Disadvantaged socioeconomic status is associated with higher stroke incidence and mortality, and higher readmission rate. We aimed to assess the effect of socioeconomic factors on case fatality, health related quality of life (HRQoL), and satisfaction with care of stroke survivors in the framework of the European Health Care Outcomes, Performance and Efficiency (EuroHOPE) study in Hungary, one of the leading countries regarding stroke mortality. We evaluated 200 consecutive patients admitted for first-ever ischemic stroke in a single center and performed a follow-up at 3 months after stroke. We recorded pre- and post-stroke socioeconomic factors, and assessed case fatality, HRQoL and patient satisfaction with the care received. Stroke severity at onset was scored by the National Institutes of Health Stroke scale (NIHSS), disability at discharge from acute care was evaluated by the modified Rankin Score (mRS). To evaluate HRQoL and patient satisfaction with care we used the EQ-5D-5L, 15D and EORTC IN PATSAT 32 questionnaires. At 3 months after stroke the odds of death was significantly increased by stroke severity (NIHSS, OR = 1.209, 95%CI: 1.125–1.299, p<0.001) and age (OR = 1.045, 95%CI: 1.003–1.089, p = 0.038). In a multiple linear regression model, independent predictors of HRQoL were age, disability at discharge, satisfaction with care, type of social dwelling after stroke, length of acute hospital stay and rehospitalization. Satisfaction with care was influenced negatively by stroke severity (Coef. = -1.111, 95%C.I.: -2.159- -0.062, p = 0.040), and positively by having had thrombolysis (Coef. = 25.635, 95%C.I.: 5.212–46.058, p = 0.016) and better HRQoL (Coef. = 22.858, 95%C.I.: 6.007–39.708, p = 0.009). In addition to age, disability, and satisfaction with care, length of hospital stay and type of social dwelling after stroke also predicted HRQoL. Long-term outcome after stroke could be improved by reducing time spent in hospital, i.e. by developing home care rehabilitation facilities thus reducing the need for readmission to inpatient care.

Psychiatric symptoms (PS) can be non-motor features in Parkinson’s disease (PD) which are common even in the prodromal, untreated phase of the disease. Some PS, especially depression and anxiety recently became known predictive markers for PD. Our objective was to explore retrospectively the prevalence of PS before the diagnosis of PD. In the framework of the Hungarian Brain Research Program we created a database from medical and medication reports submitted for reimbursement purposes to the National Health Insurance Fund in Hungary, a country with 10 million inhabitants and a single payer health insurance system. We used record linkage to evaluate the prevalence of PS before the diagnosis of PD and compared that with patients with ischemic cerebrovascular lesion (ICL) in the period between 2004–2016 using ICD-10 codes of G20 for PD, I63-64 for ICL and F00-F99 for PS. We included only those patients who got their PD, ICL and psychiatric diagnosis at least twice. There were 79 795 patients with PD and 676 874 patients with ICL. Of the PD patients 16% whereas of those with ischemic cerebrovascular lesion 9.7% had a psychiatric diagnosis before the first appearance of PD or ICL (p<0.001) established in psychiatric care at least twice. The higher rate of PS in PD compared to ICL remained significant after controlling for age and gender in logistic regression analysis. The difference between PD and ICL was significant for Mood disorders (F30-F39), Organic, including symptomatic, mental disorders (F00-F09), Neurotic, stress-related and somatoform disorders (F40-F48) and Schizophrenia, schizotypal and delusional disorders (F20-F29) diagnosis categories (p<0.001, for all). The higher rate of psychiatric morbidity in the premotor phase of PD may reflect neurotransmitter changes in the early phase of PD.

As there were only regional studies in Hungary about the prevalence of multiple sclerosis (MS), we aimed to estimate its epidemiological features using data of Hungary’s single-payer health insurance system. Pseudonymized database of claims reported by hospitals and outpatient services between 2004–2016 was analyzed and linked with an independent database of outpatient pharmacy refills between 2010–2016. We established an administrative case definition of MS and validated it on medical records of 309 consecutive patients. A subject was defined as MS-patient if received MS diagnosis (International Classification of Diseases, 10th edition, code G35) on three or more occasions at least in 2 calendar years and at least once documented by a neurologist. Patients were counted as incident cases in the year of the first submitted claim for MS. We allowed a 6-year-long run-in period, so only data between 2010–2015 are discussed. Sensitivity of the administrative case definition turned out to be 99%, while specificity was >99%. Crude prevalence of MS has increased from 109.3/100,000 in 2010 to 130.8/100,000 in 2015 (p-value = 0.000003). Crude incidence declined from 7.1/100,000 (2010) to 5.4/100,000 (2015) (p-value = 0.018). Direct standardization − based on European standard population and results of nationwide Hungarian census of 2011 − revealed that age standardized prevalence was 105.2/100,000 (2010), which has grown to 127.2/100,000 (2015) (p-value = 0.000001). Age standardized incidence rate declined from 6.7/100,000 (2010) to 5.1/100,000 (2015) (p-value = 0.016). The ratio of MS-patients receiving ≥1 prescription for disease modifying treatment increased from 0.19 (2010) to 0.29 (2015) (p-value = 0.0051). The female/male ratio of prevalent cases remained 2.6. The prevalence of MS in Hungary is higher than previously reported, the incidence rate is moderate. The prevalence is rising, the incidence rate shows decline. The proportion of patients receiving disease modifying treatment grows but was still around 30% in 2015.

Data about the coronavirus disease 2019 (COVID-19) pandemic’s collateral damage on ischemic stroke (IS) care during the second epidemic wave in Central Europe are limited. We sought to evaluate the impact of the COVID-19 outbreak on Hungarian IS care during the two epidemic waves. This retrospective observational study was based on a nationwide reimbursement database that encompasses all IS admissions and all reperfusion interventions, i.e., intravenous thrombolysis (IVT) and endovascular therapy (EVT) from 2 January 2017 to 31 December 2020 in Hungary. COVID-19 pandemic’s effect on the number of IS admissions and reperfusion interventions were analyzed using different statistics: means, medians, trends, relative rates, and linear relationships. The mean and median values of IS admissions and reperfusion interventions decreased only in some measure during the COVID-periods. However, trend analysis demonstrated a significant decline from the trends. The decline’s dynamic and amplitude have differed for each variable. In contrast to IVT, the number of IS admissions and EVTs negatively correlated with the epidemic waves’ amplitude. Besides, the decrease in the number of IS admissions was more pronounced than the decrease in the number of reperfusion interventions. Our study demonstrated a significant disruption in IS care during the COVID-19 epidemic in Hungary, in which multiple different factors might play a role. The disproportionate reduction of IS admission numbers could partially be explained by the effect of health emergency operative measures and changes in patients’ social behavior. Further studies are needed to evaluate the causes of our observations.

Control charts have traditionally been used in industrial statistics but are constantly seeing new areas of application, especially in the age of Industry 4.0. This paper introduces a new method, which is suitable for applications in the health care sector, especially for monitoring the health characteristic of a patient. We adopt a Markov chain‐based approach and develop a method in which not only the shift size (ie, the degradation of the patient's health) can be random, but the effect of the repair (ie, treatment) and time between samplings (ie, visits) too. This means that we do not use many often‐present assumptions that are usually not applicable for medical treatments. The average cost of the protocol, which is determined by the time between samplings and the control limit, can be estimated using the stationary distribution of the Markov chain.Furthermore, we incorporate the standard deviation of the cost into the optimisation procedure, which is often very important from a process control viewpoint. The sensitivity of the optimal parameters and the resulting average cost and cost standard deviation on different parameter values is investigated. We demonstrate the usefulness of the approach for real‐life data of patients treated in Hungary, namely the monitoring of cholesterol level of patients with cardiovascular event risk. The results showed that the optimal parameters from our approach can be somewhat different from the original medical parameters.

Considerable depressive symptoms follow stroke in about one third of patients. Initial depressive symptoms may wane after the acute phase of stroke, but persisting depressive symptoms adversely affect rehabilitation and quality of life. We set forth to evaluate predictors of depressive symptoms with a focus on socioeconomic factors. We evaluated clinical features and socioeconomic characteristics in 233 consecutive patients with acute ischemic stroke or TIA. Depressive symptoms could be evaluated in 168 subjects in the acute phase with a repeated testing after a mean of 14.7 months via telephone interview in 116 patients. Survival status, scores on the Center for Epidemiologic Studies-Depression Scale (CES-D), Beck Depression Inventory (BDI) and disability (modified Rankin scale, mRS) were recorded. In the acute phase, employment status (p = 0.037) and level of education (p = 0.048) whereas one year later dependency (mRS≥3, p = 0.002) and income (p = 0.012) were the significant predictors of the severity of depressive symptoms. A change from independent (mRS≤2) to dependent living predicted worsening depressive symptoms (p = 0.008), whereas improving to functional independence from an initially dependent condition was associated with diminishing depressive symptoms (p = 0.077 for CES-D and p = 0.044 for BDI) in the first year after an acute ischemic cerebrovascular event. Predictors of the severity of depressive symptoms differed in the acute phase and at follow-up. In addition to disability, education and employment status in the acute phase and income in the late phase predict the severity of depressive symptoms after ischemic stroke or TIA.