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Record W7073892434

Establishing the prevalence and prevalence at birth of hemophilia in males : a meta-analytic approach using national registries

2019· article· en· W7073892434 on OpenAlexaboutno aff

Bibliographic record

VenueWhite Rose Research Online (University of Leeds, The University of Sheffield, University of York) · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLife expectancyCoagulopathyPrevalenceDisadvantageEpidemiology
DOInot available

Abstract

fetched live from OpenAlex

Background: \n \nThe large observed variability in hemophilia prevalence prevents robust estimation of burden of disease. \n \nObjective: \n \nTo estimate the prevalence and prevalence at birth of hemophilia and the associated life expectancy disadvantage. \n \nDesign: \n \nRandom-effects meta-analysis of registry data. \n \nSetting: \n \nAustralia, Canada, France, Italy, New Zealand, and the United Kingdom. \n \nParticipants: \n \nMale patients with hemophilia A or B. \n \nMeasurements: \n \nPrevalence of hemophilia as a proportion of cases to the male population, prevalence of hemophilia at birth as a proportion of cases to live male births by year of birth, life expectancy disadvantage as a 1 − ratio of prevalence to prevalence at birth, and expected number of patients worldwide based on prevalence in high-income countries and prevalence at birth. \n \nResults: \n \nPrevalence (per 100 000 males) is 17.1 cases for all severities of hemophilia A, 6.0 cases for severe hemophilia A, 3.8 cases for all severities of hemophilia B, and 1.1 cases for severe hemophilia B. Prevalence at birth (per 100 000 males) is 24.6 cases for all severities of hemophilia A, 9.5 cases for severe hemophilia A, 5.0 cases for all severities of hemophilia B, and 1.5 cases for severe hemophilia B. The life expectancy disadvantage for high-income countries is 30% for hemophilia A, 37% for severe hemophilia A, 24% for hemophilia B, and 27% for severe hemophilia B. The expected number of patients with hemophilia worldwide is 1 125 000, of whom 418 000 should have severe hemophilia. \n \nLimitation: \n \nDetails were insufficient to adjust for comorbid conditions and ethnicity. \n \nConclusion: \n \nThe prevalence of hemophilia is higher than previously estimated. Patients with hemophilia still have a life expectancy disadvantage. Establishing prevalence at birth is a milestone toward assessing years of life lost, years of life with disability, and burden of disease.

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)0.044
metaresearch head score (Gemma)0.081
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.232

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0440.081
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.031
Bibliometrics0.0070.008
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.150
GPT teacher head0.251
Teacher spread0.102 · 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 designMeta-analysis
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

Citations60
Published2019
Admission routes1
Has abstractyes

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