ReviewCureus2026
Advances in Minimally Invasive General Surgery: A Narrative Review of Techniques, Technologies, and Patient Outcomes.
Review in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Minimally invasive general surgery (MIGS) encompasses a broad spectrum of contemporary operative techniques and technologies, including laparoscopy, robotic assistance, novel access approaches, advanced energy platforms, enhanced imaging, and emerging digital tools. This narrative review, conducted through a structured literature search of major medical databases, critically examines the evolution of these innovations and their impact on surgical practice, patient outcomes, and healthcare systems. Evidence from randomized controlled trials, meta-analyses, and large observational studies published over the past decade indicates that MIGS is generally associated with reduced postoperative morbidity, shorter hospital stay, reduced postoperative pain, faster functional recovery, improved cosmetic outcomes, and enhanced patient-reported quality of life compared with open surgery. However, important limitations persist, including heterogeneity in study design, limited long-term outcome data for emerging technologies, steep procedural learning curves, and disparities in global access. Particular emphasis is placed on the incorporation of artificial intelligence (AI), machine learning (ML), and simulation-based training, which hold the potential to enhance operative precision and accelerate skill acquisition but require rigorous validation and ethical oversight. Cost-effectiveness and international dissemination remain central concerns, underscoring the need for scalable innovations and standardized training models to achieve equitable adoption. Sustainable advancement in MIGS will depend on rigorous evidence generation, structured training pathways, cost-conscious implementation, and policies that promote equitable access across healthcare systems.
Indexed as
Identifiers
What Socratic 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 Socratic graph.