A Case of Reverse Dialysis: Bladder Perforation During Robotic Hysterectomy Presenting as Acute Renal Failure
Bibliographic record
Abstract
Robotic surgery is gaining more fame due to its advantages over laproscopic surgery especially in gynecological procedures. Intra operative complications are far less in the former. Bladder perforation is a rare intra operative complication of robotic hysterectomy that can present as fatal electrolyte disturbances, sepsis and might even give a picture of acute renal failure. We present a case of a bladder perforation status post hysterectomy that arrived in emergency with the symptoms of nausea, vomiting and ascities. Her blood chemistry was consistent with acute renal failure but with no radiological evidence of kidney disease. Cystoscopy and ureterography revealed a bladder perforation. The clinical and lab picture was thought to be due to the same injury that might have caused the urea and creatinine to be absorbed in the peritoneal cavity. The diagnosis was supported by the fact that her symptoms and abnormal lab values reverted to normal after the repair of the injury. The case which we have presented is yet another in league to help physician making diagnosis of bladder injury when they see a patient with a rapid hypercreatininemia and ascities of short duration especially in the setting of a recent intra abdominal surgery. doi:10.4021/wjnu6e
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.012 | 0.006 |
| 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".