International journal of health sciences
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To evaluate post-operative shoulder tip pain in low pressure (10MMHG Co2) versus standard pressure (14MMHG Co2) pneumoperitoneum in laparoscopic cholecystectomy: A one year randomized controlled trial hospital-based study
Full text linkBackground: Nowadays, the gold standard of care for cholelithiasis is laparoscopic cholecystectomy (LC). After a LC, post-operative shoulder tip pain is a typical complaint. The main cause of this shoulder tip pain is pneumoperitoneum caused by carbon dioxide. The present study was undertaken to evaluate the post-operative shoulder tip pain in low pressure (10MMHG Co2) versus standard pressure (14MMHG Co2) pneumoperitoneum in LC. Method: A prospective randomized controlled trial incorporating 70 patients with symptomatic uncomplicated cholelithiasis who underwent LC using a four-port technique. Patients were divided randomly in two groups: 35 patients underwent Low Pressure LC (10MMHG Co2) (Group-A), and another 35 patients underwent Standard Pressure LC (14MMHG Co2) (Group-B). Postoperative shoulder tip pain was assessed at 4, 8 and 24 h after operation by the Visual Analogue Scale (VAS) of Pain. Results: 11 patients (31.42%) in group B complained of post-operative shoulder tip pain as compared to only 4 patients (11.42%) in group A which was statistically significant, (P=0.0414).
Comparing functional versus absolute iron deficiency in chronic kidney disease patients
Full text linkChronic kidney disease (CKD) is a noteworthy public health concern, often leading to complications as kidney function declines. Anemia is a common early complication linked to reduced quality of life, increased cardiovascular risks, mortality, and progression to end-stage kidney disease. Iron deficiency is an adjustable risk factor for cardiovascular and renal damage. Two forms of iron deficiency exist absolute, characterized by depleted iron stores, and functional, with inaccessible iron stores despite normal or increased total body iron. The prevalence of Anemia in CKD patients ranges from 8.4% - 53%, but the specific prevalence of absolute and functional iron deficiency remains majorly unreported. Materials and methods: Demographic details, previous blood reports (Iron Profile including Serum Iron, Total iron binding capacity, Transferrin saturation, Ferritin), and medical and treatment history were taken. Data analysis was done on SPSS software. Results and Discussion: A total of 70 CKD patients were evaluated in this study. We compared functional and absolute iron deficiency in them. Both types raise the risk of cardiovascular hospitalization; however, absolute iron deficiency may be managed with medical means. These dual deficiencies coexist in a significant CKD population. Anemia in CKD stems from various factors, including erythropoietin deficiency and disordered iron regulation
Frequency and risk factors of cigarette smoking among male medical students of Bacha Khan Medical College, Mardan
Full text linkTobacco consumption is a major global health issue that contributes significantly to morbidity and mortality rates. The World Health Organization (WHO) estimates that over five million deaths occur each year due to tobacco use, projected to rise to 8 million by 2030. Furthermore, current research reveals that 47% of males and 12% of females worldwide smoke. Of particular concern is cigarette and tobacco use among medical students, given their role in crafting public health policy and guiding society's tobacco prevention measures. Studies show that smoking rates among medical students in developing countries are between 16-21%, with multi-country surveys in countries like Malaysia, India, Pakistan, Nepal and Bangladesh indicating rates between 6.7% and 17.8%. For example, a study conducted on medical students in Damascus University Faculty of Medicine revealed a 10.9% prevalence of cigarette smoking, 23.5% for water pipe, and 7.3% for both, with higher rates reported among final-year students. Likewise, a study of Rawalpindi Medical College students found that 24% had smoked at least once, with greater prevalence among hostellites rather than day scholar students.
The impact of timing of antimicrobial therapy on outcome and mortality in severe sepsis and septic shock
Full text linkEven though new antimicrobial treatments have been available for over 60 years, the fatality rate from septic shock has not decreased. Evolutionary pressure on microbial pathogens has, as expected, led to selection towards resistant species as a consequence of the creation of ever more broad-spectrum and strong antimicrobials. The ineffectiveness of antibiotic treatment of septic shock un the decades that followed may have been a result of this phenomena. The treatment of septic shock has traditionally focused on resuscitative measures. The management of these serious illnesses has not prioritised the prompt provision of effective antibiotic treatment
Malaysian Hospitals on the web: A multi-criteria assessment of official websites
Full text linkThis study thoroughly examines and assesses hospital websites in Malaysia according to a predefined list of indicators and sub-indicators, based on four criteria: Technology Features, Content, Services, and Community Interaction, as defined in the Health Sector Website Assessment Index (HSWAI). A total of 107 Malaysia hospitals were assessed. Private and university hospitals outperform public ones, especially in online appointment management and patient care automation areas. Most hospital websites perform well in the technology features criterion and satisfactorily on content, but show shortcomings in accessibility, reliability, research and teaching, participation, and community interaction elements, and most of them fall short in quality metrics data. Malaysian hospitals should adopt best practices to improve their websites concerning accessibility, reliability, services, and community interaction. The website design should endeavour to include multiple stakeholders, considering people with disabilities, in line with the sustainable development goals of leaving no one behind. Additionally, websites should ensure the dissemination of evidence-based information while taking advantage of social media to reach a wider audience
Next-generation sequencing in laboratory practice: Applications and challenges
Full text linkBackground _ The COVID-19 pandemic has underscored the critical role of next-generation sequencing (NGS) in diagnostic testing and surveillance-based screening. Public health laboratories need to incorporate these advanced molecular technologies to enhance their capabilities. However, challenges such as a shortage of skilled personnel, lack of sequencing expertise, assay standardization issues, and workload management within turnaround times are common. Aim of Work – This perspective paper aims to shed light on the benefits and challenges of using laboratory automation for sequencing purposes. It explores strategies for implementation, including instrument selection, validation approaches, staff training, and troubleshooting. Methods – In order to locate journal publications, the Scopus, Web of Science, and PubMed academic databases were searched. The following selection criteria were utilized: Articles must be written in English, focus on normative reasons rather than merely empirical research, include an abstract for software analysis, and describe NGS technology. The paper reviews current literature on laboratory automation in the context of NGS, examines case studies of successful implementation, and discusses potential barriers and solutions
COVID-19 led work environment disruption in India and its impact on the workers’ mental wellbeing
Full text linkThis study is designed to assess the impact of the Covid-19 pandemic on the mental wellbeing of remote e-workers. The study opts for a survey-based research and measures anxiety related to Covid-19 and job stress through Covid-19-related Anxiety Stress (CAS-7) and new Job Stress Scale (JSS-22) standardized instruments. For a sample of 79 respondents, a moderate Covid-19 related anxiety and Job Stress was observed. The mean score for the CAS was 18.31 ± 3.46 indicating a moderate Covid-19 related anxiety. Further, a noticeable trend was observed in the subscales of the Job Stress Scale where mean Job Stress was 12.32 ± 3.87; and Role Expectation Conflict was 13.86 ± 4.87. Coworker Support was 15.92 ± 4.54 and for Anxiety the score was 12.39 ± 5.15. The overall results of job stress scale indicate a moderate occupational anxiety and stress. Age, gender and the work experience are seen to have varied impacts on the anxiety and stress in e-workers. The study adds support to extending the literature that emphasizes implementation of policies for an improved mental and psychological well-being in the situation like COVID-19 pandemic and in such future disruptive events
Predicting hospital readmissions in diabetes patients: A comparative study of machine learning models
Full text linkThis study addresses the high hospital readmission rates among diabetes patients, which contribute to increased healthcare costs and strain on resources. By leveraging machine learning (ML) techniques, the objective is to predict readmissions and help healthcare providers identify high-risk patients for early intervention. Six machine learning models—Logistic Regression, Random Forest, Gradient Boosting, XGBoost, LightGBM, and CATBoost—were employed using the Diabetes 130-US hospitals dataset, incorporating patient demographics, clinical data, and discharge information. The models were evaluated based on metrics such as accuracy, precision, recall, and AUC-ROC. Among the models, CATBoost performed the best, achieving an AUC score of 0.70 and an accuracy of 64.2%. The most critical predictive features were the number of inpatient visits, medications prescribed, and the length of hospital stays. These results highlight the potential of machine learning in predicting hospital readmissions, providing actionable insights for improving patient outcomes. Future research should explore integrating real-time health data from wearables and examine the role of social determinants to further enhance predictive accuracy and optimize healthcare resources
Outcome of early versus late CRRT in critically ill patients with acute kidney injury
Full text linkAKI is a common but serious complication in acutely unwell patients and results in high morbidity and mortality. This review considers the issue of the effects of early versus late initiation of CRRT on patient outcomes. Early CRRT may be defined as inception shortly after the diagnosis of AKI has been established, especially in the case of signs related to fluid overload or severe electrolyte disturbances. Early CRRT would offer potential benefits like an improved survival rate, complications avoided as regards pulmonary edema and cardiac failure, better nutritional support, and a reduced need for more intensive renal replacement support later. On the other hand, late CRRT is performed in clinical practice when more severe AKI manifestations have occurred, which are usually associated with higher mortality and complications due to fluid overload and metabolic disturbances. Key studies referred to report worse outcomes for late initiation, considering higher multi-organ failure and prolongation of the length of stay in the ICU. Most observational studies report better outcomes with early CRRT, while randomized controlled trials exhibit variable results, with some finding no clinically significant difference in mortality between the timing of early and delayed initiation. 
Urinary Tract Infections (UTIs): Laboratory diagnosis - The role of artificial intelligence and smart diagnosis
Full text linkBackground: Urinary tract infections (UTIs) are prevalent outpatient conditions affecting up to 50% of individuals, with diagnostic errors common in clinical settings. The traditional reliance on clinical criteria alone yields a diagnostic error rate of about 33%, necessitating improved diagnostic methods. Aim: This mini-review evaluates the role of artificial intelligence (AI) and smart diagnostic tools in enhancing UTI diagnosis, particularly within vulnerable populations. Methods: A comprehensive literature review was conducted, assessing 782 articles, of which 14 met the inclusion criteria for AI applications in UTI diagnosis. These studies were categorized based on their focus: uncomplicated UTIs, complicated UTIs, and specific demographic groups. Results: The review revealed that 12 studies employed machine learning techniques while 2 utilized deep learning. The most frequently used models included artificial neural networks (ANNs) and extreme gradient boosting (XGBoost). Key variables influencing predictive models encompassed demographic data, anamnesis, and comorbidities. Notably, models for diagnosing uncomplicated UTIs achieved accuracy rates of up to 98.3%, while approaches for complicated UTIs demonstrated area under the curve (AUC) values ranging from 0.71 to 0.904. AI models were particularly effective in stratifying high-risk subgroups, including pregnant women and children, with models achieving AUCs of 0.82 and 0.83 for specific populations