Iron Deficiency Anemia in Adults and its Diagnosis and Treatment: A Systemic Review

The aim of this study is to explore the clinical management in diagnosis and treatment of the iron deficiency anemia in adults with a systematic review methodology, as the iron deficiency is the most frequent cause of anemia worldwide. And it impairs quality of life, increases asthenia and can lead to clinical worsening of patients. In addition, iron deficiency has a complex mechanism whose pathologic pathway is recently becoming better understood. This review summarizes the current knowledge regarding diagnostic algorithms for iron deficiency anemia. The majority of aetiologies occur in the digestive tract, and justify morphological examination of the gut. First line investigations are upper gastrointestinal endoscopy and colonoscopy, and when negative, the small bowel should be explored; newer tools such as video capsule endoscopy have also been developed. The treatment of iron deficiency is aetiological if possible and iron supplementation whether in oral or in parenteral form

Improving the time delay in the design of the damping controller with the aim of improving the stability of the power system in the presence of high penetration of renewable energy sources

Due to the high penetration of renewable energy sources (RES) such as wind units in power systems, the need to check the stability of transmission networks has been given more attention than before. Therefore, in this paper, due to the importance of the topic, the wide area damping controller (WADC) has been used for the battery energy storage system (BESS) connected to the photovoltaic unit and the permanent magnet synchronous generator (PMSG) in the dc link. The WADC design is based on free weight matrices (FWM), which can solve a set of constraints based on the linear matrix inequality (LMI) based on the delay-dependent feedback control theory. The working method is that the constraints related to LMI are considered in such a way that it has the ability to tolerate the maximum amount of time delay. FWM has been used to communicate between LMI constraints and the maximum value of the time delay margin. FWM matrices are also based on an iterative algorithm based on linearization of the conical complement, which tries to search for the most optimal value for the control parameters. To implement the simulation results in MATLAB software, an improved power system of 16 machines has been used, the results of which are clearly analyzed and show the superiority of the proposed method compared to other mentioned methods

Adherence to antidiabetic medication during the month of Ramadan among diabetes mellitus patients in the kingdom of Saudi Arabia

Background: Ramadan may lead to reduced adherence to antidiabetic medications among Saudi diabetes patients due to fasting, changes in daily routine, social and cultural influences, health risks, and inadequate awareness. This study aimed to assess the Saudi population adherence to the diabetes management medication in Ramadan. Methodology: A convenience sampling method was used to recruit participants for the study. Participants were sourced from social media platforms, diabetes mellitus patient groups, and healthcare providers groups. The Medication Adherence Rating Scale (MARS), a tool, was used to assess medication compliance. Results: A total of 384 individuals were included in this study, 20.3% were from Riyadh, 52.3% were males, 35% aged 31-50 years, and 64.1% had type 2 diabetes mellitus of participants. Age between 31-50 years was negatively associated with compliance (β = -1.06, p = 0.002), while age between 51-65 years is positively associated ((β= 1.00, p = 0.003). Being male was negatively associated with compliance (β= -0.72, p = 0.001). Different fasting behaviors like non-fasting one day or more (β = -2.92, p < 0.001) and fasting all month (β = -2.90, p < 0.001), significantly affect compliance scores with negative associations indicating lower compliance during fasting periods. Various HbA1c levels were significant predictors of compliance. Higher HbA1c levels were associated with increased compliance. Conclusions: The study reveals that age, gender, fasting behaviors and HbA1c levels significantly impact medication compliance among patients with diabetes mellitus during Ramadan

Human Fall Detection Using 3D Multi-Stream Convolutional Neural Networks with Fusion

Human falls, especially for elderly people, can cause serious injuries that might lead to permanent disability. Approximately 20–30% of the aged people in the United States who experienced fall accidents suffer from head trauma, injuries, or bruises. Fall detection is becoming an important public healthcare problem. Timely and accurate fall incident detection could enable the instant delivery of medical services to the injured. New advances in vision-based technologies, including deep learning, have shown significant results in action recognition, where some focus on the detection of fall actions. In this paper, we propose an automatic human fall detection system using multi-stream convolutional neural networks with fusion. The system is based on a multi-level image-fusion approach of every 16 frames of an input video to highlight movement differences within this range. This results of four consecutive preprocessed images are fed to a new proposed and efficient lightweight multi-stream CNN model that is based on a four-branch architecture (4S-3DCNN) that classifies whether there is an incident of a human fall. The evaluation included the use of more than 6392 generated sequences from the Le2i fall detection dataset, which is a publicly available fall video dataset. The proposed method, using three-fold cross-validation to validate generalization and susceptibility to overfitting, achieved a 99.03%, 99.00%, 99.68%, and 99.00% accuracy, sensitivity, specificity, and precision, respectively. The experimental results prove that the proposed model outperforms state-of-the-art models, including GoogleNet, SqueezeNet, ResNet18, and DarkNet19, for fall incident detection

A Robust and Automated Vision-Based Human Fall Detection System Using 3D Multi-Stream CNNs with an Image Fusion Technique

Unintentional human falls, particularly in older adults, can result in severe injuries and death, and negatively impact quality of life. The World Health Organization (WHO) states that falls are a significant public health issue and the primary cause of injury-related fatalities worldwide. Injuries resulting from falls, such as broken bones, trauma, and internal injuries, can have severe consequences and can lead to a loss of mobility and independence. To address this problem, there have been suggestions to develop strategies to reduce the frequency of falls, in order to decrease healthcare costs and productivity loss. Vision-based fall detection approaches have proven their effectiveness in addressing falls on time, which can help to reduce fall injuries. This paper introduces an automated vision-based system for detecting falls and issuing instant alerts upon detection. The proposed system processes live footage from a monitoring surveillance camera by utilizing a fine-tuned human segmentation model and image fusion technique as pre-processing and classifying a set of live footage with a 3D multi-stream CNN model (4S-3DCNN). The system alerts when the sequence of the Falling of the monitored human, followed by having Fallen, takes place. The effectiveness of the system was assessed using the publicly available Le2i dataset. System validation revealed an impressive result, achieving an accuracy of 99.44%, sensitivity of 99.12%, specificity of 99.12%, and precision of 99.59%. Based on the reported results, the presented system can be a valuable tool for detecting human falls, preventing fall injury complications, and reducing healthcare and productivity loss costs

Evaluation of the Clinical Outcome and Cost Analysis of Antibiotics in the Treatment of Acute Respiratory Tract Infections in the Emergency Department in Saudi Arabia

This study aims to assess the prevalence and antibiotic-treatment patterns of respiratory tract infections (RTIs), prevalence and types of antibiotic-prescribing errors, and the cost of inappropriate antibiotic use among emergency department (ED) patients. A cross-sectional study was conducted at the ED in King Abdulaziz Medical City, Riyadh, Saudi Arabia. Patient characteristics (age, sex, weight, allergies, diagnostic tests (CX-Ray), cultures, microorganism types, and prescription characteristics) were studied. During the study, 3185 cases were diagnosed with RTIs: adults (>15 years) 55% and pediatrics (<15 years) 44%. The overall prevalence of RTIs was 21%, differentiated by upper respiratory tract infections (URTI) and lower respiratory tract infections (LRTI) (URTI 13.4%; LRTI 8.4%), of total visits. Three main antibiotics (ATB) categories were prescribed in both age groups: penicillin (pediatrics 43%; adults 26%), cephalosporin (pediatrics 29%; adults 19%), and macrolide (pediatrics 26%; adults 38%). The prevalence of inappropriate ATB prescriptions was 53% (pediatrics 35%; adults 67%). Errors in ATB included selection (3.3%), dosage (22%), frequency (3%), and duration (32%). There is a compelling need to create antimicrobial stewardship (AMS) programs to improve antibiotic use due to the high number of prescriptions in the ED deemed as inappropriate. This will help to prevent unwanted consequences on the patients and the community associated with antibiotic use

Mycobacterium riyadhense as the opportunistic infection that lead to HIV diagnosis: A report of 2 cases and literature review

Human immunodeficiency virus (HIV) infection usually presents with a wide range of manifestations. Although HIV patients are prone to pulmonary infections by opportunistic pathogens in the late stage of AIDS, manifesting the disease with pulmonary infections caused by Mycobacterium riyadhense (newly identified non-tuberculous mycobacteria) is extremely rare with only one case reported in the literature. We are describing two previously healthy patients who presented with M. riyadhense lung infection and were subsequently found to have HIV, illustrating the need for considering the possibility M. riyadhense lung infection as a presenting illness of HIV. Keywords: Non-tuberculous mycobacteria, Mycobacterium, Mycobacterium riyadhense, Opportunistic infection

Characteristics, Management, and Outcomes of Community-Acquired Pneumonia Due to Human Rhinovirus—A Retrospective Study

Introduction. Human rhinovirus (HRV) can lead to a variety of respiratory illnesses; it is also an uncommon cause of community-acquired pneumonia (CAP). We described the characteristics and outcomes of patients hospitalized for CAP due to HRV. Methods. We retrospectively studied consecutive adult patients admitted to King Abdulaziz Medical City-Riyadh with CAP due to HRV between 2016 and 2019. The diagnosis was made by respiratory multiplex PCR within 48 hours of hospitalization. We compared patients requiring ICU admission to those who did not. Results. One-hundred-and-six patients were studied (peak hospitalization between November and January, median age 71.5 years, hypertension 59%, diabetes 50%, and chronic respiratory disease 44.3%); 16 (15.1%) patients required ICU admission. The median pneumonia severity index score (PSI) was 107, with no significant difference between ICU and nonICU patients. ICU patients had a higher prevalence of tachypnea (62.5% vs. 26.7%, p=0.005), hemoptysis (12.5% vs 0%, p=0.001), and lymphopenia (71.4% vs 26.3%, p=0.01). Chest X-ray on presentation showed bilateral infiltrates in 47/101 (46.5%) patients and unilateral infiltrates in 26/101 (25.7%) patients. Systemic corticosteroids were used in 54.7% of patients (the median initial dose was 120 mg of prednisone equivalent and was higher in nonICU patients). Most (69.2%) ICU patients received mechanical ventilation (median duration of 8 days). Bacterial coinfection (6.6%) and superinfection (3.8%) were rare. The overall hospital mortality was 9.4% (higher for ICU patients: 37.5% vs. 4.4%, p<0.001). Conclusions. Most patients with CAP due to HRV were elderly and had significant comorbidities. ICU admission was required in almost one in six patients and was associated with higher mortality

Characteristics, Management, and Outcomes of Community-Acquired Pneumonia due to Respiratory Syncytial Virus: A Retrospective Study

Background. Respiratory syncytial virus (RSV), a well-known cause of bronchiolitis in children, can cause community-acquired pneumonia (CAP) in adults, but this condition is not well studied. Hence, we described the characteristics and outcomes of patients hospitalized for CAP due to RSV. Methods. This was a retrospective study of patients admitted to a tertiary-care hospital between 2016 and 2019 with CAP due to RSV diagnosed by a respiratory multiplex PCR within 48 hours of admission. We compared patients who required ICU admission to those who did not. Results. Eighty adult patients were hospitalized with CAP due to RSV (median age 69.0 years, hypertension 65.0%, diabetes 58.8%, chronic respiratory disease 52.5%, and immunosuppression 17.5%); 19 (23.8%) patients required ICU admission. The median pneumonia severity index score was 120.5 (140.0 for ICU and 102.0 for non-ICU patients; p=0.09). Bacterial coinfection was rare (10.0%). Patients who required ICU admission had more hypotension (systolic blood pressure<90 mmHg) and a higher prevalence of bilateral infiltrates on chest X-ray (CXR) (89.5% versus 32.7%; p<0.001). Systemic corticosteroids were used in 57.3% of patients (median initial dose was 40 mg of prednisone equivalent) with ICU patients receiving a higher dose compared to non-ICU patients (p=0.02). Most (68.4%) ICU patients received mechanical ventilation (median duration of 4 days). The overall hospital mortality was 8.8% (higher for ICU patients: 31.6% versus 1.6%, p<0.001). Conclusions. Most patients with CAP due to RSV were elderly and had significant comorbidities. ICU admission was required in almost one in four patients and was associated with higher mortality

Influenza co-infection associated with severity and mortality in COVID-19 patients

Abstract Background In COVID-19 patients, undetected co-infections may have severe clinical implications associated with increased hospitalization, varied treatment approaches and mortality. Therefore, we investigated the implications of viral and bacterial co-infection in COVID-19 clinical outcomes. Methods Nasopharyngeal samples were obtained from 48 COVID-19 patients (29% ICU and 71% non-ICU) and screened for the presence of 24 respiratory pathogens using six multiplex PCR panels. Results We found evidence of co-infection in 34 COVID-19 patients (71%). Influenza A H1N1 (n = 17), Chlamydia pneumoniae (n = 13) and human adenovirus (n = 10) were the most commonly detected pathogens. Viral co-infection was associated with increased ICU admission (r = 0.1) and higher mortality (OR 1.78, CI = 0.38–8.28) compared to bacterial co-infections (OR 0.44, CI = 0.08–2.45). Two thirds of COVID-19 critically ill patients who died, had a co-infection; and Influenza A H1N1 was the only pathogen for which a direct relationship with mortality was seen (r = 0.2). Conclusions Our study highlights the importance of screening for co-infecting viruses in COVID-19 patients, that could be the leading cause of disease severity and death. Given the high prevalence of Influenza co-infection in our study, increased coverage of flu vaccination is encouraged to mitigate the transmission of influenza virus during the on-going COVID-19 pandemic and reduce the risk of severe outcome and mortality