The Abdominal Reapproximation Anchor Device
Bibliographic record
Abstract
INTRODUCTION: Achieving primary fascial closure after damage control laparostomy can be challenging. A number of devices are in use, with none having yet emerged as best practice. In July 2013, at Westmead Hospital, we started using the abdominal reapproximation anchor (ABRA; Canica Design, Almonte, Ontario, Canada) device. We report on our experience. METHODS: A retrospective review of medical records for patients who had open abdomens managed with the ABRA device between July to December 2013 was done. Data extracted included age, sex, body mass index (BMI), reason for the open abdomen, Acute Physiology and Chronic Health Evaluation II (APACHE II) score, number of laparostomies prior to ABRA placement, duration of placement, device complications, length of hospital and intensive care unit (ICU) stay, and outcomes. RESULTS: , APACHE II score was 14.5, duration with open abdomen prior to ABRA placement was 11.75 days, duration with ABRA in situ was 9 days, duration of hospital stay was 64.25 days, and ICU stay was 37.75 days. Three patients (75%) achieved fascial closure, and 1 achieved skin closure. No incidences of enterocutaneous fistulae occurred. CONCLUSION: The ABRA is a unique emerging alternative to aid in achieving fascial closure in patients managed with open abdomens. Our case series demonstrates that it can be used effectively in selected patients. Studies are needed to compare its efficacy with more traditional methods.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".