Halpin, Brooke S.

Background: Matching techniques such as direct covariate matching and propensity score matching (PSM) are increasingly used in anterior cruciate ligament reconstruction (ACLR) research to reduce bias in observational study designs. However, the rationale for covariate selection, consistency in methodological reporting, and patterns of matching practices remain unclear. Purpose: To systematically evaluate covariate matching practices in ACLR literature, including the types and number of covariates used, methodological transparency, and trends in matching strategies. Study Design: Systematic review. Methods: A systematic literature search of the PubMed, EMBASE, and Cochrane databases was conducted to evaluate covariate matching practices in the ACLR literature. A comprehensive search identified 798 unique studies, of which 97 met eligibility criteria. Data were extracted on study design, matching technique, covariate inclusion, reporting practices, and matching ratios. Descriptive and comparative statistics were used to summarize trends. Results: The 97 included studies encompassed 91,165 ACLRs. Most studies were retrospective (90.7%) and cohort in design (92.8%). PSM was used in 41 studies (42.3%), while 56 (57.7%) used direct matching. A total of 60 unique covariates were used across 76 different combinations. PSM studies used significantly more covariates than direct matching studies (6.17 ± 2.79 vs 3.75 ± 1.63; P < .0001), and database studies used more covariates than single-center studies (6.33 ± 2.89 vs 4.08 ± 1.96; P < .0001). The most commonly used covariates were age (96.9%), sex (84.5%), and body mass index (41.2%). Only 6 studies (6.2%) provided justification for covariate selection. The most frequent matching ratio was 1:1 (73.2%). While most studies reported descriptive statistics after matching (95.9%), only 10.3% did so before matching, and 13.4% failed to report prematching sample size. Conclusion: Matching practices in ACLR studies remain highly variable, with limited justification provided for covariate selection. PSM and database-based studies tend to incorporate a greater number of covariates, yet reporting of matching methodology is often inconsistent. To enhance the quality, reproducibility, and comparability of ACLR research, future studies should adopt standardized reporting practices for matching, including explicit descriptions of covariate selection, matching algorithms, balance diagnostics, and match ratios. These steps can serve as a foundation for a more unified research framework, enabling future studies to collectively generate higher quality, generalizable evidence for ACLR outcomes.

Background: Gender-based reimbursement disparities in orthopedic surgery remain poorly understood, particularly when accounting for practice composition and setting. The purpose of this study was to compare and evaluate gender-based differences in Medicare reimbursement and practice patterns among female and male orthopedic surgeons. Methods: A cross sectional analysis of public Medicare data from 2013 to 2021 was performed. Outcomes included annual Medicare payments, submitted charges, total services, service categories, and beneficiaries treated by orthopedic surgeons who bill Medicare. Univariate and multivariable analyses quantified differences in payment, practice volume and composition, geographic adjustment, and Current Procedural Terminology (CPT)-matched reimbursements. Results: A total of 29,357 orthopedic surgeons (27,442 men and 1,919 women) billed Medicare fee-for-service during the study period. Female surgeons, on average, submitted 48.3% fewer total charges and received 44.1% lower annual Medicare payments per surgeon compared with male surgeons. These differences persisted after multivariable regression adjusted for practice metrics and excluded top and bottom earners. Female surgeons also billed fewer services, treated fewer beneficiaries, and submitted fewer unique CPT codes. However, payment disparities persisted even after matching surgeons by volume of services, beneficiaries, and years in practice. Male surgeons performed higher volumes of all 10 highest-paying orthopedic CPT codes. In CPT matched analyses, female surgeons received lower reimbursement per service than male surgeons performing identical procedures. Conclusion: These findings suggest that the observed gender-based disparities in orthopedic surgery Medicare reimbursement cannot be explained by differences in volume, procedural mix, or geographic practice cost. Instead, they likely reflect a combination of structural and behavioral mechanisms described in prior literature that may influence how access to clinical opportunities, referrals, and reimbursement practices unfold in surgical practices. Variations in coding practices may represent an important focus for future investigation and targeted educational initiatives. Level of Evidence: Level III , Retrospective Cohort Study. See Instructions for Authors for a complete description of levels of evidence.

BACKGROUND AND OBJECTIVES: Aneurysm risk prediction remains an imprecise science that places patients at risk for either over or undertreatment. Machine learning (ML) models may improve clinical practice by adding precision to risk assessment. This study aims to comprehensively assess the current landscape of ML applications in predicting the risk of aneurysm rupture and compare the performance with the widely used PHASES score. METHODS: A systematic review of PubMed, Scopus, and Web of Science was conducted. All studies using ML tools to predict the rupture risk of intracranial aneurysms were included. Meta-analysis was conducted with consideration to the ML algorithms and compared with the PHASES score. RESULTS: Thirty-six studies involving 22 462 patients were included in the final analysis. ML techniques, including 124 models using 25 algorithms, were employed. Among various ML models, while they had comparable diagnostic performance, deep learning exhibited a slightly better performance profile (sensitivity = 0.792, specificity = 0.788, and accuracy = 0.778 in external validation). Based on our analysis, ML, regardless of the algorithm, provides comparable sensitivity (0.743 vs 0.771, P = .60) and higher specificity (0.763 vs 0.507, P < .01) compared with the PHASES score. Consistently, pooling the area under the receiver operating characteristic curve (AUC) for 60 ML models and 5 PHASES score data, ML models exhibited higher AUC (0.84 vs 0.64, P < .01). Using hemodynamic parameters as input for models improved specificity ( P < .01) in the test sets without any significant changes in the sensitivity. The later improvement was not observed in the external validation sets. CONCLUSION: ML techniques have the potential to enhance the prediction of intracranial aneurysm rupture compared with traditional approaches, like the PHASES score. Incorporating hemodynamic parameters may further enhance the accuracy of ML models. Feature prospective studies are required to validate the utility of ML models for clinical integration.

OBJECTIVE Patients with autosomal dominant polycystic kidney disease (ADPKD) have been identified to have a significantly increased risk of developing intracranial aneurysms (IAs). These patients are diagnosed at younger ages and are also at increased risk for IA rupture. The objective of this systematic review and meta-analysis was to identify risk factors associated with IA detection during screening of asymptomatic ADPKD patients. METHODS The authors searched for studies reporting the prevalence of IA among patients with ADPKD screened using MRA, CTA, or DSA on PubMed, Embase, Google Scholar, Scopus, Web of Science, Cochrane Database of Systematic Reviews, and ClinicalTrials.gov prior to August 2023 by using individualized standardized search strategies. Eligibility of all retrieved studies was assessed according to the PRISMA guidelines. Risk of bias of the included observational studies was assessed using the Newcastle-Ottawa Scale. Meta-analysis was performed using a random-effects model. RESULTS Twenty-four observational studies involving 5907 patients with ADPKD were identified for quantitative analysis. The authors observed an overall prevalence of IA of 12.6%. They identified several risk factors for IA with statistically significantly increased odds for unruptured IA (UIA) detection, including female sex (18 studies, OR 1.63, 95% CI 1.37–1.94, I 2 = 0%), family history of either IA or subarachnoid hemorrhage (SAH) (12 studies, OR 2.17, 95% CI 1.68–2.81, I 2 = 0%), family history of SAH (3 studies, OR 2.67, 95% CI 1.25–5.71, I 2 = 66.0%), stage 3 or greater chronic kidney disease (CKD) (4 studies, OR 2.55, 95% CI 1.84–3.54, I 2 = 0%), and hypertension (13 studies, OR 1.41, 95% CI 1.04–1.91, I 2 = 34%). Age > 45 years, family history of ADPKD, smoking status, and presence of liver cysts did not reach statistical significance as risk factors during this meta-analysis. CONCLUSIONS The results of the authors’ meta-analysis suggest increased risk of UIA detection in screening of ADPKD patients who are female, have a family history of IA or SAH, have hypertension, or have moderate or more severe CKD. Given the increased prevalence of IA in ADPKD patients with these risk factors, these patients may stand to benefit from screening for IA early in treatment or at time of diagnosis, even if neurologically asymptomatic.

OBJECTIVE While the relationship between smoking and subarachnoid hemorrhage is well established, data regarding the probability of detecting unruptured intracranial aneurysms (UIAs) in smokers remain sparse. The aim of this systematic review and meta-analysis is to provide a comprehensive understanding of the relationship between smoking and the likelihood of identifying UIAs in healthy asymptomatic patients who underwent brain imaging for indications unrelated to UIAs. METHODS A systematic review was conducted following the PRISMA guidelines. The PubMed and Scopus databases were searched for studies published before March 2024 that reported on the presence of UIAs in healthy asymptomatic patients who had undergone brain imaging for indications unrelated to UIAs. Three independent reviewers assessed the eligibility of all retrieved studies. Risk of bias for the included observational studies was assessed using the methodological index for non-randomized studies. Data on UIA prevalence, smoking status, and patient and aneurysm characteristics were extracted. The association between smoking and the presence of UIA was studied. A prevalence proportional meta-analysis was conducted across the included studies. A meta-analysis was performed with a random-effects model by using summary statistics from the included studies. RESULTS Six studies involving 47,788 patients who had undergone brain imaging were identified for quantitative analysis. The pooled UIA prevalence in the sample was 3.07% (95% CI 2.27%–4.16%). Patients who smoked had higher rates of aneurysm detection than the patients who did not smoke (pooled prevalence of 2.96%, 95% CI 2.68%–3.27% vs 2.23%, 95% CI 2.08%–2.39%). Although the relation between the two was not statistically significant (p = 0.06), smoking was associated with higher odds for UIA detection, yielding an OR of 1.34 (95% CI 1.07–1.67) with an I 2 value of 53%. CONCLUSIONS This study suggests a potentially higher risk of UIAs in patients who smoked than in those who never smoked. However, the results of this meta-analysis revealed that smoking was not statistically associated with higher UIA detection. This result could be explained by the limited number of studies published on this topic. If these findings reach statistical significance in future larger studies, it could justify revising guidelines to include cigarette smokers in intracranial aneurysm screening.

BACKGROUND: Smoking and observed growth of intracranial aneurysms are known risk factors for rupture. The mechanism by which smoking increases this risk is not completely elucidated. Furthermore, an association between smoking and aneurysm growth has not been clearly defined in the literature. We hypothesize that smoking is associated with aneurysm growth, which, in turn, may serve as one of the mechanisms by which smoking drives rupture risk. METHODS: We report a systematic review of the literature in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines. Using the R software, we performed a meta-analysis to investigate the association between smoking and the growth of unruptured intracranial aneurysms. Studies on familial aneurysms and genetic syndromes known to increase the risk of aneurysms were excluded. RESULTS: Eighteen observational studies were included with a total of 3535 patients and 4289 aneurysms with a mean follow-up period ranging from 17 to 226 months. The mean age among the studies ranged from 38.4 to 73.9 years; 74% of patients were female. Ever-smoking status (odds ratio, 1.10 [95% CI, 0.87–1.38]) and current smoking status (odds ratio, 1.43 [95% CI, 0.84–2.43]) did not show a statistically significant association with growth of intracranial aneurysms. Patients currently smoking did not have a statistically significant association with the growth of intracranial aneurysms (odds ratio, 1.18 [95% CI, 0.72–1.93]) compared with patients without a smoking history. No significant association was found in patients who previously smoked compared with patients who never smoked (odds ratio, 1.46 [95% CI, 0.88–2.43]). CONCLUSIONS: Smoking is not clearly associated with the growth of unruptured intracranial aneurysms, despite trends being observed, there is no statistical association. The mechanism by which smoking increases rupture risk might not be growth. In patients for whom observation is recommended, the absence of growth over time in the setting of smoking history does not, therefore, imply protection from rupture.

BACKGROUND: Minimally invasive surgical techniques have reinvigorated the role of surgical options for spontaneous intracranial hematomas; however, they are limited by the lack of real-time feedback on the extent of hematoma evacuation. OBJECTIVE: To describe the development of a MRI-guided catheter-based aspiration system, the ClearPoint Pursuit Neuroaspiration Device (ClearPoint Neuro) and validation in phantom models. METHODS: In this preclinical experimental trial, 8 phantom brains with skull models were created to simulate an intracranial hematoma with 2 clot sizes, 30 cc (small clot) and 60 cc (large clot). After registration, the aspiration catheter (Pursuit device) was aligned to the desired planned trajectory. The aspiration of the clot was performed under real-time MRI scan in 3 orthogonal views. The primary end point was reduction of the clot volume to less than 15 cc or 70% of the original clot volume. RESULTS: Successful completion of clot evacuation was achieved in all models. The average postaspiration clot volume was 9.5 cc (8.7 cc for small clots and 10.2 cc for large clots). The average percentage reduction of clot volume was 76.3% (range 58.7%-85.2%). The average total procedure time (from frame registration to final postaspiration clot assessment) was 50 min. The average aspiration time was 6.9 min. CONCLUSION: This preclinical trial confirms the feasibility and efficacy of MRI-guided aspiration under real-time image guidance in simulation models for intracranial hematoma. Clinical use of the system in patients would further validate its efficacy and safety.