Evidence map›Paper›PMID 33681506›Full record

ArticleJournal of medical robotics research

Extracting Subtask-specific Metrics Toward Objective Assessment of Needle Insertion Skill for Hemodialysis Cannulation.

Ziyang Zhang, Zhanhe Liu, Ravikiran Singapogu

Open access · greenAbstract read
In one paragraph

Article in Journal of medical robotics research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.3field-weighted citation impact, top 11% 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

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Simulator-Based Metrics for Quantifying Vascular Palpation Skill for Cannulation.IEEE access : practical innovations, open solutions · 2022
    Article
  4. Article
  5. 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

3 authors at 1 institution in 1 country.

Ziyang ZhangDepartment of Bioengineering, Clemson University, 301 Rhodes Research Center, Clemson, SC 29634, USA.
Zhanhe LiuDepartment of Bioengineering, Clemson University, 301 Rhodes Research Center, Clemson, SC 29634, USA.
Ravikiran SingapoguDepartment of Bioengineering, Clemson University, 301 Rhodes Research Center, Clemson, SC 29634, USA.
Clemson University · US

Funding

CanSim: A novel simulator for training cannulation skills in dialysis careK01DK111767 · NIDDK · CLEMSON UNIVERSITY · PI SINGAPOGU, RAVIKIRAN · 2016 to 2020
$660k
NIDDK NIH HHS K01 DK111767
6 · The paper itself

Abstract

About 80% of all in-hospital patients require vascular access cannulation for treatments. However, there is a high rate of failure for vascular access cannulation, with several studies estimating up to a 50% failure rate for these procedures. Hemodialysis cannulation (HDC) is arguably one of the most difficult of these procedures with a steep learning curve and an extremely high failure rate. In light of this, there is a critical need that clinicians performing HDC have requisite skills. In this work, we present a method that combines the strengths of simulator-based objective skill quantification and task segmentation for needle insertion skill assessment at the subtask level. The results from our experimental study with seven novice nursing students on the cannulation simulator demonstrate that the simulator was able to segment needle insertion into subtask phases. In addition, most metrics were significantly different between the two phases, indicating that there may be value in evaluating participants' behavior at the subtask level. Further, the outcome metric (risk of infiltrating the simulated blood vessel) was successfully predicted by the process metrics in both phases. The implications of these results for skill assessment and training are discussed, which could potentially lead to improved patient outcomes if more extensive validation is pursued.

Indexed as

hemodialysis cannulationmedical training simulatorskill assessmentVascular access

Identifiers

PMID33681506
PMCPMC7932179
OpenAlexW3003697434

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.