International Journal of Statistics in Medical Research

Multiple Mean Comparison for Clusters of Gene Expression Data through the t-SNE Plot and PCA Dimension Reduction

2025-01-22T12:31:07+00:00

This paper introduces a novel methodology for multiple mean comparison of clusters identified in gene expression data through the t-distributed Stochastic Neighbor Embedding (t-SNE) plot, which is a powerful dimensionality re- duction technique for visualizing high-dimensional gene expression data. Our approach integrates the t-SNE visualization with rigorous statistical testing to validate the differences between identified clusters, bridging the gap between exploratory and confirmatory data analysis. We applied our methodology to two real-world gene expression datasets for which the t-SNE plots provided clear separation of clusters corresponding to different expression levels. Our findings underscore the value of combining the t-SNE visualization with multiple mean comparison in gene expression analysis. This integrated approach enhances the interpretability of complex data and provides a robust statistical framework for validating observed patterns. While the classical MANOVA method can be applied to the same multiple mean comparison, it requires a larger total sample size than the data dimension and mostly relies on an asymptotic null distribution. The proposed approach in this paper has broad applicability in the case of high dimension with small sample sizes and an exact null distribution of the test statistic.

Objective: Propose a two-step approach to analysis of gene expression data.

Gene expression data usually possess a complicated nonlinear structure that cannot be visualized under simple linear dimension reduction like the principal component analysis (PCA) method. We propose to employ the existing t-SNE approach to dimension reduction first so that clusters among data can be clearly visualized and then multiple mean comparison methods can be further employed to carry out statistical inference. We propose the PCA-type projected exact F-test for multiple mean comparison among the clusters. It is superior to the classical MANOVA method in the case of high dimension and relatively large number of clusters.

Results: Based on a simple Monte Carlo study on a comparison between the projected F-test and the classical MANOVA Wilks’ Lambda-test and an illustration of two real datasets, we show that the projected F-test has better empirical power performance than the classical Wilks’ Lambda-test. After applying the t-SNE plot to real gene expression data, one can visualize the clear cluster structure. The projected F-test further enhances the interpretability of the t-SNE plot, validating the significant differences among the visualized clusters.

Conclusion: Our findings suggest that the combination of the t-SNE visualization and multiple mean comparison through the PCA-projected exact F-test is a valuable tool for gene expression analysis. It not only enhances the interpretability of high-dimensional data but also provides a rigorous statistical framework for validating the observed patterns.

The Effect of Interpersonal Communication on Prevention Behavior of Early Hypertension among Student at SMAN 6 and SMAN 19 Bone

2025-01-27T09:00:02+00:00

Background: Hypertension is a health issue that is not only experienced by adults but can also develop during adolescence. This condition often continues into adulthood, with essential hypertension in adults frequently stemming from habits and risk factors that emerge during adolescence. Centers for Disease Control and Prevention (CDC) 2023 revealed that one in every 25 adolescents aged between 12 to 19 years old is diagnosed with hypertension. Among adolescents diagnosed with hypertension, 10% were found to have a prior history of prehypertension.

Objective: This study aims to determine the effect of interpersonal communication on early hypertension prevention behavior among students of SMAN 6 and SMAN 19 Bone.

Materials and Methods: The research design used was Quasi Experiment with pretest-posttest control group design. 110 grade 11 students made up the study population. They were split into two groups: the experimental group, which got an interpersonal communication intervention (n=55), and the control group, which received counseling (n=55). This study was carried out at SMAN 6 and SMAN 19 Bone. Simple random sampling was the method of sampling employed in this study, and a questionnaire was utilized as the research tool to gauge students' knowledge, attitudes, and action both before and after they received the intervention, which had been validated and proven to be reliable. Wilcoxon and Mann-Whitney tests were used for both univariate and bivariate data analysis.

Results: This study showed significant differences in knowledge, attitudes, and actions in the experimental group regarding hypertension prevention behaviors, with p-values for knowledge (p=0.017), attitude (p=0.000), and action (p=0.002).

Conclusion: The interpersonal communication approach applied in the intervention proved to have an influence on hypertension prevention behavior, including knowledge, attitudes, and actions in students of SMAN 6 and SMAN 19 Bone.

Assessing the Impact of Human and Technological Factors on Hospital Management Information System Utilization: A Case Study at Hospital X In Padang City Indonesia

2025-02-05T08:57:59+00:00

This study examines the application of the HOT-Fit method, which evaluates the relationship between Human, Technology, and Net Benefit components within the Hospital Management Information System (HMIS) at Hospital X Padang. The Human component is assessed based on system usage and user satisfaction, while the Technology component is analyzed through information quality, service quality, and system quality. This study employs a quantitative crosssectional design, with the research population comprising all active users of the HMIS application at Hospital X Padang, including employees from various departments interacting with the system. The research aims to determine the extent to which the Human and Technology components influence the Net Benefit of the HMIS and to explore these relationships in greater depth. The findings reveal a significant relationship between the Human component and the Net Benefit, as well as between the Technology component and the Net Benefit of the HMIS. Among the factors examined, Technology emerges as the most dominant factor affecting the Net Benefit of the system. These results provide valuable insights for optimizing the implementation and impact of HMIS in healthcare settings.

Comparative Analysis of Kolmogorov-Inspired CNN and Traditional CNN Models for Pneumonia Detection: A Study on Chest CT Images

2025-02-05T11:24:17+00:00

Aim: In this study, our goal is to compare the effectiveness of Kolmogorov Inspired Convolutional Neural Networks (KAN) with traditional Convolutional Neural Networks (CNN) models in pneumonia detection and to contribute to the development of more efficient and accurate diagnostic tools in the field of medical imaging.

Methods: Both models are structured with the same layers and hyperparameters to ensure a fair comparison of their performance. For a robust evaluation, the relevant dataset was divided into 80% for training and 20% for testing.

Results and Conclusion: Performance metrics of KAN; 95.2% sensitivity, 97.6% specificity, 94.1% precision, 96.9% accuracy (Acc), 0.9466 F1 score (F1) and 0. 9251 Matthews Correlation Coefficient (MCC), while the CNN model was found 92.5%, 96.4%, 91.2%, 95.3%, 0.9188 and 0.8858 for the same criteria, indicating that KAN outperformed. This comparison emphasizes that KAN has the potential to be a more effective model for pneumonia detection in chest CT images.

Predictors of Type-2 Diabetes Self-Screening: The Impact of Health Beliefs Model, Knowledge, and Demographics

2025-02-13T08:58:46+00:00

Background: Diabetes mellitus (DM) is a global health concern, and the intention to undergo diabetes self-screening among patients varies based on demographics and the Health Belief Model (HBM).

Objective: This study aimed to identify the factors associated with the intention to engage in DM self-screening.

Methods: This study included 404 participants with a 99% response rate. Saudi Arabian residents from the Jazan region, all diagnosed with type 2 diabetes, were enrolled. A validated, Arabic-translated, and structured questionnaire was used to collect data on demographics, family history, chronic disease status, DM knowledge, HBM constructs, and DM screening behavior. The study methods adhered to the STROBE Checklist for clear and reliable reporting.

Results: The study found that 24.5% of the participants were in the 35-44 age group and 67.3% were male. Regarding education, 52.2% had university-level education and 79.7% had no family history of DM. Among the participants, 62.1% reported no chronic disease. The mean knowledge score was 6.44 (SD = 2.01). The study revealed that 56.9% of the respondents intended to engage in DM screening. Factors associated with intention included age (65 and over had lower odds), gender (females had slightly higher odds), and education (school qualification had higher odds). Family history and chronic disease status did not significantly affect intention. Among the HBM constructs, higher perceived susceptibility increased the odds, higher perceived severity decreased the odds, and perceived benefits and barriers had no significant associations with intention.

Conclusions: This study provides valuable insights into the factors influencing the intention to engage in DM self-screening among diabetic patients. This understanding can guide targeted interventions to promote DM self-screening and enhance diabetes care outcomes.

Prevalence of Depression among Women Using Hormonal Contraceptive Use: Insights from a Hospital-Based Cross-Sectional Study

2025-02-17T11:52:43+00:00

Background: Hormonal contraceptives (HC) serve as a key component in managing premenopausal symptoms and controlling birth rates. However, mood-related side effects, ranging from minor disturbances to severe clinical depression, are the primary reasons for discontinuation.

Objective: To assess the prevalence of depression among women who use hormonal contraceptive methods. Additionally, the study aims to explore the association between specific types of contraceptives—such as oral pills, implants, injectables—and the prevalence of depression.

Methods: From October 2023 to October 2024, a total of 1500 women between the ages of 21 and 45 who currently take hormonal contraception participated in this hospital-based cross-sectional study, which was carried out at the tertiary care hospital at King Fahd Central Hospital's outpatient gynecology clinic.

Results: The most frequent age categories were from 26 to 40 years (85.7%). The majority of the studied cases were non-lean (82.6%). Most of the cases had parity from 1 to 4 (97.1%). Women were mainly of a low social class (77.1%). Social problems were found in (21.8%). Hypertension and diabetes mellitus were in 4.9% and 3.2% respectively. The most frequent contraceptive method were OCPs (40.3%), followed by POPs (31.2%), then subdermal implants (16.3%), injectable (8.6%), hormonal IUD (2.2%) and patches (1.4%). Most of the studied women used such method from 3 to 6 years (88.2%). Prevalence of depression among the studied cases was (8.7%; CI: 7.3%–10.2%). Obese individuals demonstrated a significantly higher prevalence of depression (11.5%) compared to overweight (8.5%) and lean individuals (5.0%), with a statistically significant association (p=0.015). Additionally, obese participants were more likely to have diabetes mellitus (27.1%), face social issues (21.8%), and belong to a low socioeconomic class (77.1%). Regarding contraceptive types, depression was notably less common among women using combined oral contraceptives (COCs) and progesterone-only pills (POPs), with rates of 4.6% and 4.5%, respectively. In contrast, higher rates of depression were observed in users of subdermal implants (19.2%), injectables (18.6%), hormonal IUDs (18.2%), and hormonal patches (19.0%) (p<0.001). The duration of contraceptive use also played a significant role, with depression rates increasing progressively from 2.8% for women using contraceptives for 1–2 years to 3.7% for 3–4 years and 12.7% for 5–6 years. The highest rate of depression, 37.7%, was observed among women using hormonal contraceptives for seven or more years (p<0.001)

Conclusion: Given the observed associations between certain hormonal contraceptives, prolonged use, and elevated depression rates, clinicians should adopt a proactive approach in assessing patients’ mental well-being, especially for women with additional risk factors like high BMI, socioeconomic challenges, or chronic conditions such as diabetes. Screening tools like the PHQ-9 should be routinely used during consultations to monitor for early signs of depression, allowing for timely intervention if needed.

Understanding Thrombocytopenia in the Obstetric Population: A Study from a Tertiary Care Center

2025-02-18T09:22:31+00:00

Background: Thrombocytopenia in pregnancy is a common condition with diverse etiologies, ranging from benign causes such as gestational thrombocytopenia (GT) to more serious conditions like preeclampsia and immune thrombocytopenic purpura (ITP). The clinical implications of thrombocytopenia during pregnancy include potential maternal and fetal complications, highlighting the importance of early detection and appropriate management.

Objective: To evaluate the incidence, causes, clinical outcomes, and complications of thrombocytopenia in pregnancy at a tertiary care hospital.

Methods: This retrospective cohort study included 130 pregnant women who were diagnosed with thrombocytopenia during their antenatal care between 2020 and 2021. Data on demographics, etiology, severity of thrombocytopenia, and maternal and fetal outcomes were collected and analyzed.

Results: The incidence of thrombocytopenia in pregnancy was found to be 3.85%. The most common causes were gestational thrombocytopenia (48.48%), preeclampsia (18.18%), and anemia (27.27%). Mild thrombocytopenia (<100,000/µL) was the most frequent severity (68.18%), with severe thrombocytopenia (<50,000/µL) observed in 6.06% of cases. Maternal complications included postpartum hemorrhage (10.60%) and incision site oozing (7.57%). Fetal outcomes included intrauterine growth restriction (12.12%) and birth asphyxia (7.57%). Most cases were diagnosed in the second trimester, and a significant proportion (56.06%) were in primigravida women.

Conclusion: Thrombocytopenia in pregnancy is predominantly mild, with gestational thrombocytopenia being the most common cause. Although the condition generally carries a good prognosis, associated complications such as postpartum hemorrhage and adverse fetal outcomes underscore the need for careful monitoring. Early diagnosis and individualized management are essential to minimize risks for both mother and child.