Long Term Outcome After Open Abdomen Treatment: Function and Quality of Life
Bibliographic record
Abstract
Background: Open abdomen treatment (OAT) is widely accepted to manage severe abdominal conditions such as peritonitis and abdominal compartment syndrome but can be associated with high morbidity and mortality. The main risks in OAT are (1) entero-atmospheric fistula (EAF), (2) failure of primary fascial closure, and (3) incisional hernias. In this study, we assessed the long-term functional outcome after OAT to understand which factors impacted most on quality of life (QoL)/daily living activities and the natural course after OAT. Materials and Methods: After a retrospective analysis of 165 consecutive OAT patients over a period of 10 years (2002–2012) with over 65 clinical parameters that had been performed at our center (1), we initiated a prospective structured follow-up approach. All survivors were invited for a clinical follow-up. Forty complete datasets including clinical and social follow-up with SF-36 scores were available for full analysis. Results: The patients were dominantly male (75%) with a median age of 52 years. Primary fascial closure (PC) was achieved in 9/40 (23%), while in 77% a planned ventral hernia (PVH) approach was followed. A total of 3/4 of the PVH patients underwent a secondary-stage abdominal wall reconstruction (SSR), but 2/3 of these reconstructed patients developed recurrent hernias. Fifty-five percent of the patients with PC developed an incisional hernia, while 20% of all patients developed significant scarring (Vancouver Scar Score >8). Scar pain was described by 15% of the patients as “moderate” [Visual Analog Scale (VAS) 4–6] and by 10% as “severe” (VAS > 7). While hernia presence, PC or PVH, and scarring showed no impact on QoL, male sex and especially EAF formation significantly reduced QoL. Discussion: Despite many advantages, OAT was associated with relevant mortality and morbidity, especially in the early era before the implementation of a structured concept at our center. Follow-up revealed that hernia incidence after OAT and secondary reconstruction were high and that 25% of patients qualifying for a secondary reconstruction either did not want surgery or were unfit. Sex and EAF formation impacted significantly on QoL, which was lower than in the general population. With regard to hernia incidence, new strategies such as prophylactic mesh implantation upon fascial closure should be discussed analogous to other major abdominal procedures.
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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 | 0.004 |
| 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 | 0.001 | 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".