Classification of Adult-onset Diabetes in Five Subgroups in Pakistani Population
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- This is an observational study: the protocol does not assign a study treatment.
- Who it may be relevant to
- Registry conditions: Diabetes Mellitus, Diabetes Mellitus, Adult-Onset, Diabetes Mellitus Type 1 and 2. Basic parameters: from 16 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Center list to be confirmed — check the primary protocol.
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Unsure about the terms? Read our patient guide →
Overview
This study aims to classify adult-onset diabetes patients into distinct data-driven clusters, such as severe insulin-deficient, severe insulin-resistant, mild obesity-related, and mild age-related diabetes, based on clinical and biochemical characteristics. Using a cross-sectional design, data will be collected from individuals attending outpatient diabetes clinics at tertiary care hospitals in Pakistan. The study will analyze the distribution of metabolic and demographic characteristics within each cluster and assess subgroup-specific risks for diabetic complications. Additionally, the relationship between clustering variables and the risk of complications will be evaluated to enhance the understanding of diabetes heterogeneity and its impact on patient outcomes.
Primary outcome measures
- Classify patients into data-driven clusters (e.g., severe insulin-deficient, severe insulin-resistant, mild obesity-related and mild age-related diabetes). [Time frame: At the time of clinic visit during enrollment]
Secondary outcome measures (3)
- Analyze the distribution of metabolic and demographic characteristics within each cluster. [Time frame: At the time of clinic visit during enrollment]
- • Assess subgroup-specific risks for diabetic macrovascular complications such as CVD, Stroke/TIA, and microvascular complications such as nephropathy, retinopathy, peripheral and autonomic neuropathy [Time frame: At the time of clinic visit during enrollment]
- Evaluate the relationship between clustering variables and complications. [Time frame: At the time of clinic visit during enrollment]
Eligibility criteria
Inclusion criteria
- Patients of both genders whose age of disease onset was older than 16 years
- Patients newly diagnosed with or previously diagnosed with T2D
- Able and willing to provide written informed consent and to comply with the study
Exclusion criteria
- Patients with other medical comorbidities (not a complication of diabetes), such as malignancies.
- Pregnancy
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Cohort
Study locations
Center list to be confirmed — check the primary protocol.
Publications
- Levy JC, Matthews DR, Hermans MP. Correct homeostasis model assessment (HOMA) evaluation uses the computer program. Diabetes Care. 1998 Dec;21(12):2191-2. doi: 10.2337/diacare.21.12.2191. No abstract available. PMID 9839117
- Slieker RC, Donnelly LA, Fitipaldi H, Bouland GA, Giordano GN, Akerlund M, Gerl MJ, Ahlqvist E, Ali A, Dragan I, Festa A, Hansen MK, Mansour Aly D, Kim M, Kuznetsov D, Mehl F, Klose C, Simons K, Pavo I, Pullen TJ, Suvitaival T, Wretlind A, Rossing P, Lyssenko V, Legido-Quigley C, Groop L, Thorens B, Franks PW, Ibberson M, Rutter GA, Beulens JWJ, 't Hart LM, Pearson ER. Replication and cross-valida PMID 34110439
- Li PF, Chen WL. Are the Different Diabetes Subgroups Correlated With All-Cause, Cancer-Related, and Cardiovascular-Related Mortality? J Clin Endocrinol Metab. 2020 Dec 1;105(12):dgaa628. doi: 10.1210/clinem/dgaa628. PMID 32893854
- Bonora E, Trombetta M, Dauriz M, Travia D, Cacciatori V, Brangani C, Negri C, Perrone F, Pichiri I, Stoico V, Zoppini G, Rinaldi E, Da Prato G, Boselli ML, Santi L, Moschetta F, Zardini M, Bonadonna RC. Chronic complications in patients with newly diagnosed type 2 diabetes: prevalence and related metabolic and clinical features: the Verona Newly Diagnosed Type 2 Diabetes Study (VNDS) 9. BMJ Open D PMID 32819978
- Ahlqvist E, Storm P, Karajamaki A, Martinell M, Dorkhan M, Carlsson A, Vikman P, Prasad RB, Aly DM, Almgren P, Wessman Y, Shaat N, Spegel P, Mulder H, Lindholm E, Melander O, Hansson O, Malmqvist U, Lernmark A, Lahti K, Forsen T, Tuomi T, Rosengren AH, Groop L. Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. Lancet Diabe PMID 29503172
- Anjana RM, Baskar V, Nair ATN, Jebarani S, Siddiqui MK, Pradeepa R, Unnikrishnan R, Palmer C, Pearson E, Mohan V. Novel subgroups of type 2 diabetes and their association with microvascular outcomes in an Asian Indian population: a data-driven cluster analysis: the INSPIRED study. BMJ Open Diabetes Res Care. 2020 Aug;8(1):e001506. doi: 10.1136/bmjdrc-2020-001506. PMID 32816869
Identifiers
NCT: NCT06706609 · GTZ-DM-008-24