POCUS Evaluation in Acute Kidney Injury
Bibliographic record
Abstract
Acute kidney injury is a common clinical problem encountered in general internal medicine. The evaluation of acute kidney injury is mainly driven by the patient's clinical history, physical exam, and laboratory investigation including urinalysis and urine sediment examination. Point of care ultrasound (POCUS) may be a useful tool to help clinicians to narrow and/or prioritize differential diagnosis in patients presenting with acute kidney injury. Here we present a case of a 67-year-old male presenting with dysuria, fevers, and flank pain along with elevation in serum creatinine who was admitted with concern for acute kidney injury secondary to complicated urinary tract infection. Subsequent kidney POCUS of the kidneys and bladder showed bilateral anechoic fluid collection within the kidney sinus with dilated calyces suggestive of bilateral hydronephrosis, most likely due to a new diagnosis of benign prostatic hyperplasia. This case demonstrates the use of POCUS-obtained valuable diagnostic information and subsequent therapeutic management for this patient presenting with suspected acute kidney injury.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".