Initial evaluation of thyroid dysfunction - Are simultaneous TSH and fT4 tests necessary?
Bibliographic record
Abstract
OBJECTIVE: Guidelines for thyroid function evaluation recommend testing TSH first, then assessing fT4 only if TSH is out of the reference range (two-step), but many clinicians initially request both TSH and fT4 (one-step). Given limitations of previous studies, we aimed to compare the two-step with the one-step approach in an unselected community-dwelling study population, and develop a prediction score based on clinical parameters that could identify at-risk patients for thyroid dysfunction. DESIGN: Cross-sectional analysis of the population-based Busselton Health Study. METHODS: We compared the two-step with the one-step approach, focusing on cases that would be missed by the two-step approach, i.e. those with normal TSH, but out-of-range fT4. We used likelihood ratio tests to identify demographic and clinical parameters associated with thyroid dysfunction and developed a clinical prediction score by using a beta-coefficient based scoring method. RESULTS: Following the two-step approach, 93.0% of all 4471 participants had normal TSH and would not need further testing. The two-step approach would have missed 3.8% of all participants (169 of 4471) with a normal TSH, but a fT4 outside the reference range. In 85% (144 of 169) of these cases, fT4 fell within 2 pmol/l of fT4 reference range limits, consistent with healthy outliers. The clinical prediction score that performed best excluded only 22.5% of participants from TSH testing. CONCLUSION: The two-step approach may avoid measuring fT4 in as many as 93% of individuals with a very small risk of missing thyroid dysfunction. Our findings do not support the simultaneous initial measurement of both TSH and fT4.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".