Managing the health of the eSport athlete: an integrated health management model.

OBJECTIVES: eSport is a form of electronic gaming, also known as professional or competitive video gaming, and is growing at a rapid pace worldwide. Over 50 US colleges have established varsity gaming teams over the past three years; some colleges offer eSport scholarships as they do for traditional sports. There is little objective research on the health habits of these players who are often placed under the direction of the athletics department on college campuses, and there is currently no health management model on how to treat these new athletes. METHODS: Anonymous electronic surveys were sent to 65 collegiate eSport players from nine universities across the USA and Canada inquiring about gaming and lifestyle habits, and musculoskeletal complaints due to eSport competition. RESULTS: Players practiced between 3 and 10 hours per day. The most frequently reported complaint was eye fatigue (56%), followed by neck and back pain (42%). eSport athletes reported wrist pain (36%) and hand pain (32%). Forty per cent of participants do not participate in any form of physical exercise. Among the players surveyed, only 2% had sought medical attention. CONCLUSION: eSport players, just like athletes in traditional sports, are susceptible to overuse injuries. The most common complaint was eye fatigue, followed by neck and back pain. This study shows eSport athletes are also prone to wrist and hand pain. This paper proposes a health management model that offers a comprehensive medical team approach to prevent and treat eSport athletes.

Utilizing wearable technology to increase physical activity in future physicians: A randomized trial.

This study examined the use of activity trackers alone or combined with weekly communication through email to improve activity and body composition over one academic year in medical students. This randomized clinical trial conducted at the New York Institute of Technology from July 7, 2016 through June 4, 2017 enrolled 120 medical students. The first group (Fitbit-Plus) wore activity trackers and received weekly emails offering fitness challenges and lifestyle modification challenges. The second group (Fitbit-Only) received only activity trackers and did not receive weekly emails. The third group (Control) was asked not to purchase an activity tracker of any kind throughout the study. All groups had a body composition analysis prior to the start of the academic year and at the end of the first academic year. Outcome measures included step count and body composition (body fat percentage and lean body mass). The results showed the overall mean daily steps were greater in the Fitbit-Plus group than the Fitbit-Only group for the academic year (7429 ±â€¯2833 vs. 6483 ±â€¯2359) with only months April and May showing a significant difference between the groups (p = 0.011; p = 0.044). Body fat percentage decreased in the Fitbit-Plus overweight women (2.1 ±â€¯1.6%) lean body mass increased in the Fitbit-Plus group in overweight men (2.4 ±â€¯4.6 lbs.). A subsequent finding of this study showed improved body composition in a small sub-group of over-weight students. Weekly behavioral challenges combined with an activity tracker increased step count in medical students compared to an activity tracker alone. Clinicaltrials.gov Identifier: NCT02778009.

Prospective validation of a prediction model for isolating inpatients with suspected pulmonary tuberculosis.

BACKGROUND: Current guidelines for the control of nosocomial transmission of tuberculosis (TB) recommend respiratory isolation for all patients with suspected TB. Application of these guidelines has resulted in many patients without TB being isolated on admission to the hospital, significantly increasing hospital costs. This study was conducted to prospectively validate a clinical decision rule to predict the need for respiratory isolation in inpatients with suspected TB. METHODS: A cohort of 516 individuals, who presented to 2 New York City hospitals between January 16, 2001, and September 29, 2002, and who were isolated on admission for clinically suspected TB, were enrolled in the study. Face-to-face interviews were conducted to determine the presence of clinical variables associated with TB in the prediction model, including TB risk factors, clinical symptoms, and findings from physical examination and chest radiography. RESULTS: Of the 516 patients, 19 were found to have TB (prevalence, 3.7%; 95% confidence interval [CI], 2.2%-5.7%). The prediction rule had a sensitivity of 95% (95% CI, 74%-100%) and a specificity of 35% (95% CI, 31%-40%). Using a prevalence of TB of 3.7%, the positive predictive value was 9.6% and the negative predictive value was 99.7%. CONCLUSIONS: Among inpatients with suspected active pulmonary TB who are isolated on admission to the hospital, a prediction rule based on clinical and chest radiographic findings accurately identified patients at low risk for TB. Approximately one third of the unnecessary episodes of respiratory isolation could have been avoided had the prediction rule been applied. Future studies should assess the feasibility of implementing the rule in clinical practice.

Perioperative use of beta-blocker in noncardiac surgery: a multicenter educational intervention to achieve best practice guidelines.

Perioperative cardiac ischemia and infarction are important causes of morbidity and mortality in patients undergoing noncardiac surgery. There is now significant evidence that the use of prophylactic beta-adrenergic antagonists among selected patients at risk for perioperative cardiovascular complications is associated with a reduction in myocardial ischemia and cardiac events. Furthermore, consensus guidelines have incorporated the findings of recent studies and provide recommendations for the appropriate utilization of beta-adrenergic antagonists among selected patients. Despite these guidelines, it is unknown to what extent these recommendations have become translated into clinical practice. After measuring perioperative beta-blocker use among participating hospitals within the New York Presbyterian Health Network, we developed a multicenter educational intervention to improve the overall utilization of beta-adrenergic prophylactic therapy in accordance with best practice guidelines. The literature supporting the development of this intervention is presented in this paper, along with the tools that are currently being used for decision support across an academic healthcare network.