Prediction of congenital hypothyroidism based on initial screening thyroid-stimulating-hormone
Bibliographic record
Abstract
BACKGROUND: In thyroid-stimulating-hormone (TSH)-based newborn congenital hypothyroidism (CH) screening programs, the optimal screening-TSH cutoff level is critical to ensuring that true cases of CH are not missed. Screening-TSH results can also be used to predict the likelihood of CH and guide appropriate clinical management. The purpose of this study is to evaluate the predictive value of various screening-TSH levels in predicting a diagnosis of CH in the Ontario Newborn Screening Program (ONSP). METHODS: The initial screening and follow-up data of 444,744 full term infants born in Ontario, Canada from April 1, 2006 to March 31, 2010 were analyzed. Confirmed CH cases were based on local endocrinologists' report and initiation of thyroxine treatment. RESULTS: There were a total of 541 positive screening tests (~1/822 live births) of which 296 were true positives (~1:1,500 live births). Subjects were further subdivided based on screening-TSH and positive predictive values (PPV) were calculated. Twenty four percent in the 17-19.9 mIU/L range were true positives. In the 17-30 mIU/L range, 29 % were true positives with a significantly higher PPV for those sampled after (43 %) rather than before (25 %) 28 h of age (p < 0.02). Seventy three percent of neonates with an initial screening-TSH of ≥ 30 mIU/L and 97 % of those with ≥ 40 mIU/L were later confirmed to have CH. CONCLUSIONS: Infants with modestly elevated screening positive TSH levels between 17 and 19.9 mIU/L have a significant risk (24 %) of having CH. The very high frequency of true positives in term newborns with initial TSH values ≥ 30mIU/L suggests that this group should be referred directly to a pediatric endocrinologist in an effort to expedite further assessment and treatment. Screen positives with a modestly elevated TSH values (17-19.9 mIU/L) need to be examined in more detail with extended follow-up data to determine if they have transient or permanent CH.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".