Evidence map›Paper›PMID 30207946›Full record

ArticleIEEE transactions on bio-medical engineering2019

Suture Breakage Warning System for Robotic Surgery.

Ahmad Abiri, Syed J Askari, Anna Tao, Yen-Yi Juo, Yuan Dai, Jake Pensa, Robert Candler, Erik P Dutson, Warren S Grundfest

Abstract read
In one paragraph

Article in IEEE transactions on bio-medical engineering, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Tactile Feedback in Robot-Assisted Minimally Invasive Surgery: A Systematic Review.The international journal of medical robotics + computer assisted surgery : MRCAS · 2024
    Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Bio-Inspired Haptic Feedback for Artificial Palpation in Robotic Surgery.IEEE transactions on bio-medical engineering · 2021
    Article
  8. Article
  9. Article
  10. 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

9 authors.

Ahmad Abiri
Syed J Askari
Anna Tao
Yen-Yi Juo
Yuan Dai
Jake Pensa
Robert Candler
Erik P Dutson
Warren S Grundfest

Funding

Haptic Feedback for Robotic Surgery using bi-axial capacitive force sensorsR01EB019473 · NIBIB · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI DUTSON, ERIK, GRUNDFEST, WARREN S · 2014 to 2017
$1.3M
NIBIB NIH HHS R01 EB019473
6 · The paper itself

Abstract

As robotic surgery has increased in popularity, the lack of haptic feedback has become a growing issue due to the application of excessive forces that may lead to clinical problems such as intraoperative and postoperative suture breakage. Previous suture breakage warning systems have largely depended on visual and/or auditory feedback modalities, which have been shown to increase cognitive load and reduce operator performance. This work catalogues a new sensing technology and haptic feedback system (HFS) that can reduce instances of suture failure without negatively impacting performance outcomes including knot quality. Suture breakage is common in knot-tying as the pulling motion introduces prominent shear forces. A shear sensor mountable on the da Vinci robotic surgical system's Cadiere grasper detects forces that correlate to the suture's internal tension. HFS then provides vibration feedback to the operator as forces near a particular material's failure load. To validate the system, subjects tightened a total of four knots, two with the Haptic Feedback System (HFS) and two without feedback. The number of suture breakages were recorded and knot fidelity was evaluated by measuring knot slippage. Results showed that instances of suture failure were significantly reduced when HFS was enabled (p = 0.0078). Notably, knots tied with HFS also showed improved quality compared to those tied without feedback (p = 0.010). The results highlight the value of HFS in improving robotic procedure outcomes by reducing instances of suture failures, producing better knots, and reducing the need for corrective measures.

Indexed as

SuturesTensile StrengthEquipment DesignFeedbackHumansMaterials TestingRobotic Surgical ProceduresSuture TechniquesTask Performance and Analysis

Identifiers

PMID30207946
PMCPMC6494981

What OpenQuestion holds

Textmetadata
LicenceTDM
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.