Is the Incidence of Congenital Hypothyroidism Really Increasing? A 20-Year Retrospective Population-Based Study in Québec
Bibliographic record
Abstract
CONTEXT: Congenital hypothyroidism (CH) is reportedly increasing in the United States, possibly reflecting changes in screening methods. In Québec, the same initial TSH cutoff (15 mU/liter) has been used for the last 20 yr, but in 2001, the cutoff was decreased from 15 to 5 mU/liter for the second test, which is requested when TSH is intermediate (15-30 mU/liter) on the first. OBJECTIVES: Our objective was to assess the incidence of CH over the last 20 yr in Québec. DESIGN, SETTING, PATIENTS, AND MAIN OUTCOME MEASURE: This is a population-based retrospective study. Incidences by etiology based on thyroid scintigraphy with technetium were compared between 1990-2000 and 2001-2009. RESULTS: Of 1,660,857 newborns over 20 yr, 620 had CH (incidence 1:2679). Etiology was dysgenesis (n = 389, 1:4270), either ectopy (n = 290) or athyreosis (n = 99), goiter (n = 52, 1:31,940), normal-size gland in situ (n = 115, 1:14,442), and unknown (n = 64, 1:25,950). The new screening algorithm identified 49 additional cases (i.e. 25 normal-size gland in situ, 12 unknown etiology, 10 ectopies, and two goiters). Consequently, the incidence of normal-size gland in situ or of unknown etiology more than doubled (1:22,222 to 1:9,836, P = 0.0015; and 1:43,824 to 1:17,143, P = 0.0018, respectively) but that of dysgenesis and goiter remained stable. Had the 1990-2000 algorithm been applied in 2001-2009, no change in incidence would have been observed in any category. CONCLUSION: Estimating the incidence of CH is influenced by minimal changes in TSH screening cutoffs. Lower cutoffs identify additional cases that have predominantly functional disorders whose impact on intellectual disability, if left untreated, remains to be determined.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".