The Effect of Pre-TURP Bladder Irrigation with 0.2% Chlorhexidine in Patients with Foley Catheter Regarding Postoperative Bacteremia Decrease
Bibliographic record
Abstract
Background: Transurethral resection of the prostate (TURP) has been widely used for patients suffering from bladder colonization with bacteria, increasing the probability of bacteremia and sepsis despite consuming prophylaxis antibiotics. Objectives: The study aimed to evaluate the effect of pre- TURP bladder irrigation with 0.2% chlorhexidine in reducing postoperative bacteremia. Methods: This clinical trial study was conducted on 60 benign prostatic hyperplasia (BPH) patients who were candidates for TURP in the urology department of Al-Zahra Hospital. All patients suffered from urinary catheters, and they were allocated into two groups (n = 30). Antibiotic prophylaxis was prescribed for all the patients. In the case group, the bladder was rinsed by chlorhexidine 0.2% before TURP; however, and the bladder in the control group was rinsed by distilled water. Postoperative bacteremia were evaluated using procalcitonin (PCT) measurement and BACTEC automated blood culture six hours after surgery. Results: Positive BACTEC blood culture was observed in three (10%) and no (0%) patients in the control and case groups, respectively (P = 0.071). Moreover, 6.6 % and 46.6 % of the patients in the control group had low and high PCT levels, respectively. Furthermore, 40 % and 6.66 % of the patients in the case group had low and high PCT levels, respectively. There was a significant difference between the two groups in terms of the PCT level (P < 0.01). Conclusions: The frequency of patients with a high PCT level was higher in the control group than in the case group, suggesting that chlorhexidine in the catheterized patients undergoing TURP reduced the number of bacteria in the bladder.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".