Evidence map›Paper›PMID 30649650›Full record

Article3D printing in medicine2018

3D printing for congenital heart disease: a single site's initial three-yearexperience.

Justin Ryan, Jonathan Plasencia, Randy Richardson, Daniel Velez, John J Nigro, Stephen Pophal, David Frakes

Abstract read
In one paragraph

Article in 3D printing in medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 1 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

37 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  20. Impact of multi-lattice inner structures on FDM PLA 3D printed orthosis using Industry 4.0 concepts.International journal on interactive design and manufacturing · 2023
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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

7 authors.

Justin RyanRady Children's Hospital-San Diego, San Diego, CA, USA. jryan2@rchsd.org.ORCID http://orcid.org/0000-0002-5432-1817
Jonathan PlasenciaPhoenix Children's Hospital, Phoenix, AZ, USA.
Randy RichardsonSt. Joseph's Hospital and Medical Center, Phoenix, AZ, USA.
Daniel VelezPhoenix Children's Hospital, Phoenix, AZ, USA.
John J NigroRady Children's Hospital-San Diego, San Diego, CA, USA.
Stephen PophalPhoenix Children's Hospital, Phoenix, AZ, USA.
David FrakesArizona State University, Tempe, AZ, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

background3D printing is an ideal manufacturing process for creating patient-matched models (anatomical models) for surgical and interventional planning. Cardiac anatomical models have been described in numerous case studies and journal publications. However, few studies attempt to describe wider impact of the novel planning augmentation tool. The work here presents the evolution of an institution's first 3 full years of 3D prints following consistent integration of the technology into clinical workflow (2012-2014) - a center which produced 79 models for surgical planning (within that time frame). Patient outcomes and technology acceptance following implementation of 3D printing were reviewed.

methodsA retrospective analysis was designed to investigate the anatomical model's impact on time-based surgical metrics. A contemporaneous cohort of standard-of-care pre-procedural planning (no anatomical models) was identified for comparative analysis. A post-surgery technology acceptance assessment was also employed in a smaller subset to measure perceived efficacy of the anatomical models. The data was examined.

resultsWithin the timeframe of the study, 928 primary-case cardiothoracic surgeries (encompassing both CHD and non-CHD surgeries) took place at the practicing pediatric hospital. One hundred sixty four anatomical models had been generated for various purposes. An inclusion criterion based on lesion type limited those with anatomic models to 33; there were 113 cases matching the same criterion that received no anatomical model. Time-based metrics such as case length-of-time showed a mean reduction in overall time for anatomical models. These reductions were not statistically significant. The technology acceptance survey did demonstrate strong perceived efficacy. Anecdotal vignettes further support the technology acceptance. DISCUSSION &

conclusionThe anatomical models demonstrate trends for reduced operating room and case length of time when compared with similar surgeries in the same time-period; in turn, these reductions could have significant impact on patient outcomes and operating room economics. While analysis did not yield robust statistical powering, strong Cohen's d values suggest poor powering may be more related to sample size than non-ideal outcomes. The utility of planning with an anatomical model is further supported by the technology acceptance study which demonstrated that surgeons perceive the anatomical models to be an effective tool in surgical planning for a complex CHD repair. A prospective multi-center trial is currently in progress to further validate or reject these findings.

Indexed as

3D printingCongenital heart diseasePatient outcomesRetrospective chart review

Identifiers

PMID30649650
PMCPMC6223396

What OpenQuestion holds

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LicenceCC BY
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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.