Evidence map›Paper›PMID 39189555›Full record

Observational studyJoint diseases and related surgery2024

A comparison between 3D printed models and standard 2D planning in the use of metal block augments in revision knee arthroplasty.

Giovanni Balato, Vincenzo De Matteo, Amedeo Guarino, Domenico De Mauro, Dario Baldi, Carlo Cavaliere, Marco Salvatore, Mustafa Citak, Massimo Mariconda

Abstract readComparative StudyObservational Study
In one paragraph

Observational study in Joint diseases and related surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Giovanni Balato
Vincenzo De MatteoUnit of Orthopaedic Surgery, Department of Public Health, School of Medicine, Federico II University, Naples, Italy. vincenzo.dematteo@unina.it.
Amedeo Guarino
Domenico De Mauro
Dario Baldi
Carlo Cavaliere
Marco Salvatore
Mustafa Citak
Massimo Mariconda

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe study focused on the ability to predict the need and size of femoral and tibial augmentation using standard two-dimensional (2D) templates and models created with three-dimensional (3D) printing in surgical planning. PATIENTS AND

methodsThis observational cohort study included 28 consecutive patients (22 females, 6 males; mean age: 71±7.3 years; range, 54 to 82 years) with periprosthetic joint infection recruited between March 2021 and September 2023 undergoing revision total knee arthroplasty revision (TKA). Standard planning was made using calibrated X-ray images. The 3D planning started with computed tomography scans to generate a 3D template of the distal femur and proximal tibia. The model was exported to a 3D printer to produce a patient-specific phantom. The surgery was then simulated on the 3D phantom using revision knee arthroplasty instrumentation to evaluate the appropriate augmentation to use until a correct alignment was obtained.

resultsThree-dimensional planning predicted the need for femoral and tibial augments in 22 (78.6%) cases at both the tibial and femoral components, while 2D planning correctly predicted the need for augmentation in 17 (60.7%) for the tibial side and 18 (64.3%) for the femoral side. The Cohen's kappa demonstrated a significant agreement between the 3D planning for the femoral metal block and the intraoperative requirement (kappa=0.553), whereas 2D planning showed only nonsignificant poor agreement (kappa=0.083). In contrast, the agreement between 2D or 3D preoperative planning for tibial augment and the intraoperative requirement was nonsignificant (kappa=0.130 and kappa=0.158, respectively). On the femoral side, 2D planning showed only a fair nonsignificant correlation (r=0.35, p=0.069), whereas 3D planning exhibited substantial agreement with the actual thickness of the implanted augment (r=0.65, p<0.001). On the tibial side, 3D and 2D planning showed substantial agreement with the actual size of implanted augments (3D planning, r=0.73, p<0.001; 2D planning, r=0.69, p<0.001).

conclusionPrediction based on 3D computed tomography segmentation showed significant agreement with the intraoperative need for augmentations in revision TKA. The results suggest that planning with 3D printed models represents a stronger aid in this kind of surgery rather than standard 2D planning, providing greater accuracy in the prediction of the required augmentation in revision TKA.

Indexed as

Arthroplasty, Replacement, KneeKnee ProsthesisPrinting, Three-DimensionalReoperationAgedAged, 80 and overFemaleFemurHumansMaleMiddle AgedProsthesis DesignProsthesis-Related InfectionsTibiaTomography, X-Ray Computed

Identifiers

PMID39189555
PMCPMC11411891

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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.