High training/competition ratio, less incidence of injury? Professional football calendar exploration

Objectives: This study theorizes that a high training/competition ratio predisposes to fewer injuries in professional footballers. This has not been studied in elite professional players. The objective of this study was to investigate the incidence of injuries in professional players who had a frequency of one competition per week for twelve seasons. Furthermore, it highlights the importance of recovery-training cycles lasting from five to eight days between competitions.MethodThis research is an analysis of prospectively recorded data on injuries in an Argentine professional football team. Data was collected throughout twelve seasons and on a daily basis.ResultsThe evaluated team had a frequency of 3.85 competitions per month and the ratio was 8.4 training hours per match hour throughout this twelve-year study. The injury incidence rate obtained in this investigation was 4.2 per 1000 training and competition hours. The injury incidence rate in training sessions was 2.3 injuries per 1000 training hours. The injury incidence rate in competition was 20.5 injuries per 1000 competition hours. Of 65% of all injuries, players returned to play (RTP) within seven days, with medical and kinesiological treatment customized for each athlete. Comparison tables with European Football are shown.ConclusionsSports calendars with a high training/competence ratio and a recovery/training period lasting from 5 to 8 days between competitions could cause a decrease in injuries requiring longer RTP time and result in a relatively low injury incidence rate in professional footballers. (AU)

Daylight Saving Time Transitions: Impact on Total Mortality.

In Europe and many countries worldwide, a half-yearly changing time scheme has been adopted with the aim of optimizing the use of natural daylight during working hours and saving energy. Because the expected net economic benefit was not achieved, the discussion about the optimal solution has been reopened with a shifted focus on social and health related consequences. We set out to produce evidence for this discussion and analysed the impact of daylight saving time on total mortality of a general population in a time series study on daily total mortality for the years 1970-2018 in the city of Vienna, Austria. Daily deaths were modelled by Poisson regression controlling for seasonal and long-term trend, same-day and 14-day average temperature, humidity, and day of week. During the week after the spring transition a significant increase in daily total mortality of about 3% per day was observed. This was not the case during the week after the fall transition. The increase in daily mortality as observed in the week after spring DST-transition is most likely causally linked to the change in time scheme.

Exponential Family Functional data analysis via a low-rank model.

In many applications, non-Gaussian data such as binary or count are observed over a continuous domain and there exists a smooth underlying structure for describing such data. We develop a new functional data method to deal with this kind of data when the data are regularly spaced on the continuous domain. Our method, referred to as Exponential Family Functional Principal Component Analysis (EFPCA), assumes the data are generated from an exponential family distribution, and the matrix of the canonical parameters has a low-rank structure. The proposed method flexibly accommodates not only the standard one-way functional data, but also two-way (or bivariate) functional data. In addition, we introduce a new cross validation method for estimating the latent rank of a generalized data matrix. We demonstrate the efficacy of the proposed methods using a comprehensive simulation study. The proposed method is also applied to a real application of the UK mortality study, where data are binomially distributed and two-way functional across age groups and calendar years. The results offer novel insights into the underlying mortality pattern.

Emergency department imaging: are weather and calendar factors associated with imaging volume?

AIM: To identify weather and calendar factors that would enable prediction of daily emergency department (ED) imaging volume to aid appropriate scheduling of imaging resources for efficient ED function. MATERIALS AND METHODS: Daily ED triage and imaging volumes for radiography, computed tomography (CT), and ultrasound were obtained from hospital databases for the period between January 2011 and December 2013 at a large tertiary urban hospital with a Level II trauma centre. These data were tabulated alongside daily weather conditions (temperature, wind and precipitation), day of week, season, and holidays. Multivariate analysis was performed. Pearson correlations were used to measure the association between number of imaging studies performed and ED triage volume. RESULTS: For every additional 50 triaged patients, the odds of having high (imaging volume ≥90th percentile) radiography, CT, and ultrasound volume increased by 4.3 times (p<0.001), 1.5 times (p=0.02), and 1.4 times (p=0.02), respectively. Tuesday was an independent predictor of high radiography volume (odds ratio=2.8) and Monday was an independent predictor of high CT volume (odds ratio=3.0). Weekday status was an independent factor increasing the odds of a high US volume compared to Saturday (odds ratios ranging from 5.6-9.8). Weather factors and other calendar variables were not independent predictors of high imaging volume. Using Pearson correlations, ED triage volume correlated with number of radiographs, CT, and ultrasound examinations with r=0.73, 0.37, and 0.41, respectively (p<0.0001). CONCLUSION: As ED triage volume was found to be the only factor associated with imaging volume for all techniques, analysis of predictors of ED triage volumes at a particular healthcare facility would be useful to determine imaging needs. Although calendar and weather factors were found to be minor or non-significant independent predictors of ED imaging utilisation, these may be important in influencing the actual number of ED triages.