The impact of underlying RMD diagnosis on dignity landscape in patients with systemic lupus erythematosus, rheumatoid arthritis, and systemic sclerosis
Bibliographic record
Abstract
Distress related to perceived dignity (DPD) has been associated with mental health comorbidity, intensive treatment, and quality of life among patients with rheumatic diseases (RMDs). Within the RMD landscape, each individual diagnosis might present with distinctive sociodemographic characteristics, clinical phenotypes, and prognoses, all of which shape the patient's perceived dignity. The study utilized a cross-sectional design to determine the impact of underlying RMD diagnosis on DPD phenomenon and to compare DPD patterns in patients with systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), and systemic sclerosis (SSc). Between February 2022 and April 2023, consecutive outpatients diagnosed with SLE, RA, and SSc completed the Mexican version of the Patient Dignity Inventory (PDI-Mx), along with additional patient-reported outcomes, which assessed participants perceived mental health, resilience, disease activity/severity, family functioning, fatigue, disability, quality of life, and satisfaction with medical care (SMC). A score of 54.5 or higher on the PDI-Mx was defined as indicating DPD. The attending rheumatologist determined the adequacy of control for the underlying RMD, comorbidities, and RMD diagnosis. Multivariate logistic regression analyses were performed to identify the factors associated with DPD. There were 137 patients (38.3%) with SLE, 124 (34.6%) with RA, and 97 (27.1%) with SSc. Among them, 88 patients (24.6%) had DPD. SSc diagnosis (exp ß, 95% confidence interval [95% CI] and P value: 0.291, 0.109-0.773, .013), World Health Organization Quality of Life-Brief questionnaire score (0.953, 0.926-0.980, .001 [irrespective of the specific dimension]), age (0.970, 0.942-0.999, .040), at least moderate severity for depression (9.512, 4.019-22.021, ≤.0001), 1-year previous hospitalization (2.673, 1.249-5.723, .011), Health Assessment Questionnaire Disability Index score (2.495, 1.409-4.420, .002), Routine Assessment of Patient Index Data score (1.084, 1.015-1.158, .016), and Functional Assessment of Chronic Illness Therapy score (1.023, 1.006-1.041, .009) were the factors associated with DPD, with an R² of 0.627. Overall, scores for PDI-Mx and its corresponding domains were similar across the 3 patient groups. Among patients with SLE, RA, and SSc, a diagnosis of SSc was found to be a protective factor against DPD. We also identified other protective factors, including age and quality of life. On the other hand, mental health comorbidity, disability, and more severe clinical phenotypes were associated with an increased risk of DPD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".