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EN
INTRODUCTION: Drug-drug interactions (DDIs) constitute a serious health hazard in everyday clinical practice in the intensive care unit (ICU) setting. DDIs can be divided into pharmacokinetic and pharmacodynamic. We sought to investigate the quantity and quality of possible pharmacodynamic DDIs, and their possible side effects in ICU patients over a 12-month period. MATERIAL AND METHODS: This retrospective study covered data on the pharmacological treatment of 43 consecutive patients (11 F, 32 M) aged 62 ± 15 years, hospitalized between 01.2015 and 02.2016 in a mixed ICU. Pharmacokinetic DDIs were identified and graded. Only severe and clinically important DDIs were subjected to further analysis. RESULTS: The median baseline SAPS III was 53 (IQR 38–67) points. The median ICU stay was 12 (6–25) days. The subjects were treated with a median number of 22 (12–27) drugs. We identified 27 (16–41) possible DDIs per patient, including 3 (1–7) DDI of a severe grade. The total number of severe and clinically important pharmacodynamic pDDIs was 1189 and 320 of them were analyzed in details. Despite the gross number of those life-threatening conditions identified, no clinical sequelae of DDIs were recognized. CONCLUSIONS: DDIs as well as their effects are challenging for precise evaluation, especially due to the need for multidrug treatment in ICU patients. Despite the gross number of pDDIs in the ICU setting, further investigations are needed to examine their clinical sequelae.
PL
WSTĘP: Interakcje międzylekowe (DDIs) stanowią poważne zagrożenie dla zdrowia w codziennej praktyce klinicznej na oddziale intensywnej terapii (ICU). DDI dzielą się na farmakokinetyczne i farmakodynamiczne. Celem pracy była ocena częstości występowania i możliwych skutków interakcji farmakodynamicznych na ICU na przestrzeni 12 miesięcy. MATERIAŁ I METODY: Dokonano retrospektywnej analizy kart historii choroby 43 kolejnych pacjentów (11 kobiet, 32 mężczyzn) w wieku 62 ± 15 lat, hospitalizowanych między styczniem 2015 a lutym 2016 r. na wieloprofilowym ICU. Wyszukano i oceniono interakcje farmakodynamiczne. Analizie poddano tylko ciężkie i klinicznie istotne DDI. WYNIKI: Mediana w skali SAPS II wyniosła 53 (IQR 38–67), średni czas pobytu na oddziale 12 (6–12) dni, mediana liczby leków przyjmowanych przez pacjentów – 22 (12–27). Zidentyfikowano 27 (16–41) DDI w przeliczeniu na pacjenta, z czego 3 (1–7) stopnia ciężkiego. Całkowita liczba zidentyfikowanych farmakodynamicznych ciężkich i istotnych klinicznie DDI wynosiła 1189 z czego 320 poddano szczegółowej analizie. Nie badano i nie stwierdzono skutków klinicznych tych DDI. WNIOSKI: Identyfikacja DDI oraz ich skutków klinicznych jest wyzywaniem w praktyce lekarskiej, zwłaszcza przez wzgląd na wielolekowość u pacjentów na ICU. Pomimo znaczącej liczby pDDI w warunkach ICU, ocena ich efektów klinicznych wymaga dalszych analiz.
EN
Introduction. Evaluation of the prognostic potential of the S100B protein and neuron-specific enolase (NSE) as predictors of mortality in critically ill patients in intensive care units (ICU). Materials and Methods. The study was conducted on 62 patients. Basic clinical variables and blood samples for S100B and NSE level testing were obtained during the first four days after admission. Mortality was described as the patient's death during hospitalization in the ICU. Results. 35% of the patients had died. The level of S100B and NSE was significantly higher in non-survivors in comparison with survivors (p=0.007 and p=0.02, respectively). Mortality risk was significantly higher in patients with higher levels of biomarkers than the reference values for S100B (OR 9.00; 95% CI 2.38-33.99; p<0.001) as well as for NSE (OR 5.75; 95%CI 1.31-25.27; p=0.016). Receiver operating characteristic proved that S100B is a better mortality predictor than NSE (AUC 0.76 for S100B and 0.68 for NSE). From all the other variables, the Apache II score turned out to be the only significant predictor of mortality (AUC 0.88). Conclusion. There is a significant correlation between mortality in the ICU and increased serum concentration of S100B and NSE. This correlation is stronger for S100B. Testing for serum levels of S100B and NSE may be useful for prediction of treatment outcomes in the ICU patients.
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2017
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vol. 64
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issue 3
499-501
EN
Many studies have suggested a link between long-term PPI treatment and hypomagnesaemia, though none of them investigated the short-term exposure in high-risk patients. We sought to investigate this issue in 90 critically ill patients. We assessed serum Mg concentrations, necessity of Mg supplementation, PPI dose, duration of PPI therapy and route of administration. In multiple analysis we found that Mg supplementation (positive effect/p=0.03) and enteral route of PPI administration (negative effect/p=0.02) had significant impact on Mg concentration. Although the deleterious relationship between short-term PPI treatment and Mg concentration was found, further studies should be provided to confirm this interesting effect.
EN
INTRODUCTION: Lifestyle is a major determinant of health, but this can change over time. Students tend to have worse health behaviors than adults. This interesting phenomenon has not been verified in relation to the medical community. The aim of this study was to evaluate the lifestyle of physicians and compare it with their habits from their student years. MATERIAL AND METHODS: A cross-sectional study was conducted in 2020 using an original questionnaire assessing various lifestyle elements that were classified as “healthy” or “unhealthy” based on World Health Organization recommendations. 112 physicians (64.3% male and 35.7% female) with a median age of 37 years (IQR 36–38) participated in the study. The results were compared with data obtained in this group from the same questionnaire distributed between 2003 and 2005, i.e. when the subjects were medical students. RESULTS: Significant favorable changes were observed regarding less frequent consumption of meals with a high content of table salt (p < 0.01) and increased consumption of fruits and vegetables (p < 0.01). An increased frequency of coffee drinking was observed (p < 0.01). Their dietary habits and stimulant use remained unchanged. There were no differences in physical activity, the occurrence of stress or its nature (mobilizing or destabilizing). CONCLUSIONS: The lifestyles of physicians do not change significantly compared to their student years, which may be related to the habits from their youth.
PL
WSTĘP: Styl życia jest głównym determinantem zdrowia, może jednak zmieniać się z biegiem lat. Studentów cechują zwykle „gorsze” zachowania zdrowotne niż te u osób dorosłych. To ciekawe zjawisko nie było badane w środowisku lekarskim. Celem pracy była ocena stylu życia lekarzy w porównaniu z ich zachowaniami z lat studenckich. MATERIAŁ I METODY: Badanie przekrojowe przeprowadzono w 2020 r. z wykorzystaniem autorskiego kwestionariusza oceniającego różne elementy stylu życia, które klasyfikowano jako „zdrowe” lub „niezdrowe” na podstawie rekomendacji Światowej Organizacji Zdrowia. W badaniu uczestniczyło 112 lekarzy (64,3% mężczyzn i 35,7% kobiet); mediana wieku wynosiła 37 lat (IQR 36–38). Wyniki porównano z danymi otrzymanymi w tej grupie na podstawie tego samego kwestionariusza dystrybuowanego w latach 2003–2005, tj. gdy badani byli studentami medycyny. WYNIKI: Zaobserwowano istotne, korzystne zmiany dotyczące rzadszego spożycia posiłków z dużą zawartością soli kuchennej (p < 0,01) oraz częstszego spożycia warzyw i owoców (p < 0,01). Zaobserwowano zwiększenie częstości picia kawy (p < 0,01). W pozostałym zakresie nawyki żywieniowe i stosowanie używek pozostawały niezmienne. Nie stwierdzono różnic dotyczących aktywności fizycznej, występowania stresu oraz jego charakteru (mobilizujący/destabilizujący). WNIOSKI: Styl życia lekarzy nie zmienia się znacząco w porównaniu z latami studenckimi, co można wiązać z przyzwyczajeniami z lat młodości.
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