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DDAVP responsiveness in children with mild or moderate haemophilia A correlates with age, endogenous FVIII:C level and with haemophilic genotype

2011· article· en· W1489348643 on OpenAlexafffund
M. E. SEARY, David Feldman, Manuel Carção

Bibliographic record

VenueHaemophilia · 2011
Typearticle
Languageen
FieldMedicine
TopicHemophilia Treatment and Research
Canadian institutionsUniversity of TorontoInstitute for Clinical Evaluative SciencesSickKids FoundationHospital for Sick Children
FundersHospital for Sick ChildrenCanadian Hemophilia Society
KeywordsHaemophiliaMedicineHaemophilia AGenotypeInternal medicineCohortPediatricsEndogeny

Abstract

fetched live from OpenAlex

In most individuals with moderate/mild haemophilia A, FVIII:C levels increase following DDAVP administration to a haemostatic range, thus avoiding the need for FVIII concentrates. We sought to determine the relationship between responsiveness to DDAVP in boys (<18 years old) with mild/moderate haemophilia and patient age, haemophilic severity and haemophilic genotype. Our cohort consisted of 13 boys with moderate and 61 boys with mild haemophilia who, between them, had 38 different mutations; 21 had unique mutations not shared by any other clinic patient, whereas 53 shared one of 17 mutations with some other clinic patient (included 26 boys with ≥ 1 haemophilic brother). Patient age and endogenous FVIII:C levels were strong predictors of response to DDAVP. Younger patients responded less well to DDAVP and 10 of the 11 patients, when retested at an older age, showed an improved response to DDAVP. Only 1 patient with moderate haemophilia responded to DDAVP, whereas 80% of patients with mild haemophilia responded (including all patients with an endogenous FVIII:C of >0.15 U mL(-1)). Almost all patients with the same mutation had the same response to DDAVP or only a minor discordance in response. Patient's age, disease severity and genotype all are predictors of response to DDAVP.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
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
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.122
GPT teacher head0.286
Teacher spread0.164 · 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 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

Citations44
Published2011
Admission routes2
Has abstractyes

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