Cultural comparison of symptoms in patients on maintenance hemodialysis
Bibliographic record
Abstract
Although symptoms are common and frequently severe in patients on maintenance hemodialysis, little is known about the relationship between cultural background and symptom burden. The aim of this study was to explore differences in the prevalence and severity of symptoms between American and Italian hemodialysis patients. We administered the 30-item Dialysis Symptom Index to American and Italian patients receiving maintenance hemodialysis during routine dialysis sessions. The prevalence and severity of individual symptoms were compared between patient populations, adjusting for multiple comparisons. Multivariable logistic regression and ordinal logistic regression were used to assess the independent associations of cultural background with the prevalence and severity of symptoms, respectively. We enrolled 75 American and 61 Italian patients. American patients were more likely to be black (36% vs. 0%, P<0.001) and diabetic (53% vs. 13%, P<0.001). Italian patients were more likely to report decreased interest in sex, decreased sexual arousal, feeling nervous, feeling irritable, and worrying (P<0.001, respectively). Adjustment for demographic and clinical variables had no impact on these cultural differences in symptom prevalence. The median severity of 11 symptoms including muscle soreness, muscle cramps, and itching was greater among Americans (P<0.001, respectively), although nearly all of these differences were rendered nonstatistically significant with adjustment for race, diabetes, and/or Kt/V. Italian patients receiving chronic hemodialysis report a greater burden of symptoms than American patients, particularly those related to sexual dysfunction and psychosocial distress. These findings suggest that cultural background may affect adaptation to chronic hemodialysis therapy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".