Complex abdominal wall hernias as a barrier to quality of life in cancer survivors
Bibliographic record
Abstract
Background: Many cancer survivors live with postoperative complex abdominal wall hernias (CAWHs). However, the impact of CAWHs on their quality of life is unknown, and few descriptions of patient experiences exist. We performed a qualitative study to explore cancer survivors’ experience with CAWHs before and after repair. Methods: Patients waiting to undergo CAWH repair or who had completed the surgery in the previous 18 months were identified from a single surgeon’s practice in CAWH at a tertiary care centre. Clinical and demographic data were extracted from the electronic patient record. An in-depth semistructured interview guide was developed by experts in CAWH and qualitative methodology. Interviews were conducted in March 2013. We used comparative analysis techniques and coding strategies to identify themes. Results: Ten preoperative and 12 postoperative participants were interviewed. The average age of the participants was 64 years in both groups, with an even sex distribution. The most frequently diagnosed cancer in both groups was colorectal cancer. Participants’ views were organized into 5 themes: 1) unable to return to normal life, 2) sense of abandonment, 3) experiencing fear and distress, 4) preoperative: desperate for help and 5) postoperative: “getting my life back.” Conclusion: Our findings show the all-encompassing impact of a CAWH on the life of cancer survivors. They strongly suggest that hernia management should be viewed as an integral part in the continuum of cancer treatment to improve the quality of life of cancer survivors with hernias.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".