. Still structure and full docking calculations will be necessary to advance the in-silico molecular mimicry predictions. </span> Here we presnt the following files:</p> <p><span><span>·<span> </span></span></span>Fasta files of all epitopes studied.</p> <p><span><span>·<span> </span></span></span>Alphafold calculated Structures of all epitopes.</p> <p><span><span>·<span> </span></span></span>Antigen structures.</p> <p><span><span>·<span> </span></span></span>Epitope pair structure comparison and their electrostatics.</p> <p> </p> <p> </p>
Multimodal optical measurement for study of lower limb tissue viability in patients with diabetes mellitus
<p>According to the International Diabetes Federation, the challenges of early stage diagnosis and treatment effectiveness monitoring in diabetes is currently one of the highest priorities in modern healthcare. In this experimental study, the potential of combined measurements of skin fluorescence and blood perfusion by the laser Doppler flowmetry method in diagnostics of low limb diabetes complications was evaluated. With the use of Monte Carlo probabilistic modelling, the diagnostic volume and depth of the diagnosis were evaluated. The experimental study involved 76 patients with type 2 diabetes mellitus. These patients were divided into two groups depending on the degree of complications. The control group consisted of 48 healthy volunteers. The local thermal stimulation was selected as a stimulus on the blood microcirculation system. Experimental studies have shown that diabetic patients have elevated values of normalised fluorescence amplitudes, as well as a lower perfusion response to local heating. In the group of people with diabetes with trophic ulcers, these parameters also significantly differ from the control and diabetes only groups. Thus, the intensity of skin fluorescence and level of tissue blood perfusion can act as markers for various degrees of complications from the beginning of diabetes to the formation of trophic ulcers.</p>
Dataset Validation of seven type 2 diabetes mellitus risk scores in a population-based cohort. The CoLaus Study
<p>This dataset is related to "Validation of seven type 2 diabetes mellitus risk scores in a population-based cohort. The CoLaus Study".</p> <p>Vanessa Kraege*, Janko Fabecic*, Pedro Marques Vidal, Gérard Waeber and Marie Méan</p> <p>*Contributed equally; co-first authors</p>
Vitamin B12 deficiency anaemia and gestational diabetes mellitus: a two-sample Mendelian randomization study
Open the record for dataset details and reuse information.
Raman spectra of urine from patients with diabetes mellitus and other pathologies
<p>This dataset contains raw (<strong>unprocessed Raman spectra</strong>) of urine from de-identified human patients. Analysis of this dataset is included in our journal article, "<em><strong>Analysis of urine Raman spectra differences from patients with diabetes mellitus and other pathologies</strong></em>." The dataset includes urine Raman spectra from (1) healthy volunteers, (2) patients with chronic kidney disease and diabetes mellitus, (3) patients with chronic kidney disease and without diabetes mellitus, (4) patients with biopsy-confirmed diabetic nephropathy, (5) patients with biopsy-confirmed immune-mediated nephropathy, (5) patients with biopsy-confirmed membranous nephropathy, (6) patients with biopsy-confirmed renal neoplasm, (7) patients with other glomerular pathologies, and (8) Surine (urinalysis control).</p> <p>Raman spectra were obtained with the following parameters:</p> <ul> <li>Raman spectrometer: Agiltron PeakSeeker PRO-785</li> <li>Mode: Bulk liquid scanning</li> <li>Wavelength: 785 nm</li> <li>Wavenumber range: 200-2000 cm-1</li> <li>Laser power: 30 mW</li> <li>Spectral resolution: 8 cm-1</li> <li>Laser spot size: 0.2 mm</li> <li>Excitation time: 30 s</li> </ul> <p>Raman spectral data and de-identified metadata are present in tab-separated value (tsv) files. Each urine sample is bar-code identified and linked to a disease state (or control) in the metadata tsv file. Ten (10) independent Raman scan replicates exist for each urine sample and are identified by bar-code in the spectral data tsv file. The study IRB approval and a sample blank patient consent form are also included here.</p>
The short-term cost-effectiveness of once-weekly semaglutide versus once-weekly dulaglutide for the treatment of type 2 diabetes mellitus in Colombian adults
<p>Dataset used for the study titled "A relative cost of control analyses of once weekly semaglutide versus dulaglutide for the treatment of type 2 diabetes mellitus in Colombian adults"</p>
Comparison of the Safety and Efficacy of HOE901-U300 With Lantus in Children and Adolescents With Type 1 Diabetes Mellitus
ClinicalTrials.gov study NCT02735044. IPD Sharing: YES. Countries: 24. Publications: 1.
Comparison of SAR341402 to NovoLog in Adult Patients With Type 1 Diabetes Mellitus Also Using Insulin Glargine
ClinicalTrials.gov study NCT03874715. IPD Sharing: YES. Countries: 1. Publications: 2.
Comparison of a New Formulation of Insulin Glargine With Lantus in Patients With Type 2 Diabetes Mellitus on Basal Plus Mealtime Insulin
ClinicalTrials.gov study NCT01499082. IPD Sharing: YES. Countries: 13. Publications: 3.
Assessment of Glycemic Control in Patients With Type 2 Diabetes Mellitus and Late Stage Chronic Kidney Disease
ClinicalTrials.gov study NCT03383627. IPD Sharing: NO. Countries: 1. Publications: 4.
A Study to Evaluate the Safety, Pharmacokinetics (PK) and Pharmacodynamics (PD) for TAK-906 in Participants With Diabetes Mellitus and Gastroparesis (DG) or With Idiopathic Gastroparesis (IG)
ClinicalTrials.gov study NCT03268941. IPD Sharing: YES. Countries: 1. Publications: 1.
Comparison of SAR341402 to NovoLog/NovoRapid in Adult Patients With Diabetes Mellitus Also Using Insulin Glargine
ClinicalTrials.gov study NCT03211858. IPD Sharing: YES. Countries: 7. Publications: 3.
A Study to Assess the Safety and Efficacy of SAR425899 in Patients With Type 2 Diabetes Mellitus
ClinicalTrials.gov study NCT02973321. IPD Sharing: YES. Countries: 8. Publications: 2.
VERIFY:A Study to Compare Combination Regimen With Vildagliptin & Metformin Versus Metformin in Treatment-naïve Patients With Type 2 Diabetes Mellitus
ClinicalTrials.gov study NCT01528254. IPD Sharing: YES. Countries: 34. Publications: 5.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.