Evidence map›Paper›PMID 40666161›Full record

SynthesisJSLS : Journal of the Society of Laparoendoscopic Surgeons

Clear Vision, Clear Savings: Enhancing Efficiency in Minimally Invasive Surgery.

Juslyn Dhingra, Noah Beinart, Abraar Ahmed, Mansi Patel, Aysha Ameerah, Maansi Srinivasan, Christopher R Idelson, John M Uecker

Abstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in JSLS : Journal of the Society of Laparoendoscopic Surgeons. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Juslyn DhingraThe College of Natural Sciences, The University of Texas at Austin, Austin, TX, USA. (Ms. Dhingra, Ms. Patel, Mr. Ahmed, and Ms. Ameerah).
Noah BeinartThe McCombs School of Business, The University of Texas at Austin, Austin, TX, USA. (Mr. Beinart).
Abraar AhmedThe College of Natural Sciences, The University of Texas at Austin, Austin, TX, USA. (Ms. Dhingra, Ms. Patel, Mr. Ahmed, and Ms. Ameerah).
Mansi PatelThe College of Natural Sciences, The University of Texas at Austin, Austin, TX, USA. (Ms. Dhingra, Ms. Patel, Mr. Ahmed, and Ms. Ameerah).
Aysha AmeerahThe College of Natural Sciences, The University of Texas at Austin, Austin, TX, USA. (Ms. Dhingra, Ms. Patel, Mr. Ahmed, and Ms. Ameerah).
Maansi SrinivasanClearCam Inc, Austin, TX, USA. (Ms. Srinivasan, Dr. Idelson, and Dr. Uecker).
Christopher R IdelsonClearCam Inc, Austin, TX, USA. (Ms. Srinivasan, Dr. Idelson, and Dr. Uecker).
John M UeckerClearCam Inc, Austin, TX, USA. (Ms. Srinivasan, Dr. Idelson, and Dr. Uecker).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objectives: Minimally invasive surgery (MIS) offers faster recovery and smaller incisions but is limited by persistent visualization issues such as lens fogging, debris, and camera instability. These challenges compromise surgical performance, increase complications, and elevate healthcare costs. This review evaluates the clinical and economic impact of suboptimal visualization in MIS and explores potential solutions. Methods: A systematic review was conducted using peer-reviewed literature from January 1990 to August 2024. Studies included those examining visualization challenges in laparoscopic and robotic MIS, clinical outcomes, surgeon-reported frustrations, and cost analyses. Exclusion criteria included studies with significant conflicts of interest, especially those funded by medical device companies. Results: Surgeons spend an estimated 40% of MIS operating time under suboptimal visual conditions, contributing to nearly 20% of surgical complications. Lens cleaning adds $132-$493 per procedure, averaging $312.53 based on 9.7 cleaning events per case. Visualization-related complications contribute an additional $251 per case. Combined, these issues result in over $2.2 billion in annual costs in the U.S. Poor visualization also disrupts workflow, increases surgeon fatigue, and hinders integration of emerging technologies such as artificial intelligence (AI). Conclusions: Suboptimal visualization in MIS stands to significantly affect patient safety and healthcare costs. Addressing these challenges through standardized cleaning protocols, improved surgeon training, and adoption of advanced technologies-including AI-driven imaging-is essential. Enhancing visualization is not just a technical upgrade but a critical step toward safer, more efficient, and cost-effective surgical care.

Indexed as

LaparoscopyMinimally Invasive Surgical ProceduresRobotic Surgical ProceduresHealth Care CostsHumansOperative TimePostoperative ComplicationsArtificial intelligenceEconomic impactMinimally invasive surgeryPatient safetySuboptimal visualizationWorkflow efficiency

Identifiers

PMID40666161
PMCPMC12257872

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.