Evidence map›Paper›PMID 35066636›Full record

ArticleWorld journal of urology2022

Utilizing head-mounted eye trackers to analyze patterns and decision-making strategies of 3D virtual modelling platform (IRIS

Rachel Melnyk, Yuxin Chen, Tyler Holler, Nathan Schuler, Patrick Saba, Scott Quarrier, Jonathan Bloom, William Tabayoyong, Thomas Frye, Hani Rashid and 2 more

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Article in World journal of urology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.7field-weighted citation impact, top 17% of its field
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

4 citing papers in PubMed, 9 citations in OpenAlex.

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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

12 authors at 1 institution in 1 country.

Rachel MelnykSimulation Innovation Lab, University of Rochester Medical Center (URMC), 601 Elmwood Ave, Rochester, NY, USA. ahmed_ghazi@urmc.rochester.edu.ORCID http://orcid.org/0000-0003-4894-6789
Yuxin ChenSimulation Innovation Lab, University of Rochester Medical Center (URMC), 601 Elmwood Ave, Rochester, NY, USA.
Tyler HollerSimulation Innovation Lab, University of Rochester Medical Center (URMC), 601 Elmwood Ave, Rochester, NY, USA.
Nathan SchulerSimulation Innovation Lab, University of Rochester Medical Center (URMC), 601 Elmwood Ave, Rochester, NY, USA.
Patrick SabaSimulation Innovation Lab, University of Rochester Medical Center (URMC), 601 Elmwood Ave, Rochester, NY, USA.
Scott QuarrierDepartment of Urology, URMC, Rochester, NY, USA.
Jonathan BloomDepartment of Urology, URMC, Rochester, NY, USA.
William TabayoyongDepartment of Urology, URMC, Rochester, NY, USA.
Thomas FryeDepartment of Urology, URMC, Rochester, NY, USA.
Hani RashidDepartment of Urology, URMC, Rochester, NY, USA.
Jean JosephDepartment of Urology, URMC, Rochester, NY, USA.
Ahmed GhaziSimulation Innovation Lab, University of Rochester Medical Center (URMC), 601 Elmwood Ave, Rochester, NY, USA.
University of Rochester Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeIRIS

methodsSeven surgeons randomly reviewed IRIS and CT images of 9 patients with renal masses [5 high complexity (RENAL score ≥ 8), 4 low complexity (≤ 7)]. Surgeons answered a series of questions regarding patient anatomy, perceived difficulty (/100), confidence (/100), and surgical plan. Eye tracking metrics (mean pupil diameter, number of fixations, and gaze duration) were collected.

resultsSurgeons spent significantly less time interpreting data from IRIS than CT scans (- 67.1 s, p < 0.01) and had higher inter-rater agreement of surgical approach after viewing IRIS (α = 0.16-0.34). After viewing IRIS, surgical plans although not statistically significant demonstrated a greater tendency towards a more selective ischemia approaches which positively correlated with improved identification of vascular anatomy. Planned surgical approach changed in 22/59 of the cases. Compared to viewing the CT scan, left and right mean pupil diameter and number/duration of fixations were significantly lower when using IRIS (p < 0.01, p < 0.01, p = 0.42, p < 0.01, respectively), indicating interpreting information from IRIS required less mental effort despite under-utilizing its interactive features.

conclusionsSurgeons extrapolated more detailed information in less time with less mental effort using IRIS than CT scans and proposed surgical approaches with potential to enhanced surgical outcomes.

Indexed as

Kidney NeoplasmsSurgeonsHumansImaging, Three-DimensionalKidneyNephrectomyTomography, X-Ray Computed3D modelingAnatomic visualizationPartial nephrectomyRadical nephrectomyRobotic surgerySimulation

Identifiers

PMID35066636
OpenAlexW4207004289

What OpenQuestion 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 OpenQuestion graph.