DG-RAR (Doppler-guided recto-anal repair): a new mini invasive technique in the treatment of prolapsed hemorrhoids (grade III-IV): preliminary report.
Bibliographic record
Abstract
We present preliminary data from a prospective observational study on an initial group of 40 patients, selected from our Department, affected by grade III-IV hemorrhoids and treated with a new less invasive technique called Doppler-guided recto-anal repair [DG-RAR; Agency for Medical Innovations GmbH (AMI), Feldkirch, Osterreich, Austria]. This study was performed by analyzing bleeding, pain, and prolapse in the preoperative period and after surgery. Follow-up ranged from 5 to 37 months. We used this technique to treat the "vascular factor" with a Doppler-guided suture of the terminal branches of the hemorrhoidal arteries (HAL Doppler), and then we reduced hemorrhoidal prolapse [recto-anal repair (RAR)]. Recto-anal repair was performed with a special proctoscope with an oblique slot that when rotating shows a progressively wider portion of anorectal mucosa and submucosa in a longitudinal direction. Furthermore, this rotation enables the performance of a longitudinal pexy where the prolapse is located. The result is an immediate reduction of hemorrhoidal prolapse. Postoperative follow-up showed disappearance of pain and no bleeding. Relapse of prolapse occurred in 2 (5%) patients. Complications included 2 rectal impactions and 2 cases of thrombosis. The data appear encouraging for grade III-IV hemorrhoids treated with DG-RAR because of reduced trauma and a lower rate of complications with respect to other techniques used for prolapse reduction.
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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) | 0.000 | 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) | 0.001 | 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".