Pneumoperitoneum Post-Fluoroscopic Percutaneous Gastrojejunostomy Insertion: Computed Tomography and Clinical Evaluation
Bibliographic record
Abstract
INTRODUCTION: To assess the incidence and clinical significance of pneumoperitoneum after radiologic percutaneous gastrojejunostomy (PGJ) tube insertion. METHODS: Sixteen subjects were prospectively assessed after imaging-guided PGJ tube insertion to discern the incidence of pneumoperitoneum related to specific clinical signs and symptoms. Computed tomography of the abdomen and the pelvis was performed immediately after PGJ insertion. A clinical evaluation, including history, general and abdominal physical examination, temperature, complete blood cell count, abdominal pain, and abdominal tension, was performed on days 1 and 3, and at the discretion of the nutritional support team on day 7 after PGJ insertion. RESULTS: Fifteen of the 16 subjects demonstrated imaging findings of pneumoperitoneum after the PGJ-tube insertion. Only a small amount of pneumoperitoneum was demonstrated in 10 of the subjects, whereas a large volume of gas was detected in 2 of the subjects. The only altered clinical findings encountered were increased white blood cell count and fever. These abnormal clinical data were most frequently seen immediately after feeding-tube placement. DISCUSSION: Pneumoperitoneum was a common finding after PGJ-tube placement in our study population. There were no statistically significant abnormal clinical parameters, in the presence or absence of pneumoperitoneum, for any of the subjects after PGJ-tube insertion. Conservative management of pneumoperitoneum after PGJ is warranted.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".