A Case of Multiple Intra-Abdominal Abscesses Due to Remnant Gallstones during Laparoscopic Cholecystectomy
Bibliographic record
Abstract
腹腔鏡下胆囊摘出術（laparoscopic cholecystectomy；以下，LCと略記）施行時の，腹腔内の落下結石の遺残による膿瘍形成は注意すべき合併症の一つである．今回，我々はLC時の遺残結石により，腹腔内多発膿瘍を形成し治療に難渋した1例を経験したので報告する．症例は81歳の女性で，コントロール不良の糖尿病を合併しており，LC施行時に小結石が落下し可及的に回収した．術後2か月後に右側腹部痛を主訴に来院し，遺残結石を核とした腹腔内多発膿瘍を認めた．当初は保存加療を行ったが，治療抵抗性であり開腹結石除去，洗浄ドレナージを施行した．しかし，結石の完全除去は困難であり，腹腔内膿瘍の再燃を認めたため再ドレナージを要した．再手術後8か月後に画像上膿瘍の消失を確認でき，再手術後12か月の時点で膿瘍の再燃なく外来で経過観察中である．LC時に結石が落下し遺残した場合，特に膿瘍形成のリスクが高い症例では治療に難渋することもあり，初回手術時に落下結石の完全除去が重要である．
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 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".