Use of Tc‐99 m thyroid scans in borderline congenital hypothyroidism
Bibliographic record
Abstract
BACKGROUND: Mild or borderline congenital hypothyroidism [often referred to as mild neonatal hyperthyrotropinemia (MNH)] is characterized by an abnormal newborn screen (NBS), followed by mildly elevated TSH and normal FT4 on confirmatory testing. This condition is increasingly observed, but data regarding optimal management are limited. OBJECTIVE: Examine the use of routine technetium thyroid scanning (TS) in the management of MNH. METHODS: Retrospective study of infants with MNH between 2000 and 2011. We assessed the clinical course of infants with MNH according to TS results; as a comparator, infants with classic congenital hypothyroidism (CH) were analysed in parallel. RESULTS: We identified 69 infants (52% boys) with MNH and 164 (34% boys) with classic CH. TS results were divided into four subgroups: no uptake in 7% of MNH vs 24% of classic CH (P < 0·01), decreased uptake/anatomical abnormalities in 39% vs 46% (p = NS), increased uptake in 35% vs 26% (p = NS) and normal uptake in 19% vs 4% (P < 0·01). In MNH, neither NBS-TSH, confirmatory TSH and FT4, mean LT-4 treatment doses and number of dose escalations, nor post-treatment FT4 and TSH differed among the four subgroups. In contrast, clinical features in infants with classic CH differed among the subgroups. Among MNH infants who reached 3 years of age, trial-off treatment was successful in 6 of 11 (55%) with no apparent difference in success rates among TS subgroups. CONCLUSIONS: The information provided by TS during evaluation of MNH does not predict clinical course; obtaining these scans in infants with MNH may not be an effective use of healthcare resources.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".