Correlation of Lactate Dehydrogenase Level with Severity of Disease and In-hospital Outcome in Individuals Diagnosed with COVID-19: A Retrospective Study

Introduction: The presence of tissue damage in the lungs, kidneys, heart, or other organs can be detected by monitoring the level of Lactate Dehydrogenase (LDH) in the blood and considered a reliable biomarker in early prediction of patients' prognosis. Aim: To determine extent of correlation between LDH level with the spectrum and in-hospital outcome of Coronavirus Disease -2019 (COVID-19) infected patients. Materials and Methods: This retrospective research was undertaken during March 2020 to May 2020, based on the data of 205 COVID-19 infected patients, reported at Dammam Medical Complex, Dammam, Eastern Province, Saudi Arabia. Patients' records were retrieved and the following data were recorded-age, gender, nationality, co-morbidities, lactate dehydrogenase level, number of days since the patient tested positive (Up to 7,14 and > 14 days), COVID-19 symptoms [mild, moderate, or severe as per British Thoracic Society guidelines (CURB (Confusion, Blood Urea Nitrogen, Respiratory Rate, Blood Pressure)-65)]. The data was collected and tabulated as mean +/- SD, frequency and percentages. Analysis was carried out using specialized software of Statistical Package for Social Sciences (SPSS) version 20.0. Results: On analysis of the collected data of all 205 included patients, the LDH level was found significantly high among males, 46-60 years old, and among non-Saudi patients. The severity of COVID-19 symptoms and LDH levels were found to have a strong relationship (p-value < 0.001). Patients between the ages of 46 and 60 were more likely (4.3 times) to have poor outcomes, and diabetes mellitus was predicted to be 2.32 times more likely to be associated with poor COVID-19 outcomes. Raised LDH levels were > 5 times more likely to lead to in-hospital poor outcomes compared to those with borderline LDH levels. Conclusion: LDH level is a reliable predictor for the cause of COVID-19. The results of the present study suggest that patients aged 46-60 years, diabetic patients, or those suffering from severe symptoms of COVID-19 have raised levels of LDH.

Differential impact of COVID-19 on mental health and burnout.

BACKGROUND: There may be differential impact of the COVID-19 pandemic on mental health and burnout rates of healthcare professionals (HCPs) performing different roles. AIMS: To examine mental health and burnout rates, and possible drivers for any disparities between professional roles. METHODS: In this cohort study, online surveys were distributed to HCPs in July-September 2020 (baseline) and re-sent 4 months later (follow-up; December 2020) assessing for probable major depressive disorder (MDD), generalized anxiety disorder (GAD), insomnia, mental well-being and burnout (emotional exhaustion and depersonalization). Separate logistic regression models (at both phases) compared the risk of outcomes between roles: healthcare assistants (HCAs), nurses and midwives (nurses), allied health professionals (AHPs) and doctors (reference group). Separate linear regression models were also developed relating the change in scores to professional role. RESULTS: At baseline (n = 1537), nurses had a 1.9-fold and 2.5-fold increased risk of MDD and insomnia, respectively. AHPs had a 1.7-fold and 1.4-fold increased risk of MDD and emotional exhaustion, respectively. At follow-up (n = 736), the disproportionate risk between doctors and others worsened: nurses and HCAs were at 3.7-fold and 3.6-fold increased risk of insomnia, respectively. Nurses also had a significantly increased risk of MDD, GAD, poor mental well-being and burnout. Nurses also had significantly worsened anxiety, mental well-being and burnout scores over time, relative to doctors. CONCLUSIONS: Nurses and AHPs had excess risk of adverse mental health and burnout during the pandemic, and this difference worsened over time (in nurses especially). Our findings support adoption of targeted strategies accounting for different HCP roles.

Correlation of Lactate Dehydrogenase Level with Severity of Disease and In-hospital Outcome in Individuals Diagnosed with COVID-19: A Retrospective Study

Introduction: The presence of tissue damage in the lungs, kidneys, heart, or other organs can be detected by monitoring the level of Lactate Dehydrogenase (LDH) in the blood and considered a reliable biomarker in early prediction of patients' prognosis. Aim(s): To determine extent of correlation between LDH level with the spectrum and in-hospital outcome of Coronavirus Disease-2019 (COVID-19) infected patients. Material(s) and Method(s): This retrospective research was undertaken during March 2020 to May 2020, based on the data of 205 COVID-19 infected patients, reported at Dammam Medical Complex, Dammam, Eastern Province, Saudi Arabia. Patients' records were retrieved and the following data were recorded-age, gender, nationality, co-morbidities, lactate dehydrogenase level, number of days since the patient tested positive (Up to 7,14 and >14 days), COVID-19 symptoms [mild, moderate, or severe as per British Thoracic Society guidelines (CURB (Confusion, Blood Urea Nitrogen, Respiratory Rate, Blood Pressure)-65)]. The data was collected and tabulated as mean+/-SD, frequency and percentages. Analysis was carried out using specialized software of Statistical Package for Social Sciences (SPSS) version 20.0. Result(s): On analysis of the collected data of all 205 included patients, the LDH level was found significantly high among males, 46-60 years old, and among non-Saudi patients. The severity of COVID-19 symptoms and LDH levels were found to have a strong relationship (p-value<0.001). Patients between the ages of 46 and 60 were more likely (4.3 times) to have poor outcomes, and diabetes mellitus was predicted to be 2.32 times more likely to be associated with poor COVID-19 outcomes. Raised LDH levels were >5 times more likely to lead to in-hospital poor outcomes compared to those with borderline LDH levels. Conclusion(s): LDH level is a reliable predictor for the cause of COVID-19. The results of the present study suggest that patients aged 46-60 years, diabetic patients, or those suffering from severe symptoms of COVID-19 have raised levels of LDH. Copyright © 2023 Journal of Clinical and Diagnostic Research. All rights reserved.

Impact of the COVID-19 Pandemic Lockdown on Oral Health and Behaviour Change among Children in the Eastern Province of Saudi Arabia

Introduction: The Coronavirus Disease-2019 (COVID-19) pandemic has been concomitant to a number of alterations in children's dental health. The indoor activities and intermittent eating during the COVID-19 pandemic lockdown had an impact on oral hygiene practices and behavioural change in children. Aim: To assess the impact of the COVID-19 pandemic lockdown on oral health and behaviour change among children in the eastern province of Saudi Arabia. Materials and Methods: This cross-sectional study was conducted in Department of Paediatric Dentistry, Dammam Specialised Dental Center, Dammam, Eastern Province, Saudi Arabia, from 6(th) October 2021 to 8(th) March 2022, among 510 children. A well-structured questionnaire consisting of 24 closed-end items related to socio-demographic data, children's behavioural change during lockdown and oral health practices in the eastern province of Saudi Arabia was tailored. All parents or legal guardians of children aged between 6 and 12 years old were asked to sign a written informed permission to complete a questionnaire voluntarily. Statistical analysis was executed by using Statistical Package for Social Sciences version 22.0 (IBM Product, USA). Results: Of 510 children to be evaluated for the impact of the COVID-19 pandemic lockdown, 284 (55.7%) mothers, 209 (41%) fathers, and 17 (3.3%) caregivers were the respondents. Although one-half of the children 273 (53.5%) had no change in oral health attention, 72 (14.1%) had increased, while 165 (32.5%) had decreased oral health attention during the COVID-19 pandemic lockdown. There were three significant predictors of children's oral health behaviour during the COVID-19 pandemic lockdown including frequency of tooth brushing increased (OR=18.7), decreased brushing (OR=28.3), consumption of sugary meals (OR=4.6), and noticing of caries, toothache, bad breath, bleeding/swelling of the gingiva (OR=3.1). Conclusion: Study findings demonstrated that the COVID-19 pandemic caused considerable behavioural and psychological alterations in children. The frequency of brushing, dental visits, and sugar consumption all decreased significantly.

NLP-Based Subject with Emotions Joint Analytics for Epidemic Articles

For the last couple years, governments and health authorities worldwide have been focused on addressing the Covid-19 pandemic;for example, governments have implemented countermeasures, such as quarantining, pushing vaccine shots to minimize local spread, investigating and analyzing the virus??? characteristics, and conducting epidemiological investigations through patient management and tracers. Therefore, researchers worldwide require funding to achieve these goals. Furthermore, there is a need for documentation to investigate and trace disease characteristics. However, it is time consuming and resource intensive to work with documents comprising many types of unstructured data. Therefore, in this study, natural language processing technology is used to automatically classify these documents. Currently used statistical methods include data cleansing, query modification, sentiment analysis, and clustering. However, owing to limitations with respect to the data, it is necessary to understand how to perform data analysis suitable for medical documents. To solve this problem, this study proposes a robust in-depth mixed with subject and emotion model comprising three modules. The first is a subject and non-linear emotional module, which extracts topics from the data and supplements them with emotional figures. The second is a subject with singular value decomposition in the emotion model, which is a dimensional decomposition module that uses subject analysis and an emotion model. The third involves embedding with singular value decomposition using an emotion module, which is a dimensional decomposition method that uses emotion learning. The accuracy and other model measurements, such as the F1, area under the curve, and recall are evaluated based on an article on Middle East respiratory syndrome. A high F1 score of approximately 91% is achieved. The proposed joint analysis method is expected to provide a better synergistic effect in the dataset.

Ups and Downs of COVID-19: Can We Predict the Future? Local Analysis with Google Trends for Forecasting the Burden of COVID-19 in Pakistan

BACKGROUND: We aim to study the utility of Google Trends search history data for demonstrating if a correlation may exist between web-based information and actual coronavirus disease 2019 (COVID-19) cases, as well as if such data can be used to forecast patterns of disease spikes. PATIENTS & METHODS: Weekly data of COVID-19 cases in Pakistan was retrieved from online COVID-19 data banks for a period of 60 weeks. Search history related to COVID-19, coronavirus and the most common symptoms of disease was retrieved from Google Trends during the same period. Statistical analysis was performed to analyze the correlation between the two data sets. Search terms were adjusted for time-lag over weeks, to find the highest cross-correlation for each of the search terms. RESULTS: Search terms of 'fever' and 'cough' were the most commonly searched online, followed by coronavirus and COVID. The highest peak correlations with the weekly case series, with a 1-week backlog, was noted for loss of smell and loss of taste. The combined model yielded a modest performance for forecasting positive cases. The linear regression model revealed loss of smell (adjusted R(2) of 0.7) with significant 1-week, 2-week and 3-week lagged time series, as the best predictor of weekly positive case counts. CONCLUSIONS: Our local analysis of Pakistan-based data seemingly confirms that Google trends can be used as an important tool for anticipating and predicting pandemic patterns and pre-hand preparedness in such unprecedented pandemic crisis.

Procalcitonin as a predictor of severity and mortality in a cohort of patients hospitalised with COVID-19

INTRODUCTION: To evaluate the association of Procalcitonin (PCT) with severity in Coronavirus disease 2019 (COVID-19), hospitalised patients and to test the hypothesis that it is an independent predictor of mortality. MATERIALS AND METHODS: This study was conducted at Chemical Pathology, Department of Pathology and Laboratory Medicine and Department of Medicine, Aga Khan University (AKU), Karachi Pakistan. Electronic medical records of all in-patients including both genders and all age groups with documented COVID-19 from March to August 2020 were reviewed and recorded on a pre-structured performa. The subjects were divided into two categories severe and non-severe COVID-19;and survivors and non-survivors. Between-group differences were tested using the Chi-square and Mann-Whitney's U-test. The receiver operating characteristic curve was plotted for serum PCT with severity and mortality. A binary logistic regression was used to identify variables independently associated with mortality. The data was analysed using SPSS. RESULTS: 336 patients were reviewed as declared COVID-19 positive during the study duration, and 136 were included in the final analysis including 101 males and 35 females. A statistically significant difference in PCT was found between severe and non-severe COVID-19 (p value=0.01);and survivors and nonsurvivors (p value<0.0001). PCT, older age and increased duration of hospital stay were revealed as variables independently associated with mortality. On ROC analysis, an AUC of 0.76 for mortality prediction was generated for PCT. CONCLUSION: Baseline serum PCT concentration is a promising predictor of mortality and severity in COVID-19 cases when considered in combination with clinical details and other laboratory tests.

Robotic HPB surgery and impact of COVID-19 in a community hospital setting

Presenter: Imran Siddiqui MD ;Hartford Healthcare St.Vincent's Medical Center Background: Complex hepatopancreaticobiliary (HPB) surgery is associated with high morbidity even in high volume tertiary care centers. Minimally invasive robotic HPB surgeries including robotic whipple and major hepatectomies are resource intense. The COVID-19 pandemic has brought about new challenges in terms of resources and patient safety. We evaluate outcomes of patients undergoing Robotic HPB oncology surgery at high volume community center during COVID-19 pandemic Methods: All patients undergoing robotic HPB and foregut surgery for malignancies from March 2020 to January 2021 were included. Non-malignant indications were excluded. Mortality, morbidity, length of stay and oncologic outcomes were evaluated. Nosocomial COVID-19 infection and mortality and morbidity associated with it were evaluated separately Results: 33 patients were included out of which 22 of which were robotic and others included laparoscopy and hybrid approaches Surgeries included robotic whipple, robotic major hepatectomies, robotic gastrectomies, robotic duodenal resection, robotic biliary and gastric bypass surgery. Clavien III/IV morbidity was 6.5%. There was no post-operative respiratory failure or 30-day mortality. No patients were diagnosed with COVID 19 in the postoperative setting and none developed symptoms in the 30-day post-operative period. All patients were cared for in dedicated non COVID units and were discharged home or COVID free rehab centers. All patients who needed adjuvant treatment received it in a timely setting. Conclusion: Although COVID-19 pandemic has had a significant impact on the mortality and morbidity in the general setting and data has demonstrated worse outcomes for patients with COVID-19 in the post-operative period, we describe in this case series that with COVID safety protocols and preoperative testing, even complex and resource intense surgeries like robotic HPB surgeries can be performed safely in a community hospital setting with significant resource limitations.