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Record W2139707829 · doi:10.1258/096914107782066202

Assessing the impact of screening and counselling high school children for <i>β</i>-thalassaemia in India

2007· letter· en· W2139707829 on OpenAlexaboutno aff
Roshan Colah, Mariamma Thomas, Pramod Mayekar

Bibliographic record

VenueJournal of Medical Screening · 2007
Typeletter
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGenetic counselingPediatricsFamily medicine

Abstract

fetched live from OpenAlex

b-Thalassaemia is the commonest single gene disorder in India. It has been estimated that around 10,000–12,000 children with b-thalassaemia major are born each year. 1 A programme for education, screening and genetic counselling of high school students was undertaken between 1984 and 1988. In total, 5682 school children (age – 11–18 years) from 75 schools in Mumbai city were screened after obtaining informed consent from their parents. Of the 5682 children, 153 (prevalence 2.7%) were found to be b-thalassaemia heterozygotes. A few carriers of haemoglobin (Hb) S, Hb D, Hb E, db thalassaemia and Hereditary Persistance of Fetal Haemoglobin (o1.0%) were also identified. 2 Screening and counselling family members (parents and other siblings) had been possible in 71 of the 153 children who were carriers of b-thalassaemia. All of them were given report cards as well as a booklet giving information on thalassaemia. After a gap of 20 years, an attempt was made to follow-up these 71 families to evaluate the impact of screening this group. The results are reported here. Letters were first sent asking the families to attend a follow-up clinic, but the response was very poor. Home visits were then made by a medical social worker and a well-designed proforma was used to gather information on the outcome of screening. Specific questions were asked to evaluate whether they remembered having been tested in school and were aware of their carrier status, how many of them had arranged for their partners to be tested before marriage or their spouses tested after marriage and if any thalassaemia major children were born. Forty-seven of the 71 families could be contacted. Eighteen families had moved residence and in six cases the addresses given were incorrect. The students screened were now in the age group of 30–38 years. The response of the individuals screened and/or their parents is summarized in Table 1. Only 12 of the 47 individuals contacted (26%) recollected that they were b-thalassaemia carriers. The others vaguely remembered that some blood test was carried out in school but had lost their reports. None of the 41 individuals who were now married had revealed their carrier status or had their partners tested before marriage. However, 11 individuals had had their spouses tested for haemoglobinopathies after marriage. Thirty-four of these couples had children but only four families had had their children screened. A thalassaemia major child was born in one family in spite of screening. Screening for b-thalassaemia and other haemoglobinopathies is a prerequisite for a community control programme. In India, both retrospective and prospective screening had been carried out in different target groups. 3–5 However, the long-term impact of screening has never been evaluated. This has immense relevance as a lot of time, effort and money goes into such programmes. A similar programme on screening over 25,000 high school students, in Montreal, Canada showed that virtually all the carriers identified in the high

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)0.004
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.018
GPT teacher head0.333
Teacher spread0.315 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations16
Published2007
Admission routes1
Has abstractyes

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