Cuneyt Ardic

Objective: Family planning is the prevention of unintended pregnancies and the avoidance of excessive fertility. Arranging the interval between pregnancies is one of the basic requirements for a healthy pregnancy and postpartum period. The family medicine practice, implemented in Türkiye since the early 2000s, addresses this fundamental need. Our study was conducted to determine the prevalence of family planning methods, sociodemographic characteristics, and the relationship between pregnancy history and family planning method use among women aged 18-49 living in the central district of Rize. Methods: Our descriptive cross-sectional study was conducted between 2022 and 2023 and included 413 women aged 18-49 who were registered at four Family Health Centers in the central district of Rize. Data were collected retrospectively from the Family Medicine Information System (FMIS) by the researchers involved in the study. In univariate analyses, Mann-Whitney U, Kruskal-Wallis, and Chi-square tests were used. To identify the primary factors associated with modern method use, age over 35, and the number of pregnancies were included in the analysis. Odds ratios (OR) with 95% confidence intervals (CI) were calculated. Results: In our study, 86.9% of individuals (n = 359) used family planning methods. Among those who used a method, 57.7% (n=207) used only modern methods, 25.9% (n=93) used only traditional methods, and 16.4% (n=59) used both modern and traditional methods. When assessing the relationships among educational status, employment status, smoking, and method use, only modern method use was significantly higher than the others (p=0.001). When evaluating the relationship between gravidity and the number of pregnancies by method-use status, the mean gravidity among users of modern methods or both modern and traditional methods was significantly higher than among those using only traditional methods (p=0.049). The primary variables associated with method use were identified as being a non-smoker, not having a child younger than two years of age, having no history of abortion, and the number of pregnancies. Conclusion: The study reveals a high rate of family planning method use in the central district of Rize province; however, adoption of modern methods remains an area requiring further development.

Background/Objectives: Metabolic syndrome (MetS) and dry eye disease (DED) share inflammatory mechanisms, yet few studies have examined objective tear function and serum inflammatory markers together in this population. The aim of this study was to compare tear function tests and a panel of systemic inflammatory indices between patients with MetS who did and did not have DED. Methods: This observational comparative study enrolled 104 adults with MetS (52 MetS-DED and 52 MetS-nonDED), with group-level comparability for age and sex. All participants underwent ophthalmologic evaluation, including the Ocular Surface Disease Index (OSDI), the Schirmer I test, and fluorescein tear break-up time (TBUT). DED was defined by a mean Schirmer I value of ≤5 mm/5 min. Routine blood tests were used to derive the neutrophil-, platelet-, monocyte-, and eosinophil-to-lymphocyte ratios (NLR, PLR, MLR, ELR), the neutrophil–lymphocyte–platelet ratio (NLPR), the C-reactive protein (CRP)-to-albumin ratio, and the monocyte-to-high density lipoprotein cholesterol (HDL) ratio. Between-group comparisons, receiver operating characteristic (ROC) analysis with Youden’s index, and age- and sex-adjusted binary logistic regression were performed. Results: TBUT and Schirmer I values were significantly lower in the MetS-DED group, whereas OSDI scores did not differ between the groups. NLR, MLR, NLPR, CRP, and the CRP-to-albumin ratio were significantly higher in MetS-DED patients (all p < 0.05), while classic metabolic parameters were comparable. ROC analysis revealed statistically significant but weak-to-modest discriminatory ability (areas under the curve (AUCs) 0.617–0.652). In age- and sex-adjusted models, MLR (odds ratio (OR) = 1.072 per 0.01 unit, p = 0.046), the CRP-to-albumin ratio (OR = 1.062 per 0.01 unit, p = 0.011), and NLPR (OR = 1.123 per 0.001 unit, p = 0.038) remained significantly associated with MetS-DED. Conclusions: Among individuals with MetS, the presence of DED was accompanied by impaired tear function and a more pronounced systemic inflammatory profile despite similar metabolic parameters. However, the modest discriminatory performance and borderline adjusted associations indicate that these findings should be regarded as preliminary signals rather than evidence supporting the clinical use of these markers for screening or risk identification.

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Background: This study aimed to evaluate office blood pressure control, antihypertensive treatment patterns, and factors associated with uncontrolled office blood pressure among adults attending family health centers across Türkiye. Methods: This multicenter cross-sectional study was conducted across the 7 geographical regions of Türkiye from February to December 2025. Adults aged ≥ 18 years with previous hypertension, antihypertensive treatment, and/or elevated office blood pressure at the study visit were included. Controlled office blood pressure was defined as

Objective: Chronic kidney disease (CKD) is a well-established risk factor for cardiovascular disease (CVD). This study aimed to examine the relationship between estimated glomerular filtration rate (eGFR) and the Systematic Coronary Risk Estimation (SCORE) algorithm, which predicts the risk of fatal cardiovascular events. Material and Methods: In this descriptive cross-sectional study, 262 individuals aged 40–70 years were included. The association between various laboratory parameters—including eGFR—and SCORE risk categories was assessed. Results: Based on SCORE values, 94 participants were classified as low risk, 70 as moderate, 20 as high, and 78 as very high risk. A moderate negative correlation was observed between SCORE and eGFR (r = -0.580, p < 0.001). Linear regression analysis showed that urea, creatinine, and eGFR significantly predicted SCORE values (p < 0.05). ROC analysis identified an eGFR cut-off of 94.5 to detect very high CVD risk, with 68.5% specificity and 69.2% sensitivity. Conclusion: These findings demonstrate that a reduced eGFR—even prior to meeting diagnostic criteria for CKD—is associated with increased cardiovascular risk. Incorporating kidney function assessment into routine cardiovascular risk evaluation may improve early identification of high-risk individuals. Timely intervention could help prevent or delay the progression of both CKD and CVD.

Objective: This study aimed to evaluate the role and importance of adult vaccination clinics in immunizing individuals with diabetes with the pneumococcal conjugate vaccine (PCV13), influenza vaccine, hepatitis B vaccine, tetanus-diphtheria (Td) vaccine, and herpes zoster vaccine. Methods: This descriptive study was conducted in 14 tertiary healthcare institutions with Family Medicine Clinics. The vaccination histories of individuals diagnosed with diabetes were reviewed, and information on PCV13, influenza, hepatitis B, Td, and herpes zoster vaccines was provided. Participants were informed about the adult vaccination clinic, if available at the institution, and followed up for one month to assess whether they received the recommended vaccines. Results: A total of 388 participants were included, with a median age of 60 years; 55.4% of the participants were female. Only 27.8% were aware of the existence of an adult vaccination clinic in their institution. Prior to the study, 43.3% had received Td, 42.3% had received influenza vaccine, 21.4% had received PCV13, and 13.1% had received hepatitis B vaccine; only one person had received the herpes zoster vaccine. Physician recommendation was the most influential factor for vaccination (88.9%), while the most common reason for vaccine refusal was distrust in vaccines (57.9%). At the end of the one-month follow-up, 20.6% of participants had received at least one of the recommended vaccines; PCV13 was the most commonly administered vaccine among those who received any. Among them, 93.8% had applied to institutions with an adult vaccination clinic (p=0.011). A statistically significant association was found between receiving the PCV13 vaccine and the presence of an adult vaccination clinic (p=0.002). In contrast, no such association was observed for Td, influenza, or hepatitis B vaccines (p>0.05). Conclusion: Vaccination rates among individuals with diabetes remain low. However, the presence of adult vaccination clinics and providing structured information significantly increase vaccine uptake. Strengthening these services could improve immunization coverage in this high-risk group.

Heart failure (HF) is a complex clinical condition associated with significant morbidity and mortality. Early diagnosis and effective management at the primary care level are essential for improving patient outcomes and reducing the burden on the healthcare systems. The Eurasian Society of HF and the Turkish Association of Family Medicine developed a guideline that underscores the critical role of natriuretic peptides (NPs) in the early detection, diagnosis, and management of HF. NPs, particularly the N-terminal pro-B-type NP, are a reliable biomarker for identifying HF, guiding treatment decisions, and monitoring disease progression. This guideline emphasizes the importance of measuring the levels of these peptides in primary care so as to detect individuals at risk, confirm the diagnosis of HF in symptomatic patients, and evaluate the treatment response. The recommended thresholds for NP levels account for variations arising from factors such as age, gender, and the presence of other health conditions. B-type natriuretic peptides (BNP) levels ≥ 35 pg/ml or N-terminus-proBNP levels ≥ 125 pg/ml are used to confirm the likelihood of HF in symptomatic patients, enabling timely diagnosis and appropriate intervention. Incorporating NP testing into routine clinical practice enables timely referrals and ensures appropriate management at all stages of HF. Beyond diagnosis, the measurement of NPs provides valuable information about treatment effectiveness and prognosis, allowing clinicians to individualize the treatment. By integrating NP testing into primary care, healthcare providers can facilitate early detection, optimize treatment strategies, and improve the quality of life for patients with or at risk of HF. Thus, this guideline highlights the essential role of primary care physicians in addressing the growing challenges of HF through the effective and evidence-based use of NPs.

SUMMARY INTRODUCTION: Advanced maternal age is defined as the mother being ≥35 years of age at the time of birth. Gestational weight gain is the difference between the weight measurements of the pregnant woman at prenatal follow-up just before birth and at pre-conception or at the beginning of the first trimester. In our study, we examined the effects of maternal age and gestational weight gain on neonatal outcomes. METHODS: This study was conducted, in the Rize province between April 2022 and January 2023, on pregnant women registered in seven Family Health Centers in the last 5 years and their resulting newborns. In total, this study analyzed the data of 642 pregnant women and their 642 newborns. Data records in the study are pregnant-puerperal follow-up form, newborn-child follow-up form, and family medicine information system. RESULTS: The probability of newborns of mothers with excessive gestational weight gain being large-for-gestational-age was found to be 1.81 times higher in univariate analysis and 1.72 times higher in multivariate analysis. While the effect of gestational weight gain status on birth weight Z-score was significant, gestational age had no significant effect (p=0.001 and p=0.136, respectively). CONCLUSION: In this period, when obesity, which is a disease of our age, is widespread and the gestational age has moved to older ages, there is a need for more extensive research on this subject in future studies.

Background and Objective: Diabetes Mellitus is a long-term, multifaceted metabolic condition that necessitates ongoing medical management. Hypogonadism is a syndrome that is a clinical and/or biochemical indicator of testosterone deficiency. Cross-sectional studies have reported that 20–80.4% of all men with Type 2 diabetes have hypogonadism, and Type 2 diabetes is related to low testosterone. This study presents an analysis of the use of ML and EL classifiers in predicting testosterone deficiency. In our study, we compared optimized traditional ML classifiers and three EL classifiers using grid search and stratified k-fold cross-validation. We used the SMOTE method for the class imbalance problem. Methods: This database contains 3397 patients for the assessment of testosterone deficiency. Among these patients, 1886 patients with Type 2 diabetes were included in the study. In the data preprocessing stage, firstly, outlier/excessive observation analyses were performed with LOF and missing value analyses were performed with random forest. The SMOTE is a method for generating synthetic samples of the minority class. Four basic classifiers, namely MLP, RF, ELM and LR, were used as first-level classifiers. Tree ensemble classifiers, namely ADA, XGBoost and SGB, were used as second-level classifiers. Results: After the SMOTE, while the diagnostic accuracy decreased in all base classifiers except ELM, sensitivity values increased in all classifiers. Similarly, while the specificity values decreased in all classifiers, F1 score increased. The RF classifier gave more successful results on the base-training dataset. The most successful ensemble classifier in the training dataset was the ADA classifier in the original data and in the SMOTE data. In terms of the testing data, XGBoost is the most suitable model for your intended use in evaluating model performance. XGBoost, which exhibits a balanced performance especially when the SMOTE is used, can be preferred to correct class imbalance. Conclusions: The SMOTE is used to correct the class imbalance in the original data. However, as seen in this study, when the SMOTE was applied, the diagnostic accuracy decreased in some models but the sensitivity increased significantly. This shows the positive effects of the SMOTE in terms of better predicting the minority class.

Background and Objective: Diabetes Mellitus is a long-term, multifaceted metabolic condition that necessitates ongoing medical management. Hypogonadism is a syndrome that is a clinical and/or biochemical indicator of testosterone deficiency. Cross-sectional studies have reported that 20-80.4 % of all men with Type 2 diabetes have hypogonadism, and Type 2 diabetes is related with low testosterone. This study presents an analysis of the use of ML and EL classifiers in predicting testosterone deficiency. In our study, we compared optimized traditional ML classifiers and three EL classifiers using grid search and stratified k-fold cross-validation. We used the SMOTE method for the class imbalance problem. Methods: This database contains 3397 patients for the assessment of testosterone deficiency. Among these patients, 1886 patients with type 2 diabetes were included in the study. In the data pre-processing stage, firstly outlier/excessive observation analyses were performed LOF and missing value analyses were performed with random forest. The SMOTE is a method for generating synthetic samples of the minority class. Four basic classifiers, namely MLP, RF, ELM and LR, were used as first level classifiers. Tree ensemble classifiers, namely ADA, AGBoost, and SGB, were used as second level classifiers. Results: After SMOTE, while the diagnostic accuracy decreased in all base classifiers except ELM, sensitivity values increased in all classifiers. Similarly, while the specificity values decreased in all classifiers, F1 score increased. The RF classifier gave more successful results on the base-training dataset. The most successful ensemble classifier in the training dataset was the ADA classifier in the original data and in the after SMOTE data. The testing data, XGBoost is the most suitable model for your intended use in evaluating model performance. XGBoost, which exhibits a balanced performance especially when SMOTE is used, can be preferred to correct class imbalance. Conclusions: SMOTE is used to correct the class imbalance in the original data. However, as seen in this study, when SMOTE was applied, the diagnostic accuracy decreased in some models, but the sensitivity increased significantly. This shows the positive effects of SMOTE to better predict the minority class.