Evaluating International Prostate Symptom Score (IPSS) in Accuracy for Predicting Post-Operative Urinary Retention After Elective Cataract Surgery: A Prospective Study
Bibliographic record
Abstract
BACKGROUND: Postoperative urinary retention-a common and important complication of surgical procedures, can occur after any form of surgical intervention, in both sexes and all ages regardless of patients' previous history of urinary problems. The importance of post operative urinary tract retention is due to its effect on development of post operative urinary infection, patient anxiety and discomfort, prolongation of hospital stay and increase in hospital costs and morbidity. The International Prostate Symptom Score (IPSS) is an easy method for quantifying and estimating the association between pre-operative bladder-outflow problems and post-operative urinary retention. The aim of present study was to investigate whether the IPSS could predict the likelihood of patients developing urinary retention after elective cataract surgery. METHODS: One hundred and fourteen male patients older than fifty years old, who were candidate for elective cataract surgery, were enrolled in this study. All patients completed an IPSS questionnaire form before operation, and classified into three groups regarding their score (0-7: mild, 8-19: moderate, 20- 35: severe). RESULTS: Totally 8 patients (7%) developed post-operative urinary retention during first 24 hours after operation. Of the 8 urinary retention patients, 2 had moderate symptoms and 6had severe symptoms. There was a significant difference in developing postoperative urinary retention between patients having mild symptoms and patients having severe symptoms (P-value: 0.025). CONCLUSION: It is concluded that while some litterateurs definitely support the idea that IPSS may be useful for predicting post operative urinary retention, there are still some controversies. Considering our results, it seems that IPSS score is not useful in the accurate prediction of those patients who are likely to develop postoperative retention after surgical procedures other than arthroplasty, and more precise studies are need to be conducted about urinary retention occurring postoperatively in different type surgeries, different methods of anesthesia considering age and gender of patients.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".