Evidence map›Paper›PMID 42376219›Full record

ArticleJournal of medical devices2026

Design of a Novel Insertion Training System for Central Venous Catheterization.

William Worrall, Jason Z Moore

Abstract read
In one paragraph

Article in Journal of medical devices, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

William WorrallDepartment of Mechanical Engineering, Pennsylvania State University, 318 Leonhard Building, University Park, PA 16802.
Jason Z MooreDepartment of Mechanical Engineering, Pennsylvania State University, 318 Leonhard Building, University Park, PA 16802.

Funding

Dynamic Haptic Robotic Training for Central Venous Catheter InsertionR01HL127316 · NHLBI · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI Scarlett Miller, Jason Zachary Moore · 2015 to 2026
$3.7M
NHLBI NIH HHS R01 HL127316
6 · The paper itself

Abstract

Central venous catheterization (CVC) is a common medical procedure with a complication rate of over 15%. Current CVC manikin-based simulators lack anatomical variation and objective feedback of user interaction skills, which greatly hinders effective skill acquisition. To address these limitations, a novel CVC insertion training system was developed and integrated with the Advanced Dynamic Haptic Robotic Trainer (DHRT+). This insertion training system contains a sensorized syringe, custom tissue phantom, and a tool detection subsystem, allowing residents to practice nearly the entire CVC procedure with realistic haptics and automated feedback on subcutaneous tool positioning. Five experiments were conducted to assess the haptic fidelity of the sensorized syringe and custom tissue and to evaluate the accuracy of subcutaneous tool detection. Results showed that the sensorized syringe, which detects aspiration and simulates arterial and venous flash, accurately reproduced clinical aspiration forces. The custom tissue phantom provided realistic force feedback during ultrasound (US) compression and needle insertion, comparable to that of commercial tissue phantoms at a substantially lower cost. The color sensors used to distinguish between inserted guidewires and catheters accurately verified tool depth and enabled tool insertion across multiple positions on the tissue surface. Overall, novel CVC insertion training system components were presented that enabled CVC simulation and provided accurate measurement on aspiration, guidewire depth, and catheter depth.

Indexed as

central venous catheterizationmedical trainingsensorized syringetissue phantom

Identifiers

PMID42376219
PMCPMC13313113

What OpenQuestion holds

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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.