COVID-19, A New Outlook on Pandemic Symptoms and Diagnostic Approach

Background: The main objective of this research is to learn the symptoms that occur in this pathology, since we are currently still fighting COVID-19, because of this, it is important to keep us informed about the different diagnostic methods available, which help us reach an earlier and more effective diagnosis. Various articles have been compiled to identify as soon as possible the active cases and thus reduce the number of infections. Materials and methods: This research was conducted on the basis of scientific articles and books, related to COVID-19. Methods: This research was conducted based on 15 scientific articles and 3 books, related to COVID-19. Results: The most important risk factors are diabetes mellitus, hypertension, obesity, age and sex. The most common symptoms in Latin America are dry cough, fatigue, sore throat, and fever. The preferred diagnostic test for COVID-19 is the polymerase chain reaction for its specificity and sensitivity Conclusions: As a conclusion, the main objective of the research was achieved, which is to inform the reader about the most relevant symptoms of SARS-CoV-2 in order to improve the identification of suspected cases. Furthermore, we compare various diagnostic methods that exist to date and determine that PCR is the most specific and sensitive.

A Retrospective Study on “Effectiveness of Remote Patient Monitoring in Covid-19 patients"

Corona virus disease19 has spread over the world, affecting millions of people. It has put enormous strain on the global healthcare system. Due to frequent mutations, the pandemic is spreading rapidly. The world requires a technology that will facilitate the effective diagnosis, treatment, and discharge of COVID19 patients. A model like remote patient monitoring [RPM] makes it easier to handle Covid 19 patients. RPM helps in remotely diagnosis, treatment, as well as allowing for prompt interventions. The RPM makes use of mobile technology and IoT platforms to take clinical interventions. In this study out of 151 covid19 positive subjects 91% of them were shifted to home monitoring within 5 days of MVM monitoring with few readmissions. The study investigated the effectiveness of RPM in the Indian healthcare system, as well as the performance and usability of the Vigocare mobile application by patients and doctors.

Prenatal Abdominal Electrocardiogram Monitoring System using IoT in Cloud Environment: A MIMO approach

<p>The application of Internet of Things (IoT) for acquiring, analyzing and transmission of medical data is increasing in recent years. Especially in abdominal ECG processing the need is more. Since the fetal movements are random in the abdomen, a single electrode can’t be able to acquire the fetal ECG. So multi-electrodes are used to record the same. At the same time all electrodes will not provide continuous ECG signal due to the fetal movements. The temperature, pressure and heart rate of the mother also monitored for effective diagnosis. This options makes the design a multi-input structure. In existing methods, Multi-input multi-output options are not available. In addition to that the complexity increases if number of input increases. In conventional methods, the complete machine is available in the patient room. But here in this work the product is divided into three units, bedside unit, doctors unit and main server. The bedside unit is an ECG acquisition device developed using a multi-lead heart rate monitor, sensors and microcontroller. Zigbee is used to transmit the information from the patient bedside to doctors unit which makes it wireless. During the movement of the patient also the data can be viewed. The Multi-output data corresponds to fetal ECG, maternal ECG, heart rate, temperature, pressure. The IoT using raspberry pi module connects the doctors unit with the main server. The machine learning algorithms analyze the ECG data of all electrodes and sensor outputs. The multi-outputs are viewed in a Graphical User Interface (GUI). The integration of the system is conducted to construct a complete IoT-based ECG monitoring system and diagnosis in Cloud environment. </p>

Prenatal Abdominal Electrocardiogram Monitoring System using IoT in Cloud Environment: A MIMO approach

<p>The application of Internet of Things (IoT) for acquiring, analyzing and transmission of medical data is increasing in recent years. Especially in abdominal ECG processing the need is more. Since the fetal movements are random in the abdomen, a single electrode can’t be able to acquire the fetal ECG. So multi-electrodes are used to record the same. At the same time all electrodes will not provide continuous ECG signal due to the fetal movements. The temperature, pressure and heart rate of the mother also monitored for effective diagnosis. This options makes the design a multi-input structure. In existing methods, Multi-input multi-output options are not available. In addition to that the complexity increases if number of input increases. In conventional methods, the complete machine is available in the patient room. But here in this work the product is divided into three units, bedside unit, doctors unit and main server. The bedside unit is an ECG acquisition device developed using a multi-lead heart rate monitor, sensors and microcontroller. Zigbee is used to transmit the information from the patient bedside to doctors unit which makes it wireless. During the movement of the patient also the data can be viewed. The Multi-output data corresponds to fetal ECG, maternal ECG, heart rate, temperature, pressure. The IoT using raspberry pi module connects the doctors unit with the main server. The machine learning algorithms analyze the ECG data of all electrodes and sensor outputs. The multi-outputs are viewed in a Graphical User Interface (GUI). The integration of the system is conducted to construct a complete IoT-based ECG monitoring system and diagnosis in Cloud environment. </p>

Food and Aeroallergen Sensitization in IgE -Mediated Asthma in Egypt

Purpose: Identifying the distribution of allergens is valuable to the effective diagnosis and treatment of allergic disease. So, our aim is to explore the sensitization of food and aeroallergens in Egyptian patients with atopic asthma. Methods: Cross-sectional study recruited 268 Egyptian patients with atopic asthma. Asthmatic patients were assessed by the enzyme allegro sorbent test (EAST) method for specific IgE to a panel of 19 common regional inhaled allergens and 15 food allergens. Results and Discussion: One hundred percent of the patients were sensitive to at least one allergen. Allergy to food allergens only was 2.9%; inhaled allergens only were 26.2% and both were70.9%. Fungi (62%) were the most frequent sensitizing aeroallergen amongst our asthmatic patients, followed by the pollen allergens (42.5%) and house dust mites (HDMs) (26%). Cows’ milk (30.5%) was the most frequent sensitizing food amongst our asthmatic patients, followed by eggs (22.4%) and fish (21.6%). Mono-sensitized patients accounted for 6.7% of all cases, while polysensitized was 93.3%. Moderate and severe asthma showed a significantly higher frequency of polysensitization compared to mild asthma. Conclusion: Fungi and cow's milk are the chief sensitizing allergens in Egyptian patients with atopic asthma. This study represents the first report of sensitization in atopic adult asthma using a large extract panel in Upper Egypt.

Diagnosis and Analysis of Transabdominal and Intracavitary Ultrasound in Gynecological Acute Abdomen

In order to explore the effective diagnosis method of gynecological acute abdomen, this paper takes hospital gynecological acute abdomen patients as samples and selects gynecological acute abdomen patients admitted to the hospital to be included in this study. They are divided into transabdominal ultrasound group, intracavitary ultrasound group, and combined group. Moreover, this paper uses mathematical statistics to carry out sample statistics. The statistical data mainly include ectopic pregnancy, torsion of ovarian tumor pedicle, acute suppurative salpingitis, torsion of fallopian tube, hemorrhagic salpingitis, acute pelvic inflammatory disease, rupture of corpus luteum cyst, and diagnosis accuracy rate. In addition, this paper compares the diagnostic accuracy of the abdominal ultrasound group, the intracavitary ultrasound group, and the combined group. The experimental research shows that the combined ultrasound diagnosis method can effectively improve the accuracy of the diagnosis of gynecological acute abdomen.

Expert opinion on current and emerging treatments in dermatophytosis

<p class="abstract">Dermatophytosis continues to be a worldwide public health problem, predominantly in developing countries like India. Early diagnosis and appropriate management are imperative to enhance patient outcomes and improve quality of life of individuals with dermatophytosis. Multiple focused group discussions involving 76 dermatologists across 36 cities in India were conducted to provide a consensus clinical viewpoint of expert dermatologists to gain insights toward effective diagnosis and management of Indian subjects with dermatophytosis. These discussions mainly aimed at reviewing current literature on prevalence, etiology, diagnosis and management of dermatophytosis and highlighting variations in diagnostic and treatment approaches in routine clinical practice. The current article summarizes the experts’ clinical viewpoint on overall management of dermatophytosis. Diagnosis of dermatophytosis involves clinical observation, microscopic examination and dermoscopy. Molecular techniques have certain advantages over conventional microscopy and culture methods but are associated with issues of cost and technique complexity. Oral itraconazole 200 mg–400 mg daily and terbinafine 500 mg/day could be considered for recalcitrant tinea infections. Topical azoles like luliconazole, sertaconazole, and terbinafine could be beneficial. A combination of oral and topical antifungal drugs is effective in patients with steroid-modified and difficult-to-treat tinea infections. Also, patient counselling and use of adjunctive therapies like antihistamines, retinoids, and moisturizers are essential for managing tinea infections. </p><p class="abstract"> </p>

Medical Image Processing: Detection and Prediction of PCOS – A Systematic Literature Review

Purpose: Considered as the most common hormonal disorder among women, polycystic ovary syndrome or PCOS affects 1 in 10 reproductive aged women (18 - 44 years). Ultrasonography is applied for assessing the ovaries to detect PCOS. The patients affected by PCOS consist of 10-12 cysts present in the ovary, but more than 10 cysts are more enough to diagnose the disorder from the ultrasound images. Then, by examining the ultrasound the presence of follicles will be determined. Therefore, the image processing approaches have assisted to identify the characteristics like follicle size, number of follicles and structure to minimize the workload and time of doctors. PCOS do not have better treatment and effective diagnosis. This paper includes reviewing a summary of some of the researches that have been going in area of medical diagnosis. Based on the review, research gap, research agendas to carry out further research are identified. Approach: A detailed study on the algorithms used in medical image processing and classification. Findings: The study indicated that most of the classification of polycystic ovarian syndrome is done merely on the clinical data sets. The new hybrid methodology proposed will be more precise as both images and lifestyle are analysed. Originality: The type of data required for detection system are studied and the architecture and schematic diagram of a proposed system are included. Paper Type: Literature Review.

Assessment of Marine Gill Disease in Farmed Atlantic Salmon (Salmo salar) in Chile Using a Novel Total Gross Gill Scoring System: A Case Study

Gill disorders have become more prevalent and widespread in finfish aquaculture in recent years. Their aetiology is often considered to be multifactorial. Effective diagnosis, control and prevention are hindered by the lack of standardised methodologies to characterise the aetiological agents, which produce an array of clinical and pathological presentations. The aim of this study was to define a novel gross pathological scoring system suitable for field-based macroscopic assessment of complex or multifactorial gill disease in farmed Atlantic salmon, using samples derived from a gill disease outbreak in Chile. Clinical assessment of gross gill morphology was performed, and gill samples were collected for qPCR and histology. A novel total gill scoring system was developed, which assesses gross pathological changes combining both the presumptive or healed amoebic gill disease (AGD) and the presence of other types of gill lesions. This scoring system offers a standardised approach to characterise the severe proliferative pathologies in affected gills. This total gill scoring system can substantially contribute to the development of robust mitigation strategies and could be used as an indicator trait for incorporating resistance to multifactorial gill disease into breeding goals.