EPH-International Journal of Medical and Health Science
type: channel
description: EPH - International Journal of Medical and Health Science (IJMHS) is an open access journal publishing high-quality medical research since 2015. The journal features original research, reviews, and clinical studies with strong scientific and practical relevance. All submissions undergo a double-blind peer review to ensure quality, accuracy, and global accessibility. Publication Standards Rigorous Peer Review All manuscripts undergo a strict double-blind peer review process conducted by qualified experts to ensure originality, scientific accuracy, and research integrity. Open Access Policy The journal provides immediate open access to all published content, supporting unrestricted dissemination of knowledge to researchers worldwide. Ethical Publishing The journal strictly follows international publication ethics, ensuring transparency, plagiarism screening, and adherence to global scholarly standards. Call for Manuscripts Submit your research to a double-blind, open access platform focused on quality and global reach. Submit Now
publisher: E-Publication
language: en
publication name: EPH-International Journal of Medical and Health Science
issn: 2456-6063
copyright: Copyright (c) 2026 Author <img src="[binary]" /> This work is licensed under a Creative Commons Attribution 4.0 International License.
items: CLINICORADIOLOGICAL, ETIOLOGICAL PROFILE AND OUTCOME IN MODERATE TO MASSIVE HEMOPTYSIS IN ADMITTED PATIENTS IN A TERTIARY CARE HOSPITAL
items: A COMPARATIVE STUDY ON PREDISPOSING FACTORS FOR THE DEVELOPMENT OF DRUG SUSCEPTIBLE AND DRUG RESISTANT CASES IN PULMONARY TB RETREATMENT CASES AT GOVERNMENT CHEST DISEASES AND TB HOSPITAL, HANUMAKONDA
items: ROLE OF PLEURAL FLUID ADENOSINE DEAMINASE AND LYMPHOCYTE NEUTROPHIL RATIO IN DIFFERENTIATING TUBERCULOUS PLEURAL EFFUSION FROM OTHER EXUDATIVE EFFUSIONS
items: TRANSNASAL HIGH-FLOW OXYGEN THERAPY VERSUS NON-INVASIVE POSITIVE PRESSURE VENTILATION IN ACUTE EXACERBATION OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE PATIENTS WITH TYPE II RESPIRATORY FAILURE
items: STUDY ON SERUM ELECTROLYTES AMONG PATIENTS WITH CHRONIC OBSTRUCTIVE PULMONARY DISEASE
items: ANTIBACTERIAL EFFECT OF PROPOLIS MODIFIED AND NON PROPOLIS MODIFIED COLLAGEN MEMBRANE AGAINST P.GINGIVALIS AND S. MUTANS – AN IN VITRO STUDY
items: ASSESSMENT OF BACTERIAL ADHERENCE AND BIOFILM FORMATION OF STREPTOCOCCUS MUTANS ANDPORPHYROMONAS GINGIVALIS ON XENOGRAFT AND PERIOGLAS BONE GRAFT MATERIALS – AN IN VITRO STUDY
items: A PROSPECTIVE OBSERVATIONAL STUDY IN PREDICTING DIABETIC FOOT ULCERS BY USING SINBAD SCORING SYSTEM
items: INTEGRATED SYSTEMS BIOLOGY AND MACHINE LEARNING FRAMEWORK FOR THE IDENTIFICATION OF MITOCHONDRIAL AND SIGNALING SIGNATURES IN ISCHEMIC AND DILATED CARDIOMYOPATHY
items: A DATA-DRIVEN PARADIGM FOR FORECASTING TYPE 2 DIABETES RISK THROUGH THE INTEGRATION OF MACHINE LEARNING TECHNIQUES AND CLINICAL DATA WITHIN A UNIFIED WEB-BASED PLATFORM
items: URINARY TRACT INFECTIONS IN TYPE 2 DIABETES: AN ANALYSIS OF PREVALENCE AND CONTRIBUTING FACTORS
items: RECURRENT MIDFACIAL PLEXIFORM NEUROFIBROMA ASSOCIATED WITH NEUROFIBROMATOSIS TYPE 1: A CASE REPORT
items: STUDY OF EFFICACY OF ADDITION OF KINESIOLOGICAL TAPING WITH CONVENTIONAL PHYSIOTHERAPY IN CASE OF TRAUMATIC BRACHIAL PLEXUS INJURY A CASE REPORT
items: IMPACT OF LIFESTYLE AND TREATMENT INTERVENTIONS ON MENTAL HEALTH OUTCOMES: A CROSS-SECTIONAL STUDY
items: CLINICAL AND EPIDEMIOLOGICAL DETERMINANTS OF STROKE IN ADULTS
items: ASSESSING THE IMPACT OF SOCIO-DEMOGRAPHIC AND LIFESTYLE FACTORS ON COMMUNITY HEALTH OUTCOMES: AN EVIDENCE-BASED ANALYSIS FOR PUBLIC HEALTH AND SOCIAL CARE INTERVENTIONS
items: ASSESSMENT OF CLINICAL DETERMINANTS ASSOCIATED WITH MATERNAL HEALTH RISK
items: GLOBAL DETERMINANTS OF HEALTH OUTCOMES: AN ANALYSIS OF RISK FACTORS, HEALTH SYSTEMS, AND DISEASE BURDEN
items: ANTIMICROBIAL RESISTANCE PATTERNS AND INFECTION CONTROL PRACTICES IN HOSPITAL-BASED CLINICAL SETTINGS
items: ANALYSIS OF HOSPITAL READMISSION RATES USING PREDICTIVE ANALYTICS FOR IMPROVED HEALTHCARE DELIVERY
items: CLINICAL AND HEALTHCARE UTILIZATION FACTORS ASSOCIATED WITH HOSPITAL READMISSION AMONG DIABETIC PATIENTS
items: HEALTHCARE POLICY REFORMS AND THEIR INFLUENCE ON ACCESS TO AFFORDABLE MEDICAL SERVICES IN LOW- AND MIDDLE-INCOME COUNTRIES
items: CLINICAL EVALUATION OF BIOCHEMICAL MARKERS IN HEPATITIS C AND ASSOCIATED LIVER DISEASES
items: PREDICTIVE MODELING OF DIABETES RISK USING CLINICAL AND LIFESTYLE INDICATORS: A POPULATION-BASED DATA ANALYSIS
items: RETROSPECTIVE ANALYSIS OF ANTIMICROBIAL RESISTANCE PATTERNS AMONG BACTERIAL ISOLATES
items: MACHINE LEARNING–BASED PRIORITIZATION OF CARDIOVASCULAR DISEASE–ASSOCIATED GENES USING WHOLE GENOME SEQUENCING DATA
items: INTEGRATIVE TRANSCRIPTOMIC, PROTEOMIC, AND MACHINE LEARNING ANALYSIS OF COVID-19 SEVERITY AND ITS IMPLICATIONS FOR POST-VIRAL OUTCOMESFor Post-Viral Outcomes
items: PHYSIOLOGY OF SLEEP DEPRIVATION AND ITS IMPACT ON BRAIN FUNCTION

CLINICORADIOLOGICAL, ETIOLOGICAL PROFILE AND OUTCOME IN MODERATE TO MASSIVE HEMOPTYSIS IN ADMITTED PATIENTS IN A TERTIARY CARE HOSPITAL
type: item
description: Hemoptysis is the expectoration of blood from the respiratory tract and ranges from mild blood-streaked sputum to massive life-threatening bleeding. Moderate to massive hemoptysis is associated with significant morbidity and mortality, requiring prompt evaluation and management. In developing countries like India, pulmonary tuberculosis remains one of the most common causes, while bronchiectasis, bronchitis, and lung malignancy are also important etiologies. This prospective observational study aims to determine the clinicoradiological profile, etiology, and outcome of moderate to massive hemoptysis in patients admitted to a tertiary care hospital in Telangana. The study will include 100 patients presenting with true active hemoptysis who meet the inclusion criteria and are willing to participate. Patients with hematemesis, oral bleed, epistaxis, and upper respiratory tract infections will be excluded. Data collection will include detailed clinical history, physical examination, chest X-ray, computed tomography, sputum examination including CBNAAT and culture studies, and fibre optic bronchoscopy. The study will be conducted over a period of 18 months at Government General and Chest Hospital, Erragadda. The study is expected to provide valuable insights into the clinical presentation, radiological findings, underlying etiologies, and outcomes of moderate to massive hemoptysis, thereby contributing to improved diagnosis and management strategies.
subject: Articles
  topic: section
subject: Hemoptysis
  topic: keywords
subject: Massive Hemoptysis
  topic: keywords
subject: Moderate Hemoptysis
  topic: keywords
subject: Pulmonary Tuberculosis
  topic: keywords
subject: Bronchiectasis
  topic: keywords
creator: Dr. Sheelam snehalatha
creator: Dr. M. Sravan Kumar
creator: Dr. Sandiri Durga Keerthi
creator: Dr. Thaisam Srinivas
creator: Surya Teja Meka
creator: Dr Thilak Rachamalla
creator: Dr. Jaswanthkumar
rights: Copyright (c) 2026 EPH-International Journal of Medical and Health Science https://creativecommons.org/licenses/by-nc/4.0
date: 2026-04-08
publication date: 2026-04-08
starting page: 90
ending page: 106
doi: 10.69980/ty0yx606

A COMPARATIVE STUDY ON PREDISPOSING FACTORS FOR THE DEVELOPMENT OF DRUG SUSCEPTIBLE AND DRUG RESISTANT CASES IN PULMONARY TB RETREATMENT CASES AT GOVERNMENT CHEST DISEASES AND TB HOSPITAL, HANUMAKONDA
type: item
description: Background: Drug-resistant tuberculosis (DR-TB) remains a major challenge to tuberculosis control programmes, particularly among retreatment pulmonary TB cases. Identifying factors associated with the development of drug resistance is essential for improving treatment outcomes and preventing transmission. Materials and Methods: This analytical observational cross-sectional study was conducted over 24 months (May 2023–April 2025) at Government Chest Diseases and Tuberculosis Hospital, Hanumakonda. A total of 100 pulmonary TB retreatment cases aged ≥18 years were included, comprising 50 drug-resistant (DR-TB) and 50 drug-sensitive (DS-TB) cases. Demographic, clinical, microbiological, radiological, and treatment-related factors were assessed. Data were analyzed using SPSS software, and associations were evaluated using the Chi-square test, with p<0.05 considered statistically significant. Results: Significant factors associated with DR-TB included older age (p=0.037), male gender (88% vs. 68%, p=0.0158), illiteracy (26% vs. 10%, p=0.0373), alcohol consumption (84% vs. 62%, p=0.013), smoking (p=0.0001), multiple previous TB episodes (26% vs. 10%, p=0.037), longer interval between TB episodes (p=0.0004), previous loss to follow-up (64% vs. 42%, p=0.027), and default during the intensive phase of prior treatment (p=0.007). Undernutrition and anaemia were highly prevalent and significantly associated with disease status. HIV, diabetes mellitus, hypoproteinemia, sputum smear positivity, and radiological severity did not show significant association with drug resistance. Conclusion: Male gender, poor education, smoking, alcohol use, multiple TB episodes, and treatment default were important predictors of DR-TB. Strengthening counselling, adherence monitoring, nutritional rehabilitation, and tobacco/alcohol cessation interventions may help reduce the burden of drug-resistant tuberculosis.
subject: Articles
  topic: section
subject: Pulmonary Tuberculosis
  topic: keywords
subject: Retreatment Tuberculosis Cases
  topic: keywords
subject: Tuberculosis Risk Factors
  topic: keywords
subject: Treatment Default
  topic: keywords
subject: Smoking and Tuberculosis
  topic: keywords
subject: Tuberculosis Recurrence
  topic: keywords
creator: Dr M Sravan Kumar
creator: Dr Srutilaya R
creator: Dr Pantham Sunitha
creator: Dr Sandiri Durga Keerthi
creator: Dr Sowmya J
creator: Dr Thaisam Srinivas
creator: Dr Surya Teja Meka
rights: Copyright (c) 2026 EPH-International Journal of Medical and Health Science https://creativecommons.org/licenses/by-nc/4.0
date: 2026-04-08
publication date: 2026-04-08
starting page: 105
ending page: 117
doi: 10.69980/y5y6f269

ROLE OF PLEURAL FLUID ADENOSINE DEAMINASE AND LYMPHOCYTE NEUTROPHIL RATIO IN DIFFERENTIATING TUBERCULOUS PLEURAL EFFUSION FROM OTHER EXUDATIVE EFFUSIONS
type: item
description: Tubercular Pleural Effusion is the second most common extrapulmonary tuberculosis with incidence of 3-5% in low burden areas and upto 30% in high burden areas. In general, a cutoff level of between 40 and 45 U/L is used with levels above this being indicative of tuberculosis. An ADA level above 70 U/L in a patient who does not have an empyema or rheumatoid arthritis (RA) is essentially diagnostic of tuberculous pleuritis. (1,2,5,6) High pleural fluid ADA levels have also been reported with a very small percent of other neoplasms, with Q fever, with Brucellosis and with Legionnaire's disease Lymphocyte/Neutrophil (L/N) ratio >0.75 is seen to be more likely of TB pleural effusion. (1,2) Aim and Objectives: To evaluate the role of Adenosine deaminase (ADA) and Lymphocyte Neutrophil Ratio (L/N RATIO) in differentiating Tuberculous pleural effusion from other exudative pleural effusion. To study the demographical, clinical, radiological, and microbiological profile in various exudative pleural effusions. To assess Sensitivity, Specificity, PPV, NPV of pleural fluid ADA and L/N Ratio in tubercular and other exudative effusions. Patients and Methods: An Institutional based Prospective Observational study was conducted among the patients attended the tertiary care centre in Warangal from May 2023 to April 2025. In current study, ADA levels are seen to be elevated (> 40IUL) in all the patients with empyema (100%) followed by patients with tubercular pleural effusion (81.2%). This study demonstrates L/N ratio more than 0.75 in all patients with tubercular pleural effusion (100%) followed by patients with malignancy (95%) and parapneumonic effusion empyema (80%). Whereas, majority (71.4%) patients with empyema had L/N ratio less than 0.75.In present study a pleural fluid ADA has high sensitivity (93.1%), high Specificity (96%), high PPV (84%) and high NPV (66%). Pleural fluid L/N ratio also has high sensitivity (99%), high Specificity (100%), high PPV (89%) and high NPV (91%).…
subject: Articles
  topic: section
subject: Pleural Effusion
  topic: keywords
subject: Exudative Pleural Effusion
  topic: keywords
subject: Tuberculosis
  topic: keywords
subject: Pleural Tuberculosis
  topic: keywords
subject: Empyema
  topic: keywords
creator: Dr. Akhila Jose
creator: Dr. P Ravi
creator: Dr. T Srinivas
creator: Dr.M Sravan Kumar
creator: Dr Pantham Sunitha
creator: Dr Sowmya J
creator: Dr.Surya Teja Meka
rights: Copyright (c) 2026 EPH-International Journal of Medical and Health Science https://creativecommons.org/licenses/by-nc/4.0
date: 2026-04-08
publication date: 2026-04-08
starting page: 90
ending page: 104
doi: 10.69980/8yv9yg73

TRANSNASAL HIGH-FLOW OXYGEN THERAPY VERSUS NON-INVASIVE POSITIVE PRESSURE VENTILATION IN ACUTE EXACERBATION OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE PATIENTS WITH TYPE II RESPIRATORY FAILURE
type: item
description: Background: Non-invasive ventilation (NIV) is the standard of care for acute exacerbation of chronic obstructive pulmonary disease (AECOPD) with type II respiratory failure. However, patient discomfort and interface intolerance often limit its use. Transnasal high-flow oxygen therapy (TNHFOT) has emerged as a potential alternative that may improve tolerance while maintaining gas exchange. Aim & Objectives: This prospective comparative study aimed to compare the safety and efficacy of TNHFOT versus NIV in AECOPD patients with type II respiratory failure. Objectives included assessing effectiveness, clinical outcomes, and duration of ICU stay.Methods: 70 patients with AECOPD and type II respiratory failure (PaCO₂ >45 mmHg, RR >25) were enrolled at Osmania Medical College, Hyderabad, and divided equally into TNHFOT (n=35) and NIV (n=35) groups. TNHFOT was delivered at 30-60 L/min with FiO₂ 100%. NIV was delivered via BiPAP with IPAP 15 cm H₂O, EPAP 6 cm H₂O, and PEEP 6. Respiratory variables including ABG, SpO₂, and RR were measured 12th hourly.Results: Most patients were aged 65-70 years with male predominance. Treatment failure rates were 25.7% in the HFNC group vs 14.3% in the NIV group. Invasive ventilation was required in 14.3% of HFNC patients vs 5.7% of NIV patients (P = 0.026). Length of ICU stay was 7 days for HFNC vs 9 days for NIV (P = 0.059). 28-day mortality was 8.6% for HFNC vs 5.7% for NIV (P = 0.485).Conclusion: Both TNHFOT and NIV are viable options for managing AECOPD with type II respiratory failure. NIV showed lower treatment failure and invasive ventilation rates. However, TNHFOT was associated with better patient tolerance and a trend toward shorter ICU stay. TNHFOT may serve as a comfortable and effective alternative to NIV in select patients.
subject: Articles
  topic: section
subject: Mechanical Ventilation
  topic: keywords
subject: Oxygen Therapy
  topic: keywords
subject: Hypercapnia
  topic: keywords
subject: Hypoxemia
  topic: keywords
subject: Pulmonary Medicine
  topic: keywords
creator: Dr Syed Fayazuddin
creator: Dr M Sravan Kumar
creator: Dr. Thaisam Srinivas
creator: Dr. Sandiri Durga Keerthi
creator: Dr Thilak Rachamalla
creator: Dr Surya Teja Meka
creator: Dr Mohammad Asifuddin
rights: Copyright (c) 2026 EPH-International Journal of Medical and Health Science https://creativecommons.org/licenses/by-nc/4.0
date: 2026-04-08
publication date: 2026-04-08
starting page: 72
ending page: 89
doi: 10.69980/cc1tm957

STUDY ON SERUM ELECTROLYTES AMONG PATIENTS WITH CHRONIC OBSTRUCTIVE PULMONARY DISEASE
type: item
description: Introduction: Chronic obstructive pulmonary disease (COPD) is one of the most important diseases among adults which is associated with significant morbidity, mortality and quality of life. Presence of electrolyte imbalance affects the outcome of the patients with COPD particularly in those with acute exacerbation of COPD (AECOPD). Objectives: To find out the prevalence of electrolyte imbalance in patients with COPD To identify the relation between severity of COPD and electrolyte levels. Methodology: A cross sectional study was conducted for a period of 6 months from January to June 2025. Both male and female patients those who were aged more than 18 years admitted in the in-patient department of General Medical department were included in the study. Patients in all stages of COPD were recruited. All patients were interviewed using a structured proforma and the investigations such as complete blood count (CBC), liver function test (LFT), renal function test (RFT), serum sodium, potassium, calcium, phosphorus, chest X ray and spirometry were done. Appropriate statistical tests were performed. Results: A total of 100 patients with COPD were included in the study. Mean age of the study participants was 57.8 years. Majority of the participants (78%) were male. Complete blood count, liver function test and renal function test were normal in all the patients. All the patients had hyperinflation of lungs in the X ray. The mean FEV1 (predicted %) in the study group was 57.9% which was ranging from 36 to 75%. Among the total study participants, 74% had moderate COPD and 26% had severe COPD. The mean sodium and potassium level was significantly less among patients with severe COPD than patients with moderate COPD. Serum calcium and phosphorous levels were almost similar between patients with moderate and severe COPD. Among the total 100 patients, 27% had hyponatremia, 12% had hypokalemia, 1% had hypophosphatemia and all the patients had normal calcium levels. Conclusion: Hypo…
subject: Articles
  topic: section
subject: COPD
  topic: keywords
subject: sodium
  topic: keywords
subject: potassium
  topic: keywords
subject: calcium
  topic: keywords
subject: phosphorous
  topic: keywords
creator: Bingi Dharun Kumar
creator: Dr Raffat Rehmaan
creator: Dr K Sundaresan
creator: Dr C Senthil
rights: Copyright (c) 2026 EPH-International Journal of Medical and Health Science
date: 2026-04-30
publication date: 2026-04-30
starting page: 76
ending page: 83
doi: 10.69980/kjvn2468

ANTIBACTERIAL EFFECT OF PROPOLIS MODIFIED AND NON PROPOLIS MODIFIED COLLAGEN MEMBRANE AGAINST P.GINGIVALIS AND S. MUTANS – AN IN VITRO STUDY
type: item
description: Background: Collagen Membranes used in Guided tissue regeneration, are prone to microbial colonization, which can reduce their therapeutic efficiency. Propolis, a naturally occurring antibacterial agent, may be added to enhance the clinical results and strengthen antimicrobial qualities. Aim: To evaluate and compare the antibacterial efficacy of propolis modified and non propolis modified collagen membrane against Streptococcus mutans and Porphyromonas gingivalis Materials & Methods: An in vitro comparative study was conducted using sterile collagen membrane discs. An ethanolic extract of propolis (EEP) was added to test membranes. The agar diffusion assay (zone of inhibition) and colony forming unit (CFU) measurement were used to evaluate the antibacterial efficacy. Propolis extract alone serves as the reference control Results: Propolis extract alone demonstrated the highest antibacterial activity. Unmodified collagen membranes exhibited negligible inhibition. Propolis-modified membranes showed measurable antibacterial effects against both microorganisms. Zones of inhibition were more pronounced against P. gingivalis. CFU analysis revealed substantial bacterial reduction with propolis treatment, with the modified membranes demonstrating intermediate efficacy compared to propolis extract alone. These differences were statistically significant (P <0.05) Conclusion: propolis incorporation strengthen the antibacterial capability of collagen membranes, and may increase their performance during periodontal regeneration
subject: Articles
  topic: section
subject: Guided tissue regeneration
  topic: keywords
subject: Biomaterial modification
  topic: keywords
subject: Oral biofilm
  topic: keywords
creator: Dr Gopika s1
rights: Copyright (c) 2026 EPH-International Journal of Medical and Health Science https://creativecommons.org/licenses/by-nc/4.0
date: 2026-04-28
publication date: 2026-04-28
starting page: 65
ending page: 75
doi: 10.69980/rzye3n43

ASSESSMENT OF BACTERIAL ADHERENCE AND BIOFILM FORMATION OF STREPTOCOCCUS MUTANS ANDPORPHYROMONAS GINGIVALIS ON XENOGRAFT AND PERIOGLAS BONE GRAFT MATERIALS – AN IN VITRO STUDY
type: item
description: Background Bacterial colonization and biofilm formation on bone graft materials can compromise periodontal regenerative outcomes. Xenografts and bioactive glass (PerioGlas®) are widely used graft materials; however, limited data exist regarding their susceptibility to microbial adherence. Aim To evaluate and compare the bacterial adherence and biofilm formation of Streptococcus mutans and Porphyromonas gingivalis on xenograft and PerioGlas® bone graft materials under in vitro conditions. Materials And Methods An in vitro study was conducted using xenograft and PerioGlas® samples inoculated with S. mutans and P. gingivalis. After incubation, biofilm formation was assessed using crystal violet staining. The intensity of staining was evaluated to quantify bacterial adherence and biofilm formation. All experiments were performed in triplicate. Results PerioGlas® demonstrated significantly reduced biofilm formation compared to xenograft. The percentage of biofilm inhibition by PerioGlas® was 19.64% for S. mutans and 36.1% for P. gingivalis, indicating superior resistance to bacterial colonization. P-values <0.05 were considered statistically significant. Conclusion PerioGlas® exhibited significantly lower bacterial adherence and biofilm formation than xenograft. These findings suggest that PerioGlas® may offer improved resistance to microbial colonization, potentially enhancing the success and predictability of periodontal regenerative procedures.
subject: Articles
  topic: section
subject: PerioGlas
  topic: keywords
subject: Xenograft;
  topic: keywords
subject: Bacterial adherence
  topic: keywords
creator: Dr Sapna Mariyam Jaco
rights: Copyright (c) 2026 EPH-International Journal of Medical and Health Science https://creativecommons.org/licenses/by-nc/4.0
date: 2026-04-28
publication date: 2026-04-28
starting page: 54
ending page: 64
doi: 10.69980/randma50

A PROSPECTIVE OBSERVATIONAL STUDY IN PREDICTING DIABETIC FOOT ULCERS BY USING SINBAD SCORING SYSTEM
type: item
description: Background: Diabetic foot ulcers remain one of the most serious complications of diabetes mellitus and are a major contributor to lower-limb amputations globally. Reliable and easily applicable classification systems are essential for early risk stratification and outcome prediction. The SINBAD Classification System is a practical scoring tool that evaluates ulcer site, ischemia, neuropathy, bacterial infection, ulcer area, and ulcer depth to determine ulcer severity. Aim and Objectives: To analyze the clinical characteristics and outcomes of patients with diabetic foot ulcers and to determine the prognostic utility of the SINBAD Classification System in predicting ulcer healing and limb salvage. Methods: A prospective observational study was conducted involving 150 patients with diabetic foot ulcers presenting to a tertiary care center. Clinical data including demographic variables, duration of diabetes, comorbidities, ulcer characteristics, and microbiological findings were recorded. Ulcer severity was assessed using the SINBAD Classification System. Patients were followed until resolution of the ulcer or occurrence of adverse outcomes, including disarticulation, major amputation, or persistent non-healing. Statistical analyses were performed to evaluate associations between clinical variables, SINBAD scores, and treatment outcomes. Results: The majority of patients were aged 61–70 years (44.6%) with a predominance of males (70.0%). Forefoot ulcers were most common (71.3%). Neuropathy and ischemia were present in 41.3% and 61.3% of patients, respectively. Overall, complete ulcer healing was achieved in 52.7% of cases, while 19.3% required disarticulation and 17.3% underwent major amputation. Increasing SINBAD Classification System scores demonstrated a significant association with adverse outcomes (p=0.04). Advanced age, longer duration of diabetes, presence of neuropathy, and ulcer location were also significantly associated with poorer clinical outcomes. Conclus…
subject: Articles
  topic: section
subject: Diabetic foot ulcer
  topic: keywords
subject: SINBAD Classification System
  topic: keywords
subject: Diabetes mellitus
  topic: keywords
creator: Lakshmi Narasamma
rights: Copyright (c) 2026 EPH-International Journal of Medical and Health Science https://creativecommons.org/licenses/by-nc/4.0
date: 2026-04-27
publication date: 2026-04-27
starting page: 47
ending page: 53
doi: 10.69980/mhgv6579

INTEGRATED SYSTEMS BIOLOGY AND MACHINE LEARNING FRAMEWORK FOR THE IDENTIFICATION OF MITOCHONDRIAL AND SIGNALING SIGNATURES IN ISCHEMIC AND DILATED CARDIOMYOPATHY
type: item
description: Cardiovascular diseases (CVDs), predominantly manifested as ischemic cardiomyopathy (ICM) and dilated cardiomyopathy (DCM), constitute the leading cause of morbidity and mortality worldwide, driven by a complex architecture of genetic, metabolic, and environmental alterations. Traditional clinical diagnostic modalities, while effective for hemodynamic assessment, often fail to capture the granular molecular heterogeneity required for early intervention and personalized therapeutic strategies. The advent of high- throughput transcriptomics has provided a systems-level view of these pathologies, yet the translation of high- dimensional genomic data into robust clinical biomarkers remains hindered by the "curse of dimensionality" and the noise inherent in biological datasets. This study presents a comprehensive, integrated bioinformatics and machine learning pipeline to identify a compact, biologically potent gene signature for CVD classification. Drawing conceptual inspiration from the "Moana" classification framework—which prioritizes biological structure over raw feature variance—we employed a pathway-guided feature selection strategy on RNA- sequencing data (GSE55296) and microarray validation datasets (GSE57338). Functional enrichment analysis using KEGG and Reactome databases revealed a profound dysregulation of mitochondrial metabolism, oxidative phosphorylation, and cardiomyopathy-related pathways. Subsequent protein–protein interaction (PPI) network analysis, refined through the intersection of multiple topological centrality algorithms (Degree, Maximal Clique Centrality, and Betweenness), distilled the transcriptome into a core signature of six genes: COX4I1, NDUFA5, NDUFV2, NDUFS3, NDUFS4, and AKT1. These features were utilized to train and evaluate supervised machine learning models. The Random Forest classifier demonstrated superior stability and performance, achieving a mean cross-validation accuracy of approximately 69.5%, significantly outperforming a D…
subject: Articles
  topic: section
subject: Systems Biology,
  topic: keywords
subject: Machine Learning
  topic: keywords
subject: Cardiomyopathy
  topic: keywords
creator: Mahak
rights: Copyright (c) 2026 EPH-International Journal of Medical and Health Science https://creativecommons.org/licenses/by-nc/4.0
date: 2026-04-28
publication date: 2026-04-28
starting page: 30
ending page: 46
doi: 10.69980/p3yfya45

A DATA-DRIVEN PARADIGM FOR FORECASTING TYPE 2 DIABETES RISK THROUGH THE INTEGRATION OF MACHINE LEARNING TECHNIQUES AND CLINICAL DATA WITHIN A UNIFIED WEB-BASED PLATFORM
type: item
description: Type 2 diabetes mellitus (T2DM) has emerged as one of the most significant metabolic disorders affecting populations globally, necessitating the development of sophisticated early screening methodologies. The integration of artificial intelligence and data science in clinical applications has created unprecedented opportunities for improving disease prediction accuracy while advancing the United Nations Sustainable Development Goal 3 (Good Health and Well-Being). This research endeavors to establish a robust predictive framework by systematically evaluating multiple classification algorithms across four distinct diabetes- related datasets obtained from Kaggle and the UCI Machine Learning Repository. Our comprehensive analysis encompasses eight traditional machine learning classifiers alongside three deep neural network architectures, with model effectiveness measured using standard evaluation metrics including Accuracy, Precision, Recall, F1-Score, and Area Under the ROC Curve (AUC). We introduce a dimensionality reduction strategy based on Principal Component Analysis (PCA) to optimize feature representation, comparing i ts effectiveness against LASSO-based feature selection. Our experimental findings demonstrate that the XGBoost classifier combined with PCA-based feature engineering delivers exceptional predictive capability, achieving approximately 97% accuracy and F1 -score with a 96% AUC across the diabetes datasets. The optimized model has been deployed within an intuitive web-based application designed to facilitate accessible diabetes risk assessment. Additionally, we propose an integrated digital health framework incorporating Internet of Medical Things (IoMT), Robotic Process Automation (RPA), and AI technologies to enhance the reliability and scalability of personalized diabetes management solutions.
subject: Articles
  topic: section
subject: diabetes detection
  topic: keywords
subject: feature engineering
  topic: keywords
subject: deep learning.
  topic: keywords
creator: Janani Sp1
rights: Copyright (c) 2026 EPH-International Journal of Medical and Health Science https://creativecommons.org/licenses/by-nc/4.0
date: 2026-04-28
publication date: 2026-04-28
starting page: 8
ending page: 29
doi: 10.69980/h8nc7k69

URINARY TRACT INFECTIONS IN TYPE 2 DIABETES: AN ANALYSIS OF PREVALENCE AND CONTRIBUTING FACTORS
type: item
description: Background: Type 2 Diabetes Mellitus (T2DM) is a chronic metabolic disorder with rising global prevalence, frequently associated with complications such as urinary tract infections (UTIs). Diabetic patients are more susceptible to UTIs due to impaired immune responses, glycosuria, and bladder dysfunction, resulting in more frequent, severe, and recurrent infections. Objective: This study aimed to assess the prevalence, risk factors, and microbial etiology of UTIs among patients with T2DM presenting with clinical features suggestive of infection. Methods: A prospective observational study was conducted at the Teerthanker Mahaveer University College of Paramedical Sciences and the Department of Microbiology, Teerthanker Mahaveer Hospital & Research Centre, Moradabad. A total of 158 T2DM patients aged above 18 years with symptomatic features of UTI were enrolled. Midstream urine samples were collected aseptically and analyzed using standard microbiological techniques including culture on CLED agar, wet mount microscopy, and Gram staining. Significant bacteriuria was defined as colony growth ≥10⁵ CFU/ml based on Kass criteria. Results: Of the 158 urine samples, 40 (25.31%) showed significant bacteriuria. The prevalence was highest among patients aged >35 years. Gram-negative bacteria accounted for 65% of isolates, with Escherichia coli being the most common pathogen (52.5%), followed by Staphylococcus aureus (12.5%) and Pseudomonas aeruginosa (10%). Gram-positive organisms comprised 35% of isolates. Conclusion: The study reveals a notable prevalence of UTIs among T2DM patients, particularly in older adults. E. coli remains the predominant uropathogen. Early microbiological evaluation and culture-guided antimicrobial therapy are crucial for managing UTIs in diabetics. Routine screening and timely diagnosis can significantly reduce complications and improve clinical outcomes in this high-risk population.
subject: Articles
  topic: section
subject: Urinary Tract Infection
  topic: keywords
subject: Diabetes Mellitus
  topic: keywords
subject: Asymptomatic Bacteriuria
  topic: keywords
creator: Ruchi Kant
rights: Copyright (c) 2026 EPH-International Journal of Medical and Health Science
date: 2026-04-22
publication date: 2026-04-22
starting page: 1
ending page: 6
doi: 10.69980/0d8gqx65

RECURRENT MIDFACIAL PLEXIFORM NEUROFIBROMA ASSOCIATED WITH NEUROFIBROMATOSIS TYPE 1: A CASE REPORT
type: item
description: Plexiform neurofibroma (PNF) is a rare benign peripheral nerve sheath tumor and a pathognomonic manifestation of Neurofibromatosis Type 1 (NF1). These tumors are characterized by diffuse infiltrative growth involving multiple nerve fascicles and are associated with significant cosmetic deformity, functional impairment, recurrence, and risk of malignant transformation. Craniofacial involvement poses considerable diagnostic and surgical challenges because of extensive soft tissue infiltration and proximity to vital anatomical structures. A review of head and neck neurofibromas reported that approximately 25% of all neurofibromas are seen in the head and neck region and 6.5% occur in the oral cavity as solitary or multiple lesions associated with NF-1. 1 This report presents a 29-year-old male with a 17-year history of progressively enlarging recurrent midfacial swelling associated with NF1. The patient had previously undergone two surgical debulking procedures, both followed by rapid recurrence. Clinical examination revealed a large lobulated left midfacial mass with classical “bag of worms” consistency, axillary freckling and an intraoral palatal swelling. MRI and ultrasonography demonstrated diffuse infiltrative soft tissue involvement with associated vascular-lymphatic malformation. Histopathological examination showed thickened nerve bundles composed of Schwann cells with wavy hyperchromatic nuclei embedded within a myxoid stroma, confirming the diagnosis of plexiform neurofibroma. This case highlights the aggressive recurrent nature of craniofacial PNF and emphasizes the importance of clinicoradiological and histopathological correlation for accurate diagnosis and long-term management.
subject: Articles
  topic: section
subject: Plexiform neurofibroma
  topic: keywords
subject: Neurofibromatosis Type 1
  topic: keywords
subject: Crowe sign
  topic: keywords
subject: 3T MR
  topic: keywords
subject: Axillary freckling
  topic: keywords
creator: Dr. Sisodia Divya
creator: Dr. Sima Prajapati
creator: Dr. Chinar Suneja
creator: Dr. Nayka Priya
creator: Dr. Priyang Chauhan
creator: Dr. Niharika Sinha
rights: Copyright (c) 2026 EPH-International Journal of Medical and Health Science https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2026-04-30
publication date: 2026-04-30
starting page: 84
ending page: 89
doi: 10.69980/pe8x0174

STUDY OF EFFICACY OF ADDITION OF KINESIOLOGICAL TAPING WITH CONVENTIONAL PHYSIOTHERAPY IN CASE OF TRAUMATIC BRACHIAL PLEXUS INJURY A CASE REPORT
type: item
description: Rationable- Adult traumatic brachial plexus injury is a serious and difficult to treat peripheral nerve injuries, it leads to multiple physical disabilities ,sensory and motor deficit .It is devastating, and occurring with increasing frequency. Physical therapist does Patient evaluation concentrating over upper limb sensory and motor function with radiologic studies. This study discusses conservative management and addition of kinesiological taping to comprehensive Rehabilitation Protocol for Brachial Plexus Injury. Kinesiological taping helps in pain management, improved circulation selective immobilization of the soft tissues and at the same time correction of biomechanics of the joints and the muscles involved. It provide proprioceptive sensory stimulation through the soft tissue. To ensure the efficiency of the protocol, therapist documented progress using MMT modified oxford grading, and validated functional outcome scales (e.g., DASH score) with nerve conduction test pre and post rehabilitation. Patient concern- Intense neuropathic pain, especially of the neck and shoulder Sever Sensory and motor deficit. Tenderness over affected tissues. Weakness or heaviness in the extremity, loss of function ,psychological distress. Diminished pulses . Intervention- One adult patient with traumatic BPI underwent with kinesiotaping , with muscle stimulation and specialized exercise prescription .kinesiotaping once in a week and muscle stimulation alternate days. Record the patient’s MMT MRC grading with VAS and DASH score pre rehab and 2 weeks,1 month,2months,and 6,month after rehab. Diagnosis- Adult with traumatic brachial plexus injury preganglionic . Outcome-After kinesiotaping Marked improvement in VAS scale, MMT , and improved DASH score. However exercise protocol was being followed by the patient with taping. Abbreviation-MMT,NCV, BPI, DASH score.
subject: Articles
  topic: section
subject: BPI- brachial plexus injury
  topic: keywords
subject: MMT- Manual muscle testing
  topic: keywords
subject: MRC grading- medical research council
  topic: keywords
subject: VAS –visual analogue scale
  topic: keywords
subject: DASH-Disability of ARM
  topic: keywords
subject: Shoulder and hand
  topic: keywords
creator: Dr.Kumari Nilay
rights: Copyright (c) 2026 EPH-International Journal of Medical and Health Science
date: 2026-04-30
publication date: 2026-04-30
starting page: 01
ending page: 07
doi: 10.69980/7qwdyb02

IMPACT OF LIFESTYLE AND TREATMENT INTERVENTIONS ON MENTAL HEALTH OUTCOMES: A CROSS-SECTIONAL STUDY
type: item
description: This study aimed to examine the impact of lifestyle behaviours and treatment interventions on mental health outcomes using a cross-sectional design. A total of 2500 participants from diverse demographic and socioeconomic backgrounds were included in the analysis. Data were collected on mental health status, lifestyle factors such as physical activity and sleep, and treatment interventions including therapy and medication. Descriptive and inferential statistical analyses were performed to assess associations between variables. The findings revealed that 35.08% of participants reported good mental health outcomes, while 30.84% reported fair outcomes, indicating a moderate overall mental health status within the population. Participants engaging in moderate to high physical activity and maintaining adequate sleep duration demonstrated better mental health outcomes compared to those with low activity levels and poor lifestyle patterns. Additionally, individuals receiving combined treatment interventions, including both therapy and medication, showed more favourable outcomes than those receiving a single form of treatment. The results suggest a significant association between healthy lifestyle behaviours, treatment engagement, and improved mental health. The study highlights the importance of integrating lifestyle modifications with clinical interventions to achieve optimal mental health outcomes. Despite limitations related to the cross-sectional design and self-reported data, the findings provide valuable insights for developing holistic and evidence-based approaches to mental health care.
subject: Articles
  topic: section
subject: : Mental health outcomes;
  topic: keywords
subject: Lifestyle factors
  topic: keywords
subject: Physical activity;
  topic: keywords
creator: Dr. Rakesh Chatterjee
rights: Copyright (c) 2025 EPH-International Journal of Medical and Health Science
date: 2025-12-27
publication date: 2025-12-27
starting page: 74
ending page: 82
doi: 10.69980/kya2cb61

CLINICAL AND EPIDEMIOLOGICAL DETERMINANTS OF STROKE IN ADULTS
type: item
description: Stroke remains a major cause of mortality and long-term disability worldwide, posing a substantial burden on individuals, healthcare systems, and public health. This study aimed to examine the clinical and epidemiological determinants associated with stroke occurrence in adults. A quantitative cross-sectional analytical design was adopted using a structured secondary dataset comprising 5,110 adult records. The analysis included demographic, clinical, and lifestyle-related variables, namely age, gender, hypertension, heart disease, marital status, work type, residence type, average glucose level, body mass index, smoking status, and stroke status. Descriptive statistics were used to summarize the study variables, while inferential statistical techniques, including Chi-square tests and independent sample t-tests, were applied to assess the association between predictor variables and stroke occurrence. The findings revealed that age, hypertension, heart disease, average glucose level, body mass index, marital status, work type, and smoking status were significantly associated with stroke. Individuals with stroke had higher mean age, glucose level, and body mass index than those without stroke. Hypertension and heart disease emerged as the strongest clinical determinants, with substantially higher stroke prevalence among affected participants. In contrast, gender and residence type were not significantly associated with stroke occurrence. Overall, the findings indicate that stroke in adults is influenced by a combination of clinical, epidemiological, and lifestyle-related factors. These results highlight the need for integrated prevention strategies emphasizing cardiovascular risk screening, metabolic monitoring, and targeted public health interventions to reduce stroke burden and improve adult health outcomes.
subject: Articles
  topic: section
subject: Stroke;
  topic: keywords
subject: hypertension
  topic: keywords
subject: clinical risk factors
  topic: keywords
creator: Dr. Harpreet Singh
rights: Copyright (c) 2025 EPH-International Journal of Medical and Health Science
date: 2025-12-27
publication date: 2025-12-27
starting page: 67
ending page: 73
doi: 10.69980/kchgts19

ASSESSING THE IMPACT OF SOCIO-DEMOGRAPHIC AND LIFESTYLE FACTORS ON COMMUNITY HEALTH OUTCOMES: AN EVIDENCE-BASED ANALYSIS FOR PUBLIC HEALTH AND SOCIAL CARE INTERVENTIONS
type: item
description: Understanding the determinants of community health outcomes is essential in the context of rising chronic disease burden and increasing pressure on healthcare systems. While socio-demographic and lifestyle factors are widely recognized as key influences on health, their direct relationship with healthcare utilization remains insufficiently understood. This study addresses this gap by examining the impact of socio-demographic and lifestyle-related factors on healthcare visits using a structured community health dataset comprising 1,000 observations. The objective is to assess the relative contribution of age and body mass index (BMI) to variations in healthcare utilization. The analysis employs exploratory data analysis, correlation assessment, and multiple linear regression modeling to evaluate associations and predictive effects. The results indicate that age is a statistically significant and dominant predictor of healthcare utilization, demonstrating a strong positive relationship with the number of visits, whereas BMI does not exhibit a significant effect. These findings suggest a disconnect between lifestyle-related health risk and actual engagement with healthcare services. The study highlights the importance of distinguishing between determinants of health risk and healthcare demand, emphasizing the need for age-responsive healthcare planning and strengthened preventive strategies. The findings contribute to improving evidence-based public health interventions and resource allocation in community health systems.
subject: Articles
  topic: section
subject: Community Health
  topic: keywords
subject: Healthcare Utilization
  topic: keywords
subject: Lifestyle Factors
  topic: keywords
creator: Dr. Sunil Verma
rights: Copyright (c) 2025 EPH-International Journal of Medical and Health Science
date: 2026-05-09
publication date: 2026-05-09
starting page: 59
ending page: 66
doi: 10.69980/ysjzsd32

IMPACT OF LIFESTYLE AND TREATMENT INTERVENTIONS ON MENTAL HEALTH OUTCOMES: A CROSS-SECTIONAL STUDY
type: item
description: This study aimed to examine the impact of lifestyle behaviours and treatment interventions on mental health outcomes using a cross-sectional design. A total of 2500 participants from diverse demographic and socioeconomic backgrounds were included in the analysis. Data were collected on mental health status, lifestyle factors such as physical activity and sleep, and treatment interventions including therapy and medication. Descriptive and inferential statistical analyses were performed to assess associations between variables. The findings revealed that 35.08% of participants reported good mental health outcomes, while 30.84% reported fair outcomes, indicating a moderate overall mental health status within the population. Participants engaging in moderate to high physical activity and maintaining adequate sleep duration demonstrated better mental health outcomes compared to those with low activity levels and poor lifestyle patterns. Additionally, individuals receiving combined treatment interventions, including both therapy and medication, showed more favourable outcomes than those receiving a single form of treatment. The results suggest a significant association between healthy lifestyle behaviours, treatment engagement, and improved mental health. The study highlights the importance of integrating lifestyle modifications with clinical interventions to achieve optimal mental health outcomes. Despite limitations related to the cross-sectional design and self-reported data, the findings provide valuable insights for developing holistic and evidence-based approaches to mental health care
subject: Articles
  topic: section
subject: Mental health outcomes
  topic: keywords
subject: Lifestyle factors
  topic: keywords
subject: Physical activity;
  topic: keywords
creator: Dr. Rakesh Chatterjee
rights: Copyright (c) 2025 EPH-International Journal of Medical and Health Science
date: 2025-12-27
publication date: 2025-12-27
starting page: 50
ending page: 58
doi: 10.69980/08zg4592

ASSESSMENT OF CLINICAL DETERMINANTS ASSOCIATED WITH MATERNAL HEALTH RISK
type: item
description: Maternal health risk assessment is essential for early identification of women who may require closer monitoring and timely clinical intervention during pregnancy. This study assessed clinical determinants associated with maternal health risk using routinely measurable clinical and physiological indicators. An observational analytical design was adopted using a maternal health dataset containing age, systolic blood pressure, diastolic blood pressure, blood glucose, body temperature, heart rate, and maternal health risk level. Data were screened for completeness, duplicate observations, and clinically implausible values. After data preparation, the final analytical sample comprised 451 records. Descriptive statistics, risk-category distribution, correlation analysis, and one-way analysis of variance were used to examine differences across low, mid, and high-risk maternal health categories. The results showed that low-risk cases represented 51.66% of the sample, while mid-risk and high-risk cases represented 23.50% and 24.83%, respectively. High-risk cases had higher mean age, systolic blood pressure, diastolic blood pressure, blood glucose, body temperature, and heart rate compared with low-risk cases. Blood glucose showed the strongest difference across risk categories, followed by systolic and diastolic blood pressure. All selected indicators differed significantly across maternal health risk groups. The findings suggest that routinely available clinical indicators can support maternal risk assessment and may assist early identification of women requiring closer antenatal monitoring.
subject: Articles
  topic: section
subject: maternal health risk
  topic: keywords
subject: clinical determinants
  topic: keywords
subject: blood pressure
  topic: keywords
creator: Dr. Sunil Verma
rights: Copyright (c) 2025 EPH-International Journal of Medical and Health Science
date: 2025-09-27
publication date: 2025-09-27
starting page: 41
ending page: 49
doi: 10.69980/dpt85572

GLOBAL DETERMINANTS OF HEALTH OUTCOMES: AN ANALYSIS OF RISK FACTORS, HEALTH SYSTEMS, AND DISEASE BURDEN
type: item
description: Global health outcomes are shaped by a complex interaction of environmental, behavioural, and health system factors. This study aims to analyze the determinants of health outcomes by examining the combined influence of risk factors, health system performance, and disease burden across countries. A cross-sectional analytical approach was adopted using secondary data from internationally recognized health databases, covering indicators such as life expectancy, mortality rates, noncommunicable diseases (NCDs), and healthcare access. The findings indicate that global health indicators improved significantly between 2000 and 2019, particularly in life expectancy and reductions in communicable diseases. However, these gains were disrupted during the COVID-19 pandemic, which led to a decline in healthy life expectancy. Noncommunicable diseases emerged as the leading cause of premature mortality globally, while communicable diseases remained prevalent in low-income regions. Strong associations were observed between environmental and behavioural risk factors and increased disease burden, whereas robust health systems were linked to reduced mortality and improved health outcomes. The study highlights significant disparities across regions and income groups, emphasizing the need for integrated and targeted public health strategies. Strengthening health systems and addressing modifiable risk factors are essential for improving global health outcomes and reducing inequalities
subject: Articles
  topic: section
subject: Global Health Outcomes
  topic: keywords
subject: Health Systems
  topic: keywords
subject: Disease Burden
  topic: keywords
creator: Dr. Vivek Rajan
rights: Copyright (c) 2026 EPH-International Journal of Medical and Health Science
date: 2025-09-28
publication date: 2025-09-28
starting page: 75
ending page: 84
doi: 10.69980/v4ky7920

ANTIMICROBIAL RESISTANCE PATTERNS AND INFECTION CONTROL PRACTICES IN HOSPITAL-BASED CLINICAL SETTINGS
type: item
description: Antimicrobial resistance is a major threat to hospital-based healthcare because it increases treatment failure, prolongs hospitalization, and limits therapeutic options. Infection prevention and antimicrobial stewardship are essential for controlling the spread of multidrug-resistant organisms in clinical settings. This study aimed to assess antimicrobial resistance patterns and infection control practices in hospital-based clinical settings. A hospital-based cross-sectional descriptive study was conducted using two components: laboratory record review and healthcare worker assessment. Clinical specimens were reviewed to identify bacterial isolates and antimicrobial susceptibility patterns. Infection control practices were assessed among healthcare workers using a structured questionnaire and observation checklist. Data were analyzed using descriptive statistics, and resistance patterns were summarized by organism type, antibiotic class, and multidrug resistance status. A total of 420 clinical specimens were reviewed, of which 276 showed bacterial growth, giving a culture positivity rate of 65.7%. Gram-negative bacteria accounted for 71.7% of isolates. Escherichia coli was the most common pathogen, followed by Klebsiella pneumoniae, Staphylococcus aureus, Pseudomonas aeruginosa, and Acinetobacter baumannii. High resistance was observed against ampicillin, ceftriaxone, ciprofloxacin, and cotrimoxazole. Overall multidrug resistance prevalence was 50.0%, with the highest rate among A. baumannii. Infection control compliance was variable, with lower compliance for hand hygiene before patient contact and regular infection control training. The findings highlight a substantial burden of antimicrobial resistance and persistent infection control gaps. Continuous surveillance, hospital-specific antibiograms, improved hand hygiene, regular staff training, and integrated antimicrobial stewardship are recommended.
subject: Articles
  topic: section
subject: Antimicrobial resistance
  topic: keywords
subject: multidrug-resistant organisms
  topic: keywords
subject: ; infection control practices
  topic: keywords
creator: Dr. Pradeep Kumar Singh
rights: Copyright (c) 2026 EPH-International Journal of Medical and Health Science
date: 2025-09-30
publication date: 2025-09-30
starting page: 64
ending page: 74
doi: 10.69980/kvbr3r49

ANALYSIS OF HOSPITAL READMISSION RATES USING PREDICTIVE ANALYTICS FOR IMPROVED HEALTHCARE DELIVERY
type: item
description: Hospital readmission is a key measure of health care quality, safety and hospital performance. This study aimed to investigate hospital readmission rates using predictive analytics to determine which patients were at greater risk of readmission and help inform healthcare services. In this study used a structured hospital readmission dataset with 25,000 patients and 17 variables. Readmission was the dependent variable, with the independent variables being age, length of stay, number of laboratory tests, number of medications, number of outpatient visits, number of inpatient visits, number of emergency visits, medical speciality, diagnosis categories, glucose test, A1C test, medication change and diabetes medication status. There were no missing data or duplicate records in the dataset. Descriptive statistics revealed a readmission rate of 47.02% of patients, suggesting a high readmission rate. Machine learning models, such as Logistic Regression, Decision Tree and Random Forest were trained and tested based on accuracy, precision, recall, F1-score, and ROC-AUC. Random Forest emerged as the top model with the highest F1-score (0.5428) and Logistic Regression with the highest ROC-AUC (0.6434). Laboratory procedures, number of medications, time in hospital, age, diagnosis categories, medical speciality, and past inpatient visits were identified as important features in predicting readmission. The results indicate that predictive analytics can help hospitals identify patients at risk, plan discharge, organise follow-up care and allocate resources, which can lead to better patient-centred care.
subject: Articles
  topic: section
subject: Hospital Readmission
  topic: keywords
subject: Predictive Analytics
  topic: keywords
subject: Machine Learning,
  topic: keywords
creator: Dr. Sandeep Kulkarni
rights: Copyright (c) 2026 EPH-International Journal of Medical and Health Science
date: 2025-09-27
publication date: 2025-09-27
starting page: 54
ending page: 63
doi: 10.69980/g5f4jg42

CLINICAL AND HEALTHCARE UTILIZATION FACTORS ASSOCIATED WITH HOSPITAL READMISSION AMONG DIABETIC PATIENTS
type: item
description: Hospital readmission among diabetic patients remains a significant challenge for healthcare systems due to its association with increased clinical burden, healthcare costs, and reduced quality of care. This study aimed to examine the clinical and healthcare utilization factors associated with hospital readmission among diabetic patients. A quantitative analytical design was employed using a structured dataset comprising 25,000 patient records with variables related to demographic characteristics, clinical indicators, healthcare utilization, and readmission status. Descriptive and inferential statistical analyses were conducted to identify patterns and associations between study variables and hospital readmission. The results indicated that 47.02% of patients experienced readmission, highlighting a substantial readmission burden. Clinical factors such as age, primary diagnosis, medication use, and medication change were associated with variations in readmission rates. Patients with diabetes as the primary diagnosis and those undergoing medication adjustments showed relatively higher readmission levels. Healthcare utilization factors demonstrated the strongest association, with readmission rates increasing significantly among patients with higher numbers of prior inpatient, emergency, and outpatient visits. Additionally, longer hospital stays and higher healthcare utilization were observed among readmitted patients. The findings suggest that hospital readmission among diabetic patients is influenced by both clinical complexity and prior healthcare utilization. Identifying high-risk patients based on these factors can support targeted interventions, improve discharge planning, and enhance continuity of care. These insights contribute to evidence-based strategies aimed at reducing readmission rates and improving overall patient outcomes in diabetes management.
subject: Articles
  topic: section
subject: Hospital readmission
  topic: keywords
subject: , Clinical factors
  topic: keywords
subject: Healthcare utilization
  topic: keywords
creator: Dr. Rahul Sharma
rights: Copyright (c) 2026 EPH-International Journal of Medical and Health Science
date: 2025-09-28
publication date: 2025-09-28
starting page: 43
ending page: 53
doi: 10.69980/jz2gff44

HEALTHCARE POLICY REFORMS AND THEIR INFLUENCE ON ACCESS TO AFFORDABLE MEDICAL SERVICES IN LOW- AND MIDDLE-INCOME COUNTRIES
type: item
description: Access to affordable medical services remains a major challenge in low- and middle-income countries (LMICs), despite growing policy commitments to universal health coverage, primary healthcare strengthening, and financial protection. Many reforms have expanded formal coverage, yet households continue to face out-of-pocket payments, medicine costs, transport expenses, and unequal service availability. This article examines how healthcare policy reforms influence access to affordable medical services in LMICs, with particular attention to health financing, universal health coverage, primary healthcare, equity, and implementation barriers. The study adopted a qualitative documentary research design using thematic analysis. Six secondary data sources published or updated between 2020 and 2024 were used, including reports and databases from the World Health Organization, World Bank, UNICEF, and the DHS Program. Data were extracted using a structured matrix covering reform type, access outcomes, affordability, financial protection, equity dimensions, and implementation challenges. The analysis identified six major themes: health financing reform, universal health coverage expansion, primary healthcare strengthening, affordability and financial protection, equity in healthcare access, and implementation barriers. Reforms improved access when they reduced direct payments, expanded pooled financing, strengthened frontline services, and targeted vulnerable populations. However, weak governance, inadequate funding, workforce shortages, medicine stock-outs, and rural-urban disparities limited effectiveness. Healthcare policy reforms can improve affordable access in LMICs when they combine financing reform, primary healthcare investment, and equity-focused implementation. Formal coverage alone is insufficient without financial protection and reliable service availability.
subject: Articles
  topic: section
subject: Affordable healthcare
  topic: keywords
subject: Healthcare policy reform
  topic: keywords
subject: Universal health coverage
  topic: keywords
creator: Dr. Anjali Mukherjee
rights: Copyright (c) 2026 EPH-International Journal of Medical and Health Science
date: 2025-09-27
publication date: 2025-09-27
starting page: 32
ending page: 42
doi: 10.69980/bygpzm96

CLINICAL EVALUATION OF BIOCHEMICAL MARKERS IN HEPATITIS C AND ASSOCIATED LIVER DISEASES
type: item
description: Hepatitis C is a significant liver disease, which may progress from minimal hepatic inflammation to fibrosis and cirrhosis. Laboratory measures give valuable information about liver damage, dysfunction and disease progression. This research examined biochemical marker profiles in a Hepatitis C dataset of blood donors, hepatitis, fibrosis and cirrhosis cases. Biochemical markers, such as AST, BIL, GGT, ALB, CHE, CREA, ALT, ALP, CHOL and PROT were evaluated using descriptive statistics, group comparison, trend analysis, and cirrhosis deviation. Biochemical differences between groups were observed. The highest variation was observed in cirrhosis cases, with an increase in AST, BIL, GGT, and CREA and decrease in ALB and CHE compared to blood donor group. These suggest that severe liver damage is linked to multiple biochemical dysfunction related to liver cell damage, bile metabolism, decreased synthetic capacity, and potentially other systems. The research demonstrates the potential of biochemical profiling as a feasible and understandable means of evaluating the impact of Hepatitis C-associated liver disease. While conventional markers should not be used to diagnose liver disease, their integrated assessment may contribute to early identification, follow-up, and risk assessment of progressive liver disease.
subject: Articles
  topic: section
subject: hepatitis c
  topic: keywords
subject: liver disease
  topic: keywords
subject: liver function tests
  topic: keywords
creator: Dr. Kavya Srinivasan
rights: Copyright (c) 2025 EPH-International Journal of Medical and Health Science
date: 2025-06-29
publication date: 2025-06-29
starting page: 77
ending page: 85
doi: 10.69980/r7e52w77

ASSESSING THE IMPACT OF SOCIO-DEMOGRAPHIC AND LIFESTYLE FACTORS ON COMMUNITY HEALTH OUTCOMES: AN EVIDENCE-BASED ANALYSIS FOR PUBLIC HEALTH AND SOCIAL CARE INTERVENTIONS
type: item
description: Understanding the determinants of community health outcomes is essential in the context of rising chronic disease burden and increasing pressure on healthcare systems. While socio-demographic and lifestyle factors are widely recognized as key influences on health, their direct relationship with healthcare utilization remains insufficiently understood. This study addresses this gap by examining the impact of socio-demographic and lifestyle-related factors on healthcare visits using a structured community health dataset comprising 1,000 observations. The objective is to assess the relative contribution of age and body mass index (BMI) to variations in healthcare utilization. The analysis employs exploratory data analysis, correlation assessment, and multiple linear regression modeling to evaluate associations and predictive effects. The results indicate that age is a statistically significant and dominant predictor of healthcare utilization, demonstrating a strong positive relationship with the number of visits, whereas BMI does not exhibit a significant effect. These findings suggest a disconnect between lifestyle-related health risk and actual engagement with healthcare services. The study highlights the importance of distinguishing between determinants of health risk and healthcare demand, emphasizing the need for age-responsive healthcare planning and strengthened preventive strategies. The findings contribute to improving evidence-based public health interventions and resource allocation in community health systems.
subject: Articles
  topic: section
subject: community health
  topic: keywords
subject: socio economic factors
  topic: keywords
subject: public health
  topic: keywords
creator: Dr. Sunil Verma
rights: Copyright (c) 2025 EPH-International Journal of Medical and Health Science
date: 2025-06-30
publication date: 2025-06-30
starting page: 69
ending page: 76
doi: 10.69980/nmme4232

PREDICTIVE MODELING OF DIABETES RISK USING CLINICAL AND LIFESTYLE INDICATORS: A POPULATION-BASED DATA ANALYSIS
type: item
description: Diabetes mellitus is an increasing worldwide health issue that needs to be addressed with proper measures of early detection and prevention. The purpose of the study is to design and test predictive equations of diabetes risk with the help of both clinical and lifestyle predictors based on the large population-based dataset containing 100,000 records. Examples of variables present in the dataset are age, gender, body mass index (BMI), hypertension, heart disease, smoking history, HbA1c level, and blood glucose level, and diabetes status is the outcome variable. The analytical design used was a cross-sectional design, which included data preprocessing, feature selection, and supervised machine learning. Several models, such as logistic regression, decision tree, random forest, and gradient boosting, were created and tested on performance measures, including accuracy, precision, recall, F1-score, and ROC-AUC. The findings point to the conclusion that the most predictive variables of diabetes are the levels of HbA1c and blood glucose, then BMI, and age. Ensemble models, especially gradient boosting, showed better predictive accuracy than the traditional methods. The results indicate the usefulness of using a combination of clinical and lifestyle data in predictive modeling to determine the risk of diabetes early. This method has huge consequences on preventive healthcare, allowing the timely intervention and better clinical decision-making.
subject: Articles
  topic: section
subject: Diabetes prediction
  topic: keywords
subject: Machine Learning
  topic: keywords
subject: Risk Assesment
  topic: keywords
creator: Dr. Khalid Al-Rashid
rights: Copyright (c) 2025 EPH-International Journal of Medical and Health Science
date: 2025-12-29
publication date: 2025-12-29
starting page: 33
ending page: 40
doi: 10.69980/x9jzzh17

RETROSPECTIVE ANALYSIS OF ANTIMICROBIAL RESISTANCE PATTERNS AMONG BACTERIAL ISOLATES
type: item
description: Antimicrobial resistance has emerged as a critical global health challenge, significantly affecting the management of bacterial infections and limiting the effectiveness of commonly used antibiotics. This study aimed to analyze antimicrobial resistance patterns among bacterial isolates using a retrospective dataset-based approach. The study was conducted using secondary data comprising bacterial isolates and their corresponding antimicrobial susceptibility profiles. Data were cleaned, standardized, and analyzed using descriptive statistical methods, including frequency distribution and cross-tabulation, to evaluate resistance patterns across different bacterial species and antibiotics. The results revealed a predominance of gram-negative bacterial isolates, with organisms such as Escherichia coli, Proteus mirabilis, and Morganella morganii occurring more frequently. Considerable variability in antimicrobial resistance patterns was observed, with certain antibiotics demonstrating higher resistance rates, while others retained relatively lower resistance levels. Organism-specific analysis indicated distinct resistance profiles among different bacterial species, highlighting the importance of targeted evaluation. The findings also suggested that resistance patterns are not uniform and vary significantly depending on both the bacterial isolate and the antibiotic tested. The study underscores the importance of continuous monitoring and analysis of antimicrobial resistance patterns to support informed decision-making in clinical and microbiological practice. Despite limitations associated with the use of secondary data, the study provides valuable insights into resistance trends and contributes to the growing body of evidence addressing antimicrobial resistance. The results emphasize the need for rational antibiotic use and sustained efforts to monitor resistance patterns to improve the management of bacterial infections.
subject: Articles
  topic: section
subject: Antimicrobial resistence
  topic: keywords
subject: microbiology
  topic: keywords
subject: bacterial isolates
  topic: keywords
creator: Dr. Ahmed Al-Harthy
rights: Copyright (c) 2025 EPH-International Journal of Medical and Health Science
date: 2025-09-30
publication date: 2025-09-30
starting page: 24
ending page: 31
doi: 10.69980/snba5013

MACHINE LEARNING–BASED PRIORITIZATION OF CARDIOVASCULAR DISEASE–ASSOCIATED GENES USING WHOLE GENOME SEQUENCING DATA
type: item
description: Cardiovascular disease (CVD) remains the leading cause of global mortality, driven by complex interactions among genetic, environmental, and lifestyle factors. Although genome-wide studies have identified multiple risk loci, prioritizing disease-relevant genes from whole genome sequencing (WGS) data remains challenging due to data complexity. This study presents an integrative computational framework combining WGS, variant annotation, machine learning–based gene prioritization, and pathway enrichment analysis to identify candidate genes associated with CVD. High-throughput WGS data comprising over 510 million reads were processed through quality control, trimming, and alignment to the human reference genome (hg38), achieving a 99.94% mapping rate. Variant calling identified 9,622 genetic variants, with 70.62% being nonsynonymous. Functional impact analysis using SIFT classified 13.75% of these variants as potentially deleterious. Gene-level features based on variant burden and functional impact were used to train a Gradient Boosting model, optimized using Optuna and tracked via MLflow. The model achieved an ROC–AUC of 0.709 and generated a ranked list of candidate genes. Key prioritized genes included AHNAK2, MUC17, HRNR, FLNC, and MYH7, associated with cytoskeletal organization, vascular signaling, inflammation, and metabolism. Pathway analysis highlighted immune signaling, MAPK pathways, lipid metabolism, and cellular stress responses as critical mechanisms in CVD. Overall, this integrative approach demonstrates the effectiveness of combining genomics and machine learning for identifying disease-associated genes, offering valuable insights for precision medicine and therapeutic target discovery.
subject: Articles
  topic: section
subject: Machine Learning in Genomics
  topic: keywords
subject: Cardiovascular Disease Genetics
  topic: keywords
subject: Whole Genome Sequencing
  topic: keywords
subject: Gene Prioritization
  topic: keywords
subject: Bioinformatics Analysis
  topic: keywords
subject: Predictive Modeling
  topic: keywords
creator: Shaik Mubarak Basha
creator: Mahak
creator: Himanshu Shekhar Singh
creator: Janani Sp
creator: Dr.Chemmugil
rights: Copyright (c) 2026 EPH-International Journal of Medical and Health Science https://creativecommons.org/licenses/by-nc/4.0
date: 2026-04-22
publication date: 2026-04-22
starting page: 35
ending page: 51
doi: 10.69980/8j187w55

INTEGRATIVE TRANSCRIPTOMIC, PROTEOMIC, AND MACHINE LEARNING ANALYSIS OF COVID-19 SEVERITY AND ITS IMPLICATIONS FOR POST-VIRAL OUTCOMESFor Post-Viral Outcomes
type: item
description: COVID-19, caused by SARS-CoV-2, exhibits wide variability in clinical severity, ranging from asymptomatic infection to critical respiratory failure. Understanding the molecular determinants of this severity is essential for biomarker discovery, risk stratification, and improved clinical management. This study presents an integrative multi-omics framework combining transcriptomic analysis, proteomic enrichment profiling, and machine learning-based feature prioritization to identify molecular signatures associated with COVID-19 severity and their potential implications for post-viral outcomes. Transcriptomic analysis of the publicly available whole-blood dataset GSE213313 (Agilent microarray) identified 1,544 significantly differentially expressed genes (FDR < 0.05) in critical versus healthy samples, with enrichment of innate immune response, leukocyte activation, antigen processing, T-cell differentiation, and cytokine-mediated signalling pathways. Proteomic analysis using a published peer-reviewed dataset comparing mild (n = 3) and severe (n = 5) COVID-19 cases identified 91 severity-associated proteins, with significant enrichment of acute-phase response, complement cascade activation, platelet degranulation, and coagulation-related processes. Multi-omics integration identified 8 overlapping molecules between transcriptomic and proteomic datasets, with an inverse RNA–protein fold-change correlation (r = −0.58), indicative of post-transcriptional regulatory complexity. Machine learning analysis using a Random Forest classifier demonstrated perfect discrimination between mild and severe cases (AUC = 1.0; LOOCV accuracy = 100%), and prioritized proteins including LIPG, CLEC11A, KDR, FAIM3, and BST1 as key severity-associated features. Collectively, this study demonstrates that severe COVID-19 is characterized by coordinated dysregulation of immune activation, inflammatory signalling, complement amplification, and coagulation mechanisms across multiple molecular layer…
subject: Articles
  topic: section
subject: Transcriptomics
  topic: keywords
subject: Proteomics
  topic: keywords
subject: Machine Learning
  topic: keywords
subject: COVID-19 Severity
  topic: keywords
subject: Multi-Omics Integration
  topic: keywords
subject: Post-Viral Outcomes
  topic: keywords
creator: Himanshu Shekhar Singh
creator: Janani Sp
creator: Shaik Mubarak Basha
creator: Mahak
creator: Dr. Ramachandraprasad La
creator: Dr. Chemmugil
rights: Copyright (c) 2026 EPH-International Journal of Medical and Health Science https://creativecommons.org/licenses/by-nc/4.0
date: 2026-04-28
publication date: 2026-04-28
starting page: 52
ending page: 71
doi: 10.69980/w53n3j86

PHYSIOLOGY OF SLEEP DEPRIVATION AND ITS IMPACT ON BRAIN FUNCTION
type: item
description: Sleep is a fundamental biological process essential for maintaining optimal physiological and cognitive functions. Sleep deprivation, whether acute or chronic, disrupts normal brain activity and leads to significant impairments in neurological processes. This research paper explores the physiological mechanisms underlying sleep deprivation and examines its effects on brain function. The study highlights how lack of sleep alters neurotransmitter balance, hormonal regulation, and neural connectivity, particularly in brain regions such as the prefrontal cortex, hippocampus, and amygdala. Sleep deprivation is associated with reduced cognitive performance, impaired memory consolidation, decreased attention span, and emotional instability. Additionally, it affects synaptic plasticity, increases oxidative stress, and contributes to neuroinflammation, which may predispose individuals to neurodegenerative disorders. The paper also discusses the impact of sleep loss on circadian rhythm disruption and its role in metabolic and psychological disorders. Experimental findings from previous studies indicate that even short-term sleep deprivation can significantly affect decision-making abilities and reaction time, while long-term deprivation may result in irreversible neural damage. Understanding the physiological basis of sleep deprivation is crucial for developing effective interventions and promoting healthy sleep habits. This study emphasizes the importance of adequate sleep in maintaining brain health and overall well-being.
subject: Articles
  topic: section
subject: Sleep deprivation
  topic: keywords
subject: brain function
  topic: keywords
subject: neurotransmitters
  topic: keywords
subject: cognitive impairment
  topic: keywords
subject: circadian rhythm
  topic: keywords
creator: Helisha Kalpesh Gundaria
rights: Copyright (c) 2026 EPH-International Journal of Medical and Health Science https://creativecommons.org/licenses/by-nc/4.0
date: 2026-05-27
publication date: 2026-05-27
starting page: 28
ending page: 34
doi: 10.69980/qhjkkv90