Physicians' Perception About the Side Effects of COVID-19 Vaccine and Their Role in Vaccination Program.

INTRODUCTION: The Coronavirus disease 2019 (COVID-19) caused many problems in the health sector. Effective and safe vaccines are the only tool to combat the COVID-19 disease. Researchers and regulatory agencies have made efforts to develop such vaccines and healthcare professionals were prioritized for the vaccination program as first-line care providers. Considering this prioritization, we aimed to assess the physicians' perceptions regarding the side effects of the COVID-19 vaccine. METHODS: An interview-based study was conducted from May 5 May to November 5, 2021 (6 months) in a teaching hospital in the capital city of Islamabad, Pakistan. RESULTS: Among the 200 physicians who agreed to participate in the interview, 74% were male. A total of 94% did not experience any side effects after receiving the COVID-19 vaccine, regardless of the type of vaccine; 6% experienced side effects. Furthermore, 90% of physicians were afraid of side effects due to the high number of vaccine doses. CONCLUSION: Conclusively, physicians had a positive perception regarding the COVID-19 vaccine. Healthcare authorities and related departments must take precautions to ensure the effective and safe COVID-19 vaccine to change the perceptions of physicians who had a negative perception. This will not only reduce the reluctance among physicians regarding administering COVID-19 vaccine, but will also boost and facilitate the vaccination program for the general public as well.

Gastronomic Tourism and Tourist Motivation: Exploring Northern Areas of Pakistan.

Gastronomic tourism is becoming an essential consideration among tourists when choosing a tourist destination. One of the main reasons for visiting a specific destination for almost 15% of tourists is "gastronomy". This has led to the development of a new kind of tourism called "Gastronomic Tourism". However, there has been minimal research on gastronomy tourism, specifically in Pakistan. The primary purpose of this study is to measure the level of satisfaction in a tourist destination and furthermore consider gastronomy as a component of visitor motivation. A survey of 307 tourists who had recently visited Pakistan's northern areas was undertaken to conduct the study. This has enabled us to better understand the variables that influence the behaviors and attitudes of tourists toward this popular tourist attraction. Gastronomy motivation impacts tourism location selection, and gastronomic experience influences satisfaction, according to the research. Specifically, tourists show a keen interest in gastronomic experiences after feeling satisfied with the destination and local foods, developing loyalty toward the destination.

Radiographic patterns on Chest X-ray as a supporting imaging tool in triaging of suspected Corona Virus Disease (COVID) patients.

Objective: To evaluate the radiographic patterns on Chest X-Ray (CXR) in accordance with Modified Brixia Scoring as supporting imaging tool in triaging of Corona Virus Disease (COVID-19) pneumonia. Methods: In this cross-sectional study, chest radiographs of suspected COVID patients at emergency triage, Lady Reading Hospital (LRH) from April 18th to July 22nd 2020 were evaluated for patterns of COVID pneumonia and scored in accordance with modified Brixia score. Each zone was categorized as score of "one" for interstitial pattern, "two" for mixed interstitial /alveolar pattern and "three" for alveolar pattern. Radiographic patterns consistent with COVID pneumonia or patients having strong clinical suspicion were advised Polymerase Chain Reaction (PCR) tests. Results: Total of 2,225 individuals were screened for patterns of COVID-19 pneumonia on chest radiograph. Out of these 1465(65.8%) had normal chest radiograph and 760(34.2%) had abnormal findings. Out of the total, 648 suspected COVID patients were selected for PCR. The radiographic patterns ranged from mixed interstitial/alveolar pattern in 261(40.3%) patients, alveolar pattern in 231(35.6%), interstitial pattern in 87(13.4%), pleural effusion in 12(1.9%), other findings in 5(0.8%) while 52(8%) suspected Covid patients had normal radiographs. The PCR was positive in 326(50.3%), negative in 100(15.4%) and inconclusive in 60(9.3%) while 162(25%) were lost to follow up. Amongst the 52 suspected Covid patients having normal chest radiographs, 10 were positive on PCR, 21 negative, seven suspected and two inconclusive, while 12 were lost to follow up. Conclusion: Chest radiograph is used for triaging of suspected COVID pneumonia patients in emergency settings. It assesses the severity of disease according to modified Brixia scoring for treatment plan.

Knowledge, Attitude, and Perception of Cancer Patients towards COVID-19 in Pakistan: A Cross-Sectional Study.

BACKGROUND: Cancer patients, being immunocompromised, are at higher risk of coronavirus disease (COVID-19). The current study determines cancer patients' knowledge, attitude, perception, and impact of the COVID-19 pandemic. METHOD: A cross-sectional online survey was conducted in Pakistan from 1 April 2020 to 1 May 2020. The study respondents were cancer patients with ages equal to or greater than 18 years. Following a request for participation, the URL for the survey was distributed on numerous channels. Other social media platforms, including WeChat, WhatsApp, Facebook, Twitter, Instagram, Messenger, and LinkedIn, were used to increase cancer patient interaction. The questionnaire comprised five different sections such as: (1) sociodemographic information, (2) knowledge, (3) attitude, (4) perception, and (5) impact of COVID-19 on cancer patients. Descriptive medical statistics such as frequency, percentage, mean, and standard deviation were used to illustrate the demographic characteristics of the study participants. To compare mean knowledge scores with selected demographic variables, independent sample t-tests and one-way analysis of variance (ANOVA) were used, which are also practical methods in epidemiological, public health and medical research. The cut-off point for statistical significance was set at a p-value of 0.05. RESULTS: More than 300 cancer patients were invited, of which 208 agreed to take part. The response rate was 69.33% (208/300). Gender, marital status, and employment status had a significant association with knowledge scores. Of the total recruited participants, 96% (n = 200) (p < 0.01) knew about COVID-19, and 90% were aware of general symptoms of COVID-19 disease, such as route of transmission and preventive measurements. In total, 94.5% (n = 197) (p < 0.01) were willing to accept isolation if they were infected with COVID-19, and 98% (n = 204) (p < 0.01) had reduced their use of public transportation. More than 90% (n = 188) (p < 0.01) of cancer patients were found to be practicing preventative measures such as using a face mask, keeping social distance, and avoiding handshaking and hugging. Around 94.4% (n = 196) (p < 0.01) of cancer patients had been impacted by, stopped or had changed cancer treatment during this pandemic, resulting in COVID-related anxiety and depression. CONCLUSION: The included cancer patients exhibited a good level of COVID-19 knowledge, awareness, positive attitude, and perception. Large-scale studies and efforts are needed to raise COVID-19 awareness among less educated and high-risk populations. The present survey indicates that mass-level effective health education initiatives are required for developing countries to improve and reduce the gap between KAP and COVID-19.

Artificial Intelligence-Based Solution in Personalized Computer-Aided Arthroscopy of Shoulder Prostheses.

BACKGROUND: Early recognition of prostheses before reoperation can reduce perioperative morbidity and mortality. Because of the intricacy of the shoulder biomechanics, accurate classification of implant models before surgery is fundamental for planning the correct medical procedure and setting apparatus for personalized medicine. Expert surgeons usually use X-ray images of prostheses to set the patient-specific apparatus. However, this subjective method is time-consuming and prone to errors. METHOD: As an alternative, artificial intelligence has played a vital role in orthopedic surgery and clinical decision-making for accurate prosthesis placement. In this study, three different deep learning-based frameworks are proposed to identify different types of shoulder implants in X-ray scans. We mainly propose an efficient ensemble network called the Inception Mobile Fully-Connected Convolutional Network (IMFC-Net), which is comprised of our two designed convolutional neural networks and a classifier. To evaluate the performance of the IMFC-Net and state-of-the-art models, experiments were performed with a public data set of 597 de-identified patients (597 shoulder implants). Moreover, to demonstrate the generalizability of IMFC-Net, experiments were performed with two augmentation techniques and without augmentation, in which our model ranked first, with a considerable difference from the comparison models. A gradient-weighted class activation map technique was also used to find distinct implant characteristics needed for IMFC-Net classification decisions. RESULTS: The results confirmed that the proposed IMFC-Net model yielded an average accuracy of 89.09%, a precision rate of 89.54%, a recall rate of 86.57%, and an F1.score of 87.94%, which were higher than those of the comparison models. CONCLUSION: The proposed model is efficient and can minimize the revision complexities of implants.