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People with chronic diseases are often limited in their workability. Evaluating and enabling workability is central in rehabilitation. The aim of this study was to evaluate validity and utility of workability assessments in German for persons with chronic diseases.

The clinical management of coronary artery disease and the prevention of acute coronary syndromes require knowledge of the underlying atherosclerotic plaque pathobiology. Hybrid imaging modalities capable of comprehensive assessment of biochemical and morphological plaques features can address this need. Here we report the first implementation of an intravascular catheter system combining fluorescence lifetime imaging (FLIm) with polarization-sensitive optical coherence tomography (PSOCT). This system provides multi-scale assessment of plaque structure and composition via high spatial resolution morphology from OCT, polarimetry-derived tissue microstructure, and biochemical composition from FLIm, without requiring any molecular contrast agent. This result was achieved with a low profile (2.7 Fr) double-clad fiber (DCF) catheter and high speed (100 fps B-scan rate, 40 mm/s pullback speed) console. Use of a DCF and broadband rotary junction required extensive optimization to mitigate the reduction in OCT performance originating from additional reflections and multipath artifacts. This challenge was addressed by the development of a broad-band (UV-visible-IR), high return loss (47 dB) rotary junction. We demonstrate in phantoms, ex vivo swine coronary specimens and in vivo swine heart (percutaneous coronary access) that the FLIm-PSOCT catheter system can simultaneously acquire co-registered FLIm data over four distinct spectral bands (380/20 nm, 400/20 nm, 452/45 nm, 540/45 nm) and PSOCT backscattered intensity, birefringence, and depolarization. The unique ability to collect complementary information from tissue (e.g., morphology, extracellular matrix composition, inflammation) with a device suitable for percutaneous coronary intervention offers new opportunities for cardiovascular research and clinical diagnosis.

Abstract Ultramarathon running is of increasing popularity, where the time-limited 24-hour run is one of the most popular events. Although we have a high scientific knowledge about different topics for this specific race format, we do not know where the best 24-hour runners originate from and where the fastest races are held. The purpose of the present study was to investigate the origin of these runners and the fastest race locations. A machine learning model based on the XG Boost algorithm was built to predict running speed based on the athlete´s age, gender, country of origin and the country where the race takes place. Model explainability tools were used to investigate how each independent variable would influence the predicted running speed. A sample of 171,358 race records from 63,514 unique runners from 73 countries participating in 24-hour races held in 57 countries between 1807 and 2022 was analyzed. Most of the athletes originated from the USA, France, Germany, Great Britain, Italy, Japan, Russia, Australia, Austria, and Canada. Tunisian athletes achieved the fastest average running speed, followed by runners from Russia, Latvia, Lithuania, Island, Croatia, Slovenia, and Israel. Regarding the country of the event, the ranking looks quite similar to the participation by the athlete, suggesting a high correlation between the country of origin and the country of the event. The fastest 24-hour races are recorded in Israel, Romania, Korea, the Netherlands, Russia, and Taiwan. On average, men were 0.4 km/h faster than women, and the fastest runners belonged to age groups 35–39, 40–44, and 45–49 years. In summary, the 24-hour race format is spread over the world, and the fastest athletes mainly originate from Eastern Europe, while the fastest races were organized in European and Asian countries.

Abstract The majority of participants in Ironman triathlon races are age group athletes. We have extensive knowledge about recreational athletes’ training and competition participation. Nonetheless, Ironman age group triathletes must achieve fast race times to qualify for the Ironman World Championship in Hawaii. They can, therefore, benefit from knowing where the fastest Ironman racecourses in the world are. The aim of the present study was to investigate where the fastest Ironman racecourses for age group triathletes are located in the world. Data from 677,702 Ironman age group finishers’ records (544,963 from men and 132,739 from women) originating from 228 countries and participating in 444 events across 66 different Ironman race locations between 2002 and 2022 were analyzed. Data was analyzed through traditional descriptive statistics and with machine learning regression models. Four algorithms were tested (Random Forest Regressor, XG Boost Regressor, Cat Boot Regressor, and Decision Tree Regressor). The models used gender, age group, country of origin, environmental factors (average air and water temperatures), and the event location as independent variables to predict the final overall race time. Despite the majority of successful Ironman age group triathletes originating from the USA (274,553), followed by athletes from the United Kingdom (55,410) and Canada (38,264), these countries exhibited average overall race times that were significantly slower compared to the fastest countries. Most of the triathletes competed in Ironman Wisconsin (38,545), followed by Ironman Florida (38,157) and Ironman Lake Placid (34,341). The fastest overall race times were achieved in Ironman Copenhagen (11.68 ± 1.38 h), followed by Ironman Hawaii (11.72 ± 1.86 h), Ironman Barcelona (11.78 ± 1.43 h), Ironman Florianópolis (11.80 ± 1.52 h), Ironman Frankfurt (12.03 ± 1.38 h) and Ironman Kalmar (12.08 ± 1.47 h). The fastest athletes originated from Belgium (11.48 ± 1.47 h), followed by athletes from Denmark (11.59 ± 1.40 h), Switzerland (11.62 ± 1.49 h), Austria (11.68 ± 1.50), Finland (11.68 ± 1.40 h) and Germany (11.74 ± 15.1 h). Flat running and cycling courses were associated with faster overall race times. Three of the predictive models identified the ‘country’ and ‘age group’ variables as the most important predictors. Environmental characteristics showed the lowest influence regarding the other variables. The origin of the athlete was the most predictive variable whereas environmental characteristics showed the lowest influence. Flat cycling and flat running courses were associated with faster overall race times. The fastest overall race times were achieved mainly in European races such as Ironman Copenhagen, Ironman Hawaii, Ironman Barcelona, Ironman Florianópolis, Ironman Frankfurt and Ironman Kalmar. The fastest triathletes originated from European countries such as Belgium, Denmark, Switzerland, Austria, Finland, and Germany.

Hail represents a major threat to agriculture in Switzerland, and assessments of current and future hail risk are of paramount importance for decision-making in the insurance industry and the agricultural sector. However, relating observational information on hail with crop-specific damage is challenging. Here, we build and systematically assess an open-source model to predict hail damage footprints for field crops (wheat, maize, barley, rapeseed) and grapevine from the operational radar product Maximum Expected Severe Hail Size (MESHS) at different spatial resolutions. To this end, we combine the radar information with detailed geospatial information on agricultural land use and geo-referenced damage data from a crop insurer for 12 recent hail events in Switzerland. We find that for field crops model skill gradually increases when the spatial resolution is reduced from 1 km down to 8 km. For even lower resolutions, the skill is diminished again. In contrast, for grapevine, decreasing model resolution below 1 km tends to reduce skill, which is attributed to the different spatial distribution of field crops and grapevine in the landscape. It is shown that identifying a suitable MESHS thresholds to model damage footprints always involves trade-offs. For the lowest possible MESHS threshold (20 mm) the model predicts damage about twice as often as observed (high frequency bias and false alarm ratio), but it also has a high probability of detection (80 %). The frequency bias decreases for larger thresholds and reaches an optimal value close to 1 for MESHS thresholds of 30–40 mm. However, this comes at the cost of a substantially lower probability of detection (around 50 %), while overall model skill, as measured by the Heidke skill score (HSS), remains largely unchanged (0.41–0.44). We argue that, ultimately, the best threshold therefore depends on the relative costs of a false alarm versus a missed event. Finally, the frequency of false alarms is substantially reduced and skill is improved (HSS = 0.54) when only areas with high cropland density are considered. Results from this simple, open-source model show that modelling of hail damage footprints to crops from single-polarization radar in Switzerland is skilful and is best done at 8 km resolution for field crops and 1 km for grapevine.

Purpose The IRONMAN® triathlon is an endurance multisport discipline of high popularity. Professional IRONMAN® triathletes need to qualify for the IRONMAN® World Championships and, therefore, would benefit from identifying the fastest race courses. Our purpose was to identify the fastest races held for professional IRONMAN® triathletes competing from 2002 to 2022. Methods This was an observational study, sampling 7,078 race records (380 different events in 55 different event locations) of professional IRONMAN® triathletes of both sexes (4,235 males and 2,843 females). We downloaded information about sex, nationality, both split (swimming, cycling, and running) and overall race times, the event location, and the year. Information about race course characteristics, water temperatures, and air temperatures was obtained. Descriptive statistics were calculated for each event location, and factorial ANOVA tests were used to explore the statistical significance of the results. A confidence interval of 95% was adopted. Results The fastest overall IRONMAN® average race times were achieved during the IRONMAN® Tallinn, IRONMAN® Switzerland held in Thun, and IRONMAN® Des Moines. A lake for the swim split characterized the first five courses, while the bike split featured rolling or hilly terrain. For the run split, most of the courses were characterized as flat. For environmental characteristics, lower water and air temperatures also added time to the average finish time. Conclusions Understanding the fastest race courses and their characteristics would assist professional IRONMAN® triathletes in selecting races that offer the optimal conditions for their competition. Fast IRONMAN® race courses typically feature a lakeside swim course, a rolling or hilly bike course, and a flat run course.

ObjectivesPregnant women are at increased risk for severe SARS-CoV-2 infection and adverse neonatal outcome, primarily preterm birth and stillbirth. Our study aimed to investigate to which extent SARS-CoV-2 affects placental tissue and if viral replication within the placenta is evident, thus if there is a correlation between placental damage and adverse pregnancy outcome such as stillbirth.MethodsWe prospectively collected placentas from 61 SARS-CoV-2 infected pregnant women and 10 controls. Histopathological, immunohistochemical, and in situ hybridization studies were performed on all placentas with antibodies for SARS-CoV-2 proteins, ACE2, various immune cells, and inflammatory markers or probes for SARS-CoV-2 genes and an antisense strand.ResultsThe measured scores of SARS-CoV-2 glycoprotein, nucleocapsid, and antisense strand indicating replication correlated with both the severity of maternal symptoms and presence of stillbirth. Specifically, 15/61 placentas exhibited replication, while the three cases with stillbirth had high or maximal replication scores. ACE2-H-score was significantly higher in COVID-19 patients, while the expression of various immune cells did not differ statistically. In multivariate analysis, presence of maternal comorbidities correlated with presence of severe COVID-19 infection.ConclusionWe report evidence of active in vivo SARS-CoV-2 replication in the placenta after maternal infection in pregnancy in a case–control setting in a large population. Intensity of placental viral replication as well as viral levels were higher in women with severe or critical COVID-19 disease, supporting the rationale that severity of maternal SARS-CoV-2 infection could correlate with the severity of placentitis. Replication was maximal in cases of stillbirth, which suggests direct placental involvement in the pathophysiology of this dramatic outcome. Continuing to advocate for preventive measures against COVID-19 during pregnancy, including (re)vaccination, as well as appropriately counseling women with diagnosed infection, are of utter importance.

Abstract Optical coherence tomography (OCT) is a medical imaging method that generates micron-resolution 3D volumetric images of tissues in-vivo. Photothermal (PT)-OCT is a functional extension of OCT with the potential to provide depth-resolved molecular information complementary to the OCT structural images. PT-OCT typically requires long acquisition times to measure small fluctuations in the OCT phase signal. Here, we use machine learning with a neural network to infer the amplitude of the photothermal phase modulation from a short signal trace, trained in a supervised fashion with the ground truth signal obtained by conventional reconstruction of the PT-OCT signal from a longer acquisition trace. Results from phantom and tissue studies show that the developed network improves signal to noise ratio (SNR) and contrast, enabling PT-OCT imaging with short acquisition times and without any hardware modification to the PT-OCT system. The developed network removes one of the key barriers in translation of PT-OCT (i.e., long acquisition time) to the clinic.

Abstract The 50-km ultra-marathon is a popular race distance, slightly longer than the classic marathon distance. However, little is known about the country of affiliation and age of the fastest 50-km ultra-marathon runners and where the fastest races are typically held. Therefore, this study aimed to investigate a large dataset of race records for the 50-km distance race to identify the country of affiliation and the age of the fastest runners as well as the locations of the fastest races. A total of 1,398,845 50-km race records (men, n = 1,026,546; women, n = 372,299) were analyzed using both descriptive statistics and advanced regression techniques. This study revealed significant trends in the performance of 50-km ultra-marathoners. The fastest 50-km runners came from African countries, while the fastest races were found to occur in Europe and the Middle East. Runners from Ethiopia, Lesotho, Malawi, and Kenya were the fastest in this race distance. The fastest 50-km racecourses, providing ideal conditions for faster race times, are in Europe (Luxembourg, Belarus, and Lithuania) and the Middle East (Qatar and Jordan). Surprisingly, the fastest ultra-marathoners in the 50-km distance were found to fall into the age group of 20–24 years, challenging the conventional belief that peak ultra-marathon performance comes in older age groups. These findings contribute to a better understanding of the performance models in 50-km ultra-marathons and can serve as valuable insights for runners, coaches, and race organizers in optimizing training strategies and racecourse selection.

This work aimed to investigate a potential link between serum IL-1β levels in patients with giant cell arteritis (GCA) and their responsiveness to combined anti-IL-6 receptor (IL-6R) and glucocorticoid (GC) treatments within the context of two separate clinical trials. IL-1β levels were analyzed in serum samples of two prospective clinical trials investigating tocilizumab in GCA patients using quantitative Polymerase Chain Reaction (qPCR) based Proximity Ligation Assays (PLA). In the phase II randomized controlled trial, serum samples from five patients were quantified at two critical time points: the commencement of the trial (Week 2) and the conclusion of the trial (Week 52). In the GUSTO trial, serum samples from nine patients were similarly analyzed using PLA at Day 0 and Week 52. Furthermore, for the GUSTO trial, serum samples from 18 patients were assessed for IL-1β and IL-1RN at six time points: days 0, 3, and 10, weeks 4, 24, and 52 by a second assay (Proximity Extension Assay, PEA). PLA results from both studies indicated that IL-1β levels were below 1 pg/mL in most of the patients, resulting in notable signal deviations within the same samples. In the analysis of the GUSTO trial, both PLA and PEA exhibited similar trends in IL-1β variations among patients from day 0 to week 52. Notably, the PEA analysis did not show significant variation over time. Furthermore, we did not find a correlation of IL-1β levels with active disease as compared to remission, but interestingly, the measurement of IL-1β receptor antagonist (IL-1RN) revealed a substantial decrease over time. Our study shows that IL-1RN but not IL-1β concentration in serum samples could be directly related to anti-IL-6R treatment in patients diagnosed with GCA.

Severe hailstorms result in substantial damage to buildings and vehicles, necessitating the quantification of associated risks. Here, we present a novel open-source hail damage model for buildings and cars based on single-polarization radar data and 250 000 geolocated hail damage reports in Switzerland from 2002 to 2021. To this end, we conduct a detailed evaluation of different radar-based hail intensity measures at 1 km resolution and find that the maximum expected severe hail size (MESHS) outperforms the other measures, despite a considerable false-alarm ratio. Asset-specific hail damage impact functions for buildings and cars are calibrated based on MESHS and incorporated into the open-source risk modelling platform CLIMADA. The model successfully estimates the correct order of magnitude for the number of damaged building in 91 %, their total cost in 77 %, the number of damaged vehicles in 74 %, and their total cost in 60 % of over 100 considered large hail events. We found considerable uncertainties in hail damage estimates, which are largely attributable to limitations of radar-based hail detection. Therefore, we explore the usage of crowdsourced hail reports and find substantially improved spatial representation of severe hail for individual events. By highlighting the potential and limitations of radar-based hail size estimates, particularly MESHS, and the utilization of an open-source risk modelling platform, this study represents a significant step towards addressing the gap in risk quantification associated with severe hail events in Switzerland.

Water vapour isotopes reflect the history of moist atmospheric processes encountered by the vapour since evaporating from the ocean, offering potential insights into the controls of shallow trade-wind cumuli. Given that these clouds, particularly their amount at the cloud base level, play an important role in the global radiative budget, improving our understanding of the hydrological cycle associated with them is crucial. This study examines the variability of water vapour isotopes at cloud base in the winter trades near Barbados and explores its connection to the atmospheric circulations ultimately governing cloud fraction. The analyses are based on nested COSMOiso simulations with explicit convection during the EUREC4A (Elucidating the role of clouds-circulation coupling in climate) field campaign. It is shown that the contrasting isotope and humidity characteristics in clear-sky versus cloudy environments at cloud base emerge due to vertical transport on timescales of 4 to 14 h associated with local, convective circulations. In addition, the cloud base isotopes are sensitive to variations in the large-scale circulation on timescales of 4 to 6 d, which shows on average a Hadley-type subsidence but occasionally much stronger descent related to extratropical dry intrusions. This investigation, based on high-resolution isotope-enabled simulations in combination with trajectory analyses, reveals how dynamical processes at different timescales act in concert to produce the observed humidity variations at the base of trade-wind cumuli.

This study aimed to investigate the trends of finishers in the São Silvestre race in Brazil, taking into account sex, age, and performance levels. A total of 31 ​775 runners (women, n ​= ​13 ​847; men, n ​= ​17 ​928), aged (45.2 ​± ​16.8) years, finishers in the São Silvestre race between 2007 and 2021, were considered in the present analysis. Data (event year, date of birth, sex, and race times) were downloaded from the official race website. The man-Whitney U test, Spearman correlation, and robust regression model were computed. Participation increased over time for both sexes. Regarding age groups, “31–40 years” (women) and “> 60 years” (men) were those with the highest number of finishers. We found a decrease in performance across the years (β ​= ​2.45; p ​

Background: For Ironman® triathlon, it has been reported that most of the fnishers and the fastest women and men in Ironman® Hawaii originated from the United States of America (USA). We have, however, no knowledge of where the fastest race courses in the Ironman® 70.3 triathlon took place. We aim to analyse where the Ironman® 70.3 races were held and where the fastest split and overall race times were achieved. Methods: The athletes’ sex, age group, country of origin, and split times for swimming, running, cycling, and transitioning were obtained from the official Ironman® website. To investigate the locations of the fastest Ironman® 70.3 competitions between 2004 and 2020, a full sample of 852,721 qualifying records throughout 197 different event locations was processed. These race records were aggregated by location, and each location’s split and full finish times were calculated. Data analysis was performed first for the full sample (all race records), and then for an elite sub-sample consisting of the top 100 males and top 100 females records in each location. Results: For the full sample, the fastest overall race times were achieved in Ironman® 70.3 Zell am See (Austria). For the top 100 athletes sub-sample, the Ironman® 70.3 European Championship Elsinore and Ironman® 70.3 World Championship were the fastest courses. Conclusion: These results are useful for athletes’ strategic planning and inform event organisers about the strengths of different courses, aiding in the optimisation and promotion of future Ironman® 70.3 races worldwide. Keywords: endurance, performance, half-distance Ironman®, multi-sport, running.

Naturally available, stable, and heavy water molecules such as HDO and H218O have a lower saturation vapour pressure than the most abundant light water molecule H216O; therefore, these heavy water molecules preferentially condense and rain out during cloud formation. Stable water isotope observations thus have the potential to provide information on cloud processes in the trade-wind region, in particular when combined with high-resolution model simulations. In order to evaluate this potential, nested COSMOiso (isotope-enabled Consortium for Small Scale Modelling; Steppeler et al., 2003; Pfahl et al., 2012) simulations with explicit convection and horizontal grid spacings of 10, 5, and 1 km were carried out in this study over the tropical Atlantic for the time period of the EUREC4A (Elucidating the role of clouds-circulation coupling in climate; Stevens et al., 2021) field experiment. The comparison to airborne in situ and remote sensing observations shows that the three simulations are able to distinguish between different mesoscale cloud organisation patterns as well as between periods with comparatively high and low rain rates. Cloud fraction and liquid water content show a better agreement with aircraft observations with higher spatial resolution, because they show strong spatial variations on the scale of a few kilometres. A low-level cold-dry bias, including too depleted vapour in the subcloud and cloud layer and too enriched vapour in the free troposphere, is found in all three simulations. Furthermore, the simulated secondary isotope variable d-excess in vapour is overestimated compared to observations. Special attention is given to the cloud base level, which is the formation altitude of shallow cumulus clouds. The temporal variability of the simulated isotope variables at cloud base agrees reasonably well with observations, with correlations of the flight-to-flight data as high as 0.7 for δ2H and d-excess. A close examination of isotopic characteristics under precipitating clouds, non-precipitating clouds, clear-sky and dry-warm patches at the altitude of cloud base shows that these different environments are represented faithfully in the model with similar frequencies of occurrence, isotope signals, and specific-humidity anomalies as found in the observations. Furthermore, it is shown that the δ2H of cloud base vapour at the hourly timescale is mainly controlled by mesoscale transport and not by local microphysical processes, while the d-excess is mainly controlled by large-scale drivers. Overall, this evaluation of COSMOiso, including the isotopic characterisation of different cloud base environments, suggests that the simulations can be used for investigating the role of atmospheric circulations on different scales for controlling the formation of shallow cumulus clouds in the trade-wind region, as will be done in part 2 of this study.

Abstract Background Giant cell arteritis (GCA) is primarily treated with glucocorticoids (GCs), which have substantial toxicity. Tocilizumab, an interleukin-6-receptor inhibitor (IL-6Ri), showed beneficial effects in GCA, leading to its approval. This study investigated the efficacy and safety of sarilumab (another IL-6Ri) in GCA. Methods This Phase 3, double-blind study comprised a 52-week treatment period and a 24-week follow-up phase. Eligible GCA patients were randomized to receive sarilumab 200 mg (SAR200 + 26W) or 150 mg (SAR150 + 26W) with a 26-week GC taper, or placebo with a 52-week (PBO + 52W) or 26-week (PBO + 26W) GC taper. The primary efficacy endpoint was sustained remission (SR) at week 52. Additional endpoints were SR at week 24, cumulative GC dose, and safety. The study was discontinued prematurely due to protracted recruitment timelines, because of the impact of COVID-19. Therefore, only descriptive statistics were summarized. Results Of the planned 360 subjects, only 83 were randomized and 36 were included in the week 52 analysis. At week 52, 46% (n = 6/13) of patients in SAR200 + 26W, 43% (n = 3/7) in SAR150 + 26W, 30% (n = 3/10) in PBO + 52W, and 0 (n = 0/6) in PBO + 26W taper groups achieved SR. Sensitivity analyses, excluding acute-phase reactants from the SR definition, showed similar results for SAR groups, but 60% (n = 6/10) in PBO + 52W and 17% (n = 1/6) in PBO + 26W taper groups achieved SR at week 52. Similar findings were noted at week 24. The proportions of patients who adhered to GC taper from week 12 through week 52 in each group were as follows: 46% (n = 6/13, SAR200 + 26W), 43% (n = 3/7, SAR150 + 26W), 60% (n = 6/10, PBO + 52W), and 33% (n = 2/6, PBO + 26W). The median actual cumulative GC dose received in the SAR200 + 26W group was lower than other groups. Most patients (80–100%) experienced treatment-emergent adverse events, with similar incidences reported across groups. Conclusions Owing to the small sample size due to the early termination, it is difficult to draw clear conclusions from this study. There were no unexpected safety findings. Trial registration ClinicalTrials.gov NCT03600805. Registered on July 26, 2018.

Abstract Pacing during cycling and running in an IRONMAN triathlon has been investigated in only one study with elite IRONMAN triathletes. We have, however, no knowledge of how professional triathletes pace during an IRONMAN World Championship. To investigate the split-by-split speed, pacing strategies and pacing variability in professional female and male IRONMAN World Championship participants in the fastest IRONMAN World Championship ever in IRONMAN Hawaii 2022. For both cycling and running, 25 specific split times were recorded in each discipline. The best 30 men and 30 women overall were chosen from the official IRONMAN website database for further analysis. They were divided into three performance groups: Top 10, 11–20th place, and 21st–30th place. Mean speed, individual linear regressions with the corresponding correlation coefficients, and coefficient of variation were calculated to assess split-by-split speed, pacing strategies, and pacing variability, respectively. In both men’s and women’s cycling and running segments, the top ten participants exhibited faster split times compared to the slower performance groups. Notably, no discernible differences existed between the 11–20th and 21st–30th place in men’s cycling and women’s running times. Conversely, in men’s running and women’s cycling segments, those in the 11–20th place displayed quicker times than those in the 21st–30th place. In the cycling segment across all groups, men demonstrated a more negative pacing pattern (indicating an increase in speed), whereas women exhibited more consistent pacing. In the running segment, the top 10 men and all women’s groups showcased relatively similar slightly positive pacing profiles. However, men ranking 11–20th and 21st–30th displayed more pronounced positive pacing strategies, implying a more significant decline in speed over time. In terms of cycling, the variability in pacing remained relatively consistent across the three performance groups. Conversely, during the running segment, the top ten male triathletes and those in the 11–20th place displayed lower pacing variability than their counterparts in the 21st–30th position place and all women’s groups. In summary, performance and pacing were examined in professional male and female IRONMAN World Championship participants during IRONMAN Hawaii 2022. Top performers showed faster cycling and running split times, with differences in pacing strategies between sexes. The pacing was more consistent in cycling, while running pacing varied more, particularly among male triathletes in different performance groups.

Abstract Background The sex difference in the three split disciplines (swimming, cycling, and running) and overall race times in triathlon races has mainly been investigated for the Olympic distance and IRONMAN® triathlon formats, but not for the half IRONMAN® distance, i.e., the IRONMAN® 70.3. The aim of the present study was to investigate the sex differences in IRONMAN® 70.3 by age group in 5-year intervals for the split disciplines of this race. Data from 823,459 records (625,393 males and 198,066 females) of all age group finishers (in 5-year intervals) competing in all official IRONMAN® 70.3 races held worldwide between 2004 and 2020 were analyzed, and sex differences by age group and split disciplines were evaluated. Results Males were faster than females in all split disciplines and all age groups. The sex difference was lower in swimming than in cycling and running and less pronounced for triathletes between 20 and 50 years of age. After the age of 60 years, females were able to reduce the sex difference to males in swimming and cycling, but not in running, where the reduction in the sex difference started after the age of 70 years. The lowest sex difference was in the age group 75 + years for swimming and cycling and in the age group 30–34 years for running. Across age groups, the sex difference was U-shaped in swimming and running, with an increase after 18–24 years in swimming and after 40–44 years in running. In contrast, the sex difference decreased continuously with the increasing age for cycling. Conclusions In conclusion, the study found that the sex difference in performance decreases with age in the IRONMAN® 70.3 race distance. However, females did not outperform males at older ages. Notably, sex differences were observed across different disciplines, with swimming displaying lower differences compared to cycling and running. These findings underscore the complex interplay between age, sex, and performance in endurance sports, emphasizing the need for additional research to understand the factors influencing these differences.

Self-regulated learning (SRL) is a crucial competence in our rapidly changing society, yet its systematic promotion in the classroom remains limited. Addressing this gap, this study reports on a teacher-led intervention to promote SRL within reading tasks among 5th and 6th grade students. Although some interventions have been implemented to promote SRL, little attention has been paid to promoting SRL in primary schools. Building on a previous SRL intervention, the current study added cooperative learning among students and parental involvement, two aspects that are assumed to add value when fostering SRL. A randomized controlled field trial was designed to evaluate the effect of an intervention using pre-test, post-test and follow-up measures. A total of 757 students from 40 classes participated in the study. The data were analyzed using a multilevel approach. This study revealed no significant difference in SRL or reading comprehension outcomes in the post-test and the follow-up test between students of the experimental and control group. Further investigations showed that several aspects of treatment integrity had a significant impact on SRL outcome. This study encourages future SRL and reading intervention studies to assess and analyze the multiple aspects of treatment integrity.

Abstract Knowing which discipline contributes most to a triathlon performance is important to plan race pacing properly. To date, we know that the running split is the most decisive discipline in the Olympic distance triathlon, and the cycling split is the most important discipline in the full-distance Ironman® triathlon. However, we have no knowledge of the Ironman® 70.3. This study intended to determine the most crucial discipline in age group athletes competing from 2004 to 2020 in a total of 787 Ironman® 70.3 races. A total of 823,459 athletes (198,066 women and 625,393 men) from 240 different countries were analyzed and recorded in 5-year age groups, from 18 to 75 + years. Correlation analysis, multiple linear regression, and two-way ANOVA were applied, considering p

IntroductionOur study examined 16,611 records of professional triathletes from 163 Ironman® 70.3 races across 97 countries (2004-2020). The aim was to identify the most predictive discipline—swim, bike, or run—for overall race time.MethodsWe used correlation matrices to compare the dependent variable “finish time” with independent variables “swim time,” “bike time,” and “run time.” This analysis was conducted separately for male and female athletes. Additionally, univariate and multiple linear regression models assessed the strength of these associations.ResultsThe results indicated that “bike time” had the strongest correlation with finish time (0.85), followed by “run time” (0.75 for females, 0.82 for males) and “swim time” (0.46 for females, 0.63 for males). Regression models confirmed “bike time” as the strongest predictor of overall race time (R² = 0.8), with “run time” and “swim time” being less predictive.DiscussionThe study concludes that in Ironman 70.3 races, “bike time” is the most significant predictor of overall race performance for both sexes, suggesting a focus on cycling in training and competition strategies. It also highlights a smaller performance gap between genders in swimming than in cycling or running.

The present study intended to determine the nationality of the fastest 100-mile ultra-marathoners and the country/events where the fastest 100-mile races are held. A machine learning model based on the XG Boost algorithm was built to predict the running speed from the athlete's age (Age group), gender (Gender), country of origin (Athlete country) and where the race occurred (Event country). Model explainability tools were then used to investigate how each independent variable influenced the predicted running speed. A total of 172,110 race records from 65,392 unique runners from 68 different countries participating in races held in 44 different countries were used for analyses. The model rates Event country (0.53) as the most important predictor (based on data entropy reduction), followed by Athlete country (0.21), Age group (0.14), and Gender (0.13). In terms of participation, the United States leads by far, followed by Great Britain, Canada, South Africa, and Japan, in both athlete and event counts. The fastest 100-mile races are held in Romania, Israel, Switzerland, Finland, Russia, the Netherlands, France, Denmark, Czechia, and Taiwan. The fastest athletes come mostly from Eastern European countries (Lithuania, Latvia, Ukraine, Finland, Russia, Hungary, Slovakia) and also Israel. In contrast, the slowest athletes come from Asian countries like China, Thailand, Vietnam, Indonesia, Malaysia, and Brunei. The difference among male and female predictions is relatively small at about 0.25 km/h. The fastest age group is 25-29 years, but the average speeds of groups 20-24 and 30-34 years are close. Participation, however, peaks for the age group 40-44 years. The model predicts the event location (country of event) as the most important predictor for a fast 100-mile race time. The fastest race courses were occurred in Romania, Israel, Switzerland, Finland, Russia, the Netherlands, France, Denmark, Czechia, and Taiwan. Athletes and coaches can use these findings for their race preparation to find the most appropriate racecourse for a fast 100-mile race time.

IntroductionMany studies indicate a considerable impact of optimal pacing on long-distance running performance. Given that the amount of carbohydrates in metabolic processes increases supralinearly with the running intensity, we may observe differences between the pacing strategies of two long-distance races and different performance levels of runners. Accordingly, the present study aimed to examine the differences in pacing strategies between marathon and half-marathon races regarding the performance levels of runners.MethodsThe official results and split times from a total of 208,760 (marathon, N = 75,492; half-marathon, N = 133,268) finishers in the “Vienna City Marathon” between 2006 and 2018 were analyzed. The percentage of the average change of speed for each of the five segments (CS 1–5), as well as the absolute change of speed (ACS) were calculated. The CS 1–5 for the marathon are as follows: up to the 10th km, 10th – 20th km, 20th – 30th km, 30th – 40th km, and from the 40th km to the 42.195 km. For the half-marathon, the CS 1–5 are half of the marathon values. Four performance groups were created as quartiles of placement separately for sexes and races: high-level (HL), moderate to high-level (MHL), moderate to low-level (MLL), and low-level (LL).ResultsPositive pacing strategies (i.e., decrease of speed) were observed in all performance groups of both sex and race. Across CS 1–5, significant main effects (p

BACKGROUND: Paediatric inflammatory multisystem syndrome temporally associated with SARS-CoV-2 (PIMS-TS) may occur 4 to 8 weeks after SARS-CoV-2 infection. The acute presentation of PIMS-TS has been well described, but data on longer-term outcomes, particularly cardiac, is scarce. METHODS: This prospective nationwide surveillance study included children and adolescents less than 18 years of age who were hospitalised with PIMS-TS in Switzerland between March 2020 and March 2022. Data was collected from all 29 paediatric hospitals through the Swiss Paediatric Surveillance Unit (SPSU) during hospitalisation and approximately six weeks after discharge. The data was analysed after categorising the participants into three groups based on their admission status to the intensive care unit (ICU) (non-ICU, ICU-moderate) and the requirement for invasive ventilatory and/or inotropic support (ICU-severe). RESULTS: Overall, 204 children were included of whom 194 (95.1%) had follow-up data recorded. Median age was 9.0 years (interquartile range [IQR] 6.0–11.5) and 142 (69.6%) were male. In total, 105/204 (51.5%) required ICU admission, of whom 55/105 (52.4%) received inotropic support and 14/105 (13.3%) mechanical ventilation (ICU-severe group). Echocardiography was performed in 201/204 (98.5%) children; 132 (64.7%) had a cardiac abnormality including left ventricular systolic dysfunction (73 [36.3%]), a coronary artery abnormality (45 [22.4%]), pericardial effusion (50 [24.9%]) and mitral valve regurgitation (60 [29.9%]). Left ventricular systolic dysfunction was present at admission in 62/201 (30.8%) children and appeared during hospitalisation in 11 (5.5%) children. A coronary artery abnormality was detected at admission in 29/201 (14.2%) children and developed during hospitalisation or at follow-up in 13 (6.5%) and 3 (1.5%) children, respectively. None of the children had left ventricular systolic dysfunction at follow-up, but a coronary abnormality and pericardial effusion were found in 12 (6.6%) and 3 (1.7%) children, respectively. School absenteeism at the time of follow-up was more frequent in children who had been admitted to the ICU (2.5% in the non-ICU group compared to 10.4% and 17.6% in the ICU-moderate and ICU-severe group, respectively) (p = 0.011). CONCLUSION: Cardiac complications in children presenting with PIMS-TS are common and may worsen during the hospitalisation. Irrespective of initial severity, resolution of left ventricular systolic dysfunction is observed, often occurring rapidly during the hospitalisation. Most of the coronary artery abnormalities regress; however, some are still present at follow-up, emphasising the need for prolonged cardiac evaluation after PIMS-TS.