Increased resting-state EEG functional connectivity in benign childhood epilepsy with centro-temporal spikes

AbstractPurposeTo explore intrahemispheric, cortico-cortical EEG functional connectivity (EEGfC) in benign childhood epilepsy with rolandic spikes (BECTS).Methods21-channel EEG was recorded in 17 non-medicated BECTS children and 19 healthy controls. 180s of spike- and artifact-free activity was selected for EEGfC analysis. Correlation of Low Resolution Electromagnetic Tomography- (LORETA-) defined current source density time series were computed between two cortical areas (region of interest, ROI). Analyses were based on broad-band EEGfC results. Groups were compared by statistical parametric network (SPN) method. Statistically significant differences between group EEGfC values were emphasized at p<0.05 corrected for multiple comparison by local false discovery rate (FDR).Results(1) Bilaterally increased beta EEGfC occurred in the BECTS group as compared to the controls. Greatest beta abnormality emerged between frontal and frontal, as well as frontal and temporal ROIs. (2) Locally increased EEGfC emerged in all frequency bands in the right parietal area.ConclusionsAreas of increased EEGfC topographically correspond to cortical areas that, based on relevant literature, are related to speech and attention deficit in BECTS children

Isolation and NMR Scaling Factors for the Structure Determination of Lobatolide H, a Flexible Sesquiterpene from Neurolaena lobata

A new flexible germacranolide (1, lobatolide H) was isolated from the aerial parts of Neurolaena lobata. The structure elucidation was performed by classical NMR experiments and DFT NMR calculations. Altogether, 80 theoretical level combinations with existing 13C NMR scaling factors were tested, and the best performing ones were applied on 1. 1H and 13C NMR scaling factors were also developed for two combinations utilizing known exomethylene containing derivatives, and the results were complemented by homonuclear coupling constant (JHH) and TDDFT-ECD calculations to elucidate the stereochemistry of 1. Lobatolide H possessed remarkable antiproliferative activity against human cervical tumor cell lines with different HPV status (SiHa and C33A), induced cell cycle disturbance and exhibited a substantial antimigratory effect in SiHa cells

Low factor XIII levels after intravenous thrombolysis predict short-term mortality in ischemic stroke patients

L

Intracardiac hemostasis and fibrinolysis parameters in patients with atrial fibrillation

Aims. To identify intracardiac hemostasis or fibrinolysis abnormalities, which are associated with atrial fibrillation (AF) and increase the risk of thromboembolism. Patients and Methods. Patient group consisted of 24 patients with AF and control group included 14 individuals with other supraventricular tachycardia undergoing transcatheter radiofrequency ablation. Blood samples were drawn from the femoral vein (FV), left atrium (LA), and left atrial appendage (LAA) before the ablation procedure. Fibrinogen, factor VIII (FVIII) and factor XIII activity, von Willebrand factor (VWF) antigen, thrombin-antithrombin (TAT) complex, quantitative fibrin monomer (FM), plasminogen, α2-plasmin inhibitor, plasmin-α2-antiplasmin (PAP) complex, PAI-1 activity, and D-dimer were measured from all samples. Results. Levels of FVIII and VWF were significantly elevated in the FV and LA of AF patients as compared to controls. TAT complex, FM, PAP complex, and D-dimer levels were significantly elevated in the LA as compared to FV samples in case of both groups, indicating a temporary thrombotic risk associated with the catheterization procedure. Conclusions. None of the investigated hemostasis or fibrinolysis parameters showed significant intracardiac alterations in AF patients as compared to non-AF controls. AF patients have elevated FVIII and VWF levels, most likely due to endothelial damage, presenting at both intracardiac and systemic level

A méhnyakrák okozta éves epidemiológiai és egészségbiztosítási betegségteher Magyarországon = Annual epidemiological and health insurance burden of cervical cancer in Hungary

Összefoglaló. Bevezetés: A méhnyakdaganatok kérdése kiemelten fontos, megoldatlan népegészségügyi probléma. A betegség terhe magas, ami elsősorban az alacsony és közepes jövedelmű országokban élőknél jelentkezik. Célkitűzés: Elemzésünk célja volt meghatározni a méhnyakdaganatok epidemiológiai és egészségbiztosítási betegségterhét Magyarországon a 2018-as évre vonatkoztatva. Adatok és módszerek: Elemzésünket a Nemzeti Egészségbiztosítási Alapkezelő (NEAK) finanszírozási adatbázisának 2018. évi adatai alapján végeztük az in situ (D06), a jóindulatú (D26.0) és a malignus (C53) méhnyakdaganatokra vonatkozóan. Az elemzés a NEAK által finanszírozott összes szolgáltatóra és ellátási formára kiterjed. Meghatároztuk az éves betegszámokat, a prevalenciát 100 000 lakosra, továbbá az éves egészségbiztosítási kiadásokat betegségcsoportonként és korcsoportos bontásban, valamennyi egészségbiztosítási ellátás tekintetében. Eredmények: A NEAK 2018-ban 1,276 milliárd Ft-ot (4,7 millió USD; 4,0 millió EUR) költött a méhnyakdaganatok kezelésére. A betegek és a finanszírozás döntő többsége a méhnyak rosszindulatú daganatához kapcsolható. A finanszírozásból a malignus méhnyakdaganatok részesedése 97%. Ellátási típusonként vizsgálva a legnagyobb kiadási tétel az aktívfekvőbeteg-szakellátásban jelenik meg, éves szinten 763,9 millió Ft, ami az összköltség 59,9%-a. A 100 000 lakosra jutó prevalencia az aktívfekvőbeteg-szakellátás igénybevételi adatai alapján 26/100 000 lakos. Következtetés: A méhnyakdaganatok kezelésének meghatározó költségeleme az aktívfekvőbeteg-szakellátás. Hazánkban a szervezett méhnyakszűrés korszerűsítéseként az új szűrési stratégiát megfelelő finanszírozási támogatással célszerű bevezetni, a szűrővizsgálatoknak, a hozzájuk kapcsolódó további diagnosztikus kivizsgálásnak és terápiának a teljesítményvolumen-korlát alóli mentesítésével. Orv Hetil. 2021; 162(Suppl 1): 22-29.Cervical cancer is a particularly important, unresolved public health problem. The burden of the disease is high, primarily in those living in low- and middle-income countries.Our aim was to determine the annual epidemiological disease burden and health insurance cost of cervical cancer in Hungary in 2018.Our analysis was made according to the financial database of the National Health Insurance Fund Administration (NHIFA) of Hungary for the year 2018, which covers all service providers and maintenance forms financed by NHIFA. We analysed the in situ (D06), the benignant (D26.0) and the malignant (C53) cervical tumours. The data analysed included annual patient numbers and prevalence of care utilisation per 100 000 population furthermore annual health insurance costs calculated for disease and age groups.In 2018, NHIFA spent 1.276 billion HUF (4.7 million USD, 4.0 million EUR) on the treatment of patients with cervical cancer. The majority of patients and funding can be linked to malignant cervical cancer (97%). Acute inpatient care was the major cost driver: 763.9 million HUF (59.9% of the total health insurance expenditures) annually. The prevalence is 26 per 100 000 population based on acute inpatient care data.Acute inpatient care was the major cost driver. In Hungary, as a modernization of organized cervical screening, it is appropriate to introduce a new screening strategy with appropriate financial support, by exempting screening tests, associated additional diagnostic testing, and therapy from the performance volume limit. Orv Hetil. 2021; 162(Suppl 1): 22-29

Pharmacogenetics of the Central Nervous System—Toxicity and Relapse Affecting the CNS in Pediatric Acute Lymphoblastic Leukemia

Despite improving cure rates in childhood acute lymphoblastic leukemia (ALL), therapeutic side effects and relapse are ongoing challenges. These can also affect the central nervous system (CNS). Our aim was to identify germline gene polymorphisms that influence the risk of CNS events. Sixty single nucleotide polymorphisms (SNPs) in 20 genes were genotyped in a Hungarian non-matched ALL cohort of 36 cases with chemotherapy related acute toxic encephalopathy (ATE) and 544 controls. Five significant SNPs were further analyzed in an extended Austrian-Czech-NOPHO cohort (n = 107 cases, n = 211 controls) but none of the associations could be validated. Overall populations including all nations’ matched cohorts for ATE (n = 426) with seizure subgroup (n = 133) and posterior reversible encephalopathy syndrome (PRES, n = 251) were analyzed, as well. We found that patients with ABCB1 rs1045642, rs1128503 or rs2032582 TT genotypes were more prone to have seizures but those with rs1045642 TT developed PRES less frequently. The same SNPs were also examined in relation to ALL relapse on a case-control matched cohort of 320 patients from all groups. Those with rs1128503 CC or rs2032582 GG genotypes showed higher incidence of CNS relapse. Our results suggest that blood-brain-barrier drug transporter gene-polymorphisms might have an inverse association with seizures and CNS relapse

A gyermekkori koronavírus-fertőzést követő sokszervi gyulladás diagnosztikája és kezelése

A SARS-CoV-2-fertőzés ritka gyermekkori szövődménye a sokszervi gyulladás, angol terminológiával paediatric inflammatory multisystem syndrome (PIMS). Két vagy több szerv érintettségével járó, súlyos tünetekkel induló betegségről van szó, amelynek tünetei átfedést mutatnak a Kawasaki-betegséggel, a toxikus sokk szindrómával és a makrofágaktivációs szindrómával. A PIMS-betegek intenzív terápiás osztályon vagy intenzív terápiás háttérrel rendelkező intézményben kezelendők, ahol biztosítottak a kardiológiai ellátás feltételei is. A szükséges immunterápia a klinikai prezentációtól függ. A jelen közleményben a szerzők a releváns nemzetközi irodalom áttekintését követően ajánlást tesznek a PIMS diagnosztikai és terápiás algoritmusára. Orv Hetil. 2021; 162(17): 652-667. Summary. Pediatric inflammatory multisystem syndrome (PIMS) is a rare complication of SARS-CoV-2 infection in children. PIMS is a severe condition, involving two or more organ systems. The symptoms overlap with Kawasaki disease, toxic shock syndrome and macrophage activation syndrome. PIMS patients should be treated in an intensive care unit or in an institution with an intensive care background, where cardiological care is also provided. The required specific immunotherapy depends on the clinical presentation. In this paper, after reviewing the relevant international literature, the authors make a recommendation for the diagnostic and therapeutic algorithm for PIMS. Orv Hetil. 2021; 162(17): 652-667

EASY-APP : An artificial intelligence model and application for early and easy prediction of severity in acute pancreatitis

Acute pancreatitis (AP) is a potentially severe or even fatal inflammation of the pancreas. Early identification of patients at high risk for developing a severe course of the disease is crucial for preventing organ failure and death. Most of the former predictive scores require many parameters or at least 24 h to predict the severity; therefore, the early therapeutic window is often missed.The early achievable severity index (EASY) is a multicentre, multinational, prospective and observational study (ISRCTN10525246). The predictions were made using machine learning models. We used the scikit-learn, xgboost and catboost Python packages for modelling. We evaluated our models using fourfold cross-validation, and the receiver operating characteristic (ROC) curve, the area under the ROC curve (AUC), and accuracy metrics were calculated on the union of the test sets of the cross-validation. The most critical factors and their contribution to the prediction were identified using a modern tool of explainable artificial intelligence called SHapley Additive exPlanations (SHAP).The prediction model was based on an international cohort of 1184 patients and a validation cohort of 3543 patients. The best performing model was an XGBoost classifier with an average AUC score of 0.81 ± 0.033 and an accuracy of 89.1%, and the model improved with experience. The six most influential features were the respiratory rate, body temperature, abdominal muscular reflex, gender, age and glucose level. Using the XGBoost machine learning algorithm for prediction, the SHAP values for the explanation and the bootstrapping method to estimate confidence, we developed a free and easy-to-use web application in the Streamlit Python-based framework (http://easy-app.org/).The EASY prediction score is a practical tool for identifying patients at high risk for severe AP within hours of hospital admission. The web application is available for clinicians and contributes to the improvement of the model