MRI and biopsy in prostate cancer are the hot topic in this number of International Brazilian Journal of Urology
Bibliographic record
Abstract
19, Endourology, BPH and Urethral stricture.The papers came from many different countries such as Brazil, Italy, Canada, Spain, Japan and USA, and as usual the editor ś comment highlights some of them.The editor in chief would like to highlight the following works:Dr. Andrade and collegues from Brazil, presented in page 237 (1) a nice systematic review about the outcomes of ablative therapy and radical treatment for prostate cancer and concluded that the biochemical recurrence and urinary continence outcomes of ablative therapy and radical treatment were similar.Ablative therapy appears to have a high rate of sexual potency.Dr. Lepine and collegues from Brazil, presented in page 250 (2) we can obseve an important sytematic review about the intraoperative Computed Tomography (ICT) for detection of residual stones in endourology procedures and concluded that the use of ICT scans during PCNL significantly increases success rates when compared to the standard fluoroscopy-guided detection of residual stones.Our findings also indicate decreased reintervention rates, with no statistically significant differences in complication rates.Dr. Gomes and collegues from Brazil performed in page 287 (3) an interesting study about theurinary tract symptoms in a prospective cohort of COVID-19 survivors and concluded that LUTS are highly prevalent and bothersome six months after hospitalization due to COVID-19.Assessment of LUTS may help ensure appropriate diagnosis and treatment in these patients.Dr. Paesano and collegues from Spain, performed in page 296 (4) a nice study about the effectiveness of mapping-targeted biopsies on the index lesion in transperineal prostate biopsies and concluded that this model had the potential to avoid 23.3% of prostate biopsies without missing additional csPCa cases.Mapping-targeted biopsies of the index lesion was highly effective for identifying clinically significant prostate cancer (csPCa) in fusion transperineal prostate biopsies.A developed predictive model successfully reduced the need for almost one quarter of biopsies without missing csPCa cases.Dr. Manfredi and collegues from Italy performed in page 309 (5) a study about the new technologies in BPH treatment.The authors shows the long term functional outcomes and surgical retreatment after thulium laser enucleation of prostate and concluded that ThuLEP is associated with optimal functional outcomes and a low frequency of
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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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".