Coronavirus disease (COVID-19): A systematic review and meta-analysis to evaluate the impact of various comorbidities on serious events

Post-traumatic Stress Disorder Among COVID-19 Survivors at 3-Month Follow-up After Hospital Discharge

BACKGROUND

Post-traumatic stress disorder (PTSD) is a severe but treatable mental disorder that develops after a life-threatening traumatic event. Coronavirus disease 19 (COVID-19) hospitalisation is a potentially traumatic experience, especially in severe cases. Furthermore, the unprecedented context of the severe acute respiratory syndrome coronavirus 2 pandemic, with daily media bombardment about COVID-19 mortality, may have amplified life-threatening perception also in patients with moderate infection. The aim of this study was to assess the prevalence and risk factors of PTSD at 3-month follow-up in patients hospitalised for COVID-19 infection.

DESIGN

In this cohort follow-up study conducted in a large Italian academic COVID-19 hospital, 115 recruited survivors were contacted by telephone 3 months after discharge to home care. The Posttraumatic Stress Disorder Checklist for DSM-5 was administered. Multivariate logistic regression models were used to analyse risk factors for the development of PTSD.

KEY RESULTS

A total of 10.4% of the sample received a PCL-5-based diagnosis of PTSD. Other 8.6% of the sample received a diagnosis of subthreshold PTSD, which leads to significant levels of distress and impairment. Multivariate regression analysis indicated that previous psychiatric diagnosis (odds ratio (OR) = 6.3, 95% confidence interval (CI): 3.7-78.6, p < 0.001) and obesity (OR = 3.51, 95% CI: 1.4-857.9, p = 0.03) were risk factors for developing PTSD. Chronic pulmonary diseases approached significance as a risk factor (OR = 6.03, 95% CI: 1.0-37.1, p = 0.053). Male sex was a protective factor (OR=0.04, 95% CI: 0.0-0.041, p = 0.007).

CONCLUSIONS

PTSD and subthreshold PTSD rates in patients hospitalised for COVID-19 are worrying. Female sex and pre-existing mental disorders are established risk factors for PTSD, while the prospective association with obesity needs further investigation. Clinicians treating COVID-19 should consider screening for PTSD at follow-up assessments in patients discharged from the hospital.

Vitamin D in the Covid-19 era: a review with recommendations from a G.I.O.S.E.G. expert panel

Vitamin D (VITD) is a key hormone for bone health and has relevant extra-skeletal effects that might play a role in the prevention and treatment of COronaVIrus Disease 19 (COVID-19). Literature regarding this scenario is voluminous but controversial. Glucocorticoid Induced Osteoporosis Skeletal Endocrinology Group (G.I.O.S.E.G) has been present in the scientific debate about the use of VITD and has regularly interfaced national regulatory agencies to ensure appropriateness of its employment. Given the current pandemic and the questions on COVID-19 and VITD, G.I.O.S.E.G. appointed an expert panel to advise how to consider this issue best. The results of these deliberations are reported in the current recommendation paper.

A snapshot of the prevalence of endocrine disorders in pregnancies complicated by coronavirus disease 2019: A narrative review with meta-analysis

Background

Some maternal characteristics indicate worse prognosis in pregnant women with coronavirus disease 2019 (COVID‐19).

Objective

To describe the prevalence of endocrine disorders in pregnancies involving COVID‐19, and its impact on maternal outcomes.

Search strategy

Search terms were “pregnancy” and “COVID‐19”.

Selection

PubMed, Embase, medRxiv, and Cochrane worksheet from February to July 2020 were searched.

Data collection and analysis

Articles describing endocrine disorders in pregnancies with and without COVID‐19 involvement were considered. We performed meta‐analyses of prevalence using random‐effect models and estimated relative risk and 95% confidence intervals (CI) of maternal outcomes relative to presence of endocrine disorders.

Main results

Articles included (n = 141) were divided into three data sets: individual (119 articles, 356 women), case series (17 articles, 1064 women), and national registries (7 articles, 10 178 women). Prevalence of obesity ranged from 16% to 46% and hyperglycemia in pregnancy (HIP) ranged from 8% to 12%. In data set 1, HIP and obesity were risk factors for severe disease in crude and age‐adjusted models, although not for intensive care unit admission. In data from two national registries, risk of dying was 5.62 (95% CI 0.30–105.95) in women with diabetes and 2.26 (95% CI 1.03–4.96) in those with obesity.

Conclusion

Obesity and HIP were prevalent in pregnant women with severe COVID‐19.

In pregnant women with COVID‐19, obesity and hyperglycemia were prevalent and associated with adverse maternal outcomes.

Phenome-wide association of 1809 phenotypes and COVID-19 disease progression in the Veterans Health Administration Million Veteran Program

BACKGROUND

The risk factors associated with the stages of Coronavirus Disease-2019 (COVID-19) disease progression are not well known. We aim to identify risk factors specific to each state of COVID-19 progression from SARS-CoV-2 infection through death.

METHODS AND RESULTS

We included 648,202 participants from the Veteran Affairs Million Veteran Program (2011-). We identified characteristics and 1,809 ICD code-based phenotypes from the electronic health record. We used logistic regression to examine the association of age, sex, body mass index (BMI), race, and prevalent phenotypes to the stages of COVID-19 disease progression: infection, hospitalization, intensive care unit (ICU) admission, and 30-day mortality (separate models for each). Models were adjusted for age, sex, race, ethnicity, number of visit months and ICD codes, state infection rate and controlled for multiple testing using false discovery rate (≤0.1). As of August 10, 2020, 5,929 individuals were SARS-CoV-2 positive and among those, 1,463 (25%) were hospitalized, 579 (10%) were in ICU, and 398 (7%) died. We observed a lower risk in women vs. men for ICU and mortality (Odds Ratio (95% CI): 0.48 (0.30-0.76) and 0.59 (0.31-1.15), respectively) and a higher risk in Black vs. Other race patients for hospitalization and ICU (OR (95%CI): 1.53 (1.32-1.77) and 1.63 (1.32-2.02), respectively). We observed an increased risk of all COVID-19 disease states with older age and BMI ≥35 vs. 20-24 kg/m2. Renal failure, respiratory failure, morbid obesity, acid-base balance disorder, white blood cell diseases, hydronephrosis and bacterial infections were associated with an increased risk of ICU admissions; sepsis, chronic skin ulcers, acid-base balance disorder and acidosis were associated with mortality.

CONCLUSIONS

Older age, higher BMI, males and patients with a history of respiratory, kidney, bacterial or metabolic comorbidities experienced greater COVID-19 severity. Future studies to investigate the underlying mechanisms associated with these phenotype clusters and COVID-19 are warranted.

A Simplified Comorbidity Evaluation Predicting Clinical Outcomes Among Patients With Coronavirus Disease 2019

Background

Patients with coronavirus disease 2019 (COVID-19) have shown a range of clinical outcomes. Previous studies have reported that patient comorbidities are predictive of worse clinical outcomes, especially when patients have multiple chronic diseases. We aim to: 1) derive a simplified comorbidity evaluation and determine its accuracy of predicting clinical outcomes (i.e., hospital admission, intensive care unit (ICU) admission, ventilation, and in-hospital mortality); and 2) determine its performance accuracy in comparison to well-established comorbidity indexes.

Methods

This was a single-center retrospective observational study. We enrolled all emergency department (ED) patients with COVID-19 from March 1, 2020, to December 31, 2020. A simplified comorbidity evaluation (COVID-related high-risk chronic condition (CCC)) was derived to predict different clinical outcomes using multivariate logistic regressions. In addition, chronic diseases included in the Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Index (ECI) were scored, and its accuracy of predicting COVID-19 clinical outcomes was also compared with the CCC.

Results

Data were retrieved from 90,549 ED patient visits during the study period, among which 3,864 patients were COVID-19 positive. Forty-seven point nine percent (1,851/3,864) were admitted to the hospital, 9.4% (364) patients were admitted to the ICU, 6.2% (238) received invasive mechanical ventilation, and 4.6% (177) patients died in the hospital. The CCC evaluation correlated well with the four studied clinical outcomes. The adjusted odds ratios of predicting in-hospital death from CCC was 2.84 (95% confidence interval (CI): 1.81 - 4.45, P < 0.001). C-statistics of CCC predicting in-hospital all-cause mortality was 0.73 (0.69 - 0.76), similar to those of the CCI's (0.72) and ECI's (0.71, P = 0.0513).

Conclusions

CCC can accurately predict clinical outcomes among patients with COVID-19. Its performance accuracies for such predictions are not inferior to those of the CCI or ECI's.

Probabilities of ICU admission and hospital discharge according to patient characteristics in the designated COVID-19 hospital of Kuwait

BACKGROUND

Subsequent epidemic waves have already emerged in many countries and in the absence of highly effective preventive and curative options, the role of patient characteristics on the development of outcomes needs to be thoroughly examined, especially in middle-east countries where such epidemiological studies are lacking. There is a huge pressure on the hospital services and in particular, on the Intensive Care Units (ICU). Describing the need for critical care as well as the chance of being discharged from hospital according to patient characteristics, is essential for a more efficient hospital management. The objective of this study is to describe the probabilities of admission to the ICU and the probabilities of hospital discharge among positive COVID-19 patients according to demographics and comorbidities recorded at hospital admission.

METHODS

A prospective cohort study of all patients with COVID-19 found in the Electronic Medical Records of Jaber Al-Ahmad Al-Sabah Hospital in Kuwait was conducted. The study included 3995 individuals (symptomatic and asymptomatic) of all ages who tested positive from February 24th to May 27th, 2020, out of which 315 were treated in the ICU and 3619 were discharged including those who were transferred to a different healthcare unit without having previously entered the ICU. A competing risk analysis considering two events, namely, ICU admission and hospital discharge using flexible hazard models was performed to describe the association between event-specific probabilities and patient characteristics.

RESULTS

Results showed that being male, increasing age and comorbidities such as chronic kidney disease (CKD), asthma or chronic obstructive pulmonary disease and weakened immune system increased the risk of ICU admission within 10 days of entering the hospital. CKD and weakened immune system decreased the probabilities of discharge in both females and males however, the age-related pattern differed by gender. Diabetes, which was the most prevalent comorbid condition, had only a moderate impact on both probabilities (18% overall) in contrast to CKD which had the largest effect, but presented only in 7% of those admitted to ICU and in 1% of those who got discharged. For instance, within 5 days a 50-year-old male had 19% (95% C.I.: [15,23]) probability of entering the ICU if he had none of these comorbidities, yet this risk jumped to 31% (95% C.I.: [20,46]) if he had also CKD, and to 27% in the presence of asthma/COPD (95% C.I.: [19,36]) or of weakened immune system (95% C.I.: [16,42]).

CONCLUSIONS

This study provides useful insight in describing the probabilities of ICU admission and hospital discharge according to age, gender, and comorbidities among confirmed COVID-19 cases in Kuwait. A web-tool is also provided to allow the user to estimate these probabilities for any combination of these covariates. These probabilities enable deeper understanding of the hospital demand according to patient characteristics which is essential to hospital management and useful for developing a vaccination strategy.

A systematic review and meta-analysis of geographic differences in comorbidities and associated severity and mortality among individuals with COVID-19

Several comorbidities have been shown to be associated with coronavirus disease 2019 (COVID-19) related severity and mortality. However, considerable variation in the prevalence estimates of comorbidities and their effects on COVID-19 morbidity and mortality have been observed in prior studies. This systematic review and meta-analysis aimed to determine geographical, age, and gender related differences in the prevalence of comorbidities and associated severity and mortality rates among COVID-19 patients. We conducted a search using PubMed, Scopus, and EMBASE to include all COVID-19 studies published between January 1st, 2020 to July 24th, 2020 reporting comorbidities with severity or mortality. We included studies reporting the confirmed diagnosis of COVID-19 on human patients that also provided information on comorbidities or disease outcomes. We used DerSimonian and Laird random effects method for calculating estimates. Of 120 studies with 125,446 patients, the most prevalent comorbidity was hypertension (32%), obesity (25%), diabetes (18%), and cardiovascular disease (16%) while chronic kidney or other renal diseases (51%, 44%), cerebrovascular accident (43%, 44%), and cardiovascular disease (44%, 40%) patients had more COVID-19 severity and mortality respectively. Considerable variation in the prevalence of comorbidities and associated disease severity and mortality in different geographic regions was observed. The highest mortality was observed in studies with Latin American and European patients with any medical condition, mostly older adults (≥ 65 years), and predominantly male patients. Although the US studies observed the highest prevalence of comorbidities in COVID-19 patients, the severity of COVID-19 among each comorbid condition was highest in Asian studies whereas the mortality was highest in the European and Latin American countries. Risk stratification and effective control strategies for the COVID-19 should be done according to comorbidities, age, and gender differences specific to geographical location.

The fight against COVID-19: Striking a balance in the renin-angiotensin system

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enters host cells by interacting with membrane-bound angiotensin-converting enzyme 2 (ACE2), a vital element in the renin–angiotensin system (RAS), which regulates blood pressure, fluid balance, and cardiovascular functions. We herein evaluate existing evidence for the molecular alterations within the RAS pathway (e.g., ACE2 and angiotensin II) during SARS-CoV-2 infection and subsequent Coronavirus Disease 2019 (COVID-19). This includes reports regarding potential effect of RAS blockade (e.g., ACE inhibitors and angiotensin II receptor blockers) on ACE2 expression and clinical outcomes in patients with co-morbidities commonly treated with these agents. The collective evidence suggests a dual role for ACE2 in COVID-19, depending on the stage of infection and the coexisting diseases in individual patients. This information is further discussed with respect to potential therapeutic strategies targeting RAS for COVID-19 treatment.

A systematic review of health sector responses to the coincidence of disasters and COVID-19

BACKGROUND

In December 2019, the Chinese city of Wuhan reported a novel pneumonia caused by COVID-19. While the COVID-19 pandemic has been increasingly affecting the world, the occurrence of disasters resulted in complex emergencies. The present review is aimed to identify the literature focused on health system response to coincidence of COVID-19 and disasters as well as describing their finding, implications and lessons-learned.

METHODS

This study was conducted and reported based on PRISMA guideline. The databases of Web of Sciences, PubMed, Scopus, Google Scholar and World Health Organization Library were searched. The inclusion criteria were all forms of published articles which investigated the coincidence of disasters and COVID-19 pandemic. Using the title and abstract screening, the selections of studies were performed by two researchers. Once, the relevant papers were finalized, the analysis was done in two parts of descriptive analysis and implications for health systems.

RESULTS

Out of 1245 studies generated by initial search, a number of 13 articles was selected for final analysis. Earthquake was the most frequent disaster which its coincidence with COVID-19 was studied by researchers (31%). The implications of researchers for healthcare system were explained in three sections of climatic events, earthquakes and all hazard approach in relation to COVID-19.

CONCLUSION

Extracting the lessons learned from the regions affected by disasters at the time of COVID-19 pandemic can be helpful for healthcare professionals and policy-makers to improve their preparedness and response during disasters and a serious pandemic such as COVID-19. Further research is needed to identify the factors which strengthen the preparedness of health system for the dual risk of natural hazards and pandemics.

Mental health issues among health care workers during the COVID-19 pandemic - A study from India

Mental health issues among health care workers (HCWs) in treatment settings during COVID-19 remains understudied in India. This study examines its prevalence and correlates among HCWs in Karnataka State, India. HCWs who attended a workshop to improve mental health well-being during COVID-19 completed an anonymous online questionnaire. In addition to socio-demographics, domains assessed include occupational characteristics, COVID-19 related concerns, anxiety/depression, substance use, suicidality, lifestyle and family functioning. Of the 3083 HCWs who completed the survey (response rate-51.4 %), anxiety disorder and depression was highest among those with frontline COVID-19 responsibilities (anxiety disorder-26.6 %, depression-23.8 %). Prevalence was significantly higher among those with clinical responsibilities compared to those with supportive responsibilities (anxiety disorder: 23.9 % vs 15.5 %), (depression: 20.0 % vs 14.2 %). In the backward step-wise logistic regression analysis, HCWs with anxiety disorder were more likely to be doctors/nurses/hospital assistants, older, female, unmarried, without a leisure activity, report increased alcohol use and suicidal thoughts after pandemic onset, and having a history of receiving mental health interventions. Participants with depression additionally had family distress and hardly ever exercised. To conclude, mental health issues are common among HCWs in India. Interventions need to ensure that HCWs are protected from mental health consequences of working in COVID-19 treatment settings.

Characteristics of COVID-19 Recurrence: A Systematic Review and Meta-Analysis

Background:

Previous studies reported the recurrence of coronavirus disease 2019 (COVID-19) among discharge patients. This study aimed to examine the characteristic of COVID-19 recurrence cases by performing a systematic review and meta-analysis.

Methods:

A systematic search was performed in PubMed and Embase and gray literature up to September 19, 2020. A random-effects model was applied to obtain the pooled prevalence of disease recurrence among recovered patients and the prevalence of subjects underlying comorbidity among recurrence cases. The other characteristics were calculated based on the summary data of individual studies.

Results:

A total of 41 studies were included in the final analysis, we have described the epidemiological characteristics of COVID-19 recurrence cases. Of 3,644 patients recovering from COVID-19 and being discharged, an estimate of 15% (95% CI, 12% to 19%) patients was re-positive with SARS-CoV-2 during the follow-up. This proportion was 14% (95% CI, 11% to 17%) for China and 31% (95% CI, 26% to 37%) for Korea. Among recurrence cases, it was estimated 39% (95% CI, 31% to 48%) subjects underlying at least one comorbidity. The estimates for times from disease onset to admission, from admission to discharge, and from discharge to RNA positive conversion were 4.8, 16.4, and 10.4 days, respectively.

Conclusion:

This study summarized up-to-date evidence from case reports, case series, and observational studies for the characteristic of COVID-19 recurrence cases after discharge. It is recommended to pay attention to follow-up patients after discharge, even if they have been in discharge quarantine.

Relationship between physical and mental health comorbidities and COVID-19 positivity, hospitalization, and mortality

BACKGROUND

Understanding the association between separate and combined mental and physical health diagnoses and COVID-19 outcomes is greatly needed to address the severity of illness.

METHODS

Data on 24,034 patients screened for COVID-19 as of July 2020 were extracted from the Froedtert/Medical College of Wisconsin Epic medical record. COVID-19 outcomes were defined as positive screens, proportion hospitalized among positive screens, and proportion that died among positive and hospitalized population. The primary independent variable was a 3-category variable: physical health diagnosis alone, mental health diagnosis alone, and combined mental and physical health diagnoses. Logistic regression and Cox proportional hazard models were used to examine the independent relationship between separate and combined diagnoses and COVID-19 outcomes.

RESULTS

Compared to physical health diagnosis alone, mental health diagnosis alone had lower odds of screening positive (OR=0.68, CI=0.51;0.92) and was not associated with hospitalization or mortality among positive screens. Combined had lower odds of screening positive (OR=0.78, CI=0.69;0.88) and higher odds of hospitalization among positive screens after adjusting for demographics (OR=1.58, CI=1.20;2.08) but lost significance in the fully adjusted model. No category of diagnoses was associated with mortality.

LIMITATIONS

Analysis is cross-sectional and cannot speak to any causal relationships.

CONCLUSIONS

Overall, compared to physical health diagnosis alone, mental health diagnosis and combined had lower odds of positive screens. However, individuals with combined were more likely to be hospitalized, after adjusting for demographics only. These findings add new evidence for risk of COVID-19 and related hospitalization in individuals who have a physical and mental health diagnosis.

Hypertension and Related Comorbidities as Potential Risk Factors for COVID-19 Hospitalization and Severity: A Prospective Population-Based Cohort Study

The independent role of hypertension for COVID-19 outcomes in the population remains unclear. We aimed to estimate the independent effect of hypertension and hypertension-related conditions, i.e., cardiovascular, cerebrovascular and chronic kidney diseases, as potential risk factors for COVID-19 hospitalization and severe COVID-19 (i.e., intensive care unit admission or death) in the population. The risk for severe COVID-19 among hospitalized patients was also evaluated. A Spanish population-based cohort of people aged 25-79 years was prospectively followed from March to May 2020 to identify hospitalizations for laboratory-confirmed COVID-19. Poisson regression was used to estimate the adjusted relative risk (aRR) for COVID-19 hospitalization and severe COVID-19 among the whole cohort, and for severe COVID-19 among hospitalized patients. Of 424,784 people followed, 1106 were hospitalized by COVID-19 and 176 were severe cases. Hypertension was not independently associated with a higher risk of hospitalization (aRR 0.96, 95% CI 0.83-1.12) nor severe COVID-19 (aRR 1.12, 95% CI 0.80-1.56) in the population. Persons with cardiovascular, cerebrovascular and chronic kidney diseases were at higher risk for COVID-19 hospitalization (aRR 1.33, 95% CI 1.13-1.58; aRR 1.41, 95% CI 1.04-1.92; and aRR 1.52, 95% CI 1.21-1.91; respectively) and severe COVID-19 (aRR 1.61, 95% CI 1.13-2.30; aRR 1.91, 95% CI 1.13-3.25; and aRR 1.78, 95% CI 1.14-2.76; respectively). COVID-19 hospitalized patients with cerebrovascular diseases were at higher risk of mortality (aRR 1.80, 95% CI 1.00-3.23). The current study shows that, in the general population, persons with cardiovascular, cerebrovascular and chronic kidney diseases, but not those with hypertension only, should be considered as high-risk groups for COVID-19 hospitalization and severe COVID-19.

Mantenimiento de tratamientos crónicos en pacientes afectados de COVID-19

•Los pacientes en tratamiento con IECA o ARAII no tienen mayor riesgo de infección por SARS-COVID, ni mayor riesgo de COVID-19 grave ni de mortalidad. Por ello, deben continuar con el tratamiento, y solo estaría justificada su retirada por motivos clínicos. •Los pacientes con COVID-19 en tratamiento con hipolipemiantes deben continuar con ellos, especialmente aquellos con alto riesgo de enfermedad cardiovascular. Se suspenderán si hay riesgo hepático o renal o si está impedida la vía oral. Se valorará el cambio de estatina si hay interacción con el tratamiento para la infección. •En pacientes diabéticos con COVID-19 se recomienda suspender los iSGLT-2 (gliflozinas o uricosúricos) en caso de fiebre o diarrea, y vigilar función renal y glucemia por si es necesario ajustar el resto de los antidiabéticos. La insulina es el tratamiento de elección en caso de retirada del resto de fármacos. •Los medicamentos psicotrópicos pueden interactuar con los fármacos utilizados para la COVID-19 y algunos de sus efectos adversos, especialmente los relacionados con la depresión respiratoria, pueden empeorar la evolución de la infección. •No se ha encontrado asociación entre el uso de inhibidores de la bomba de protones o anti-H2 y la aparición de COVID-19. La evidencia actual no indica la necesidad de retirar el omeprazol en los casos con clara indicación. •No hay evidencia científica que relacione el uso de antiinflamatorios no esteroideos (AINE) con el empeoramiento de la COVID-19, por lo que pueden usarse en el tratamiento sintomático de la infección y/u otras comorbilidades asociadas. •No se deben interrumpir los tratamientos crónicos con AINE u opiáceos que están bien indicados. Se recomienda elegir opioides con menos efecto inmunosupresor. •Durante la COVID-19 se recomienda suspender temporalmente los anticonceptivos y continuar con los anticoagulantes o antiagregantes que tomase previamente.

Therapeutic Intervention of COVID-19 by Natural Products: A Population-Specific Survey Directed Approach

To date very few promising leads from natural products (NP) secondary metabolites with antiviral and immunomodulatory properties have been identified for promising/potential intervention for COVID-19. Using in-silico docking studies and genome based various molecular targets, and their in vitro anti-SARS CoV-2 activities against whole cell and/or selected protein targets, we select a few compounds of interest, which can be used as potential leads to counteract effects of uncontrolled innate immune responses, in particular those related to the cytokine storm. A critical factor for prevention and treatment of SARS-CoV-2 infection relates to factors independent of viral infection or host response. They include population-related variables such as concurrent comorbidities and genetic factors critically relevant to COVID-19 health disparities. We discuss population risk factors related to SARS-CoV-2. In addition, we focus on virulence related to glucose-6-phosphate dehydrogenase deficiency (G6PDd), the most common human enzymopathy. Review of data on the response of individuals and communities with high prevalence of G6PDd to NP, prompts us to propose the rationale for a population-specific management approach to rationalize design of therapeutic interventions of SARS-CoV-2 infection, based on use of NP. This strategy may lead to personalized approaches and improve disease-related outcomes.

Prevalence of comorbidity in Chinese patients with COVID-19: systematic review and meta-analysis of risk factors

BACKGROUND

Coronavirus disease 2019 (COVID-19) is an infectious disease characterized by cough, fever, and fatigue and 20% of cases will develop into severe conditions resulting from acute lung injury with the manifestation of the acute respiratory distress syndrome (ARDS) that accounts for more than 50% of mortality. Currently, it has been reported that some comorbidities are linked with an increased rate of severity and mortality among COVID-19 patients. To assess the role of comorbidity in COVID-19 progression, we performed a systematic review with a meta-analysis on the relationship of COVID-19 severity with 8 different underlying diseases.

METHODS

PubMed, Web of Science, and CNKI were searched for articles investigating the prevalence of comorbidities in severe and non-severe COVID-19 patients. A total of 41 studies comprising 12,526 patients were included.

RESULTS

Prevalence of some commodities was lower than that in general population such as hypertension (19% vs 23.2%), diabetes (9% vs 10.9%), chronic kidney disease (CKD) (2% vs 9.5%), chronic liver diseases (CLD) (3% vs 24.8%) and chronic obstructive pulmonary disease (COPD) (3% vs 8.6%), while some others including cancer (1% vs 0.6%), cardiovascular disease (6% vs 1.8%) and cerebrovascular disease (2% vs 0.9%) exhibited greater percentage in COVID-19. Cerebrovascular disease (OR = 3.70, 95%CI 2.51-5.45) was found to be the strongest risk factor in disease exacerbation, followed by CKD (OR = 3.60, 95%CI 2.18-5.94), COPD (OR = 3.14, 95% CI 2.35-4.19), cardiovascular disease (OR = 2.76, 95% CI 2.18-3.49), malignancy (OR = 2.63, 95% CI 1.75-3.95), diabetes (OR = 2.49, 95% CI 2.10-2.96) and hypertension (OR = 2.13, 95% CI 1.81-2.51). We found no correlation between CLD and increased disease severity (OR = 1.32, 95% CI 0.96-1.82).

CONCLUSION

The impact of all eight underlying diseases on COVID-19 deterioration seemed to be higher in patients outside Hubei. Based on different comorbidities, COVID-19 patients tend to be at risk of developing poor outcomes to a varying degree. Thus, tailored infection prevention and monitoring and treatment strategies targeting these high-risk subgroups might improve prognosis during the COVID-19 pandemic.

Machining learning predicts the need for escalated care and mortality in COVID-19 patients from clinical variables

Objective: This study aimed to develop a machine learning algorithm to identify key clinical measures to triage patients more effectively to general admission versus intensive care unit (ICU) admission and to predict mortality in COVID-19 pandemic. Materials and methods: This retrospective study consisted of 1874 persons-under-investigation for COVID-19 between February 7, 2020, and May 27, 2020 at Stony Brook University Hospital, New York. Two primary outcomes were ICU admission and mortality compared to COVID-19 positive patients in general hospital admission. Demographic, vitals, symptoms, imaging findings, comorbidities, and laboratory tests at presentation were collected. Predictions of mortality and ICU admission were made using machine learning with 80% training and 20% testing. Performance was evaluated using receiver operating characteristic (ROC) area under the curve (AUC). Results: A total of 635 patients were included in the analysis (age 60±11, 40.2% female). The top 6 mortality predictors were age, procalcitonin, C-creative protein, lactate dehydrogenase, D-dimer and lymphocytes. The top 6 ICU admission predictors are procalcitonin, lactate dehydrogenase, C-creative protein, pulse oxygen saturation, temperature and ferritin. The best machine learning algorithms predicted mortality with 89% AUC and ICU admission with 79% AUC. Conclusion: This study identifies key independent clinical parameters that predict ICU admission and mortality associated with COVID-19 infection. The predictive model is practical, readily enhanced and retrained using additional data. This approach has immediate translation and may prove useful for frontline physicians in clinical decision making under time-sensitive and resource-constrained environment.

A meta-meta-analysis: Evaluation of meta-analyses published in the effectiveness of cardiovascular comorbidities on the severity of COVID-19

On January 2020, WHO confirmed the epidemic outbreak of SARS-CoV-2 as a Health Emergency of International Concern. The aim of this meta-meta-analysis is quantifying meta-analytic findings on the association of cardiovascular disease (CVD) comorbidities and COVID-19 severity. Findings suggest that chances of getting severe COVID-19 disease in patients with CVD is greater than those without CVD. Also, prevalence of CVD in patents with COVID-19 is 0.08 (95% CI = 0.07–0.08). The OR as 3.44 indicates that the odds of getting severe COVID-19 is more than 3 times higher in those with CVD. Also, prevalence of hypertension in patient with COVID-19 is 0.27 (95%CI = 0.27–0.28) and the OR as 2.68 indicates that the odds of getting severe COVID-19 in cases with high blood pressure is more than 2.5 times higher than those without hypertension. It is rational to suppose that persons with coronary artery disease are prone to severe viral infection thereby, guideline-directed diagnosis and medical therapy is vital in CVD patients.

Which Factors, Smoking, Drinking Alcohol, Betel Quid Chewing, or Underlying Diseases, Are More Likely to Influence the Severity of COVID-19?

The global outbreak of the coronavirus disease 2019 (COVID-19) pandemic occurred in late 2019 and early 2020. The factors that influence disease severity should be of clinical concern. Existing findings on the effects of smoking on COVID-19 are also controversial and need to be confirmed by further research. In addition, the effects of alcohol consumption and betel quid (BQ) chewing on COVID-19 are unclear. The aim of this study was to examine the demographic characteristics of COVID-19 patients and the effects of smoking, drinking, BQ chewing, and underlying diseases on the severity of COVID-19. A retrospective study was conducted on 91 patients with confirmed cases of COVID-19 hospitalized in Yueyang, Hunan Province, China from 21 January to 8 March, 2020. Patient demographic data, and information on smoking, drinking and BQ chewing, and underlying diseases were extracted from the patient electronic medical records (EMR) and telephone interviews. The chi-square test was used to conduct a univariate analysis of the factors influencing the severity of COVID-19, and ordinal logistic regression analysis was used to identify the factors related to the severity of COVID-19. The results showed that the rates of smoking, drinking and BQ chewing were 15.4, 26.4, and 7.1%, respectively, there was no significant relationship between these lifestyle factors and the severity of COVID-19 (P > 0.05). However, underlying diseases such as diabetes [odds ratio (OR) = 7.740, 95% confidence interval (CI):1.000-60.740, P = 0.050], source of infection (OR = 0.180, 95% CI: 0.030-0.980, P = 0.049), and employment status (retired/unemployed vs. employed: OR = 29.430, 95% CI, 1.050 - 822.330, P = 0.047) were significant independent predictors of severe COVID-19 infection. These individuals should be informed of methods to increase personal protection, and doctors should prevent these individuals from developing serious diseases. It is important to pay attention to the source of infection and timely medical treatment. This study showed that the clinical classification of COVID-19 was associated with patients with diabetes, source of infection, and retired/unemployed. Therefore in the clinical practice of COVID-19 should be more concern these factors. Although no statistical significance was found in smoking, drinking alcohol, BQ chewing, and severity of COVID-19 patients, more studies have confirmed that are harmful and risk factors for underlying diseases in the population. Health authorities should formulate policies to publicize the harmful effects of smoking, drinking, and betel nut chewing and promote a healthy lifestyle.

Macrolevel association of COVID-19 with non-communicable disease risk factors in India

BACKGROUND & AIMS

Greater COVID-19 related mortality has been reported among persons with various non-communicable diseases (NCDs). We performed an ecological study to determine the association of state-level cases and deaths with NCD risk factors and healthcare and social indices.

METHODS

We obtained cumulative national and state-level data on COVID-19 cases and deaths from publicly available database www.covid19india.org from February to end November 2020. To identify association with major NCD risk factors, NCDs, healthcare related and social variables we obtained data from public sources. Association was determined using univariate and multivariate statistics.

RESULTS

More than 9.5 million COVID-19 cases and 135,000 deaths have been reported in India towards end of November 2020. There is significant positive correlation (Pearson r) of state-level COVID-19 cases and deaths per million, respectively, with NCD risk factors- obesity (0.64, 0.52), hypertension (0.28, 0.16), diabetes (0.66, 0.46), NCD epidemiological transition index (0.58, 0.54) and ischemic heart disease mortality (0.22, 0.33). Correlation is also observed with indices of healthcare access and quality (0.71, 0.61), urbanization (0.75, 0.73) and human (0.61, 0.56) and sociodemographic (0.70, 0.69) development. Multivariate adjusted analyses shows strong correlation of COVID-19 burden and deaths with NCD risk factors (r² = 0.51, 0.43), NCDs (r² = 0.32, 0.16) and healthcare (r² = 0.52, 0.38).

CONCLUSIONS

COVID-19 disease burden and mortality in India is ecologically associated with greater state-level burden of NCDs and risk factors, especially obesity and diabetes.

Severe COVID-19: A distinct entity

Severe coronavirus disease-2019 (COVID-19) is a distinct entity that rapidly evolves and may abruptly culminate in to a critical illness. As per Chinese experience, approximately, 15% of patients of COVID-19 progress to severe disease and 5% become critically ill. The incidence of severe and critical illness is higher among men, patients older than 65 years of age and in persons with other medical comorbidities. Cytokine storm cause pronounced lung damage and multiorgan failure. Coagulopathy is a key component of severe COVID-19. Critically ill patients are generally predisposed to a high risk of thromboembolism as well. Lymphopenia predisposes to severe disease. None of the antiviral or immunomodulators has proven efficacy in severe COVID-19. Supplemental oxygen need be administered in patients with hypoxemia. Excessive breathing effort, acute respiratory distress syndrome (ARDS), encephalopathy, and multiorgan failure are indications for mechanical ventilation. In a large number of patients, the overall outcome is poor. Health care workers in intensive care units are exposed to the enormous risk of acquiring hospital acquired SARS-COV-2 infection.

Hydroxychloroquine / azithromycin in COVID-19: The association between time to treatment and case fatality rate

BACKGROUND

Currently, there is no formally accepted pharmacological treatment for COVID-19.

MATERIALS AND METHODS

We included COVID-19 outpatients of a Peruvian primary care center from Lima, Peru, who were treated between April 30 - September 30, 2020, with hydroxychloroquine and azithromycin. Logistic regression was applied to determine factors associated with case-fatality rate.

RESULTS

A total of 1265 COVID-19 patients with an average age of 44.5 years were studied. Women represented 50.1% of patients, with an overall 5.9 symptom days, SpO2 97%, temperature of 37.3 °C, 41% with at least one comorbidity and 96.1% one symptom or sign. No patient treated within the first 72 h of illness died. The factors associated with higher case fatality rate were age (OR = 1.06; 95% CI 1.01-1.11, p = 0.021), SpO2 (OR = 0.87; 95% CI 0.79-0.96, p = 0.005) and treatment onset (OR = 1.16; 95% CI 1.06-1.27, p = 0.002), being the latter the only associated in the multivariate analysis (OR = 1.18; 95% CI 1.05-1.32, p = 0.005). 0.6% of our patients died.

CONCLUSIONS

The case fatality rate in COVID-19 outpatients treated with hydroxychloroquine/azithromycin was associated with the number of days of illness on which treatment was started.

Independent and combined effects of hypertension and diabetes on clinical outcomes in patients with COVID-19: A retrospective cohort study of Huoshen Mountain Hospital and Guanggu Fangcang Shelter Hospital

It is widely recognized that hypertension is one of the major risk factor for disease severity and mortality in patients with coronavirus disease 2019 (COVID‐19). However, type 2 diabetes mellitus (T2DM) and hypertension are frequent comorbid conditions, complicating the assessment of hypertension's individual contribution to the risk. The aims of this study were to evaluate the contributions of hypertension alone, T2DM alone, or their combination to the risk of death, acute respiratory distress syndrome (ARDS)/respiratory failure, and severe COVID‐19 infection. Additionally, we assessed risks associated with elevated blood pressure and fasting blood glucose on the same three clinical outcomes. Multivariate logistic models were used for these analyses. Among the 3400 patients, 3327(97.9%) survived and 73(2.1%) died. Compared to patients having neither hypertension nor T2DM (n = 1392), the risk of mortality was significantly higher in patients with T2DM alone (n = 226, OR 5.26 [95% CI: 2.39–11.58]) or with T2DM in combination with hypertension (n = 507, OR 3.02, [95% CI: 1.48–6.15]). Similarly, T2DM was a risk factor for development of ARDS/respiratory failure and severe infection. Hypertension alone (n = 1275) only conferred additional risk for the development of severe infection (OR 1.22 [95% CI: 1.00–1.51]). In conclusion, neither hypertension nor elevated blood pressure was independent risk factors for death or ARDS/respiratory failure but hypertension marginally increased the risk of severe COVID‐19 infection. The risk associated with hypertension is accentuated through its confounding effect on T2DM.

COVID-19 and Cardiovascular Comorbidities

The emergence of a new coronavirus - severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) - has resulted in a global pandemic. The associated coronavirus disease 2019 (COVID-19) has resulted in a high number of death worldwide. Observational studies and case reports have provided insights that older age and the presence of chronic diseases is frequently associated with a higher COVID-19 severity. These individuals also seem to have a higher risk of mortality due to COVID-19. In this review we provide insights into the impact chronic diseases associated with the cardiovascular system, such as obesity, diabetes mellitus, hypertension and cardiovascular disease might have on SARS-CoV-2 infection and COVID-19. Additionally we review recommendations and guidance's of international scientific associations and discuss which key learnings might be of importance for the future.

Predictors of in-hospital COVID-19 mortality: A comprehensive systematic review and meta-analysis exploring differences by age, sex and health conditions

OBJECTIVE

Risk factors for in-hospital mortality in confirmed COVID-19 patients have been summarized in numerous meta-analyses, but it is still unclear whether they vary according to the age, sex and health conditions of the studied populations. This study explored these variables as potential mortality predictors.

METHODS

A systematic review was conducted by searching the MEDLINE, Scopus, and Web of Science databases of studies available through July 27, 2020. The pooled risk was estimated with the odds ratio (p-OR) or effect size (p-ES) obtained through random-effects meta-analyses. Subgroup analyses and meta-regression were applied to explore differences by age, sex and health conditions. The MOOSE guidelines were strictly followed.

RESULTS

The meta-analysis included 60 studies, with a total of 51,225 patients (12,458 [24.3%] deaths) from hospitals in 13 countries. A higher in-hospital mortality risk was found for dyspnoea (p-OR = 2.5), smoking (p-OR = 1.6) and several comorbidities (p-OR range: 1.8 to 4.7) and laboratory parameters (p-ES range: 0.3 to -2.6). Age was the main source of heterogeneity, followed by sex and health condition. The following predictors were more markedly associated with mortality in studies with patients with a mean age ≤60 years: dyspnoea (p-OR = 4.3), smoking (p-OR = 2.8), kidney disease (p-OR = 3.8), hypertension (p-OR = 3.7), malignancy (p-OR = 3.7), diabetes (p-OR = 3.2), pulmonary disease (p-OR = 3.1), decreased platelet count (p-ES = -1.7), decreased haemoglobin concentration (p-ES = -0.6), increased creatinine (p-ES = 2.4), increased interleukin-6 (p-ES = 2.4) and increased cardiac troponin I (p-ES = 0.7). On the other hand, in addition to comorbidities, the most important mortality predictors in studies with older patients were albumin (p-ES = -3.1), total bilirubin (p-ES = 0.7), AST (p-ES = 1.8), ALT (p-ES = 0.4), urea nitrogen (p-ES), C-reactive protein (p-ES = 2.7), LDH (p-ES = 2.4) and ferritin (p-ES = 1.7). Obesity was associated with increased mortality only in studies with fewer chronic or critical patients (p-OR = 1.8).

CONCLUSION

The prognostic effect of clinical conditions on COVID-19 mortality vary substantially according to the mean age of patients.

PROSPERO REGISTRATION NUMBER

CRD42020176595.

No benefit of hydroxychloroquine in COVID-19: Results of Systematic Review and Meta-Analysis of Randomized Controlled Trials"

BACKGROUND AND AIMS

Coronavirus pandemic is currently a global public health emergency with no definitive treatment guidelines. We conducted a systematic review and meta-analysis of the literature evaluating the efficacy of hydroxychloroquine and its related formulations in COVID-19 patients.

METHODS

A systematic search of PubMed, Scopus, MedRxiv data and Cochrane Central Register of Clinical Trials for published articles that reported the outcomes of COVID-19 patients treated with hydroxychloroquine or its compounds was done. We identified 1071 published studies and 7 studies were included in the analysis.

RESULTS

The study population consisted of a total of 4984 patients, of which 1721 (34.5%) received hydroxychloroquine or its congeners (HCQ group) while 3091 (62.01%) received standard of care or had included antiviral medication (control group). The pooled estimate of successful treatment in the hydroxychloroquine group and the control group was 77.45% and 77.87% respectively, which indicated similar clinical outcomes in patients treated with hydroxychloroquine compared to the control group. The odds ratio of a favourable outcome with hydroxychloroquine was 1.11 (95 CI 0.72 to 1.69) (p = 0.20). The pooled risk difference of favourable outcome with hydroxychloroquine versus control group was 0.00 (95 CI -0.03 to 0.03) which was statistically not significant (p = 0.10).

CONCLUSIONS

The present evidence shows no benefit of hydroxychloroquine in patients affected by mild to moderate COVID-19 disease. However, now several trials on HCQ are ongoing and hopefully more data will be available soon. Hence, the management of COVID-19 is set to change for better in the future.

A proposed ABCD scoring system for better triage of patients with COVID-19: Use of clinical features and radiopathological findings

BACKGROUND AND AIMS

Currently there are limited tools available for triage of patients with COVID -19. We propose a new ABCD scoring system for patients who have been tested positive for COVID-19.

METHODS

The ABCD score is for patients who have been tested positive for COVID-19 and admitted in a hospital. This score includes age of the patient, blood tests included leukopenia, lymphocytopenia, CRP level, LDH level,D-Dimer, Chest radiograph and CT Scan, Comorbidities and Dyspnea.

RESULTS

The triage score had letters from alphabets which included A, B, C, D. The score was developed using these variables which outputs a value from 0 to 1. We had used the code according to traffic signal system; green(mild), yellow moderate) and red(severe). The suggestions for mild (green)category: symptomatic treatment in ward, in moderate (yellow) category: active treatment, semi critical care and oxygen supplementation, in severe (red) category: critical care and intensive care.

CONCLUSIONS

This study is, to our knowledge, is the first scoring tool that has been prepared by Indian health care processional's and used alphabets A, B,C,D as variables for evaluation of admitted patients with COVID-19. This triage tool will be helpful in better management of patients with COVID-19. This score component includes clinical and radiopathological findings.A multi-centre study is required to validate all available scoring systems.