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Physical activity participation and bleeding characteristics in young patients with severe haemophilia

2009· article· en· W2057213141 on OpenAlexaff
R. TIKTINSKY, Gili Kenet, Zeevi Dvir, Bareket Falk, M. Heim, U. Martinowitz, Michal Katz‐Leurer

Bibliographic record

VenueHaemophilia · 2009
Typearticle
Languageen
FieldMedicine
TopicSports injuries and prevention
Canadian institutionsBrock University
Fundersnot available
KeywordsMedicineHaemophiliaHaemophilia ABleedMuscle strengthPhysical activityPhysical therapyIntensity (physics)Prospective cohort studyYoung adultPediatricsInternal medicineSurgery

Abstract

fetched live from OpenAlex

Patients with haemophilia are now widely advised to participate in sport activities. However, no extensive data are available about their actual participation. The aim of this study was to describe the type; intensity and duration of leisure time physical activity (PA) among young patients with severe hemophilia and to assess whether there are differences in bleeding profile and muscle strength in related to activity intensity. Forty-four boys (ages 12-25 years) with severe haemophilia were studied. PA was assessed by the Godin and Shephard (G&S) questionnaire. Bleeding profile was determined based on a one month diary filled by each patient. Muscle strength of the lower limbs muscles was assessed using a hand held dynamometer. Only three subjects did not perform any PA. Twenty-five of the participants performed strenuous PA at least once a week. An inverse, moderate association (r(p) =-0.45, P < 0.002) was found between the G&S score and age. There were no significant differences in bleeding frequency or pain but a significant difference in the cause of bleed was found: those who exercised strenuously showed a higher proportion of bleeds due to traumatic reasons (P < 0.01). No differences in muscle strength values were noted in related to activity intensity also no linear association was noted between muscle strength and bleeding profile. Further investigation, including prospective studies, is needed in order to assess the temporal sequencing between training and the occurrence of bleeds and bleeds cause.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.493

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.011
GPT teacher head0.276
Teacher spread0.265 · 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

Citations46
Published2009
Admission routes1
Has abstractyes

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