P124 Risk of surgery in inflammatory bowel disease: A systematic review and meta-analysis of sex-based differences
Bibliographic record
Abstract
Abstract Background Inflammatory bowel diseases (IBDs) are chronic diseases that require routine hospital visits and long-term medical treatment for control of disease activity. Factors such as gender may impact the use and need for healthcare. This systematic review aimed to summarize what is known about sex differences in the risk of bowel surgery in patients with IBD. Methods Embase, Medline, CINAHL, and Web of Science abstracts (January 2012 to January 2022) were searched systematically for observational studies examining associations between sex and risk of bowel surgery. Screening and data extraction were performed independently by two reviewers using Covidence. Study data were analysed and reported in accordance with the PRISMA guidelines. Quality assessment of included studies was conducted using the Newcastle-Ottawa Scale for cohort studies. Pooled hazard ratios (HRs) were calculated using random effects model meta-analysis for the risk of surgery. In addition, meta-analysis was undertaken to assess the risk of surgery by IBD subtype. The between-study heterogeneity was assessed by calculating the tau-squared and the I-squared statistics. Results Of 9,902 screened articles, 36 studies were included in the review. Most studies were retrospective by design (74.6%). In total, 21 of 36 studies found statistically significant sex-based differences in the risk of bowel surgery for IBD patients. A pooled estimate of HRs for the 13 studies eligible for meta-analysis showed a statistically significant increased risk of bowel surgery among male patients (HR: 1.43 [95% confidence interval (CI): 1.09;1.86]) compared to female patients. The between-study heterogeneity was high (I2=88.60 [60.60;96.33] and tau2=0.17 [0.03;0.58]) indicating that the pooled estimate should be interpreted with caution. These findings were consistent with the subgroup analysis for ulcerative colitis (HR: 1.78 [1.16;2.72]), but no statistically significant sex difference in the risk of surgery in Crohn’s disease patients was found (HR: 1.26 [0.82;1.93]). Conclusion Sex differences exist in the risk of bowel surgery in IBD patients, and further research is needed to address the underlying causes and consequences of these disparities. It is unclear whether differences are due to underlying biologic mechanisms or are associated with healthcare system related factors such as differential access to care. Surgical procedures or the lack or delay thereof, will have consequences for the further disease trajectory.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| 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".