Evidence map›Paper›PMID 35615077›Full record

ArticleAdvances in urology2022

Role and Utility of Mixed Reality Technology in Laparoscopic Partial Nephrectomy: Outcomes of a Prospective RCT Using an Indigenously Developed Software.

Nariman Gadzhiev, Igor Semeniakin, Aleksandr Morshnev, Antonio Alcaraz, Vineet Gauhar, Zhamshid Okhunov

Open access · goldAbstract read
In one paragraph

Article in Advances in urology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 3 pooled it
1.7field-weighted citation impact, top 15% 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

9 citing papers in PubMed, 3 syntheses or guidelines pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Visual extended reality tools in image-guided surgery in urology: a systematic review.European journal of nuclear medicine and molecular imaging · 2024
    Pooled it
  3. Pooled it
  4. Article
  5. Review
  6. Article
  7. Article
  8. Review
  9. HoloLensTherapeutic advances in urology
    Review
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

6 authors at 6 institutions in 4 countries.

Nariman GadzhievDepartment of Urology, Saint Petersburg State University Hospital, Saint Petersburg, Russia.ORCID https://orcid.org/0000-0002-6255-0193
Igor SemeniakinDepartment of Urology, A. I. Yevdokimov Moscow State University of Medicine and Dentistry, Moscow, Russia.ORCID https://orcid.org/0000-0003-3246-7337
Aleksandr MorshnevBauman Moscow State Technical University, Moscow, Russia.ORCID https://orcid.org/0000-0003-2792-0432
Antonio AlcarazDepartment of Urology, Hospital Clinic, Barcelona, Spain.ORCID https://orcid.org/0000-0003-2612-5250
Vineet GauharDepartment of Urology, Ng Teng Fong General Hospital (NTFGH), Singapore.ORCID https://orcid.org/0000-0002-3740-7141
Zhamshid OkhunovDepartment of Urology, University of California, Irvine, CA, USA.ORCID https://orcid.org/0000-0001-8294-933X
Bauman Moscow State Technical University · RUHospital Clínic de Barcelona · ESMoscow State University of Medicine and Dentistry · RUNg Teng Fong General Hospital · SGSt Petersburg University · RUUniversity of California, Irvine · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To develop a software for mixed reality (MR) anatomical model creation and study its intraoperative clinical utility to facilitate laparoscopic partial nephrectomy. Materials and Methods: After institutional review board approval, 47 patients were prospectively randomized for LPN into two groups: the control group (24 patients) underwent operation with an intraoperative ultrasound (US) control and the experimental group (23 patients) with smart glasses HoloLens 2 (Microsoft, Seattle, WA, USA). Our team has developed an open-source software package called "HLOIA," utilization of which allowed to create and use during surgery the MR anatomical model of the kidney with its vascular pedicle and tumor. The study period extended from June 2020 to February 2021 where demographic, perioperative, and pathological data were collected for all qualifying patients. The objective was to assess the utility of a MR model during LPN and through a 5-point Likert scale questionnaire, completed by the surgeon, immediately after LPN. Patient characteristics were tested using the chi-square test for categorical variables and Student's Results: Comparison of the variables between the groups revealed statistically significant differences only in the following parameters: the time for renal pedicle exposure and the time from the renal pedicle to the detection of tumor localization ( Conclusions: Developed open-source software "HLOIA" allowed to create the mixed reality anatomical model by operating urologist which is when used with smart glasses has shown improvement in terms of time for renal pedicle exposure and time for renal tumor identification without compromising safety.

Identifiers

PMID35615077
PMCPMC9126718
OpenAlexW4280646370

What OpenQuestion holds

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LicenceCC BY
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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.