Prevalence of Parastomal Hernia and Factors Associated With Its Development
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to identify risk factors for development of a parastomal hernia (PH). DESIGN: Cross-sectional survey. SETTING AND SUBJECTS: The target population comprised 2854 persons receiving services from the Manitoba Ostomy Program. Seven hundred sixty-four responses were received, yielding a response rate of 29.3%. Respondents average age was 70 years (SD = 12.8); 425 (55.6%) had a colostomy, 236 (30.8%) had an ileostomy, 63 (8.2%) had a urostomy, and 40 (5.2%) indicated other types of stomas or fistula. INSTRUMENTS: A questionnaire was developed by the authors that collected the following data: demographics, relevant medical history, personal and lifestyle factors, surgery-related factors, pre- and postoperative care factors, and information about the presence of a PH and physical and lifestyle effects related to a PH. Devices to enable respondents to measure the size of their stoma and abdominal girth were included in the survey package. The survey tool took approximately 30 to 45 minutes to complete. METHODS: An informational pamphlet and introductory letter were mailed 2 weeks before the survey was mailed. This was followed by a reminder letter. Bivariate analyses were completed in order to identify potential associations between all variables and a diagnosis of a PH; multivariate analysis was then completed to determine which factors were associated with an increased likelihood of a PH. RESULTS: Significant univariate associations were found between a diagnosis of a PH and diverticulitis, cirrhosis, benign prostatic enlargement, previous diagnosis of hernia, a smoking history, type of ostomy, stoma size, and continuous variables age and abdominal girth. Multiple regression analysis indicated that patients who underwent stoma surgery for cancer had larger stomas (1.5 to >3 in), and a colostomy were more likely to develop a PH. CONCLUSIONS: The results of this study indicate that PHs are prevalent. Additional research is needed to determine more effective intervention for preventing and managing a PH.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".