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Record W7161997495 · doi:10.82308/54302

Patient-physician discordance in systemic lupus erythematosus and its impact on medication adherence and alternative medicine use

2001· dissertation· en· W7161997495 on OpenAlexaboutno aff
Yen, Jim C., 1967-

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
Fundersnot available
KeywordsVisual analogue scaleSystemic lupus erythematosusDiseaseLupus erythematosusRepeated measures designLogistic regressionMedication adherenceAnalysis of variance

Abstract

fetched live from OpenAlex

Introduction. Preliminary studies found that discordance between the patients' and physicians' assessments of disease activity in systemic lupus erythematosus (SLE) exists. We investigated the factors associated with discordance and explored the impact of discordance on medication adherence and complementary/alternative medicine (CAM) use. Methods. Part I investigated the factors associated with discordance, defined as the patient visual analog scale (VAS) minus the physician VAS for global disease activity. Data were extracted from the Montreal General Hospital Lupus Registry. Potential covariates included the Medical Outcomes Studies SF-36, the Systemic Lupus Activity Measure (SLAM), and a lupus damage index. The first visit data were analyzed using multiple regression. Unbalanced repeated measures analysis of variance was used to analyze follow-up data and to investigate the influence of time. Part II used a patient questionnaire to measure adherence and CAM use, which was then linked to discordance data from the Registry. The associations between discordance and non-adherence and CAM use were tested using multivariable logistic regression. Non-linear relationships were tested by generalized additive models (GAM). Results. Clinically important discordance occurred in nearly 30% of the visits. The SF-36 scales for Bodily Pain and Vitality were important variables for predicting discordance. SLAM-Skin and -Musculoskeletal components were also associated with discordance. The mean discordance tended to increase over time. While both the patients' and physicians' VAS scores tended to decrease over time, the decrease was more pronounced in the physicians' VAS scores. Non-adherence and CAM use occurred in 32% and 55% of the subjects, respectively. Patients who scored much lower disease activity than their physicians were more likely to be non-adherent than concordant patients (odds ratio = 2.25, 95% confidence interval: 0.32, 15.96). GAM testing supported this finding. Odds ratios for discordance and use of CAM therapies ranged from 0.89 to 1.48 (all non-significant), and GAM showed a non-linear relationship represented by an inverted U-shaped curve. Conclusion. Patient-physician discordance exists in SLE. Factors such as bodily pain and fatigue increase discordance while clinically visible signs, such as skin manifestations, reduce discordance. Clinically important discordance appears to be associated with patient self-care behaviour, particularly, medication nonadherence.

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)0.007
metaresearch head score (Gemma)0.040
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.040
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.028
GPT teacher head0.350
Teacher spread0.321 · 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 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

Citations0
Published2001
Admission routes1
Has abstractyes

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