Chronic kidney disease of unknown cause (CKDu) is now considered an important occupational and public health problem. It affects predominantly outdoor workers in agriculture, construction, and industries. Whereas typical cases of CKD are usually caused by diabetes and/or hypertension, recent studies have linked CKDu to repeated occupational heat stress, dehydration, and nephrotoxicity in hot work environments. This review incorporates relevant literature on the subject to demonstrate the possible pathways through which chronic heat exposure can lead to renal damage. These pathways include repetitive acute subclinical injury to the kidneys from dehydration and hyperthermia; fructokinase pathway activation from dehydration; oxidative stress pathways; and nephrotoxic effects due to co-exposure to agrochemicals and heavy metals. Considerations regarding occupational health practice are discussed. The rising temperatures due to climate change make heat-related disorders common not just in outdoor occupations but in most industries. Thus, CKDu is a preventable occupational disorder that warrants the attention of environmental health experts, policymakers, and employers.
The importance of early diagnosis of chronic diseases will help in minimizing disease burden, reduce the outcome of patients, and decrease the cost of healthcare in the long-term. New technologies in the field of Artificial Intelligence (AI) allow applying predictive analytics to diagnose disease risk at an early stage using big data on clinical analysis. In this research, the researchers examine the capability of AI-based predictive models to identify early chronic disease through anonymized electronic health record data. An analysis of 30,214 patient records with demographic variables, clinical variables, laboratory variables, lifestyle variables, and medical history variables was performed. Five machine learning models applying 18 key predictors to develop and compare were created on the post-processing and feature selection: Logistic Regression, Decision Tree, Random Forest, Support Vector Machine and Deep Neural Network (DNN). The performance of the model was measured in terms of accuracy, precision, recall, and F1-score, and AUC-ROC, and the focus was on recall and AUC-ROC as these indicators are necessary in early screening. The findings indicate that the improved AI models are more superior to conventional models, and the DNN attains the highest recall (0.91) and AUC-ROC (0.94), and then the Random Forest model comes next, with the recall = 0.90, and AUC-ROC = 0.93. The analysis of feature importance showed that the most influential predictors were age, level of fasting glucose, body mass index, blood pressure (systolic), and family history, which is consistent with the existing clinical risk factors. In general, the results show that AI-based predictive analytics can be an efficient and trustworthy clinical decision-support second-wave tool to predict chronic illnesses in their early stages, which promotes the transition to preventive, data-driven healthcare.
Chest radiography is an essential diagnostic tool in the detection and management of cardiopulmonary and thoracic pathologies, especially in orthopaedic settings like the National Orthopaedic Hospital, Enugu (NOHE). The quality of chest radiographs is largely influenced by the appropriate selection of exposure parameters, specifically kilovoltage peak (kVp), milliampere-seconds (mAs), and source-to-image distance (SID). However, the effect of these parameters on image quality at NOHE has not been extensively studied. This study aimed to assess how variations in kVp, mAs, and SID influence the diagnostic quality of chest radiographs performed at NOHE. A descriptive, cross-sectional study was conducted on 200 chest radiographs randomly selected from routine clinical practice. Diagnostic quality was assessed using four indicators: contrast, density, sharpness, and artifacts, all rated on a 5-point Likert scale. The study found that higher kVp (above 110), appropriate mAs (4.0–5.0), and longer SID (>180 cm) were associated with significantly improved contrast, density, sharpness, and fewer artifacts. Multiple regression analysis indicated that kVp and mAs were the strongest predictors of overall image quality. Mismanagement of exposure parameters, such as low kVp with high mAs or excessive SID, significantly decreased image quality and increased the presence of artifacts. The findings emphasize the need for standardizing exposure protocols and enhancing training for radiographers to ensure optimal image quality and minimize patient radiation exposure.
Psychoactive substance use among Nigerian adolescents stems from intertwined intrapersonal factors such as emotional distress and low self-control, and interpersonal factors such as peer influence and family conflict, yet these remain underexplored in semi-urban South-South contexts despite high reported prevalence rates of 30-80% lifetime use. To identify and quantify inter- and intrapersonal factors associated with substance use in these settings, a cross-sectional survey of 1,200 students from 20 semi-urban schools was conducted using multistage sampling, with a modified WHO questionnaire alongside scales for stress, self-esteem (Rosenberg), and peer/family influence. The data were analyzed using SPSS with chi-square tests, correlations, and logistic regression at p<0.05. Current use prevalence was 41.2% (alcohol 19%, stimulants 17%); intrapersonal factors such as stress (OR=3.2, p<0.001) and low self-esteem (OR=2.7, p=0.002) were present in 55% of users, while interpersonal drivers included peer pressure (χ²=28.4, p<0.001, 62% endorsement) and poor parental bonding (OR=2.1); males showed stronger peer links (χ²=9.1, p=0.003), and the regression model (R²=0.35) confirmed a dual-factor interplay. Conclusion: Integrated counseling that targets personal resilience and social networks is vital, and school-based resilience training and family involvement programs are recommended.
The role of pre-imaging radiation education in reducing anxiety and improving procedural compliance among orthopaedic X-ray patients was evaluated in this study conducted at the National Orthopaedic Hospital, Enugu, Nigeria. This quasi-experimental study employed a pre-test/post-test control group design and included 168 adult patients, assigned to either an intervention group (receiving structured radiation education) or a control group (receiving standard care). Anxiety levels were measured using the State-Trait Anxiety Inventory (STAI), and procedural compliance was assessed using a checklist. Results indicated that the intervention group exhibited significantly lower post-test anxiety scores and better procedural compliance compared to the control group. The findings suggest that pre-imaging education, which provided information about the procedure, radiation risks, and the importance of patient cooperation, effectively reduced anxiety and enhanced compliance, leading to better patient outcomes in diagnostic imaging. This study underscores the importance of structured education in improving patient experience and clinical efficiency during orthopaedic X-ray procedures.
Rabies is a highly fatal viral zoonotic disease that continues to pose a significant public health challenge worldwide, particularly in developing countries. In Algeria, rabies remains endemic, with rural communities disproportionately affected due to the high prevalence of stray and unvaccinated dogs, which constitute the principal source of human exposure. Despite the availability of effective preventive measures, cases of animal bites and potential human exposure continue to be reported annually. This article examines the regulatory framework governing rabies prevention and control in Algeria, including relevant veterinary and public health legislation. It also reviews the principal preventive strategies implemented at the national level, such as animal vaccination, post-exposure prophylaxis, epidemiological surveillance, public awareness campaigns, and multisectoral collaboration. Furthermore, the article highlights the major challenges hindering effective rabies control, including inadequate stray dog management, insufficient vaccination coverage, limited public awareness, and disparities in access to healthcare services. Finally, perspectives and recommendations are proposed to strengthen rabies prevention efforts and support the achievement of the global objective of eliminating dog-mediated human rabies deaths.
Delayed inflammatory reactions (DARs) following injectable aesthetic procedures, including hyaluronic acid (HA) fillers and botulinum toxin type A (BoNT-A), represent an emerging clinical challenge in aesthetic medicine. These reactions present as inflammatory nodules, granulomas, or edema, many weeks to years after administration. The pathophysiology remains incompletely understood, particularly in heterogeneous populations, despite the rising number of cases. These reactions involve T-cell hypersensitivity, cytokine dysregulation, and exogenous antigens. This study aimed to characterize these immunological pathways to guide prevention and management strategies. The study is a multicenter prospective cohort (n=218 adults; mean age=41.7 ± 9.2 years; 81% female) based on the U.S. sites recruiting subjects with DARs (onset ≥14 days post-injection) and then followed them over time. Comprehensive assessments included clinical grading (0–4 scale), skin biopsies (n=187) with immunohistochemistry (CD3, CD4, CD8, CD68, FoxP3), multiplex cytokine profiling (IL-1β, IL-4, IL-6, IL-17, TNF-α, IFN-γ), T-cell subset analysis by flow cytometry, serum immunoglobulin measurement, PCR for biofilm detection, and HLA typing were done. There were documents on triggers (e.g., vaccinations, infections) that were filled in through structured questionnaires. Data analysis was done in SPSS v28 and R v4.3 in multivariate logistic regression as predictors (p<0.05). Principally, DARs were type IV hypersensitivity reactions (72%), dominated by CD4+ T-cell infiltrates (68%; mean CD4/CD8 ratio 3.1:1) and non-caseating granulomas (41%). Th1/Th17 cytokines were significantly elevated (TNF-α: 52.4 pg/mL; IL-17: 21.3 pg/mL; p<0.0001 vs. controls) and correlated with severity (r=0.62, p<0.005). In severe cases, there was marked depletion of regulatory T cells (mean 3.8% vs. 9.2% in mild cases; p=0.002). Biofilms were detected in 17% of recurrent cases (OR 4.2, 95% CI 2.1–8.4; p<0.001). MRNA COVID-19 vaccination (29%), infections (24%), and dental procedures (11%) were the triggers. The results of our observations indicate that there might be differences between Hispanic (48%) and African American (45%) subgroups, and the granuloma rates were higher (p=0.012); nevertheless, these results have to be investigated in greater and more varied populations. Multivariate analysis has revealed vaccination (OR 2.4, 95% CI 1.3-4.5; p=0.008) and HA fillers (OR 1.8, 95% CI 1.1-3.0; p=0.02) to be independent predictors. A longitudinal follow up showed that 68% of the cases were resolved in 12 months, and there were better DLQI scores (12.3 to 3.8; p<0.001). T-cell hypersensitivity and Th1/Th17 dominate DARs, accompanied by Treg dysfunction, which is enhanced by immunizations and biofilms. The results suggest the use of immunological screening before the procedure, ethnicity-specific risk stratification, and focused immunomodulation to promote safety in aesthetic medicine. Future studies need to consider Treg-modulating therapy and worldwide populations to be widely applicable.
