PubMed HealthSearch

PubMed · 42560067

Preoperative Proximal Migration of the Radial Head as an Independent Predictor of Suboptimal Outcomes After Osteochondral Autograft Transplantation for Capitellar Osteochondritis Dissecans: A Retrospective Cohort Study.

Abstract

BACKGROUND: Osteochondral autograft transplantation (OAT) is widely performed for capitellar osteochondritis dissecans (OCD). However, preoperative predictors of suboptimal postoperative outcomes remain unclear. PURPOSE/HYPOTHESIS: The authors aimed to evaluate clinical outcomes after OAT for capitellar OCD and identify preoperative risk factors associated with suboptimal outcomes. They hypothesized that radiographic indicators of disease severity, including preoperative proximal migration of the radial head, lesion size, and lateral wall disruption, would be associated with suboptimal postoperative clinical outcomes. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: The records of adolescent athletes who underwent OAT for capitellar OCD with a minimum 2-year follow-up were retrospectively reviewed. Clinical outcomes included elbow range of motion (ROM) and Timmerman-Andrews (T-A) score. A suboptimal outcome was defined as a postoperative T-A score <160. Preoperative radiographs were used to measure proximal migration of the radial head relative to the coronoid process, hypertrophy of the radial head, OCD lesion area, and a 5-grade lateral wall disruption classification; measurement reliability was assessed. Multivariate logistic regression analysis was performed to identify independent predictors of a suboptimal outcome, and receiver operating characteristic (ROC) curve analysis was used to determine the optimal cutoff value for proximal migration. RESULTS: A total of 69 elbows (mean age, 13.6 years; mean follow-up, 48 months) were included. ROM and T-A scores improved significantly after OAT, and all athletes returned to any sports. Of these, 50 elbows (72%) achieved good outcomes, whereas 19 (28%) had suboptimal outcomes. Preoperative proximal migration was significantly greater in the suboptimal outcome group compared with the good outcome group (mean, 2.1 &#xb1; 2.3 vs 0.5 &#xb1; 1.7 mm; P = .002), as were lesion area (mean, 70 &#xb1; 16 vs 58 &#xb1; 20 mm2; P = .02) and lateral wall disruption grade (median, 5 vs 3; P = .01). On multivariate analysis, proximal migration of the radial head was the only independent predictor of a suboptimal outcome (adjusted OR, 1.47 per 1-mm increase; 95% CI, 1.03-2.09; P = .033). ROC analysis showed an area under the curve of 0.72 with an optimal cutoff of 2.2 mm (sensitivity, 56%; specificity, 84%). CONCLUSION: OAT resulted in significant clinical improvement in adolescents with capitellar OCD; however, 28% of patients were classified as having suboptimal outcomes. Preoperative proximal migration of the radial head is an independent predictor of a suboptimal postoperative outcome. A value >2.2 mm may indicate advanced radiocapitellar incongruity, a condition in which OAT may be less effective.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Hideki Kamijo, Norimasa Takahashi, Keisuke Matsuki, Daisuke Ishii, Taro Akiyama, Hiroyuki Sugaya, Itaru Kawashima. 2026-08-06. Preoperative Proximal Migration of the Radial Head as an Independent Predictor of Suboptimal Outcomes After Osteochondral Autograft Transplantation for Capitellar Osteochondritis Dissecans: A Retrospective Cohort Study.. https://doi.org/10.1177/03635465261469691

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans