Duration of elevated heart rate Is an important predictor of exercise-induced troponin elevation

Background The precise mechanisms causing cardiac troponin (cTn) increase after exercise remain to be determined. The aim of this study was to investigate the impact of heart rate (HR) on exercise‐induced cTn increase by using sports watch data from a large bicycle competition. Methods and Results Participants were recruited from NEEDED (North Sea Race Endurance Exercise Study). All completed a 91‐km recreational mountain bike race (North Sea Race). Clinical status, ECG, blood pressure, and blood samples were obtained 24 hours before and 3 and 24 hours after the race. Participants (n=177) were, on average, 44 years old; 31 (18%) were women. Both cTnI and cTnT increased in all individuals, reaching the highest level (of the 3 time points assessed) at 3 hours after the race (P150 beats per minute was a significant predictor of both cTnI and cTnT, at both 3 and 24 hours after exercise. Neither mean HR nor mean HR in percentage of maximum HR was a significant predictor of the cTn response at 3 and 24 hours after exercise. Conclusions The duration of elevated HR is an important predictor of physiological exercise‐induced cTn elevation.publishedVersio

Myocardial damage during mountain bike race - an analysis of data from Nordsjørittet 2014 (NEEDED study)

Master's thesis in Cybernetics and signal processingDuring Nordsjørittet 2014, blood samples, blood pressure and ECG were systematically gathered from over 1000 contestants. With this gathering of data, there is an opportunity to study the effects an endurance bike race has on presumably healthy individuals. In addition to this data, there are complete data from sports watches from a third of these contestants. When the medical analysis was done, 25 contestants were diagnosed with myocardial damage. Eight of these were from those with sports watches. The motivation for this thesis is to test if the data logged with the sports watches can be used to predict myocardial damage. Or whether this data can be used to separate the contestants with high or low troponin I values. To achieve this, a classification system was designed to test if there are patterns in the sports watch data that can be connected to myocardial damage or troponin I values. As a consequence of variable sampling, the sports watch data were interpolated and smoothed. After this pre-processing, several features were extracted from the sports watches, from a predefined segment in the race. Two different methods, exhaused search and sequential forward selection, were used to select the feature subset maximizing the prediction rate. Furthermore, a Naive Bayes classifier was trained and validated using leave-one-out cross-validation. To measure reliability of the results in the experiments, Matthews correlation coefficient were used. With an achieved prediction rate of 86% and a correlation coefficient of 0.58, the results clearly indicates that the data logged in the sports watches can predict myocardial damage. When testing if the sports watch data can separate the contestants with high or low Tropinin I, the results were inconclusive. Therefore, it is uncertain if this is achievable with the current data. Fjern valgt

A U‑net based approach to epidermal tissue segmentation in whole slide histopathological images

Malignant melanoma is a severe and aggressive type of skin cancer, with a rapid decrease in survival rate if not diagnosed and treated at an early stage. Histopathological examination of hematoxylin and eosin stained tissue biopsies under a light microscope is currently the gold standard for diagnosis. However, this manual examination is a difficult and time-consuming task, and diagnosis is often subject to intra- and inter-observer variability. With more pathology departments starting to convert conventional glass slides into digital resources, a Computer Aided Diagnostic (CAD) system that can automate part of the diagnostic process will help address these challenges. It is expected to reduce examination time, increase diagnostic accuracy, and reduce diagnostic variations. An important initial step in developing such a system is an automated epidermis segmentation algorithm, since several important diagnostic factors are within or seen relatively to the epidermis’ location. In this paper, we propose a new epidermis segmentation technique built on Convolutional Neural Networks. We trained an U-net based architecture end-to-end, with ∼380k overlapping high resolution image patches at 512 × 512 pixels, extracted and augmented from 36 digitized histopathological images from two different clinical sites, to discriminate pixels as either epidermal or non-epidermal. The proposed technique was evaluated on 33 test images, where we achieved a mean Positive Predictive Value at 0.89±0.16, Sensitivity at 0.92±0.1, Dice Similarity Coefficient at 0.89±0.13 and a Matthews Correlation Coefficient at 0.89±0.11, showing a superior performance when compared to existing techniques. Our algorithm also proves to be robust to variations in staining, tissue thickness and laboratory pre-processing.publishedVersio

Duration of elevated heart rate Is an important predictor of exercise-induced troponin elevation

Background The precise mechanisms causing cardiac troponin (cTn) increase after exercise remain to be determined. The aim of this study was to investigate the impact of heart rate (HR) on exercise‐induced cTn increase by using sports watch data from a large bicycle competition. Methods and Results Participants were recruited from NEEDED (North Sea Race Endurance Exercise Study). All completed a 91‐km recreational mountain bike race (North Sea Race). Clinical status, ECG, blood pressure, and blood samples were obtained 24 hours before and 3 and 24 hours after the race. Participants (n=177) were, on average, 44 years old; 31 (18%) were women. Both cTnI and cTnT increased in all individuals, reaching the highest level (of the 3 time points assessed) at 3 hours after the race (P150 beats per minute was a significant predictor of both cTnI and cTnT, at both 3 and 24 hours after exercise. Neither mean HR nor mean HR in percentage of maximum HR was a significant predictor of the cTn response at 3 and 24 hours after exercise. Conclusions The duration of elevated HR is an important predictor of physiological exercise‐induced cTn elevation. Clinical Trial Registration URL: https://www.clinicaltrials.gov/. Unique identifier: NCT02166216

Duration of elevated heart rate Is an important predictor of exercise-induced troponin elevation

Background The precise mechanisms causing cardiac troponin (cTn) increase after exercise remain to be determined. The aim of this study was to investigate the impact of heart rate (HR) on exercise‐induced cTn increase by using sports watch data from a large bicycle competition. Methods and Results Participants were recruited from NEEDED (North Sea Race Endurance Exercise Study). All completed a 91‐km recreational mountain bike race (North Sea Race). Clinical status, ECG, blood pressure, and blood samples were obtained 24 hours before and 3 and 24 hours after the race. Participants (n=177) were, on average, 44 years old; 31 (18%) were women. Both cTnI and cTnT increased in all individuals, reaching the highest level (of the 3 time points assessed) at 3 hours after the race (P150 beats per minute was a significant predictor of both cTnI and cTnT, at both 3 and 24 hours after exercise. Neither mean HR nor mean HR in percentage of maximum HR was a significant predictor of the cTn response at 3 and 24 hours after exercise. Conclusions The duration of elevated HR is an important predictor of physiological exercise‐induced cTn elevation