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Why should we care about quality of life in persons with haemophilia?

2012· article· en· W1762581249 on OpenAlexafffund
Louis M. Aledort, Monika Bullinger, Sylvia von Mackensen, Joan Wasserman, Nancy L. Young, Denise Globe

Bibliographic record

VenueHaemophilia · 2012
Typearticle
Languageen
FieldMedicine
TopicHemophilia Treatment and Research
Canadian institutionsLaurentian University
FundersCanadian Institutes of Health Research
KeywordsHaemophiliaMedicineQuality of life (healthcare)Perspective (graphical)Clotting factorHaemophilia AClinical trialPhysical therapyHealth careIntensive care medicinePediatricsNursingInternal medicine

Abstract

fetched live from OpenAlex

The very high cost of haemophilia care, including the increase in use of factor prophylaxis in both children and adults requires that funders of clotting factor concentrates require objective measures of health, such as joint status and quality of life (QOL). Many clinical trials, especially those for licensing of new products, are including QOL instruments in their protocols to evaluate the patients' perspective of wellbeing before and during therapy. This article gives a perspective on QOL the importance of QOL measurement in the field of haemophilia and its impact on patient outcome.

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)0.001
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 score0.039
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.106
GPT teacher head0.370
Teacher spread0.264 · 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 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

Citations45
Published2012
Admission routes2
Has abstractyes

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