Early surgical management of ureteral trauma
Bibliographic record
Abstract
Cl:Shrnut vlasLnch zkuenost a vsledk asn chirurgick lby porann moovod (PM).Vsledky:Vk oetench byl 33-66 let (v prmru 47 let). Nejastj pinou PM byly gynekologick vkony (43 %), dle endoskopick urologick vkony (28 %), kolorektln operace (18 %), deliberace ureteru (5 %), operace aneuryzmatu bin aorty (3 %), transvezikln prostatektomie (1,5 %) a steln porann (1,5 %).PM bylo diagnostikovno 18x nikem moi do operan rny, 16x do retroperitonea, 6x do dutiny bin a 9x do vaginy Jako typ obstrukce byl v 19 ppadech zjitn megaureter nad pekkou, 2x afunkce ledviny a 1 x anurie pi bilaterlnm podvazu moovod. Jako zpsob chirurgickho een PM byla v 21 ppadech zvolena ureterocystoneostomie (z toho 15x asn a 6x odloen), 6x Boariho lalokov plastika (5x asn a lx odloen), 14x sutura ureteru (vdy eeno peroperan) , 4x ureterorafie (3x asn a lx odloen), lx nhrada tenkou klikou (asn), 2x nefrektomie (odloen), lOx nefrostomie (9x asn a lx odloen), 13x inzerce stentu (11 asn a 2x odloen).Zvr:Bez ohledu na zpsob zvolen terapie bylo v naem souboru eeno PM asn (do tdne od stanoven sprvn diagnzy) u 58 pacient (81,7 %). Tento asn pstup k definitivn lb PM se nm osvdil. Pro pacienta bylo vhodn zejmna zkrcen len. K definitivnmu uren vhodnosti asnho operanho een PM by byla nutn prospektivn randomizovan studie.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".