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Record W2520583647 · doi:10.17925/ee.2016.12.02.99

Neonatal Screening for Congenital Hypothyroidism with Focus on Developing an Indian Screening Programme

2016· review· en· W2520583647 on OpenAlexaboutno aff
Jubbin Jacob

Bibliographic record

VenuetouchREVIEWS in Endocrinology · 2016
Typereview
Languageen
FieldMedicine
TopicNeonatal Health and Biochemistry
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineLevothyroxineCongenital hypothyroidismNewborn screeningPediatricsEtiologyIodine deficiencyIntensive care medicineThyroidPsychiatryEndocrinology

Abstract

fetched live from OpenAlex

Neonatal screening for congenital hypothyroidism, along with eradication of iodine deficiency in large parts of the world, has made it possible to prevent the development of permanent neurological impairment due to thyroid hormone deficiency in the developing brain. The first successful screening programme was demonstrated in Canada in 1973 and since then it has been standard of care in most developed societies. In India there is no national programme for neonatal screening, and screening is only done in selected larger hospitals on newborns whose parents fund it. This review summarises the current understanding of the various strategies for newborn screening that could potentially be employed in India with resource constraints. Once a case is detected, the further evaluation and determination of etiology is summarised. Treatment and long term follow-up with levothyroxine replacement is also described in detail as per current understanding.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.117
GPT teacher head0.389
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations3
Published2016
Admission routes1
Has abstractyes

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