Are North American Nephrologists Biased against Peritoneal Dialysis?
Bibliographic record
Abstract
OBJECTIVE: To examine possible bias against peritoneal dialysis (PD) by nephrologists less familiar with it. DESIGN: Secondary analysis of a previously reported survey. PARTICIPANTS: All practicing Canadian nephrologists (n = 290, response rate 66.2%) and a subgroup of American nephrologists who were members of the National Kidney Foundation Council on Dialysis (n = 507, response rate 47.3%). Responses were then subdivided by type of dialysis practice: mainly or only hemodialysis (HD, n = 117), mainly or only PD (n = 16), or both HD and PD (n = 232). INTERVENTION: Self-administered mailed questionnaire. MAIN OUTCOME MEASURES: Opinions and attitudes of nephrologists concerning patient characteristics favoring one dialysis modality over the other, as well as the relative utilization of HD and PD currently and in a hypothetical ideal situation. RESULTS: The main differences were present between physicians practicing mainly HD and physicians practicing mainly PD, with those practicing both giving answers usually intermediate to the others. The maximum weight suitable for PD was 10 kg less according to HD-oriented nephrologists compared with PD-oriented nephrologists (97.8 kg vs 108.5 kg). All nephrologists agreed that, ideally, 40% of prevalent end-stage renal disease patients should be on PD to optimize cost-effectiveness, whereas the proportion should be between 32% and 45% when one optimizes survival, wellness, and quality of life. In general, differences between groups were small. CONCLUSIONS: Most nephrologists favored a proportion of PD higher than the current prevalence seen in either Canada or the U.S.A. If physicians' biases are contributing to the distribution of dialysis modalities, they are not likely to be major factors. Unknown but important factors, external to the physician, may shape modality distribution more than the opinions and attitudes of physicians. If a more balanced and cost-effective dialysis delivery system is desired, more understanding and manipulation of these non physician-related factors will be required.
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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 | 0.007 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".