102 research outputs found
Ăšjdonságok a krĂłnikus szĂvelĂ©gtelensĂ©g gyĂłgyszeres terápiájában | Novelties in the pharmacological treatment of chronic heart failure
Absztrakt
A krĂłnikus szĂvelĂ©gtelensĂ©g gyĂłgyszeres kezelĂ©sĂ©t illetĹ‘en számos Ăşj vizsgálat
eredményét publikálták az elmúlt években, és 2016-ban megjelent az Európai
KardiolĂłgiai Társaság (ESC) akut Ă©s krĂłnikus szĂvelĂ©gtelensĂ©g diagnĂłzisára Ă©s
terápiájára vonatkozó legújabb irányelve, illetve az amerikai kardiológus
társaságoknak (ACC/AHA/HFSA) a szĂvelĂ©gtelensĂ©g gyĂłgyszeres kezelĂ©sĂ©re vonatkozĂł
irányelv megĂşjĂtása is. A közlemĂ©ny az Ăşj irányelvek tĂĽkrĂ©ben kĂván áttekintĂ©st
adni a krĂłnikus szĂvelĂ©gtelensĂ©g gyĂłgyszeres kezelĂ©sĂ©nek aktuális helyzetĂ©rĹ‘l,
magába foglalva az új klinikai vizsgálatok eredményeit. Orv. Hetil., 2016,
157(38), 1517–1521.
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Abstract
Recently, results of several novel clinical trials on the pharmacological
treatment of chronic heart failure have been published. In addition, the new
European Society of Cardiology guidelines for the diagnosis and treatment of
acute and chronic heart failure and a focused update by the ACC/AHA/HFSA on new
pharmacological therapy for heart failure has been reported in 2016. This paper
intends to provide an overview of the current state of the pharmacological
treatment of chronic heart failure in the light of the new guidelines which
incorporate the results of the new clinical trials. Orv. Hetil., 2016,
157(38), 1517–1521
Napjaink nagy trilemmája : beszámoló az MKT Agrárszakosztályának rendezvényéről
A 60. közgazdász-vándorgyűlĂ©s agrárgazdasági szekciĂłjának, „Az Ă©lelmiszerellátás biztonsága Magyarországon Ă©s EurĂłpában” cĂmű kerekasztal beszĂ©lgetĂ©s bevezetĹ‘ elĹ‘adását Farkas Sándor, az AgrárminisztĂ©rium parlamenti államtitkára tartotta. Az agrárium (AgrárminisztĂ©rium) a 2022-es Ă©vvel kezdĹ‘dĹ‘en a kereskedelem Ă©s Ă©lelmiszeripar ágazatok irányĂtását kapta meg a mezĹ‘gazdaság mellett. Az Ăşj feladatokhoz Ăşj cĂ©lok is kellenek. Farkas Sándor kiemelte, hogy az elsĹ‘dleges cĂ©ljuk: megfelelĹ‘ mennyisĂ©gű, minĹ‘sĂ©gű Ă©s biztonságos Ă©lelmiszer előállĂtása 20-25 milliĂł embernek. A miniszterhelyettes Ăşr kitĂ©rt az Ă©vtizedek Ăłta kimagaslĂł mezĹ‘gazdasági exportbevĂ©telek drámai csökkenĂ©sĂ©re is az idei Ă©vben, amit az aszály hatásaival magyarázott
Refined heart failure detection algorithm for improved clinical reliability of OptiVol alerts in CRT-D recipients
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 Background: The reliability of intrathoracic impedance monitoring for prediction of heart failure (HF) by implantable cardiac devices is controversial. Despite using additional device-based parameters described in the PARTNERS HF study, such as new onset of arrhythmias, abnormal autonomics, low biventricular pacing rate or patient activity level, the predictive power of device diagnostic algorithm is still in doubt. The objective of this study was to compare the device diagnostic algorithm described in the PARTNERS HF study to a newly developed algorithm applying refined diagnostic criteria.
Methods: Fourty two patients were prospectively enrolled who had been implanted with an intrathoracic impedance and remote monitoring capable implantable cardiac defibrillator with a cardiac resychronizaÂtion therapy (CRT-D) device in this observational study. If a remote OptiVolTM alert occurred, patients were checked for presence of HF symptoms. A new algorithm was derived from the original PARTNERS HF criteria, considering more sensitive cut-offs and changes of patterns of the device-based parameters.
Results: During an average follow-up of 38 months, 722 remote transmissions were received. From the total of 128 transmissions with OptiVol alerts, 32 (25%) corresponded to true HF events. Upon multivariate discriminant analysis, low patient activity, high nocturnal heart rate, and low CRT pacing (< 90%) proved to be independent predictors of true HF events (all p < 0.01). Incorporating these three refined criteria in a new algorithm, the diagnostic yield of OptiVol was improved by increasing specificÂity from 37.5% to 86.5%, positive predictive value from 34.1% to 69.8% and area under the curve from 0.787 to 0.922 (p < 0.01), without a relevant loss in sensitivity (96.9% vs. 93.8%).
Conclusions: A refined device diagnostic algorithm based on the parameters of low activity level, high nocturnal heart rate, and suboptimal biventricular pacing might improve the clinical reliability of OptiVol alerts. Â
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