ReviewCancers2024
Posterior Retroperitoneal Laparoscopic Adrenalectomy: An Anatomical Essay and Surgical Update.
Review in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Trial
- Review
- Machine learning-based models for intraoperative blood loss of retroperitoneal laparoscopic adrenalectomy.Surgical endoscopy · 2026Article
- Clinical application of robot-assisted laparoscopic resection of large pheochromocytomas via the renal surface plane using the fatty fissure as an anatomical landmark.Pakistan journal of medical sciences · 2026Article
- Article
- Mayo adhesive probability score predicts perioperative outcomes of laparoscopic adrenalectomy: a systematic review and meta-analysis.Frontiers in oncology · 2026Review
- An Analysis of Post-Adrenalectomy Dynamics in MACS (Mild Autonomous Cortisol Secretion)-Positive Adrenal Tumours: The Biomarkers and Clinical Impact.Journal of clinical medicine · 2025Review
- Single-Port Robotic Posterior Retroperitoneoscopic Adrenalectomy: Current Perspectives, Technical Considerations, and Future Directions.Journal of clinical medicine · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Posterior retroperitoneal laparoscopic adrenalectomy (PRLA) has emerged as a revolutionary, minimally invasive technique for adrenal gland surgery, offering significant advantages over traditional open approaches. This narrative review aims to provide a comprehensive update on PRLA, focusing on its anatomical foundations, surgical technique, and clinical implications. We conducted an extensive review of the current literature and surgical practices to elucidate the key aspects of PRLA. The procedure leverages a unique "backdoor" approach, accessing the adrenal glands through the retroperitoneum, which necessitates a thorough understanding of the posterior abdominal wall and retroperitoneal anatomy. Proper patient selection, meticulous surgical planning, and adherence to key technical principles are paramount for successful outcomes. In this paper, the surgical technique is described step by step, emphasizing critical aspects such as patient positioning, trocar placement, and adrenal dissection. PRLA demonstrates reduced postoperative pain, shorter hospital stays, and faster recovery times compared to open surgery, while maintaining comparable oncological outcomes for appropriately selected cases. However, the technique presents unique challenges, including a confined working space and the need for surgeons to adapt to a posterior anatomical perspective. We conclude that PRLA, in the right clinical setting, offers a safe and effective alternative to traditional adrenalectomy approaches. Future research should focus on expanding indications and refining techniques to further improve patient outcomes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.