Machine Learning Classification of Pediatric Health Status Based on Cardiorespiratory Signals with Causal and Information Domain Features Applied-An Exploratory Study.

This study aimed to evaluate the accuracy of machine learning (ML) techniques in classifying pediatric individuals-cardiological patients, healthy participants, and athletes-based on cardiorespiratory features from short-term static measurements. It also examined the impact of cardiorespiratory coupling (CRC)-related features (from causal and information domains) on the modeling accuracy to identify a preferred cardiorespiratory feature set that could be further explored for specialized tasks, such as monitoring training progress or diagnosing health conditions. We utilized six self-prepared datasets that comprised various subsets of cardiorespiratory parameters and applied several ML algorithms to classify subjects into three distinct groups.

Validity of the Pneumonitor for Analysis of Short-Term Heart Rate Asymmetry Extended with Respiratory Data in Pediatric Cardiac Patients.

: Wearable technologies have been developed to measure physiological parameters conveniently. To consider the new measurement device valid, the crucial point is to assess its reliability with the gold standard. The study aimed to assess the validity of the Pneumonitor (PM, fs = 250 Hz) for acquisition of 5 min RR intervals (RRi) for analysis of heart rate asymmetry (HRA) in relation to the electrocardiography (ECG, fs = 1000 Hz) in a group of 19 pediatric cardiac patients.

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.

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.

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.

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.

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).

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.

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.

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.

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.

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.

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).

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.

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.

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.

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.

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.

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.

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.

Left ventricular mass normalization in child and adolescent athletes must account for sex differences.

Background: To assess left ventricular hypertrophy, actual left ventricular mass (LVM) normalized for body size has to be compared to the LVM normative data. However, only some published normative echocardiographic data have been produced separately for girls and boys; numerous normative data for the pediatric population are not sex-specific. Thus, this study aimed to assess whether the LVM normative data should be developed separately for girls and boys practicing sports.

Vitamin B Status and Optimal Range for Hemoglobin Formation in Elite Athletes.

Background: Athletes and coaches believe in the ergogenic effect of vitamin B (which results from enhanced erythropoiesis) and they often insist on its unjustified supplementation. Therefore, our study aimed to assess the vitamin B status in Polish elite athletes and its influence on red blood cell parameters.

Methods: In total, 1131 blood samples were collected during six years from 243 track and field athletes divided into strength and endurance groups, as well as according to the declared use of vitamin B injections.

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.

Left ventricular mass normalization for body size in children based on an allometrically adjusted ratio is as accurate as normalization based on the centile curves method.

Background: Normalization for body size is required for reliable left ventricular mass (LVM) evaluation, especially in children due to the large variability of body size. In clinical practice, the allometrically adjusted ratio of LVM to height raised to the power of 2.7 is often used.