GAJRC | Global Academic Journal of Medical Sciences

Journal Name:	Global Academic Journal of Medical Sciences
Abbr. Title:	Glob Acad J Med Sci
ISSN(Print):	2706-9036
ISSN(Online):	2707-2533
Frequency:	Bi-Monthly
Language:	English
Chief Editor:	Mohammed Ahamed Ahamed Abuelnour
Publisher:	Scholars Middle East Publishers
Country of Origin:	United Arab Emirates

Journal Name:

Global Academic Journal of Medical Sciences

Abbr. Title:

Glob Acad J Med Sci

ISSN(Print):

2706-9036

ISSN(Online):

2707-2533

Frequency:

Bi-Monthly

Language:

English

Chief Editor:

Mohammed Ahamed Ahamed Abuelnour

Publisher:

Scholars Middle East Publishers

Country of Origin:

United Arab Emirates

March 14, 2026

Reproductive Health Service Preparedness in Primary Health Care Facilities across Edo State, Nigeria: A Cross-Sectional Survey with Regression Analysis of Determinants

Victor Ohenhen, Patrick O. Okundia, Osamwonyi Abiodun William Irowa, Akpojaro Ejovi, Odiko Osikemekhai David
Glob Acad J Med Sci, 2026; 8(1): 15-23
DOI : https://doi.org/10.36348/gajms.2026.v08i01.002

This study presents a robust machine learning framework to enhance stroke risk prediction and support global health objectives to reduce stroke-related morbidity and mortality. Using the Kaggle Stroke Prediction Dataset, the research integrates advanced data preprocessing, exploratory data analysis, and five machine learning algorithms: Logistic Regression, Random Forest, Gradient Boosting, XGBoost, and LightGBM. A stacked ensemble model serves as the core methodology, achieving superior predictive performance (accuracy 97%, F1-score 0.97, AUC-ROC 0.99) compared with individual models and prior works. Bayesian Optimization ensures optimal hyperparameter selection, while explainability methods such as SHAP and LIME bolster model interpretability to meet clinical transparency demands. The methodology aligns with the NZ Ngā Tikanga Paihere Framework, embedding principles of data privacy, cultural sensitivity, and fairness. Addressing challenges such as data imbalance and computational scalability via SMOTE and distributed computing, the model demonstrates robust performance, validated through bootstrapping and cross-validation. This research advances ethical, accurate, and actionable AI-driven stroke prediction for healthcare applications.

Dec. 22, 2025

Systematic Review on Predicting SVT Recurrence after Catheter Ablation Using Autonomic Markers

Dr. Tasnim Ferdous
Glob Acad J Med Sci, 2025; 7(6): 252-262
DOI : https://doi.org/10.36348/gajms.2025.v07i06.003

Purpose: This systematic review’s aim is to evaluate the role of autonomic markers in predicting supraventricular tachycardia (SVT) recurrence after catheter ablation. Understanding these markers can help to identify patients at higher risk of recurrence and improve post-procedural management. Methodology: A full literature review has been conducted using 12 electronic databases, such as PubMed, ScienceDirect, Springer, MDPI and Oxford Academic. It has covered studies in English from 1999 to 2025. The PRISMA 2020 guidelines for systematic reviews have been followed in the review. Studies have been chosen using the PICO framework: adult patients with SVT who undergo catheter ablation (Population), evaluation of autonomic markers like heart rate variability (HRV), baroreflex sensitivity (BRS), skin sympathetic nerve activity (SKNA), and P-wave alternans (Intervention), comparison with normal or baseline values (Comparator), and recurrence or non-recurrence of SVT as the outcomes (Outcome). Both qualitative and quantitative data were extracted, including statistical measures such as odds ratios, hazard ratios and predictive accuracy metrics. Findings: HRV is the most studied and widely applied autonomic marker. Early post-ablation HRV changes correlate with recurrence risk in AF studies, but evidence in SVT is limited and largely hypothetical. BRS, SKNA and PWA have showed potentiality but have been underexplored in SVT. Clinical and procedural factors, such as accessory pathway location and ablation strategy, is influencing the recurrence rates. In Bangladesh, HRV has been measured in tertiary centers, while other markers are not routinely applied due to resource constraints. Conclusion: Autonomic markers have promising potential to predict SVT recurrence, but no robust SVT-specific studies are there. Future research should focus on multicenter prospective studies with standardized measurement protocols and integration of clinical factors to develop reliable predictive models.

Men play a critical role in the transmission and control of sexually transmitted infections, yet they are often overlooked in public health discussions and interventions. Sexually transmitted infections (STI) is on the increase among male in rural communities. Possible contributing factors include multiple sexual partnerships, inconsistent condom use, alcohol and drug use, and delayed health-seeking behavior. Exploring these factors will provide valuable insight into designing more inclusive and effective STI prevention programs targeting men. This study is aim to evaluate the Rising trend of sexually transmitted infections among male in Urban areas of South-South Nigeria. This was a cross-sectional study involving 250 women. A well-structured questionnaire was administered to participants. The study lasted for a period of 3 months. Statistical analysis was done using SPSS version 25.0 and p < 0.05 was significant. The results revealed that most of the participants affected were between 23 to 37 years of age, 76% had secondary education, 68% were single, 72% farming, 72% are aware of STI, 72% have no knowledge about STI, 72% have multiple girl friends, 80% do not use condom, 80% has contacted STI, 80% treated STI with herbal, 76% do not treat their girl friend alongside, and 80% had complications from STI treatment.

Background: Dementia is a progressive neurodegenerative disorder that affects memory, cognition, and behavior, resulting in profound social and functional decline. Behavioral and Psychological Symptoms of Dementia (BPSD) are among the most distressing features, often influencing disease management and caregiver burden. The prevalence of dementia in India is estimated at 7.4% among individuals above 60 years of age. Aim: To explore the relationship between the severity of dementia and the presence of behavioral, emotional, psychotic, and biological symptoms among elderly patients. Methods: An observational study was conducted at Asha Hospital Memory Clinic over one year. Sixty patients above 60 years were screened according to inclusion criteria, and thirty completed the study. Dementia severity was assessed using Addenbrooke’s Cognitive Examination-III (ACE-III), Clinical Dementia Rating (CDR), and Neuropsychiatric Inventory (NPI). Data were categorized into behavioral, emotional, psychotic, and biological domains. Results: Among 30 participants (mean age 71 years), 16.7% had mild cognitive impairment, 26.7% mild dementia, 53.3% moderate dementia, and 3.3% severe dementia. Emotional symptoms (33.3%) were most frequent, followed by biological (24.7%), behavioral (22.2%), and psychotic (19.8%) features. Emotional and behavioral disturbances were most common in mild to moderate stages. Conclusion: BPSD were observed across all dementia stages, with emotional symptoms most prevalent. Early identification of BPSD is crucial for effective management and to minimize caregiver distress.