Hospital Readmission Rates after Ileal Pouch-Anal Anastomosis
Bibliographic record
Abstract
PURPOSE: The goal of this study was to determine the unplanned hospital readmission rate following ileal pouch-anal anastomosis, prior to loop ileostomy closure. METHODS: Patients undergoing ileal pouch-anal anastomosis over a five-year period were included in this retrospective study. Unplanned readmissions and readmission diagnoses were compiled. Gender, age, type of disease, duration of illness, elective vs. urgent surgical indication, operative method, steroid use, American Society of Anesthesiologists score, and regional anesthesia use at initial ileal pouch-anal anastomosis were evaluated as potential factors for readmission. Total length of stay was compared between patients readmitted and not readmitted. RESULTS: One hundred and ninety-five patients underwent ileal pouch-anal anastomosis with diverting ileostomy. Fifty-nine patients (30 percent) required readmission. Forty-one patients had a single readmission, and 18 patients had at least 2 readmissions. Small bowel obstruction (28/86) and pelvic sepsis/ anastomotic leak (28/86) were the most common diagnoses upon readmission. Seventeen of 59 patients (28.8 percent) required surgical intervention following readmission and 42 patients were managed nonoperatively. Patients using systemic steroids at the time of surgery were more likely to be readmitted [47/116 (41 percent) vs. 12/79 (15 percent), P = 0.001). Length of stay (including initial admission for ileal pouch-anal anastomosis) for patients requiring readmission averaged 19.6 days vs. 9.6 days for patients not readmitted. CONCLUSIONS: Hospital readmission after ileal pouch-anal anastomosis is common. We plan to institute a more intensive follow-up in an effort to prevent readmission of selected high-risk patients who might be effectively managed as outpatients.
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 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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".