Relationships between the Structural Characteristics of General Medical Practices and the Socioeconomic Status of Patients with Diabetes-Related Performance Indicators in Primary Care.

The implementation of monitoring for general medical practice (GMP) can contribute to improving the quality of diabetes mellitus (DM) care. Our study aimed to describe the associations of DM care performance indicators with the structural characteristics of GMPs and the socioeconomic status (SES) of patients. Using data from 2018 covering the whole country, GMP-specific indicators standardized by patient age, sex, and eligibility for exemption certificates were computed for adults. Linear regression models were applied to evaluate the relationships between GMP-specific parameters (list size, residence type, geographical location, general practitioner (GP) vacancy and their age) and patient SES (education, employment, proportion of Roma adults, housing density) and DM care indicators. Patients received 58.64% of the required medical interventions. A lower level of education (hemoglobin A1c test: ß = -0.108; ophthalmic examination: ß = -0.100; serum creatinine test: ß = -0.103; and serum lipid status test: ß = -0.108) and large GMP size (hemoglobin A1c test: ß = -0.068; ophthalmological examination ß = -0.031; serum creatinine measurement ß = -0.053; influenza immunization ß = -0.040; and serum lipid status test ß = -0.068) were associated with poor indicators. A GP age older than 65 years was associated with lower indicators (hemoglobin A1c test: ß = -0.082; serum creatinine measurement: ß = -0.086; serum lipid status test: ß = -0.082; and influenza immunization: ß = -0.032). Overall, the GMP-level DM care indicators were significantly influenced by GMP characteristics and patient SES. Therefore, proper diabetes care monitoring for the personal achievements of GPs should involve the application of adjusted performance indicators.

Cross-sectional comparison of health care delivery and reimbursement between segregated and nonsegregated communities in Hungary.

Introduction: Spatially segregated, socio-economically deprived communities in Europe are at risk of being neglected in terms of health care. In Hungary, poor monitoring systems and poor knowledge on the health status of people in these segregated areas prevent the development of well-informed effective interventions for these vulnerable communities. Aims: We used data available from National Health Insurance Fund Management to better describe health care performance in segregated communities and to develop more robust monitoring systems. Methods: A cross-sectional study using 2020 health care data was conducted on each general medical practice (GMP) in Hungary providing care to both segregated and nonsegregated (complementary) adult patients. Segregated areas were mapped and ascertained by a governmental decree that defines them as within settlement clusters of adults with low level of education and income. Age, sex, and eligibility for exemption certificate standardized indicators for health care delivery, reimbursement, and premature mortality were computed for segregated and nonsegregated groups of adults and aggregated at the country level. The ratio of segregation and nonsegregation specific indicators (relative risk, RR) was computed with the corresponding 95% confidence intervals (95% CI). Results: Broad variations between GMPs were detected for each indicator. Segregated groups had a significantly higher rate of health care service use than complementary groups (RR = 1.22, 95% CI: 1.219;1.223) while suffering from significantly reduced health care reimbursement (RR = 0.940, 95% CI: 0.929;0.951). The risk of premature mortality was significantly higher among segregated patients (RR = 1.184, 95% CI: 1.087;1.289). Altogether, living in a segregated area led to an increase in visits to health care services by 18.1% with 6.6% less health spending. Conclusion: Adults living in segregated areas use health care services more frequently than those living in nonsegregated areas; however, the amount of health care reimbursement they receive is significantly lower, suggesting lower quality of care. The health status of segregated adults is remarkably lower, as evidenced by their higher premature mortality rate. These findings demonstrate the need for intervention in this vulnerable group. Because our study reveals serious variation across GMPs, segregation-specific monitoring is necessary to support programs sensitive to local issues and establish necessary benchmarks.

Single Nucleotide Variants (SNVs) of the Mesocorticolimbic System Associated with Cardiovascular Diseases and Type 2 Diabetes: A Systematic Review.

The mesocorticolimbic (MCL) system is crucial in developing risky health behaviors which lead to cardiovascular diseases (CVDs) and type 2 diabetes (T2D). Although there is some knowledge of the MCL system genes linked to CVDs and T2D, a comprehensive list is lacking, underscoring the significance of this review. This systematic review followed PRISMA guidelines and the Cochrane Handbook for Systematic Reviews of Interventions. The PubMed and Web of Science databases were searched intensively for articles related to the MCL system, single nucleotide variants (SNVs, formerly single nucleotide polymorphisms, SNPs), CVDs, T2D, and associated risk factors. Included studies had to involve a genotype with at least one MCL system gene (with an identified SNV) for all participants and the analysis of its link to CVDs, T2D, or associated risk factors. The quality assessment of the included studies was performed using the Q-Genie tool. The VEP and DAVID tools were used to annotate and interpret genetic variants and identify enriched pathways and gene ontology terms associated with the gene list. The review identified 77 articles that met the inclusion criteria. These articles provided information on 174 SNVs related to the MCL system that were linked to CVDs, T2D, or associated risk factors. The COMT gene was found to be significantly related to hypertension, dyslipidemia, insulin resistance, obesity, and drug abuse, with rs4680 being the most commonly reported variant. This systematic review found a strong association between the MCL system and the risk of developing CVDs and T2D, suggesting that identifying genetic variations related to this system could help with disease prevention and treatment strategies.

Association of HDL Subfraction Profile with the Progression of Insulin Resistance.

Type 2 diabetes mellitus (T2DM) is a major global public health problem, as it is associated with increased morbidity, mortality, and healthcare costs. Insulin resistance (IR) is a condition characterized by disturbances in carbohydrate and lipid metabolism that precedes T2DM. The aim of the present study was to investigate the association between HDL and its subfraction profile and the progression of IR, as assessed by the Homeostatic Model Assessment for IR (HOMA-IR) index, and to define cut-off values to identify an increased risk of IR. Individuals with a HOMA-IR greater than 3.63 were considered to have IR. The HDL subfractions were separated using the Lipoprint system, which identifies ten subfractions (HDL-1-10) in three subclasses as large (HDL-L), intermediate (HDL-I) and small (HDL-S). Analyses were performed on samples from 240 individuals without IR and 137 with IR from the Hungarian general and Roma populations. The HDL-1 to -6 subfractions and the HDL-L and -I classes showed a significant negative association with the progression and existence of IR. Among them, HDL-2 (B = -40.37, p = 2.08 × 10-11) and HDL-L (B = -14.85, p = 9.52 × 10-10) showed the strongest correlation. The optimal threshold was found to be 0.264 mmol/L for HDL-L and 0.102 mmol/L and above for HDL-2. Individuals with HDL-L levels below the reference value had a 5.1-fold higher risk of IR (p = 2.2 × 10-7), while those with HDL-2 levels had a 4.2-fold higher risk (p = 3.0 × 10-6). This study demonstrates that the HDL subfraction profile (especially the decrease in HDL-2 and -L) may be a useful marker for the early detection and intervention of atherogenic dyslipidemia in subjects with impaired glucose and insulin metabolism.

A Transcriptomic Analysis of Smoking-Induced Gene Expression Alterations in Coronary Artery Disease Patients.

Smoking is a well established risk factor for coronary artery disease (CAD). Despite this, there have been no previous studies investigating the effects of smoking on blood gene expression in CAD patients. This single-centre cross-sectional study was designed with clearly defined inclusion criteria to address this gap. We conducted a high-throughput approach using next generation sequencing analysis with a single-end sequencing protocol and a read length of 75-cycles. Sixty-one patients with a median age of 67 years (range: 28-88 years) were recruited, and only 44 subjects were included for further analyses. Our investigation revealed 120 differentially expressed genes (DEGs) between smokers and nonsmokers, with a fold change (FC) of ≥1.5 and a p-value < 0.05. Among these DEGs, 15 were upregulated and 105 were downregulated. Notably, when applying a more stringent adjusted FC ≥ 2.0, 31 DEGs (5 upregulated, annotated to immune response pathways, and 26 downregulated, involving oxygen and haem binding or activity, with FDR ≤ 0.03) remained statistically significant at an alpha level of <0.05. Our results illuminate the molecular mechanisms underlying CAD, fortifying existing epidemiological evidence. Of particular interest is the unexplored overexpression of RCAN3, TRAV4, and JCHAIN genes, which may hold promising implications for the involvement of these genes in CAD among smokers.

A combination of strongly associated prothrombotic single nucleotide polymorphisms could efficiently predict venous thrombosis risk.

Background: Venous thrombosis (VT) is multifactorial trait that contributes to the global burden of cardiovascular diseases. Although abundant single nucleotide polymorphisms (SNPs) provoke the susceptibility of an individual to VT, research has found that the five most strongly associated SNPs, namely, rs6025 (F5 Leiden), rs2066865 (FGG), rs2036914 (F11), rs8176719 (ABO), and rs1799963 (F2), play the greatest role. Association and risk prediction models are rarely established by using merely the five strongly associated SNPs. This study aims to explore the combined VT risk predictability of the five SNPs and well-known non-genetic VT risk factors such as aging and obesity in the Hungarian population. Methods: SNPs were genotyped in the VT group (n = 298) and control group (n = 400). Associations were established using standard genetic models. Genetic risk scores (GRS) [unweighted GRS (unGRS), weighted GRS (wGRS)] were also computed. Correspondingly, the areas under the receiver operating characteristic curves (AUCs) for genetic and non-genetic risk factors were estimated to explore their VT risk predictability in the study population. Results: rs6025 was the most prevalent VT risk allele in the Hungarian population. Its risk allele frequency was 3.52-fold higher in the VT group than that in the control group [adjusted odds ratio (AOR) = 3.52, 95% CI: 2.50-4.95]. Using all genetic models, we found that rs6025 and rs2036914 remained significantly associated with VT risk after multiple correction testing was performed. However, rs8176719 remained statistically significant only in the multiplicative (AOR = 1.33, 95% CI: 1.07-1.64) and genotypic models (AOR = 1.77, 95% CI: 1.14-2.73). In addition, rs2066865 lost its significant association with VT risk after multiple correction testing was performed. Conversely, the prothrombin mutation (rs1799963) did not show any significant association. The AUC of Leiden mutation (rs6025) showed better discriminative accuracy than that of other SNPs (AUC = 0.62, 95% CI: 0.57-0.66). The wGRS was a better predictor for VT than the unGRS (AUC = 0.67 vs. 0.65). Furthermore, combining genetic and non-genetic VT risk factors significantly increased the AUC to 0.89 with statistically significant differences (Z = 3.924, p < 0.0001). Conclusions: Our study revealed that the five strongly associated SNPs combined with non-genetic factors could efficiently predict individual VT risk susceptibility. The combined model was the best predictor of VT risk, so stratifying high-risk individuals based on their genetic profiling and well-known non-modifiable VT risk factors was important for the effective and efficient utilization of VT risk preventive and control measures. Furthermore, we urged further study that compares the VT risk predictability in the Hungarian population using the formerly discovered VT SNPs with the novel strongly associated VT SNPs.

Psychiatric health care need in Hungary identified by the short screening algorithm of depression and suicide risk used in general medical practices.

Suicides are often related to depression. General medical practices (GMPs) should play a role in screening depression. We aimed to test the screening algorithm of Rihmer and Torzsa for depression and suicide and determine the prevalence and number of patients in the nationwide representative Hungarostudy 2002 population, and to estimate the corresponding extra health care need in an average GMP and in the Hungarian population in addition to patients who are already cared for by specialized care. The short version of the Beck Hopelessness Scale (BHS) and the Hungarian version of the short form of the Beck Depression Inventory (BDI-9) were used to screen for suicide risk and depression. The prevalence of suicidal thoughts and depression was determined and findings were extrapolated to an average GMP of 1,600 adults and to the population over 25 years of age. This screening would generate a considerable extra psychiatric care to organize and implement in an average GMP and throughout the country. Our findings show that with easily administered screening instruments a significant number of patients likely to have depression can be identified at the primary care level, arguing for the establishment of the extra psychiatric care capacity in Hungary.

Screening for Patients with Visual Acuity Loss in Primary Health Care: A Cross Sectional Study in a Deprived Hungarian Population.

Screening for visual acuity loss (VAL) is not applied systematically because of uncertain recommendations based on observations from affordable countries. Our study aimed to evaluate the effectiveness of primary health care-based screening. A cross-sectional investigation was carried out among adults who did not wear glasses and did not visit an ophthalmologist in a year (N = 2070). The risk factor role of sociodemographic factors and the cardiometabolic status for hidden VAL was determined by multivariable linear regression models. The prevalence of unknown VAL of at least 0.5 was 3.7% and 9.1% in adults and in the above-65 population. Female sex (b = 1.27, 95% CI: 0.35; 2.18), age (b = 0.15, 0.12; 0.19), and Roma ethnicity (b = 2.60, 95% CI: 1.22; 3.97) were significant risk factors. Higher than primary school (bsecondaryschoolwithoutgraduation = -2.06, 95% CI: -3.64; -0.47; and bsecondaryschoolwithgraduation = -2.08, 95% CI: -3.65; -0.51), employment (b = -1.33, 95% CI: -2.25; 0.40), and properly treated diabetes mellitus (b = -2.84, 95% CI: -5.08; -0.60) were protective factors. Above 65 years, female sex (b = 3.85, 95% CI: 0.50; 7.20), age (b = 0.39, 95% CI: 0.10; 0.67), Roma ethnicity (b = 24.79, 95% CI: 13.83; 35.76), and untreated diabetes (b = 7.30, 95% CI: 1.29; 13.31) were associated with VAL. Considering the huge differences between the health care and the population's social status of the recommendation-establishing countries and Hungary which represent non-high-income countries, the uncertain recommendation of VAL screening should not discourage general practitioners from organizing population-based screening for VAL in non-affordable populations.

Association of CETP Gene Polymorphisms and Haplotypes with Cardiovascular Risk.

Cholesteryl ester transfer protein (CETP) is known to influence HDL-C levels, potentially altering the profile of HDL subfractions and consequently cardiovascular risk (CVR). This study aimed to investigate the effect of five single-nucleotide polymorphisms (SNPs; rs1532624, rs5882, rs708272, rs7499892, and rs9989419) and their haplotypes (H) in the CETP gene on 10-year CVR estimated by the Systematic Coronary Risk Evaluation (SCORE), the Framingham Risk Score for Coronary Heart Disease (FRSCHD) and Cardiovascular Disease (FRSCVD) algorithms. Adjusted linear and logistic regression analyses were used to investigate the association of SNPs and 10 haplotypes (H1-H10) on 368 samples from the Hungarian general and Roma populations. The T allele of rs7499892 showed a significant association with increased CVR estimated by FRS. H5, H7, and H8 showed a significant association with increased CVR based on at least one of the algorithms. The impact of H5 was due to its effect on TG and HDL-C levels, while H7 showed a significant association with FRSCHD and H8 with FRSCVD mediated by a mechanism affecting neither TG nor HDL-C levels. Our results suggest that polymorphisms in the CETP gene may have a significant effect on CVR and that this is not mediated exclusively by their effect on TG and HDL-C levels but also by presently unknown mechanisms.

Effectiveness of and Inequalities in COVID-19 Epidemic Control Strategies in Hungary: A Nationwide Cross-Sectional Study.

INTRODUCTION: Before the mass vaccination, epidemiological control measures were the only means of containing the COVID-19 epidemic. Their effectiveness determined the consequences of the COVID-19 epidemic. Our study evaluated the impact of sociodemographic, lifestyle, and clinical factors on patient-reported epidemiological control measures. METHODS: A nationwide representative sample of 1008 randomly selected adults were interviewed in person between 15 March and 30 May 2021. The prevalence of test-confirmed SARS-CoV-2 infection was 12.1%, of testing was 33.7%, and of contact tracing among test-confirmed infected subjects was 67.9%. The vaccination coverage was 52.4%. RESULTS: According to the multivariable logistic regression models, the occurrence of infection was not influenced by sociodemographic and lifestyle factors or by the presence of chronic disease. Testing was more frequent among middle-aged adults (aOR = 1.53, 95% CI 1.10-2.13) and employed adults (aOR = 2.06, 95% CI 1.42-3.00), and was more frequent among adults with a higher education (aORsecondary = 1.93, 95% CI 1.20-3.13; aORtertiary = 3.19, 95% CI 1.81-5.63). Contact tracing was more frequently implemented among middle-aged (aOR41-7y = 3.33, 95% CI 1.17-9.45) and employed (aOR = 4.58, 95% CI 1.38-15.22), and those with chronic diseases (aOR = 5.92, 95% CI 1.56-22.47). Positive correlation was observed between age groups and vaccination frequency (aOR41-70y = 2.94, 95% CI 2.09-4.15; aOR71+y = 14.52, 95% CI 7.33-28.77). Higher than primary education (aORsecondary = 1.69, 95% CI 1.08-2.63; aORtertiary = 4.36, 95% CI 2.46-7.73) and the presence of a chronic disease (aOR = 2.58, 95% CI 1.75-3.80) positively impacted vaccination. Regular smoking was inversely correlated with vaccination (aOR = 0.60; 95% CI 0.44-0.83). CONCLUSIONS: The survey indicated that testing, contact tracing, and vaccination were seriously influenced by socioeconomic position; less so by chronic disease prevalence and very minimally by lifestyle. The etiological role of socioeconomic inequalities in epidemic measure implementation likely generated socioeconomic inequality in COVID-19-related complication and death rates.