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Record W4283466564 · doi:10.1111/hae.14615

Health‐related quality of life among adults with haemophilia in China: A comparison with age‐matched general population

2022· article· en· W4283466564 on OpenAlexaff
Wenhui Zhang, Shitong Xie, Feng Xue, Ling‐Ling Chen, Lei Zhang, Jing Wu, Renchi Yang

Bibliographic record

VenueHaemophilia · 2022
Typearticle
Languageen
FieldMedicine
TopicHemophilia Treatment and Research
Canadian institutionsMcMaster UniversityImpact
FundersNational Natural Science Foundation of China
KeywordsMedicineHaemophiliaQuality of life (healthcare)PopulationDemographyGerontologySF-36ChinaMental healthMultivariate analysisHealth related quality of lifeDiseasePsychiatryEnvironmental healthPediatricsInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Evaluating health-related quality of life (HRQoL) is vital for informing the improvement of the overall health of people with haemophilia (PwH). While there is lacking such data in China and comparisons with the general population. AIM: To evaluate the HRQoL and its associated factors among adults with haemophilia, and compare it with a sample of the general population in China. METHODS: PwH were recruited in this study using telephone-based interviews. Demographic and clinical characteristics were first collected. HRQoL was then evaluated using the self-reported Short Form 6-dimensions version 2 (SF-6Dv2) instrument. An age and gender-matched sample of the general population in China was also included as the comparator group. Linear regression was used to assess the association between the SF-6Dv2 utility value and the demographic and clinical variables of the patients. RESULTS: This study included 206 PwH (mean [SD] age: 41.36 [14.48] years) and 206 respondents from the general population. PwH reported worse levels in physical functioning, role limitation, social functioning, and mental health dimensions on SF-6Dv2 than the general respondents. The mean (SD) utility of patients was .650 (.251), which was significantly lower than the general respondents (.786 [.183], P < .001). Being a student, having a higher monthly income, absence of comorbidities, having no target joints and requiring no treatment are independent predictors of a higher HRQoL for PwH. CONCLUSION: This study provides the first practical evidence of a significantly lower level of HRQoL in PwH than in the general population in China.

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 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 score0.014
Threshold uncertainty score1.000

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 head0.038
GPT teacher head0.329
Teacher spread0.292 · 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

Citations13
Published2022
Admission routes1
Has abstractyes

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