COVID-19 Hospital Research Articles

Dynamic location model for designated COVID-19 hospitals in China.

In order to effectively cope with the situation caused by the COVID-19 pandemic, cases should be concentrated in designated medical institutions with full capability to deal with patients infected by this virus. We studied the location of such hospitals dividing the patients into two categories: ordinary and severe. Genetic algorithms were constructed to achieve a three-phase dynamic approach for the location of hospitals designated to receive and treat COVID-19 cases based on the goal of minimizing the cost of construction and operation isolation wards as well as the transportation costs involved. A dynamic location model was established with the decision variables of the corresponding 'chromosome' of the genetic algorithms designed so that this goal could be reached. In the static location model, 15 hospitals were required throughout the treatment cycle, whereas the dynamic location model found a requirement of only 11 hospitals. It further showed that hospital construction costs can be reduced by approximately 13.7% and operational costs by approximately 26.7%. A comparison of the genetic algorithm and the Gurobi optimizer gave the genetic algorithm several advantages, such as great convergence and high operational efficiency.

Neighbourhood immigrant density and COVID-19 infection and hospitalization among healthcare workers

Abstract Background Studies have shown inequalities in COVID-19 infection among healthcare workers (HCWs), with occupational exposure failing to fully explain the inequalities. Little is known about the role of other social determinants of health, such as neighborhood immigrant density. We examined if living in immigrant-dominated neighborhoods was associated with increased risk of COVID-19 infection and hospitalization among HCWs in Sweden, and if so, whether such exposure amplified the risk of COVID-19 among immigrant HCWs. Addressing this question would contribute to a better understanding of factors driving COVID-19 disparities among HCWs. Methods Data were from HCWs aged 20 to 62 years (N = 86187) resident in one of 14 Swedish municipalities (three of which are Sweden’s largest metropolitan cities) on 1 January 2020. Residential neighborhoods were categorised into Swedish-dominated, mixed, and immigrant-dominated. The study outcomes were the first occurrence of COVID-19 infection and hospitalization registered until 30 September 2022. Multilevel mixed-effects survival regression was used for the association analyses, with control for confounders (age, sex, income, comorbidities etc). Results After adjusting for confounders, living in immigrant-dominated neighborhoods was only associated with an increased risk of COVID-19 infection in the first pandemic wave (HR 1.17, 95%CI 1.07 - 1.29), but living in these areas was associated with an elevated risk of COVID-19 hospitalization throughout the entire period. Immigrant HCWs, regardless of where they lived, had around 2-fold higher risk of being hospitalised for COVID-19 than non-immigrant HCWs living in Swedish-dominated neighborhoods. Conclusions Neighborhood immigrant density was associated with COVID-19 hospitalization among HCWs in Sweden. However, immigrant HCWs had a high risk of the outcome regardless of where they lived. More research is needed to identify the root causes of the excess risk among immigrant HCWs. Key messages • HCWs living in immigrant-dominated neighborhoods had an elevated risk of COVID-19 hospitalization. • This study sheds additional light on the drivers of COVID-19 inequalities among Swedish HCWs.

SARS-CoV-2 Infection And COVID-19 Outcomes Among Mental Disorders: A Register-based Study in Catalonia

Abstract This study aimed to study the risk of SARS-CoV-2 infection and severe COVID-19 outcomes across different mental diagnoses and to assess the role of sex in these associations. We used electronic health records from Catalonia to identify adults receiving inpatient/outpatient mental health care between 2017-2019 with diagnosis of non-affective psychosis (NAP), bipolar disorder (BD), depressive disorder (DEP), stress-related disorders, neurotic/somatoform disorders (NSD), and substance misuse (SUB) (exposed). Outcomes included SARS-CoV-2 infection, COVID-19 hospitalization, and COVID-19-related death. Adjusted logistic regression analyses were conducted. 785,378 adults were included (70.3% < 65 years old; 57.1% women). Compared to unexposed, those with NAP [OR (95%CI): 0.84 (0.80-0.88)], BD [0.80 (0.75-0.86)], DEP [0.97 (0.94-1.00)] and SUB [0.81 (0.78-0.84)] had a lower risk of SARS-CoV-2 infection, while people with NSD presented an increased risk [1.03 (1.01-1.06)]. Among those infected, people with DEP, NSD, and SUB had a lower risk of COVID-19 hospitalization, but higher risk of COVID-19-related death [1.23 (1.07-1.41); 1.26 (1.07-1.48); 1.48 (1.24-1.71), respectively]. A higher COVID-19-related death was also found in people with NAP and BD [1.68 (1.34-2.12); 2.02 (1.50-2.73)]. Sex-stratified analysis showed that women with NSD were especially vulnerable to infection [1.07 (1.03-1.11)], and women with DEP and NSD to COVID-19-related death [1.24 (1.05-1.47); 1.26 (1.02-1.54)]. These results suggest different vulnerabilities to infection and COVID-19 hospitalization and death across mental disorders. These findings have implications for pandemic preparedness, highlighting the need for specific public health strategies to mitigate the excess of mortality of people with certain mental disorders.

Impact of primary course COVID-19 vaccination on hospitalizations in Belgium, a Bayesian approach

Abstract Background The Belgian COVID-19 primary course vaccine rollout was prioritized for individuals aged 18-64 years with underlying health conditions (increased risk of severe COVID-19), over their peers of the same age. This led to a 32-day earlier vaccination of prioritized individuals. In this research, we assessed the impact of vaccine rollout prioritization on hospitalizations for COVID-19 in Belgium between April 1st 2021 and June 30th 2021. Methods The sample consisted of the Belgian population aged 18-64 years. Individuals were classified by their priority status according to underlying health conditions and by vaccination status, creating weekly changing cohorts. The hospitalization probability was estimated by cohort using a national COVID-19 hospital surveillance. Two counterfactual scenarios were considered: (1) a no vaccination scenario and (2) a scenario in which the vaccine administration occurred at random in both cohorts (a vaccine rollout without prioritization). We used a Bayesian model to jointly estimate cohort-specific hospitalization probability and scenario outcomes. Results Out of the sample of 5,448,534 individuals, 22.65 % was prioritized. By May 1st, vaccination coverage was 18% and 2% within the prioritized and the non-prioritized cohort. In scenario 2, coverage within the prioritized was 6% by May 1st. There were 6968 hospitalizations reported through the hospital survey. Our initial scenario-outcomes indicated a reduction in hospitalizations of 3203 (95%CI[2548;3858]) and 919 (95%CI[406;1433]) by the vaccination prioritization, compared to scenarios 1 and 2, respectively. Conclusions This research provides insights in the impact of vaccination in a pandemic context in Belgium. We report a significant reduction in simulated COVID-19 hospitalization by vaccine prioritization compared to at random vaccination and no vaccination at all. Currently, we are investigating the effect of age-dependent vaccination next to at random vaccination. Key messages • The prioritised vaccination campaign in Belgium led to a significant reduction in hospitalizations. • Prioritisation based on underlying health conditions is an important public health measure.

Long-term cardiovascular events in individuals hospitalised with COVID-19: a retrospective cohort

Abstract Background The post-COVID condition involves a range of persistent or new symptoms affecting various organs, including an increased risk of cardiovascular issues. As there are limited data on cardiovascular events in post-acute COVID-19 patients, we aimed to estimate their incidence and assess its association with patient and infection characteristics in Portugal. Methods We conducted a registry-based retrospective cohort study from seven hospitals across Portugal, including individuals hospitalised due to COVID-19 between March 2020 and March 2021. Our outcome of interest was cardiovascular events in the post-acute phase of COVID-19, occurring at least 30 days after the positive SARS-CoV-2 test. The variables of interest considered were the severity of the episode, existing cardiovascular risk and vaccination status before the SARS-CoV-2 test. Person-years and incidence rates were estimated. A Cox proportional hazard regression model was employed to assess risk factors. Results We included 1,803 patients in the analysis, of which 143 (7.9%) experienced at least one cardiovascular event following COVID-19 hospitalisation. The overall incidence rate of having at least one cardiovascular event was 34.65 per 1,000 person-years (95% confidence interval (CI): 29.20; 40.82). We found a higher risk of cardiovascular events for individuals with pre-existing cardiovascular risk (adjusted hazard ratio (aHR): 3.76, 95% CI: 1.53; 9.24) and lower risk for individuals with at least one vaccine dose before the SARS-CoV-2 test (partial - aHR: 0.44, 95%CI: 0.30; 0.64, complete - aHR: 0.46, 95%CI: 0.2; 0.80). We did not find a significant difference between the severity of the COVID-19 episode and the risk of having cardiovascular events post-COVID-19. Conclusions Our results indicate the presence of cardiovascular complications post-COVID-19, emphasising the need for healthcare systems to initiate screening and preventive strategies for individuals deemed at elevated risk. Key messages • COVID-19 vaccination decreases the risk of cardiovascular events post-COVID-19. • Healthcare systems should start screening and preventive strategies for individuals with pre-existing risk of cardiovascular events.

Unraveling Social Health Inequalities during COVID-19 in Belgium: The Vital Role of Data Linkages

Abstract Background During the COVID-19 crisis, data linkages were set up to efficiently monitor the outbreak and identify vulnerable population groups. Yet, considerable technical, administrative and data security issues have hindered the effectiveness of data linkages as a critical instrument during public health emergencies. This workshop aims to provide a practical demonstration of the challenges encountered in a Belgian data linkage during the COVID-19 crisis, along with the strategies implemented to overcome these challenges. This case study offers insights into the development of a highly sensitive linkage between COVID-19 hospital data and information related to social and health use in Belgium. Methods The HELICON data linkage is developed at the individual level to investigate the risk of COVID-19 hospitalization and the influence of various social and biomedical factors during and after the crisis. Data are drawn from data collections on hospitalization from the COVID-19 health surveillance (Sciensano), on the socioeconomic and sociodemographic context (Statistics Belgium), and on healthcare use and reimbursement (InterMutualistic Agency). Results A representative case-cohort study is established comprising 1,149,264 million randomly selected Belgians and 44,508 hospitalized patients. Annual follow-up is scheduled over a four-year span, allowing the investigation of pre- and post-pandemic health data from July 2020 to January 2026. Conclusions The HELICON data linkage took 3.5 years to complete. Among the many challenges, we were faced with complicated approval procedures, ambiguous data security guidelines, unclear cost estimates, and technical issues related to the analysis environment. Building on these experiences, we explore the strengths and weaknesses of data linkages as a research instrument during the COVID-19 pandemic and discuss which lessons should be drawn to for the post-pandemic era.

Risk of long COVID and associated symptoms after acute SARS-COV-2 infection in ethnic minorities: a Danish nationwide cohort study

Abstract Background and aim Ethnic minorities living in high-income countries have been disproportionately affected by COVID-19 in terms of infection rates, hospitalisations, and deaths; however, less is known about long COVID in these populations. Our aim was to examine the risk of long COVID and associated symptoms among ethnic minorities. Methods We used Danish nationwide register-based cohort data on individuals diagnosed with COVID-19 aged ≥18 years (n = 2 334 271) between January 2020 and August 2022. We calculated the risk of long COVID diagnosis and long COVID symptoms among ethnic minorities compared with native Danes using multivariable Cox proportional hazard regression and logistic regression, respectively. Results Of the diagnosed COVID-19 cases, 1 973 998 (84.6%) were native Danes and 360 273 (15.4%) were ethnic minorities. After adjustment for age, sex, civil status, education, family income, and Charlson comorbidity index, ethnic minorities from North Africa (adjusted hazard ratio [aHR] 1.41, 95% CI [1.12,1.79]), Middle East (aHR 1.38, 95% CI [1.24,1.55]), Eastern Europe (aHR 1.35, 95% CI [1.22,1.49]), and Asia (aHR 1.23, 95% CI [1.09,1.40]), had significantly greater risk of long COVID diagnosis than native Danes. In the analysis by largest countries of origin, the greater risks of long COVID diagnosis were found in Iraqis (aHR 1.56, 95% CI [1.30,1.88]), Turks (aHR 1.42, 95% CI [1.24,1.63]), and Somalis (aHR 1.42, 95% CI [1.07,1.91]). A significant factor associated with an increased risk of long COVID diagnosis was COVID-19 hospitalisation. Conclusions Migrants and ethnic minorities had higher risk of long-COVID compared to native Danes.

Social health gradient and risk factors among patients hospitalized for COVID-19 and pre-pandemic respiratory infections. A linked national individual case-control study in Belgium

IntroductionThe literature establishes a clear social gradient in health for transmissible respiratory diseases. However, this gradient’s extent remains largely unexplored in the context of COVID-19, and it is uncertain whether the pandemic has exacerbated this gradient. The study aims to compare the socio-economic profiles and comorbidities during the COVID-19 pandemic with a control population affected by viral pneumonia/respiratory disease in 2019.MethodsThis case-control study analyzed linked data from all patients hospitalized for COVID-19 in 2020 (n = 22,087) and for respiratory diseases in 2019 (n = 7,586). Socio-economic data from the social security database were linked to clinical data from the hospital registry. We analyzed the socio-demographic and clinical factors associated with COVID-19 hospitalization (control group, wave 1, and wave 2) using multinomial regressions and logistic regression models and the length of stay during hospitalization using binomial negative regressions.ResultsA social health gradient was observed in both the COVID-19 and control groups, with a significant increase across waves for COVID-19 (p-trend < 0.0001). Men, people over the age of 45, those with comorbidities, high population density, lower income, lower socio-economic status, and people living in Brussels capital were at higher risk of COVID-19 hospitalization and longer length of stay compared to the control group. Except for sub-Saharan Africans, all patients of foreign nationality had a significantly increased risk of hospitalization (p < 0.001), but a shorter length of stay compared to Belgians.ConclusionThe socio-health gradient for COVID-19 followed the same pattern as that observed in pre-pandemic respiratory diseases, intensifying in the second wave and among the most deprived groups. This study emphasizes the importance of collecting social data alongside clinical data for a better understanding of social health inequalities and for tailoring health prevention policies.

Risk of long COVID in migrants and the contribution of vaccinations, disease severity, social inequalities and preexisting health: A nationwide register study in Sweden

Abstract Background and aim A number of studies have found higher COVID-19 infection rates, hospitalizations and deaths in migrants and ethnic minorities throughout the Corona Pandemic. Some recent evidence also suggests higher risk of long COVID in migrants although less is known about the risk factors for long COVID in this population. The objective of our study is to examine the risk of long COVID in migrants and to examine whether preexisting health conditions, disease severity, social inequalities and vaccinations contribute to the association. Methods We used linked Swedish administrative registers to estimate the risk of a long COVID diagnosis in the population that had a confirmed COVID-19 infection. Poisson regressions were used to calculate incidence rate ratios between the Swedish born and migrant groups. Adjustments for preexisting health conditions, disease severity, vaccinations and social inequalities were separately introduced. Results Higher risks of long COVID were found among migrants from Africa, Asia, Eastern Europe, Finland, Middle-East and South America. While the contribution of vaccinations and social inequalities were modest, we found that disease severity (i.e. whether the person was hospitalized or treated in an intensive care unit) primarily contributed to the higher risk of long COVID found in migrants. Conclusions The greater exposure and impact of the COVID-19 virus among migrants during the pandemic also affected the longer-term consequences of infection in this at-risk population.

Covid-19 and mental health hospitalizations in Italy. Results from a multicenter longitudinal cohort

Abstract Background The impact of Covid-19 pandemic on mental health (MH) is still being assessed. The aim of this study was to evaluate the impact of Covid-19 on ordinary hospital admissions for psychiatric disorders in Italy. Methods The multicenter project “Covid-19 and mental health” (CoMeH), coordinated by the National Institute for Health, Migration and Poverty, enrolled an open cohort of subjects resident in three large areas of Italy (2018-2021) aged 10 + (N = 5,159,363), and followed-up until 2021. The study outcome was the first ordinary admission with a psychiatric disorder as main diagnosis (FMHA). Citizenship and deprivation level (DL) are the socioeconomic factor considered. Different groups of diagnosis were used to characterize the hospitalizations. The impact of Covid-19 on FMHAs was evaluated by interrupted time series (ITS) analysis, pre (until February 2020) and post (from March 2020) the outbreak of pandemic, using a step-change model. Results 11,171 FMHAs were observed. Patients hospitalized with a MH diagnosis were younger compared to the study population; the distributions by sex, deprivation level and citizenship were similar. A decrease of incidence of FMHAs was found after the outbreak of the pandemic, overall and for all group of diagnoses, except for post-traumatic stress disorders (PTSD). A reduction in adjusted FMHA rates after the onset of Covid-19 (RR 0.80[0.72-0.90]) were observed through multivariate ITS. The oldest patients had the lowest probabilities of FMHAs in pre Covid-19 and experienced the highest reduction in post-Covid19. PTSD presented trend in countertendency compared with the other diagnosis, with an immediate effect of Covid-19 increasing FMHAs (+97%), followed by a post-outbreak return to the pre-pandemic levels, below the counterfactual line. Conclusions Covid-19 pandemic determined a general reduction of admissions for psychiatric disorders. A significant impact was observed among the eldest (decrease) and for PTSD (increase). Key messages • Covid-19 pandemic determined a reduction of admissions for psychiatric disorders. • Older people were mostly affected. No significant socioeconomic impact was observed.

Exploring the Psychosocial Impact of Hospitalization for COVID-19: Insights from Patient Experiences

Abstract Background The COVID-19 pandemic has severely tested the organizational structure and operational effectiveness of healthcare systems. We aimed to explore the experiences of patients who have been hospitalized due to COVID-19. Methods Employing purposive sampling, semi-structured interviews were conducted covering eight topics: 1) the experience of COVID-19 diagnosis, 2) the most difficult moments during hospitalization, 3) difficulties related to hospital conditions and safety protocols, 4) interactions with healthcare professionals, 5) received support, 6) social stigma, 7) concerns about the future, and 8) post-COVID and long COVID syndrome. Twelve individuals (six women and six men; mean age 57.5 (SD = 13) years; mean length of stay 18.1 (SD = 3.1) days) participated. The data analysis was carried out using the phenomenological method according to Colaizzi. Results Patients reported a spectrum of emotions including loneliness, isolation, abandonment, disappointment, insecurity and fear of death. Interactions with healthcare professionals revealed a dichotomy: experiences of respectful, reassuring care contrasted with encounters lacking psycho-emotional support within an impersonal healthcare setting. Conclusions This study sheds light on the experiences of patients on the nursing wards and their psychosocial burden. Most of them reported negative emotions such as loneliness, isolation, sadness, fear and anxiety rather than positive experiences such as hope, interpersonal connectedness, self-identity, empathy, caring and safety. Key messages • The study highlights psychosocial challenges for COVID-19 patients, emphasizing the urgent need for robust support systems. • The study provides insights for future similar situations and highlights the need for adaptable care models based on principles such as empathy, safety and personalized approaches.

Spatially varying associations between community-level predictors and COVID-19 outcomes in NYC

Abstract Background The cumulative impacts of COVID-19 on hospitalization and mortality were not uniformly distributed across New York City (NYC). To better understand potential drivers of this observed geospatial disparity, we explored the associations between community-level sociodemographic characteristics and cumulative COVID-19 hospitalizations and mortality using geographically weighted Poisson regression (GWPR). Methods Cumulative COVID-19 hospitalization and mortality rates in 177 NYC modified ZIP code tabulation areas as of Dec 2022 were taken from the NYC Department of Health and Mental Hygiene, and sociodemographic predictors were taken from the 2018 American Community Survey. GWPR was applied using both non-multiscale (single bandwidth) and multiscale (flexible bandwidth) models to assess which predictors were significant and which associations varied spatially (allowing them to potentially act as both risk and protective factors, depending on the location). Results Multiscale GWPR models outperformed non-multiscale models in rendering residual spatial autocorrelation insignificant. Although multiscale GWPR allowed flexible bandwidths for each predictor, most yielded global bandwidths, suggesting geographically consistent effects. For mortality, the percent of residents without health insurance acted solely as a risk factor. Similarly, for hospitalizations, the percent of residents with a disability acted solely as a risk factor. The percent of residents with a bachelors degree or higher acted solely as a protective factor against both outcomes. Conclusions Even when associations were allowed to vary spatially in GWPR models, we still found geographically consistent associations between many sociodemographic predictors and cumulative COVID-19 outcomes in NYC. Consistent risk factors, such as prevalence of disability, or protective factors, such as prevalence of higher education, highlight potential areas for city-wide policies to reduce the burden of future epidemics. Key messages • For cumulative COVID-19 outcomes across NYC communities, geographically consistent risk factors include disability prevalence for hospitalization and lack of health insurance for mortality. • Increasing prevalence of higher education acted as a geographically consistent protective factor against both hospitalization and mortality due to COVID-19.

Public Health Benefits of Applying Evidence-Based Best Practices in Managing Patients Hospitalized for COVID-19.

As COVID-19-related mortality remains a concern, optimal management of patients hospitalized for COVID-19 continues to evolve. We developed a population model based on real-world evidence to quantify the clinical impact of increased utilization of remdesivir, the effectiveness of which has been well established in hospitalized patients with COVID-19. The PINC AI healthcare database records for patients hospitalized for COVID-19 from January to December 2023 were stratified by those treated with or without remdesivir ("RDV" and "No RDV") and by supplemental oxygen requirements: no supplemental oxygen charges (NSOc), low-flow oxygen (LFO), and high-flow oxygen/non-invasive ventilation (HFO/NIV). Key vulnerable subgroups such as elderly and immunocompromised patients were also evaluated. The model applied previously published hazard ratios (HRs) to 28-day in-hospital mortality incidence to determine the number of potential lives saved if additional "No RDV" patients had been treated with remdesivir upon hospital admission. Of 84,810 hospitalizations for COVID-19 in 2023, 13,233 "No RDV" patients were similar in terms of characteristics and clinical presentation to the "RDV" patients. The model predicted that initiation of remdesivir in these patients could have saved 231 lives. Projected nationally, this translates to >800 potential lives saved (95% CI: 469-1,126). Eighty-nine percent of potential lives saved were elderly and 19% were immunocompromised individuals. Seventy-one percent were among NSOc or LFO patients. This public health model underscores the value of initiating remdesivir upon admission in patients hospitalized for COVID-19, in accordance with evidence-based best practices, to minimize lives lost due to SARS-CoV-2 infection.

Respiratory tract and bloodstream infections: microbiological profile in an intensive care unit for COVID-19

This is a retrospective cross-sectional study aimed at identifying the profile of lower respiratory tract (RTI) and bloodstream infections (BSI) in patients in the Intensive Care Unit (ICU) of a Reference Hospital for COVID-19 in Recife, Pernambuco. Data were collected on the age and sex of patients, material used in cultures, microorganisms detected, and resistance and sensitivity to the antimicrobials used. The most frequent species was Acinetobacter baumannii in RTI and Staphylococcus haemolyticus in BSI, being more resistant to levofloxacin and more sensitive to linezolid. Knowing the pathogens and their respective susceptibility patterns facilitates the choice of initial therapy, as well as the establishment of action protocols for health professionals and hospital infection control committees.

Factors associated with the effectiveness of high-flow therapy in patients with acute hypoxemic respiratory failure: An observational study

BackwardThe COVID-19 pandemic has severely tested global health systems. Non-invasive respiratory support, especially combining high-flow nasal cannula (HFNC) and continuous positive airway pressure, has effectively treated COVID-19 induced Acute Hypoxemic Respiratory Failure and reduced mortality. However, HFNC alone is more comfortable, better tolerated, and less costly than non-invasive ventilation. Understanding which patients benefit from HFNC monotherapy versus combined therapies is essential. MethodsThis observational study included patients admitted to the intermediate respiratory care unit of a COVID-19 hospital between December 2020 and September 2021. All patients treated with HFNC were included (n = 1301). HFNC failure was defined as the need for escalated therapy (non-invasive ventilation, intubation) or death. Epidemiological, clinical, non-invasive respiratory support parameters, and laboratory data were collected, and a multivariable analysis identified key determinants. ResultsHFNC was successful in 39.9 % of patients. (n = 511) Risk factors for HFNC failure included increased age, male gender, obesity, obstructive sleep apnea, higher respiratory rate, initial SpO2/FiO2 ≤ 148, and initial PaO2/FiO2 ≤ 100. An increase in the ROX Index at 24 h and slower disease progression were associated with successful treatment. These findings led to the developmet of an index to identify patients who benefit most from HFNC monotherapy. ConclusionsHFNC monotherapy can be effective for a specific profile of patients with Acute Hypoxemic Respiratory Failure due to COVID-19. This tool may help manage these patients more appropriately. Further studies are needed to determine if these findings can be applied to Acute Hypoxemic Respiratory Failure caused by other pathologies. Implications for Clinical PracticeThis study underscores the importance of early identification and management of patients at risk of HFNC failure in intermediate respiratory care units. By recognizing factors such as age, comorbidities, and respiratory indices, healthcare providers can implement targeted strategies to enhance HFNC success. These strategies may include more stringent monitoring, tailored respiratory support, and timely escalation to more intensive therapies if needed. Our findings highlight the need for a comprehensive approach to managing severe respiratory failure in critical care settings, ultimately improving patient outcomes and reducing the burden on healthcare systems.

Spatial and Ethno-national Health Inequalities: Health and Mortality Gaps between Palestinians and Jews in Israel.

This research adopts an analytical spatial perspective to explain ethno-national health inequality between Palestinians and Jews in Israel. The work identifies the forces that instigated and maintained the spatial segregation of Palestinians and elaborates the role of segregation in generating health gaps between Palestinians and Jews. The analysis suggests a novel conceptualization of two types of segregation: (a) exclusion from the center and confinement to the periphery and (b) segregation within the geographic periphery. Using administrative data on COVID-19 incidence, hospitalization, and death and various health indicators for localities, I devise a decomposition method that evaluates the relative contribution of each type of segregation to the total health gap. The findings indicate that the segregation of Palestinians from the center and their confinement to peripheral regions are crucial determinants of their poor health outcomes and that the segregation of the Palestinian community within the geographic periphery also contributes to poorer health.

COVID-19 in acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS): a propensity matched analysis (2020-2021)

BackgroundBy 2023, COVID-19 had caused 6.8 million deaths in the United States. COVID-19 presents more severely in leukemia compared to solid tumors (OR 1.6, p<0.05). However, data on Acute Myeloid Leukemia (AML) and Myelodysplastic Syndrome (MDS) are limited. We investigated the mortality in AML and MDS patients with COVID-19.MethodsData from the 2020-2021 National Inpatient Sample was used to conduct a cross-sectional analysis. We identified AML and MDS patients with COVID-19 hospitalizations through ICD-10 codes. Analysis was done by propensity matching and multivariate regression with a p-value of ≤0.05.ResultsOf 28,028 AML admissions, 336 (1.2%) were admitted for COVID-19. AML-COVID-19 cohort had a lower hospitalization risk (aOR 0.3, p=0.000) and higher mortality (21.7% vs 8.7%; aOR 1.6, p=0.023) than AML patients admitted for other causes. AML patients post-HSCT (Hematopoietic Stem Cell Transplantation) had a higher risk of COVID-19 (20.2% vs 9.8%; aOR 2.6, p=0.000) and increased mortality (19.1% vs 6.7%; aOR 4.1, p=0.000) compared to other causes. Similarly, of 28,148 MDS patients, 769 (2.7%) were admitted for COVID-19. The MDS-COVID-19 cohort had a lower hospitalization risk (aOR 0.59, p=0.000) and higher mortality (19.6% vs 6.6%; aOR 2.2, p=0.000) compared to other causes. In MDS, HSCT did not alter the risk of COVID-19 hospitalizations (3% vs 3.9%; aOR 0.9, p=0.662), but these patients had higher mortality (17.4% vs 5.1%; aOR 4.0, p=0.032).ConclusionCOVID-19 hospitalization was low in AML and MDS but carried a high mortality risk. Post-HSCT, the mortality is high, warranting research into understanding the underlying factors.

Impact of COVID-19 pandemic on the prevalence of metabolic syndrome in healthcare workers: a cohort study at a designated COVID-19 hospital in Taiwan.

This cohort study aimed to determine the effect of the COVID-19 pandemic on the prevalence of Metabolic syndrome (MetS) among healthcare workers at a dedicated COVID-19 hospital in Taiwan. This study recruited 397 healthcare workers who completed health checkups before and during the COVID-19 pandemic. The differences of MetS and its components prevalence before and during the COVID-19 pandemic were compared using the paired samples t-tests for normally distributed variables, and Wilcoxon signed-rank tests for non-normally distributed variables. The prevalence of MetS among healthcare workers significantly increased from 20.9% to 28.7% during the pandemic (p < .001). Central obesity and hypertension were the primary contributors to the development of MetS. COVID-19 pandemic was associated with an increasing prevalence of MetS in healthcare workers, necessitating health-promoting measures to mitigate this risk.

Systematic review and meta analysis of cross immunity and the smokers paradox in COVID19

COVID-19 pandemic, caused by the novel SARS-CoV-2 virus, has raised significant interest in understanding potential cross-immunity mechanisms. Recent evidence suggests that T-cells associated with common cold coronaviruses (229E, NL63, OC43, HKU1) may provide some level of cross-immunity against SARS-CoV-2. It is also known that the prevalence of smokers among patients admitted to hospital for COVID-19 is lower than expected according to the corresponding country’s smoking prevalence, which is known as smoker’s paradox in COVID-19. No clear consensus to explain it has yet been reached. This phenomenon suggests a complex interaction between smoking and immune response. Nonetheless, very few works have studied the prevalence of smokers in those infected by common cold coronaviruses, and its relation to COVID-19 has not been investigated. We performed a systematic review and meta-analysis to study the prevalence of smokers among patients infected by common cold coronaviruses, and to compare them to the corresponding country’s smoking prevalence. L’Abbé plots were used to visually assess the consistency of the observed effects across the different studies included in the meta-analysis. Additionally, significant differences were found in smoking prevalence among the various types of ccCoV, indicating the need for further research into the biological mechanisms driving these disparities. The results show that smoking prevalence is higher among those patients infected by these coronaviruses than in the general population (OR = 1.37, 95% CI: 0.81–2.33). A study was separately done for the four coronavirus types, and the prevalence of smokers was higher in three of the four than that corresponding to country, gender and study year: OC43 (OR = 1.93, 95% CI: 0.64–5.82); HKU1 (OR = 3.62, 95% CI: 1.21–10.85); NL63 (OR = 1.93, 95% CI: 0.64–5.82); 229E (OR = 0.97, 95% CI: 0.50–1.90). The heterogeneity of the studies was assessed using the Cochrane Chi-squared test, I-squared (I2), and Tau-squared (τ2). This detailed statistical analysis enhances the robustness of our findings and highlights the variations in smoking prevalence among different ccCoVs. Our data suggest that COVID-19 might be less prevalent among smokers due to greater cross-immunity from a larger number or more recent infections by common cold coronaviruses than the non-smoking population, which would explain smoker’s paradox in COVID-19. IMPLICATIONS. The low prevalence of current smokers among SARS-CoV-2 patients is a finding recurrently repeated, even leading to postulate the “smoker’s paradox” in COVID-19. This fact compelled us to study the prevalence of smokers among patients infected by common cold coronaviruses, and to compare them to the corresponding country’s smoking prevalence. Our data could explain smoker’s paradox in COVID-19 by a greater cross immunity due to a larger number, or more recent infections by common cold coronaviruses than the non-smoking population. This manuscript allow understand potential unrevealed mechanism for low prevalence of current smokers among SARS-CoV-2 patients.

Occupational burnout of health care workers in a specialised COVID hospital setting

The aim is to evaluate the peculiarities of the development of professional burnout (PB) among physicians of therapeutic and surgical specialties, as well as middle medical workers, specialised red zones, as well as its prediction and prevention in this category of workers. Material and methods. The following groups of medical workers were examined: the 1st group consisted of doctors of therapeutic specialities (GPs) working in the red zone (n=111); the 2nd group consisted of doctors of surgical specialities (MDs) working in the ‘red zone’ (n=61); the 3rd group consisted of nurses working in the red zone (n=29); the 4th group – the control group included workers of engineering, technical and economic specialities not related to work in medical organisations (n=190). Professional burnout syndrome was assessed using the Maslach Burnout questionnaire and V.V. Boyko’s technique of diagnosing the level of burnout [4, 5]. The data were processed using Statistica statistical package by StatSoft (USA). Results. It was found that the work of therapeutic and surgical doctors, as well as middle medical workers of specialised red zones, is connected with the exposure of medical workers to a number of specific risk factors related to the provision of medical care to infected patients, as well as with significant changes in the work regarding aspects related to organisation, safety, which contribute to the increase in the level of stress and the increase in the level of SP. Conclusions. The work of physicians of therapeutic and surgical specialities, as well as middle medical workers of specialised red zones, is associated with an increase in the level of professional stress and the level of SP. It is necessary to continue the research of emotional state of medical doctors and average medical workers working in conditions of extreme epidemic situations with the purpose of timely preventive treatment for preservation of health of medical workers.