Graph-Based Fusion of Imaging and Non-Imaging Data for Disease Trajectory Prediction

This study proposes a graph convolutional neural networks (GCN) architecture for fusion of radiological imaging and non-imaging tabular electronic health records (EHR) for the purpose of clinical event prediction. We focused on a cohort of hospitalized patients with positive RT-PCR test for COVID-19 and developed GCN based models to predict three dependent clinical events (discharge from hospital, admission into ICU, and mortality) using demographics, billing codes for procedures and diagnoses and chest X-rays. We hypothesized that the two-fold learning opportunity provided by the GCN is ideal for fusion of imaging information and tabular data as node and edge features, respectively. Our experiments indicate the validity of our hypothesis where GCN based predictive models outperform single modality and traditional fusion models. We compared the proposed models against two variations of imaging-based models, including DenseNet-121 architecture with learnable classification layers and Random Forest classifiers using disease severity score estimated by pre-trained convolutional neural network. GCN based model outperforms both imaging-only methods. We also validated our models on an external dataset where GCN showed valuable generalization capabilities. We noticed that edge-formation function can be adapted even after training the GCN model without limiting application scope of the model. Our models take advantage of this fact for generalization to external data. © 2023 IEEE.

COVID-19 vaccine acceptance and associated factors among people living with HIV in the Middle East and North Africa region

AJOL : Background: Identifying coronavirus disease 2019 (COVID-19) vaccine acceptance and associated factors among people living with HIV (PLHIV) in the Middle East and North Africa region is important to meet the need for broad-scale vaccination against COVID-19. Objectives: To investigate the COVID-19 vaccine acceptance rate and factors among PLHIV in the Middle East and North Africa region. Method: An online cross-sectional survey was conducted among PLHIV currently living in Egypt, Tunisia and Saudi Arabia between March 2021 and August 2021. Results: Of the 540 respondents, 19.3% reported already being vaccinated against COVID-19 (n = 104), 32.0% responded 'definitely yes' (n = 173), and 13.3% responded 'probably yes' (n = 72) for intention to receive a COVID-19 vaccine, with an overall COVID-19 vaccine acceptance rate of 64.6% among PLHIV in the region. The most significant predictors of COVID-19 vaccine acceptance included feeling less worried about COVID-19 transmission post- vaccination (221.0% higher odds), and believing the disease is vaccine-preventable (160.0% higher odds). Reported barriers to COVID-19 vaccine acceptance include concerns about vaccine effectiveness and belief that HIV medications protect against COVID-19 transmission, living in a rural area and reporting less-frequent engagement with HIV care. Nine out of 10 participants reported that the chances of them getting COVID-19 vaccine would increase if given adequate information and if their doctor recommended it. Conclusion: Findings of the study can help researchers, health officials, and other health system actors understand the predictors and barriers to COVID-19 vaccine acceptance reported by PLHIV. This understanding could inform the future planning of interventions tailored to PLHIV

Acceptance and Perceptions of COVID-19 Booster Dose;A Survey among Residents of Rawalpindi

Objective: To determine public acceptance of COVID-19 booster dose, to know about perceptions and possible barriers regarding the vaccine. Study Design: Analytical cross-sectional study. Place and Duration of Study: Conducted regarding the acceptance and perception of the vaccine booster dose among the residents of Rawalpindi Pakistan, from Jun till Aug 2022 Methodology: The sample size was 320 and collected using convenient sampling technique. The study included residents of Rawalpindi between ages 18 and 65. Google forms based on Health Belief Model were used for data collection. Data analysis was done using SPSS version 28 and summary statistics were produced using frequencies, percentages and mean. Chi-square test was also used to determine associations between categorical variables. Results: The results revealed that 74% of the participants' primary reason for getting booster dose was their own safety while major barrier to booster dose vaccination was side effects related to vaccine-62%. 81.3% people were willing to get the booster dose and 87.9% people agreed to receive booster dose for free. Chi-square test indicated a significant association between acceptance and perceived susceptibility, benefits and severity. Conclusion: In conclusion, our findings reveal that majority of people were willing to get booster dose primarily for own safety. However, counselling is required to decrease the perceived barriers to vaccination regarding side effects of the vaccine. © 2022, Army Medical College. All rights reserved.

Neutralising antibody titers and COVID outcomes in cancer patients

Background: Cancer patients are at high risk of severe COVID infection and recommended at least three doses of SARS-CoV2 mRNA vaccines. Various anti-neoplastic treatments may affect long-term vaccine immunogenicity. Methods: Patients with solid or haematological cancer were recruited from two Singapore hospitals between July 2021 and March 2022. GenScript cPASS surrogate virus neutralisation assays measured antibody responses, which were correlated with clinical outcomes obtained from medical records and national mandatory-reporting databases. Results: In total, 273 patients were recruited (40 with haematological malignancies and the rest solid tumours). Two-hundred and four patients (74.7%) were receiving active cancer therapy: 98 (35.9%) receiving systemic chemotherapy and the rest targeted or immunotherapy. All patients were seronegative at baseline. After receiving one, two and three doses of SARS-CoV-2-mRNA vaccination, seroconversion rate was 35.2%, 79.4% and 92.4% respectively. After three doses, patients on active treatment for haematological malignancies had lower antibodies (57.3%±46.2) as compared to patients on immunotherapy (94.1%±9.56, p<0.05) and chemotherapy (92.8%±18.1, p<0.05). SARS-CoV-2 infection was reported in 77 (28.2%) patients of which 18 were severe. Conclusion: This study demonstrates high immunogenicity of three doses of vaccines and protection against severe infection in cancer patients.

Evolution of Clinical Phenotypes of COVID-19 Patients During Intensive Care Treatment: An Unsupervised Machine Learning Analysis.

BACKGROUND: Identification of clinical phenotypes in critically ill COVID-19 patients could improve understanding of the disease heterogeneity and enable prognostic and predictive enrichment. However, previous attempts did not take into account temporal dynamics with high granularity. By including the dimension of time, we aim to gain further insights into the heterogeneity of COVID-19. METHODS: We used granular data from 3202 adult COVID patients in the Dutch Data Warehouse that were admitted to one of 25 Dutch ICUs between February 2020 and March 2021. Parameters including demographics, clinical observations, medications, laboratory values, vital signs, and data from life support devices were selected. Twenty-one datasets were created that each covered 24 h of ICU data for each day of ICU treatment. Clinical phenotypes in each dataset were identified by performing cluster analyses. Both evolution of the clinical phenotypes over time and patient allocation to these clusters over time were tracked. RESULTS: The final patient cohort consisted of 2438 COVID-19 patients with a ICU mortality outcome. Forty-one parameters were chosen for cluster analysis. On admission, both a mild and a severe clinical phenotype were found. After day 4, the severe phenotype split into an intermediate and a severe phenotype for 11 consecutive days. Heterogeneity between phenotypes appears to be driven by inflammation and dead space ventilation. During the 21-day period, only 8.2% and 4.6% of patients in the initial mild and severe clusters remained assigned to the same phenotype respectively. The clinical phenotype half-life was between 5 and 6 days for the mild and severe phenotypes, and about 3 days for the medium severe phenotype. CONCLUSIONS: Patients typically do not remain in the same cluster throughout intensive care treatment. This may have important implications for prognostic or predictive enrichment. Prominent dissimilarities between clinical phenotypes are predominantly driven by inflammation and dead space ventilation.

Preparedness of Primary Care Centers for COVID-19 epidemic in Aseer region, KSA.

Objective: The objective of this study is to assesses the preparedness of primary care centers (PHCs) in Aseer region, KSA, for the coronavirus disease 2019 (COVID-19) pandemic. Methods: This survey was conducted during April 2020 in PHCs. The questionnaire was developed by the investigators and sent via e-mail to health care providers of primary health care centers (PHCCs). The questionnaire consisted of five parts to assesses readiness of PHCs, knowledge, attitude, and practice of health care providers (HCPs) concerning the COVID-19 pandemic. Data entry and analysis were managed by SPSS version 20. Results: Three hundred and seventy-one HCPs participated in this study. Most of them were males (58%), doctors or nurses (81%). Almost all PHCCs have adequate infection control resources, with some shortage in sterilization rooms. Most of participants received on-job training (85%) and had good knowledge about COVID-19. Attitudes of participants showed variation toward COVID-19; 74% were afraid to be infected, 54% were afraid to care for infected patients, 58% were ready for vaccination, and 80% thought that COVID-19 has a huge negative impact on the health care system. Compliance with preventive measures ranged from 66% for keeping social distance to 90% for using personal protective equipment. Most of the participants had positive contributions regarding health education of individuals and communities using different methods including the new social media (80%). Conclusion: This study revealed that PHCCs in Aseer region were well equipped and HCPs were well prepared to deal with the COVID-19 pandemic. There are some shortage in a few items of infection control at PHCCs and gaps in knowledge and practice among HCPs which need continuous assessment and monitoring to overcome such barriers.

INCIDENCE, RISK FACTORS, AND OUTCOME OF SUSPECTED CENTRAL VENOUS CATHETER-RELATED INFECTIONS IN CRITICALLY ILL COVID-19 PATIENTS: A MULTICENTER RETROSPECTIVE COHORT STUDY.

ABSTRACT: Background: Aims of this study were to investigate the prevalence and incidence of catheter-related infection, identify risk factors, and determine the relation of catheter-related infection with mortality in critically ill COVID-19 patients. Methods: This was a retrospective cohort study of central venous catheters (CVCs) in critically ill COVID-19 patients. Eligible CVC insertions required an indwelling time of at least 48 hours and were identified using a full-admission electronic health record database. Risk factors were identified using logistic regression. Differences in survival rates at day 28 of follow-up were assessed using a log-rank test and proportional hazard model. Results: In 538 patients, a total of 914 CVCs were included. Prevalence and incidence of suspected catheter-related infection were 7.9% and 9.4 infections per 1,000 catheter indwelling days, respectively. Prone ventilation for more than 5 days was associated with increased risk of suspected catheter-related infection; odds ratio, 5.05 (95% confidence interval 2.12-11.0). Risk of death was significantly higher in patients with suspected catheter-related infection (hazard ratio, 1.78; 95% confidence interval, 1.25-2.53). Conclusions: This study shows that in critically ill patients with COVID-19, prevalence and incidence of suspected catheter-related infection are high, prone ventilation is a risk factor, and mortality is higher in case of catheter-related infection.

Tele-Dentistry during Covid-19 Pandemic, Perceptions of Dentists in Pakistan

Objective: The aim of this study is to analyze the perception of Dentists in Pakistan towards Tele-Dentistry and its usefulness during Covid-19 pandemic. Material(s) and Method(s): The study was conducted among general dentists of Lahore after taking approval from the Ethics and Research Committee of the institution. This descriptive cross-sectional study was completed over the period of three months. Non-probability snowball sampling technique was used. Result(s): The results revealed that most of the dentists (89.5%) perceived that Tele-Dentistry can be of help during COVID 19 Pandemic in Pakistan. Conclusion(s): Most of the dentists were aware of teledentistry, and its uses, advantages and disadvantages in Covid-19 pandemic. Copyright © 2022 Lahore Medical And Dental College. All rights reserved.

COVID-19 vaccine acceptance and associated factors among people living with HIV in the Middle East and North Africa region.

Background: Identifying coronavirus disease 2019 (COVID-19) vaccine acceptance and associated factors among people living with HIV (PLHIV) in the Middle East and North Africa region is important to meet the need for broad-scale vaccination against COVID-19. Objectives: To investigate the COVID-19 vaccine acceptance rate and factors among PLHIV in the Middle East and North Africa region. Method: An online cross-sectional survey was conducted among PLHIV currently living in Egypt, Tunisia and Saudi Arabia between March 2021 and August 2021. Results: Of the 540 respondents, 19.3% reported already being vaccinated against COVID-19 (n = 104), 32.0% responded 'definitely yes' (n = 173), and 13.3% responded 'probably yes' (n = 72) for intention to receive a COVID-19 vaccine, with an overall COVID-19 vaccine acceptance rate of 64.6% among PLHIV in the region. The most significant predictors of COVID-19 vaccine acceptance included feeling less worried about COVID-19 transmission post-vaccination (221.0% higher odds), and believing the disease is vaccine-preventable (160.0% higher odds). Reported barriers to COVID-19 vaccine acceptance include concerns about vaccine effectiveness and belief that HIV medications protect against COVID-19 transmission, living in a rural area and reporting less-frequent engagement with HIV care. Nine out of 10 participants reported that the chances of them getting COVID-19 vaccine would increase if given adequate information and if their doctor recommended it. Conclusion: Findings of the study can help researchers, health officials, and other health system actors understand the predictors and barriers to COVID-19 vaccine acceptance reported by PLHIV. This understanding could inform the future planning of interventions tailored to PLHIV.

Predicting responders to prone positioning in mechanically ventilated patients with COVID-19 using machine learning.

BACKGROUND: For mechanically ventilated critically ill COVID-19 patients, prone positioning has quickly become an important treatment strategy, however, prone positioning is labor intensive and comes with potential adverse effects. Therefore, identifying which critically ill intubated COVID-19 patients will benefit may help allocate labor resources. METHODS: From the multi-center Dutch Data Warehouse of COVID-19 ICU patients from 25 hospitals, we selected all 3619 episodes of prone positioning in 1142 invasively mechanically ventilated patients. We excluded episodes longer than 24 h. Berlin ARDS criteria were not formally documented. We used supervised machine learning algorithms Logistic Regression, Random Forest, Naive Bayes, K-Nearest Neighbors, Support Vector Machine and Extreme Gradient Boosting on readily available and clinically relevant features to predict success of prone positioning after 4 h (window of 1 to 7 h) based on various possible outcomes. These outcomes were defined as improvements of at least 10% in PaO2/FiO2 ratio, ventilatory ratio, respiratory system compliance, or mechanical power. Separate models were created for each of these outcomes. Re-supination within 4 h after pronation was labeled as failure. We also developed models using a 20 mmHg improvement cut-off for PaO2/FiO2 ratio and using a combined outcome parameter. For all models, we evaluated feature importance expressed as contribution to predictive performance based on their relative ranking. RESULTS: The median duration of prone episodes was 17 h (11-20, median and IQR, N = 2632). Despite extensive modeling using a plethora of machine learning techniques and a large number of potentially clinically relevant features, discrimination between responders and non-responders remained poor with an area under the receiver operator characteristic curve of 0.62 for PaO2/FiO2 ratio using Logistic Regression, Random Forest and XGBoost. Feature importance was inconsistent between models for different outcomes. Notably, not even being a previous responder to prone positioning, or PEEP-levels before prone positioning, provided any meaningful contribution to predicting a successful next proning episode. CONCLUSIONS: In mechanically ventilated COVID-19 patients, predicting the success of prone positioning using clinically relevant and readily available parameters from electronic health records is currently not feasible. Given the current evidence base, a liberal approach to proning in all patients with severe COVID-19 ARDS is therefore justified and in particular regardless of previous results of proning.

Assess and validate predictive performance of models for in-hospital mortality in COVID-19 patients: A retrospective cohort study in the Netherlands comparing the value of registry data with high-granular electronic health records.

PURPOSE: To assess, validate and compare the predictive performance of models for in-hospital mortality of COVID-19 patients admitted to the intensive care unit (ICU) over two different waves of infections. Our models were built with high-granular Electronic Health Records (EHR) data versus less-granular registry data. METHODS: Observational study of all COVID-19 patients admitted to 19 Dutch ICUs participating in both the national quality registry National Intensive Care Evaluation (NICE) and the EHR-based Dutch Data Warehouse (hereafter EHR). Multiple models were developed on data from the first 24 h of ICU admissions from February to June 2020 (first COVID-19 wave) and validated on prospective patients admitted to the same ICUs between July and December 2020 (second COVID-19 wave). We assessed model discrimination, calibration, and the degree of relatedness between development and validation population. Coefficients were used to identify relevant risk factors. RESULTS: A total of 1533 patients from the EHR and 1563 from the registry were included. With high granular EHR data, the average AUROC was 0.69 (standard deviation of 0.05) for the internal validation, and the AUROC was 0.75 for the temporal validation. The registry model achieved an average AUROC of 0.76 (standard deviation of 0.05) in the internal validation and 0.77 in the temporal validation. In the EHR data, age, and respiratory-system related variables were the most important risk factors identified. In the NICE registry data, age and chronic respiratory insufficiency were the most important risk factors. CONCLUSION: In our study, prognostic models built on less-granular but readily-available registry data had similar performance to models built on high-granular EHR data and showed similar transportability to a prospective COVID-19 population. Future research is needed to verify whether this finding can be confirmed for upcoming waves.

Cheese Intake Exhibits an Alteration of Glycolipid Profile and Impacts on Non-Alcoholic Fatty Liver in Bahraini Older Adults.

Background: Metabolic syndrome (MetS) is a multifactorial condition characterized by a complex interrelation between genetic and environmental factors that heighten the risk of cardiovascular diseases and all-cause mortality. It is hypothesized that diet may play an important role in the regulation of metabolic syndrome factors and influence the process. Therefore, the main objective of this study was to investigate the specific dietary patterns associated with metabolic syndrome markers and quantify the possible effects of dietary patterns among Bahrain older adults. Methods: This is a cross-sectional study that included 151 Bahraini patients diagnosed with MetS, 89 (58.7%) were females and 62 (41.3%) males. Results: The prevalence of Non-Alcoholic Fatty Liver was 89%. Statistically significant correlations were found between dairy products with low fat and SBP (r = 0.182, p < 0.001) body mass index (BMI) (r = -0.195; p < -0.01). Higher chicken consumption was associated with reduction of BMI (r = -0.273; p < -0.01). A higher consumption of ricotta and cheddar cheese (high in fat) was associated with higher levels of triglycerides (p < 0.01). Higher frequent consumption of rice (basmati) was associated with lower glucose levels (r = -0.200; p < -0.01). Fatty liver has been associated with high consumption of cream cheese (p < 0.01). Conclusion: In older Bahraini adults with metabolic syndrome, higher frequency of food consumption of full-fat cheese was linked with a derangement of lipid profile and Non-Alcoholic Fatty Liver. Positive effects on BMI have been recorded with higher-frequency consumption of basmati rice and chicken.

COVID-19 vaccine acceptance and associated factors among people living with HIV in the Middle East and North Africa region

Background Identifying coronavirus disease 2019 (COVID-19) vaccine acceptance and associated factors among people living with HIV (PLHIV) in the Middle East and North Africa region is important to meet the need for broad-scale vaccination against COVID-19. Objectives To investigate the COVID-19 vaccine acceptance rate and factors among PLHIV in the Middle East and North Africa region. Method An online cross-sectional survey was conducted among PLHIV currently living in Egypt, Tunisia and Saudi Arabia between March 2021 and August 2021. Results Of the 540 respondents, 19.3% reported already being vaccinated against COVID-19 (n = 104), 32.0% responded ‘definitely yes’ (n = 173), and 13.3% responded ‘probably yes’ (n = 72) for intention to receive a COVID-19 vaccine, with an overall COVID-19 vaccine acceptance rate of 64.6% among PLHIV in the region. The most significant predictors of COVID-19 vaccine acceptance included feeling less worried about COVID-19 transmission post-vaccination (221.0% higher odds), and believing the disease is vaccine-preventable (160.0% higher odds). Reported barriers to COVID-19 vaccine acceptance include concerns about vaccine effectiveness and belief that HIV medications protect against COVID-19 transmission, living in a rural area and reporting less-frequent engagement with HIV care. Nine out of 10 participants reported that the chances of them getting COVID-19 vaccine would increase if given adequate information and if their doctor recommended it. Conclusion Findings of the study can help researchers, health officials, and other health system actors understand the predictors and barriers to COVID-19 vaccine acceptance reported by PLHIV. This understanding could inform the future planning of interventions tailored to PLHIV.

The Impact of COVID-19 on Physical (In)Activity Behavior in 10 Arab Countries.

Insufficient physical activity is considered a strong risk factor associated with non-communicable diseases. This study aimed to assess the impact of COVID-19 on physical (in)activity behavior in 10 Arab countries before and during the lockdown. A cross-sectional study using a validated online survey was launched originally in 38 different countries. The Eastern Mediterranean regional data related to the 10 Arabic countries that participated in the survey were selected for analysis in this study. A total of 12,433 participants were included in this analysis. The mean age of the participants was 30.3 (SD, 11.7) years. Descriptive and regression analyses were conducted to examine the associations between physical activity levels and the participants' sociodemographic characteristics, watching TV, screen time, and computer usage. Physical activity levels decreased significantly during the lockdown. Participants' country of origin, gender, and education were associated with physical activity before and during the lockdown (p < 0.050). Older age, watching TV, and using computers had a negative effect on physical activity before and during the lockdown (p < 0.050). Strategies to improve physical activity and minimize sedentary behavior should be implemented, as well as to reduce unhealthy levels of inactive time, especially during times of crisis. Further research on the influence of a lack of physical activity on overall health status, as well as on the COVID-19 disease effect is recommended.

Too Real or Just Real Enough? Service Adaptation and Authenticity Perception in Cross-Cultural Service Encounters: An Abstract

With limited travel in a post COVID-19 world, consumers seek cultural experiences closer to home. Services like ethnic dining provide consumers the opportunity to immerse in a culturally authentic experience not a part of their daily lives (Southworth 2018;Yu et al. 2020). However, to date, research has not determined how authentic is authentic enough or if customer need some adaptation of the service encounter to their own culture for full satisfaction. On the one hand, prior research suggest that cross-cultural service encounter adaptation is associated with positive customer outcomes such as rapport, satisfaction, and WOM (Azab and Clark 2017). On the other hand, cultural authenticity is suggested to be a driver of successful service encounters (Wang and Mattila 2015), increasing customers’ satisfaction and loyalty (Park et al. 2019). Thus, adaptation and authenticity present conflicting forces in optimizing the cross-cultural service experience and satisfying customers’ demand to immerse in a foreign culture. Further complicating the situation, there is a lack of generalization across different customer groups. In this study, the authors explore the following research questions;(1) Could higher service adaptation lead to lower satisfaction if it is perceived to take away from cultural authenticity? Does too much authenticity lead to discomfort, reducing positive customer outcomes? Is there an optimum level of authenticity-adaptation? (2) Do the same assumptions hold across different generations? Is seeking authentic or more adapted cultural service experiences a generational phenomenon? (3) What role do cultural competences play - can customer cultural competences bridge the perceived authenticity – customer experience gap? The authors explore these research questions using scenario-based experiments set in the context of an Indian restaurant. Results show that too much authenticity may hinder the optimum service experience (Study 1). While younger customers prefer moderate adaptation/ authenticity (rather than low adaptation), older generation seems more adventurous and perceives a better experience (satisfaction, WoM, repatronage) when there is low to no adaptation (full authenticity) (Study 1 and 2). We find that positive outcomes are significantly higher for older generations when adaptation is low (Study 2). The effect of cultural competences is yet to be determined (Study 3). This study contributes to the literature by revealing that high levels of perceived authenticity do not always ensure positive outcomes, and that outcomes associated with perceived authenticity vary across generations. Managerially, the study helps organizations tailor the optimal level of authenticity by adjusting the level of adaptation of the offering to suit particular clientele. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Revisiting Middle East Respiratory Coronavirus (MERS-CoV) Outbreak Chest Radiographic Initial Findings, Temporal Progression, and Correlation to Outcomes: A Multicenter Study.

Objectives Accounts of initial and follow-up chest X-rays (CXRs) of the Middle East respiratory coronavirus (MERS-CoV) patients, and correlation with outcomes, are sparse. We retrospectively evaluated MERS-CoV CXRs initial findings, temporal progression, and outcomes correlation. Materials and methods Fifty-three real-time reverse-transcriptase-polymerase chain reaction (rRT-PCR)-confirmed MERS-CoV patients with CXRs were retrospectively identified from November 2013 to October 2014. Initial and follow-up CXR imaging findings and distribution were evaluated over 75 days. Findings were correlated with outcomes. Results Twenty-two of 53 (42%) initial CXRs were normal. In 31 (68%) abnormal initial CXRs, 15 (48%) showed bilateral non-diffuse involvement, 16 (52%) had ground-glass opacities (GGO), and 13 (42%) had peripheral distribution. On follow-up CXRs, mixed airspace opacities prevailed, seen in 16 (73%) of 22 patients 21-30 days after the initial CXRs. Bilateral non-diffuse involvement was the commonest finding throughout follow-up, affecting 16 (59%) of 27 patients 11-20 days after the initial CXRs. Bilateral diffuse involvement was seen in five (63%) of eight patients 31-40 days after the initial CXRs. A bilateral diffuse CXR pattern had an odds ratio for mortality of 13 (95% CI=2-78) on worst and 18 (95% CI=3-119) on final CXRs (P-value <0.05). Conclusion Initially, normal CXRs are common in MERS-CoV patients. Peripherally located ground-glass and mixed opacities are common on initial and follow-up imaging. The risk of mortality is higher when bilateral diffuse radiographic abnormalities are detected.

Effect of COVID-19 Pandemic on Neonatal Sepsis.

BACKGROUND: There is a sudden rise in infectious diseases, with special concern to the most recent SARS-CoV 2 outbreak. A retrospective study was conducted to study the effect of this outbreak on neonatal sepsis as a global issue that poses a challenge for pediatric management and to identify its risk factors, microbial profile, and mortality rate at King Faisal Medical Complex, Taif, KSA, a COVID-19-tertiary care segregation hospital. METHODS: This research included 111 neonates with a culture-proven diagnosis of neonatal sepsis (4 and 62 cases during 2019 and 2020, respectively). RESULTS: During 2019 early onset sepsis (EOS) occurred in 6/49 (12.2%) while in 2020 22/62 (35.5%), and during 2019 late onset sepsis (LOS) occurred in 43/49 (87.7%) while in 2020 40/62 (64.5%). Premature rupture of membrane was the major neonatal risk factor for EOS during 2019 and 2020 with proportions of 4 (66.7%), 20 (90.9%); respectively. As regards LOS, the peripherally inserted central catheters and peripheral lines were the top neonatal risk factors. In the two-year outbreak, the most prevalent causative organism for EOS neonates was Escherichia coli and for LOS neonates it was Klebsiella. There was non-significant change in the mortality rate of neonatal sepsis between 2019 and 2020. However, the mortality rate was higher in EOS 9/22 (40.9%) in 2020 in comparison to 2/6 (33.3%) in 2019. CONCLUSIONS: Neonatal sepsis remains a major health problem causing serious morbidity and mortality, and health care policy makers have to implement EOS preventive measures.

Sub-epidemic Model Forecasts During the First Wave of the COVID-19 Pandemic in the USA and European Hotspots

Mathematical models have been widely used to understand the dynamics of the ongoing coronavirus disease 2019 (COVID-19) pandemic as well as to predict future trends and assess intervention strategies. The asynchronicity of infection patterns during this pandemic illustrates the need for models that can capture dynamics beyond a single-peak trajectory to forecast the worldwide spread and for the spread within nations and within other sub-regions at various geographic scales. Here, we demonstrate a five-parameter sub-epidemic wave modeling framework that provides a simple characterization of unfolding trajectories of COVID-19 epidemics that are progressing across the world at different spatial scales. We calibrate the model to daily reported COVID-19 incidence data to generate six sequential weekly forecasts for five European countries and five hotspot states within the United States. The sub-epidemic approach captures the rise to an initial peak followed by a wide range of post-peak behavior, ranging from a typical decline to a steady incidence level to repeated small waves for sub-epidemic outbreaks. We show that the sub-epidemic model outperforms a three-parameter Richards model, in terms of calibration and forecasting performance, and yields excellent short- and intermediate-term forecasts that are not attainable with other single-peak transmission models of similar complexity. Overall, this approach predicts that a relaxation of social distancing measures would result in continuing sub-epidemics and ongoing endemic transmission. We illustrate how this view of the epidemic could help data scientists and policymakers better understand and predict the underlying transmission dynamics of COVID-19, as early detection of potential sub-epidemics can inform model-based decisions for tighter distancing controls. © 2022, Springer Nature Switzerland AG.

Impact Of Covid-19 On Post Natal Mental Health

BACKGROUND: In January, 2020 COVID-19 infection was declared a public health emergency characterized as pandemic by the World Health Organization (WHO). In March 2020, special guidelines were issued to address mental and psychological aspects of the disease survivors and community at large. This study was conducted with the aim to evaluate the psychological impact of COVID-19 on mothers in the postpartum period. METHODS: It was cross-sectional study of six months duration on COVID-19 positive deliveries and Covid negative mothers. A total of 84 women (42 Covid Positive and 42 Covid negative) were included through non-probability quota with consecutive sampling technique. Mothers with pre-existing mental health issues, those who had been on medication for any psychological issues or those who suffered from obstetrical and neonatal complications or required transfer to High Dependency Unit (HDU) were excluded from the study. The Edinburgh Postnatal Depression Scale (EPDS) was used to screen the women for postpartum depression. Independent sample t test was used for continuous variables and Fisher exact test was used for qualitative variables. RESULTS: Mean EPDS score was 9.48+/-6.33 in COVID-19 positive group. The sub-scale analysis showed mean scores 1.6+/-1.76 and 4.86+/-2.94 for Anhedonia and Anxiety with statistically significant difference. CONCLUSIONS: Women experiencing COVID-19 infection during pregnancy were found to have greater anxiety and nervousness in post-natal period compared to their COVID-19 negative counterparts.

Evolution of Clinical Phenotypes of COVID-19 Patients During Intensive Care Treatment: An Unsupervised Machine Learning Analysis (preprint)

Background: Identification of distinct clinical phenotypes in critically ill COVID-19 patients could improve understanding of the disease heterogeneity and enable prognostic and predictive enrichment facilitating more personalized treatment. However, previous attempts did not take into account temporal dynamics of the disease. By including the dimension of time, we aim to gain further insights into the heterogeneity of COVID-19.Methods: We used highly granular data from 3202 adult critically ill COVID patients in the multicenter Dutch Data Warehouse that were admitted to one of 25 Dutch ICUs between February 2020 and March 2021. Parameters including demographics, clinical observations, medications, laboratory values, vital signs, and data from life support devices were selected based on relevance and availability. Twenty-one consecutive datasets were created that each covered 24 hours of ICU data for each day of ICU treatment up until day 21. After aggregation and multiple imputation of the temporal data, clinical phenotypes in each dataset were identified by performing multiple cluster analyses. Clinical phenotypes were identified by aggregating values from all patients per cluster. Both evolution of the clinical phenotypes over time and patient allocation to these clusters over time were tracked.Results: The final patient cohort consisted of 2438 critically ill COVID-19 patients with a registered ICU mortality outcome. Forty-one parameters were chosen for the cluster analysis. On admission, both a mild and a more severe clinical phenotype were found. After day 4, the severe phenotype split into an intermediate and a severe phenotype for 11 consecutive days. Heterogeneity between phenotypes appears to be strongly driven by inflammation and dead space ventilation. During the 21-day period only 8.2% and 4.6% of patients in the initial mild and severe clusters remained assigned to the same phenotype respectively. The clinical phenotype half-life was between 5 and 6 days for the mild and severe phenotypes, and about 3 days for the medium severe phenotype.Conclusions: Patients typically do not remain in the same cluster throughout intensive care treatment. This may have important implications for prognostic or predictive enrichment. Prominent dissimilarities between clinical phenotypes are predominantly driven by inflammation and dead space ventilation.