Prevalence of Undiagnosed Hypothyroidism in Europe: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Abstract Background: Patients with undiagnosed hypothyroidism are not treated for the disease and are at high risk of developing serious complications, with major impact on public health. There is a need to systematically review the available evidence on this topic. Objective: To identify the prevalence of undiagnosed hypothyroidism in Europe. Methods: A systematic review of the literature (Medline, EMBASE, and Cochrane Central) was performed to identify epidemiological studies on the prevalence of undiagnosed hypothyroidism among European populations published between January 2008 and April 2018. The Newcastle-Ottawa Scale was used to assess the methodological quality of the included studies. Random-effects meta-analyses were performed to pool estimates of proportions (with 95% confidence intervals [CIs]) of undiagnosed (1) subclinical, (2) overt, and (3) total hypothyroidism. Results: The search returned 15,565 citations (4,526 duplicates). Twenty papers were included in the study. Fourteen and 6 studies were of good and moderate methodological quality, respectively. The results of the meta-analyses were as follows for the prevalence of undiagnosed hypothyroidism: subclinical, 4.11% (95% CI 3.05–5.31%, I<sup>2</sup> = 99.32%); overt, 0.65% (95% CI 0.38–0.99%, I<sup>2</sup> = 96.67%); and total, 4.70% (95% CI 2.98–6.79%, I<sup>2</sup> = 99.53%). According to the sensitivity analysis, the prevalence of hypothyroidism tends to be higher in female patients, in those aged ≥65 years, among studies with lower sample sizes, in those with thyroid-stimulating hormone levels <4.5 mIU/L, and in Eastern and Southern Europe. Conclusions: The current evidence suggests that a considerable proportion of the European population has hypothyroidism, particularly subclinical hypothyroidism, which is undiagnosed. This issue deserves further investigation because of possible deleterious consequences for public health.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.012 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".