Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
2,801
datasets available to search
ShareScore release 0.7.1
Dataset results
2,801 results for “diabetes mellitus”
Single-cell transcriptomics reveals a role for pancreatic duct cells as potential mediators of inflammation in diabetes mellitus
GEO Series GSE263365. Homo sapiens. 9 samples. Type: Expression profiling by high throughput sequencing.
Primary documentation on the scientific study of indicators of continuous monitoring and flash monitoring of glycemia in children and adolescents with type 1 diabetes mellitus
<p>The main purpose of creating an electronic database was to evaluate the performance of continuous glucose monitoring (CGM) and flash monitoring (FMS) in children and adolescents diagnosed with type 1 diabetes mellitus. The database is intended for entering, systematizing, storing and displaying patient data (date of birth, age, date of diagnosis of type 1 diabetes mellitus, length of illness, date of first visit to an endocrinologist, with the installation of a CGM or FMS), glycated hemoglobin indicators initially , during the study and ultimately, as well as CGM, FMS data (average glucose level, glycemic variability, percentage of cases above the target range, percentage of cases within the target range, percentage of cases below the target range, number of hypoglycemic episodes and their average duration, frequency of daily scans and frequency of sensor readings).</p><p>The database is the basis for comparative statistical analysis of dynamic monitoring indicators in groups of patients with the presence or absence of diabetic complications (neuropathy, retinopathy and nephropathy). The database presents the results of a prospective, open, controlled, clinical study obtained over a year and a half. The database includes information on 307 patients (adolescent children) aged 3 to 17 years inclusive. During the study, the observed patients were divided into two groups: Group 1 - patients diagnosed with type 1 diabetes mellitus and with diabetic complications, 152 people, Group 2 – patients diagnosed with type 1 diabetes mellitus and with no diabetic complications, 155 people. All registrants of the database were assigned individual codes, which made it possible to exclude personal data (full name) from the database.</p><p>The database is executed in the Microsoft Office Excel program and has the character of a depersonalized summary table, which consists of two blocks-sheets: patients of groups 1 and 2 and is structured according to the following sections: "Patient number"; "Patient code"; "Date of birth"; "Age of the patient"; section "Date of diagnosis of DM1" indicates the date of the official diagnosis of type 1 diabetes mellitus at the first hospitalization of the patient, this information is borrowed from medical information systems; section "Length of service DM1" reflects information about the duration of the patient's illness; the section "Date of the first visit" contains information about the date of the registrant's visit to the endocrinologist with the installation of FMS / CGM devices; the section "Frequency of self-monitoring with a glucometer" contains information about the frequency of measuring blood glucose levels by the patient at home using a glucometer until the establishment of FMS / CGM.</p><p>Sections "HbA1c initially (GMI)", "HbA1c (GMI)", "HbA1c final (GMI)", display the indicators of the level of glycated hemoglobin from the total for the period of the beginning of the study, at the intermediate stages of the study and at the end of observation.</p><p>The database structure has a number of sections accumulating information obtained with CGM/FMS, in particular: the section "Average glucose level"; the section "% above the target range", reflecting the percentage of the patient's stay with glycemia above the target indicators during the day; the section "% within the target range", reflecting the percentage of the patient's stay within the target glycemia indicators per day; the section "% below the target range", reflecting the percentage of the patient's stay with glycemia below the target indicators during the day; the section "Hypoglycemic phenomena", reflecting the number of cases of hypoglycemia in patients within 2 weeks; the section "Average duration", reflecting the average duration of hypoglycemic phenomena registered in the patient; the section "Sensor data received", indicating the percentage of time the patient was with an active device sensor; the section "Daily scans" show the frequency of scans of the patient's glycemic level (once a day); the section "%CV" displays the variability of the patient's glycemia recorded by the device. The listed sections are repeated in the database in accordance with the number of follow-up visit.</p><p>Also in the database there is a section "Mid. values", which contains indicators of the average values of patient data for all of the above sections, both in the first and in the second group of patients.</p><p>When working with the database, the use of filters (in the "Data" tab) containing the names of indicators allows you to enter information about new registrants in a convenient form or correct existing data, as well as sort and search for one or more specified indicators.</p><p>The electronic database allows you to systematize a large volume of results, distribute data into categories, search for any field or set of fields in the input format, systematize the selected array, makes it possible to directly use this data for statistical analysis, as well as to view and print information on specified conditions with the location of fields in a convenient sequence.</p>
Primary documentation on the scientific study of glycemic variability indicators in children and adolescents with diabetes mellitus type 1 diabetes
<p>The main purpose of creating an electronic database was to assess indicators of glycemic variability in adolescents and children diagnosed with diabetes mellitus type 1. The database presents the results of prospective, open, controlled, clinical study obtained over a period of one and a half years. Base data includes information on 307 patients (children and adolescents) aged 3 to 17 years inclusive. The observed patients were divided into two groups: Group 1 - patients diagnosed with type 1 diabetes mellitus and with diabetic complications, 152 people, Group 2 – patients diagnosed with type 1 diabetes mellitus and without diabetic complications, 155 people. All database registrants were assigned individual codes, which made it possible to exclude personal data (full name) from the database.</p><p>During the study, an analysis of carbohydrate metabolism was carried out with an assessment HbA1c (glycated hemoglobin), CGMS (continuous glucose monitoring), FMG (flash glucose monitoring) with face-to-face consultations with an endocrinologist and analysis of the data obtained. Obtained monitoring results were processed using a specialized variability calculator glycemia (EasyGV®, ver. 9), the following indicators and indices were calculated variability: average glycemic level (Mean), standard deviation (SD); index prolonged increase in glycemia (CONGA); glycemic lability index (LI); index risk of hypoglycemia (LBGI); hyperglycemia risk index (HBGI), average value overall risk (ADRR), average amplitude of glycemic fluctuations (MAGE); grade inter-day GV (MODD), rate of change in glycemia (MAG), J-index - indicator quality of glycemic control. The database is intended for entering, organizing, storing and displaying all of the above data.</p>
QUALITATIVE STUDY OF THE FLOUNDER MUSCLE AFTER AMPUTATION IN PATIENTS WITH CRITICAL LOWER LIMB ISCHEMIA ON THE BACKGROUND OF DIABETES MELLITUS
Open the record for dataset details and reuse information.
fritzvascones: Analysis code | All-cause mortality attributable to type 2 diabetes mellitus in Peru: a comparative risk assessment analysis
Open the record for dataset details and reuse information.
Effectiveness of Intermittent Vacuum Therapy Combined with Aerobic Exercise in Individuals with Diabetes Mellitus
ClinicalTrials.gov study NCT06292624. IPD Sharing: NO. Countries: 1. Publications: 0.
A Study Of Rosiglitazone Plus Insulin To Treat Type 2 Diabetes Mellitus Patients
ClinicalTrials.gov study NCT00349427. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Serum 1,25-dihydroxyvitamin D Levels in Type 2 Diabetes Mellitus Patients With Different Levels of Albuminuria
ClinicalTrials.gov study NCT01845870. IPD Sharing: Not stated. Countries: 1. Publications: 0.
A Study to Evaluate the Efficacy and Safety of DBPR108 100 mg in Type 2 Diabetes Mellitus Patients
ClinicalTrials.gov study NCT04161430. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Healing of Apical periodontitis-the Effect of Diabetes Mellitus and Tobacco Smoking
ClinicalTrials.gov study NCT04812171. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Almond Intervention in Type 2 Diabetes Mellitus
ClinicalTrials.gov study NCT02027740. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Safety and Efficacy of S-707106 in Subjects With Type 2 Diabetes Mellitus and Inadequate Glycemic Control With Metformin Therapy
ClinicalTrials.gov study NCT01240759. IPD Sharing: Not stated. Countries: 1. Publications: 0.
A Non-Interventional Pilot Study to Explore the Role of Gut Flora in Diabetes Mellitus
ClinicalTrials.gov study NCT04213651. IPD Sharing: NO. Countries: 1. Publications: 0.
1.2% Rosuvastatin Subgingivally Delivered In Chronic Periodontitis With Type 2 Diabetes Mellitus
ClinicalTrials.gov study NCT02985099. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Efficacy and Safety of Nutraceuticals in Patients With Diabetes Mellitus Type II and Dyslipidemia.
ClinicalTrials.gov study NCT03676309. IPD Sharing: NO. Countries: 1. Publications: 0.
The Clinical Study of the Effect of Highland Barley Diet on Blood Glucose in Patients With Type 2 Diabetes Mellitus
ClinicalTrials.gov study NCT03766308. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Glycemic Control Of Carvedilol Versus Metoprolol In Patients With Type II Diabetes Mellitus And Hypertension
ClinicalTrials.gov study NCT00060918. IPD Sharing: Not stated. Countries: 1. Publications: 0.
The Effectiveness of "CARE Coaching Model" as an Effort to Empower Type 2 Diabetes Mellitus Patients
ClinicalTrials.gov study NCT04289818. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Study to Assess the Efficacy and Safety of SK3530 on Erectile Dysfunction in Patients With Diabetes Mellitus
ClinicalTrials.gov study NCT00705861. IPD Sharing: Not stated. Countries: 1. Publications: 0.
A Study to Evaluate Efficacy and Safety of HM11260C in Adult Obesity Patients Without Diabetes Mellitus
ClinicalTrials.gov study NCT06174779. IPD Sharing: NO. Countries: 1. Publications: 0.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.