Evidence map›Paper›PMID 38918593›Full record

ArticleScientific reports2024

Prediction of Robotic Anastomosis Competency Evaluation (RACE) metrics during vesico-urethral anastomosis using electroencephalography, eye-tracking, and machine learning.

Somayeh B Shafiei, Saeed Shadpour, James L Mohler, Parisa Rashidi, Mehdi Seilanian Toussi, Qian Liu, Ambreen Shafqat, Camille Gutierrez

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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.

Somayeh B ShafieiIntelligent Cancer Care Laboratory, Department of Urology, Roswell Park Comprehensive Cancer Center, Elm and Carlton Streets, Buffalo, NY, 14263, USA. Somayeh.besharatshafiei@roswellpark.org.ORCID 0000-0002-9256-6284
Saeed ShadpourDepartment of Animal Biosciences, University of Guelph, Guelph, ON, N1G 2W1, Canada.ORCID 0000-0002-2842-031X
James L MohlerDepartment of Urology, Roswell Park Comprehensive Cancer Center, Buffalo, NY, 14263, USA.
Parisa RashidiDepartment of Biomedical Engineering, University of Florida, Gainesville, FL, 32611, USA.
Mehdi Seilanian ToussiIntelligent Cancer Care Laboratory, Department of Urology, Roswell Park Comprehensive Cancer Center, Elm and Carlton Streets, Buffalo, NY, 14263, USA.
Qian LiuDepartment of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA.
Ambreen ShafqatIntelligent Cancer Care Laboratory, Department of Urology, Roswell Park Comprehensive Cancer Center, Elm and Carlton Streets, Buffalo, NY, 14263, USA.
Camille GutierrezObstetrics and Gynecology Residency Program, Sisters of Charity Health System, Buffalo, NY, 14214, USA.

Funding

Two-Spirit Films in Indigenous Cancer HealthP30CA016056 · NCI · ROSWELL PARK CANCER INSTITUTE CORP · PI Dean G. Tang · 1985 to 2026
$116.6M
Synchronized brain dynamics and eye movement trajectory for objective evaluation of robot-assisted surgical skillsR01EB029398 · NIBIB · ROSWELL PARK CANCER INSTITUTE CORP · PI BESHARAT SHAFIEI, SOMAYEH · 2020 to 2023
$1.9M
Division of Cancer Prevention, National Cancer Institute P30CA016056NCI NIH HHS P30 CA016056NIBIB NIH HHS R01 EB029398NIBIB NIH HHS R01EB029398
6 · The paper itself

Abstract

Residents learn the vesico-urethral anastomosis (VUA), a key step in robot-assisted radical prostatectomy (RARP), early in their training. VUA assessment and training significantly impact patient outcomes and have high educational value. This study aimed to develop objective prediction models for the Robotic Anastomosis Competency Evaluation (RACE) metrics using electroencephalogram (EEG) and eye-tracking data. Data were recorded from 23 participants performing robot-assisted VUA (henceforth 'anastomosis') on plastic models and animal tissue using the da Vinci surgical robot. EEG and eye-tracking features were extracted, and participants' anastomosis subtask performance was assessed by three raters using the RACE tool and operative videos. Random forest regression (RFR) and gradient boosting regression (GBR) models were developed to predict RACE scores using extracted features, while linear mixed models (LMM) identified associations between features and RACE scores. Overall performance scores significantly differed among inexperienced, competent, and experienced skill levels (P value < 0.0001). For plastic anastomoses, R

Indexed as

Anastomosis, SurgicalClinical CompetenceElectroencephalographyMachine LearningRobotic Surgical ProceduresUrethraEye-Tracking TechnologyHumansMaleProstatectomyUrinary BladderQuantitative assessmentRadical prostatectomySurgical performanceVesico-urethral anastomosis

Identifiers

PMID38918593
PMCPMC11199555

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LicenceCC BY
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Registered trials

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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.