Bratislava Medical Journal-Bratislavske Lekarske Listy最新文献

Non-invasive diabetes detection refers to the utilization and development of technologies and methods that can monitor and diagnose diabetes without requiring invasive procedures, namely invasive glucose monitoring or blood sampling. The objective is to provide a more convenient and less burdensome approach to screening and management of diabetes. It is noteworthy that while non-invasive method offers promising avenues for diabetes detection, they frequently require validation through clinical studies and might have limitation in terms of reliability and accuracy than classical invasive approaches. In recent times, deep learning (DL) and feature selection (FS) are used to monitor and diagnose diabetes accurately without requiring invasive procedures. This technique combines the FS method with the DL algorithm for making accurate predictions and extracting relevant features from non-invasive data. This article introduces a new Binary Fire Hawks Optimizer with Deep Learning-Driven Non-Invasive Diabetes Detection and Classification (BFHODL-NIDDC) technique. The major intention of the BFHODL-NIDDC technique focuses on the involvement of non-invasive procedures for the detection of diabetes. In the BFHODL-NIDDC technique, data preprocessing is initially performed to preprocess the input data. Next, the BFHO algorithm chooses an optimal subset of features and improves the classifier results. For the identification of diabetes, multichannel convolutional bidirectional long short-term memory (MC-BLSTM) model is used. At last, the beetle antenna search (BAS) algorithm is used for the hyperparameter selection of the MC-BLSTM method which in turn enhances the detection performance of the MC-BLSTM model. A series of simulations were conducted on the diabetes dataset to assess the diabetes detection performance of the BFHODL-NIDDC technique. The experimental outcomes illustrated better performance of the BFHODL-NIDDC method over other recent approaches in terms of different metrics (Tab. 4, Fig. 9, Ref. 23). Keywords: diabetes, non-invasive detection, binary fire hawks optimizer, deep learning, hyperparameter tuning.

Medication adherence is crucial for optimal treatment outcomes, yet many patients struggle to follow their prescribed regimens, impacting patients, families, and healthcare systems. Measurement of adherence is vital for effective care planning and intervention. This review explores medication adherence challenges and measurement methods, including therapeutic drug monitoring (TDM), medication event monitoring system (MEMS), analysis of adherence in insurance/pharmacy database, pill counts, and self-reports, each with its advantages and limitations.This review advocates a partnership-based approach to adherence, stressing standardized reporting and team-based care. Adherence is influenced by many factors such as complex regimens, packaging, patient perspectives, side effects. Effectively addressing these factors is crucial for improving patient outcomes. In summary, medication adherence is vital but complex. The article covers various adherence measurement methods to promote medication adherence as an important matter (Tab. 5, Fig. 2, Ref. 91). Text in PDF www.elis.sk Keywords: medication adherence, adherence barriers, primary non-adherence, medication event monitoring system, pill count, self-report.

Dental caries remains the most prevalent chronic, oral biofilm-associated disease affecting majority of the globe's population in all age categories. Despite enormous and revolutionary progress in omics technologies, it´s aetiology is not fully understood. The interest of current research is primarily focused on the identification and understanding of the crosstalk between main players such as host cell genome, oral microbiome´s genome, factors of immune response, saliva content and nutrition. For accurate, multi-omix analyses, it is essential to know which patient´s genes enter into crucial interactions. Identifying genes and understanding the mechanism of their action is the key for deeper understanding of their involvement in the pathogenesis of this disease. Serious alterations of these genes should be consequently used as markers to determine the extent of genetic predisposition to dental caries and identify susceptible patients. That should significantly improve the prevention, diagnostic and therapy of the disease with an individual approach and provide more efficient and effective implementation of newer preventive measures and novel therapeutic approaches in the management of the disease. This review focuses on contemporary evidence on genetics factors affecting dental caries and to provide an up-to-date comprehensive description and classification of the genes and their alterations influencing the disease. It also aims to delineate and discuss evidence gaps and potential novel applications of genetics in the context of recent advances (Tab. 2, Ref. 113). Text in PDF www.elis.sk Keywords: dental caries, candidate gene, genetic variation, multifactorial disease.

Despite the worldwide decrease in the incidence of gastric cancer, the proportion of occurrence of carcinomas of the esophagogastric junction and proximal third of stomach is on the rise. The cause of this development is believed to lie in an increasing incidence of reflux esophagitis with Barrett´s metaplasia and successful eradication of Helicobacter pylori infection. The aim of this work is to present various views on the definition of the esophagogastric junction itself and to give an overview of tumor classification schemes being used (Fig. 2, Ref. 54). Keywords: gastric cancer, esophagogastric junction, definition, classification.

Objectives: The objective of this study was to identify a parameter that can facilitate the diagnosis of prediabetes and predict the likelihood of its development in individuals at high risk.

Methods: In this retrospective study, the study population was selected from Bolu Abant Izzet Baysal University Hospital's patients. Participants were divided into two groups, prediabetes and healthy group. We excluded individuals with certain conditions or taking certain medications. The study compared the ratios of uric acid to high-density lipoprotein (HDL) between the two groups and identified the optimal point of differentiation.

Results: The study analyzed data from 228 individuals, including 125 with prediabetes and 103 healthy controls. Those with prediabetes had a significantly higher median UHR (0.13 (0.07-0.24) %) compared to healthy individuals (0.09 (0.05-0.16) %) (p < 0.001). Higher UHR values were associated with a greater risk of prediabetes. A UHR cut-off points greater than 0.11 % had a sensitivity of 74 % and specificity of 69 % in detecting prediabetes.

Conclusion: The study provides evidence that UHR can serve as a practical and valuable diagnostic and screening tool for prediabetes (Tab. 2, Fig. 1, Ref. 23). Text in PDF www.elis.sk Keywords: serum uric acid, HDL cholesterol, UHR, prediabetes.

Aim: To analyse postnatal characteristics, clinical and laboratory findings, results of investigations in the newborn (25 gestational weeks; Apgar score: 6/9 points; born per caesarean section; birth weight: 600 g; birth length: 31 cm; head circumference: 21 cm) from the first high-risk pregnancy with acquired form of acrodermatitis enteropathica.

Results: After summarizing the clinical picture with laboratory findings, we analysed the components of parenteral nutrition with regard to the deficiency of trace elements and vitamins. The zinc depletion dominated.

Conclusion: The diagnosis is clinical, based on the presence of a typical clinical picture together with a low serum zinc concentration. Standard preparations with elementary elements do not sufficiently cover the daily needs of children, other possibilities of supplementation in intravenous form are not available. It is necessary to supplement zinc in premature children, in children with high losses of zinc (with diarrhoea, in patients with a stoma, in patients with severe skin disease) (Fig. 4, Ref. 15).

Objective: To predict the possibility of postoperative atrial fibrillation (AF) with mitral annular plane systolic excursion (MAPSE) measurement, which is a cheap, reproducible echocardiographic method and to monitor these patients more closely and to evaluate them more effectively postoperatively.

Material and methods: 247 patients scheduled for coronary artery bypass surgery were evaluated and 200 patients were included in the study.The enrolled patients were classified into the two groups according to the occurrence of postoperative AF or maintained sinus rhythm after coronary artery bypass surgery (normal sinus rhythm [NSR] group vs. AF group).The clinical and demographic data of all the patients were recorded on admission. Two-dimensional transthoracic echocardiography (TTE) was performed prior to elective surgery.

Results: Postoperative new onset AF occurred in 37 (18.5%) patients. In the multivariate logistic regression analysis carried out after the formation of the model based on the parameters related to AF development, the relationships with white blood cell count, LAd and MAPSE were observed to be prevalent.When MAPSE, which is a parameter used to predict the development of postoperative atrial fibrillation, was compared in the ROC analysis, the area under the curve was found to be 0.831, 95% CI lower-95% CI upper (0.761-0.901) (p<0.001).The distinguishing MAPSE value in predicting postoperative atrial fibrillation development was found to be 11.6 (sensitivity: 90%, specificity: 81%).

Conclusions: We showed that MAPSE could play a role in determining postoperative atrial fibrillation development after coronary artery bypass surgery (Tab. 2, Fig. 2, Ref. 28).

Ntroduction: Distal pancreatectomy is a standard surgical procedure for selected benign, premalignant, and malignant lesions localized in the pancreatic body or tail. Surgical resection remains the only curative option for patients diagnosed with adenocarcinoma of the pancreas.

Patients and methods: Perioperative and postoperative clinical courses were retrospectively assessed in patients, who underwent distal pancreatectomy during the 2011‒2021 period.

Results: During the 2011‒2021 period, a total of 112 distal pancreatectomies were performed. 67 patients (59.8%) underwent laparoscopic distal pancreatectomy, and 45 patients (40.2%) open laparotomy. The conversion was necessary for 13 patients (11.6%). Distal pancreatectomies performed laparoscopically were associated more often with biochemical leak and the development of grade B fistula, on the other hand grade C fistula developed only in patients operated by open laparotomy (LPT). The mean operating time was slightly longer in the laparoscopic group (227.1 min vs 214.6 min). The mean estimated blood loss was significantly higher in the LPT group (540.4 ml vs 191.9 ml). The mean hospitalization time was slightly longer in the LPT group (11.8 days vs 9.3 days). The rates of early reoperations were comparable between both groups (6 vs 5).

Conclusion: Laparoscopic techniques are preferred in centers around the world to bring patients benefits by using a minimally invasive approach. These techniques are also preferred in our center, in nearly 60% of all distal pancreatectomies performed during 10 years, but on the other hand, there is a much more careful approach chosen in cases of malignant disease to achieve adequate radicality (Tab.4, Ref. 20).

Objectives: The aim of this study is to determine the role of Respiratory Rate Oxygenation (ROX), shock, and diastolic shock indexes ​​in predicting mortality in coronavirus disease 2019 (COVID-19) patients admitted to the emergency department.

Background: The COVID-19 spread worldwide in a short time and caused a major pandemic. The ROX, shock, and diastolic shock indexes are used in various life-threatening clinical situations. The use of these indexes in triage at emergency departments can accelerate the determination of COVID-19 patients' severity.

Methods: The ROX, shock and diastolic shock indices were calculated and recorded. Patients were divided into three groups; 1) who were discharged from the hospital, 2) who were admitted to the hospital and 3) who were admitted to the intensive care unit.

Results: Increased diastolic shock index and decreased ROX index were found to be independent risk factors for mortality. In the prediction of mortality, the sensitivity and specificity of the diastolic shock index were 61.2% and 60.8%, respectively. However, the sensitivity and specificity of ROX index was 73.1% and 71.5%, respectively.

Conclusion: In conclusion, we found that the ROX index had higher sensitivity and specificity than other indexes in predicting mortality in the evaluation of COVID-19 patients (Tab. 3, Fig. 2, Ref. 18).

Hepatocellular carcinoma (HCC) is one of the most common forms of cancer significantly affecting the mortality and morbidity rates. The increasing incidence of HCC is a great concern across the globe. The current methods of HCC screening, detection and diagnosis depend mainly on imaging techniques. However, biomarkers represent a relatively easy and noninvasive way to detect and estimate the disease prognosis. New potential biomarkers such as α-fetoprotein (AFP), des‑γ‑carboxyprothrombin (DCP), α-fetoprotein L3 (AFP-L3), glypican 3 (GCP3), micro-RNA, and Golgi-protein 73 (GP73) are being used more often in the diagnosis and prognosis of HCC. The lack of prudent diagnostic measures makes early detection of HCC nearly impossible. The use of biomarkers to detect cancer has helped to screen for the disease. However, the most commonly used biomarkers for HCC have inadequate performance characteristics. Despite numerous efforts to identify molecules as potential biomarkers, there is no single ideal marker for HCC. In this paper the main biomarkers for the surveillance, diagnosis and prognosis of HCC are reviewed. The advantages and limitations of these biomarkers are summarized, and the future development directions are proposed (Tab. 1, Ref. 30). Keywords: hepatocellular carcinoma, biomarkers, AFP, DCP, diagnosis.