Evidence map›Paper›PMID 35955377›Full record

ArticleMaterials (Basel, Switzerland)2022

A Clinical Risk Assessment of a 3D-Printed Patient-Specific Scaffold by Failure Modes and Effects Analysis.

Ping Qi Lim, Sue Huey Lim, Maria Sherilyn, Tulio Fernandez-Medina, Sašo Ivanovski, Sepanta Hosseinpour

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Ping Qi LimSchool of Dentistry, The University of Queensland, Brisbane 4006, Australia.
Sue Huey LimSchool of Dentistry, The University of Queensland, Brisbane 4006, Australia.
Maria SherilynSchool of Dentistry, The University of Queensland, Brisbane 4006, Australia.
Tulio Fernandez-MedinaSchool of Dentistry, The University of Queensland, Brisbane 4006, Australia.
Sašo IvanovskiSchool of Dentistry, The University of Queensland, Brisbane 4006, Australia.ORCID 0000-0001-5339-0936
Sepanta HosseinpourSchool of Dentistry, The University of Queensland, Brisbane 4006, Australia.ORCID 0000-0002-6503-4223

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims to carry out a risk assessment to identify and rectify potential clinical risks of a 3D-printed patient-specific scaffold for large-volume alveolar bone regeneration. A survey was used to assess clinicians' perceptions regarding the use of scaffolds in the treatment of alveolar defects and conduct a clinical risk assessment of the developed scaffold using the Failure Modes and Effects Analysis (FMEA) framework. The response rate was 69.4% with a total of 41 responses received. Two particular failure modes were identified as a high priority through the clinical risk assessment conducted. The highest mean Risk Priority Number was obtained by "failure of healing due to patient risk factors" (45.7 ± 27.7), followed by "insufficient soft tissue area" (37.8 ± 24.1). Despite the rapid developments, finding a scaffold that is both biodegradable and tailored to the patient's specific defect in cases of large-volume bone regeneration is still challenging for clinicians. Our results indicate a positive perception of clinicians towards this novel scaffold. The FMEA clinical risk assessment has revealed two failure modes that should be prioritized for risk mitigation (safe clinical translation). These findings are important for the safe transition to in-human trials and subsequent clinical use.

Indexed as

additive manufacturingalveolar bone graftingbone substitutesFMEAguided tissue regenerationrisk analysisscaffold

Identifiers

PMID35955377
PMCPMC9369557

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.