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A study of variations in the reported haemophilia A prevalence around the world

2009· article· en· W2168114765 on OpenAlex
Jeffrey S. Stonebraker, Paula Bolton‐Maggs, J. Michael Soucie, Irwin Walker, Mark Brooker

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHaemophilia · 2009
Typearticle
Languageen
FieldMedicine
TopicHemophilia Treatment and Research
Canadian institutionsCanadian Hemophilia SocietyMcMaster University
Fundersnot available
KeywordsHaemophiliaMedicineHaemophilia APrevalenceEnvironmental healthHealth careDeveloping countryHaemophilia BDemographyPediatricsPopulationEconomic growth

Abstract

fetched live from OpenAlex

The objectives of this paper were to study the reported haemophilia A prevalence (per 100 000 males) on a country-by-country basis and address the following: Does the reported prevalence of haemophilia A vary by national economies? We collected prevalence data for 106 countries from the World Federation of Hemophilia (WFH) annual global surveys and the literature. We found that the reported haemophilia A prevalence varied considerably among countries, even among the wealthiest of countries. The prevalence (per 100 000 males) for high income countries was 12.8 +/- 6.0 (mean +/- SD) whereas it was 6.6 +/- 4.8 for the rest of the world. Within a country, there was a strong trend of increasing prevalence over time--the prevalence for Canada ranged from 10.2 in 1989 to 14.2 in 2008 (R = 0.94 and P < 0.001) and for the United Kingdom it ranged from 9.3 in 1974 to 21.6 in 2006 (R = 0.94 and P < 0.001). Prevalence data reported from the WFH compared well with prevalence data from the literature. Patient registries generally provided the highest quality of prevalence data. The lack of accurate country-specific prevalence data has constrained planning efforts for the treatment and care of people with haemophilia A. With improved information, healthcare agencies can assess budgetary needs to develop better diagnostic and treatment facilities for affected patients and families and work to ensure adequate supplies of factor VIII concentrates for treatment. In addition, this information can help manufacturers plan the production of concentrates and prevent future shortages.

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.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.430

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.075
GPT teacher head0.367
Teacher spread0.292 · 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