Kidney Point-of-Care Ultrasonography (POCUS): Development and Evaluation of a Training Program for Nephrology Fellows
Bibliographic record
Abstract
Background: Insonation is now considered the 5th pillar in physical examination. Despite its exciting potential, the uptake of POCUS in nephrology training curricula is slow. Our study aims to evaluate a locally developed program to train nephrology fellows to accurately perform a kidney POCUS scan to answer two important questions in the workup of kidney dysfunction in hospitalized patients: 1) is there urinary tract obstruction? and 2) are there small kidneys? Methods: The program consisted of two workshops that included a didactic session and hands-on training session. Trainees identified the presence or absence of urinary tract obstruction in each native kidney or kidney allograft. They also performed a measurement of kidney length. POCUS findings were compared with the abdominal ultrasound exams performed in the medical imaging department. All nephrology fellows participating in the workshop completed pre- and post-workshop surveys to document self-reported comfort level with the use of renal POCUS. Patients were asked to complete a patient satisfaction questionnaire. Results: A total of 56 native kidneys were assessed. Assessment of hydronephrosis compared to radiology-read kidney imaging reports revealed a specificity of 0.96. Assessment of small right and left kidney size showed a specificity of 0.81 and 0.75, respectively. A total of 32 transplant kidneys were assessed. Assessment of hydronephrosis and kidney allograft size revealed a specificity of 0.96 and 0.97, respectively. Post-workshop, 10 out of 11 trainees had an overall comfort level of 5 or greater out of 7 using POCUS for kidney assessment, in ruling out urinary tract obstruction and measuring kidney size. A total of 51 patients were surveyed. Most patients (71%) strongly agreed that their interaction with their doctors was improved with POCUS. Conclusion: Our study shows that training programs can provide trainees with the confidence to acquire and apply skills in POCUS and the downstream benefits from patient satisfaction.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".