Citations

Abstract Fields, JB, Kuhlman, NM, Jagim, AR, Dulak-Sigler, C, and Jones, MT. Analysis of accumulated workloads and performance testing across a collegiate women's lacrosse season. J Strength Cond Res 37(11): 2213–2221, 2023—Monitoring accumulated workloads, acute:chronic workload ratios (ACWR), and training monotony (TM) are practical methods for monitoring athlete physical stress. Performance testing provides useful information about the changing nature of physical abilities. Therefore, the purpose was to examine differences in accumulated workloads based on session type, explore seasonal trends in ACWR and TM, and assess changes in performance assessments in collegiate women's lacrosse athletes. Athletes, who were identified as starters ( n = 12), wore positional monitoring technology during training sessions ( n = 61) and games ( n = 17) and completed preseason and postseason assessments of speed, agility, power (jump tests), strength, aerobic capacity, and body composition. Separate 1-way analyses of variance were used to determine differences in accumulated workloads for session type and differences in performance assessments from preseason to postseason ( p < 0.05). When compared with games, practice sessions elicited greater ( p < 0.001) accumulated total distance, player load, repeated high-intensity efforts, accelerations, change of direction, explosive efforts, high-speed efforts ( p = 0.002), and high-speed distance ( p = 0.002). Throughout the season, ACWR and TM ranged from 0.16 to 1.40 AU and 0.68–1.69 AU, respectively. The 40-yd sprint ( p < 0.001) and pro-agility ( p < 0.001) improved from preseason to postseason, whereas no changes in aerobic capacity, lower-body power, or strength were observed ( p > 0.05). The monitoring of accumulated loads, ACWR and TM, and performance tests revealed novel information about the seasonal demands of collegiate women's lacrosse. Women lacrosse players are able to improve speed and agility throughout the season, while maintaining strength, power, and endurance, with minimal reductions in fat-free mass.

Abstract Askow, AT, Jennings, W, Jagim, AR, Fields, JB, Beaudoin, RG, Sanchez, GM, Weeks, JE, Oliver, JM, and Jones, MT. Athlete external load measures across a competitive season in high school basketball. J Strength Cond Res 37(11): 2206–2212, 2023—The purpose of this retrospective analysis was to quantify in-season external load and to determine if relationships existed between load metrics and basketball performance. Eleven male high school varsity basketball athletes (n = 11; mass 80.5 ± 9.6 kg, height 190.2 ± 9.4 cm, age 17.6 ± 0.7 years) were monitored across a season. PlayerLoad (PL), PL per minute (PL·min −1 ), total jumps, and explosive movements (EMs) were quantified using a commercially available local positioning unit. Basketball-specific performance metrics, including points scored, points allowed, point differentials, and shooting percentages for each quarter and game, were compiled. Data were analyzed using repeated-measure analysis of variance to evaluate differences in load by starting status, session type, game outcome, and game type. Pearson's correlation coefficients were used to assess relationships between load metrics and basketball performance. Statistical significance was set at p < 0.05. The mean values across 23 games for PL, PL·min −1 , total jumps, and EMs were 457 ± 104 AU, 10.9 ± 1.6 AU, 42.6 ± 9.6, and 46.7 ± 7.2, respectively. Relationships were observed ( p < 0.05) between PL and points scored ( r = 0.38) and free throw percentage ( r = 0.21). Further relationships were observed between PL·min −1 and free throw shooting percentage ( r = −0.27), and between points scored and total jumps ( r = 0.28), and EMs ( r = 0.26). Notable differences in game demands were observed for playing status. Meaningful differences in measures of external load were observed between each quarter of play, with the highest measures evident in quarters 1 and 3. Guards and forwards experienced minimal differences in external load during gameplay, and game outcome did not result in differences. Higher point totals corresponded with higher PL, total jumps, and EM.

Purpose To establish consensus statements on platelet‐rich plasma (PRP) for the treatment of musculoskeletal pathologies. Methods A consensus process on the treatment of PRP using a modified Delphi technique was conducted. Thirty‐five orthopaedic surgeons and sports medicine physicians participated in these consensus statements on PRP. The participants were composed of representatives of the Biologic Association, representing 9 international orthopaedic and musculoskeletal professional societies invited due to their active interest in the study of orthobiologics. Consensus was defined as achieving 80% to 89% agreement, strong consensus was defined as 90% to 99% agreement, and unanimous consensus was indicated by 100% agreement with a proposed statement. Results There was consensus on 62% of statements about PRP. Conclusions (1) PRP should be classified based on platelet count, leukocyte count, red blood count, activation method, and pure‐plasma versus fibrin matrix; (2) PRP characteristics for reporting in research studies are platelet count, leukocyte count, neutrophil count, red blood cell count, total volume, the volume of injection, delivery method, and the number of injections; (3) the prognostic factors for those undergoing PRP injections are age, body mass index, severity/grade of pathology, chronicity of pathology, prior injections and response, primary diagnosis (primary vs postsurgery vs post‐trauma vs psoriatic), comorbidities, and smoking; (4) regarding age and body mass index, there is no minimum or maximum, but clinical judgment should be used at extremes of either; (5) the ideal dose of PRP is undetermined; and (6) the minimal volume required is unclear and may depend on the pathology. Level of Evidence Level V, expert opinion.

Abstract Purpose: Targeting the programmed cell death protein 1 (PD-1)/programmed cell death ligand 1 (PD-L1) interaction has led to durable responses in fewer than half of patients with mismatch repair–deficient (MMR-d) advanced colorectal cancers. Immune contexture, including spatial distribution of immune cells in the tumor microenvironment (TME), may predict immunotherapy outcome. Experimental Design: Immune contexture and spatial distribution, including cell-to-cell distance measurements, were analyzed by multiplex immunofluorescence (mIF) in primary colorectal cancers with d-MMR (N = 33) from patients treated with anti–PD-1 antibodies. By digital image analysis, density, ratio, intensity, and spatial distribution of PD-L1, PD-1, CD8, CD3, CD68, LAG3, TGFβR2, MHC-I, CD14, B2M, and pan-cytokeratin were computed. Feature selection was performed by regularized Cox regression with LASSO, and a proportional hazards model was fitted to predict progression-free survival (PFS). Results: For predicting survival among patients with MMR-d advanced colorectal cancer receiving PD-1 blockade, cell-to-cell distance measurements, but not cell densities or ratios, achieved statistical significance univariately. By multivariable feature selection, only mean number of PD-1+ cells within 10 μm of a PD-L1+ cell was significantly predictive of PFS. Dichotomization of this variable revealed that those with high versus low values had significantly prolonged PFS [median not reached (&gt;83 months) vs. 8.5 months (95% confidence interval (95% CI), 4.7–NR)] with a median PFS of 28.4 months for all patients [adjusted HR (HRadj) = 0.14; 95% CI, 0.04–0.56; P = 0.005]. Expression of PD-1 was observed on CD8+ T cells; PD-L1 on CD3+ and CD8+ T lymphocytes, macrophages (CD68+), and tumor cells. Conclusions: In d-MMR colorectal cancers, PD-1+ to PD-L1+ receptor to ligand proximity is a potential predictive biomarker for the effectiveness of PD-1 blockade.

Total knee arthroplasty (TKA) is a treatment option for individuals with symptomatic osteoarthritis who have failed conservative therapy. In this manuscript the authors describe the pathophysiology of post-operative edema and explore the patient dependent factors potentially contributing to lymphatic dysfunction and thus directly influencing the TKA postoperative course. A proposed multimodal perioperative protocol is presented that focuses on identifying limb edema/lymphedema preoperatively, intraoperative technique changes that may decrease swelling post-TKA.

IMD0 and WLST were assessed for their clinical utility in assessing patients with symptoms of gastroparesis. Low IMD0 is associated with less gastric retention and less heartburn. Volume of water consumed during WLST, while associated with IMD0, has associations with early satiety, postprandial fullness, loss of appetite, and nausea. IMD0 and WLST appear to overlap somewhat in their assessment of gastric physiology in adults with symptoms of gastroparesis but relate to different dyspeptic symptoms.

ABSTRACT Aims Takotsubo syndrome (TTS) is associated with a substantial rate of adverse events. We sought to design a machine learning (ML)-based model to predict the risk of in-hospital death and to perform a clustering of TTS patients to identify different risk profiles. Methods and results A ridge logistic regression-based ML model for predicting in-hospital death was developed on 3482 TTS patients from the International Takotsubo (InterTAK) Registry, randomly split in a train and an internal validation cohort (75% and 25% of the sample size, respectively) and evaluated in an external validation cohort (1037 patients). Thirty-one clinically relevant variables were included in the prediction model. Model performance represented the primary endpoint and was assessed according to area under the curve (AUC), sensitivity and specificity. As secondary endpoint, a K-medoids clustering algorithm was designed to stratify patients into phenotypic groups based on the 10 most relevant features emerging from the main model. The overall incidence of in-hospital death was 5.2%. The InterTAK-ML model showed an AUC of 0.89 (0.85–0.92), a sensitivity of 0.85 (0.78–0.95) and a specificity of 0.76 (0.74–0.79) in the internal validation cohort and an AUC of 0.82 (0.73–0.91), a sensitivity of 0.74 (0.61–0.87) and a specificity of 0.79 (0.77–0.81) in the external cohort for in-hospital death prediction. By exploiting the 10 variables showing the highest feature importance, TTS patients were clustered into six groups associated with different risks of in-hospital death (28.8% vs. 15.5% vs. 5.4% vs. 1.0.8% vs. 0.5%) which were consistent also in the external cohort. Conclusion A ML-based approach for the identification of TTS patients at risk of adverse short-term prognosis is feasible and effective. The InterTAK-ML model showed unprecedented discriminative capability for the prediction of in-hospital death.

This Viewpoint describes the relevance of sex-specific differences in the treatment of migraine, including in evidence from trials of CGRP therapeutics, and the clinical implications for decision-making in practice and trial design.