P474 Postoperative infectious complications in patients with Inflammatory Bowel Disease: experience of a tertiary center
Bibliographic record
Abstract
Abstract Background Patients with Inflammatory Bowel Disease (IBD) are at increased risk of postoperative infectious complications (PIC). There are few studies and conflicting data regarding the risk factors involved in these patients. The aim of this study was to investigate the incidence of infectious complications and postoperative mortality in patients with IBD who underwent intestinal surgery, as well as describe the characteristics of our population and identify possible risk factors. Methods Retrospective study on patients with Inflammatory Bowel Disease (Crohn’s disease (CD) and Ulcerative Colitis (UC)) treated in “Virgen de las Nieves” University Hospital between January 2019 and December 2020. Patients who underwent small bowel or colorectal surgery were included. Information regarding demographic and clinical data, procedures, treatments and surgical outcomes were collected. Clinical outcomes documented were postoperative infectious complications and in-hospital mortality. Descriptive inferential were carried out. Results 36 patients were included (47.2% male, median age 44.9 years). All the characteristics of our sample are detailed in Figures 1 and 2. Regarding surgical outcomes, 7 patients developed PIC (6 surgical site infection (SSI) and 1 multiple infections including pneumonia, candidemia and SSI). The features of these patients are detailed in Figures 3 and 4. Conclusion Postoperative infectious complications after intestinal surgery are an important cause of morbi-mortality in CD and UC patients. Identifying risk factors early, could help reduce the incidence of these complications. Seven patients (19,4%) in our sample developed PIC, mostly SSI. All of them diagnosed of CD, which explains the greater need of surgery in them compared to patients with UC. These patients had more severe disease: penetrating pattern (B3 according to Montreal Classification) and ileocolonic location (L3). Most patients were receiving immunosuppressive treatments by the time of surgery, especially biological treatments. The median time of evolution of the disease was high, describing a profile of disease more advanced. Our efforts should be determined to early prevention and treatment of modifiable risk factors during the perioperative period. In order to achieve this aim, further research is needed, with prospective, multicenter and wider population studies, trying to control any confusion factors. Finally, we would like to highlight the need of studies analyzing UC population, as most of them focus on patients with CD.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".