Chronic diseases associated with increased likelihood of hospitalization and mortality in 68,913 COVID-19 confirmed cases in Spain: A population-based cohort study.

BACKGROUND: Clinical outcomes among COVID-19 patients vary greatly with age and underlying comorbidities. We aimed to determine the demographic and clinical factors, particularly baseline chronic conditions, associated with an increased risk of severity in COVID-19 patients from a population-based perspective and using data from electronic health records (EHR). METHODS: Retrospective, observational study in an open cohort analyzing all 68,913 individuals (mean age 44.4 years, 53.2% women) with SARS-CoV-2 infection between 15 June and 19 December 2020 using exhaustive electronic health registries. Patients were followed for 30 days from inclusion or until the date of death within that period. We performed multivariate logistic regression to analyze the association between each chronic disease and severe infection, based on hospitalization and all-cause mortality. RESULTS: 5885 (8.5%) individuals showed severe infection and old age was the most influencing factor. Congestive heart failure (odds ratio -OR- men: 1.28, OR women: 1.39), diabetes (1.37, 1.24), chronic renal failure (1.31, 1.22) and obesity (1.21, 1.26) increased the likelihood of severe infection in both sexes. Chronic skin ulcers (1.32), acute cerebrovascular disease (1.34), chronic obstructive pulmonary disease (1.21), urinary incontinence (1.17) and neoplasms (1.26) in men, and infertility (1.87), obstructive sleep apnea (1.43), hepatic steatosis (1.43), rheumatoid arthritis (1.39) and menstrual disorders (1.18) in women were also associated with more severe outcomes. CONCLUSIONS: Age and specific cardiovascular and metabolic diseases increased the risk of severe SARS-CoV-2 infections in men and women, whereas the effects of certain comorbidities are sex specific. Future studies in different settings are encouraged to analyze which profiles of chronic patients are at higher risk of poor prognosis and should therefore be the targets of prevention and shielding strategies.

Types of myocardial injury and mid-term outcomes in patients with COVID-19.

AIMS: To evaluate the acute and chronic patterns of myocardial injury among patients with coronavirus disease-2019 (COVID-19), and their mid-term outcomes. METHODS AND RESULTS: Patients with laboratory-confirmed COVID-19 who had a hospital encounter within the Mount Sinai Health System (New York City) between 27 February 2020 and 15 October 2020 were evaluated for inclusion. Troponin levels assessed between 72 h before and 48 h after the COVID-19 diagnosis were used to stratify the study population by the presence of acute and chronic myocardial injury, as defined by the Fourth Universal Definition of Myocardial Infarction. Among 4695 patients, those with chronic myocardial injury (n = 319, 6.8%) had more comorbidities, including chronic kidney disease and heart failure, while acute myocardial injury (n = 1168, 24.9%) was more associated with increased levels of inflammatory markers. Both types of myocardial injury were strongly associated with impaired survival at 6 months [chronic: hazard ratio (HR) 4.17, 95% confidence interval (CI) 3.44-5.06; acute: HR 4.72, 95% CI 4.14-5.36], even after excluding events occurring in the first 30 days (chronic: HR 3.97, 95% CI 2.15-7.33; acute: HR 4.13, 95% CI 2.75-6.21). The mortality risk was not significantly different in patients with acute as compared with chronic myocardial injury (HR 1.13, 95% CI 0.94-1.36), except for a worse prognostic impact of acute myocardial injury in patients <65 years of age (P-interaction = 0.043) and in those without coronary artery disease (P-interaction = 0.041). CONCLUSION: Chronic and acute myocardial injury represent two distinctive patterns of cardiac involvement among COVID-19 patients. While both types of myocardial injury are associated with impaired survival at 6 months, mortality rates peak in the early phase of the infection but remain elevated even beyond 30 days during the convalescent phase.

Factors associated with mortality in patients with COVID-19 admitted to intensive care: a systematic review and meta-analysis.

Identification of high-risk patients admitted to intensive care with COVID-19 may inform management strategies. The objective of this meta-analysis was to determine factors associated with mortality among adults with COVID-19 admitted to intensive care by searching databases for studies published between 1 January 2020 and 6 December 2020. Observational studies of COVID-19 adults admitted to critical care were included. Studies of mixed cohorts and intensive care cohorts restricted to a specific patient sub-group were excluded. Dichotomous variables were reported with pooled OR and 95%CI, and continuous variables with pooled standardised mean difference (SMD) and 95%CI. Fifty-eight studies (44,305 patients) were included in the review. Increasing age (SMD 0.65, 95%CI 0.53-0.77); smoking (OR 1.40, 95%CI 1.03-1.90); hypertension (OR 1.54, 95%CI 1.29-1.85); diabetes (OR 1.41, 95%CI 1.22-1.63); cardiovascular disease (OR 1.91, 95%CI 1.52-2.38); respiratory disease (OR 1.75, 95%CI 1.33-2.31); renal disease (OR 2.39, 95%CI 1.68-3.40); and malignancy (OR 1.81, 95%CI 1.30-2.52) were associated with mortality. A higher sequential organ failure assessment score (SMD 0.86, 95%CI 0.63-1.10) and acute physiology and chronic health evaluation-2 score (SMD 0.89, 95%CI 0.65-1.13); a lower PaO2 :FI O2 (SMD -0.44, 95%CI -0.62 to -0.26) and the need for mechanical ventilation at admission (OR 2.53, 95%CI 1.90-3.37) were associated with mortality. Higher white cell counts (SMD 0.37, 95%CI 0.22-0.51); neutrophils (SMD 0.42, 95%CI 0.19-0.64); D-dimers (SMD 0.56, 95%CI 0.43-0.69); ferritin (SMD 0.32, 95%CI 0.19-0.45); lower platelet (SMD -0.22, 95%CI -0.35 to -0.10); and lymphocyte counts (SMD -0.37, 95%CI -0.54 to -0.19) were all associated with mortality. In conclusion, increasing age, pre-existing comorbidities, severity of illness based on validated scoring systems, and the host response to the disease were associated with mortality; while male sex and increasing BMI were not. These factors have prognostic relevance for patients admitted to intensive care with COVID-19.

Correlation study to identify the factors affecting COVID-19 case fatality rates in India.

BACKGROUND AND AIMS: In India, COVID-19 case fatality rates (CFRs) have consistently been very high in states like Punjab and Maharashtra and very low in Kerala and Assam. To investigate the discrepancy in state-wise CFRs, datasets on various factors related to demography, socio-economy, public health, and healthcare capacity have been collected to study their association with CFR. METHODS: State-wise COVID-19 data was collected till April 22, 2021. The latest data on the various factors have been collected from reliable sources. Pearson correlation, two-tailed P test, Spearman rank correlation, and Artificial Neural Network (ANN) structures have been used to assess the association between various factors and CFR. RESULTS: Life expectancies, prevalence of overweight, COVID-19 test positive rates, and H1N1 fatality rates show a significant positive association with CFR. Human Development Index, per capita GDP, public affairs index, health expenditure per capita, availability of govt. doctors & hospital beds, prevalence of certain diseases, and comorbidities like diabetes and hypertension show insignificant association with CFR. Sex ratio, health expenditure as a percent of GSDP, and availability of govt. hospitals show a significant negative correlation with CFR. CONCLUSION: The study indicates that older people, males of younger age groups, and overweight people are at more fatality risk from COVID-19. Certain diseases and common comorbidities like diabetes and hypertension do not seem to have any significant effect on CFR. States with better COVID-19 testing rates, health expenditure, and healthcare capacity seem to perform better with regard to COVID-19 fatality rates.

Prevalence of multiple risk factors for poor outcomes associated with COVID-19 among an elderly Australian population.

BACKGROUND AND OBJECTIVES: Increasing age, male sex and various chronic conditions have been identified as important risk factors for poor outcomes from COVID-19. The aim of this study was to examine the prevalence of risk factors for poor outcomes due to COVID-19 infection in an older population. METHOD: The proportion of the population with one or more risk factors and the prevalence of individual risk factors and multiple risk factors were calculated among Department of Veterans' Affairs (DVA) clients aged ≥70 years. RESULTS: There were 103,422 DVA clients included. Of these, 79% in the community and 82% in residential aged care had at least one risk factor for poor outcomes from COVID-19. Hypertension was most prevalent, followed by chronic heart and airways disease. Over half had ≥2 risk factors, and one in five had ≥3 risk factors across multiple body systems. DISCUSSION: A substantial proportion of older Australians are at risk of poor outcomes from COVID-19 because of their multimorbid risk profile. These patients should be prioritised for proactive monitoring to avoid unintentional harm due to potential omission of care during the pandemic.

Clinical Features and Outcomes of Acute Kidney Injury in Patients Infected with COVID-19 in Xiangyang, China.

BACKGROUND: In December 2019, pneumonia associated with COVID-19 has spread from Wuhan to other areas in China. In the present study, we aimed to further clarify the clinical features and outcomes of acute kidney injury (AKI) in patients infected with COVID-19 in Xiangyang, Hubei, China. METHODS: All confirmed cases of COVID-19 with AKI in Xiangyang Central Hospital from January 22 to May 31, 2020, were included in this retrospective study. Data of epidemiological, clinical, laboratory, radiological tests, treatment, complication, and outcomes were collected and analyzed. Patients were divided into intensive care unit (ICU) group and isolation ward (non-ICU) group. RESULTS: Of the total patients, 33.3% in the non-ICU group and 85.7% in the ICU group had chronic diseases. In addition, 85.7% of patients in the ICU group died. The most common symptoms were fever, cough, and fatigue. The lymphocyte count in the ICU group was significantly reduced compared with the non-ICU group. The chest computed tomography (CT) images appeared showed multiple mottles and ground-glass opacity. Strip shadow could be found in chest CT images of some recovered patients. All patients received antiviral treatment. Most patients in the ICU group were given methylprednisolone, immunoglobulin, antibiotics, and mechanical ventilation and 35.7% of patients in the ICU group received continuous renal replacement therapy. CONCLUSIONS: Elderly with chronic comorbidities were more susceptible to COVID-19, showing a higher mortality rate due to multiple organ damage, and 35.7% of patients with AKI in ICU received renal replacement therapy. Moreover, part of the cured patients might need additional time to recover for poor lung function.

The Correlation of Comorbidities on the Mortality in Patients with COVID-19: an Observational Study Based on the Korean National Health Insurance Big Data.

BACKGROUND: Mortality of coronavirus disease 2019 (COVID-19) is a major concern for quarantine departments in all countries. This is because the mortality of infectious diseases determines the basic policy stance of measures to prevent infectious diseases. Early screening of high-risk groups and taking action are the basics of disease management. This study examined the correlation of comorbidities on the mortality of patients with COVID-19. METHODS: We constructed epidemiologic characteristics and medical history database based on the Korean National Health Insurance Service Big Data and linked COVID-19 registry data of Korea Centers for Disease Control & Prevention (KCDC) for this emergent observational cohort study. A total of 9,148 patients with confirmed COVID-19 were included. Mortalities by sex, age, district, income level and all range of comorbidities classified by International Classification of Diseases-10 based 298 categories were estimated. RESULTS: There were 3,556 male confirmed cases, 67 deaths, and crude death rate (CDR) of 1.88%. There were 5,592 females, 63 deaths, and CDR of 1.13%. The most confirmed cases were 1,352 patients between the ages of 20 to 24, followed by 25 to 29. As a result of multivariate logistic regression analysis that adjusted epidemiologic factors to view the risk of death, the odds ratio of death would be hemorrhagic conditions and other diseases of blood and blood-forming organs 3.88-fold (95% confidence interval [CI], 1.52-9.88), heart failure 3.17-fold (95% CI, 1.88-5.34), renal failure 3.07-fold (95% CI, 1.43-6.61), prostate malignant neoplasm 2.88-fold (95% CI, 1.01-8.22), acute myocardial infarction 2.38-fold (95% CI, 1.03-5.49), diabetes was 1.82-fold (95% CI, 1.25-2.67), and other ischemic heart disease 1.71-fold (95% CI, 1.09-2.66). CONCLUSION: We hope that this study could provide information on high risk groups for preemptive interventions. In the future, if a vaccine for COVID-19 is developed, it is expected that this study will be the basic data for recommending immunization by selecting those with chronic disease that had high risk of death, as recommended target diseases for vaccination.

Delayed Primary and Specialty Care: The Coronavirus Disease-2019 Pandemic Second Wave.

Time is of the essence to continue the pandemic disaster cycle with a comprehensive post-COVID-19 health care delivery system RECOVERY analysis, plan and operation at the local, regional and state level.The second wave of COVID-19 pandemic response are not the ripples of acute COVID-19 patient clusters that will persist until a vaccine strategy is designed and implemented to effect herd immunity. The COVID-19 second wave are the patients that have had their primary and specialty care delayed. This exponential wave of patients requires prompt health care delivery system planning and response.