Perceived barriers to guidelines in peritoneal dialysis
Bibliographic record
Abstract
BACKGROUND: Little is known regarding barriers to guideline adherence in the nephrology community. We set out to identify perceived barriers to evidence-based medicine (EBM) and measurement of continuous quality indicators (CQI) in an international cohort of peritoneal dialysis (PD) practitioners. METHODS: Subscribers to an online nephrology education site (Nephrology Now) were invited to participate in an online survey. Nephrology Now is a non-profit, monthly mailing list that highlights clinically relevant articles in nephrology. Four hundred and seventy-five physicians supplying PD care participated in an online survey assessing their use of EBM and CQI in their PD practice. Ordinal logistic regression was utilized to determine relationships between baseline characteristics and EBM and CQI practices. RESULTS: The majority of physicians were nephrologists (89.7%), and 50.4% worked in an academic centre. Respondents were from the following geographic regions: 13.5% Canadian, 24% American, 23.8% European, 4.4% Australian, 5.3% South American, 10.7% African and 12.2% Asian. Adherence to PD clinical practice guidelines were generally strong; however, lower adherence was associated with countries with lower healthcare expenditure, not using personal digital assistant (PDA), the longer the physician had been practising and smaller (< 20 patients per centre) PD practice. CONCLUSIONS: International variation in guideline adherence may be influenced by a country's healthcare expenditure, physician's PDA use and experience, and size of PD practice which may impact future guideline development and implementation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".