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ObjectiveTo assess the diagnostic accuracy of antigen compared with reverse transcriptase (RT)-PCR testing in an asymptomatic athlete screening programme and to monitor infection in college athletes.MethodsQuidel Sofia-2 SARS-CoV-2 Antigen Tests were performed daily before sports participation for football, basketball, wrestling and water polo from 29 September 2020 to 28 February 2021. Paired RT-PCR and antigen tests were performed at least once a week. Positive antigen tests were confirmed with RT-PCR.Results81 175 antigen and 42 187 RT-PCR tests were performed, including 23 462 weekly paired antigen/RT-PCR screening tests in 1931 athletes. One hundred and seventy-two athletes had a positive screening RT-PCR (0.4%), of which 83 (48%) occurred on paired testing days. The sensitivity of antigen tests varied with the frequency of RT-PCR testing and prevalence of COVID-19. The sensitivity of antigen testing was 35.7% (95% CI: 17% to 60%) and specificity 99.8% (95% CI: 99.7% to 99.9%) with once-a-week RT-PCR testing after adjusting for school prevalence. Daily antigen testing was similar to RT-PCR testing two to three times a week in identifying infection. Antigen testing identified infection before the next scheduled PCR on 89 occasions and resulted in 234 days where potentially infectious athletes were isolated before they would have been isolated with RT-PCR testing alone. Two athletic-related outbreaks occurred; 86% of total infections were community acquired.ConclusionAntigen testing has high specificity with a short turnaround time but is not as sensitive as RT-PCR. Daily antigen testing or RT-PCR testing two to three times a week is similar. There are benefits and drawbacks to each testing approach.

ObjectiveTo assess the prevalence and clinical implications of persistent or exertional cardiopulmonary symptoms in young competitive athletes following SARS-CoV-2 infection.MethodsThis observational cohort study from the Outcomes Registry for Cardiac Conditions in Athletes included 3597 US collegiate athletes after SARS-CoV-2 infection. Clinical characteristics, advanced diagnostic testing and SARS-CoV-2-associated sequelae were compared between athletes with persistent symptoms >3 weeks, exertional symptoms on return to exercise and those without persistent or exertional symptoms.ResultsAmong 3597 athletes (mean age 20 years (SD, 1 year), 34% female), data on persistent and exertional symptoms were reported in 3529 and 3393 athletes, respectively. Persistent symptoms >3 weeks were present in 44/3529 (1.2%) athletes with 2/3529 (0.06%) reporting symptoms >12 weeks. Exertional cardiopulmonary symptoms were present in 137/3393 (4.0%) athletes. Clinical evaluation and diagnostic testing led to the diagnosis of SARS-CoV-2-associated sequelae in 12/137 (8.8%) athletes with exertional symptoms (five cardiac involvement, two pneumonia, two inappropriate sinus tachycardia, two postural orthostatic tachycardia syndrome and one pleural effusion). No SARS-CoV-2-associated sequelae were identified in athletes with isolated persistent symptoms. Of athletes with chest pain on return to exercise who underwent cardiac MRI (CMR), 5/24 (20.8%) had probable or definite cardiac involvement. In contrast, no athlete with exertional symptoms without chest pain who underwent CMR (0/20) was diagnosed with probable or definite SARS-CoV-2 cardiac involvement.ConclusionCollegiate athletes with SARS-CoV-2 infection have a low prevalence of persistent or exertional symptoms on return to exercise. Exertional cardiopulmonary symptoms, specifically chest pain, warrant a comprehensive evaluation.

Pelagic Sargassum macroalgal rafts in the North Atlantic support sessile and motile epifauna that attract ecologically and economically important migratory organisms. Three prevalent pelagic Sargassum morphotypes vary in their degree of branching and foliation, and thus have different structural complexities that can influence their respective value as motile epifauna habitat. Sargassum fluitans III and S. natans I have denser foliation, creating a complex habitat; in contrast, S. natans VIII is more open and architecturally simple. In 2015/2016, 373 dip net samples of algae were collected from the Tropical Atlantic, Greater Caribbean, Gulf of Mexico, Gulf Stream, and Sargasso Sea. 20,975 individual motile epifauna from 32 taxa were recorded. Sargassum fluitans III supported higher densities of individuals and greater numbers of taxa than S. natans VIII or S. natans I, a pattern attributed to its more complex architecture and consistent with communities on benthic and floating macroalgae. Most assemblages comprised a few dominant and many rare motile epifauna; when compared to historical studies, dominant motile epifauna had shifted. These findings suggest important differences in ecological value between pelagic Sargassum morphotypes with implications for coastal and pelagic conservation strategies, which warrant consideration given recent shifts in morphotype distribution and recurring pelagic Sargassum inundation events.

The Centers for Disease Control and Prevention (CDC) and US Preventative Services Task Force (USPSTF) have recommended one-time HCV screening for persons born between 1945 and 1965,2 3 yet only 14%–17% of this cohort has been screened for HCV.4 5 To improve adherence to HCV screening recommendations for patients hospitalised at our medical centre, the Division of Infectious Diseases (ID) at the University of Vermont Medical Center (UVMMC) undertook a quality improvement (QI) initiative to screen patients born between 1945 and 1965 who were seen by the ID Consultation Service. Programme costs were calculated based on Medicare reimbursement for laboratory tests (a cost surrogate), estimated physician and analyst hours, and the mean hourly wage for physicians ($98.02) and computer systems analysts ($40.25) reported by the US Bureau of Labor Statistics.6 A secure database (Access 2016; Microsoft Corporation; Redmond, Washington, USA) was used to track screening results and basic demographic information to allow outpatient clinic staff to coordinate follow-up care as needed. According to the policy defining research activities at UVM, this project met criteria for operational improvement activities exempt from ethics review. [...]due to competing information technology demands at the time of our initiative, we were not able to incorporate automated EMR alerts to identify and prompt screening for eligible patients and instead relied on physicians remembering to recommend screening and engage with patients, leading to missed opportunities.10 11 These missed opportunities for screening decreased our sample size and may have impacted our baseline HCV testing positivity rate of only 1%.

Background: As machine learning becomes increasingly utilized in orthopaedic clinical research, the application of machine learning methodology to cohort data from the Multicenter ACL Revision Study (MARS) presents a valuable opportunity to translate data into patient-specific insights. Purpose: To apply novel machine learning methodology to MARS cohort data to determine a predictive model of revision anterior cruciate ligament reconstruction (rACLR) graft failure and features most predictive of failure. Study Design: Cohort study; Level of evidence, 3. Methods: The authors prospectively recruited patients undergoing rACLR from the MARS cohort and obtained preoperative radiographs, surgeon-reported intraoperative findings, and 2- and 6-year follow-up data on patient-reported outcomes, additional surgeries, and graft failure. Machine learning models including logistic regression (LR), XGBoost, gradient boosting (GB), random forest (RF), and a validated ensemble algorithm (AutoPrognosis) were built to predict graft failure by 6 years postoperatively. Validated performance metrics and feature importance measures were used to evaluate model performance. Results: The cohort included 960 patients who completed 6-year follow-up, with 5.7% (n = 55) experiencing graft failure. AutoPrognosis demonstrated the highest discriminative power (model area under the receiver operating characteristic curve: AutoPrognosis, 0.703; RF, 0.618; GB, 0.660; XGBoost, 0.680; LR, 0.592), with well-calibrated scores (model Brier score: AutoPrognosis, 0.053; RF, 0.054; GB, 0.057; XGBoost, 0.058; LR, 0.111). The most important features for AutoPrognosis model performance were prior compromised femoral and tibial tunnels (placement and size) and allograft graft type used in current rACLR. Conclusion: The present study demonstrated the ability of the novel AutoPrognosis machine learning model to best predict the risk of graft failure in patients undergoing rACLR at 6 years postoperatively with moderate predictive ability. Femoral and tibial tunnel size and position in prior ACLR and allograft use in current rACLR were all risk factors for rACLR failure in the context of the AutoPrognosis model. This study describes a unique model that can be externally validated with larger data sets and contribute toward the creation of a robust rACLR bedside risk calculator in future studies. Registration: NCT00625885 (ClinicalTrials.gov identifier).

Objectives: Patients with anterior cruciate ligament (ACL) injury are at high risk for the development of post-traumatic osteoarthritis (PTOA), despite ACL reconstruction (ACLR). ACL injuries are frequently associated with damage of other structures within the knee, such as the meniscus. The meniscus is an important structure that provides protection for articular cartilage and stabilization of the joint. Long-term studies of PTOA after ACLR mainly used radiographs. Conventional magnetic resonance imaging (MRI) has been used in a limited number of studies to evaluate structural damages, but this only provides information on morphologic changes that occur at relatively late stages of the disease. In this study, we aim to use quantitative MRI (qMRI) to evaluate cartilage and meniscus degeneration in patients at 10 years after ACLR. Methods: This is a multi-site multi-vendor study that involves three sites and two MR platforms (Siemens 3T and Philips 3T). MRI protocols have been harmonized between sites and cross validation data were collected using phantoms. The patients are from a nested cohort within Multicenter Orthopaedic Outcomes Network (MOON) Onsite Cohort at 10 years after ACLR. Inclusion/Exclusion criteria were: 22-50 years old; ACL tear during a sport; no previous knee injury; no graft rupture during follow-up. In this preliminary report, 51 patients (age 32.8 ± 6.4 years; 25 females; body mass index [BMI] 25.7 ± 5.7 kg/m2; 40 hamstring autograft, 9 bone-patellar tendon-bone autograft, and 2 allograft) and 17 healthy control participants (age 30.8 ± 7.8 years; 10 females; BMI 23.8 ± 5.6 kg/m2) were studied. The MRI protocol included high-resolution Dual-Echo Steady State (DESS), and combined gradient echo MAPSS T1ρ and T2 mapping. Cartilage and meniscus were automatically segmented on DESS images using an in-house developed deep-learning model into medial/lateral femoral condyle (MFC/LFC), medial/lateral tibia (MT/LT), trochlear (TRO), and patellar cartilage (PAT), and medial and lateral menisci (MM/LM). Each cartilage compartment was further divided into sub-regions based on a modified MRI Osteoarthritis Knee Score (MOAKS) definition: central and posterior for MFC/LMC (cMFC/cLMC, pMFC/pLMC); anterior, central, and posterior for MT/LT (aMT/aLT, cMT/cLT, pMT/pLT); medial, central, and lateral for PAT/TRO (mPAT/mTRO, cPAT/cTRO, lPAT/lTRO). Menisci were further divided into anterior horn (aMM, aLM), central (body) (cMM, cLM), and posterior horn (pMM, pLM) subregions. These cartilage and menisci subregions were then transformed and overlaid onto the T1ρ and T2 parameter maps after co-registering the DESS image to the first echo of the 3D MAPSS sequence using the Elastix toolbox. T1ρ and T2 parameter maps were obtained by a voxel-wise two-parameter monoexponential fitting. The mean and standard deviation for each subregion was recorded and compared between three knee groups: operated and contralateral knees from patients, and control knees from healthy controls, using a mixed-effects regression model, adjusted for age, sex, and BMI. Results: For cartilage, compared to contralateral knees, operated knees in patients had significantly higher T1ρ and T2 values in MFC, MT, and TRO compartments. Looking into subcompartments, for MFC, MT, and TRO, most of the subcompartments (cMFC, pMFC; cMT, pMT; mTRO, cTRO) showed significantly higher T1ρ and T2 values compared to contralateral knees. For LFC and LT, only the posterior subcompartments showed significantly higher T1ρ and T2 values compared to contralateral knees. For PAT, no significant differences were observed between operated and contralateral knees. Compared to healthy control knees, operated knees in patients had significantly higher T1ρ and T2 values in all the six compartments. Besides, contralateral knees also showed higher T1ρ and T2 values in LFC, LT and PAT compartments compared to healthy control knees (Figure 1 for T1ρ, T2 with similar trend was not shown). For meniscus, no significant differences in T1ρ and T2 values were observed between injured and contralateral knees. Compared to healthy control knees, both operated and contralateral knees in patients had significantly higher T1ρ values in LM and significantly higher T2 values in MM (Figure 2). Conclusions: Cartilage T1ρ and T2 values were higher in operated knees compared to contralateral knees at 10 years after ACLR, except for patellar compartment. In patellar cartilage, no significant differences were observed between sides in patients, but both sides were significantly higher than control knees. Our data showed that contralateral knees after ACLR may not represent ‘healthy controls’ as there might be compensatory changes and early degeneration in contralateral knees as a result of injury and surgery to their other knee. Although we observed this general trend of higher cartilage T1ρ and T2 values in the operated knees compared to contralateral knees, no significant differences were observed in meniscus T1ρ and T2 values between sides in patients, suggesting the timing of cartilage and meniscus degeneration may be different for patients after ACLR. Meniscus T1ρ and T2 values in both sides are higher than control knees, suggesting early degeneration in meniscus in patients in both sides. The results will be confirmed with more patient data being collected in the ongoing study. The relationship between qMRI, morphological tissue changes, and patient-reported outcomes after ACLR will also be evaluated in future work. Figure 1. T1p comparisons of cartilage among operated, contralateral, and healthy control knees. *P < 0.05, **P < 0.01. ***P < 0.001. Figure 2. T1p and T2 comparisons of menisci among operated, contralateral, and healthy control knees. *P < 0.05. **P < 0.01. ***P < 0.001.