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Record W4404674935 · doi:10.1097/md.0000000000040641

Urinary calculi successfully expelled in a patient through traditional Chinese exercise: A case report

2024· article· en· W4404674935 on OpenAlexaff
Jing Xian Li, Guanwu Li, Rong-liang Dun, Min Fang, Qingguang Zhu

Bibliographic record

VenueMedicine · 2024
Typearticle
Languageen
FieldHealth Professions
TopicTherapeutic Uses of Natural Elements
Canadian institutionsUniversity of Ottawa
FundersNational Natural Science Foundation of China
KeywordsMedicineHydronephrosisNauseaVomitingUrinary systemUreterPelvisSurgeryAbdominal painRenal pelvisLower urinary tract symptomsRegimenRadiologyInternal medicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.661
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.092
GPT teacher head0.455
Teacher spread0.363 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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