Thirty-Day Mortality After Transurethral Resection of the Prostate in Patients Treated with Androgen Deprivation Therapy
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Seven percent of patients with prostate cancer (PCa) who are exposed to androgen deprivation therapy (ADT) may need transurethral resection of the prostate (TURP). Our objective was to examine the rate and the predictors of 30-day mortality (30dM) after TURP in patients who were exposed to ADT in a large, contemporary Canadian cohort. PATIENTS AND METHODS: We assessed the 30dM rate after TURP in 853 men with the diagnosis of PCa who were treated with primary ADT or radiation therapy followed by ADT. The effect of age, comorbidity (coded according to the Charlson Comorbidity Index [CCI]), number of previous TURP procedures, history of radiation therapy, exposure to antiandrogens, and the type and the duration of ADT before TURP were all tested in univariable and multivariable logistic regression models that predicted 30dM after TURP. RESULTS: During the initial 30 days after TURP, 38 deaths occurred (4.5%, 95% confidence interval: 3.2%-6.2%). Of all variables, the CCI was the only statistically significant (P = 0.001) predictor of 30dM after TURP. The accuracy of CCI in predicting 30dM after TURP in individual patients was 65.1%. Lack of consideration of clinical variables that could predict the 30dM rate after TURP, such as prostate size or prostate-specific antigen level, represents a limitation of this study. CONCLUSIONS: A substantial risk of 30dM is associated with TURP that is performed in patients who are exposed to ADT. Unfortunately, the predictors used in this analysis could not define the individual risk of 30dM with sufficient accuracy. Nonetheless, the average 4.5% risk should be considered at the time of informed consent.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.000 | 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".