Citations

Objective: Despite excellent functional outcomes after shoulder stabilization surgery, a substantial number of patients fail to return to sports (RTS) at the preinjury level. The psychological factors affecting RTS postsurgery have been underexplored. This scoping review aimed to identify and analyze potential psychological factors influencing the decision to RTS after shoulder stabilization surgery. Data Sources: We reviewed the EBSCOhost/SPORTDiscus, PubMed/Medline, Scopus, EMBASE, and Cochrane Library databases for studies on patients with anterior glenohumeral instability who underwent stabilization surgery. We included studies that reported on RTS and considered the psychological factors influencing the decision to return. Main Results: Our analysis comprised 21 articles involving 2073 patients. Psychological factors influencing RTS after surgery were categorized within the framework of transactional stress and coping model. Primary appraisal factors, such as fear of reinjury, kinesiophobia, and anxiety, emerged as significant influencers. In addition, we explored factors related to social support, self-determination, motivation, competing interests, and advanced age. Assessment tools were used to evaluate the psychological readiness for RTS. Conclusions: This scoping review identified fear of reinjury and kinesiophobia as important psychological barriers to returning to sports after shoulder stabilization surgery. The limited use of psychological assessment tools and lack of comparative studies have restricted robust conclusions. Level of Evidence: Level IV, Scoping review.

Abstract Aims Gender-affirming hormone therapy (GAHT) is used by some transgender individuals (TG), who comprise 1.4% of US population. However, the effects of GAHT on electrocardiogram (ECG) remain unknown. The objective is to assess the effects of GAHT on ECG changes in TG. Methods and results Twelve-lead ECGs of TG on GAHT at the Mayo Clinic were inspected using a validated artificial intelligence (AI) algorithm. The algorithm assigns a patient’s ECG male pattern probability on a scale of 0 (female) to 1 (male). In the primary analysis, done separately for transgender women (TGW) and transgender men (TGM), 12-lead ECGs were used to estimate the male pattern probability before and after GAHT. In a subanalysis, only patients with both pre- and post-GAHT EGCs were included. Further, the autopopulated PR, QRS, and QTc intervals were compared before and after GAHT. Among TGW (n = 86), the probability (mean ± SD) of an ECG male pattern was 0.84 ± 0.25 in the pre-GAHT group, and it was lowered to 0.59 ± 0.36 in the post-GAHT group (n = 173, P < 7.8 × 10−10). Conversely, among TGM, male pattern probability was 0.16 ± 0.28 (n = 47) in the pre-GAHT group, and it was higher at 0.41 ± 0.38 in the post-GAHT group (n = 53, P < 2.4×10−4). The trend persisted in the subanalysis. Furthermore, both the PR (P = 5.68 × 10−4) and QTc intervals (P = 6.65×10−6) prolonged among TGW. Among TGM, the QTc interval shortened (P = 4.8 × 10−2). Conclusion Among TG, GAHT is associated with ECG changes trending towards gender congruence, as determined by the AI algorithm and ECG intervals. Prospective studies are warranted to understand GAHT effects on cardiac structure and function.

Abstract Background Hypergammaglobulinemia poses a challenge for identifying and quantitating monoclonal proteins (M-protein). The Increased polyclonal immunoglobulin background can lead to imprecise estimation of the M-protein when quantitated by serum protein electrophoresis (SPEP). This is especially true using the perpendicular drop method of peak integration. Hypergammaglobulinemia also makes it difficult to detect small M-proteins on immunofixation electrophoresis. Overestimation of M-protein concentration can lead to unnecessary follow-ups while missing small M-proteins can mask the underlying diagnosis for patients. In this study, we retrospectively evaluated the prevalence and concentration of M-protein within polyclonal hypergamma backgrounds using immunocapture matrix-assisted laser desorption ionization time-of-flight mass-spectrometry (MASS-FIX). Methods We retrospectively analyzed 47061 unique patients tested for SPEP and MASS-FIX in 2022 at Mayo Clinic. If a patient underwent multiple tests during this period, only the first result was included in the analysis. Polyclonal hypergammaglobulinemia was defined as a gamma fraction >1.7g/dL by SPEP. MASS-FIX was used to identify and isotype M-proteins. MASS-FIX was then combined with total immunoglobin quantitation (IgG, IgA or IgM) using nephelometry to quantify concentration of the M- protein using mathematical modeling (method currently under validation). Results Of the 47,061 unique patients, 24,796 were normal by SPEP (53%). M-spikes were present in 5,808 cases (12%). Hypogammaglobulinemia (gamma fraction < 0.5g/dL) in 2897 cases (6%). Small non-quantifiable M-proteins by SPEP were present in 8363 cases (18%). [JC2] There were 4222 hypergamma cases in the cohort (9%), without a quantitative M-spike on SPEP. Of these, 16.1% (680/4222) patients had an M-protein by MASS-FIX. When polyclonal hypergamma was the sole SPEP abnormality, 5.5% were MASS-FIX positive. However, when a small abnormality pattern was observed within the polyclonal hypergamma background on SPEP, 50% of patients were MASS-FIX positive. The most common isotype was IgG (27.2%), followed by IgM (10.2%), IgA (8.1%), and biclonal (3.7%), which is similar to overall isotype distribution in other backgrounds. Using quantitative MASS-FIX, we identified that 95% MASS-FIX positive small monoclonal proteins in polyclonal hypergamma are < 1 g/dL, which is the recommended limited of quantitation for M-protein using SPEP in setting of hypergammaglobulinemia. Conclusion Majority of polyclonal hypergammaglobulinemia cases (83.9%) do not have a monoclonal protein. MASS-FIX allows quantitation of small monoclonal proteins below the SPEP limit of quantitation, which can enhance our understanding of conditions which present with small M-proteins in a polyclonal hypergammaglobulinemia background. Small visual abnormalities within polyclonal hypergamma background on SPEP should be followed-up with immunofixation or MASS-FIX to confirm the presence or absence of M- proteins.

Abstract Introduction/Objective Recent advancements in artificial intelligence (AI), particularly with Large Language Models like ChatGPT-4Vision (GPT-4V), have expanded the potential for automated interpretation of medical images. This study evaluates the diagnostic accuracy of GPT-4V in histopathological analysis of neurodegenerative diseases and compares its performance with traditional Convolutional Neural Networks (CNNs). Methods/Case Report We utilized 1515 histopathological images, including hematoxylin and eosin (H&E) staining and tau immunohistochemistry, from patients with various neurodegenerative diseases, such as Alzheimer’s disease, progressive supranuclear palsy, and corticobasal degeneration. GPT-4V’s performance was assessed through multi- step prompts to assess how textual context influences the image interpretation. In the quantitative analysis, the diagnostic accuracy of GPT-4V and the CNN-based model YOLOv8 was assessed for classifying three tau lesions—astrocytic plaques, neuritic plaques, and tufted astrocytes. The analysis used both zero-shot and few-shot learning methods, where GPT-4V and YOLOv8 were evaluated on their ability to distinguish these lesions using ten hold-out test images and 490 training images per lesion. Results (if a Case Study enter NA) GPT-4V accurately recognized Lewy bodies in all cases, but it showed limited accuracy in identifying neurofibrillary tangles (20%) and Pick bodies (0%) on H&E slides. Notably, GPT-4V often suggested Alzheimer’s disease as a potential diagnosis, relying more on contextual clues, such as the prevalence of certain diseases, rather than direct image analysis. In the tau immunohistochemical analysis, GPT-4V’s diagnoses were strongly influenced by additional information about staining and brain region. However, few-shot learning markedly improved GPT-4V’s diagnostic capabilities from 40% accuracy with zero-shot learning to 90% with few-shot learning, reaching best accuracy with 20-shot learning. This performance compared favorably against YOLOv8, which also achieved 90% accuracy but required 100-shot learning. Conclusion While GPT-4V faces challenges in independently interpreting histopathological images, few-shot learning significantly improves its accuracy. This approach is particularly promising for neuropathology, where acquiring extensive labeled datasets is challenging. The findings highlight the need for ongoing refinement of AI applications in pathology, emphasizing balanced integration of textual and visual data to optimize diagnostic efficacy and reliability.

Abstract Introduction/Objective Infections of prosthetic joints cause significant morbidity and often result in removal of the infected joint. In many cases, an infectious etiology can be difficult to definitively identify. As a result, providers suspecting prosthetic joint infections (PJI) often place large order sets of microbiology tests, including fungal and mycobacterial cultures. Fungal and mycobacterial cultures are labor-intensive for the laboratory taking up to 28 days and 42 days, respectively, to complete. As a potential area for a diagnostic stewardship intervention, we wanted to evaluate how often a fungal or mycobacterial culture produced actionable information in cases of suspected PJI. Methods/Case Report Data reports were retrieved from both the Electronic Health Record (EHR) and the Laboratory Information System (LIS) from May 2022 to May 2023. As sources submitted by the provider often do not specify that the joint is prosthetic, data from LIS was evaluated to identify microbiology culture test sets ordered on joint sources, while data from EHR was examined to isolate patients with implanted joints. Using Microsoft Excel, data from both systems was compared in order to match microbiology culture test sets to the known implanted joints. LIS data from implanted joint sources was assessed to record negative (no growth) and positive (growth) cultures, and to register all organisms isolated. Results (if a Case Study enter NA) Of 794 order sets for cultures collected from prosthetic joint sources, 430 included requests for fungal culture and 79 included requests for mycobacterial culture. Of these 79 requests for mycobacterial culture, 0 organisms were isolated (0%). Of these 430 requests for fungal culture, 7 grew yeast (1.6%) and 7 out of 7 (100%) of these yeasts were also isolated on general (aerobic bacterial) culture. No molds were isolated. Conclusion Discontinuing the routine practice of ordering fungal and mycobacterial culture for prosthetic joint sources would have no negative impact on patient care but would reduce unnecessary work in the microbiology laboratory and potentially avoid additional costs to the patient. Education to the orthopedic provider group as well as best practice alerts in the EHR will be pursued, based on the findings from this study, in order to reduce unnecessary culture orders.

Abstract Introduction/Objective Distinguishing follicular lymphoma (FL) from marginal zone lymphoma (MZL) can be challenging, as the morphology and immunophenotype can overlap particularly in CD10-negative cases or those with marginal zone differentiation (MZD). MEF2B (Myocyte enhancer binding factor B) is a transcription factor that controls BCL6 expression in germinal center (GC) B-cells. Previous studies report MEF2B to have a high sensitivity and specificity for FL compared to other GC markers. We investigated the expression of MEF2B in low grade B cell lymphomas (LGBCL) to evaluate its utility in classifying diagnostically challenging cases and FL with MZD. Methods/Case Report Our archives were searched from 2005-2023 to identify excisional biopsies of LGBCL with MZD, including (FL), splenic MZL (SMZL), MZL of mucosa-associated lymphoid tissue (MALT), nodal MZL (NMZL) and difficult-to-classify (DTC) cases with a differential diagnosis of MZL and FL. MEF2B immunohistochemistry was performed retrospectively (Atlas Antibodies). Two hematopathologists assigned a pre-and post-MEF2B diagnosis to DTC cases. Results (if a Case Study enter NA) 57 cases were included: 21 FL (12 with MZD), 11 SMZL, 13 MALT, 4 NMZL, and 8 DTC cases. 19/21 FL cases (90%) were positive for MEF2B, including 11/12 (92%) cases with MZD. However, MEF2B expression was restricted to the follicles and negative in MZD areas in 7/11 cases (64%), while 4 cases showed partial weak expression in the areas of MZD. 0/11 SMZL (0%), 0/13 MALT (0%), and 0/4 (0%) NMZL were positive for MEF2B. 6/8 DTC cases (75%) were positive for MEF2B. Within DTC cases, retrospective inclusion of MEF2B results helped to render a more definitive diagnosis in 5 cases (2 negative/3 positive). Conclusion MEF2B immunohistochemistry can aid in distinguishing FL from MZL in challenging cases. However, it is often negative in areas of FL with MZD so care must be taken on interpretation in small biopsies.

BACKGROUND: Defining qualitative grades of echocardiographic metrics of right heart chamber size and function is critical for screening, clinical assessment, and measurement of therapeutic response in individuals with pulmonary vascular disease (PVD). In a population enriched for PVD, we sought to establish qualitative grades and prognostic value of right heart chamber size and function. METHODS: We investigated 1053 study participants in PVDOMICS (Redefining Pulmonary Hypertension Through the PVD Phenomics Program) to determine clinical and echocardiographic differences associated with increasing pulmonary vascular resistance severity. Right heart chamber size and function were qualitatively assessed using a percentile-based approach above the median values to create a clinical grading system for right heart adaptation. The relationship between echocardiographic categories and all-cause mortality was examined using survival analyses adjusted for potential confounders. RESULTS: A stepwise increase in adverse right heart remodeling was observed with a concomitant decrease in functional parameters by pulmonary vascular resistance strata ( P <0.001 for all). Mild, moderate, and severe categories of right heart chamber size and dysfunction were defined using a percentile-based approach across the spectrum of PVD. During a median follow-up of 2.07 years (interquartile range, 1.23–3.01 years), 130 participants died (11.4%). Progressive pulmonary vascular resistance increase and 2DE evidence of right heart dysfunction inclusive of fractional area change, and right ventricular global longitudinal strain were independently associated with increased all-cause mortality risk in multivariate analysis adjusted for age, disease duration, and male sex. CONCLUSIONS: In this well-characterized sample of adults with diverse etiologies and varying PVD severity, we define categories of abnormal right heart chamber size and function. Further, we demonstrate a stepwise relationship between these categories of abnormal morphology and function and all-cause mortality. Defining grades of right ventricular dysfunction in individuals with known PVD has important clinical implications for monitoring disease progression and response to therapies.

Introduction Surgical site infections (SSI) continue to be a risk associated with surgery. The Centers for Disease Control (CDC) uses surgical wound class (SWC) to predict SSI postoperatively. Prior studies have shown that the current wound class definitions are unreliable for surgical subspecialties. Therefore, an alternative surgical wound classification (ASWC) was created to more accurately reflect risk of SSI following orthopedic procedures. The purpose of this study was to compare the two systems. Methods Seventy patients who developed 90-day SSI following total joint arthroplasty (TJA) were matched 1:1 to patients without postoperative SSI. The SWC was recorded from operative reports. Wounds were then retrospectively reclassified according to the ASWC based on preoperative history from the medical record. The degree of agreement and degree of association with occurrence of SSI was compared between the two systems. Results The proportion of agreement between the systems was poor (41.4%). The current SWC was associated with risk of SSI in both unadjusted (p=0.045) and multivariable analysis (p=0.050). Comparatively, the ASWC demonstrated a stronger association with SSI in both unadjusted (p=0.001) and multivariable analysis (p=0.001). Conclusion The results of this study suggest that the ASWC is more predictive for SSI following TJA than the current SWC definitions for total joint arthroplasty.