Heart rate dynamics and asymmetry during sympathetic activity stimulation and post-stimulation recovery in ski mountaineers-a pilot exploratory study.

There is a lack of studies on non-linear heart rate (HR) variability in athletes. We aimed to assess the usefulness of short-term HR dynamics and asymmetry parameters to evaluate the neural modulation of cardiac activity based on non-stationary RR interval series by studying their changes during sympathetic nervous system activity stimulation (isometric handgrip test) and post-stimulation recovery in professional ski mountaineers. The correlation between the changes in the parameters and the respiratory rate (RespRate) and also the duration of the career was analyzed. Short-term (5 min) and ultra-short-term (1 min) rates of patterns with no variations (0V), number of acceleration runs of length 1 (AR1), and short-term Porta's Index were greater, whereas Guzik's Index (GI) was smaller during sympathetic stimulation compared to rest. GI increased and the number of AR1 decreased during recovery. Greater increases in GI and RMSSD were associated with greater decreases in RespRate during recovery. Greater increases in RespRate from rest to short-term sympathetic stimulation were associated with greater increases in 0V (Max-min method) and AR1 but also with greater decreases in decelerations of short-term variance and accelerations and decelerations of long-term variance. Greater increases in 0V (Max-min method) and number of AR1 during sympathetic stimulation were associated with a shorter career duration. Greater decreases in these parameters during recovery were associated with a longer career duration. Changes in measures of HR dynamics and asymmetry, calculated based on short-term non-stationary RRi time series induced by sympathetic stimulation and post-stimulation recovery, reflected sympathovagal shift and were associated with condition-related alterations in RespRate and career duration in athletes who practice ski mountaineering.

Prediction of peak oxygen consumption using cardiorespiratory parameters from warmup and submaximal stage of treadmill cardiopulmonary exercise test.

This study investigates the quality of peak oxygen consumption (VO2peak) prediction based on cardiac and respiratory parameters calculated from warmup and submaximal stages of treadmill cardiopulmonary exercise test (CPET) using machine learning (ML) techniques and assesses the importance of respiratory parameters for the prediction outcome. The database consists of the following parameters: heart rate (HR), respiratory rate (RespRate), pulmonary ventilation (VE), oxygen consumption (VO2) and carbon dioxide production (VCO2) obtained from 369 treadmill CPETs. Combinations of features calculated based on the HR, VE and RespRate time-series from different stages of CPET were used to create 11 datasets for VO2peak prediction. Thirteen ML algorithms were employed, and model performances were evaluated using cross-validation with mean absolute percentage error (MAPE), R2 score, mean absolute error (MAE), and root mean squared error (RMSE) calculated after each iteration of the validation. The results demonstrated that incorporating respiratory-based features improves the prediction of VO2peak. The best results in terms of R2 score (0.47) and RMSE (5.78) were obtained for the dataset which included both cardiac- and respiratory-based features from CPET up to 85% of age-predicted HRmax, while the best results in terms of MAPE (10.5%) and MAE (4.63) were obtained for the dataset containing cardiorespiratory features from the last 30 seconds of warmup. The study showed the potential of using ML models based on cardiorespiratory features from submaximal tests for prediction of VO2peak and highlights the importance of the monitoring of respiratory signals, enabling to include respiratory parameters into the analysis. Presented approach offers a feasible alternative to direct VO2peak measurement, especially when specialized equipment is limited or unavailable.

The discovery of a data-driven causal diagram of sport participation in children and adolescents with heart disease: a pilot study.

The interventions aimed at improving the levels of physical activity (PA) in children and adolescents diagnosed with heart disease did not produce the expected outcomes. Safe participation in sport activities proposed based on actual recommendations could be a solution to promote PA in this population. The aims of this study were to discover a causal diagram of sport participation in children and youth with heart disease and establish the factors that affect and are affected thereof through the use of questionnaires. Furthermore, the study aims to qualitatively assess the reliability of the constructed diagram in comparison with existing medical knowledge. The Greedy Fast Causal Inference method was employed to conduct a data-driven search of the directed acyclic graph that represents the causal relationships within the provided observational data. This causal discovery was performed using the Tetrad software. The analysis involved a cohort of 121 Caucasian patients (50 females) diagnosed with heart disease. The age range of the patients included in the study was 8-17 years. The study findings indicate that the participants engaged in sports presented significantly higher values of health-related quality of life (QoL) and motives for participating in physical and leisure activities. Age appears to be a cause of sport participation. Sport participation appears to be a cause of participation in physical education classes, which in turn appears to be a cause of higher enjoyment. Higher enjoyment appears to be a cause of other motives for participating in physical and leisure activities, as well as a higher score in terms of physical health. The causal diagram provided a graphical representation of the causal relationship between sport participation and better QoL with potential confounders for children and adolescents with heart disease that nearly coincided with the existing literature. Clinical trials should be designed to validate clinical utility of the presented causal diagram.

Evaluation of the performance of GPT-3.5 and GPT-4 on the Polish Medical Final Examination.

The study aimed to evaluate the performance of two Large Language Models (LLMs): ChatGPT (based on GPT-3.5) and GPT-4 with two temperature parameter values, on the Polish Medical Final Examination (MFE). The models were tested on three editions of the MFE from: Spring 2022, Autumn 2022, and Spring 2023 in two language versions-English and Polish. The accuracies of both models were compared and the relationships between the correctness of answers with the answer's metrics were investigated. The study demonstrated that GPT-4 outperformed GPT-3.5 in all three examinations regardless of the language used. GPT-4 achieved mean accuracies of 79.7% for both Polish and English versions, passing all MFE versions. GPT-3.5 had mean accuracies of 54.8% for Polish and 60.3% for English, passing none and 2 of 3 Polish versions for temperature parameter equal to 0 and 1 respectively while passing all English versions regardless of the temperature parameter value. GPT-4 score was mostly lower than the average score of a medical student. There was a statistically significant correlation between the correctness of the answers and the index of difficulty for both models. The overall accuracy of both models was still suboptimal and worse than the average for medical students. This emphasizes the need for further improvements in LLMs before they can be reliably deployed in medical settings. These findings suggest an increasing potential for the usage of LLMs in terms of medical education.

Automatic Heart Rate Detection during Sleep Using Tracheal Audio Recordings from Wireless Acoustic Sensor.

BACKGROUND: Heart rate is an essential diagnostic parameter indicating a patient's condition. The assessment of heart rate is also a crucial parameter in the diagnostics of various sleep disorders, including sleep apnoea, as well as sleep/wake pattern analysis. It is usually measured using an electrocardiograph (ECG)-a device monitoring the electrical activity of the heart using several electrodes attached to a patient's upper body-or photoplethysmography (PPG). METHODS: The following paper investigates an alternative method for heart rate detection and monitoring that operates on tracheal audio recordings. Datasets for this research were obtained from six participants along with ECG Holter (for validation), as well as from fifty participants undergoing a full night polysomnography testing, during which both heart rate measurements and audio recordings were acquired. RESULTS: The presented method implements a digital filtering and peak detection algorithm applied to audio recordings obtained with a wireless sensor using a contact microphone attached in the suprasternal notch. The system was validated using ECG Holter data, achieving over 92% accuracy. Furthermore, the proposed algorithm was evaluated against whole-night polysomnography-derived HR using Bland-Altman's plots and Pearson's Correlation Coefficient, reaching the average of 0.82 (0.93 maximum) with 0 BPM error tolerance and 0.89 (0.97 maximum) at ±3 BPM. CONCLUSIONS: The results prove that the proposed system serves the purpose of a precise heart rate monitoring tool that can conveniently assess HR during sleep as a part of a home-based sleep disorder diagnostics process.

Validity of the Pneumonitor for RR intervals acquisition for short-term heart rate variability analysis extended with respiratory data in pediatric cardiac patients.

BACKGROUND: Breathing pattern alterations change the variability and spectral content of the RR intervals (RRi) on electrocardiogram (ECG). However, there is no method to record and control participants' breathing without influencing its natural rate and depth in heart rate variability (HRV) studies. AIM: This study aimed to assess the validity of the Pneumonitor for acquisition of short-term (5 minutes) RRi in comparison to the reference ECG method for analysis of heart rate (HR) and HRV parameters in the group of pediatric patients with cardiac disease. METHODS: Nineteen patients of both sexes participated in the study. An ECG and Pneumonitor were used to record RRi in 5-minute static rest conditions, the latter also to measure the relative tidal volume and respiratory rate. The validation comprised Student's t-test, Bland-Altman analysis, intraclass correlation coefficient, and Lin's concordance correlation. The possible impact of respiratory activity on the agreement between ECG and the Pneumonitor was also assessed. RESULTS: An acceptable agreement for the number of RRi, mean RR, hazard ratio (HR), and HRV measures calculated based on RRi acquired using the ECG and Pneumonitor was presented. There was no association between the breathing pattern and RRi agreement between devices. CONCLUSIONS: The Pneumonitor might be considered appropriate for cardiorespiratory studies in the group of pediatric cardiac patients in rest condition.

Vaccine versus infection - COVID-19-related loss of training time in elite athletes.

OBJECTIVES: To determine the number of training days lost due to COVID-19 and vaccination against COVID-19 in elite athletes. DESIGN: Retrospective cohort study. METHODS: The questionnaire on the impact of vaccination and COVID-19 on training plans was filled out by 1073 elite Polish athletes who underwent routine medical screening between September and December 2021. RESULTS: COVID-19 was diagnosed in 421 subjects (39 %), of whom 26 % were asymptomatic. On the 10-point scale, <1 % of athletes had perceived severity of the disease above 8, whereas for 64 % it was 4 or below. Vaccination against COVID-19 was administered in 820 athletes (76 %), and adverse events were observed more frequently after the first dose than the second (69 % vs. 47 %). Influence on training (modified or lost) was declared by 369 of 421 (88 %) COVID-19 athletes, and by 226 of 820 vaccinated athletes (28 %). During the observation period, the average number of lost training days was 8.1 for COVID-19 and 2.6 for vaccination (p < 0.001). The cumulative number of person-days lost due to COVID-19 was 1041 versus 295 after vaccination thus, the average loss ratio was 1041/1073 = 0.97 vs. 295/820 = 0.36, respectively, p < 0.01. CONCLUSIONS: Athletes have a considerable loss of training days due to COVID-19. Vaccination against COVID-19 causes significantly smaller and predictable loss. This supports the inclusion of vaccination into prevention policies for athletes whenever they are available.

Causality in cardiorespiratory signals in pediatric cardiac patients.

Four different Granger causality-based methods - one linear and three nonlinear (Granger Causality, Kernel Granger Causality, large-scale Nonlinear Granger Causality, and Neural Network Granger Causality) were used for assessment and causal-based quantification of the respiratory sinus arrythmia (RSA) in the group of pediatric cardiac patients, based on the single-lead ECG and impedance pneumography signals (the latter as the tidal volume curve equivalent). Each method was able to detect the dependency (in terms of causal inference) between respiratory and cardiac signals. The correlations between quantified RSA and the demographic parameters were also studied, but the results differ for each method. Clinical relevance- The presented methods (among which NNGC seems to be the most valid) allow for quantification of RSA and study of dependency between tidal volume and RR intervals which may help to better understand association between respiratory and cardiovascular systems in different populations.

Sleep Position Detection with a Wireless Audio-Motion Sensor-A Validation Study.

It is well documented that body position significantly affects breathing indices during sleep in patients with obstructive sleep apnea. They usually worsen while changing from a non-supine to a supine position. Therefore, body position should be an accurately measured and credible parameter in all types of sleep studies. The aim of this study was to specify the accuracy of a neck-based monitoring device (Clebre, Olsztyn, Poland) mounted at the suprasternal notch, in determining a supine and non-supine sleeping position, as well as specific body positions during sleep, in comparison to polysomnography (PSG). A sleep study (PSG along with a neck-based audio-motion sensor) was performed on 89 consecutive patients. The accuracy in determining supine and non-supine positions was 96.9%±3.9% and 97.0%±3.6%, respectively. For lateral positions, the accuracy was 98.6%±2% and 97.4%±4.5% for the right and left side, respectively. The prone position was detected with an accuracy of 97.3%±5.6%. The study showed a high accuracy in detecting supine, as well as other gross positions, during sleep based on a sensor attached to the suprasternal notch, compared to the PSG study. We feel that the suprasternal notch is a promising area for placing wireless sleep study devices.

Reliability of Symbolic Analysis of Heart Rate Variability and Its Changes During Sympathetic Stimulation in Elite Modern Pentathlon Athletes: A Pilot Study.

Background and Purpose: Most studies on heart rate variability (HRV) in professional athletes concerned linear, time-, and frequency-domain indices, and there is lack of studies on non-linear parameters in this group. The study aimed to determine the inter-day reliability, and group-related and individual changes of short-term symbolic dynamics (SymDyn) measures during sympathetic nervous system activity (SNSa) stimulation among elite modern pentathletes. Methods: Short-term electrocardiographic recordings were performed in stable measurement conditions with a 7-day interval between tests. SNSa stimulation via isometric handgrip strength test was conducted on the second day of study. The occurrence rate of patterns without variations (0V), with one variation (1V), two like (2LV), and two unlike variations (2UV) obtained using three approaches (the Max-min, the σ, and the Equal-probability methods) were analyzed. Relative and absolute reliability were evaluated. Results: All SymDyn indices obtained using the Max-min method, 0V, and 2UV obtained using the σ method, 2UV obtained using the Equal-probability method presented acceptable inter-day reliability (the intraclass correlation coefficient between .91 and .99, Cohen's d between -.08 and .10, the within-subject coefficient of variation between 4% and 22%). 2LV, 2UV, and 0V obtained using the Max-min and σ methods significantly decreased and increased, respectively, during SNSa stimulation-such changes were noted for all athletes. There was no significant association between differences in SymDyn parameters and respiratory rate in stable conditions and while comparing stable conditions and SNSa stimulation. Conclusion: SymDyn indices may be used as reliable non-respiratory-associated parameters in laboratory settings to detect autonomic nervous system (ANS) activity modulations in elite endurance athletes. These findings provide a potential solution for addressing the confounding influence of respiration frequency on HRV-derived inferences of cardiac autonomic function. For this reason, SymDyn may prove to be preferable for field-based monitoring where measurements are unsupervised.

Granger causality test with nonlinear neural-network-based methods: Python package and simulation study.

BACKGROUND AND OBJECTIVE: Causality defined by Granger in 1969 is a widely used concept, particularly in neuroscience and economics. As there is an increasing interest in nonlinear causality research, a Python package with a neural-network-based causality analysis approach was created. It allows performing causality tests using neural networks based on Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), or Multilayer Perceptron (MLP). The aim of this paper is to present the nonlinear method for causality analysis and the created Python package. METHODS: The created functions with the autoregressive (AR) and Generalized Radial Basis Functions (GRBF) neural network models were tested on simulated signals in two cases: with nonlinear dependency and with absence of causality from Y to X signal. The train-test split (70/30) was used. Errors obtained on the test set were compared using the Wilcoxon signed-rank test to determine the presence of the causality. For the chosen model, the proposed method of study the change of causality over time was presented. RESULTS: In the case when X was a polynomial of Y, nonlinear methods were able to detect the causality, while the AR model did not manage to indicate it. The best results (in terms of the prediction accuracy) were obtained for the MLP for the lag of 150 (MSE equal to 0.011, compared to 0.041 and 0.036 for AR and GRBF, respectively). When there was no causality between the signals, none of the proposed and AR models did indicate false causality, while it was detected by GRBF models in one case. Only the proposed models gave the expected results in each of the tested scenarios. CONCLUSIONS: The proposed method appeared to be superior to the compared methods. They were able to detect non-linear causality, make accurate forecasting and not indicate false causality. The created package enables easy usage of neural networks to study the causal relationship between signals. The neural-networks-based approach is a suitable method that allows the detection of a nonlinear causal relationship, which cannot be detected by the classical Granger method. Unlike other similar tools, the package allows for the study of changes in causality over time.

Supine sleep patterns as a part of phenotyping patients with sleep apnea-a pilot study.

PURPOSE: Polysomnography (PSG) is considered the best objective study to diagnose and quantify sleep disorders. However, PSG involves multiple electrodes and is usually performed in a sleep laboratory that in itself may change the physiology of sleep. One of the parameters that can change during PSG is the sleep position, leading to more supine sleep. The aim of this study was to quantify the amount of supine sleep during PSG and compare it to consecutive nights of a home sleep apnea test (HSAT) in the same patients. METHODS: This prospective study evaluated 22 consecutive patients undergoing PSG followed by HSAT. Sleep position was analyzed during PSG and subsequently on 2 to 6 nights (mean 3.7 nights) at home, and the amount of supine sleep was recorded during each night. RESULTS: Of 22 patients, there were 12 men (55%). The median age was 60.0 years for women and 45.5 years for men. Median proportion of supine sleep during PSG and HSAT was 61% and 26% (p < 0.001), respectively. Four "phenotypes" were identified according to their sleep position during PSG and HSAT, with 5 patients sleeping mainly supine during all nights, 7 patients sleeping mainly non-supine during all nights, 3 patients sleeping in different positions during each night, and 7 patients sleeping supine during PSG but non-supine at home, during HSAT. CONCLUSIONS: There is a higher proportion of supine sleep during PSG compared to home sleep. We identified a subgroup of patients who slept mainly supine during PSG and mainly non-supine during HSAT. PSG may overestimate OSA severity in a specific phenotype of patients.

Elite athletes with COVID-19 - Predictors of the course of disease.

OBJECTIVES: The aim of the study was to identify predictors determining the course of COVID-19 and antibody response in elite athletes. DESIGN: Observational study. METHODS: Routine medical screening with physical examination, resting ECG, and laboratory tests including antibody response was performed 12-68 days after the diagnosis of COVID-19 in 111 athletes of different sports. RESULTS: Clinical symptoms were observed in 84% of subjects. The severity of COVID-19 was mild in 82% of athletes and moderate in 2% of cases. Athletes aged above 26 and male were more likely to develop symptomatic COVID-19. Asymptomatic subjects were younger and predominantly female. In 18% of subjects, symptoms were still present 20 (12-68) days (median and range) since positive diagnosis. Antibody response was observed in 88% of athletes, and its magnitude correlated with time since diagnosis of COVID-19 (RT-PCR), fatigue, fever, and conjunctivitis. There were no differences in antibody response between groups distinguished by sports discipline (p = 0.50), and sex (p = 0.59), and antibody response did not correlate with BMI (p = 0.12), age (p = 0.13), the number of symptoms (p = 0.43) or their duration (p = 0.19). CONCLUSIONS: The severity of COVID-19 in elite athletes is predominantly mild and without complications. Athletes can return to sport after two symptom-free weeks and additional heart screening is usually not required. Determination of antibodies has been shown to be a useful indicator of a previous COVID-19 disease, and some symptoms can be used as predictors of antibody response.

Respiratory Activity during Exercise: A Feasibility Study on Transition Point Estimation Using Impedance Pneumography.

The current diagnostic procedures for assessing physiological response to exercise comprise blood lactates measurements, ergospirometry, and electrocardiography. The first is not continuous, the second requires specialized equipment distorting natural breathing, and the last is indirect. Therefore, we decided to perform the feasibility study with impedance pneumography as an alternative technique. We attempted to determine points in respiratory-related signals, acquired during stress test conditions, that suggest a transition similar to the gas exchange threshold. In addition, we analyzed whether or not respiratory activity reaches steady states during graded exercise. Forty-four students (35 females), practicing sports on different levels, performed a graded exercise test until exhaustion on cycloergometer. Eventually, the results from 34 of them were used. The data were acquired with Pneumonitor 2. The signals demonstrated that the steady state phenomenon is not as evident as for heart rate. The results indicated respiratory rate approaches show the transition point at the earliest (more than 6 min before the end of the exercise test on average), and the tidal volume ones at the latest (less than 5 min). A combination gave intermediate findings. The results showed the impedance pneumography appears reasonable for the transition point estimation, but this should be further studied with the reference.

Shortwave infrared otoscopy for diagnosis of middle ear effusions: a machine-learning-based approach.

Otitis media, a common disease marked by the presence of fluid within the middle ear space, imparts a significant global health and economic burden. Identifying an effusion through the tympanic membrane is critical to diagnostic success but remains challenging due to the inherent limitations of visible light otoscopy and user interpretation. Here we describe a powerful diagnostic approach to otitis media utilizing advancements in otoscopy and machine learning. We developed an otoscope that visualizes middle ear structures and fluid in the shortwave infrared region, holding several advantages over traditional approaches. Images were captured in vivo and then processed by a novel machine learning based algorithm. The model predicts the presence of effusions with greater accuracy than current techniques, offering specificity and sensitivity over 90%. This platform has the potential to reduce costs and resources associated with otitis media, especially as improvements are made in shortwave imaging and machine learning.

Safety and Impact on Training of the Influenza Vaccines in Elite Athletes Participating in the Rio 2016 Olympics.

OBJECTIVE: The aim of the study was to evaluate the safety and tolerance of influenza vaccines for the northern and southern hemispheres in Polish elite athletes participating in the Rio 2016 Olympics. DESIGN: Prospective, observational, cohort study. SETTING: Institutional level. PARTICIPANTS: Ninety-seven athletes vaccinated only with the northern hemisphere vaccine; 98 athletes received the southern hemisphere vaccine alone, whereas 39 athletes were vaccinated with both vaccines. INTERVENTIONS: The athletes were vaccinated with a trivalent, inactivated influenza vaccine recommended for the northern hemisphere 2015/2016 and then with the vaccine recommended for the southern hemisphere 2016. Athletes kept a diary of adverse events and effects (if any) on training for 6 days after vaccination. MAIN OUTCOME MEASURES: The percentage of general and local adverse events, number of lost or modified training sessions. RESULTS: Significantly more local adverse events (pain and redness) were found in the group immunized with the vaccine for the northern hemisphere. There were no differences in the frequency of general adverse events and influence on training between groups. Of total 273 athletes who had 1911 training days during 6 days after vaccination, 6 athletes (2.2%) lost 13 training days (0.7%) and 16 athletes (5.9%) had to modify 34 (1.7%) training days within first 2 days after vaccination. CONCLUSIONS: Athletes tolerated influenza immunization well. If they are going to travel to the other hemisphere during the influenza season, the use of the second influenza vaccine should be advised. Athletes should anticipate modification of trainings for 2 days after vaccination.

Temporal orders and causal vector for physiological data analysis.

In addition to the global parameter- and time-series-based approaches, physiological analyses should constitute a local temporal one, particularly when analyzing data within protocol segments. Hence, we introduce the R package implementing the estimation of temporal orders with a causal vector (CV). It may use linear modeling or time series distance. The algorithm was tested on cardiorespiratory data comprising tidal volume and tachogram curves, obtained from elite athletes (supine and standing, in static conditions) and a control group (different rates and depths of breathing, while supine). We checked the relation between CV and body position or breathing style. The rate of breathing had a greater impact on the CV than does the depth. The tachogram curve preceded the tidal volume relatively more when breathing was slower.

A Pilot Study of the Reliability and Agreement of Heart Rate, Respiratory Rate and Short-Term Heart Rate Variability in Elite Modern Pentathlon Athletes.

Research on reliability of heart rate variability (HRV) parameters in athletes has received increasing attention. The aims of this study were to examine the inter-day reliability of short-term (5 min) and ultra-short-term (1 min) heart rate (HR), respiratory rate (RespRate) and HRV parameters, agreement between short-term and ultra-short-term parameters, and association between differences in HR, RespRate and HRV parameters in elite modern pentathletes. Electrocardiographic recordings were performed in stable measurement conditions with a week interval between tests. Relative reliability was evaluated by intra-class correlation coefficients, absolute reliability was evaluated by within-subject coefficient of variation, and agreement was evaluated using Bland-Altman (BA) plot with limits of agreement and defined a priori maximum acceptable difference. Short-term HR, RespRate, log transformed (ln) root mean square of successive normal-to-normal interval differences (lnRMSSD), ln high frequency (lnHF) and SD2/SD1 HRV indices and ultra-short-term HR, RespRate and lnRMSSD presented acceptable, satisfactory inter-day reliability. Although there were no significant differences between short-term and ultra-short-term HR, RespRate and lnRMSSD, no parameter showed acceptable differences with BA plots. Differences in time-domain and non-linear HRV parameters were more correlated with differences in HR than with differences in RespRate. Inverse results were observed for frequency-domain parameters. Short-term HR, RespRate, lnRMSSD, lnHF, and SD2/SD1 and ultra-short-term HR, RespRate and lnRMSSD could be used as reliable parameters in endurance athletes. However, practitioners should interpret changes in HRV parameters with regard to concomitant differences in HR and RespRate and caution should be taken before considering 5 min and 1 min parameters as interchangeable.

Is vitamin D status reflected by testosterone concentration in elite athletes?

Vitamin D is a nutrient whose active form affects tissues as a hormone and possibly enhances performance. One plausible mechanism is by increasing testosterone concentration, which is established as an important factor for athletic performance. Therefore the aim of the study was to examine the relationship between plasma concentration of 25(OH)D and testosterone in Polish elite track and field athletes depending on vitamin D status, season, training period, body composition, sex, type of training, sun exposure and vitamin D supplementation. Plasma concentrations of 25(OH)D and testosterone were measured in all seasons within two years in athletes (70 females, 79 males) who represent strength (n = 103) and endurance (n = 46) kinds of sports, in the preparatorycompetitive season and transition period. There were no differences in 25(OH)D concentration between male and female athletes, insufficiency [25(OH)D < 30 ng/ml] was observed in 32.9%, whereas deficiency [25(OH)D < 20 ng/ ml] in 3.2%. Circannual rhythm was noted for vitamin D but not for testosterone concentration; no correlations between them were found either in strength or endurance athletes or between 25(OH)D and body composition. Testosterone concentration was higher in the transition period than in the preparatory-competition period only in male athletes. Higher 25(OH)D was observed in athletes who trained during winter in Africa (higher sun exposure) or used oral supplementation, whereas the respective testosterone levels were unchanged. In athletes, testosterone concentration did not reflect vitamin D status. The widespread of inadequate vitamin D status among athletes, makes it vital to recommend them the regular monitoring of 25(OH)D concentration and use of reasonable supplementation.