7 results on '"Axente, L"'
Search Results
2. The relation between thrombophilia and venous thromboembolism
- Author
-
Hostiuc, M., primary, Bartos, D., additional, Chioncel, V., additional, Axente, L., additional, Badila, E., additional, Diaconu, C., additional, and Sinescu, C., additional
- Published
- 2013
- Full Text
- View/download PDF
3. Heart failure prognostic model.
- Author
-
Axente, L., Sinescu, C., and Bazacliu, G.
- Subjects
- *
HEART failure , *MULTIPLE regression analysis , *PROGNOSIS , *HEART disease related mortality , *CARDIAC pacemakers , *IMPLANTED cardiovascular instruments - Abstract
Heart failure (HF) is a common, costly, disabling and deadly syndrome. Heart failure is a progressive disease characterized by high prevalence in society, significantly reducing physical and mental health, frequent hospitalization and high mortality (50% of the patients survive up to 4 years after the diagnosis, the annual mortality varying from 5% to 75%). The purpose of this study is to develop a prognostic model with easily obtainable variables for patients with heart failure. Methods and Results. Our lot included 101 non-consecutive hospitalized patients with heart failure diagnosis. It included 49,5% women having the average age of 71.23 years (starting from 40 up to 91 years old) and the roughly estimated period for monitoring was 35.1 months (5-65 months). Survival data were available for all patients and the median survival duration was of 44.0 months. A large number of variables (demographic, etiologic, co morbidity, clinical, echocardiograph, ECG, laboratory and medication) were evaluated. We performed a complex statistical analysis, studying: survival curve, cumulative hazard, hazard function, lifetime distribution and density function, meaning residual life time, Ln S (t) vs. t and Ln(H) t vs. Ln (t). The Cox multiple regression model was used in order to determine the major factors that allow the forecasting survival and their regression coefficients: age (0.0369), systolic blood pressure (-0.0219), potassium (0.0570), sex (-0.3124) and the acute myocardial infarction (0.2662). Discussion. Our model easily incorporates obtainable variables that may be available in any hospital, accurately predicting survival of the heart failure patients and enables risk stratification in a few hours after the patients' presentation. Our model is derived from a sample of patients hospitalized in an emergency department of cardiology, some with major life-altering co morbidities. The benefit of being aware of the prognosis of these patients with high risk is extremely beneficial. The use of this model may ease the estimation of the vital prognosis, to improve the compliance and increase in the use of life-saving medical or surgical therapy (pacemakers, implantable defibrillators or transplantation). [ABSTRACT FROM AUTHOR]
- Published
- 2011
4. Incomplete locked - in syndrome
- Author
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Szilagyi, T., Zoltan Bajko, Axente, L., and Szatmari, S.
- Subjects
basilar artery thrombosis ,locked-in syndrome ,genetic structures ,lcsh:R ,lcsh:Medicine ,sense organs ,eye diseases ,lcsh:Neurology. Diseases of the nervous system ,lcsh:RC346-429 - Abstract
In this paper, we present a case of 62 year-old male with quadriplegia, dysarthria and preserved consciousness. Our case belongs to the incomplete variety of locked-in syndrome due to pontine infarction, because beside the vertical eye movements and eye lid movements, the patient had horizontal eye movements and finger movements on the right side. In general, the basilar artery occlusion is associated with poor outcome, however the urgent thrombolytic therapy may increase the chances to survive. The prognosis of our patient was disquieting and he died after 6 weeks from the onset.
5. Cohort profile. the ESC-EORP chronic ischemic cardiovascular disease long-term (CICD LT) registry
- Author
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Komajda, Michel, Cosentino, Francesco, Ferrari, Roberto, Laroche, Cécile, Maggioni, Aldo, Steg, Philippe Gabriel, Tavazzi, Luigi, Kerneis, Mathieu, Valgimigli, Marco, Gale, Chris, P, Chris, P Gale, Branko, Beleslin, Andrzej, Budaj, Ovidiu, Chioncel, Nikolaos, Dagres, Nicolas, Danchin, Jonathan, Emberson, David, Erlinge, Michael, Glikson, Alastair, Gray, Meral, Kayikcioglu, Aldo, P Maggioni, Vivien Klaudia Nagy, Aleksandr, Nedoshivin, Anna-Sonia, Petronio, Jolien, Roos-Hesselink, Lars, Wallentin, Uwe, Zeymer, Michel, Komajda, Francesco, Cosentino, Roberto, Ferrari, Gabriel, Steg, Luigi, Tavazzi, Marco, Valgimigli, Gani, Bajraktari, Pedro, Braga, Vakhtang, Chumburidze, Ana Djordjevic Dikic, Adel El Etriby, Fedele, Francesco, Jean Louis Georges, Artan, Goda, Mathieu, Kerneis, Robert, Klempfner, Peep, Laanmets, Abdallah, Mahdhaoui, Iveta, Mintale, Erkin, Mirrakhimov, Zoran, Olivari, Arman, Postadjian, Harald, Rittger, Luis, Rodriguez-Padial, David, Rott, Carlos, Serrano, Evgeny, Shlyakhto, Rimvydas, Slapikas, Maksym, Sokolov, Volha, Sujayeva, Konstantinos, Tsioufis, Dragos, Vinereanu, Parounak, Zelveian, Tase, M, Koci, J, Kuka, S, Nelaj, E, Goda, A, Simoni, L, Beka, V, Dragoti, J, Karanxha, J, Refatllari, I, Shehu, B, Bileri, A, Luzati, M, Shuperka, E, Gace, A, Shirka, E, Knuti, G, Dado, E, Dibra, L, Gjana, A, Kristo, A, Bica, L, Kabili, S, Pjeci, R, Siqeca, M, Hazarapetyan, L, Drambyan, M, Asatrya, K, Nersesyan, S, Ter-Margaryan, A, Zelveian, P, Gharibyan, H, Hakobyan, Z, Sujayeva, V, Koshlataya, O, Rozumovitch, A, Bychkovskaya, E, Lavrenova, T, Tkacheva, L, Dmitrieva, I, Serrano, C, A Cuoco, M, Favarato, D, Garzillo, C, Goes, M, Lima, E, Pitta, F, Rached, F, Segre, C, Ayres, S, Torres, M, S Hussein, M, Ragy, H, Essam, S, Fadala, H, Hassan, A, Zaghloul, S, Zarif, B, A-E, Elbakery, Nabil, M, W Mohammed Mounir, Radwan, F, Elmenyawy, E, Nafee, W, Sabri, M, A Magdy Moustafa, Helal, A, E Mohamed Abdelrahim, A M, A Elseaidy, Yousef, A, Albert, F, Dasoveanu, M, Demicheli, T, Dutoiu, T, Gorka, H, Laure, C, Range, G, Thuaire, C, Lattuca, B, Cayla, G, Delelo, E, Jouve, B, Khachab, H, Rahal, Y, Lacrimini, M, Chayeb, S, Baron, N, Chavelas, C, Cherif, G, Nay, L, Nistor, M, Vienet-Legue, A, J-B, Azowa, Noichri, Y, Kerneis, M, E Van Belle, Cosenza, A, Delhaye, C, Vincent, F, Gaul, A, Pin, G, Valy, Y, Trouillet, C, Laurencon, V, Couppie, P, J-M, Daessle, F De Poli, Goioran, F, Delarche, N, Livarek, B, L Georges, J, M Ben Aziza, Blicq, E, Charbonnel, C, Convers, R, Gibault-Genty, G, Schiele, F, L Perruche, M, Cador, R, B Lesage, J, J Aroulanda, M, Belle, L, Madiot, H, Chumburidze, V, Kikalishvili, T, Kharchilava, N, Todua, T, Melia, A, Gogoberidze, D, Katsiashvili, T, Lominadze, Z, Chubinidze, T, Brachmann, J, Schnupp, S, Linss, A, Truthan, K, M-A, Ohlow, Rosenthal, A, Ungethüm, K, Rieber, J, Deichstetter, M, Hitzke, E, Rump, S, Tonch, R, Achenbach, S, Gerlach, A, Schlundt, C, Fechner, S, Ücker, C, D Garlichs, C, Petersen, I, Thieme, M, Greiner, R, Kessler, A, Rädlein, M, Edelmann, S, Hofrichter, J, Kirchner-Rückert, V, Klug, A, Papsdorf, E, Waibl, P, Rittger, H, Karg, M, Kuhls, B, Kuhls, S, Eichinger, G, Pohle, K, Paleczny, S, Tsioufis, K, Galanakos, S, Georgiopoulos, G, Panagiotis, T, Peskesis, G, Pylarinou, V, Kanakakis, I, Stamatelopoulos, K, Tourikis, P, Tsoumani, Z, Alexopoulos, D, Bei, I, Davlouros, P, Xanthopoulou, I, Trikas, A, Grigoriou, K, Thomopoulos, T, Foussas, S, Vassaki, M, Athanasiou, K, Dimopoulos, A, Papakonstantinou, N, Patsourakos, N, Ionia, N, Patsilinakos, S, Kintis, K, Tziakas, D, Chalikias, G, Kikas, P, Lantzouraki, A, Karvounis, H, Didagelos, M, Ziakas, A, Sarrafzadegan, N, Khosravi, A, Kermani-Alghoraishi, M, Cinque, A, Fedele, F, Mancone, M, Manzo, D, L De Luca, Figliozzi, S, Tarantini, G, Fraccaro, C, Sinagra, G, Perkan, A, Priolo, L, Ramani, F, Ferrari, R, Campo, G, Biscaglia, S, Cortesi, S, Gallo, F, Pecoraro, A, Spitaleri, G, Tebaldi, M, Tumscitz, C, Lodolini, V, Mosele, E, Indolfi, C, Ambrosio, G, S De Rosa, Canino, G, Critelli, C, Calzolari, D, Zaina, C, F Grisolia, E, Ammendolea, C, Russo, P, Gulizia, M, Bonmassari, R, Battaia, E, Moretti, M, Bajraktari, G, Ibrahimi, P, Ibërhysaj, F, Tishukaj, A, Berisha, G, Percuku, L, Mirrakhimov, E, Kerimkulova, A, Bektasheva, E, Neronova, K, Kaneps, P, Libins, A, Sorokins, N, Stirna, V, Rancane, G, Putne, S, Ivanova, L, Mintale, I, Roze, R, Kalnins, A, Strelnieks, A, Vasiljevs, D, Slapikas, R, Babarskiene, R, Viezelis, M, Brazaitis, G, Orda, P, Petrauskaite, J, Kovaite, E, A Rimkiene, M, Skiauteryte, M, Janion, M, Raszka, D, Szwed, H, Dąbrowski, R, Korczyńska, A, Mączyńska, J, Jaroch, J, Ołpińska, B, Sołtowska, A, Wysokiński, A, Kania, A, Sałacki, A, Zapolski, T, Krzesinski, P, Skrobowski, A, Buczek, K, Golebiewska, K, Kolaszyńska-Tutka, K, Piotrowicz, K, Stanczyk, A, Sobolewski, P, Przybylski, A, Harpula, P, Kurianowicz, R, Wojcik, M, Czarnecka, D, Jankowski, P, Drożdż, T, Pęksa, J, Mendes, M, Brito, J, Freitas, P, V Gama Ribeiro, Braga, P, G Ribeiro, V, Melica, B, G Pires de Morais, Rodrigues, A, Santos, L, Almeida, C, L Pop-Moldovan, A, Darabantiu, D, Lala, R, Mercea, S, Sirbovan, I, Pop, D, Zdrenghea, D, Caloian, B, Comșa, H, Fringu, F, Gurzau, D, Iliesiu, A, Ciobanu, A, Nicolae, C, Parvu, I, Vinereanu, D, A Udroiu, C, G Cotoban, A, Pop, C, Dicu, D, Kozma, G, Matei, C, Mercea, D, Tarusi, M, Burca, M, Bengus, C, Ochean, V, Petrescu, L, Alina-Ramona, N, Crisan, S, Dan, R, Matei, O, Buzas, R, Ciobotaru, G, O Petris, A, I Costache, I, Mitu, O, Tudorancea, I, R Parepa, I, Cojocaru, L, Ionescu, M, Mazilu, L, Rusali, A, I Suceveanu, A, C-J, Sinescu, Axente, L, Dimitriu, I, Samoila, N, Mot, S, Cocoi, M, Iuga, H, Dorobantu, M, Calmac, L, Bataila, V, Cosmin, M, Dragoescu, B, Marinescu, M, Tase, A, Usurelu, C, Dondoi, R, C Tudorica, C, A-M, Vintilă, Ciomag, R, Gurghean, A, Ianula, R, Isacoff, D, Savulescu-Fiedler, I, Spataru, D, V Spătaru, D, Horumbă, M, Mihalcea, R, C-I, Balogh, Bakcsi, F, O-B, Szakacs, Iancu, A, Doroltan, P, Dregoesc, I, Marc, M, Niculina, S, Chernova, A, Kuskaeva, A, Novikova, D, Kirillova, I, Markelova, E, Udachkina, E, Khaisheva, L, Razumovskiy, I, Zakovryashina, I, Chumakova, G, Gritzenko, O, Lomteva, E, Shtyrova, T, Vasileva, L, Gosteva, E, Malukov, D, Pyshnograeva, L, Nedbaykin, A, Iusova, I, Gadgiev, R, Grechova, L, Kazakovtseva, M, Maksimchuk-Kolobova, N, Semenova, Y, Rusina, A, Govorin, A, Mukha, N, Radaeva, E, Vasilenko, P, Zhanataeva, L, Kosmachova, E, Tatarintseva, Z, Tripolskaya, N, Borovkova, N, Tokareva, A, Semenova, A, Spiropulos, N, Ginter, Y, Kovalenko, F, Brodskaia, T, A Nevzorova, V, Golovkin, N, Golofeevskii, S, Shcheglova, E, Aleinik, O, Glushchenko, N, Podbolotova, A, Petrova, M, Harkov, E, Lobanova, A, Tsybulskaya, N, Iakushin, S, Kuzmin, D, Pereverzeva, K, Shevchenko, I, Elistratova, O, Fetisova, E, Galyavich, A, Galeeva, Z, Chepisova, M, Eseva, S, Panov, A, Lokhovinina, N, Boytsov, S, Drapkina, O, Shepel, R, Vasilyev, D, Yavelov, I, Kochergina, A, Sedykh, D, Tavlueva, E, Duplyakov, D, Antimonova, M, Kocharova, K, Libis, R, Lopina, E, Osipova, L, Bukatov, V, Kletkina, A, Plaksin, K, Suyazova, S, Nedogoda, S, Chumachek, E, Ledyaeva, A, Totushev, M, Asadulaeva, G, Tarlovskaya, E, Kozlova, N, V Mazalov, K, Valiculova, F, Merezhanova, A, Efremova, E, Menzorov, M, Shutov, A, Garganeeva, A, Aleksandrenko, V, Kuzheleva, E, Tukish, O, Ryabov, V, Belokopytova, N, Lipnyagova, D, Simakin, N, Ivanov, K, Levashov, S, Karaulovskaya, N, Stepanovic, J, Beleslin, B, Djordjevic-Dikic, A, Giga, V, Boskovic, N, Nedeljkovic, I, Dzelebdzic, S, Arsic, S, Jovanovic, S, Katic, J, Milak, J, Pletikosic, I, Rastovic, M, Vukelic, M, Lazar, Z, J Lukic Petrov, Stankov, S, Djokic, D, Kulic, N, Stojiljkovic, G, Stojkovic, G, Stojsic-Milosavljevic, A, Ilic, A, D Ilic, M, Petrovic, D, A Martínez Cámara, L Rodriguez Padial, P Sánchez-Aguilera Sánchez-Paulete, M Iniesta Manjavacas, A, J Irazusta, F, Merás, P, Rial, V, Cejudo, L, J Fernandez Anguita, M, V Martinez Mateo, Gonzalez-Juanatey, C, S de Dios, Martí, D, C Suarez, R, D Garcia Fuertes, D, Pavlovic, D, Mazuelos, F, J Suárez de Lezo, Marin, F, M Rivera Caravaca, J, A Veliz Martínez, Zhurba, S, Mikitchuk, V, Sokolov, M, and Levchuk, N
- Subjects
chronic coronary disease ,clinical outcomes ,demographics ,medications ,registry
6. Heart failure prognostic model
- Author
-
Axente, L., Crina Julieta Sinescu, and Bazacliu, G.
- Subjects
Adult ,Heart Failure ,Male ,Young Researchers Area ,Sodium ,Models, Cardiovascular ,Myocardial Infarction ,survival function ,Blood Pressure ,Stroke Volume ,Cox multiple regression model ,Kaplan-Meier Estimate ,Middle Aged ,Prognosis ,Diabetes Complications ,Heart Rate ,Humans ,Female ,Antihypertensive Agents ,Aged ,Proportional Hazards Models - Abstract
Heart failure (HF) is a common, costly, disabling and deadly syndrome. Heart failure is a progressive disease characterized by high prevalence in society, significantly reducing physical and mental health, frequent hospitalization and high mortality (50% of the patients survive up to 4 years after the diagnosis, the annual mortality varying from 5% to 75%). The purpose of this study is to develop a prognostic model with easily obtainable variables for patients with heart failure. METHODS AND RESULTS. Our lot included 101 non-consecutive hospitalized patients with heart failure diagnosis. It included 49.5% women having the average age of 71.23 years (starting from 40 up to 91 years old) and the roughly estimated period for monitoring was 35.1 months (5-65 months). Survival data were available for all patients and the median survival duration was of 44.0 months. A large number of variables (demographic, etiologic, co morbidity, clinical, echocardiograph, ECG, laboratory and medication) were evaluated. We performed a complex statistical analysis, studying: survival curve, cumulative hazard, hazard function, lifetime distribution and density function, meaning residual life time, Ln S (t) vs. t and Ln(H) t vs. Ln (t). The Cox multiple regression model was used in order to determine the major factors that allow the forecasting survival and their regression coefficients: age (0.0369), systolic blood pressure (-0.0219), potassium (0.0570), sex (-0.3124) and the acute myocardial infarction (0.2662). DISCUSSION. Our model easily incorporates obtainable variables that may be available in any hospital, accurately predicting survival of the heart failure patients and enables risk stratification in a few hours after the patients' presentation. Our model is derived from a sample of patients hospitalized in an emergency department of cardiology, some with major life-altering co morbidities. The benefit of being aware of the prognosis of these patients with high risk is extremely beneficial. The use of this model may ease the estimation of the vital prognosis, to improve the compliance and increase in the use of life-saving medical or surgical therapy (pacemakers, implantable defibrillators or transplantation).
7. Heart failure--concepts and significance. Birth of a prognostic model.
- Author
-
Sinescu C and Axente L
- Subjects
- Acute Disease, Age Distribution, Aged, Aged, 80 and over, Chronic Disease, Female, Humans, Incidence, Male, Predictive Value of Tests, Prevalence, Prognosis, Quality of Life, Sex Distribution, Heart Failure, Diastolic mortality, Heart Failure, Systolic mortality, Proportional Hazards Models
- Abstract
Heart failure (HF) is a syndrome characterized by high prevalence in society, frequent hospitalization, reduced quality of life and high mortality (overall, 50% of patients are dead at an interval of 4 years, annual mortality varying from 5% to 75%). Outcomes in heart failure are highly variable, prognosis of individual patients differs considerably and trial data, though valuable, does not often give an adequate direction. Taking into account the high prevalence of heart failure in society and its complexity physicians need a model to predict the risk of death, to estimate the survival of heart failure patients. A key element of interest in this area is the survival function, usually noted by S and defined as S(t) = exp(-H0(t)e(a)Tx) = e(-H)0(t)e(a)Tx.
- Published
- 2010
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