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Ethical issues in haemophilia

2006· review· en· W2127044742 on OpenAlexaff
D. DiMichele, Ampaiwan Chuansumrit, Alex John London, Arthur R. Thompson, C. Cooper, Randy Killian, Lainie Friedman Ross, David Lillicrap, Jonathan Kimmelman

Bibliographic record

VenueHaemophilia · 2006
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsMcGill UniversityQueen's University
Fundersnot available
KeywordsHaemophiliaMedicinePsychological interventionPopulationHaemophilia ANursingPediatricsEnvironmental health

Abstract

fetched live from OpenAlex

Ethical issues surrounding both the lack of global access to care as well as the implementation of advancing technologies, continue to challenge the international haemophilia community. Haemophilia is not given the priority it deserves in most developing countries. Given the heavy burdens of sickness and disease and severe resource constraints, it may not be possible to provide effective treatment to all who suffer from the various 'orphan' diseases. Nevertheless, through joint efforts, some package of effective interventions can be deployed for a significant number of those who are afflicted with 'orphan' diseases. With cost-effective utilization of limited resources, a national standard of care is possible and affordable. Gene-based diagnosis carries attendant ethical concerns whether for clinical testing or for research purposes, even as the list of its potential benefits to the haemophilia community grows rapidly. As large-scale genetic sequencing becomes quicker and cheaper, moving from the research to the clinic, we will face decisions about the implementation of prenatal, neonatal and other screening programs. Such debates will require input from not just the health care professionals but from all stakeholders in the haemophilia community. Finally, long-term therapeutic success gene transfer in small and large animal models raises the question of when and in which patient population the novel therapeutic approach should first be studied in humans with haemophilia. Although gene therapy represents a worthy goal, the central question for the haemophilia community should be whether it wishes to volunteer itself as a model for a much broader set of innovations.

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 categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.952
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.001
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 head0.025
GPT teacher head0.394
Teacher spread0.368 · 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.

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

Citations17
Published2006
Admission routes1
Has abstractyes

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