CORRELATIONS BETWEEN TRUNK AND BAT KINEMATICS FOR BASEBALL PLAYERS CALCULATED USING BOTH INDIVIDUAL AND GROUP STATISTICS

This study aimed to investigate kinematic parameters associated with high batting velocity by using both group and individual analysis methods. Twenty seven junior baseball players each performed 35 strikes off a tee at speeds of 60, 80 and 100% of maximum; with pelvis, upper-trunk and bat kinematics measured by 3D motion analysis. The maximum values of all kinematic variables were positively associated with bat speed when assessed with both group and individual methods. For variables measured at impact, however, there were very different individual associations; with some participants showing strong positive correlations and others having similarly strong negative correlations with bat speed. These findings indicate that different players use different techniques to achieve high bat speeds

Anthropometric and physiological factors affecting batted ball speed of adolescent baseball players

Fifty-seven junior baseball players performed eight swings off a tee to record ball exit speed, as well as tests of grip strength, standing broad jump, lateral-to-medial (LM) jumps, chin-ups and chest pass with a medicine ball. The height, weight and age of each participant was also recorded. All anthropometric and physiological tests were significantly positively correlated with ball speed (p \u3c 0.05). Collinearity between variables meant that only chest pass (R² = 0.70, p = 0.000), body mass (ΔR² = 0.03, Δp = 0.021) and LM jump (ΔR² = 0.04, Δp = 0.005) made independent contributions to a stepwise linear regression. These findings corroborate the expectation that upper body power is a major determinant of batting speed, with leg power adding an additional, independent contribution to performance

A case study of an 87-year-old male bodybuilder with complex health conditions

This exploratory clinical case report presents an 87-year-old man who began bodybuilding at the age of 76 years and was officially recognised as the world’s oldest competitive bodybuilder, competing until age 83. He has a background of complex health conditions including polio, strokes, cardiac arrest, atrial fibrillation, prostate disease, osteoarthritis, depression, bowel obstruction, reflux, and bladder cancer. Assessments of body composition, bone density, muscle performance, and diet-related practices were performed. The bodybuilder had superior fat-free mass, lower fat mass, and generally greater muscle performance compared to untrained healthy males of a similar age. Commencement of bodybuilding in older age appears to be possible, even with ongoing complex health conditions, and the potential benefits of this practice require systematic investigation in the future

Mobile phone text messaging for medication adherence in secondary prevention of cardiovascular disease.

BACKGROUND: Cardiovascular diseases (CVDs) are the leading cause of death globally, accounting for almost 18 million deaths annually. People with CVDs have a five times greater chance of suffering a recurrent cardiovascular event than people without known CVDs. Although drug interventions have been shown to be cost-effective in reducing the risk of recurrent cardiovascular events, adherence to medication remains suboptimal. As a scalable and cost-effective approach, mobile phone text messaging presents an opportunity to convey health information, deliver electronic reminders, and encourage behaviour change. However, it is uncertain whether text messaging can improve medication adherence and clinical outcomes. This is an update of a Cochrane review published in 2017. OBJECTIVES: To evaluate the benefits and harms of mobile phone text messaging for improving medication adherence in people with CVDs compared to usual care. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, four other databases, and two trial registers. We also checked the reference lists of all primary included studies and relevant systematic reviews and meta-analyses. The date of the latest search was 30 August 2023. SELECTION CRITERIA: We included randomised controlled trials (RCTs) with participants with established arterial occlusive events. We included trials investigating interventions using short message service (SMS) or multimedia messaging service (MMS) with the aim of improving adherence to medication for the secondary prevention of cardiovascular events. The comparator was usual care. We excluded cluster-RCTs and quasi-RCTs. DATA COLLECTION AND ANALYSIS: We used standard Cochrane methods. Our primary outcomes were medication adherence, fatal cardiovascular events, non-fatal cardiovascular events, and combined CVD event. Secondary outcomes were low-density lipoprotein cholesterol for the effect of statins, blood pressure for antihypertensive drugs, heart rate for the effect of beta-blockers, urinary 11-dehydrothromboxane B2 for the antiplatelet effects of aspirin, adverse effects, and patient-reported experience. We used GRADE to assess the certainty of the evidence for each outcome. MAIN RESULTS: We included 18 RCTs involving a total of 8136 participants with CVDs. We identified 11 new studies in the review update and seven studies in the previous version of the review. Participants had various CVDs including acute coronary syndrome, coronary heart disease, stroke, myocardial infarction, and angina. All studies were conducted in middle- and high-income countries, with no studies conducted in low-income countries. The mean age of participants was 53 to 64 years. Participants were recruited from hospitals or cardiac rehabilitation facilities. Follow-up ranged from one to 12 months. There was variation in the characteristics of text messages amongst studies (e.g. delivery method, frequency, theoretical grounding, content used, personalisation, and directionality). The content of text messages varied across studies, but generally included medication reminders and healthy lifestyle information such as diet, physical activity, and weight loss. Text messages offered advice, motivation, social support, and health education to promote behaviour changes and regular medication-taking. We assessed risk of bias for all studies as high, as all studies had at least one domain at unclear or high risk of bias. Medication adherence Due to different evaluation score systems and inconsistent definitions applied for the measurement of medication adherence, we did not conduct meta-analysis for medication adherence. Ten out of 18 studies showed a beneficial effect of mobile phone text messaging for medication adherence compared to usual care, whereas the other eight studies showed either a reduction or no difference in medication adherence with text messaging compared to usual care. Overall, the evidence is very uncertain about the effects of mobile phone text messaging for medication adherence when compared to usual care. Fatal cardiovascular events Text messaging may have little to no effect on fatal cardiovascular events compared to usual care (odds ratio 0.83, 95% confidence interval (CI) 0.47 to 1.45; 4 studies, 1654 participants; low-certainty evidence). Non-fatal cardiovascular events We found very low-certainty evidence that text messaging may have little to no effect on non-fatal cardiovascular events. Two studies reported non-fatal cardiovascular events, neither of which found evidence of a difference between groups. Combined CVD events We found very low-certainty evidence that text messaging may have little to no effect on combined CVD events. Only one study reported combined CVD events, and did not find evidence of a difference between groups. Low-density lipoprotein cholesterol Text messaging may have little to no effect on low-density lipoprotein cholesterol compared to usual care (mean difference (MD) -1.79 mg/dL, 95% CI -4.71 to 1.12; 8 studies, 4983 participants; very low-certainty evidence). Blood pressure Text messaging may have little to no effect on systolic blood pressure (MD -0.93 mmHg, 95% CI -3.55 to 1.69; 8 studies, 5173 participants; very low-certainty evidence) and diastolic blood pressure (MD -1.00 mmHg, 95% CI -2.49 to 0.50; 5 studies, 3137 participants; very low-certainty evidence) when compared to usual care. Heart rate Text messaging may have little to no effect on heart rate compared to usual care (MD -0.46 beats per minute, 95% CI -1.74 to 0.82; 4 studies, 2946 participants; very low-certainty evidence). AUTHORS' CONCLUSIONS: Due to limited evidence, we are uncertain if text messaging reduces medication adherence, fatal and non-fatal cardiovascular events, and combined cardiovascular events in people with cardiovascular diseases when compared to usual care. Furthermore, text messaging may result in little or no effect on low-density lipoprotein cholesterol, blood pressure, and heart rate compared to usual care. The included studies were of low methodological quality, and no studies assessed the effects of text messaging in low-income countries or beyond the 12-month follow-up. Long-term and high-quality randomised trials are needed, particularly in low-income countries

Adaptive Management and the Value of Information: Learning Via Intervention in Epidemiology

Optimal intervention for disease outbreaks is often impeded by severe scientific uncertainty. Adaptive management (AM), long-used in natural resource management, is a structured decision-making approach to solving dynamic problems that accounts for the value of resolving uncertainty via real-time evaluation of alternative models. We propose an AM approach to design and evaluate intervention strategies in epidemiology, using real-time surveillance to resolve model uncertainty as management proceeds, with foot-and-mouth disease (FMD) culling and measles vaccination as case studies. We use simulations of alternative intervention strategies under competing models to quantify the effect of model uncertainty on decision making, in terms of the value of information, and quantify the benefit of adaptive versus static intervention strategies. Culling decisions during the 2001 UK FMD outbreak were contentious due to uncertainty about the spatial scale of transmission. The expected benefit of resolving this uncertainty prior to a new outbreak on a UK-like landscape would be £45–£60 million relative to the strategy that minimizes livestock losses averaged over alternate transmission models. AM during the outbreak would be expected to recover up to £20.1 million of this expected benefit. AM would also recommend a more conservative initial approach (culling of infected premises and dangerous contact farms) than would a fixed strategy (which would additionally require culling of contiguous premises). For optimal targeting of measles vaccination, based on an outbreak in Malawi in 2010, AM allows better distribution of resources across the affected region; its utility depends on uncertainty about both the at-risk population and logistical capacity. When daily vaccination rates are highly constrained, the optimal initial strategy is to conduct a small, quick campaign; a reduction in expected burden of approximately 10,000 cases could result if campaign targets can be updated on the basis of the true susceptible population. Formal incorporation of a policy to update future management actions in response to information gained in the course of an outbreak can change the optimal initial response and result in significant cost savings. AM provides a framework for using multiple models to facilitate public-health decision making and an objective basis for updating management actions in response to improved scientific understanding

COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records

BACKGROUND: Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework. METHODS: In this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status. FINDINGS: Among 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1. INTERPRETATION: Our analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources. FUNDING: British Heart Foundation Data Science Centre, led by Health Data Research UK

The evidence-base and clinical application of anabolic exercise in older adults at high cardiovascular risk

Ageing is associated with an increase in the risk of cardiovascular (CV) mortality, and this risk is elevated in the presence of cardiometabolic disorders such as coronary artery disease (CAD) and type 2 diabetes (T2D). In addition, ageing and disease can negatively impact other physiological variables that are closely linked to cardiovascular risk such as cardiorespiratory fitness (CRF), skeletal muscle volume and function, metabolic function, psychosocial health and functional performance. Resistance exercise provides a potentially safe treatment modality to address many of these impairments in older adults at high CV risk, while concomitantly addressing a range of other co-morbidities associated with older age such as cognitive impairment, peripheral artery disease, kidney disease, cancer, osteoarthritis, osteoporosis and depression. To evaluate the feasibility of resistance exercise in older adults at high CV risk, the aims of this thesis are threefold; (1) evaluate the effects of resistance training on individuals with existing CAD, (2) evaluate the current implementation of resistance training within cardiac rehabilitation settings in Australia, (3) evaluate the effect of a novel resistance training prescription, high-intensity power training, on CRF and other CV risk factors in high risk individuals with CAD and T2D. Collectively, the chapters within this thesis have presented a comprehensive narrative of the inter-relationship between CRF, body composition, metabolic health, CV disease and ageing, and advanced the understanding of how to approach older adults in a more wholistic and evidence-based way to best optimise health and well-being. We have also demonstrated the important role of resistance training in counteracting the deterioration of metabolic and physiological health attributed to age and disease, and its potential application as a central and vital medicine for older adults with benefits extending beyond those discussed in this thesis

Gametophytic and Sporophytic Responses of Pteris spp. to Arsenic

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A case study of an 87-year-old male bodybuilder with complex health conditions

This exploratory clinical case report presents an 87-year-old man who began bodybuilding at the age of 76 years and was officially recognised as the world’s oldest competitive bodybuilder, competing until age 83. He has a background of complex health conditions including polio, strokes, cardiac arrest, atrial fibrillation, prostate disease, osteoarthritis, depression, bowel obstruction, reflux, and bladder cancer. Assessments of body composition, bone density, muscle performance, and diet-related practices were performed. The bodybuilder had superior fat-free mass, lower fat mass, and generally greater muscle performance compared to untrained healthy males of a similar age. Commencement of bodybuilding in older age appears to be possible, even with ongoing complex health conditions, and the potential benefits of this practice require systematic investigation in the future

The evolution of digital health technologies in cardiovascular disease research

Abstract When implemented in practice, digital technologies have shown improvements in morbidity and mortality outcomes in patients with cardiovascular disease (CVD). For scholars, research into digital technologies in cardiovascular care has been relatively recent, thus it is important to understand the history of digital health technology in cardiovascular research—its emergence, rate of growth, hot topics, and its temporal evolution. The aim of this study was to analyse more than 16,000 articles in this domain based on their scientometric indicators. Web of Science (WoS) Core Collection was accessed and searched at several levels, including titles, abstracts, keywords, authors, sources and individual articles. Analysis examined the temporal shifts in research and scholarly focus based on keywords, networks of collaboration, topical divisions in relation to digital technologies, and influential publications. Findings showed this research area is growing exponentially. Co-citation analysis revealed twenty prominent research streams and identified variation in the magnitude of activities in each stream. A recent emergence of research activities in digital technology in cardiovascular rehabilitation (CR), out-of-hospital cardiac arrest (OHCA), and arrythmia research was also demonstrated. Conversely, wearable technologies, activity tracking and electronic medical records research are now past their peak of reported research activity. With increasing amounts of novel technologies becoming available and more patients taking part in remote health care monitoring, further evaluation and research into digital technologies, including their long-term effectiveness, is needed. Furthermore, emerging technologies, which are evaluated and/or validated should be considered for implementation into clinical practice as treatment and prevention modalities for CVD