Deconstructing Stereotypes: Stature, Match-playing Time, and Performance in Elite Women\u27s World Cup Soccer

Recruiting companies recommend elite female soccer players be ≥165 cm (5\u275″) in stature. This study investigated if stature limits match-playing time and performance in elite World Cup soccer among players, positions, and countries. We hypothesized stature would not affect match-playing time or performance. Descriptive data were collected on 552 players from 2019 FIFA Women\u27s World Cup. Odds ratios determined likelihood of starting for players ≥165 cm. ANOVAs compared playing time between stature groups, among positions, and between countries. Performance factors including assists, goals, attempts, corners, shots blocked, and defending blocks were reported. Independent t-tests compared differences between players (≥165 cm, \u3c 165 cm). Data are reported, mean difference [95% confidence interval] [MD (95%CI)] and effect sizes (ES). On average, 32.3% of players were F = 0.98, p = 0.32), matches (F = 0.27 p = 0.59), or average minutes per match (F = 0.48, p = 0.49) between stature groups, regardless of position. No differences existed in playing time between players ≥165 cm among any positions (p \u3e 0.05), or between countries (p \u3e 0.05). Taller mid-fielders exhibited greater performance in goals, assists, attempts, shots blocked, and defending blocks (MD [95%CI] ES; assists, -0.44[-0.76,-0.11]0.59, p = 0.009; goals, -0.35[-0.69,-0.01]0.44, p = 0.047); attempts, 3.14[1.38, 4.90]0.80, p = 0.001; corners, 2.04[0.12, 3.95]0.48, p = 0.037; shots blocked, 0.96[0.40, 1.51]0.75, p = 0.001; defending blocks, 0.43[0.32,0.82]0.48, p = 0.035), however, actual differences were minimal. Our findings indicate stature does not inhibit playing and performing elite women\u27s soccer, as nearly one-third of players were \u3c165 \u3ecm

Deconstructing stereotypes: Stature, match-playing time, and performance in elite Women's World Cup soccer

Recruiting companies recommend elite female soccer players be ≥165 cm (5′5″) in stature. This study investigated if stature limits match-playing time and performance in elite World Cup soccer among players, positions, and countries. We hypothesized stature would not affect match-playing time or performance. Descriptive data were collected on 552 players from 2019 FIFA Women's World Cup. Odds ratios determined likelihood of starting for players <165 cm and ≥165 cm. ANOVAs compared playing time between stature groups, among positions, and between countries. Performance factors including assists, goals, attempts, corners, shots blocked, and defending blocks were reported. Independent t-tests compared differences between players (≥165 cm, < 165 cm). Data are reported, mean difference [95% confidence interval] [MD (95%CI)] and effect sizes (ES). On average, 32.3% of players were <165 cm. Of total players, no differences existed in total minutes (F = 0.98, p = 0.32), matches (F = 0.27 p = 0.59), or average minutes per match (F = 0.48, p = 0.49) between stature groups, regardless of position. No differences existed in playing time between players <165 cm and ≥165 cm among any positions (p > 0.05), or between countries (p > 0.05). Taller mid-fielders exhibited greater performance in goals, assists, attempts, shots blocked, and defending blocks (MD [95%CI] ES; assists, −0.44[−0.76,−0.11]0.59, p = 0.009; goals, −0.35[−0.69,−0.01]0.44, p = 0.047); attempts, 3.14[1.38, 4.90]0.80, p = 0.001; corners, 2.04[0.12, 3.95]0.48, p = 0.037; shots blocked, 0.96[0.40, 1.51]0.75, p = 0.001; defending blocks, 0.43[0.32,0.82]0.48, p = 0.035), however, actual differences were minimal. Our findings indicate stature does not inhibit playing and performing elite women's soccer, as nearly one-third of players were <165 cm

Corrigendum: Identification of novel anti-amoebic pharmacophores from kinase inhibitor chemotypes

Acanthamoeba species, Naegleria fowleri, and Balamuthia mandrillaris are opportunistic pathogens that cause a range of brain, skin, eye, and disseminated diseases in humans and animals. These pathogenic free-living amoebae (pFLA) are commonly misdiagnosed and have sub-optimal treatment regimens which contribute to the extremely high mortality rates (>90%) when they infect the central nervous system. To address the unmet medical need for effective therapeutics, we screened kinase inhibitor chemotypes against three pFLA using phenotypic drug assays involving CellTiter-Glo 2.0. Herein, we report the activity of the compounds against the trophozoite stage of each of the three amoebae, ranging from nanomolar to low micromolar potency. The most potent compounds that were identified from this screening effort were: 2d (A. castellanii EC50: 0.92 ± 0.3 μM; and N. fowleri EC50: 0.43 ± 0.13 μM), 1c and 2b (N. fowleri EC50s: <0.63 μM, and 0.3 ± 0.21 μM), and 4b and 7b (B. mandrillaris EC50s: 1.0 ± 0.12 μM, and 1.4 ± 0.17 μM, respectively). With several of these pharmacophores already possessing blood–brain barrier (BBB) permeability properties, or are predicted to penetrate the BBB, these hits present novel starting points for optimization as future treatments for pFLA-caused diseases

Harnessing the NEON data revolution to advance open environmental science with a diverse and data-capable community

It is a critical time to reflect on the National Ecological Observatory Network (NEON) science to date as well as envision what research can be done right now with NEON (and other) data and what training is needed to enable a diverse user community. NEON became fully operational in May 2019 and has pivoted from planning and construction to operation and maintenance. In this overview, the history of and foundational thinking around NEON are discussed. A framework of open science is described with a discussion of how NEON can be situated as part of a larger data constellation—across existing networks and different suites of ecological measurements and sensors. Next, a synthesis of early NEON science, based on >100 existing publications, funded proposal efforts, and emergent science at the very first NEON Science Summit (hosted by Earth Lab at the University of Colorado Boulder in October 2019) is provided. Key questions that the ecology community will address with NEON data in the next 10 yr are outlined, from understanding drivers of biodiversity across spatial and temporal scales to defining complex feedback mechanisms in human–environmental systems. Last, the essential elements needed to engage and support a diverse and inclusive NEON user community are highlighted: training resources and tools that are openly available, funding for broad community engagement initiatives, and a mechanism to share and advertise those opportunities. NEON users require both the skills to work with NEON data and the ecological or environmental science domain knowledge to understand and interpret them. This paper synthesizes early directions in the community’s use of NEON data, and opportunities for the next 10 yr of NEON operations in emergent science themes, open science best practices, education and training, and community building

AN ELECTRONIC MEDICAL RECORD BASED ALGORITHM TO TAILOR CARDIOVASCULAR DISEASE PREVENTION USING LIPOPROTEIN(A), APOLIPOPROTEIN B, CHOLESTEROL AND MYOCARDIAL INFARCTION DIAGNOSIS: ABCDS PREVENTION PROGRAM

Therapeutic Area: CVD Prevention – Primary and Secondary; ASCVD/CVD Risk Assessment; Preventive Cardiology Best Practices Background: According to the 2022 American Heart Association Heart Disease and Stroke Statistics, coronary heart disease remains the leading cause of death attributable to cardiovascular disease (CVD). Opportunity exists to utilize electronic medical records (EMRs) and biomarkers to facilitate early identification of patients at high risk for CVD. Additionally, automatic or opt-out orders are EMR-based tools that have the potential to improve referral rates to prevention programs. The role of cardiovascular biomarkers and electronic medical records (EMRs) in optimizing identification and referral of patients at risk for CVD are explored in the ABCDs PREVENTION program. Methods: A multidisciplinary team of cardiologists, internists, engineers, and clinical informaticists defined the logic for the guideline based ABCDs PREVENTION tool. The EMR algorithm used the cardiovascular risk biomarker thresholds of lipoprotein(a) > 70 nmol/L, apolipoprotein B > 90 mg/dL, low-density lipoprotein cholesterol  > 150 mg/dL, and triglycerides > 200 mg/dL, and/or a diagnosis of ST-elevation myocardial infarction (STEMI) or non-ST-elevation MI (NSTEMI) based on ICD-10 codes to generate automatic referrals to (1) cardiac rehabilitation (CR), (2) the advanced lipid disorders clinic, and/or (3) Corrie Cardiovascular Health Program (Figure 1). Results: In a test environment, the algorithm was applied to 27 patients identified by the clinical team with STEMI or NSTEMI. The algorithm was 90% successful in triggering automatic referrals to CR and Corrie. Fail rates can be attributed to our current algorithm not detecting some ICD codes related to NSTEMI. The automatic referral to lipid disorders clinic based on abnormal lipid biomarkers is now live and undergoing automation optimization to validate accuracy. Conclusion: Building an EMR-based algorithm to individualize CVD prevention using cardiovascular risk biomarkers and diagnoses may enable early identification and intervention on high-risk patients. Future directions include applying the algorithm to clinical decision support tools as well as an automated order set to increase referral rates to evidenced-based programs focused on primary and secondary CVD prevention. Ultimately, use analysis will determine if the algorithm improves referral rates to CR, lipid clinic, and the Corrie Cardiovascular Health Program to improve access to these evidence-based services

Heterogeneity in Cardiovascular Disease Risk Factor Prevalence Among White, African American, African Immigrant, and Afro‐Caribbean Adults: Insights From the 2010–2018 National Health Interview Survey

Background In the United States, Black adults have higher rates of cardiovascular disease (CVD) risk factors than White adults. However, it is unclear how CVD risk factors compare between Black ethnic subgroups, including African Americans (AAs), African immigrants (AIs), and Afro‐Caribbeans, and White people. Our objective was to examine trends in CVD risk factors among 3 Black ethnic subgroups and White adults between 2010 and 2018. Methods and Results A comparative analysis of the National Health Interview Survey was conducted among 452 997 participants, examining sociodemographic characteristics and trends in 4 self‐reported CVD risk factors (hypertension, diabetes, overweight/obesity, and smoking). Generalized linear models with Poisson distribution were used to obtain predictive probabilities of the CVD risk factors. The sample included 82 635 Black (89% AAs, 5% AIs, and 6% Afro‐Caribbeans) and 370 362 White adults. AIs were the youngest, most educated, and least insured group. AIs had the lowest age‐ and sex‐adjusted prevalence of all 4 CVD risk factors. AAs had the highest prevalence of hypertension (2018: 41.9%) compared with the other groups. Overweight/obesity and diabetes prevalence increased in AAs and White adults from 2010 to 2018 (P values for trend <0.001). Smoking prevalence was highest among AAs and White adults, but decreased significantly in these groups between 2010 and 2018 (P values for trend <0.001), as compared with AIs and Afro‐Caribbeans. Conclusions We observed significant heterogeneity in CVD risk factors among 3 Black ethnic subgroups compared with White adults. There were disparities (among AAs) and advantages (among AIs and Afro‐Caribbeans) in CVD risk factors, suggesting that race alone does not account for disparities in CVD risk factors

Using rapid response system trigger clusters to characterize patterns of clinical deterioration among hospitalized adult patients

Background: Many rapid response system (RRS) events are activated using multiple triggers. However, the patterns in which multiple RRS triggers occur together to activate RRS events are unknown. The purpose of this study was to identify these patterns (RRS trigger clusters) and determine their association with outcomes among hospitalized adult patients. Methods: RRS events among adult patients from January 2015 to December 2019 in the Get With The Guidelines- Resuscitation registry\u27s MET module were examined (n = 134,406). Cluster analysis methods were performed to identify RRS trigger clusters. Pearson\u27s chi-squared and ANOVA tests were used to examine differences in patient characteristics across RRS trigger clusters. Multilevel logistic regressions were used to examine the associations between RRS trigger clusters and outcomes. Results: Six RRS trigger clusters were identified. Predominant RRS triggers for each cluster were: tachypnea, new onset difficulty in breathing, decreased oxygen saturation (Cluster 1); tachypnea, decreased oxygen saturation, staff concern (Cluster 2); respiratory depression, decreased oxygen saturation, mental status changes (Cluster 3); tachycardia, staff concern (Cluster 4); mental status changes (Cluster 5); hypotension, staff concern (Cluster 6). Significant differences in patient characteristics were observed across clusters. Patients in Clusters 3 and 6 had an increased likelihood of in-hospital cardiac arrest (p \u3c 0.01). All clusters had an increased risk of mortality (p \u3c 0.01). Conclusions: We discovered six novel RRS trigger clusters with differing relationships to adverse patient outcomes. RRS trigger clusters may prove crucial in clarifying the associations between RRS events and adverse outcomes and aiding in clinician decision-making during RRS events

Differential ability of Staphylococcus aureus to cause infective endocarditis and lethal sepsis in rabbits

Staphylococcus aureus is a major cause of infective endocarditis (IE) and sepsis. In addition, 50% of IE survivors develop strokes and metastatic abscesses due to the release of emboli from infected valves. Both methicillin-resistant (MRSA) and methicillin-sensitive (MSSA) strains cause IE and sepsis, and they may be categorized by pulsed-field gel electrophoresis, for example clonal types USA200, 300, and 400. We hypothesize that secreted virulence factors contribute to their differential ability to cause IE and/or sepsis. Rabbits are an excellent model for studying IE, which over the course of 4 days are monitored for development of vegetations (the hallmark signs of IE), and sepsis, as S. aureus are administered intravenously. Rabbit cardiac physiology is similar to humans, and rabbits exhibit susceptibility to superantigens and cytolysins produced by these clonal types of S. aureus. We examined the differential ability of community-associated MRSA and MSSA strains (5 USA200 or related strain FRI1169, 3 USA300, and 2 USA400) to cause vegetations versus lethal sepsis in rabbits. USA200 and related strain FRI1169 exhibited intermediate LD50s in sepsis (5x106-5x108) colony-forming units (CFUs), and 4/5 caused significant IE. In contrast, USA300 strains were highly effective in causing lethal sepsis (LD50s of 1 x 106-5 x 107 CFUs) but were minimally capable of causing IE. USA300 variant strain Newman was not highly lethal (LD50 of 2 x 109 CFUs) but was highly effective in causing IE. USA400 strains were both highly lethal (LD50s of 1 x 107-5 x 107 CFUs) and highly effective causes of IE. Additional studies showed that phenol soluble modulins produced by FRI1169 were important for sepsis but did not contribute to IE. Our studies show that these clonal groups of S. aureus have differential abilities to cause IE and lethal sepsis and suggest that secreted virulence factors, including superantigens and cytolysins, account for these differences

Presentation1_Deconstructing stereotypes: Stature, match-playing time, and performance in elite Women's World Cup soccer.zip

Recruiting companies recommend elite female soccer players be ≥165 cm (5′5″) in stature. This study investigated if stature limits match-playing time and performance in elite World Cup soccer among players, positions, and countries. We hypothesized stature would not affect match-playing time or performance. Descriptive data were collected on 552 players from 2019 FIFA Women's World Cup. Odds ratios determined likelihood of starting for players  0.05), or between countries (p > 0.05). Taller mid-fielders exhibited greater performance in goals, assists, attempts, shots blocked, and defending blocks (MD [95%CI] ES; assists, −0.44[−0.76,−0.11]0.59, p = 0.009; goals, −0.35[−0.69,−0.01]0.44, p = 0.047); attempts, 3.14[1.38, 4.90]0.80, p = 0.001; corners, 2.04[0.12, 3.95]0.48, p = 0.037; shots blocked, 0.96[0.40, 1.51]0.75, p = 0.001; defending blocks, 0.43[0.32,0.82]0.48, p = 0.035), however, actual differences were minimal. Our findings indicate stature does not inhibit playing and performing elite women's soccer, as nearly one-third of players were <165 cm.</p

Presentation2_Deconstructing stereotypes: Stature, match-playing time, and performance in elite Women's World Cup soccer.zip

Recruiting companies recommend elite female soccer players be ≥165 cm (5′5″) in stature. This study investigated if stature limits match-playing time and performance in elite World Cup soccer among players, positions, and countries. We hypothesized stature would not affect match-playing time or performance. Descriptive data were collected on 552 players from 2019 FIFA Women's World Cup. Odds ratios determined likelihood of starting for players  0.05), or between countries (p > 0.05). Taller mid-fielders exhibited greater performance in goals, assists, attempts, shots blocked, and defending blocks (MD [95%CI] ES; assists, −0.44[−0.76,−0.11]0.59, p = 0.009; goals, −0.35[−0.69,−0.01]0.44, p = 0.047); attempts, 3.14[1.38, 4.90]0.80, p = 0.001; corners, 2.04[0.12, 3.95]0.48, p = 0.037; shots blocked, 0.96[0.40, 1.51]0.75, p = 0.001; defending blocks, 0.43[0.32,0.82]0.48, p = 0.035), however, actual differences were minimal. Our findings indicate stature does not inhibit playing and performing elite women's soccer, as nearly one-third of players were <165 cm.</p