Lege Artis Medicinae

[Thoughts About a Malpractice Decision]

DÓSA Ágnes

JUNE 20, 2010

Lege Artis Medicinae - 2010;20(06-07)

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Cases of inborn errors of metabolism diagnosed in children with autism

CAKAR Emel Nafiye, YILMAZBAS Pınar

Autism spectrum disorder is a neurodevelopmental disorder with a heterogeneous presentation, the etiology of which is not clearly elucidated. In recent years, comorbidity has become more evident with the increase in the frequency of autism and diagnostic possibilities of inborn errors of metabolism. One hundred and seventy-nine patients with diagnosis of autism spectrum disorder who presented to the Pediatric Metabolism outpatient clinic between 01/September/2018-29/February/2020 constituted the study population. The personal information, routine and specific metabolic tests of the patients were analyzed retrospectively. Out of the 3261 patients who presented to our outpatient clinic, 179 (5.48%) were diagnosed with autism spectrum disorder and were included in the study. As a result of specific metabolic examinations performed, 6 (3.3%) patients were diagnosed with inborn errors of metabolism. Two of our patients were diagnosed with classical phenylketonuria, two with classical homocystinuria, one with mucopolysaccharidosis type 3D (Sanfilippo syndrome) and one with 3-methylchrotonyl Co-A carboxylase deficiency. Inborn errors of metabolism may rarely present with autism spectrum disorder symptoms. Careful evaluation of the history, physical examination and additional findings in patients diagnosed with autism spectrum disorder will guide the clinician in the decision-making process and chose the appropriate specific metabolic investigation. An underlying inborn errors of metabolism may be a treatable cause of autism.

Lege Artis Medicinae

[Second game, 37th move and Fourth game 78th move]

VOKÓ Zoltán

[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. ]

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[Family planning is an exceptionally important question in multiple sclerosis, as women of childbearing age are the ones most often affected. Although it is proven that pregnancy does not worsen the long-term prognosis of relapsing-remitting multiple sclerosis, many patients are still doubtful about having children. This question is further complicated by the fact that patients – and often even doctors – are not sufficiently informed about how the ever-increasing number of available disease-modifying treatments affect pregnancies. Breastfeeding is an even less clear topic. Patients usually look to their neurologists first for answers concerning these matters. It falls to the neurologist to rationally evaluate the risks and benefits of contraception, pregnancy, assisted reproduction, childbirth, breastfeeding and disease modifying treatments, to inform patients about these, and then together come to a decision about the best possible therapeutic approach, taking the patients’ individual family plans into consideration. Here we present a review of relevant literature adhering to international guidelines on the topics of conception, pregnancy and breastfeeding, with a special focus on the applicability of approved disease modifying treatments during pregnancy and breastfeeding. The goal of this article is to provide clinicians involved in the care of MS patients with up-to-date information that they can utilize in their day-to-day clinical practice. ]

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[Az emlődaganatok radiológiai vizsgálatának újdonságai Onco Update, 2007]

FORRAI Gábor, BODOKY György

[Experiences about the breast diagnostic methods are accumulating year-to-year, rapidly. Therefore the current examination algorithm is changing continuously. New diagnostic and therapeutic modalities are entering into the daily practice. Some of them became obsolete, so far their application is becoming a faulty decision. Some other methods become obligatory steps in the diagnostics. These are the reasons why the up-to-date knowledge of the literature is mandatory. Systematic review of the most recent articles of the last two years (January 2005-December 2006) of breast radiological diagnostics and the actual place of the imaging and interventional methods are presented. The following topics are summarized: breast cancer screening with conventional and digital mammography, computer assisted diagnostics (CAD), high risk patients' screening, US, MRI, MSCT, PET/CT, diagnostic interventions, differential diagnostics, percutaneous tumour ablation, therapy-related questions in the diagnostic work up.]

Lege Artis Medicinae

[ANALYIS OF MOTIVATIONS OF SMOKING CESSATION]

SUSÁNSZKY Éva, SZÁNTÓ Zsuzsa, KOPP Mária

[INTRODUCTION - The aim of the study was to explore the differences in motivations between successful quitters and smokers who just consider quitting. Self-reported motivations of exsmokers' smoking cessation and the reasoning of current smokers who consider quitting were analyzed. SUBJECTS AND METHODS - The study is based on Hungarostudy Health Panel conducted in 2005, which is the second wave of Hungarostudy 2002, a national representative health survey of the adult Hungarian population. Of the subjects involved in this follow-up study, data from 3701 persons could be analyzed. RESULTS - About half of the respondents had never smoked, one fifth of them had quitted and 28 percent smoked. More than half of the current smokers (52%) contemplated on giving up smoking. Among ex-smokers and contemplating current smokers alike (38-40%), disease prevention was mentioned as the single most important reason of cessation. Financial reasons were mostly mentioned by current smokers; ex-smokers were more likely to explain their decision with deteriorating health, the occurrence of certain diseases. Among these, cardio-vascular morbidity played the most important role in smoking cessation while cancers, respiratory disease and diabetes also significantly increased the odds of quitting. Social pressure was a reason for quitting mostly among women and elderly persons. Among current smokers, those living in partner relationship and the better-off tended to entertain thoughts of quitting because of social pressure. CONCLUSION - The results confirm the importance of cardiovascular diseases in smoking cessation: although people emphasize primary preventive purposes of their cessation efforts, in fact secondary prevention, i.e., existing circulatory and heart problems play the major role both in actual cessation and in quitting considerations.]