Prevalence and determinants of thyroid dysfunction in adults with type-2 diabetes mellitus in Saudi Arabia: a systematic review and meta-analysis
Bibliographic record
Abstract
Individuals with type 2 diabetes mellitus (T2DM) frequently experience thyroid dysfunction, a condition that can complicate treatment and worsen prognosis. Although this relationship is well known globally, Saudi Arabia lacks comprehensive national estimates despite its notably high diabetes burden in the region. This systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines and aimed to estimate the pooled prevalence of thyroid dysfunction and its associated factors among adults with T2DM in Saudi Arabia. A comprehensive search was conducted across PubMed, Scopus, and Web of Science for studies published between the years 2000 and 2025. Inclusion criteria encompassed original research articles reporting thyroid dysfunction among adult T2DM patients in Saudi Arabia. Data were extracted from eligible studies, and quality was assessed using the Newcastle-Ottawa Scale. A random-effects meta-analysis model was used to estimate pooled prevalence rates, and heterogeneity was evaluated using the I² statistic. A total of six studies involving 2,366 T2DM patients across various Saudi regions were included. The pooled prevalence of thyroid dysfunction among T2DM patients was 21% (95% CI: 13%-34%), with substantial heterogeneity observed (I² = 97.3%). Subclinical hypothyroidism emerged as the most common type, with a pooled prevalence of 8% (95% CI: 3%-21%). Funnel plot analysis suggested minimal publication bias. Most included studies were of moderate quality. Subclinical hypothyroidism was the most prevalent thyroid disorder identified among Saudi adults with T2DM. These findings supported the incorporation of thyroid screening into diabetes care protocols to enhance early detection and optimize metabolic outcomes.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".