Le trajet de soins de l'insuffisance rénale chronique :Développement et perspectives
Bibliographic record
Abstract
Because of the significant costs related to the treatment of end-stage kidney disease by dialysis, Belgian Health Care Authorities proposed in June 2009 to launch an early multidisciplinary care plan for chronic kidney disease (CKD) patients in the form of a clinical care pathway (CCP) focusing on a combined follow-up by the general practitioner and the nephrologist. The objective was to increase nephro-protection measures, reduce patient morbidity and mortality, and delay admission on dialysis. Our Nephrology Department at Erasme Hospital took the opportunity of CCP to set up workshops on therapy education which promote CKD patients' compliance and autonomy regarding their treatment (" empowerment "). These workshops are conducted by a health professional together with a patient partner recruited by our team according to the model developed by the faculty of medicine at the University of Montreal. This model is based on the patient's valued experience of living with a chronic disease, a knowledge which is complementary to that acquired by any health professional. This patient partnership (PP) may also be implemented in teaching and research. In health care services, patient partners with a resource profile are involved not only in the organization of these services, but also in the development and management of health care political programs. The PP model currently developed in the Nephrology Department is part of the Quality project of our academic hospital and helps to further the co-construction of future health care networks.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".