Urinary calculi successfully expelled in a patient through traditional Chinese exercise: A case report
Bibliographic record
Abstract
RATIONALE: Urinary calculi are hard mineral deposits that typically require medication or surgery, such as lithotripsy. This case report presents traditional Chinese exercises (TCEs) as a potential alternative for stone expulsion. PATIENT CONCERNS: A 41-year-old male with no history of urinary tract stones, experienced sudden severe lower back and abdominal pain accompanied by nausea and vomiting. DIAGNOSIS: Computed tomography scan revealed a small calculus at the distal end of the left ureter (within the bladder wall), approximately 2 mm in size, with mild hydronephrosis in the ureter and renal pelvis. INTERVENTIONS: The patient was initially prescribed medication for pain relief and was advised to engage in TCEs. OUTCOMES: Follow-up computed tomography scan after the exercise regimen showed complete expulsion and disappearance of the urinary calculi. The patient reported significant improvement in physical and mental health with no recurrence of calculi observed in subsequent checkups. LESSONS: This case suggests that TCEs may facilitate the expulsion of small urinary calculi, offering a noninvasive treatment option. Further research is needed to confirm the therapeutic effects of TCEs on urinary calculi and to explore its potential mechanisms.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.007 | 0.004 |
| 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".