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Record W4230593455 · doi:10.1186/s12969-018-0252-y

Proceedings of the 2018 Childhood Arthritis and Rheumatology Research Alliance (CARRA) Scientific Meeting

2018· article· en· W4230593455 on OpenAlexaff

Bibliographic record

VenuePediatric Rheumatology · 2018
Typearticle
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders Research
Canadian institutionsUniversity of British ColumbiaDalhousie UniversityBritish Columbia Children's HospitalUniversity of TorontoSickKids FoundationAlberta Children's HospitalIzaak Walton Killam Health CentreUniversity of ManitobaChildren's Hospital Research Institute of ManitobaUniversity of Calgary
FundersChildhood Arthritis and Rheumatology Research AllianceMoody College of CommunicationNational Institute of Arthritis and Musculoskeletal and Skin DiseasesUniversity of Texas at AustinNancy Taylor Foundation for Chronic DiseasesScleroderma Foundation
KeywordsAllianceMedicineRheumatologyLibrary scienceFamily medicineInternal medicineGeographyArchaeologyComputer science

Abstract

fetched live from OpenAlex

BackgroundAdverse Childhood Experiences (ACEs) such as witnessing violence in the home or neighborhood, parental incarceration, and racial or ethnic discrimination are associated with increased risk of chronic disease and poorer health in children and adults.Emerging data suggest an association between exposure to ACEs and autoimmune diseases in adults, but the relationship between ACEs and childhood-onset rheumatologic diseases has not been examined.Our objective was to investigate the relationship between ACEs and arthritis, the most common manifestation of childhood-onset rheumatologic disease. MethodsWe used data from the 2016 National Survey of Children's Health (NSCH) to describe the distribution of ACEs among children with current arthritis compared to 1) children with other chronic acquired physical conditions (CAPC)* and 2) all other children.The NSCH is a survey of sampled households with children <18 years conducted by the National Center for Health Statistics at the Centers for Disease Control.Children were determined to have current conditions, including arthritis, if their guardian indicated yes to both "has a doctor or other health care provider ever told you that this child has…" and "does this child currently have the condition?"We performed bivariate and multivariable logistic regression to determine associations between arthritis and cumulative ACE scores, measured as a categorical variable (0 ACEs, 1 ACE, 2-3 ACEs, >=4 ACEs).Logistic regression was also utilized to determine the relationship between cumulative ACE exposure and comorbid depression/ anxiety.Results Among 50,212 children included in the survey, 16,892 had CAPC and 138 had current arthritis.More children with arthritis had any ACE exposure compared to both children with other CAPC (63.4% vs 46.9%, p<0.001) and all other children (40.1%, p<0.001).The prevalence of all individual ACE categories except racial/ethnic discrimination was significantly higher among children with arthritis compared to other CAPC and all other children.A graded relationship was observed between ACE scores and arthritis in logistic regression models for 1) children with CAPC and 2) all children.An overall significant association between ACE score and arthritis persisted after adjusting for confounders in both models (Table 1).No significant interaction was found between ACE and minority status or between ACE and poverty.Among youth with current arthritis, a graded relationship was observed between ACE scores and odds of comorbid depression/anxiety (Table 2).Conclusions A markedly high prevalence of ACEs is reported among youth with arthritis from a large national survey.Higher ACE scores were associated with increased odds of arthritis.Future investigations should examine how adversity may play a role in arthritis development, disease severity, and physical and mental health outcomes.Protective psychosocial factors, such as resilience, may mitigate the impact of ACEs and should be studied further to inform development of effective interventions.*Allergies, asthma, diabetes, and epilepsy.Ethics Approval Approval for exemption was obtained from the Einstein-Montefiore Institutional Review Board.* CAPC = Chronic acquired physical conditions: allergies, asthma, arthritis, diabetes, and epilepsy.** Children with a history of arthritis, but no current arthritis, were censored from this analysis.^Adjusted for age, sex, minority race

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.024
GPT teacher head0.302
Teacher spread0.278 · 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

Citations6
Published2018
Admission routes1
Has abstractyes

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