Browsing by Author "Jović, Nebojša (56367047200)"

Objectives: To estimate the risk of seizure recurrence after antiepileptic drugs (AED) withdrawal and to identify related predictive features in patients with idiopathic generalized epilepsy (IGE) commencing at developing age (up to 16 year). Methods: Medical records of consecutive patients with IGE from two refferal hospitals were evaluated between 2001 and 2009. Inclusion criteria were clinical and EEG diagnosis of IGE and follow up for at least 2 years after the AED withdrawal. The cohort consisted of 59 patients (38 females, 21 males). Follow up after withdrawal lasted 2-10 years (median 3) Time to seizure relapse and predictive factors were analyzed by survival methods. Results: There were 21 (35.6%) patients with childhood absence epilepsy (CAE), 11 (18.6%) with juvenile absence epilepsy (JAE), 10 (16.9%) with isolated primary GTC seizures, and 17 (28.8%) with juvenile myoclonic epilepsy (JME). The relapses occured in 23 (52.2%) patients: one (6.2%) with CAE, 4 (50%) with JAE, 8 (80%) with IGE with GTC seizures and all with JME. During the first 6 months 54.5% patients relapsed (20% during withdrawal), 63.6% within 12 months, 81.8% within18 months and 95.4% within 24 months after withdrawal. Female gender, age at onset of seizures, seizure types, EEG worsening during/after AED withdrawal and age at withdrawal were significantly associated with relapse risk according to univariate analysis. In multivariate analysis, retained significant factors were: seizure types and EEG worsening. Conclusion: Diagnosis of the specific IGE syndrome strongly affects relapse rate: the lowest was in CAE, the highest in JME. Independent risk factors for seizure relapse were: seizure type and EEG worsening during and/or after withdrawal. © 2011 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Objectives: To estimate the risk of seizure recurrence after antiepileptic drugs (AED) withdrawal and to identify related predictive features in patients with idiopathic generalized epilepsy (IGE) commencing at developing age (up to 16 year). Methods: Medical records of consecutive patients with IGE from two refferal hospitals were evaluated between 2001 and 2009. Inclusion criteria were clinical and EEG diagnosis of IGE and follow up for at least 2 years after the AED withdrawal. The cohort consisted of 59 patients (38 females, 21 males). Follow up after withdrawal lasted 2-10 years (median 3) Time to seizure relapse and predictive factors were analyzed by survival methods. Results: There were 21 (35.6%) patients with childhood absence epilepsy (CAE), 11 (18.6%) with juvenile absence epilepsy (JAE), 10 (16.9%) with isolated primary GTC seizures, and 17 (28.8%) with juvenile myoclonic epilepsy (JME). The relapses occured in 23 (52.2%) patients: one (6.2%) with CAE, 4 (50%) with JAE, 8 (80%) with IGE with GTC seizures and all with JME. During the first 6 months 54.5% patients relapsed (20% during withdrawal), 63.6% within 12 months, 81.8% within18 months and 95.4% within 24 months after withdrawal. Female gender, age at onset of seizures, seizure types, EEG worsening during/after AED withdrawal and age at withdrawal were significantly associated with relapse risk according to univariate analysis. In multivariate analysis, retained significant factors were: seizure types and EEG worsening. Conclusion: Diagnosis of the specific IGE syndrome strongly affects relapse rate: the lowest was in CAE, the highest in JME. Independent risk factors for seizure relapse were: seizure type and EEG worsening during and/or after withdrawal. © 2011 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Background: In a previous study we demonstrated that heart variability parameters (HRV) could be helpful clinically as well as a prognostic tool in infants with central coordination disturbance (CCD). In recent years, outcome predictions using artificial neural networks (ANN) have been developed in many areas of health care research, but there are no published studies considered ANN models for prediction of cerebral palsy (CP) development. Objective: To compare the results of an ANN analysis with results of regression analysis, using the same data set and the same clinical and HRV parameters. Methods: The study included 35 infants with CCD and 37 healthy age and sex-matched controls. Time-domain HRV indices were analyzed from 24. h electrocardiography recordings. Clinical parameters and selected time domain HRV parameters are used to predict CP by logistic regression, and then an ANN analysis was applied to the same data set. Input variables were age, gender, postural responses, heart rate parameters (minimum, maximum and average), and time domain parameters of HRV (SDNN, SDANN and RMSSD). For each of one the pairs of ANN and clinical predictors, the area under the receiver operating characteristic (ROC) curves with test accuracy parameters were calculated and compared. Results: In the observed dataset, ANN model overall correctly classified all infants, compared with 86.11% correct classification for the logistic regression model, and compared with 67.65% and 77.14% for SDANN and SDNN respectively. Conclusions: ANN model, based on clinical and HRV data can predict development of CP in patients with CCD with accuracy greater than 90%. Our results strongly indicate that a well-validated ANN may have a role in the clinical prediction of CP in infants with CCD. © 2012 Elsevier Ltd.

Introduction It is largely known that some antipsychotic agents could have proconvulsive and proepileptogenic effects in some patients and could induce EEG abnormalities as well. However, the association of status epilepticus with certain antipsychotic drugs has been very rarely reported. Case Report A case of an 18-year-old adolescent girl, with chlorpromazine therapy started for anxiety-phobic disorder was reported. Her personal history disclosed delayed psychomotor development. Shortly after the introduction of the neuroleptic chlorpromazine therapy in minimal daily dose (37.5 mg), she developed myoclonic status epilepticus, confirmed by the EEG records. Frequent, symmetrical bilateral myoclonic jerks and altered behavior were associated with bilateral epileptiform discharges of polyspikes and spike-wave complexes. This epileptic event lasted 3.5 hours and it was stopped by the parenteral administration of valproate and lorazepam; she was EEG monitored until stable remission. Status epilepticus as initial epileptic event induced by neuroleptic agent was not previously reported in our national literature. Conclusion Introduction of chlorpromazine to a patient without history of seizures is associated with the evolution of an epileptic activity, including the occurrence of status epilepticus. Clinical evaluation of the risk factors possibly related to chlorpromazine-induced seizure is recommended in individual patients before administering this drug.

Lafora disease (LD) is a fatal neurodegenerative disorder caused by loss-of-function mutations in either laforin glycogen phosphatase gene (EPM2A) or malin E3 ubiquitin ligase gene (NHLRC1). LD is associated with gradual accumulation of Lafora bodies (LBs). LBs are aggregates of polyglucosan, a long, linear, poorly branched, hyperphosphorylated, insoluble form of glycogen. Loss-of-function mutations either in the EPM2A or in the NHLRC1 gene lead to polyglucosan formation. One hypothesis on LB formation is based on findings that laforinmalin complex downregulates glycogen synthase (GS) through malin-mediated ubiquitination, and the other one is based on findings that laforin dephosphorylates glycogen. According to the first hypothesis, polyglucosan formation is a result of increased GS activity, and according to the second, an increased glycogen phosphate leads to glycogen conformational change, unfolding, precipitation, and conversion to polyglucosan, while GS remains bound to the precipitating glycogen. In this review, we summarize all the recent findings that have important implications for the treatment of LD, all of them showing that partial inhibition of GS activity may be sufficient to prevent the progression of the disease. The current perspective in LD is high-throughput screening for small molecules that act on the disease pathway, that is, partial inhibitors of GS, which opens a therapeutic window for potential treatment of this fatal disease. © 2016 Kecmanovi et al.

Lafora disease (LD) is a fatal neurodegenerative disorder caused by loss-of-function mutations in either laforin glycogen phosphatase gene (EPM2A) or malin E3 ubiquitin ligase gene (NHLRC1). LD is associated with gradual accumulation of Lafora bodies (LBs). LBs are aggregates of polyglucosan, a long, linear, poorly branched, hyperphosphorylated, insoluble form of glycogen. Loss-of-function mutations either in the EPM2A or in the NHLRC1 gene lead to polyglucosan formation. One hypothesis on LB formation is based on findings that laforinmalin complex downregulates glycogen synthase (GS) through malin-mediated ubiquitination, and the other one is based on findings that laforin dephosphorylates glycogen. According to the first hypothesis, polyglucosan formation is a result of increased GS activity, and according to the second, an increased glycogen phosphate leads to glycogen conformational change, unfolding, precipitation, and conversion to polyglucosan, while GS remains bound to the precipitating glycogen. In this review, we summarize all the recent findings that have important implications for the treatment of LD, all of them showing that partial inhibition of GS activity may be sufficient to prevent the progression of the disease. The current perspective in LD is high-throughput screening for small molecules that act on the disease pathway, that is, partial inhibitors of GS, which opens a therapeutic window for potential treatment of this fatal disease. © 2016 Kecmanovi et al.

Lafora disease (LD) is a severe, autosomal recessive, latechildhood- to teenage-onset, progressive myoclonic epilepsy. It is due to either EPM2A or NHLRC1 mutations. We describe a patient with homozygous deletion encompassing the entire NHLRC1 gene, not previously reported, and with clinical course more progressive than in the most patients with NHLRC1 mutations. The diagnosis of LD in our patient was based on the typical clinic, neurophysiological presentation, as well as skin biopsy followed by molecular genetics findings. She developed normally until the age of 15, when she had her first occipital and generalized seizures. Four years after the first seizure the patient became bedridden, demented and presented with severe clinical condition. She died of pneumonia at age 20. This report is the first case of homozygosity for NHLRC1 deletion and thus adds to mutational heterogeneity of LD. Besides, it widens the spectrum of LD patients with severe phenotype and NHLRC1 mutations. © 2012 Elsevier B.V.

Lafora disease (LD) is a severe, autosomal recessive, latechildhood- to teenage-onset, progressive myoclonic epilepsy. It is due to either EPM2A or NHLRC1 mutations. We describe a patient with homozygous deletion encompassing the entire NHLRC1 gene, not previously reported, and with clinical course more progressive than in the most patients with NHLRC1 mutations. The diagnosis of LD in our patient was based on the typical clinic, neurophysiological presentation, as well as skin biopsy followed by molecular genetics findings. She developed normally until the age of 15, when she had her first occipital and generalized seizures. Four years after the first seizure the patient became bedridden, demented and presented with severe clinical condition. She died of pneumonia at age 20. This report is the first case of homozygosity for NHLRC1 deletion and thus adds to mutational heterogeneity of LD. Besides, it widens the spectrum of LD patients with severe phenotype and NHLRC1 mutations. © 2012 Elsevier B.V.

Objective: To develop and test model to predict outcome of treatment with initial lamotrigine monotherapy in adult patients with newly diagnosed localization - related epilepsy, using data available at the time of diagnosis. Methods: Prospective longitudinal study included consecutive series of adult patients with newly diagnosed localization - related epilepsy started of lamotrigine monotherapy. Logistic regression analysis using backward procedure was performed with treatment failure as the outcome variable. We evaluated both calibration and discrimination of the model. Internal validation of the model was performed with bootstrapping techniques. Results: A total of 159 patients on lamotrigine monotherapy have been included in final analysis. Among them 78 (49.06%) patients had persistent seizures. Finally fitted multivariate model included: 1) age at therapy start, 2) presence of complex partial seizures, 3) aetiology of epilepsy and 4) interaction of age and epilepsy aetiology. Estimated odds ratio for seizure relapse in old patients with symptomatic epilepsy is lower than for the old patients with cryptogenic epilepsy, despite strong positive covariate effect of epilepsy aetiology. The model correctly classified 69.23% patients with seizure relapses and 81.48% of patients with seizure freedom, with estimated c - statistic of 0.80. Testing practical application we observed threefold increase or reduction of odds for the seizure relapse after model's positive or negative prediction respectively. Conclusion: Standard clinical data were modesty adequate to predict response to the initial trial of lamotrigine in adult patients with localization related epilepsy. Better markers of antiepileptic failure are required to guide optimal patient counselling and clinical decisions. Formal interaction analysis of variables improves outcome prediction and may be a key to correct interpretation of data. © 2013 Elsevier B.V.

Objective: To develop and test model to predict outcome of treatment with initial lamotrigine monotherapy in adult patients with newly diagnosed localization - related epilepsy, using data available at the time of diagnosis. Methods: Prospective longitudinal study included consecutive series of adult patients with newly diagnosed localization - related epilepsy started of lamotrigine monotherapy. Logistic regression analysis using backward procedure was performed with treatment failure as the outcome variable. We evaluated both calibration and discrimination of the model. Internal validation of the model was performed with bootstrapping techniques. Results: A total of 159 patients on lamotrigine monotherapy have been included in final analysis. Among them 78 (49.06%) patients had persistent seizures. Finally fitted multivariate model included: 1) age at therapy start, 2) presence of complex partial seizures, 3) aetiology of epilepsy and 4) interaction of age and epilepsy aetiology. Estimated odds ratio for seizure relapse in old patients with symptomatic epilepsy is lower than for the old patients with cryptogenic epilepsy, despite strong positive covariate effect of epilepsy aetiology. The model correctly classified 69.23% patients with seizure relapses and 81.48% of patients with seizure freedom, with estimated c - statistic of 0.80. Testing practical application we observed threefold increase or reduction of odds for the seizure relapse after model's positive or negative prediction respectively. Conclusion: Standard clinical data were modesty adequate to predict response to the initial trial of lamotrigine in adult patients with localization related epilepsy. Better markers of antiepileptic failure are required to guide optimal patient counselling and clinical decisions. Formal interaction analysis of variables improves outcome prediction and may be a key to correct interpretation of data. © 2013 Elsevier B.V.

Purpose: The goal of the study was to assess the outcome of antiepileptic drug (AED) withdrawal in children and adolescents with cryptogenic focal epilepsies (CFE). Methods: Medical records of consecutive patients with CFE from two referral hospitals were retrospectively evaluated over a nine-year period. Inclusion criteria were: (1) diagnosis of CFE according to the ILAE criteria, (2) less than 16 years of age at onset of epilepsy, (3) established clinical remission of at least two years before AED withdrawal, and (4) follow-up period of at least two years after withdrawal (or until seizure relapse in patients who relapsed). Time to seizure relapse and predictive factors were analyzed by survival methods. Results: The cohort consisted of 52 patients (16 females, 36 males). Relapse rate was 37.85%. Most relapses occurred during the first 12 months after withdrawal. Univariate analyses indicated the following factors as significantly correlated with seizure recurrences: (1) female sex; (2) age at withdrawal of AED 14 years or higher; (3) abnormal EEG before withdrawal; and (4) abnormal EEG during and after AED withdrawal. Multivariate Cox regression analyses revealed that female sex, age at withdrawal of AED 14 years or higher; and abnormal EEG during and after withdrawal were significant independent predictive factors for seizure recurrences. Conclusion: The relapse rate in our cohort was similar to the most commonly reported overall rates for childhood-onset epilepsy. Distinguishing variables - female sex, age at withdrawal greater than 14 years, and abnormal EEG - need to be considered when choosing and further following of eligible candidates for AED withdrawal. © 2012 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Purpose: The goal of the study was to assess the outcome of antiepileptic drug (AED) withdrawal in children and adolescents with cryptogenic focal epilepsies (CFE). Methods: Medical records of consecutive patients with CFE from two referral hospitals were retrospectively evaluated over a nine-year period. Inclusion criteria were: (1) diagnosis of CFE according to the ILAE criteria, (2) less than 16 years of age at onset of epilepsy, (3) established clinical remission of at least two years before AED withdrawal, and (4) follow-up period of at least two years after withdrawal (or until seizure relapse in patients who relapsed). Time to seizure relapse and predictive factors were analyzed by survival methods. Results: The cohort consisted of 52 patients (16 females, 36 males). Relapse rate was 37.85%. Most relapses occurred during the first 12 months after withdrawal. Univariate analyses indicated the following factors as significantly correlated with seizure recurrences: (1) female sex; (2) age at withdrawal of AED 14 years or higher; (3) abnormal EEG before withdrawal; and (4) abnormal EEG during and after AED withdrawal. Multivariate Cox regression analyses revealed that female sex, age at withdrawal of AED 14 years or higher; and abnormal EEG during and after withdrawal were significant independent predictive factors for seizure recurrences. Conclusion: The relapse rate in our cohort was similar to the most commonly reported overall rates for childhood-onset epilepsy. Distinguishing variables - female sex, age at withdrawal greater than 14 years, and abnormal EEG - need to be considered when choosing and further following of eligible candidates for AED withdrawal. © 2012 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.