Casopis lekaru ceskych最新文献

From anthropometrics point of view, the Roma have retained a distinct individuality and thus differ from the majority population. They are also distinguished by cultural differences, which are reflected in the concept of health and health care consumption. The available data show socially and culturally determined health inequalities and disadvantages of the Roma compared to the majority population, which do not change in the long term. Among others, the low level of cultural competence and sensitivity of health professionals to the needs of minorities and specifically to the Roma ethnicity also plays a role. The article describes health-relevant cultural differences in the context of Roma culture and way of life of the Czech Roma and outlines some of the barriers faced by Roma in healthcare.

The incidence of monoclonal gammopathy (MG) increases with age. In individuals over 80 years of age, we can diagnose the presence of monoclonal immunoglobulin (MIg) in up to 10 % of cases. Not only malignant diseases such as multiple myeloma (MM), but also benign forms such as MGUS (monoclonal gammopathy of undetermined significance) can lead to renal involvement. The light chains of immunoglobulins (LC) are the most damaging to the kidneys, as they are freely filtered into the urine due to their molecular weight. Detection of MIg relies mainly on a combination of immunofixation electrophoresis of serum (IELFO) and urine and determination of free light chains (FLC) of kappa and lambda and their ratio (κ/λ) in serum. The combination of these tests will detect the presence of MIg with 99 % sensitivity. Renal damage in MG may be caused by direct deposition of MIg in the glomeruli (e.g. AL amyloidosis, LC deposition disease) or tubules (in the distal tubule as a myeloma kidney or in the proximal tubule as Fanconi syndrome or proximal tubulopathy). Typical urinary findings in these diseases are moderate or severe proteinuria or nephrotic syndrome. Acute kidney injury (AKI) can be expected especially when serum FLC is >500 mg/l. Renal biopsy is crucial to establish an accurate diagnosis and thus initiate the correct treatment. Treatment of these types of renal damage involves the same treatment regimens used in the treatment of MM, including proteasome inhibitors or daratumumab.

The aim of the article to present the development of artificial intelligence (AI) methods and their applications in medicine and health care. Current technological development contributes to generation of large volumes of data that cannot be evaluated only manually. We describe the process of patient care and its individual parts that can be supported by technology and data analysis methods. There are many successful applications that help in the decision support process, in processing complex multidimensional heterogeneous and/or long-term data. On the other side, failures appear in AI methods applications. In recent years, deep learning became very popular and to a certain extend it delivered promising results. However, it has certain flaws that might lead to misclassification. The correct methodological steps in design and implementation of selected methods to data processing are briefly presented.

The advent of large language models (LLMs) based on neural networks marks a significant shift in academic writing, particularly in medical sciences. These models, including OpenAI's GPT-4, Google's Bard, and Anthropic's Claude, enable more efficient text processing through transformer architecture and attention mechanisms. LLMs can generate coherent texts that are indistinguishable from human-written content. In medicine, they can contribute to the automation of literature reviews, data extraction, and hypothesis formulation. However, ethical concerns arise regarding the quality and integrity of scientific publications and the risk of generating misleading content. This article provides an overview of how LLMs are changing medical writing, the ethical dilemmas they bring, and the possibilities for detecting AI-generated text. It concludes with a focus on the potential future of LLMs in academic publishing and their impact on the medical community.

In recent years healthcare is undergoing significant changes due to technological innovations, with Artificial Intelligence (AI) being a key trend. Particularly in radiodiagnostics, according to studies, AI has the potential to enhance accuracy and efficiency. We focus on AI's role in diagnosing pulmonary lesions, which could indicate lung cancer, based on chest X-rays. Despite lower sensitivity in comparison to other methods like chest CT, due to its routine use, X-rays often provide the first detection of lung lesions. We present our deep learning-based solution aimed at improving lung lesion detection, especially during early-stage of illness. We then share results from our previous studies validating this model in two different clinical settings: a general hospital with low prevalence findings and a specialized oncology center. Based on a quantitative comparison with the conclusions of radiologists of different levels of experience, our model achieves high sensitivity, but lower specificity than comparing radiologists. In the context of clinical requirements and AI-assisted diagnostics, the experience and clinical reasoning of the doctor play a crucial role, therefore we currently lean more towards models with higher sensitivity over specificity. Even unlikely suspicions are presented to the doctor. Based on these results, it can be expected that in the future artificial intelligence will play a key role in the field of radiology as a supporting tool for evaluating specialists. To achieve this, it is necessary to solve not only technical but also medical and regulatory aspects. It is crucial to have access to quality and reliable information not only about the benefits but also about the limitations of machine learning and AI in medicine.

Postoperative pneumonia is the most common complication in patients after lung resection for non-small cell lung cancer (NSCLC). The tolerable incidence of this complication ranges from 5 to 8 %. The aim of this study was to evaluate the influence of initial risk factors on the incidence of postoperative pneumonia in patients undergoing lung resection for NSCLC. A retrospective cohort study was conducted at the University Hospital Ostrava between January 1, 2016, and December 31, 2022. All adult patients who underwent pulmonary lobectomy for primary NSCLC during the study period were included in the study. A total of 350 patients were included in the study. The incidence of postoperative pneumonia was 10.9%. Analysis of baseline risk factors did not show a statistically significant association with the incidence of this complication. The only statistically significant finding was a longer hospital stay in patients with postoperative pneumonia. The risk of postoperative pneumonia in patients undergoing lung resection for non-small cell lung cancer cannot be clearly explained by the initial risk factors examined alone. The complex nature of this risk also requires a comprehensive approach to prevention, including both patient-centred measures and improved postoperative care.

The acute climacteric syndrome has a large scale of symptoms. Main symptoms are hot flashes and night sweats. Each symptom could be presented alone or commonly in combination with other symptoms. The acute climacteric syndrome is induced by decrease and fluctuations of estrogen and neurosteroids levels. Therapy could be focused on hormone replacement. Changes of quality of life and especially effects of the therapy could be measured by standardized questionaries.

The current era witnesses a highly dynamic development of Artificial Intelligence (AI) applications, impacting various human activities. Medical imaging techniques are no exception. AI can find application in image acquisition, image processing and augmentation, as well as in the actual interpretation of images. Moreover, within the domain of radiomics, AI can be instrumental in advanced analysis surpassing the capacities of the human eye and experience. While several certified commercial solutions are available, the validation and accumulation of sufficient evidence regarding their positive impact on healthcare is currently constrained. The role of AI presently leans towards being assistive, yet further evolution is anticipated. Risks and disadvantages encompass dependency on computational power, the quality of input data, and their annotation for learning purposes. The transparency of algorithmic functioning is lacking, and issues pertaining to portability may arise. The integration and utilization of AI introduce entirely new ethical and legislative aspects. Predicting the future development of AI in imaging methods is challenging, with a further increase in implementation appearing more probable.

The rapid increase in the proportion of women using hormonal contraception in the 1990s was positively reflected in a rapid decline in the number of abortions. Czechia was unique not only among Eastern European countries, but also worldwide. At the same time the decline in the prevalence of hormonal contraception from a peak of almost 50 % in 2007 to 30 % in 2021 meant a slowing and gradual halt in the further decline in abortions. The results of the GGP 2020-2022 survey in Czechia showed that the lower use of hormonal contraception among women was only partly offset by the increased use of other reliable methods of protection against unintended pregnancy (e.g. condom use). The largest decline in the use of hormonal contraceptives in the form of the pill occurred among the youngest women aged 18-27 years, from 76 to 37 %, which was partly reflected in the more intensive use of condoms (an increase from 21 to 35% in the 18-27 age group), but is worrying, that this age group saw the largest increase in the use of less reliable methods (withdrawal from 11 to 22 % and an increase in the use of the barren days method from 1 to 6 %) and also the largest increase in the proportion of women using neither method (from 7 to 17 %). The lowest proportion of female hormonal pill users was found among female with higher education. However an important finding is that when less reliable methods are used, there is an effort to combine at least two methods. Women have a more important role in determining how to protect themselves from unintended pregnancy.

The article evaluates the prevalence of infertility problems in the Czech population, identifies methods used by individuals or couples attempting to achieve pregnancy and evaluates in more detail the use of assisted reproduction technology (ART) in contemporary Czech society. The results show that 27% of women and men in their forties declare they have experienced a time when they were trying to get pregnant but did not conceive within at least 12 months. In the general population of reproductive age, one in five declares experience with methods helping to get pregnant. Methods that do not require a doctor's visit are the most frequently used (one in ten declare monitoring ovulation), and 5% of the general population have experience of ART. Among those who have experienced some period of infertility, the experience of methods to assist conception is significantly higher (3/4 of men and 2/3 of women), and the use of medically assisted reproduction is also higher (a quarter have experience of taking medication and a quarter of assisted reproduction).