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Record W2054387927 · doi:10.1002/art.38440

A24: Validation of BASDAI and BASFI in Children with Spondyloarthritis

2014· article· en· W2054387927 on OpenAlexaff
Alisa Rachlis, Michelle Batthish, Bertha Wong, Michelle A. Anderson, Margaret Duvnjak, Jo-Anne Marcuz, Kristi Whitney-Mahoney, Brian M. Feldman, Ronald M. Laxer, Shirley M. L. Tse

Bibliographic record

VenueArthritis & Rheumatology · 2014
Typearticle
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders Research
Canadian institutionsMcMaster Children's HospitalHospital for Sick Children
Fundersnot available
KeywordsBASFIBASDAIPsychologyComputer scienceMedicineArthritis

Abstract

fetched live from OpenAlex

Background/Purpose: Juvenile‐onset Spondyloarthritis (JSpA), referred to as Enthesitis‐Related Arthritis (ERA) subtype under the International League of Associations for Rheumatology (ILAR) classification is characterized by arthritis and enthesitis largely affecting the lower limbs. Axial involvement is uncommon at presentation, but may develop in the second decade of life. Although there are validated instruments assessing spinal disease in adults with Ankylosing Spondylitis (AS) such as the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) and Bath Ankylosing Spondylitis Functional Index (BASFI), there are no validated tools to measure disease activity or functional impairment in this population of children. While we have previously reported excellent intra‐reliability of the BASDAI and BASFI, the aims of the current study were to measure the validity and responsiveness of these two adult scores in JSpA. Methods: Patients diagnosed with ERA (ILAR criteria) followed in the JSpA Clinic at The Hospital for Sick Children (June 2009–June 2010) were enrolled into the study. The BASDAI and BASFI were measured prospectively at baseline and again at 4 to 6 months. At each study visit, joint and entheseal clinical exams were performed. CHAQ and Physical Global of Disease Activity scores were recorded. The data collected at baseline and the follow up visit were used to assess construct validity and were expressed using Pearson's correlation coefficient. Responsiveness (sensitivity to change) was calculated in a subgroup of patients who showed changes in joint and entheseal counts over time by dividing the mean change between the two assessments by the standard deviation of the change scores and was expressed as the standardized response mean. Results: There were 38 patients (87% male) with a mean age at diagnosis of 12.1 ± 2.5 years and average age at enrollment of 14.5 ± 2.5 years. Average disease duration at the time of the study was 5.4 ± 1.8 years. 45% were HLA B27 positive with 18% had a family history of Spondyloarthritis. 71% had a history of clinical SI involvement. The average time between baseline and follow up clinic visits was 4.6 ± 2.3 months. Correlations between both the BASDAI and the BASFI and active joint counts were found to be high (r > 0.6) while correlations with sites of enthesitis were found to be low to moderate (r = 0.2 – 0.5). Responsiveness was greatest for the BASDAI and BASFI for detecting worsening arthritis (1.18 and 1.11, respectively). Correlations between the two instruments and CHAQ and Physical Global of Disease Activity scores were highly correlated at both time points. Conclusion: The current study demonstrates that the BASDAI and the BASFI show good construct validity and responsiveness and may be used in the evaluation of disease activity and functional impairment in children with JSpA. Correlations were higher for both measures in arthritis than in enthesitis, and sensitivity to changes over time was best for detecting worsening arthritis. The results of this study illustrate that these two instruments validated in adults may become an objective addition to developing Paediatric JSpA core sets.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.005
GPT teacher head0.232
Teacher spread0.227 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations8
Published2014
Admission routes1
Has abstractyes

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