[In this paper we present the Comprehensive Aphasia Test-Hungarian (CAT-H; Zakariás and Lukács, in preparation), an assessment tool newly adapted to Hungarian, currently under standardisation. The test is suitable for the assessment of an acquired language disorder, post-stroke aphasia. The aims of this paper are to present 1) the main characteristics of the test, its areas of application, and the process of the Hungarian adaptation and standardisation, 2) the first results from a sample of Hungarian people with aphasia and healthy controls. Ninety-nine people with aphasia, mostly with unilateral, left hemisphere stroke, and 19 neurologically intact control participants were administered the CAT-H. In addition, we developed a questionnaire assessing demographic and clinical information. The CAT-H consists of two parts, a Cognitive Screening Test and a Language Test. People with aphasia performed significantly worse than the control group in all language and almost all cognitive subtests of the CAT-H. Consistent with our expectations, the control group performed close to ceiling in all subtests, whereas people with aphasia exhibited great individual variability both in the language and the cognitive subtests. In addition, we found that age, time post-onset, and type of stroke were associated with cognitive and linguistic abilities measured by the CAT-H. Our results and our experiences clearly show that the CAT-H provides a comprehensive profile of a person’s impaired and intact language abilities and can be used to monitor language recovery as well as to screen for basic cognitive deficits in aphasia. We hope that the CAT-H will be a unique resource for rehabilitation professionals and aphasia researchers in aphasia assessment and diagnostics in Hungary. ]

[The diagnosis of hypertension is important, as high blood pressure is the most frequent and consequently the most important risk factor of cardiovascular diseases leading to mortality. The basis of diagnosis is the correct blood pressure measurement. Recent guidelines underline the importance of out of office (home and ambulatory) blood pressure monitoring besides the traditional office measurements. These methods have not only additive prognostic value, but with the help of these measurements, special hypertension forms (white coat and masked hypertension) can be diagnosed. On top of all these, home monitoring in­creases the patient’s compliance to the therapy. This short review summarizes the most important information on blood pressure measurement.]

[What has Go to do with making clinical decisions? One of the greatest intellectual challenges of bedside medicine is making decisions under uncertainty. Besides the psychological traps of traditionally intuitive and heuristic medical decision making, lack of information, scarce resources and characteristics of doctor-patient relationship contribute equally to this uncertainty. Formal, mathematical model based analysis of decisions used widely in developing clinical guidelines and in health technology assessment provides a good tool in theoretical terms to avoid pitfalls of intuitive decision making. Nevertheless it can be hardly used in individual situations and most physicians dislike it as well. This method, however, has its own limitations, especially while tailoring individual decisions, under inclusion of potential lack of input data used for calculations, or its large imprecision, and the low capability of the current mathematical models to represent the full complexity and variability of processes in complex systems. Nevertheless, clinical decision support systems can be helpful in the individual decision making of physicians if they are well integrated in the health information systems, and do not break down the physicians’ autonomy of making decisions. Classical decision support systems are knowledge based and rely on system of rules and problem specific algorithms. They are utilized widely from health administration to image processing. The current information revolution created the so-called artificial intelligence by machine learning methods, i.e. machines can learn indeed. This new generation of artificial intelligence is not based on particular system of rules but on neuronal networks teaching themselves by huge databases and general learning algorithms. This type of artificial intelligence outperforms humans already in certain fields like chess, Go, or aerial combat. Its development is full of challenges and threats, while it presents a technological breakthrough, which cannot be stopped and will transform our world. Its development and application has already started also in the healthcare. Health professionals must participate in this development to steer it into the right direction. Lee Sedol, 18-times Go world champion retired three years after his historical defeat from AlphaGo artificial intelligence, be­cause “Even if I become the No. 1, there is an entity that cannot be defeated”. It is our great luck that we do not need to compete or defeat it, we must ensure instead that it would be safe and trustworthy, and in collaboration with humans this entity would make healthcare more effective and efficient. ]

[Poststroke aphasia severity is related to several demographic, lesion-specific, and clinical factors. However, results about the importance of these factors are controversial. The aim of the current study was to investigate the effects of demographic and clinical factors on aphasia severity as well as on expressive and receptive language skills in a sample of Hungarian-speaking people with aphasia. 

Ninety-four people with aphasia with mainly unilateral left-hemisphere stroke (87.88%) participated. We used multiple stepwise linear regression to investigate the relationships between potential predictors – i.e., sex, education, time postonset, etiology, lesion localisation, pathological changes in the brain caused by small vessel disease, and other neurogenic communication disorders/swallowing disorders – and language outcome. As outcome variables, we used the total score, the receptive score, and the expressive score of the Hungarian Aphasia Screening Test.

Less years of education, pathological changes in the brain (white matter hypodensities/hyperintensities and subcortical lacunar lesions) and apraxia of speech were associated with more severe aphasia. Pathological changes and apraxia of speech were also associated with lower expressive language skills in aphasia. Finally, education, pathological changes, and sex predicted receptive language skills in poststroke aphasia (p < 0.05 in all three models).  

Pathological changes, apraxia of speech, education, and sex may affect language outcome in poststroke aphasia. We discuss our findings in light of the results of previous studies. ]

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