Are Individuals with Attention-Deficit /Hyperactivity Disorder at Increased Risk for Type 2 Diabetes Mellitus? : - A systematic literature review
Bibliographic record
Abstract
Background: Attention-deficit/hyperactivity disorder (ADHD) is a neuropsychiatric disease that affects school-aged children and adults. The overall worldwide prevalence of ADHD is estimated to be about 2- 7% in children and 2- 5% in adults. Little is known about its associations to various metabolic disorders such as type 2 diabetes mellitus (T2DM). Emerging research suggests a positive association between T2DM and ADHD, but the results are inconclusive. Moreover, the underlying mechanisms behind this possible association are still largely unknown. Aim: To explore whether there is a link between ADHD and T2DM and the potential mechanisms. Methods: We searched PubMed and Cochrane Library up to 20 November 2020 without any restrictions on language or date of publication. We included all case-control studies, cohort studies, epidemiologic studies, observational studies, longitudinal studies, and follow-up studies on ADHD subjects of any age, sex or setting who were diagnosed with T2DM during the study or prior to the study. The author then used the Newcastle-Ottawa Scale to assess the quality of the chosen studies. Results: We identified 28 articles and three of them were considered relevant and were therefore included. The included studies reported a positive association of ADHD and T2DM, the prevalence of T2DM in ADHD diagnosed subjects ranged from 0.8% to 3.9% and remained higher when compared to the prevalence of T2DM in the non-ADHD group (control group) with a prevalence ranging from 0.2 to 1.62%. Multiple mechanisms were discussed in the included studies, including proinflammatory cytokine oversecretion combined with an immunologic dysregulation and reduced blood flow to the parietal and frontal lobes in T2DM patients. Conclusion: Due to the limited number of relevant studies, there is no clear evidence for a causal link between ADHD and T2DM. More researches are needed to elucidate the exact underlying genetic and biochemical mechanisms behind this possible association
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.087 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".