Evidence map›Paper›PMID 36849565›Full record

Trial reportSurgical endoscopy2023

3D liver model-based surgical education improves preoperative decision-making and patient satisfaction-a randomized pilot trial.

Esther Giehl-Brown, Sandra Dennler, Sebastián A Garcia, Danilo Seppelt, Florian Oehme, Johannes Schweipert, Jürgen Weitz, Carina Riediger

Abstract readRandomized Controlled TrialMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Surgical endoscopy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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

  1. Pooled it
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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

8 authors.

Esther Giehl-BrownDepartment of Visceral, Thoracic and Vascular Surgery, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
Sandra DennlerDepartment of Visceral, Thoracic and Vascular Surgery, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
Sebastián A GarciaDepartment of Visceral, Thoracic and Vascular Surgery, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
Danilo SeppeltDepartment of Radiology, University Hospital Carl Gustav Carus Dresden, Technische Universität Dresden, Dresden, Germany.
Florian OehmeDepartment of Visceral, Thoracic and Vascular Surgery, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
Johannes SchweipertDepartment of Visceral, Thoracic and Vascular Surgery, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
Jürgen WeitzDepartment of Visceral, Thoracic and Vascular Surgery, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.
Carina RiedigerDepartment of Visceral, Thoracic and Vascular Surgery, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany. carina.riediger@uniklinikum-dresden.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveHepatobiliary surgery bares obstacles to informed consent for the patients due to its complexity and related risk of postoperative complications. 3D visualization of the liver has been proven to facilitate comprehension of the spatial relationship between anatomical structures and to assist in clinical decision-making. Our objective is to utilize individual 3D-printed liver models to enhance patient satisfaction with surgical education in hepatobiliary surgery. DESIGN,

settingWe conducted a prospective, randomized pilot study comparing 3D liver model-enhanced (3D-LiMo) surgical education against regular patient education during preoperative consultation at the department of Visceral, Thoracic and Vascular Surgery, University Hospital Carl Gustav Carus, Dresden, Germany.

participantsOf 97 screened patients, undergoing hepatobiliary surgery, 40 patients were enrolled from July 2020 to January 2022.

resultsThe study population (n = 40) was predominantly of male gender (62.5%) with a median age of 65.2 years and a high prevalence of preexisting diseases. Underlying disease, warranting hepatobiliary surgery, was malignancy in the majority of cases (97.5%). Patients in the 3D-LiMo group were more likely to feel very thoroughly educated and exhibited a higher level of satisfaction following surgical education than the control group (80 vs. 55%, n.s.; 90 vs. 65%, n.s.; respectively). Applying 3D models was also associated with enhanced understanding of the underlying disease with regard to amount (100% vs. 70%, p = 0.020) and location of liver masses (95 vs. 65%, p = 0.044). 3D-LiMo patients also demonstrated enhanced understanding of the surgical procedure (80 vs. 55%, n.s.), leading to better awareness for the occurrence of postoperative complications (88.9, vs. 68.4%, p = 0.052). Adverse event profiles were similar.

conclusionIn conclusion, individual 3D-printed liver models increase patient satisfaction with surgical education and facilitate patients' understanding of the surgical procedure as well as awareness of postoperative complications. Therefore, the study protocol is feasible to apply to an adequately powered, multicenter, randomized clinical trial with minor modifications.

Indexed as

Patient SatisfactionPostoperative ComplicationsAgedHumansLiverMalePilot ProjectsPrinting, Three-DimensionalProspective StudiesDisease awarenessPreventive HealthcareSituational awarenessThree-dimensional printingThree-dimensional visualizationValidation research

Identifiers

PMID36849565
PMCPMC9970129

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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.