Anatomic Considerations for Radical Retropubic Prostatectomy in an Achondroplastic Dwarf
Bibliographic record
Abstract
This is the first report of a radical retropubic prostatectomy (RRP) in an achondroplastic dwarf. We highlight the pelvic anatomy, precluding laparoscopic or robotic prostatectomy, and making open surgery extremely difficult. We review relevant literature regarding general, urological, and orthopedic abnormalities of achondroplasia (ACH) and present a clinical case. No reports of RRP in achondroplastic dwarfs exist, with only one case of an abandoned RRP due to similar pelvic anatomy in a patient with osteogenesis imperfecta. Significant lumbar lordosis found in ACH results in a short anteroposterior dimension, severely limiting access to the prostate. We present a case of a 62-year-old achondroplastic dwarf who had Gleason 3+4 disease on transrectal ultrasound-guided biopsy in four from 12 cores. Surgery was difficult due to narrow anteroposterior pelvic dimension, but achievable. Histological analysis revealed multifocal prostate cancer, with negative surgical margins and no extraprostatic extension. RRP in ACH patients, although possible, should be approached with caution due to the abnormal pelvic dimensions, and discussions regarding potential abandonment of surgery should be included during informed consent. This case highlights the preoperative use of computed tomography to assist in the surgical planning for patients with difficult pelvic anatomy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".