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Record W3141901445 · doi:10.1186/s13023-021-01804-6

Genetic counseling in the context of Bangladesh: current scenario, challenges, and a framework for genetic service implementation

2021· review· en· W3141901445 on OpenAlexafffund
Mohammad Jakir Hosen, Saeed Anwar, Jarin Taslem Mourosi, Sourav Chakraborty, Md. Faruque Miah, Olivier Vanakker

Bibliographic record

VenueOrphanet Journal of Rare Diseases · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversity of Alberta
FundersAlberta Innovates
KeywordsContext (archaeology)Genetic counselingDeveloping countryPublic healthBusinessService (business)Economic growthGenetic testingHealth careMedicineMarketingGeographyNursingEconomicsGeneticsBiology

Abstract

fetched live from OpenAlex

With the advancements in genetics and genomics in the twenty-first century, genetic services have become an integral part of medical practices in high-income and upper-middle-income countries. However, people living in low and lower-middle-income countries (LICs and LIMCs), including Bangladesh, are rather underprivileged in receiving genetic services. Consequently, genetic disorders are emerging as a significant public health concern in these countries. Lack of expertise, high expense, the dearth of epidemiological data, insufficiently updated medical education system, poor infrastructure, and the absence of comprehensive health policies are the main factors causing people living in these countries not having access to genetic services. In this article, the authors took benefit from their professional experience of practicing medical genetics in the area and reviewed existing literature to provide their opinions. Particularly, it reviews the current knowledge of genetic disorders' burden and their causative factors in Bangladesh. It focuses on why providing genetic services is challenging in the context of the country's cultural and religious sentiment. Finally, it proposes a physician-academician collaborative framework within the existing facility that aims to tackle the challenges. Such a framework could also be useful for other LICs and LMICs to address the challenges associated with providing genetic services.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score0.775

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.032
GPT teacher head0.369
Teacher spread0.337 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations20
Published2021
Admission routes2
Has abstractyes

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