Medicinal, Psychological, and Health Research Journal (MPHRJ)

Abstract Brain tumors remain among the most challenging malignancies in both adult and pediatric populations due to their heterogeneity, limited accessibility for biopsy, and variable clinical outcomes. Recently, circulating microRNAs (miRNAs) have emerged as promising minimally invasive biomarkers for cancer detection and prognosis. This systematic review and meta-analysis aimed to evaluate the diagnostic and prognostic value of circulating miRNAs in adult and pediatric brain tumors. A comprehensive literature search conducted across major electronic databases to identify eligible studies assessing circulating miRNAs in blood, serum, plasma, or cerebrospinal fluid of patients with primary brain tumors. Studies reporting diagnostic accuracy measures (sensitivity, specificity, area under the curve [AUC]) or survival outcomes (overall survival, progression-free survival, hazard ratios) were included. Data extracted and pooled using random-effects models. Study quality assessed using standardized appraisal tools. The meta-analysis demonstrated that circulating miRNAs exhibit significant diagnostic performance in differentiating brain tumor patients from healthy controls, with pooled sensitivity and specificity indicating moderate-to-high accuracy. Several miRNAs, including tumor-specific expression signatures, showed consistent upregulation or downregulation across gliomas, medulloblastomas, and other central nervous system tumors. Prognostically, elevated or reduced levels of specific circulating miRNAs were significantly associated with overall survival and disease progression, suggesting their potential role as independent prognostic indicators. Subgroup analyses revealed differences between adult and pediatric populations, reflecting underlying biological diversity. In conclusion, circulating miRNAs represent promising non-invasive biomarkers for the diagnosis and prognosis of brain tumors in both adults and children. However, heterogeneity in study design, sample processing, and analytical methods underscores the need for standardized protocols and large-scale prospective validation before clinical implementation.

Abstract Saliva plays a fundamental role in maintaining oral homeostasis gained increasing attention as a valuable diagnostic fluid in modern medicine and dentistry. As a complex biological fluid secreted by major and minor salivary glands, saliva contains a wide range of components including enzymes, antimicrobial proteins, hormones, electrolytes, nucleic acids, and metabolites. These constituents contribute not only to the protection and lubrication of oral tissues but also to the regulation of microbial balance within the oral cavity. Recent advances in salivary diagnostics have highlighted the potential of saliva as a non invasive, cost effective, and easily accessible medium for detecting both oral and systemic diseases. The present study aims to explore the biological functions of saliva in oral health and evaluate its diagnostic potential in identifying oral diseases such as dental caries, periodontal disease, and oral cancer. In addition, the study examines the presence of biomarkers in saliva and their clinical relevance for early disease detection. A descriptive analytical research design employed, using previously published clinical studies and laboratory analyses of salivary components. The findings indicate that salivary biomarkers, including immunoglobulins, enzymes, inflammatory mediators, and microbial products, play a significant role in identifying pathological changes in the oral environment. Variations in salivary flow rate, pH, buffering capacity, and biochemical composition were associated with the development and progression of oral diseases. Furthermore, saliva-based diagnostic technologies demonstrated high potential for early detection of systemic conditions such as diabetes, viral infections, and certain cancers. Overall, saliva represents a promising diagnostic tool that can complement traditional diagnostic methods in dentistry and medicine. Its non invasive nature and ease of collection make it particularly suitable for large-scale screening and monitoring of disease progression. Future research should focus on improving the sensitivity and specificity of salivary biomarkers and integrating salivary diagnostics into routine clinical practice.

Abstract Minimally Invasive Dentistry (MID) represents a paradigm shift from the traditional "extension for prevention" philosophy, originally proposed by G.V. Black, toward a more biological and conservative approach. This article explores the core principles of MID, focusing on the integration of advanced diagnostic tools, adhesive restorative materials, and precision surgical techniques that prioritize the preservation of healthy tooth structure. The abstract summarizes the transition from macro-mechanical retention to micro-mechanical and chemical bonding, which has redefined the longevity of dental restorations. By utilizing tools such as air abrasion, laser technology (Er:YAG), and bioactive materials, clinicians can now perform ultra-conservative preparations that minimize pulp irritation and structural weakening. The review also evaluates the role of remineralization therapies and the importance of early detection using fluorescence-based diagnostics. Findings suggest that MID not only enhances the mechanical integrity of the tooth but also significantly improves patient comfort and long-term oral health outcomes. This comprehensive study analyzes clinical data comparing traditional methods with MI techniques, highlighting success rates, marginal integrity, and patient satisfaction. The evidence underscores that the future of restorative dentistry lies in biomimetic principles and the continuous monitoring of lesions rather than immediate surgical intervention. Ultimately, this paper serves as a clinical guide for implementing MI strategies in daily practice, ensuring that the biological cost of dental treatment is kept to an absolute minimum while maximizing functional and aesthetic results.

Abstract Tooth loss long been treated through various restorative techniques, with dental implants and traditional fixed bridges representing two dominant modalities. This comparative clinical review aims to evaluate the long-term functional, aesthetic, biomechanical, and economic outcomes associated with dental implants versus conventional bridgework. A systematic analysis of randomized clinical trials, longitudinal cohort studies, and meta-analyses published between 2010 and 2025 conducted. Parameters assessed include survival rates, marginal bone loss, patient satisfaction, maintenance requirements, and cost-effectiveness. Findings reveal that implant-supported restorations demonstrate a superior survival rate (94-98% over 10 years) compared to traditional bridges (85-92%), primarily due to the preservation of alveolar bone and independence from adjacent teeth. Moreover, implants offer improved masticatory performance and aesthetic stability but require surgical intervention, appropriate bone quality, and higher initial cost. Traditional bridges, in contrast, provide faster treatment and lower upfront cost but are associated with increased abutment-tooth complications and secondary caries. From an evidence-based perspective, implants demonstrate greater long-term clinical and patient-reported success, though economic accessibility remains a limiting factor in some healthcare contexts. The review concludes that an individualized approach considering patient systemic health, bone availability, and financial capacity remains essential in prosthodontic decision-making.

Abstract Background: Emergency departments (EDs) represent high-acuity, high-volume environments where nursing interventions critically influence patient safety and clinical outcomes. Despite the central role of emergency nurses, the aggregate evidence supporting specific nursing interventions remains fragmented.

Objective: This systematic review and meta-analysis evaluates the effectiveness of ED nursing interventions on patient safety indicators and clinical outcomes, including infection rates, medication administration safety, pain management efficiency, waiting times, and hospital readmission rates.

Methods: Following PRISMA guidelines, we systematically searched PubMed, Cochrane Library, Scopus, Web of Science, and CINAHL from inception to May 2026. Randomized controlled trials, quasi-experimental studies, and observational studies evaluating nurse-led interventions in ED settings were included. A random-effects meta-analysis conducted using Stata 16.0. Heterogeneity was assessed using I² statistics, and publication bias evaluated via funnel plots and Egger's test.

Results: Twenty-nine studies (N=12,847 patients) met inclusion criteria. Nursing interventions significantly reduced healthcare-associated infections (OR=0.69, 95% CI: 0.65-0.74, p<0.001), medication administration errors (RR=0.58, 95% CI: 0.47-0.71, p<0.001), and time-to-analgesia administration (SMD=-1.24, 95% CI: -1.67 to -0.81, p<0.001). Emergency department length of stay was reduced by approximately 25 minutes (95% CI: -32.4 to -17.6, p<0.001). Hand hygiene protocols demonstrated the greatest infection reduction efficacy (OR=0.62, 95% CI: 0.57-0.68).

Conclusions: Emergency department nursing interventions substantially improve patient safety and clinical outcomes across multiple domains. Standardizing evidence-based nursing protocols, particularly for infection control and medication administration represents a high-yield strategy for enhancing emergency care quality.

Abstract Background: Surgical site complications (SSCs), including infection, dehiscence, and seroma formation, remain a significant burden in plastic and reconstructive surgery, often leading to prolonged hospitalization, additional interventions, and suboptimal aesthetic outcomes. Prophylactic negative pressure wound therapy (pNPWT) has emerged as a potential strategy to mitigate these risks, yet its efficacy compared with standard dressings (SD) in clean or clean-contaminated reconstructive procedures is not well defined.

Objective: To systematically review and meta-analyze randomized controlled trials (RCTs) and high-quality cohort studies comparing pNPWT versus SD for preventing SSCs in plastic and reconstructive surgery.

Methods: PubMed, Embase, CENTRAL, and Web of Science searched from inception to January 2026. Included studies reported on adult patients undergoing any form of plastic or reconstructive surgery, comparing pNPWT applied over closed incisions versus any SD. Primary outcomes were surgical site infection (SSI), wound dehiscence, and seroma. Secondary outcomes included hospital stay and reoperation rate. Risk of bias assessed using Cochrane RoB 2 and ROBINS-I tools. Random-effects meta-analyses performed.

Results: Thirteen studies (n=2,847 patients) met inclusion criteria. pNPWT significantly reduced SSI (RR 0.42; 95% CI 0.28–0.64; p<0.001; I²=34%) and wound dehiscence (RR 0.51; 95% CI 0.35–0.74; p=0.0003; I²=22%) compared to SD. Seroma risk was also lower with pNPWT (RR 0.62; 95% CI 0.44–0.87; p=0.006; I²=0%). No significant difference in hospital stay (MD -0.8 days; p=0.09) or reoperation rate (RR 0.79; p=0.31) was observed.

Conclusion: Prophylactic NPWT reduces key surgical site complications—specifically SSI, dehiscence, and seroma—compared with standard dressings in plastic and reconstructive surgery. These findings support integrating pNPWT into routine postoperative protocols for high-risk incisions.

Abstract Background: Emergency department (ED) crowding compromises timely care and patient safety. Nurse led triage interventions, including physician led triage, triage liaison providers, and advanced triage protocols, have implemented to improve patient flow, but their overall effectiveness on patient outcomes remains uncertain.

Objective: To synthesise evidence on the effectiveness of nurse led triage interventions on critical patient outcomes in EDs.

Methods: We systematically searched PubMed, CINAHL, Embase, Cochrane Central, and Web of Science from inception to March 2026 for randomised controlled trials (RCTs) and high quality quasi experimental studies comparing nurse led triage interventions with conventional triage. Primary outcomes were ED length of stay (LOS), left without being seen (LWBS) rates, and mortality. Random effects meta analyses performed. Certainty of evidence assessed using GRADE.

Results: Twelve studies (N=12,847 patients) met inclusion criteria. Nurse led triage interventions significantly reduced ED LOS (SMD = –0.68; 95% CI: –0.85 to –0.51; p<0.001), decreased LWBS rates (OR = 0.51; 95% CI: 0.38 to 0.69; p<0.001), and lowered in ED mortality (OR = 0.61; 95% CI: 0.44 to 0.85; p=0.003). Heterogeneity was moderate to high (I²=58–72%).

Conclusion: Nurse led triage interventions are associated with clinically meaningful improvements in ED operational and safety outcomes. Implementation of advanced nurse led triage models prioritised to reduce crowding and improve patient outcomes.

Abstract Skin cancer is one of the most common malignancies worldwide, and its early detection remains essential for improving survival rates and reducing healthcare burdens. Dermoscopy has significantly enhanced the diagnostic accuracy of skin cancer by allowing detailed visualization of subsurface skin structures, but its interpretation depends heavily on clinical expertise and experience. In recent years, artificial intelligence (AI) has emerged as a transformative tool in medical imaging, particularly in dermatology, enabling automated, rapid, and highly accurate analysis of dermoscopic images. This study explores the integration of AI techniques—such as convolutional neural networks (CNNs), deep learning, and ensemble models—for the early detection and classification of skin lesions, including melanoma, basal cell carcinoma, and benign nevi. By leveraging large annotated datasets and advanced feature extraction algorithms, AI-based diagnostic systems can identify subtle visual patterns that may elude human observation. The paper reviews the main architectures applied to dermoscopy, discusses data preprocessing and augmentation strategies, and analyzes the performance of AI compared to dermatologists in clinical studies. Moreover, it highlights explainability, interpretability, and ethical considerations in AI-assisted diagnosis, ensuring transparency and trust in clinical applications. Results from recent research indicate that AI models achieve dermatologist-level accuracy and can serve as valuable decision-support systems, particularly in teledermatology and resource-limited settings. The findings suggest that AI-powered dermoscopic analysis represents a paradigm shift toward personalized, accessible, and efficient skin cancer screening, with significant implications for global public health and digital medicine.