ReviewCureus2024
A Comprehensive Analysis of Single-Incision Laparoscopic Cholecystectomy: Trends, Challenges, and Future Directions.
Review in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 7 citations in OpenAlex.
- Automated surgical phase recognition and analysis in single-incision laparoscopic cholecystectomy using artificial intelligence.Surgical endoscopy · 2026Article
- A comparative study of 2908 cases of transumbilical single-incision laparoscopic cholecystectomy versus 1952 cases of traditional three-incision laparoscopic cholecystectomy in a single center.Surgical endoscopy · 2026Article
- Advances in Minimally Invasive General Surgery: A Narrative Review of Techniques, Technologies, and Patient Outcomes.Cureus · 2026Review
- Two-point lifting/retracting technology for transumbilical single-port laparoscopic cholecystectomy based on the anatomical features of Calot's triangle.World journal of gastrointestinal surgery · 2025Article
- Review
- The efficacy and safety of single-incision plus one-port laparoscopic surgeryGland surgery · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 7 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single-incision laparoscopic cholecystectomy (SILC) is a minimally invasive surgical technique introduced as an advancement to laparoscopic cholecystectomy (LC). This narrative review delves into the emergence of SILC, emphasizing its distinct advantages such as improved cosmesis, reduced postoperative pain, and potentially faster recovery compared to traditional LC. The study meticulously examines current trends and challenges in SILC, including variations in techniques and their impact on patient outcomes. Furthermore, the article sheds light on the technical intricacies and longer operative times associated with SILC. It aims to contribute valuable insights to the medical community by synthesizing existing literature and recent research findings, fostering a deeper understanding of SILC, and guiding future advancements in minimally invasive surgical approaches. The discussion extends to the learning curve, complications, and a comparative analysis between SILC and traditional LC, offering a nuanced understanding of their respective strengths and limitations. The article concludes with a forward-looking perspective, exploring future directions and innovations in SILC, including advancements in surgical techniques and the integration of innovative technologies, such as robotic assistance and in vivo robots, to enhance precision and efficacy. The call for continued research into the long-term outcomes, safety, and refined patient selection criteria emphasizes the evolving landscape of SILC and its potential to shape the future of minimally invasive abdominal surgeries.
Indexed as
Identifiers
What OpenQuestion holds
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.