Faculty of Medicine
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Item type:Publication, Distribution Analysis of Long-Term Heart Rate Variability Versus Blood Glucose(IEEE, 2021-11-15); ; This research explores the class distributions of longterm heart rate variability (HRV) parameters compared to the distribution of glycated hemoglobin (HbAlc) which depicts the long-term blood glucose regulation ability. The goal is to find the optimal HRV parameter and time interval for which it is measured that correlates to the class distribution based on HbAlc the most. The class distribution separability will provide an answer if future highly accurate, precise, and sensitive machine learning classification can be constructed and if so, to aid their interaction with the input data. We found that removing a dataset sample in which at least one feature value is considered an outlier led to much better results. The strongest point-biserial correlations for the class distribution separation were found for 24-hour SDRMSSD-3 (r=−0.43) , 20-hour SDRMSSD-3 (r=−0.34) , and 24-hour ARMSSD-3 (r=−0.33) satisfying the significance p-value threshold ( p≤0.01 ). All correlations were negative, showcasing that lower HRV is associated with worse blood glucose regulation. We observed that the longer the measurement period, the better the point-biserial correlation. The best class distribution separation based on the univariate threshold is achieved for SDRMSSD-3 with ACC=86.52% and a weighted F1 score of 86.71%, making it stand out as the single most valuable HRV parameter when it comes to distinguishing good from bad blood glucose regulation. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Posterior malleolus fractures - review of the current knowledge and single center experience(2021-03); ; - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Posterior malleolus fragment - significance in malleolar fractures(Здружение на физијатри на Р. Македонија, 2022-09); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, ROBSON CLASSIFICATION OF CESAREAN SECTION IN NORTH MACEDONIA - CURRENT TRENDS(Македонско лекарско друштво = Macedonian medical association, 2021); ; ; ; Dalipi, AdelinaAbstract Introduction. Over the last few decades, the global cesarean section rate has significantly increased and reached an unprecedented level. The World Health Organization (WHO) has advised that cesarean section (CS) rates should not rise above 15%. Several classify¬cation systems have been proposed to tackle the increased cesarean section epidemic. Most of the countries have adopted and started using the Robson (10 groups) classification as the best and the one that is the easiest internationally applicable CS classification. Aim. To present the Robson classification as a way to start better classification of cesarean section and hence to reduce the number of unnecessary cesarean section deliveries. Methods: This study was realized at the University Clinic for Gynecology and Obstetrics in Skopje, North Macedonia. It is a retrospective study where two years were compared. Results. The rate of cesarean sections for 2017 was 38.5% and for 2019 42.6%. Categorization of deliveries according to Robson criteria showed a different rate of cesarean section for each subgroup. Discussion. The implementation of the Robson classi-fication in most countries has shown a reduction in the number of cesarean deliveries and thus a reduction in overall maternal and neonatal morbidity and mortality. The analysis has shown that group 5 had the largest number of cesarean section deliveries in both years, 2017 and 2019; these were patients with previous cesarean sections. They were followed by group 1 and 2, or pri¬mi¬para with spontaneous onset and induced delivery. Conclusion. The goal of Robson clasification is to identify the target groups that contribute most in the percentage of cesarean sections and to act on these tar-get groups through appropriate education and training.