International Journal of Medical Science and Public Health Research

Beyond Survival: Long-Term Ocular Outcomes in Retinopathy of Prematurity and The Importance of Emotional Intelligence in Competency-Based Neonatal Ophthalmic Care

Dr. Mariam Al-Harthi — Sun, 01 Mar 2026 00:00:00 +0000

Background: Retinopathy of prematurity (ROP) has become one of the most significant preventable causes of childhood visual morbidity in the era of improved neonatal survival. The scientific literature has established that ROP is not limited to an acute retinal vascular event in infancy, but is also associated with later refractive errors, altered ocular biometry, macular changes, and variable long-term visual function. At the same time, medical education literature increasingly emphasizes that emotionally intelligent, competency-based clinical practice is essential in complex, high-stakes care environments. Despite this, the long-term ophthalmic literature on ROP and the professional competency literature on emotional intelligence in medicine are rarely examined together.

Objective: This article develops an integrative theoretical analysis of the relationship between long-term visual and biometric outcomes in ROP and the emotional-intellectual competencies required for high-quality neonatal ophthalmic care. It argues that optimal ROP management depends not only on timely screening and treatment but also on emotionally intelligent communication, competent judgment, follow-up discipline, and interprofessional coordination.

Methods: A text-based integrative review methodology was applied using only the supplied references. The literature was grouped into four analytical domains: childhood blindness and ROP burden; retinal vascular development, screening, treatment, and long-term ocular outcomes; competency-based medical education and entrustment; and emotional intelligence in medicine, nursing, leadership, and decision-making. The review then synthesized these domains into a unified interpretive framework.

Results: The literature indicates that ROP contributes substantially to long-term visual burden through persistent refractive, structural, and functional effects, even after treatment success in infancy (Fielder et al., 2015; Good et al., 2010; Kaur et al., 2021; Lee et al., 2018). Treatment modality influences later outcomes, particularly refractive and biometric development (Geloneck et al., 2014; Chen & Chen, 2020; Yang et al., 2013). The emotional intelligence literature suggests that self-awareness, empathy, emotional regulation, teamwork, and judgment are highly relevant to medical practice, especially in emotionally charged and high-stakes settings (Arora et al., 2010; Mayer et al., 2016; Lerner et al., 2015; Johnson, 2015). These capacities align strongly with the demands of ROP screening, treatment decision-making, parent counseling, and long-term follow-up.

Conclusion: ROP should be understood not only as a retinal disease but as a longitudinal developmental and professional-care challenge. Future ROP programs and neonatal ophthalmic training models should integrate long-term outcome science with competency-based education and emotional intelligence development to improve patient-centered visual care.

Modern Perspectives on The Impact of Comorbidities on The Course of Covid-19 In Children

Sun, 15 Mar 2026 00:00:00 +0000

This article analyzes contemporary scientific literature regarding the impact of comorbidities on the course of COVID-19 in children. Obesity, diabetes mellitus, cardiovascular diseases, chronic lung diseases, neurological disorders, and immunodeficiency states are examined as independent risk factors for a severe course of COVID-19. Pathogenetic mechanisms, including cytokine storm, increased inflammatory markers, and T-cell immunity dysfunction, are described in detail. The article also highlights the clinical significance of MIS-C syndrome, its diagnostic criteria, modern treatment approaches, and vaccination recommendations.

The Effectiveness of Medicinal Plants in The Therapy of Joint Diseases: Clinical and Statistical Analysis in The Context of Traditional Medicine

Abduraimov Musurmonbek Mustafoyevich — Fri, 13 Mar 2026 00:00:00 +0000

This article examines the effectiveness of integrating traditional medicine methods into modern treatment protocols for joint diseases (osteoarthritis, rheumatoid arthritis). A comparative analysis of phytotherapeutic extracts (Harpagophytum procumbens and Symphytum officinale) was conducted on a sample of 120 patients. The evaluation of results was carried out using the visual analogue scale (VAS), the WOMAC index, and biochemical markers (CRP). Statistical analysis ($p < 0.05$) confirmed a significant improvement in the functional state of the joints and a reduction in pain syndrome in the combined therapy group.

Ensemble Machine Learning and Natural Language Processing for Automated Cancer Indicator Detection in Clinical Notes

Mon, 23 Mar 2026 00:00:00 +0000

Trebuchet MSEarly identification of cancer indicators within clinical documentation is essential for improving diagnostic efficiency and patient outcomes. This study presents a Natural Language Processing (NLP) and machine learning framework designed to extract cancer-related indicators from unstructured clinical notes. Clinical text data obtained from Kaggle and structured diagnostic features from the Breast Cancer Wisconsin (Diagnostic) Dataset available through the UCI Machine Learning Repository were used to develop and evaluate the proposed model. The methodology involved comprehensive text preprocessing, TF–IDF-based feature extraction, and feature engineering to represent clinically meaningful patterns in narrative medical text. Multiple machine learning algorithms, including Logistic Regression, Support Vector Machines, Random Forest, and Gradient Boosting classifiers, were trained and evaluated using standard performance metrics. Experimental results indicate that ensemble learning approaches outperform traditional classifiers in detecting cancer-related information from clinical narratives. Among the evaluated models, the Gradient Boosting classifier achieved the best performance with an accuracy of 95%, precision of 94%, recall of 93%, and an F1-score of 0.93. These results demonstrate the effectiveness of machine learning–based NLP systems in identifying cancer indicators within electronic health records. The proposed framework highlights the potential of automated clinical text analysis to support early cancer detection, enhance clinical decision support systems, and improve healthcare data analytics.

Modern Aspects of Diagnosis and Treatment of Thyroiditis and Parathyroid Gland Diseases: A Clinical and Pathogenetic Analysis

Qobilov A.E. — Sun, 15 Mar 2026 00:00:00 +0000

Thyroid and parathyroid pathologies frequently manifest as complex, comorbid clinical conditions; however, the precise pathogenetic intersection between autoimmune thyroiditis (AIT) and secondary hyperparathyroidism remains insufficiently characterised in current literature. This observational study assessed the structural and functional interrelationship between these two endocrine entities in a cohort of 112 patients. Biochemical marker analysis — encompassing thyroid-stimulating hormone (TSH), parathyroid hormone (PTH), and ionised calcium — in conjunction with high-resolution ultrasonography, revealed profound disturbances in calcium-phosphorus metabolism initiated by primary hypothyroidism. Patients with uncompensated AIT demonstrated a statistically significant PTH elevation averaging 66.7% above baseline control values, which correlated directly with reactive parathyroid gland hyperplasia (r = 0.55; p < 0.05). Conversely, the thyrotoxic phase of subacute thyroiditis was characterised by transient hypercalcaemia accompanied by concurrent physiological PTH suppression. Echographic assessment identified hyperplastic parathyroid changes in 22.6% of the hypothyroid cohort. These metabolic disturbances necessitate timely, targeted intervention — specifically optimised cholecalciferol and calcium supplementation — to prevent irreversible osteological complications, including diminished bone mineral density. Incorporating routine PTH and ionised calcium monitoring into the diagnostic protocol for patients presenting with TSH levels exceeding 10 mcIU/ml substantially enhances therapeutic outcomes. This study provides evidence for a critical algorithmic transition in clinical endocrinology, advancing from isolated thyroid management towards a comprehensive, multi-glandular metabolic rehabilitation strategy.