Self-care of liver, kidney and bone marrow transplant patients with diabetes
Bibliographic record
Abstract
Self-care is a set of actions that individuals take to maintain life, good health, and well-being. Regardless of the type of diabetes, individuals must perform self-care and comply with the treatment to prevent complications, achieve better disease management, and maintain their quality of life. This study aimed to examine self-care behaviors of liver, kidney, and bone marrow transplant patients with diabetes. The study has used a descriptive correlational design and was carried out in an endocrinology and diabetes center in Brazil. A total of 101 patients participated in the study. The Diabetes Self-care Activities Questionnaire was used, and the quantitative analysis was carried out using SPSS. The results show that the highest self-care levels occurred in the medication domain, while the lowest were found in the specific diet domain. Some important correlations were found: men were more likely to assess blood glucose, use combined oral/insulin therapy, take insulin, and take medications as prescribed than women; patients on combined oral/insulin therapy followed dietary recommendations more frequently than the others; and patients with altered serum urea and history of stroke had high levels of self-care. The results made it possible to know the compliance in performing self-care activities in transplanted patients with diabetes, supporting the development of interventions to motivate and improve self-care.
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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 | 0.000 | 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) | 0.001 | 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".