ArticleAdvances in orthopedics2022
3D-Printed Models versus CT Scan and X-Rays Imaging in the Diagnostic Evaluation of Proximal Humerus Fractures: A Triple-Blind Interobserver Reliability Comparison Study.
Article in Advances in orthopedics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed, 7 citations in OpenAlex.
- A Comprehensive Review of 3D Imaging and Printing in Proximal Humerus Fractures and Sequelae.Journal of clinical medicine · 2025Review
- The Novel Impact of Augmented Reality and 3D Printing in the Diagnosis of Complex Acetabular Fractures: A Comparative Randomized Study in Orthopedic Residents.Journal of clinical medicine · 2024Article
- Computed Tomography Does Not Improve Intra- and Interobserver Agreement of Hertel Radiographic Prognostic Criteria.Medicina (Kaunas, Lithuania) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Proximal humerus fractures (PHFs) are one of the most frequent fractures in the elderly and are the third most fractures after those of the hip and wrist. PHFs are assessed clinically through conventionally standard imaging (X-ray and computed tomography (CT) scans). The present study aims to conduct the diagnostic evaluation and therapeutic efficacy of the 3D-printed models (3DPMs) for the PHFs, compared with the standard imaging. Objectives: In terms of fracture classification and surgical indication, PHFs have poor interobserver agreement between orthopedic surgeons using traditional imaging such as X-rays and CT scan. Our objective is to compare interobserver reliability in diagnostic evaluation of PHFs using 3DPMs compared to traditional imaging. Methods: The inclusion criteria were elders aged >65 years, fracture classification AO/OTA 11 B and 11 C, and no pathological fractures or polytrauma. In addition, 9 PHFs were assessed by 6 evaluators through a questionnaire and double-blinded administered for each imaging (X-ray and CT scan) and 3DPMs for each fracture. The questionnaire for each method regarded Neer classification, Hertel classification, treatment indication (IT), and surgical technique (ST). Interobserver reliability was calculated through the intraclass correlation coefficient (ICC). Results: Nine patients with PHF were included in the study (66% female). The Neer and Hertel classifications between imaging types had similar ICC values between raters with no statistical differences. IT reliability using CT scan and 3DPMs (ICC = 1; ( Conclusion: Classification systems like Neer and Hertel offer poor reliability between operators. The 3DPMs for evaluating diagnostics are comparable to CT images but superior to the surgical technique agreement. The application of 3DPMs is effective for preoperative fracture planning and the modeling of patient-specific hardware.
Identifiers
What OpenQuestion holds
Registered trials
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.