Lessons learned from regional training of paediatric nephrology fellows in Africa
Bibliographic record
Abstract
BACKGROUND: Access to care for children with kidney disease is limited in less well-resourced regions of the world and paediatric nephrology (PN) workforce development with good practical skills is critical. METHODS: Retrospective review of a PN training program and trainee feedback from 1999 to 2021, based at Red Cross War Memorial Children's Hospital (RCWMCH), University of Cape Town. RESULTS: A regionally appropriate 1-2-year training program enrolled 38 fellows with an initial 100% return rate to their country of origin. Program funding included fellowships from the International Pediatric Nephrology Association (IPNA), International Society of Nephrology (ISN), International Society of Peritoneal Dialysis (ISPD), and the African Paediatric Fellowship Program (APFP). Fellows were trained on both in- and out-patient management of infants and children with kidney disorders. "Hands-on skills" training included examination, diagnosis and management skills, practical insertion of peritoneal dialysis catheters for management of acute kidney injury and kidney biopsies. Of 16 trainees who completed > 1 year of training, 14 (88%) successfully completed subspecialty exams and 9 (56%) completed a master's degree with a research component. PN fellows reported that their training was appropriate and enabled them to make a difference in their respective communities. CONCLUSIONS: This training program has successfully equipped African physicians with the requisite knowledge and skills to provide PN services in resource-constrained areas for children with kidney disease. The provision of funding from multiple organizations committed to paediatric kidney disease has contributed to the success of the program, along with the fellows' commitment to build PN healthcare capacity in Africa. A higher resolution version of the Graphical abstract is available as Supplementary information.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".