Evidence map›Paper›PMID 37621804›Full record

ReviewCureus2023

Robotic Surgery: A Comprehensive Review of the Literature and Current Trends.

Yeisson Rivero-Moreno, Sophia Echevarria, Carlos Vidal-Valderrama, Luigi Pianetti, Jesus Cordova-Guilarte, Jhon Navarro-Gonzalez, Jessica Acevedo-Rodríguez, Gabriela Dorado-Avila, Luisa Osorio-Romero, Carmen Chavez-Campos and 1 more

Abstract readReview
In one paragraph

Review in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 133 papers, 10 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
133citing papers in PubMed, 10 pooled it
–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

133 citing papers in PubMed, 10 syntheses or guidelines pooled it.

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  10. Clear Vision, Clear Savings: Enhancing Efficiency in Minimally Invasive Surgery.JSLS : Journal of the Society of Laparoendoscopic Surgeons
    Pooled it
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73 more citing papers are in PubMed but not listed here.

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

11 authors.

Yeisson Rivero-MorenoGeneral Surgery, Universidad de Oriente, Barcelona, VEN.
Sophia EchevarriaGeneral Surgery, Universidad Mayor de San Simón, Cochabamba, BOL.
Carlos Vidal-ValderramaGeneral Surgery, Universidad Autónoma de Baja California, Baja California, MEX.
Luigi PianettiGeneral Surgery, Universidad Nacional del Litoral, Argentina, ARG.
Jesus Cordova-GuilarteGeneral Surgery, Universidad de Oriente, Barcelona, VEN.
Jhon Navarro-GonzalezGeneral Surgery, Universidad del Zulia, Maracaibo, VEN.
Jessica Acevedo-RodríguezGeneral Surgery, Tecnológico de Monterrey, Monterrey, MEX.
Gabriela Dorado-AvilaGeneral Surgery, Universidad Mayor de San Simón, Cochabamba, BOL.
Luisa Osorio-RomeroGeneral Surgery, Universidad Industrial de Santander, Colombia, COL.
Carmen Chavez-CamposGeneral Surgery, Universidad Peruana de Ciencias Aplicadas, Lima, PER.
Katheryn Acero-AlvarracínGeneral Surgery, Universidad de Guayaquil Facultad de Ciencias Médicas, Guayaquil, ECU.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Robotic surgery (RS) is an evolution of minimally invasive surgery that combines medical science, robotics, and engineering. The first robots approved by the Food and Drug Administration (FDA) were the Da Vinci Surgical System and the ZEUS Robotic Surgical System, which have been improving over time. Through the decades, the equipment applied to RS had undergone a wide transformation as a response to the development of new techniques and facilities for the assembly and implementation of the own. RS has revolutionized the field of urology, enabling surgeons to perform complex procedures with greater precision and accuracy, and many other surgical specialties such as gynecology, general surgery, otolaryngology, cardiothoracic surgery, and neurosurgery. Several benefits, such as a better approach to the surgical site, a three-dimensional image that improves depth perception, and smaller scars, enhance range of motion, allowing the surgeon to conduct more complicated surgical operations, and reduced postoperative complications have made robotic-assisted surgery an increasingly popular approach. However, some points like the cost of surgical procedures, equipment-instrument, and maintenance are important aspects to consider. Machine learning will likely have a role to play in surgical training shortly through "automated performance metrics," where algorithms observe and "learn" individual surgeons' techniques, assess performance, and anticipate surgical outcomes with the potential to individualize surgical training and aid decision-making in real time.

Indexed as

da vinci surgical systemminimally invasive surgical proceduresrobot-enhanced surgeryrobotic-assisted surgeryurology

Identifiers

PMID37621804
PMCPMC10445506

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.