Sociodemographic factors and patient perceptions are associated with attitudes to kidney transplantation among haemodialysis patients
Bibliographic record
Abstract
BACKGROUND: Treatment decisions made by patients with chronic kidney disease are crucial in the renal transplantation process. These decisions are influenced, amongst other factors, by attitudes towards different treatment options, which are modulated by knowledge and perceptions about the disease and its treatment and many other subjective factors. Here we study the attitude of dialysis patients to renal transplantation and the association of sociodemographic characteristics, patient perceptions and experiences with this attitude. METHODS: In a cross-sectional study, all patients from eight dialysis units in Budapest, Hungary, who were on haemodialysis for at least 3 months were approached to complete a self-administered questionnaire. Data collected from 459 patients younger than 70 years were analysed in this manuscript. RESULTS: Mean age of the study population was 53 +/- 12 years, 54% were male and the prevalence of diabetes was 22%. Patients with positive attitude to renal transplantation were younger (51 +/- 11 versus 58 +/- 11 years), better educated, more likely to be employed (11% versus 4%) and had prior transplantation (15% versus 7%)(P < 0.05 for all). In a multivariate model, negative patient perceptions about transplantation, negative expectations about health outcomes after transplantation and the presence of fears about the transplant surgery were associated, in addition to increasing age, with unwillingness to consider transplantation. CONCLUSIONS: Negative attitudes to renal transplantation are associated with potentially modifiable factors. Based on this we suggest that it would be necessary to develop standardized, comprehensible patient information systems and personalized decision support to facilitate modality selection and to enable patients to make fully informed treatment decisions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".