Predictors of Catheter-Related Bladder Discomfort After Surgery: A Literature Review
Bibliographic record
Abstract
Background: Indwelling bladder catheters are routinely used in clinical practice. Patients may experience postoperative indwelling catheter-related bladder discomfort (CRBD). This study aimed to perform a literature review to identify predictors of postoperative CRBD. Methods: We searched PubMed for relevant articles published between 2000 and 2020 using the search items "CRBD", "catheter-related bladder discomfort", and "prediction". Additionally, we searched for articles that matched the research objectives from the references of the extracted articles. We included only prospective observational studies involving human participants and excluded interventional studies, observational studies that did not report sample sizes, or observational studies that did not research on predictors of CRBD. We narrowed our search to the keyword "prediction" and found five references. We selected five studies that met the objectives of the study as the target literature. Results: Using the keywords "CRBD" and "catheter-related bladder discomfort", we identified 69 published articles. The results were narrowed down by the keyword "prediction", and five studies that recruited 1,147 patients remained. The predictors of CRBD can be divided into four factors: 1) patient factors; 2) surgical factors; 3) anesthesia factors; and 4) device and insertion technique factors. Conclusion: Our study suggests that patients with predictors of CRBD should be closely monitored to reduce postoperative patient suffering, and their quality of life should be improved after anesthesia.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".