MétaCan
Menu
Back to cohort
Record W2892344137 · doi:10.1111/obr.12746

Obesity in the global haemophilia population: prevalence, implications and expert opinions for weight management

2018· review· en· W2892344137 on OpenAlexaff
John Wilding, N. Zourikian, Matteo Nicola Dario Di Minno, Kate Khair, N. Marquardt, Gary Benson, Margareth C. Ozelo, Cédric Hermans

Bibliographic record

VenueObesity Reviews · 2018
Typereview
Languageen
FieldMedicine
TopicHemophilia Treatment and Research
Canadian institutionsCentre Hospitalier Universitaire Sainte-Justine
FundersNovo Nordisk
KeywordsMedicineHaemophiliaOverweightObesityPopulationUnderweightPhysical therapyHaemophilia AContext (archaeology)EpidemiologyPediatricsEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

Overweight and obesity may carry a significant disease burden for patients with haemophilia (PWH), who experience reduced mobility due to joint inflammation, muscle dysfunction and haemophilic arthropathy. This review aimed to define the prevalence and clinical impact of overweight/obesity in the global population of PWH. A detailed literature search pertaining to overweight/obesity in haemophilia in the last 15 years (2003-2018) was conducted, followed by a meta-analysis of epidemiological data. The estimated pooled prevalence of overweight/obesity in European and North American PWH was 31%. Excess weight in PWH is associated with a decreased range in motion of joints, accelerated loss of joint mobility and increase in chronic pain. Additionally, the cumulative disease burden of obesity and haemophilia may impact the requirement for joint surgery, occurrence of perioperative complications and the prevalence of anxiety and depression that associates with chronic illness. Best practice guidelines for obesity prevention and weight management, based on multidisciplinary expert perspectives, are considered for adult and paediatric PWH. Recommendations in the haemophilia context emphasize the importance of patient education and tailoring engagement in physical activity to avoid the risk of traumatic bleeding.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.936
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
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 head0.127
GPT teacher head0.435
Teacher spread0.308 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations47
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueObesity ReviewsSame topicHemophilia Treatment and ResearchFrench-language works237,207