Research Note: COVID-19 Is Not an Independent Cause of Death.

The COVID-19 pandemic has had overwhelming global impacts with deleterious social, economic, and health consequences. To assess the COVID-19 death toll, researchers have estimated declines in 2020 life expectancy at birth (e0). When data are available only for COVID-19 deaths, but not for deaths from other causes, the risks of dying from COVID-19 are typically assumed to be independent of those from other causes. In this research note, we explore the soundness of this assumption using data from the United States and Brazil, the countries with the largest number of reported COVID-19 deaths. We use three methods: one estimates the difference between 2019 and 2020 life tables and therefore does not require the assumption of independence, and the other two assume independence to simulate scenarios in which COVID-19 mortality is added to 2019 death rates or is eliminated from 2020 rates. Our results reveal that COVID-19 is not independent of other causes of death. The assumption of independence can lead to either an overestimate (Brazil) or an underestimate (United States) of the decline in e0, depending on how the number of other reported causes of death changed in 2020.

Excess years of life lost to COVID-19 and other causes of death by sex, neighbourhood deprivation, and region in England and Wales during 2020: A registry-based study.

BACKGROUND: Deaths in the first year of the Coronavirus Disease 2019 (COVID-19) pandemic in England and Wales were unevenly distributed socioeconomically and geographically. However, the full scale of inequalities may have been underestimated to date, as most measures of excess mortality do not adequately account for varying age profiles of deaths between social groups. We measured years of life lost (YLL) attributable to the pandemic, directly or indirectly, comparing mortality across geographic and socioeconomic groups. METHODS AND FINDINGS: We used national mortality registers in England and Wales, from 27 December 2014 until 25 December 2020, covering 3,265,937 deaths. YLLs (main outcome) were calculated using 2019 single year sex-specific life tables for England and Wales. Interrupted time-series analyses, with panel time-series models, were used to estimate expected YLL by sex, geographical region, and deprivation quintile between 7 March 2020 and 25 December 2020 by cause: direct deaths (COVID-19 and other respiratory diseases), cardiovascular disease and diabetes, cancer, and other indirect deaths (all other causes). Excess YLL during the pandemic period were calculated by subtracting observed from expected values. Additional analyses focused on excess deaths for region and deprivation strata, by age-group. Between 7 March 2020 and 25 December 2020, there were an estimated 763,550 (95% CI: 696,826 to 830,273) excess YLL in England and Wales, equivalent to a 15% (95% CI: 14 to 16) increase in YLL compared to the equivalent time period in 2019. There was a strong deprivation gradient in all-cause excess YLL, with rates per 100,000 population ranging from 916 (95% CI: 820 to 1,012) for the least deprived quintile to 1,645 (95% CI: 1,472 to 1,819) for the most deprived. The differences in excess YLL between deprivation quintiles were greatest in younger age groups; for all-cause deaths, a mean of 9.1 years per death (95% CI: 8.2 to 10.0) were lost in the least deprived quintile, compared to 10.8 (95% CI: 10.0 to 11.6) in the most deprived; for COVID-19 and other respiratory deaths, a mean of 8.9 years per death (95% CI: 8.7 to 9.1) were lost in the least deprived quintile, compared to 11.2 (95% CI: 11.0 to 11.5) in the most deprived. For all-cause mortality, estimated deaths in the most deprived compared to the most affluent areas were much higher in younger age groups, but similar for those aged 85 or over. There was marked variability in both all-cause and direct excess YLL by region, with the highest rates in the North West. Limitations include the quasi-experimental nature of the research design and the requirement for accurate and timely recording. CONCLUSIONS: In this study, we observed strong socioeconomic and geographical health inequalities in YLL, during the first calendar year of the COVID-19 pandemic. These were in line with long-standing existing inequalities in England and Wales, with the most deprived areas reporting the largest numbers in potential YLL.

Current forecast of COVID-19 in Mexico: A Bayesian and machine learning approaches.

The COVID-19 pandemic has been widely spread and affected millions of people and caused hundreds of deaths worldwide, especially in patients with comorbilities and COVID-19. This manuscript aims to present models to predict, firstly, the number of coronavirus cases and secondly, the hospital care demand and mortality based on COVID-19 patients who have been diagnosed with other diseases. For the first part, I present a projection of the spread of coronavirus in Mexico, which is based on a contact tracing model using Bayesian inference. I investigate the health profile of individuals diagnosed with coronavirus to predict their type of patient care (inpatient or outpatient) and survival. Specifically, I analyze the comorbidity associated with coronavirus using Machine Learning. I have implemented two classifiers: I use the first classifier to predict the type of care procedure that a person diagnosed with coronavirus presenting chronic diseases will obtain (i.e. outpatient or hospitalised), in this way I estimate the hospital care demand; I use the second classifier to predict the survival or mortality of the patient (i.e. survived or deceased). I present two techniques to deal with these kinds of unbalanced datasets related to outpatient/hospitalised and survived/deceased cases (which occur in general for these types of coronavirus datasets) to obtain a better performance for the classification.

Resolving the equation between mucormycosis and COVID-19 disease.

The COVID-19 patients, both infected and recovered are rapidly contracting mucormycetes infections due to the 'Mucorales' order, under Zygomycetes class of fungi. The mucorales fungi commonly known to exist in our natural surroundings including soil, but the frequency of incidences was never rampant. This sudden spike in infections, is locally known as 'black fungus,' and is affecting various organs, including- eyes, sinuses, nose, brain, skin, intestine, lungs, etc. The severity of situation is ascertainable from the fact that, in certain cases surgical eye/jaws removal persists as the only viable option to avert mortality, as therapeutic interventions are limited. This epidemic situation intrigued experts to investigate the probable reason behind this unpredicted escalation in reported cases, including in recuperated COVID-19 patients, as person-to-person spread of infection is not common. The comparison of physiological parameters in healthy and COVID-19 afflicted patients highlights that the underlying conditions including diabetes mellitus, steroidal therapy, lymphopenia (decreased CD4+ and CD8+ lymphocytes), deregulated cytokine release storm, elevated free iron levels (hemosiderosis) in blood and insulin insensitivity are playing major roles in deteriorating conditions in rarely pathogenic fungal infections. This review is an attempt to explain the rationalities that makes people vulnerable to mucormycetes infection.

Impact of diabetes mellitus on in-hospital mortality in adult patients with COVID-19: a systematic review and meta-analysis.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) has spread worldwide since the beginning of 2020, placing the heavy burden on the health systems all over the world. The population that particularly has been affected by the pandemic is the group of patients suffering from diabetes mellitus. Having taken the public health in considerations, we have decided to perform a systematic review and meta-analysis of diabetes mellitus on in-hospital mortality in patients with COVID-19. METHODS: A systematic literature review (MEDLINE, EMBASE, Web of Science, Scopus, Cochrane) including all published clinical trials or observational studies published till December 10, 2020, was performed using following terms "diabetes mellitus" OR "diabetes" OR "DM" AND "survival" OR "mortality" AND "SARS-CoV-2" OR "COVID-19". RESULTS: Nineteen studies were included out of the 7327 initially identified studies. Mortality of DM patients vs non-DM patients was 21.3 versus 6.1%, respectively (OR = 2.39; 95%CI: 1.65, 3.64; P < 0.001), while severe disease in DM and non-DM group varied and amounted to 34.8% versus 22.8% (OR = 1.43; 95%CI: 0.82, 2.50; P = 0.20). In the DM group, the complications were observed far more often when compared with non-DM group, both in acute respiratory distress (31.4 vs. 17.2%; OR = 2.38; 95%CI:1.80, 3.13; P < 0.001), acute cardiac injury (22.0% vs. 12.8%; OR = 2.59; 95%CI: 1.81, 3.73; P < 0.001), and acute kidney injury (19.1 vs. 10.2%; OR = 1.97; 95%CI: 1.36, 2.85; P < 0.001). CONCLUSIONS: Based on the findings, we shall conclude that diabetes is an independent risk factor of the severity of COVID-19 in-hospital settings; therefore, patients with diabetes shall aim to reduce the exposure to the potential infection of COVID-19.

Mortality and Clinical Outcomes among Patients with COVID-19 and Diabetes.

Background Diabetes mellitus (DM) is a decisive risk factor for severe illness in coronavirus disease 2019 (COVID-19). India is home to a large number of people with DM, and many of them were infected with COVID-19. It is critical to understand the impact of DM on mortality and other clinical outcomes of COVID-19 infection from this region. Aims The primary objective of our study was to analyze the mortality rate in people with DM infected with COVID-19. The secondary objectives were to assess the effect of various comorbidities on mortality and study the impact of DM on other clinical outcomes. Methods This is a retrospective study of COVID-19 infected patients admitted to a tertiary care hospital in north India in the early phase of the pandemic. Results Of the 1211 cases admitted, 19 were excluded because of incomplete data, and 1192 cases were finally considered for analysis. DM constituted 26.8% of total patients. The overall mortality rate was 6.1%, and the rate was 10.7% in the presence of diabetes (p < 0.01, OR 2.55). In univariate analysis, increased age, chronic kidney disease (CKD), coronary artery disease (CAD), stroke, and cancer were associated with mortality. On multiple logistic regression, the independent predictors of mortality were CAD, CKD, and cancer. Breathlessness and low SpO2 at presentation, extensive involvement in CXR, and elevated ANC/ALC ratio were also significantly associated with mortality. Conclusions The presence of comorbidities such as DM, hypertension, CAD, CKD, and cancer strongly predict the risk of mortality in COVID-19 infection. Early triaging and aggressive therapy of patients with these comorbidities can optimize clinical outcomes.

COVID-19-Induced New-Onset Diabetes: Trends and Technologies.

The coronavirus disease 2019 (COVID-19) global pandemic continues to spread worldwide with approximately 216 million confirmed cases and 4.49 million deaths to date. Intensive efforts are ongoing to combat this disease by suppressing viral transmission, understanding its pathogenesis, developing vaccination strategies, and identifying effective therapeutic targets. Individuals with preexisting diabetes also show higher incidence of COVID-19 illness and poorer prognosis upon infection. Likewise, an increased frequency of diabetes onset and diabetes complications has been reported in patients following COVID-19 diagnosis. COVID-19 may elevate the risk of hyperglycemia and other complications in patients with and without prior diabetes history. It is unclear whether the virus induces type 1 or type 2 diabetes or instead causes a novel atypical form of diabetes. Moreover, it remains unknown if recovering COVID-19 patients exhibit a higher risk of developing new-onset diabetes or its complications going forward. The aim of this review is to summarize what is currently known about the epidemiology and mechanisms of this bidirectional relationship between COVID-19 and diabetes. We highlight major challenges that hinder the study of COVID-19-induced new-onset of diabetes and propose a potential framework for overcoming these obstacles. We also review state-of-the-art wearables and microsampling technologies that can further study diabetes management and progression in new-onset diabetes cases. We conclude by outlining current research initiatives investigating the bidirectional relationship between COVID-19 and diabetes, some with emphasis on wearable technology.

Low mortality of people living with diabetes mellitus diagnosed with COVID-19 and managed at a field hospital in Western Cape Province, South Africa.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) was declared an international pandemic by the World Health Organization in March 2020. Throughout the pandemic, the association between diabetes mellitus (DM) and more severe COVID-19 has been well described internationally, with limited data, however, on South Africa (SA). The role of field hospitals in the management of patients with COVID-19 in SA has not yet been described. OBJECTIVES: To describe the mortality and morbidity of people living with DM (PLWD) and comorbid COVID-19, as well as to shed light on the role of intermediate facilities in managing DM and COVID-19 during the pandemic. METHODS: This is a single-centre cross-sectional descriptive study that included all patients with confirmed COVID-19 and pre-existing or newly diagnosed DM (of any type) admitted to the Cape Town International Convention Centre (CTICC) Intermediate Care Bed Facility from June 2020 to August 2020. This study presents the profile of patients admitted to the CTICC, and reports on the clinical outcome of PLWD diagnosed with COVID-19, and additionally determines some associations between risk factors and death or escalation of care in this setting. RESULTS: There were 1 447 admissions at the CTICC, with a total of 674 (46.6%) patients who had confirmed DM, of whom 125 (19%) were newly diagnosed diabetics and 550 (81%) had pre-existing DM. Included in this group were 57 referrals from the telemedicine platform - a platform that identified high-risk diabetic patients with COVID-19 in the community, and linked them directly to hospital inpatient care. Of the 674 PLWD admitted, 593 were discharged alive, 45 were escalated to tertiary hospital requiring advanced care and 36 died. PLWD who died were older, had more comorbidities (specifically chronic obstructive pulmonary disease, congestive cardiac failure and chronic kidney disease) and were more likely to be on insulin. CONCLUSIONS: In a resource-limited environment, interdisciplinary and interfacility collaboration ensured that complicated patients with DM and COVID-19 were successfully managed in a field hospital setting. Telemedicine offered a unique opportunity to identify high-risk patients in the community and link them to in-hospital monitoring and care. Future studies should explore ways to optimise this collaboration, as well as to explore possibilities for early identification and management of high-risk patients.

CXCL10 levels at hospital admission predict COVID-19 outcome: hierarchical assessment of 53 putative inflammatory biomarkers in an observational study.

BACKGROUND: Host inflammation contributes to determine whether SARS-CoV-2 infection causes mild or life-threatening disease. Tools are needed for early risk assessment. METHODS: We studied in 111 COVID-19 patients prospectively followed at a single reference Hospital fifty-three potential biomarkers including alarmins, cytokines, adipocytokines and growth factors, humoral innate immune and neuroendocrine molecules and regulators of iron metabolism. Biomarkers at hospital admission together with age, degree of hypoxia, neutrophil to lymphocyte ratio (NLR), lactate dehydrogenase (LDH), C-reactive protein (CRP) and creatinine were analysed within a data-driven approach to classify patients with respect to survival and ICU outcomes. Classification and regression tree (CART) models were used to identify prognostic biomarkers. RESULTS: Among the fifty-three potential biomarkers, the classification tree analysis selected CXCL10 at hospital admission, in combination with NLR and time from onset, as the best predictor of ICU transfer (AUC [95% CI] = 0.8374 [0.6233-0.8435]), while it was selected alone to predict death (AUC [95% CI] = 0.7334 [0.7547-0.9201]). CXCL10 concentration abated in COVID-19 survivors after healing and discharge from the hospital. CONCLUSIONS: CXCL10 results from a data-driven analysis, that accounts for presence of confounding factors, as the most robust predictive biomarker of patient outcome in COVID-19.

Does diabetes mellitus mitigate the gender gap in COVID-19 mortality?

In this SARS-COV2-pandemic, diabetes mellitus (DM) soon emerged as one of the most prominent risk factors for a severe course of corona virus disease-2019 (COVID-19) and increased mortality due to hyperglycemia/insulin resistance, obesity, inflammation, altered immune status, and cardiovascular complications. In general, men are at a higher risk of severe or fatal COVID-19 disease irrespective of age, region and despite comparable infection rates in both sexes. In COVID-19, there is also a male predominance among hospitalized patients with diabetes, however, overall, data among patients with diabetes are ambiguous so far. Of note, similar to cardiovascular complications, women with type 2 diabetes (DM2) appear to lose their biological female advantage resulting in comparable death rates to those of men. The complex interplay of biological and behavioral factors, which may put men at greater risk of a severe or fatal course of COVID-19, and gender-related psychosocial factors, which may cause disadvantage to women concerning the infection rates, might explain why sex-disaggregated data among infected patients with diabetes are conflicting. Better knowledge on biological factors leading to functionally different immune responses and of gender-sensitive sociocultural determinants of COVID-19 infection rates may help to optimize prevention and management in the high-risk groups of men and women with diabetes.

Mortality risk factors of COVID-19 infection in kidney transplantation recipients: a systematic review and meta-analysis of cohorts and clinical registries.

Kidney transplantation recipients (KTR) with coronavirus disease 2019 (COVID-19) are at higher risk of death than general population. However, mortality risk factors in KTR are still not clearly identified. Our objective was to systematically analyze published evidence for risk factors associated with mortality in COVID-19 KTR. Electronic databases were searched for eligible studies on 1 August 2021. All prospective and retrospective studies of COVID-19 in KTR were considered eligible without language restriction. Since data in case reports and series could potentially be subsets of larger studies, only studies with ≥ 50 patients were included. Random-effects model meta-analysis was used to calculate weighted mean difference (WMD) and pooled odds ratio (OR) of factors associated with mortality. From a total 1,137 articles retrieved, 13 were included in the systematic review and meta-analysis comprising 4,440 KTR. Compared with survivors, non-survivors were significantly older (WMD 10.5 years, 95% CI 9.3-11.8). KTR of deceased donor were at higher risk of death (OR 1.73, 95% CI 1.10-2.74). Comorbidities including diabetes mellitus, cardiovascular disease, and active cancer significantly increased mortality risk. KTR with dyspnea (OR 5.68, 95% CI 2.11-15.33) and pneumonia (OR 10.64, 95% CI 3.37-33.55) at presentation were at higher mortality risk, while diarrhea decreased the risk (OR 0.61, 95% CI 0.47-0.78). Acute kidney injury was associated with mortality (OR 3.24, 95% CI 1.36-7.70). Inflammatory markers were significantly higher in the non-survivors, including C-reactive protein, procalcitonin, and interleukine-6. A number of COVID-19 mortality risk factors were identified from KTR patient characteristics, presenting symptoms, and laboratory investigations. KTR with these risk factors should receive more intensive monitoring and early therapeutic interventions to optimize health outcomes.

Prognostic Value of Leucocyte to High-Density Lipoprotein-Cholesterol Ratios in COVID-19 Patients and the Diabetes Subgroup.

Background: Blood parameters, such as neutrophil-to-lymphocyte ratio, have been identified as reliable inflammatory markers with diagnostic and predictive value for the coronavirus disease 2019 (COVID-19). However, novel hematological parameters derived from high-density lipoprotein-cholesterol (HDL-C) have rarely been studied as indicators for the risk of poor outcomes in patients with severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) infection. Here, we aimed to assess the prognostic value of these novel biomarkers in COVID-19 patients and the diabetes subgroup. Methods: We conducted a multicenter retrospective cohort study involving all hospitalized patients with COVID-19 from January to March 2020 in five hospitals in Wuhan, China. Demographics, clinical and laboratory findings, and outcomes were recorded. Neutrophil to HDL-C ratio (NHR), monocyte to HDL-C ratio (MHR), lymphocyte to HDL-C ratio (LHR), and platelet to HDL-C ratio (PHR) were investigated and compared in both the overall population and the subgroup with diabetes. The associations between blood parameters at admission with primary composite end-point events (including mechanical ventilation, admission to the intensive care unit, or death) were analyzed using Cox proportional hazards regression models. Receiver operating characteristic curves were used to compare the utility of different blood parameters. Results: Of 440 patients with COVID-19, 67 (15.2%) were critically ill. On admission, HDL-C concentration was decreased while NHR was high in patients with critical compared with non-critical COVID-19, and were independently associated with poor outcome as continuous variables in the overall population (HR: 0.213, 95% CI 0.090-0.507; HR: 1.066, 95% CI 1.030-1.103, respectively) after adjusting for confounding factors. Additionally, when HDL-C and NHR were examined as categorical variables, the HRs and 95% CIs for tertile 3 vs. tertile 1 were 0.280 (0.128-0.612) and 4.458 (1.817-10.938), respectively. Similar results were observed in the diabetes subgroup. ROC curves showed that the NHR had good performance in predicting worse outcomes. The cutoff point of the NHR was 5.50. However, the data in our present study could not confirm the possible predictive effect of LHR, MHR, and PHR on COVID-19 severity. Conclusion: Lower HDL-C concentrations and higher NHR at admission were observed in patients with critical COVID-19 than in those with noncritical COVID-19, and were significantly associated with a poor prognosis in COVID-19 patients as well as in the diabetes subgroup.

Detrimental effect of diabetes and hypertension on the severity and mortality of COVID-19 infection: A multi-center case-control study from India.

AIMS: This study aims to find a quantitative association between the presence of co-existing diabetes mellitus (DM) and/or hypertension (HTN) with COVID-19 infection severity and mortality. METHODS: A total of 813 patients with a positive COVID-19 were included. A case-control design was used to dissect the association between DM and HTN with COVID-19 severity and mortality. RESULTS: According to MOHFW guidelines, 535 (65.7%) patients had mild, 160 (19.7%) patients had moderate, and 118 (14.5%) patients had severe disease outcomes including mortality in 52 patients. Age, Neutrophil%, and Diabetes status were significantly associated with severe COVID-19 infection. After adjusting for age, patients with diabetes were 2.46 times more likely to have severe disease (Chi-squared = 18.89, p-value<0.0001) and 2.11 times more likely to have a fatal outcome (Chi-squared = 6.04, p-value = 0.014). However, we did not find evidence for Hypertension modifying the COVID-19 outcomes in Diabetic patients. CONCLUSION: COVID-19 severity and mortality both were significantly associated with the status of DM and its risk may not be modified by the presence of HTN.

Clinical outcomes in patients infected with different SARS-CoV-2 variants at one hospital during three phases of the COVID-19 epidemic in Marseille, France.

OBJECTIVES: To compare the demographics, clinical characteristics and severity of patients infected with nine different SARS-CoV-2 variants, during three phases of the COVID-19 epidemic in Marseille. METHODS: A single centre retrospective cohort study was conducted in 1760 patients infected with SARS-CoV-2 of Nextstrain clades 20A, 20B, and 20C (first phase, February-May 2020), Pangolin lineages B.1.177 (we named Marseille-2) and B.1.160 (Marseille-4) variants (second phase, June-December 2020), and B.1.1.7 (alpha), B.1.351 (beta), P.1 (gamma) and A.27 (Marseille-501) variants (third phase, January 2021-today). Outcomes were the occurrence of clinical failures, including hospitalisation, transfer to the intensive-care unit, and death. RESULTS: During each phase, no major differences were observed with regards to age and gender distribution, the prevalence of chronic diseases, and clinical symptoms between variants circulating in a given phase. The B.1.177 and B.1.160 variants were associated with more severe outcomes. Infections occurring during the second phase were associated with a higher rate of death as compared to infections during the first and third phases. Patients in the second phase were more likely to be hospitalised than those in the third phase. Patients infected during the third phase were more frequently obese than others. CONCLUSION: A large cohort study is recommended to evaluate the transmissibility and to better characterise the clinical severity of emerging variants.

Diabetes Mellitus and COVID-19: Review Article.

BACKGROUND AND AIMS: We aim to cover most of the current evidence on the mutual effect of diabetes & COVID-19 infection on each other and the management of the COVID-19 patients with diabetes. METHODS: We utilized databases to review the current evidence related to diabetes mellitus and COVID-19. RESULTS: We discussed the most recent evidence of diabetes milieus and COVID-19 regarding risk factors, management, complications, and telemedicine. CONCLUSION: Diabetes mellitus is associated with a significant risk of complications, extended hospital stays, and mortality in COVID-19 infected patients.

High Fibrosis-4 Index Is Related with Worse Clinical Outcome in Patients with Coronavirus Disease 2019 and Diabetes Mellitus: A Multicenter Observational Study.

BACKGROUND: Based on recent evidence on the importance of the presence of diabetes mellitus (DM) and fibrosis-4 (FIB-4) index in coronavirus disease 2019 (COVID-19) mortality, we analyzed whether these factors could additively predict such mortality. METHODS: This multicenter observational study included 1,019 adult inpatients admitted to university hospitals in Daegu. The demographic and laboratory findings, mortality, prevalence of severe disease, and duration of quarantine were compared between patients with and without DM and/or a high FIB-4 index. The mortality risk and corresponding hazard ratio (HR) were analyzed using the Kaplan-Meier method and Cox proportional hazard models. RESULTS: The patients with DM (n=217) exhibited significantly higher FIB-4 index and mortality compared to those without DM. Although DM (HR, 2.66; 95% confidence interval [CI], 1.63 to 4.33) and a high FIB-4 index (HR, 4.20; 95% CI, 2.21 to 7.99) were separately identified as risk factors for COVID-19 mortality, the patients with both DM and high FIB-4 index had a significantly higher mortality (HR, 9.54; 95% CI, 4.11 to 22.15). Higher FIB-4 indices were associated with higher mortality regardless of DM. A high FIB-4 index with DM was more significantly associated with a severe clinical course with mortality (odds ratio, 11.24; 95% CI, 5.90 to 21.41) than a low FIB-4 index without DM, followed by a high FIB-4 index alone and DM alone. The duration of quarantine and hospital stay also tended to be longer in those with both DM and high FIB-4 index. CONCLUSION: Both DM and high FIB-4 index are independent and additive risk factors for COVID-19 mortality.

Decreased in-hospital mortality associated with aspirin administration in hospitalized patients due to severe COVID-19.

Hypercoagulability and thrombosis caused by coronavirus disease 2019 (COVID-19) are related to the higher mortality rate. Because of limited data on the antiplatelet effect, we aimed to evaluate the impact of aspirin add-on therapy on the outcome of the patients hospitalized due to severe COVID-19. In this cohort study, patients with a confirmed diagnosis of severe COVID-19 admitted to Imam Hossein Medical Center, Tehran, Iran from March 2019 to July 2020 were included. Demographics and related clinical data during their hospitalization were recorded. The mortality rate of the patients was considered as the primary outcome and its association with aspirin use was assessed. Nine hundred and ninety-one patients were included, of that 336 patients (34%) received aspirin during their hospitalization and 655 ones (66%) did not. Comorbidities were more prevalent in the patients who were receiving aspirin. Results from the multivariate COX proportional model demonstrated a significant independent association between aspirin use and reduction in the risk of in-hospital mortality (0.746 [0.560-0.994], p = 0.046). Aspirin use in hospitalized patients with COVID-19 is associated with a significant decrease in mortality rate. Further prospective randomized controlled trials are needed to assess the efficacy and adverse effects of aspirin administration in this population.

Morbidity and mortality outcomes of COVID-19 patients with and without hypertension in Lagos, Nigeria: a retrospective cohort study.

BACKGROUND: The current pandemic of coronavirus disease (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has shown epidemiological and clinical characteristics that appear worsened in hypertensive patients. The morbidity and mortality of the disease among hypertensive patients in Africa have yet to be well described. METHODS: In this retrospective cohort study all confirmed COVID-19 adult patients (≥18 years of age) in Lagos between February 27 to July 62,020 were included. Demographic, clinical and outcome data were extracted from electronic medical records of patients admitted at the COVID-19 isolation centers in Lagos. Outcomes included dying, being discharged after recovery or being evacuated/transferred. Descriptive statistics considered proportions, means and medians. The Chi-square and Fisher's exact tests were used in determining associations between variables. Kaplan-Meier survival analysis and Cox regression were performed to quantify the risk of worse outcomes among hypertensives with COVID-19 and adjust for confounders. P-value ≤0.05 was considered statistically significant. RESULTS: A total of 2075 adults with COVID-19 were included in this study. The prevalence of hypertension, the most common comorbidity, was 17.8% followed by diabetes (7.2%) and asthma (2.0%). Overall mortality was 4.2% while mortality among the hypertensives was 13.7%. Severe symptoms and mortality were significantly higher among the hypertensives and survival rates were significantly lowered by the presence of additional comorbidity to 50% from 91% for those with hypertension alone and from 98% for all other patients (P < 0.001). After adjustment for confounders (age and sex), severe COVID-19and death were higher for hypertensives {severe/critical illness: HR = 2.41, P = 0.001, 95%CI = 1.4-4.0, death: HR = 2.30, P = 0.001, 95%CI = 1.2-4.6, for those with hypertension only} {severe/critical illness: HR = 3.76, P = 0.001, 95%CI = 2.1-6.4, death: crude HR = 6.63, P = 0.001, 95%CI = 3.4-1.6, for those with additional comorbidities}. Hypertension posed an increased risk of severe morbidity (approx. 4-fold) and death (approx. 7-fold) from COVID-19 in the presence of multiple comorbidities. CONCLUSION: The potential morbidity and mortality risks of hypertension especially with other comorbidities in COVID-19 could help direct efforts towards prevention and prognostication. This provides the rationale for improving preventive caution for people with hypertension and other comorbidities and prioritizing them for future antiviral interventions.

Hyperglycaemia increases mortality risk in non-diabetic patients with COVID-19 even more than in diabetic patients.

AIM: Diabetes has been identified as a risk factor for poor outcomes in patients with COVID-19. We examined the association of hyperglycaemia, both in the presence and absence of pre-existing diabetes, with severity and outcomes in COVID-19 patients. METHODS: Data from 74,148 COVID-19-positive inpatients with at least one recorded glucose measurement during their inpatient episode were analysed for presence of pre-existing diabetes diagnosis and any glucose values in the hyperglycaemic range (>180 mg/dl). RESULTS: Among patients with and without a pre-existing diabetes diagnosis on admission, mortality was substantially higher in the presence of high glucose measurements versus all measurements in the normal range (70-180 mg/dl) in both groups (non-diabetics: 21.7% vs. 3.3%; diabetics 14.4% vs. 4.3%). When adjusting for patient age, BMI, severity on admission and oxygen saturation on admission, this increased risk of mortality persisted and varied by diabetes diagnosis. Among patients with a pre-existing diabetes diagnosis, any hyperglycaemic value during the episode was associated with a substantial increase in the odds of mortality (OR: 1.77, 95% CI: 1.52-2.07); among patients without a pre-existing diabetes diagnosis, this risk nearly doubled (OR: 3.07, 95% CI: 2.79-3.37). CONCLUSION: This retrospective analysis identified hyperglycaemia in COVID-19 patients as an independent risk factor for mortality after adjusting for the presence of diabetes and other known risk factors. This indicates that the extent of glucose control could serve as a mechanism for modifying the risk of COVID-19 morality in the inpatient environment.