Management of Men With Lower Urinary Tract Symptoms Due to Benign Prostatic Hyperplasia During and After COVID-19
Bibliographic record
Abstract
The lower urinary tract (LUT), in particular the prostate, has been theoretically recognized as a target for SARS-CoV-2. Moreover, common pathophysiological mechanisms have been described for BPE/LUTS and COVID-19, including RAS dysregulation, androgen receptors, and MetS-related factors. These factors raise concerns about the possibility of worse urological outcomes due to BPE/LUTS progression in COVID-19 patients. The available results suggest a correlation between SARS-CoV-2 infection, exacerbation or new onset of LUTS, and semen impairment. BPE patients’ care and management have been deeply affected by COVID-19. In the midst of the pandemic, the main urological guidelines suggested postponement of BPH-related deferrable medical examinations and surgery. Telemedicine, therefore, gained attention and interest. Clinical evidence of impaired QoL or complications expedited surgical intervention. An informed consent covering the risk of COVID-19 and a negative molecular PCR within 72 hours of surgery were mandatory. A reduction in procedures under general anaesthesia was recommended. Long waiting lists accrued worldwide during the pandemic, leading to regular review of the BPE waiting lists and patients’ clinical status, encouraging the increase of minimally invasive office-based procedures, even in the post-COVID-19 era, and the improvement of telemedicine. Prospective studies are still needed to assess the course of LUTS/BPE patients after COVID-19.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".