ABSTRACT
Background and purpose: Violet is a plant that has received interest in complementary medicine due to its anti-inflammatory, antipyretic, and antimicrobial effects. Fever is one of the major symptoms of COVID-19. This study was conducted to determine the effect of violet extract in the form of syrup on fever in patients with COVID-19. Materials and methods: In this randomized clinical trial, 52 patients with COVID-19 were studied in Intensive Care Unit in Amol Imam Khomeini Hospital (2021). In intervention group in addition to an injection of acetaminophen, 5 cc of violet extract syrup prepared from the aqueous extract of the plant was taken. The temperature was recorded after 30 and 60 minutes and four hours. The follow-up of the patients continued for three days and the temperature was recorded every six hours. Results: There was a significant difference between the intervention group (36.84..0.37) and control group (37.13..0.62) in mean temperature at second time in second day of follow-up (P=0.04). Also, the mean temperature was found to be significantly different between the two groups at 30 (P=0.001) and 60 minutes (P=0.05) after the intervention. At other groups, there was no significant difference between the intervention and control groups. Conclusion: The aqueous extract of violet plant in the form of syrup reduces fever in patients with COVID-19 causing no complication. Due to the ease of access to this herbal product, it can be used to prevent problems caused by fever.
ABSTRACT
Background and purpose: Violet is a plant that has received interest in complementary medicine due to its anti-inflammatory, antipyretic, and antimicrobial effects. Fever is one of the major symptoms of COVID-19. This study was conducted to determine the effect of violet extract in the form of syrup on fever in patients with COVID-19. Material(s) and Method(s): In this randomized clinical trial, 52 patients with COVID-19 were studied in Intensive Care Unit in Amol Imam Khomeini Hospital (2021). In intervention group in addition to an injection of acetaminophen, 5 cc of violet extract syrup prepared from the aqueous extract of the plant was taken. The temperature was recorded after 30 and 60 minutes and four hours. The follow-up of the patients continued for three days and the temperature was recorded every six hours. Result(s): There was a significant difference between the intervention group (36.84+/-0.37) and control group (37.13+/-0.62) in mean temperature at second time in second day of follow-up (P=0.04). Also, the mean temperature was found to be significantly different between the two groups at 30 (P=0.001) and 60 minutes (P=0.05) after the intervention. At other groups, there was no significant difference between the intervention and control groups. Conclusion(s): The aqueous extract of violet plant in the form of syrup reduces fever in patients with COVID-19 causing no complication. Due to the ease of access to this herbal product, it can be used to prevent problems caused by fever.Copyright © 2023, Mazandaran University of Medical Sciences. All rights reserved.
ABSTRACT
Background and purpose: Violet is a plant that has received interest in complementary medicine due to its anti-inflammatory, antipyretic, and antimicrobial effects. Fever is one of the major symptoms of COVID-19. This study was conducted to determine the effect of violet extract in the form of syrup on fever in patients with COVID-19. Materials and methods: In this randomized clinical trial, 52 patients with COVID-19 were studied in Intensive Care Unit in Amol Imam Khomeini Hospital (2021). In intervention group in addition to an injection of acetaminophen, 5 cc of violet extract syrup prepared from the aqueous extract of the plant was taken. The temperature was recorded after 30 and 60 minutes and four hours. The follow-up of the patients continued for three days and the temperature was recorded every six hours. Results: There was a significant difference between the intervention group (36.84±0.37) and control group (37.13±0.62) in mean temperature at second time in second day of follow-up (P=0.04). Also, the mean temperature was found to be significantly different between the two groups at 30 (P=0.001) and 60 minutes (P=0.05) after the intervention. At other groups, there was no significant difference between the intervention and control groups. Conclusion: The aqueous extract of violet plant in the form of syrup reduces fever in patients with COVID-19 causing no complication. Due to the ease of access to this herbal product, it can be used to prevent problems caused by fever.
ABSTRACT
Background and purpose: Violet is a plant that has received interest in complementary medicine due to its anti-inflammatory, antipyretic, and antimicrobial effects. Fever is one of the major symptoms of COVID-19. This study was conducted to determine the effect of violet extract in the form of syrup on fever in patients with COVID-19. Materials and methods: In this randomized clinical trial, 52 patients with COVID-19 were studied in Intensive Care Unit in Amol Imam Khomeini Hospital (2021). In intervention group in addition to an injection of acetaminophen, 5 cc of violet extract syrup prepared from the aqueous extract of the plant was taken. The temperature was recorded after 30 and 60 minutes and four hours. The follow-up of the patients continued for three days and the temperature was recorded every six hours. Results: There was a significant difference between the intervention group (36.84±0.37) and control group (37.13±0.62) in mean temperature at second time in second day of follow-up (P=0.04). Also, the mean temperature was found to be significantly different between the two groups at 30 (P=0.001) and 60 minutes (P=0.05) after the intervention. At other groups, there was no significant difference between the intervention and control groups. Conclusion: The aqueous extract of violet plant in the form of syrup reduces fever in patients with COVID-19 causing no complication. Due to the ease of access to this herbal product, it can be used to prevent problems caused by fever. © 2023, Mazandaran University of Medical Sciences. All rights reserved.
ABSTRACT
There was a sudden switch to online learning approaches because of the COVID-19 pandemic. Universities were under pressure to provide a variety of e-learning designs during a short time, impacting the quality of the learning. This study tended to evaluate the quality of e-content development related to English language courses by Shiraz University of Medical Sciences (SUMS) faculties. The survey was conducted on 610 undergraduate students of SUMS who had an English course in the first semester which was during the same time that the pandemic started. A self-devised questionnaire including 30 items in five main domains: physical design, affective design, cognitive design (e-content organization and multimedia principles), flexibility, and ease of use was used to achieve students' satisfaction around the quality of the e-content developed by their teachers. Data were analyzed using SPSS 22 via one-sample t-test, Independent t-test, and ANOVA. Despite the limitations of e-content development by teachers, students had a satisfactory perception overall. Among the dimensions of e-content quality, physical design, cognitive design, ease of use, and flexibility had a score higher than the cut-off point but the score of the affective design was less. In addition, the differences were significant concerning age, gender, degree, type of digital device, and the faculties. It seems that in the situation of pandemics and lack of access to students, faculty members in terms of structural and cognitive dimensions have been able to develop satisfactory e-content in a short and intensive time, but it is necessary to be motivating, interactive, and up-to-date. © 2022, Beijing Normal University.
ABSTRACT
Background and purpose: Violet is a plant that has received interest in complementary medicine due to its anti-inflammatory, antipyretic, and antimicrobial effects. Fever is one of the major symptoms of COVID-19. This study was conducted to determine the effect of violet extract in the form of syrup on fever in patients with COVID-19. Material(s) and Method(s): In this randomized clinical trial, 52 patients with COVID-19 were studied in Intensive Care Unit in Amol Imam Khomeini Hospital (2021). In intervention group in addition to an injection of acetaminophen, 5 cc of violet extract syrup prepared from the aqueous extract of the plant was taken. The temperature was recorded after 30 and 60 minutes and four hours. The follow-up of the patients continued for three days and the temperature was recorded every six hours. Result(s): There was a significant difference between the intervention group (36.84+/-0.37) and control group (37.13+/-0.62) in mean temperature at second time in second day of follow-up (P=0.04). Also, the mean temperature was found to be significantly different between the two groups at 30 (P=0.001) and 60 minutes (P=0.05) after the intervention. At other groups, there was no significant difference between the intervention and control groups. Conclusion(s): The aqueous extract of violet plant in the form of syrup reduces fever in patients with COVID-19 causing no complication. Due to the ease of access to this herbal product, it can be used to prevent problems caused by fever. Copyright © 2023, Mazandaran University of Medical Sciences. All rights reserved.
ABSTRACT
Background and purpose: Many studies suggest that surgery in patients with COVID-19 increases the risk of complications and mortality after surgery. The purpose of this research was to compare the frequency of outcomes during and after surgery between patients with and without COVID-19 undergoing emergency surgery in Gonbad Kavus hospitals, 2020-2021. Materials and methods: In this cross-sectional study, two groups of adults (n= 114) with and without COVID-19 (group A and group B, respectively) who underwent emergency surgery were examined. Demographic data, laboratory findings, and during and post-operative outcomes were recorded. Data analysis was done in SPSS V26. Results: Average age and weight in group A (45.5 years, 78.3±16.6 Kg, respectively) were found to be higher than those in group B (39.3 years and 67.9±11.5 Kg, respectively). Significant difference was seen in the percentage of arterial blood oxygen saturation after operations between group A (94.7±1.38) and group B (91.7±2.83) (P<0.0001). Also, mean ICU and hospital length of stay were significantly longer in group A (8.5 and 9.8 days, respectively) compared with group B (5.4 and 6 days, respectively) (P<0.0001). Moreover, death was observed more in group A (76%) than group B (23%) (P=0.041). Conclusion: All members of the surgical team are required to pay special attention to the increase in the incidence of complications during and after surgery in patients with COVID-19 undergoing emergency surgery in order to take necessary preventive and therapeutic measures. © 2022, Mazandaran University of Medical Sciences. All rights reserved.
ABSTRACT
Background and purpose: Coronavirus disease (COVID-19) causes different symptoms. Mizaj or temperament in Persian traditional medicine is a specific feature of every human being. The aim of this study was to determine the relationship between Mizaj and severity of symptoms in patients with COVID-19. Materials and methods: A descriptive correlational study was performed in patients with symptomatic COVID-19 during recovery and interviews were carried out to record patients' symptoms (fever, cough, chills, etc.). Salmannezhad Mizaj questionnaire was used to determine the patients' temperament (warm, cold, wet, and dry). The number of symptoms in each patient was determined and the severity of symptoms was classified into three levels: mild, moderate, and severe. The relationship between Mizaj and COVID-19 clinical symptoms were assessed by Chi-square and Pearson correlation coefficients.
ABSTRACT
Background and purpose: Coronavirus disease (COVID-19) causes different symptoms. Mizaj or temperament in Persian traditional medicine is a specific feature of every human being. The aim of this study was to determine the relationship between Mizaj and severity of symptoms in patients with COVID-19. Materials and methods: A descriptive correlational study was performed in patients with symptomatic COVID-19 during recovery and interviews were carried out to record patients’ symptoms (fever, cough, chills, etc.). Salmannezhad Mizaj questionnaire was used to determine the patients’ temperament (warm, cold, wet, and dry). The number of symptoms in each patient was determined and the severity of symptoms was classified into three levels: mild, moderate, and severe. The relationship between Mizaj and COVID-19 clinical symptoms were assessed by Chi-square and Pearson correlation coefficients. Results: In this study, 168 patients (48 ± 13.3 years) were cared for between 4 and 30 days in COVID Recovery Center. Fever, dyspnea, and cough were seen in 73.2%. Among the patients, 47.6% had cold Mizaj and 26.2% had warm or moderate Mizaj. The frequency of severe symptoms was higher in patients with cold Mizaj compared with that in patients with warm or moderate Mizaj (P= 0.204). Myalgia was found to be considerably higher in cold-Mizaj patients than warm-Mizaj people (P= 0.006). Significant correlations were seen between wet and dry Mizaj and severity of symptoms (P<0.046, R= 0.554) and warm and cold Mizaj and frequency of symptoms (P< 0.054, R= 0.489). Conclusion: Patients with COVID-19, who had cold or wet Mizaj had more symptoms, therefore, support, care, and preventive measures of Persian traditional medicine are recommended for people with cold or wet Mizaj exposed to Coronavirus.
ABSTRACT
Nowadays, wearing a face mask is a vital routine in life, but threats are increasing in public due to the advantage of wearing face masks. Existing works do not perfectly detect the human face and also not possible to apply for different faces detection. To overwhelm this issue, in this paper we proposed real-time face mask detection. The proposed work consists of six steps: video acquisition and keyframes selection, data augmentation, facial parts segmentation, pixel-based feature extraction, Bag of Visual Words (BoVW) generation, and face mask detection. In the first step, a set of keyframes are selected using the histogram of gradient (HoG) algorithm. Secondly, data augmentation is involved with three steps as color normalization, illumination correction (parameterized CLAHE), and pose normalization (Angular Affine Transformation). In the third step, facial parts are segmented using the clustering approach i.e., Expectation Maximization with Gaussian Mixture Model (EM-GMM), in which facial regions are segmented into Eyes, Nose, Mouth, Chin, and Forehead. Then, CapsNet based Feature Extraction is performed using CapsNet approach, which performance is higher and lightweight model than the Yolo Tiny V2 and Yolo Tiny V3, and extracted features are constructed into Codebook by Hassanat Similarity with K-Nearest neighbor (H-M with KNN) algorithm. For mask detection, L2 distance function is used. Experiments conducted using Python IDLE 3.8 for the proposed model and also previous works as GMM with Deep learning (GMM + DL), Convolutional Neural Network (CNN) with VGGF, Yolo Tiny V2, and Yolo Tiny V3 in terms of various performance metrics. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
There was a sudden switch to online learning approaches because of the COVID-19 pandemic. Universities were under pressure to provide a variety of e-learning designs during a short time, impacting the quality of the learning. This study tended to evaluate the quality of e-content development related to English language courses by Shiraz University of Medical Sciences (SUMS) faculties. The survey was conducted on 610 undergraduate students of SUMS who had an English course in the first semester which was during the same time that the pandemic started. A self-devised questionnaire including 30 items in five main domains: physical design, affective design, cognitive design (e-content organization and multimedia principles), flexibility, and ease of use was used to achieve students' satisfaction around the quality of the e-content developed by their teachers. Data were analyzed using SPSS 22 via one-sample t-test, Independent t-test, and ANOVA. Despite the limitations of e-content development by teachers, students had a satisfactory perception overall. Among the dimensions of e-content quality, physical design, cognitive design, ease of use, and flexibility had a score higher than the cut-off point but the score of the affective design was less. In addition, the differences were significant concerning age, gender, degree, type of digital device, and the faculties. It seems that in the situation of pandemics and lack of access to students, faculty members in terms of structural and cognitive dimensions have been able to develop satisfactory e-content in a short and intensive time, but it is necessary to be motivating, interactive, and up-to-date.
ABSTRACT
Background and purpose: Today, the Coronavirus disease 2019 (COVID-19), as a pandemic disease, has a high incidence and mortality rate. The experiences of those who have recovered could be of great benefit in understanding and management of the disease. This study aimed at determining the experiences of patients who have recovered from COVID-19. Materials and methods: A phenomenological study was performed in recovered COVID-19 patients (n=17) in Yavaran Mehdi Convalescent Care Center in Qom, Iran 2020. Purposive sampling was done and continued until data saturation was reached. Semi-structured in-depth interviews were conducted. Data analysis was performed using Colaizzi method and MAXQDA 2018 was used to encode the data.
ABSTRACT
In this paper we proposed a real-time face mask detection and recognition for CCTV surveillance camera videos. The proposed work consists of six steps: video acquisition and keyframes selection, data augmentation, facial parts segmentation, pixel-based feature extraction, Bag of Visual Words (BoVW) generation, face mask detection, and face recognition. In the first step, a set of keyframes are selected using histogram of gradient (HoG) algorithm. Secondly, data augmentation is involved with three steps as color normalization, illumination correction (CLAHE), and poses normalization (Angular Affine Transformation). In third step, facial parts are segmented using clustering approach i.e. Expectation Maximization with Gaussian Mixture Model (EM-GMM), in which facial regions are segmented into Eyes, Nose, Mouth, Chin, and Forehead. Then, Pixel-based Feature Extraction is performed using Yolo Nano approach, which performance is higher and lightweight model than the Yolo Tiny V2 and Yolo Tiny V3, and extracted features are constructed into Codebook by Hassanat Similarity with K-Nearest neighbor (H-M with KNN) algorithm. For mask detection, L2 distance function is used. The final step is face recognition which is implemented by a Kernel-based Extreme Learning Machine with Slime Mould Optimization (SMO). Experiments conducted using Python IDLE 3.8 for the proposed Yolo Nano model and also previous works as GMM with Deep learning (GMM+DL), Convolutional Neural Network (CNN) with VGGF, Yolo Tiny V2, and Yolo Tiny V3 in terms of various performance metrics. © 2021 IEEE.