Bone pain assessment in patients with chronic kidney disease undergoing hemodialysis
Bibliographic record
Abstract
ABSTRACT BACKGROUND AND OBJECTIVES: The objective of this study was to descriptively evaluate the symptom of pain and its influence on the quality of life in patients with chronic renal failure on hemodialysis treatment. METHODS: This is a descriptive, cross-sectional exploratory, quantitative approach. We evaluated 50 chronic renal failure patients on hemodialysis treatment through the Brief Pain Inventory and the Kidney Disease and Quality of Life Short Form. The emotional factors were evaluated by the Toronto Alexithymia and Hospital Anxiety and Depression Scales. RESULTS: The predominant age group was 40 to 60 years. 72% of the patients showed some bone changes and the majority interviewed did not have formal jobs at the time of interview. There was a noticeable increase in the intensity of pain in patients with bone alterations when compared to those without, as well as an increased ambulation impairment. The Hospital Anxiety and Depression Scale showed a slight increase in both parameters in those with bone pain. Regarding the quality of life, physical function and work status were the most affected. There was the absence of alexithymia in most of the interviewees, a positive correlation between pain intensity versus physical function (r=-0.14, p=0.03), physical function x work status (r=-0.28, p=0.04) and a negative correlation between alexithymia versus anxiety (r=0.03, p=0.62) and moderate pain versus overall health (r=0.06, p=0.40). CONCLUSION: We found worse outcomes in hemodialysis patients who presented bone alterations, regardless of the source.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".