Role of Stem Cells in Orthopaedic Surgery: Theoretical Survey

This study aims at analyzing the Stem cell application is a burgeoning field of medicine that is likely to influence the future of orthopaedic surgery. Stem cells are associated with great promise and great controversy. For the orthopaedic surgeon, stem cells may change the way that orthopaedic surgery is practiced and the overall approach of the treatment of musculoskeletal disease. Stem cells may change the field of orthopaedics from a field dominated by surgical replacements and reconstructions to a field of regeneration and prevention. This review will introduce the basic concepts of stem cells pertinent to the orthopaedic surgeon and proceed with a more in depth discussion of current developments in the study of stem cells in orthopaedic surgery. Keywords: Stem cell, orthopaedic, surgery

Outcomes from elective colorectal cancer surgery during the SARS-CoV-2 pandemic

This study aimed to describe the change in surgical practice and the impact of SARS-CoV-2 on mortality after surgical resection of colorectal cancer during the initial phases of the SARS-CoV-2 pandemic

Time-Series Analysis and Healthcare Implications of COVID-19 Pandemic in Saudi Arabia

The first case of coronavirus disease 2019 (COVID-19) in Saudi Arabia was reported on 2 March 2020. Since then, it has progressed rapidly and the number of cases has grown exponentially, reaching 788,294 cases on 22 June 2022. Accurately analyzing and predicting the spread of new COVID-19 cases is critical to develop a framework for universal pandemic preparedness as well as mitigating the disease’s spread. To this end, the main aim of this paper is first to analyze the historical data of the disease gathered from 2 March 2020 to 20 June 2022 and second to use the collected data for forecasting the trajectory of COVID-19 in order to construct robust and accurate models. To the best of our knowledge, this study is the first that analyzes the outbreak of COVID-19 in Saudi Arabia for a long period (more than two years). To achieve this study aim, two techniques from the data analytics field, namely the auto-regressive integrated moving average (ARIMA) statistical technique and Prophet Facebook machine learning technique were investigated for predicting daily new infections, recoveries and deaths. Based on forecasting performance metrics, both models were found to be accurate and robust in forecasting the time series of COVID-19 in Saudi Arabia for the considered period (the coefficient of determination for example was in all cases more than 0.96) with a small superiority of the ARIMA model in terms of the forecasting ability and of Prophet in terms of simplicity and a few hyper-parameters. The findings of this study have yielded a realistic picture of the disease direction and provide useful insights for decision makers so as to be prepared for the future evolution of the pandemic. In addition, the results of this study have shown positive healthcare implications of the Saudi experience in fighting the disease and the relative efficiency of the taken measures

CARDIOGENIC PULMONARY EDEMA IN CRITICAL CARE

The pathobiology and classification of pulmonary edoema are more complex than the previous dichotomy of hydrostatic vs. permeability. The mechanisms of alveolar fluid clearance and the factors that influence the clearance rate are being studied thoroughly in order to develop therapeutic strategies. Patients require early oxygenation and ventilation stabilization, preferably with high-flow nasal cannula oxygen or noninvasive ventilation, while the diagnostic cause is quickly sought with echocardiography and other testing. Treatments must begin as soon as possible while evaluation continues and requires multimodal intervention. Diuretics, possibly morphine, and frequently nitrates, are used to treat cardiogenic pulmonary edema. This review summarizes current knowledge of the pathophysiology, causes, and treatment of cardiogenic pulmonary edema

Stress, Anxiety, and Depression in Pre-Clinical Medical Students: Prevalence and Association with Sleep Disorders

Our aim was to assess sleep quality in different subgroups of preclinical medical students, and then to identify specific lifestyle factors, academic and social factors as well as Corona virus related factors that were associated with poor sleeping quality and poor psychological health. Study participants were all medical students at King Saud University of Medical Sciences in the first and second years (648 students), and the study was conducted from December 2021 to January 2022. We administered the survey on paper as well as online. We used three types of questionnaires in this study. The first was a self-administered questionnaire, the second was a validated Insomnia Severity Index (ISI) for finding sleeping problems, and the third was a validated DASS 10 for determining Depression, Anxiety, and Stress. A total of 361 pre-clinical medical students consisted of 146 (40.4%) males and 215 (59.5%) females. The majority of the students, 246 (68.1%), were in their second year. Furthermore, in the current study, students who had poor academic performance (15.8%), satisfactory academic performance (21.3%), or good academic performance (30.7%) had significant sleeping problems found (χ2 = 19.4; p = 0.001), among them poor academic performance students 21.6%, satisfactory academic performance students (29.3%), and good academic performance students (29.3%) had moderate to severe levelled sleeping problems. Similarly, poor, satisfactory, and good academic performers experienced the highest levels of anxiety (poor = 21.5%; satisfactory = 22.1%; and good = 22.8%); stress (poor = 22.4%; satisfactory = 25.2%; and good = 22.4%); and depression (poor = 40.5%; satisfactory = 40.5%; and good = 11.9%). The majority of students (64.8%) reported that during the pandemic crisis their anxiety levels were high. Additionally, students reported significantly high sleeping issues (χ2 = 10.6; p = 0.001) and also serious psychological issues (Anxiety = 34.9 (0.000); Stress = 32.5 (0.000); and Depression = 5.42 (0.01)). There was a high prevalence of sleep issues, anxiety, stress, and depression among the pre-clinical medical students, with significantly higher sleeping disorders, anxiety, stress, and depression levels among those medical students who struggle with their academic performances, poor lifestyle factor, and poor Social and COVID management

A Systematic Review of Clinical Pharmacokinetics of Inhaled Antiviral

Background and Objectives: The study of clinical pharmacokinetics of inhaled antivirals is particularly important as it helps one to understand the therapeutic efficacy of these drugs and how best to use them in the treatment of respiratory viral infections such as influenza and the current COVID-19 pandemic. The article presents a systematic review of the available pharmacokinetic data of inhaled antivirals in humans, which could be beneficial for clinicians in adjusting doses for diseased populations. Materials and Methods: This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. A comprehensive literature search was conducted using multiple databases, and studies were screened by two independent reviewers to assess their eligibility. Data were extracted from the eligible studies and assessed for quality using appropriate tools. Results: This systematic review evaluated the pharmacokinetic parameters of inhaled antiviral drugs. The review analyzed 17 studies, which included Zanamivir, Laninamivir, and Ribavirin with 901 participants, and found that the non-compartmental approach was used in most studies for the pharmacokinetic analysis. The outcomes of most studies were to assess clinical pharmacokinetic parameters such as the Cmax, AUC, and t1/2 of inhaled antivirals. Conclusions: Overall, the studies found that the inhaled antiviral drugs were well tolerated and exhibited favorable pharmacokinetic profiles. The review provides valuable information on the use of these drugs for the treatment of influenza and other viral respiratory infections

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population