Data-Driven Approach to Development of a Risk Score for Periprosthetic Joint Infections in Total Joint Arthroplasty Using Electronic Health Records.

Background: Periprosthetic joint infection (PJI) is an uncommon, but serious complication in total joint arthroplasty. Personalized risk prediction and risk factor management may allow better preoperative assessment and improved outcomes. We evaluated different data-driven approaches to develop surgery-specific PJI prediction models using large-scale data from the electronic health records (EHRs).

Uncertainty-Aware Deep Learning Characterization of Knee Radiographs for Large-Scale Registry Creation.

Background: We present an automated image ingestion pipeline for a knee radiography registry, integrating a multilabel image-semantic classifier with conformal prediction-based uncertainty quantification and an object detection model for knee hardware.

Methods: Annotators retrospectively classified 26,000 knee images detailing presence, laterality, prostheses, and radiographic views. They further annotated surgical construct locations in 11,841 knee radiographs.

Blood metal concentrations and cardiac structure and function in total joint arthroplasty patients.

Background: There is concern regarding potential long-term cardiotoxicity with systemic distribution of metals in total joint arthroplasty (TJA) patients.

Aim: To determine the association of commonly used implant metals with echocardiographic measures in TJA patients.

Methods: The study comprised 110 TJA patients who had a recent history of high chromium, cobalt or titanium concentrations.

Deep learning classification of pediatric spinal radiographs for use in large scale imaging registries.

Purpose: The purpose of this study is to develop and apply an algorithm that automatically classifies spine radiographs of pediatric scoliosis patients.

Methods: Anterior-posterior (AP) and lateral spine radiographs were extracted from the institutional picture archive for patients with scoliosis. Overall, there were 7777 AP images and 5621 lateral images.

Persistent changes in calcium-regulating hormones and bone turnover markers in living kidney donors more than 20 years after donation.

In a previous study, we observed decreased 1,25-dihydroxyvitamin D levels, secondary hyperparathyroidism, and increased bone turnover markers in living kidney donors (LKDs) at 3 months and 36 months after kidney donation. In our recent survey-based study, we found no increased risk of fractures of all types but observed significantly more vertebral fractures in LKDs compared with matched controls. To elucidate the long-term effects of kidney donation on bone health, we recruited 139 LKDs and 139 age and sex matched controls from the survey-based participants for further mechanistic analyses.

Multimorbidity in Psoriasis as a Risk Factor for Psoriatic Arthritis: A Population-Based Study.

Objectives: To examine multimorbidity in psoriasis and its association with the development of PsA.

Methods: A retrospective cohort study was performed using the Rochester Epidemiology Project. Population-based incidence (2000-2009) and prevalence (Jan 1, 2010) cohorts of psoriasis were identified by manual chart review.

Fracture Risk Among Living Kidney Donors 25 Years After Donation.

Importance: Living kidney donors may have an increased risk of fractures due to reductions in kidney mass, lower concentrations of serum 1,25-dihydroxyvitamin D, and secondary increases in serum parathyroid hormone.

Objective: To compare the overall and site-specific risk of fractures among living kidney donors with strictly matched controls from the general population who would have been eligible to donate a kidney but did not do so.

Design, Setting, And Participants: This survey study was conducted between December 1, 2021, and July 31, 2023.

A Stepwise Approach to Analyzing Musculoskeletal Imaging Data With Artificial Intelligence.

The digitization of medical records and expanding electronic health records has created an era of "Big Data" with an abundance of available information ranging from clinical notes to imaging studies. In the field of rheumatology, medical imaging is used to guide both diagnosis and treatment of a wide variety of rheumatic conditions. Although there is an abundance of data to analyze, traditional methods of image analysis are human resource intensive.

Whole Blood Metal Levels in the Setting of an Oncologic Endoprosthesis: Is There Cause for Concern?

Background: Massive modular endoprostheses have become a primary means of reconstruction after oncologic resection of a lower extremity tumor. These implants are commonly made with cobalt-chromium alloys that can undergo wear and corrosion, releasing cobalt and chromium ions into the surrounding tissue and blood. However, there are few studies about the blood metal levels in these patients.

The use of deep learning in medical imaging to improve spine care: A scoping review of current literature and clinical applications.

Background: Artificial intelligence is a revolutionary technology that promises to assist clinicians in improving patient care. In radiology, deep learning (DL) is widely used in clinical decision aids due to its ability to analyze complex patterns and images. It allows for rapid, enhanced data, and imaging analysis, from diagnosis to outcome prediction.

Demystifying Statistics and Machine Learning in Analysis of Structured Tabular Data.

Electronic health records have facilitated the extraction and analysis of a vast amount of data with many variables for clinical care and research. Conventional regression-based statistical methods may not capture all the complexities in high-dimensional data analysis. Therefore, researchers are increasingly using machine learning (ML)-based methods to better handle these more challenging datasets for the discovery of hidden patterns in patients' data and for classification and predictive purposes.

Correlation of Blood Metal Concentrations with Cognitive Scores and Neuroimaging Findings in Patients with Total Joint Arthroplasty.

Total joint arthroplasty (TJA) implants are composed of metals, ceramics, and/or polyethylene. Studies suggest that the debris released from metal implants may possess neurotoxic properties with reports of neuropsychiatric symptoms and memory deficits, which could be relevant to Alzheimer's disease and related dementias. This exploratory study examined the cross-sectional correlation of blood metal concentrations with cognitive performance and neuroimaging findings in a convenience sample of 113 TJA patients with history of elevated blood metal concentrations of either titanium, cobalt and/or chromium.

Depression and anxiety are associated with an increased risk of infection, revision, and reoperation following total hip or knee arthroplasty.

The aim of this study was to determine the prevalence of depressive and anxiety disorders prior to total hip (THA) and total knee arthroplasty (TKA) and to assess their impact on the rates of any infection, revision, or reoperation. Between January 2000 and March 2019, 21,469 primary and revision arthroplasties (10,011 THAs; 11,458 TKAs), which were undertaken in 15,504 patients at a single academic medical centre, were identified from a 27-county linked electronic medical record (EMR) system. Depressive and anxiety disorders were identified by diagnoses in the EMR or by using a natural language processing program with subsequent validation from review of the medical records.

Can the American Joint Replacement Registry Utilize Administrative Claims Data to Accurately Classify Revision Total Hip Arthroplasty (THA) Surgical Diagnoses?

Background: The American Joint Replacement Registry (AJRR) is a valuable tool for studying revision total hip arthroplasty (rTHA). Currently, International Classification of Diseases-10 (ICD-10) codes are utilized by the AJRR for classifying surgical diagnoses. However, the validity of this methodology is unknown.

Comparative Survival of Contemporary Cementless Acetabular Components Following Revision Total Hip Arthroplasty.

Background: The advent of highly porous ingrowth surfaces and highly crosslinked polyethylene has been expected to improve implant survivorship in revision total hip arthroplasty. Therefore, we sought to evaluate the survival of several contemporary acetabular designs following revision total hip arthroplasty.

Methods: Acetabular revisions performed from 2000 to 2019 were identified from our institutional total joint registry.

Cross-sectional association between systemic metal concentrations and immune markers in patients with total joint arthroplasty.

Total joint arthroplasty (TJA) implants are composed of metal components. Although they are regarded safe, the long-term immunological effects of chronic exposure to the specific implant materials are unknown. We recruited 115 hip and/or knee TJA patients (mean age 68 years) who provided a blood draw for measurement of chromium, cobalt, titanium concentrations, inflammatory markers and systemic distribution of immune cells.

Frank Stinchfield Award: Creation of a Patient-Specific Total Hip Arthroplasty Periprosthetic Fracture Risk Calculator.

Background: Many risk factors have been described for periprosthetic femur fracture (PPFFx) following total hip arthroplasty (THA), yet a patient-specific risk assessment tool remains elusive. The purpose of this study was to develop a high-dimensional, patient-specific risk-stratification nomogram that allows dynamic risk modification based on operative decisions.

Methods: We evaluated 16,696 primary nononcologic THAs performed between 1998 and 2018.

Is the American Joint Replacement Registry Able to Correctly Classify Revision Total Knee Arthroplasty Procedural Diagnoses?

Background: The American Joint Replacement Registry (AJRR) is a powerful tool for the study of revision total knee arthroplasty (rTKA). The AJRR uses International Classification of Diseases-10 (ICD-10-CM) codes for recording surgical diagnoses. However, the validity of this methodology is unknown.

Longitudinal factors associated with increased alcohol consumption in adults during the COVID-19 pandemic.

Alcohol is the most abused substance among adults in the United States. The COVID-19 pandemic impacted patterns of alcohol use, but data are conflicting, and previous studies are largely limited to cross-sectional analyses. This study aimed to longitudinally assess sociodemographic and psychological correlates of changes in three patterns of alcohol use (number of alcoholic drinks, drinking regularity, and binge drinking) during COVID-19.

Prediction Models for Knee Osteoarthritis: Review of Current Models and Future Directions.

Background: Knee osteoarthritis (OA) is a prevalent joint disease. Clinical prediction models consider a wide range of risk factors for knee OA. This review aimed to evaluate published prediction models for knee OA and identify opportunities for future model development.

Propensity Scores: Confounder Adjustment When Comparing Nonrandomized Groups in Orthopaedic Surgery.

Many studies in arthroplasty research are based on nonrandomized, retrospective, registry-based cohorts. In these types of studies, patients belonging to different treatment or exposure groups often differ with respect to patient characteristics, medical histories, surgical indications, or other factors. Consequently, comparisons of nonrandomized groups are often subject to treatment selection bias and confounding.

How to Develop and Validate Prediction Models for Orthopedic Outcomes.

Prediction models are common in medicine for predicting outcomes such as mortality, complications, or response to treatment. Despite the growing interest in these models in arthroplasty (and orthopaedics in general), few have been adopted in clinical practice. If robustly built and validated, prediction models can be excellent tools to support surgical decision making.

Patient-specific Hip Arthroplasty Dislocation Risk Calculator: An Explainable Multimodal Machine Learning-based Approach.

Purpose: To develop a multimodal machine learning-based pipeline to predict patient-specific risk of dislocation following primary total hip arthroplasty (THA).

Materials And Methods: This study retrospectively evaluated 17 073 patients who underwent primary THA between 1998 and 2018. A test set of 1718 patients was held out.

Nuts and Bolts of Patient-Reported Outcomes in Orthopaedics.

Patient-reported outcomes (PROs) are commonly used in orthopaedic clinical practice, comparative effectiveness research (CER), and label claims. In this paper, we provide an overview of PROs, their development, validation, and use in orthopaedic research with examples and conclude with practical guidelines for researchers and reviewers. We discuss considerations for conceptual framework, validity, reliability, factor analysis, and measurement of change with Knee Injury and Osteoarthritis Outcome score (KOOS), as an example.

How to Distinguish Correlation From Causation in Orthopaedic Research.

Correlations in observational studies are commonly misinterpreted as causation. Although correlation is necessary to establish a causal relationship between two variables, correlations may also arise due to chance, reverse causality, or confounding. There are several methods available to orthopaedic researchers to determine whether the observed correlations are causal.