Citations

Abstract Background: Intra-articular corticosteroid injections (ICSI) have been shown to be an effective symptomatic non-operative treatment for hip osteoarthritis (OA) and other joint-related pain. There has been recent dispute over the true risk of complications from ICSI specifically when injected into the hip. Avascular necrosis (AVN) of the femoral head has been reported to occur in up to 30.5% of patients after undergoing hip ICSI, and up to 50.6% of patients experiencing osteoarthritis progression in as little as 3 months following injection. Purpose: To analyze the current protocol of hip ICSIs performed by two fellowship-trained non-operative sports medicine physicians and assess the rate of femoral head avascular necrosis. We hypothesized that the rate of AVN will be less than what has been recently reported in the literature. Study Design: Retrospective chart review Methods: Patients that underwent at least one intra-articular corticosteroid hip injection by two fellowship trained non-operative sports medicine physicians at this institution were identified using an institutional database. Exclusion criteria included injections with contrast dye used for imaging, injections that administered orthobiologics to the intra-articular, and non-intra-articular injections. Procedure notes were reviewed for anesthetic and steroid type, dosage, and needle size. Each chart was screened for demographic information, post-injection infections, AVN diagnosis, and subsequent hip replacement. 10 patients were identified with an AVN diagnosis. Their MRNs were sent to a board-certified radiologist at the same medical institution. The radiologist was blinded to the patient’s chart and instructed to identify the first radiograph with evidence of AVN. Patients were excluded if the reviewer did not agree with the diagnosis as it appeared in the medical chart or the AVN developed post-traumatically. Results: 449 patients, 530 hips, underwent 1.8 ± 1.4 ICSIs and 16.3% underwent THA at an average of 2.2 ± 2.3 years following their first injection. Of the 530 hips that underwent ICSI, only 1 hip demonstrated findings of AVN on radiographs following the first injection, and this patient had been taking oral prednisone for over 20 years. Conclusions: Intra-articular corticosteroid injections are a relatively safe symptomatic treatment option for hip pain secondary to both OA and non-OA pathology to be considered when other non-operative treatment options have failed. While the use of steroids comes with an inherent risk of osteonecrosis and cartilage damage, these results demonstrate that, when performed properly with ultrasound guidance and sterile technique, the risk of femoral head avascular necrosis is minimal.

Abstract The pharmacological provocation test is a pivotal tool in cardiac electrophysiology for the diagnosis of potential causes of sudden cardiac death, sudden cardiac arrest (SCA), arrhythmias, symptoms, or ECG abnormalities. The 2022 European Society of Cardiology Guidelines for the Treatment of Ventricular Arrhythmias and Prevention of Sudden Cardiac Death offered guidance on provocation testing but did not describe the indications and requirements in depth. This clinical consensus statement, led by the European Heart Rhythm Association and approved by major international stakeholders, aims to advise the general cardiologist and the arrhythmia expert who to test and when, where, and how to do it. The statement focuses on current practice for the diagnosis of subclinical arrhythmia syndromes and the causes of SCA, building upon the recommendations of the Guidelines. We address the sodium channel blocker provocation test for patients suspected of Brugada syndrome as well as the use of epinephrine, isoproterenol, adenosine, ergonovine, and acetylcholine.

AimsContemporary outcomes of total femoral arthroplasties (TFAs) in the non-oncological setting are limited. This study aimed to assess implant survival free from revision and reoperation, clinical outcomes, and radiological results associated with TFAs for non-oncological conditions.MethodsWe identified 24 patients who received TFAs between 1 January 2007 and 31 December 2021 through our institutional total joint registry. The patients’ mean age was 66 years (48 to 83), mean BMI was 33 kg/m2 (21 to 54), and median follow-up was four years (IQR 2 to 5). Bearings used included eight flat-faced polyethylene bearings, seven dual-mobility constructs, six constrained liners, and three face-changing liners. Of the 24 patients, 17 had a previously documented periprosthetic joint infection (PJI) and 12 were treated with chronic antibiotic suppression following their TFAs.ResultsThe two-, five-, and ten-year survivals free of any revision were 66%, 51%, and 34%, respectively. There were 12 revisions: five for hip dislocation, four for PJI, one for aseptic tibial loosening, one for prosthetic knee dislocation, and one for acetabular loosening with pelvic discontinuity. The two-, five-, and ten-year survivals free of any reoperation were 53%, 47%, and 34%, respectively. In addition to the stated TFA revisions, one patient required open reduction of a hip dislocation, and two patients required superficial irrigation and debridement procedures for wound complications. Mean Harris Hip Scores improved from a mean score of 48 to 69 (p = 0.002), and Knee Society Scores improved from a mean score of 56 to 71 (p = 0.110). At final follow-up, 20 patients had TFAs in situ, but four patients had been treated with hip disarticulation due to recalcitrant infection. All but one tibial and all non-revised acetabular components were radiologically well-fixed at final follow-up.ConclusionThe use of TFAs in the non-oncological setting, mostly for salvage of multiply revised hips with previous PJI, had a low five-year survival free from any revision of 51%, mostly for hip dislocation and infection. Nevertheless, clinical outcomes improved in this challenging cohort of patients.Cite this article: Bone Joint J 2025;107-B(4):449–454.

Abstract Aims Artificial intelligence (AI) has the potential to transform cardiac electrophysiology (EP), particularly in arrhythmia detection, procedural optimization, and patient outcome prediction. However, a standardized approach to reporting and understanding AI-related research in EP is lacking. This scientific statement aims to develop and apply a checklist for AI-related research reporting in EP to enhance transparency, reproducibility, and understandability in the field. Methods and results An AI checklist specific to EP was developed with expert input from the writing group and voted on using a modified Delphi process, leading to the development of a 29-item checklist. The checklist was subsequently applied to assess reporting practices to identify areas where improvements could be made and provide an overview of the state of the art in AI-related EP research in three domains from May 2021 until May 2024: atrial fibrillation (AF) management, sudden cardiac death (SCD), and EP lab applications. The EHRA AI checklist was applied to 31 studies in AF management, 18 studies in SCD, and 6 studies in EP lab applications. Results differed between the different domains, but in no domain reporting of a specific item exceeded 55% of included papers. Key areas such as trial registration, participant details, data handling, and training performance were underreported (<20%). The checklist application highlighted areas where reporting practices could be improved to promote clearer, more comprehensive AI research in EP. Conclusion The EHRA AI checklist provides a structured framework for reporting AI research in EP. Its use can improve understanding but also enhance the reproducibility and transparency of AI studies, fostering more robust and reliable integration of AI into clinical EP practice.

OBJECTIVE: To systematically review and synthesize the evidence surrounding factors impacting women rising to leadership positions in critical care medicine (CCM). DATA SOURCES: PubMed, Embase, Web of Science, and Cochrane Library from 2011 to 2024. STUDY SELECTION: Articles included were cohort studies, surveys, and interviews addressing women physicians practicing in CCM and related fields of academic medicine. DATA EXTRACTION: Causes of not rising to leadership among women were extracted and tabulated along with other pertinent study characteristics. DATA SYNTHESIS: The database searches generated 892 records. Thirty-nine studies met inclusion criteria for data extraction. The included articles represented seven countries, with 30 studies originating in the United States. Only two studies were from CCM, whereas others addressed leadership in other academic and clinical fields of medicine, medical journals, and societies and medical faculty. Twenty-six studies were qualitative, observational studies; five were survey based and eight included interviews. Using thematic analysis, the following five domains emerged: pipeline issues, lack of opportunities, lack of self-efficacy, lack of mentorship, and sustaining women in leadership. CONCLUSIONS: While the satisfaction rates of women in CCM were high, challenges remain for women to obtain leadership opportunities. A culture of support could better nurture and sustain women in leadership roles. More CCM-focused gender bias research is needed. Future targets for interventions include gender bias training, awareness, and developing strategies to break through the cycle of gender preferential promotions in CCM.

Key Points Pooled discrimination metrics were acceptable (area under the receiver operating characteristic curve >0.70) for all AKI risk classification categories in both internal and external validation. Better performance was observed in most recently published studies and those with a low or unclear risk of bias. Significant heterogeneity in patient populations, definitions, clinical predictors, and methods limit implementation in real-world clinical scenarios. Background Artificial intelligence through machine learning models seems to provide accurate and precise AKI risk classification in some clinical settings, but their performance and implementation in real-world settings has not been established. Methods PubMed, Excerpta Medica (EMBASE) database, Web of Science, and Scopus were searched until August 2023. Articles reporting on externally validated models for prediction of AKI onset, AKI severity, and post-AKI complications in hospitalized adult and pediatric patients were searched using text words related to AKI, artificial intelligence, and machine learning. Two independent reviewers screened article titles, abstracts, and full texts. Areas under the receiver operating characteristic curves (AUCs) were used to compare model discrimination and pooled using a random-effects model. Results Of the 4816 articles initially identified and screened, 95 were included, representing 3.8 million admissions. The Kidney Disease Improving Global Outcomes (KDIGO)-AKI criteria were most frequently used to define AKI (72%). We identified 302 models, with the most common being logistic regression (37%), neural networks (10%), random forest (9%), and eXtreme gradient boosting (9%). The most frequently reported predictors of hospitalized incident AKI were age, sex, diabetes, serum creatinine, and hemoglobin. The pooled AUCs for AKI onset were 0.82 (95% confidence interval, 0.80 to 0.84) and 0.78 (95% confidence interval, 0.76 to 0.80) for internal and external validation, respectively. Pooled AUCs across multiple clinical settings, AKI severities, and post-AKI complications ranged from 0.78 to 0.87 for internal validation and 0.73 to 0.84 for external validation. Although data were limited, results in the pediatric population aligned with those observed in adults. Between-study heterogeneity was high for all outcomes (I 2 >90%), and most studies presented high risk of bias (86%) according to the Prediction Model Risk of Bias Assessment Tool. Conclusions Most externally validated models performed well in predicting AKI onset, AKI severity, and post-AKI complications in hospitalized adult and pediatric populations. However, heterogeneity in clinical settings, study populations, and predictors limits their generalizability and implementation at the bedside.

Abstract Multimodal artificial intelligence (AI) has the potential to revolutionise healthcare by enabling the simultaneous processing and integration of various data types, including medical imaging, electronic health records, genomic information and real‐time data. This review explores the current applications and future potential of multimodal AI across healthcare, with a particular focus on orthopaedic surgery. In presurgical planning, multimodal AI has demonstrated significant improvements in diagnostic accuracy and risk prediction, with studies reporting an Area under the receiving operator curve presenting good to excellent performance across various orthopaedic conditions. Intraoperative applications leverage advanced imaging and tracking technologies to enhance surgical precision, while postoperative care has been advanced through continuous patient monitoring and early detection of complications. Despite these advances, significant challenges remain in data integration, standardisation, and privacy protection. Technical solutions such as federated learning (allowing decentralisation of models) and edge computing (allowing data analysis to happen on site or closer to site instead of multipurpose datacenters) are being developed to address these concerns while maintaining compliance with regulatory frameworks. As this field continues to evolve, the integration of multimodal AI promises to advance personalised medicine, improve patient outcomes, and transform healthcare delivery through more comprehensive and nuanced analysis of patient data. Level of Evidence: Level V.

Abstract Background Atypical teratoid rhabdoid tumor (ATRT) is a deadly central nervous system embryonal tumor caused by loss of SMARCB1, a core subunit of SWItch/Sucrose Non-Fermentable (SWI/SNF) chromatin remodeling complexes. SMARCB1-deficient cancers are defined by loss of cell differentiation-associated enhancers, but how SWI/SNF interacts with other arbiters of cell differentiation (specifically lineage-specific transcription factors [TFs]) remains poorly understood. Methods We leveraged a multi-omics approach, patient-derived ATRT cells, and patient-derived orthotopic xenografts to investigate the interplay of SWI/SNF with lineage-specific TFs in a clinically relevant setting. Results We observe that an activating protein 1 (AP-1)-dependent transcriptional regulatory network is lost in ATRT, and AP-1 and lineage-specific TFs TEAD1 and ZIC2 require SMARCB1 for enhancer binding. SMARCB1-dependent SWI/SNF integrates transcriptional functions of lineage-specific TFs into a core regulatory circuit that depends on the AP-1 subunit c-JUN, whose expression is determined by a SMARCB1-dependent super-enhancer that is lost in ATRT-MYC. In the absence of SMARCB1, lineage-specific TFs are sequestered to promoters, where they maintain core transcriptional programs necessary for cell survival. Targeting residual, promoter-proximal TF activity by a protein degrader of the SWI/SNF ATPase SMARCA4 or small-molecule inhibitors that indirectly inhibit AP-1 and TEAD activity abrogates expression of these networks, reducing cell viability in vitro and prolonging survival in an orthotopic patient-derived xenograft model. Conclusions These results demonstrate SWI/SNF complexes are critical for lineage-specific TF binding and activity at both promoters and enhancers. In the context of ATRT, these findings reveal a previously underappreciated therapeutic vulnerability in targeting residual promoter-proximal TF function in ATRT.

ABSTRACTObjectiveIntrathecal fluorescein (IF) is effective for localizing nasal cerebrospinal fluid (CSF) leaks along the skull base during endoscopic exploration, with largest studies reporting sensitivities ranging from 66%–93%. Due to reports of intraoperative and postoperative neurologic complications such as seizures and paralysis, surgeons often dilute the fluorescein and inject it intrathecally slowly over a variable amount of time. However, no study has assessed whether rapid IF administration causes the aforementioned risks or whether it affects its accuracy in identifying CSF leaks intraoperatively.MethodsA prospective study was conducted from 2015 to 2024, where all patients undergoing endoscopic exploration and/or repair of CSF rhinorrhea had 0.1 mL of 10% fluorescein (10 mg) mixed with 3–5 mL of patients' CSF injected rapidly via the lumbar drain over a few seconds.ResultsOf the 82 included patients, the mean age was 53.8 ± 15.2 years, and 84% were female. Sixty‐nine patients underwent successful endoscopic CSF leak repairs, and 13 had negative endoscopic explorations. Rapid IF injection was 80% sensitive (20% false negative rate) and 100% specific for identifying CSF leaks, and it caused no seizures, paralysis, or other neurologic complications.ConclusionCompared to prior reports of slow low‐dose IF injection for CSF leak localization, rapid IF injection yielded similar efficacy (80% sensitivity) with no IF‐related complications. Rapid IF injection was safe and effective but should be corroborated by future studies.Level of Evidence4.