Long-term mortality following SARS-CoV-2 infection: A national cohort study from Estonia

Dialysis parameters associated with SARS-CoV-2 infection and prognosis in end-stage kidney disease

BACKGROUND

The Covid-19 pandemic has affected patients with end-stage kidney disease (ESKD). Whether dialysis parameters have a prognostic value in ESKD patients with Covid-19 remains unclear.

MATERIALS AND METHODS

We retrospectively evaluated clinical characteristics, blood pressure (BP) and dialysis parameters in ESKD patients undergoing maintenance outpatient hemodialysis, with (Covid-ESKD) and without (No-Covid-ESKD) Covid-19, at four Brazilian hemodialysis facilities. The Covid-ESKD (n = 107; 54% females; 60.8 ± 17.7 years) and No-Covid-ESKD (n = 107; 62% females; 58.4 ± 14.6 years) groups were matched by calendar time. The average BP and dialysis parameters were calculated during the pre-infection, acute infection, and post-infection periods. The main outcomes were Covid-19 hospitalization and all-cause mortality.

RESULTS

Covid-ESKD patients had greater intradialytic and postdialysis systolic BP and lower predialysis weight, postdialysis weight, ultrafiltration rate, and interdialytic weight gain during acute-illness compared to 1-week-before-illness, while these changes were not observed in No-Covid-ESKD patients. After 286 days of follow-up (range, 276-591), there were 18 Covid-19-related hospitalizations and 28 deaths among Covid-ESKD patients. Multivariable logistic regression analysis showed that increases in predialysis systolic BP from 1-week-before-illness to acute-illness (OR, 95%CI = 1.06, 1.02-1.10; p = .004) and Covid-19 vaccination (OR, 95%CI = 0.16, 0.04-0.69; p = .014) were associated with hospitalization in Covid-ESKD patients. Multivariable Cox-regression analysis showed that Covid-19-related hospitalization (HR, 95%CI = 5.17, 2.07-12.96; p < .001) and age (HR, 95%CI = 1.05, 1.01-1.08; p = .008) were independent predictors of all-cause mortality in Covid-ESKD patients.

CONCLUSION

Acute Covid-19 illness is associated with variations in dialysis parameters of volume status in patients with ESKD. Furthermore, increases in predialysis BP during acute Covid-19 illness are associated with an adverse prognosis in Covid-ESKD patients.

Long-Term Mortality in Very Old Survivors of COVID-19

OBJECTIVES

This report aimed to describe mortality at 18 months in older survivors of the first wave of COVID-19.

DESIGN

Observational cohort study.

SETTING AND PARTICIPANTS

Patients aged ≥65 years hospitalized for COVID-19 in the acute geriatric wards of 2 centers.

METHODS

Characteristics of deceased and survivors were compared by Fisher exact, Mann-Whitney U, or 2-tailed t tests. Survival rates were analysed by Cox proportional hazards regression models.

RESULTS

Of a total of 323 patients admitted during the first wave, 196 survived the acute phase, with 34 patients who died in the 18 months after hospital discharge (17.3%). Higher mortality was observed in patients living in nursing homes (P = .033) and in those who were hospitalized after discharge during the follow-up period (97.1% vs 72.8%, P = .001). There was no difference in survival curves according to age, sex, presence of dyspnea, and dementia. Living in a nursing home significantly increased the mortality rates in the multivariate model adjusted for age and sex (hazard ratio 3.07, 95% CI 1.47-6.40; P = .007).

CONCLUSIONS AND IMPLICATIONS

No excess mortality was observed during 18 months in older survivors of COVID-19. Living in a nursing home was associated with decreased survival rates.

Cytokine profiles of mild-to-moderate SARS-CoV-2 infected and recovered pre-vaccinated individuals residing in Indonesia

Background

Accumulating evidence suggests the involvement of cytokine-mediated inflammation, in clinical severity and death related to SARS-CoV-2 infection, especially among pre-vaccinated individuals. An increased risk of death was also described among SARS-CoV-2 recovered individuals, which might be correlated with prolonged inflammatory responses. Despite being among the countries with the highest cumulative deaths due to COVID-19, evidence regarding cytokine profiles among SARS-CoV-2 infected and recovered pre-vaccinated individuals in Indonesia is scarce. Thus, this study aimed to describe the cytokines profiles of pre-vaccinated individuals residing in Indonesia, with mild-to-moderate SARS-CoV-2 infection and those who recovered.

Methods

Sixty-one sera from 24 hospitalized patients with mild-to-moderate SARS-CoV-2 infection, 24 individuals recovered from asymptomatic-to-moderate SARS-CoV-2 infection, and 13 healthy controls unexposed to SARS-CoV-2 were used in this study. Quantification of serum cytokine levels, including IL-6, IL-8, IP-10, TNF-α, CCL-2, CCL-3, CCL-4, and CXCL-13, was performed using a Luminex multi-analyte-profiling (xMAP)-based assay.

Results

The levels of IL-8 along with CCL-2 and CCL-4, were significantly higher (p ≤ 0.01) in hospitalized patients with mild-to-moderate SARS-CoV-2 infection and recovered individuals compared to healthy controls. However, no significant difference was observed in these cytokine levels between infected and recovered individuals. On the other hand, there were no significant differences in several other cytokine levels, including IL-6, IL-10, TNF-α, CCL-3, and CXCL-13, among all groups.

Conclusion

IL-8, CCL-2, and CCL-4 were significantly elevated in pre-vaccinated Indonesian individuals with mild-to-moderate SARS-CoV-2 infection and those who recovered. The cytokine profiles described in this study might indicate inflammatory responses not only among SARS-CoV-2 infected, but also recovered individuals.

Post-discharge all-cause mortality in COVID-19 recovered patients hospitalized in 2020: the impact of chronic kidney disease

In Brazil, the COVID-19 burden was substantial, and risk factors associated with higher in-hospital mortality rates have been extensively studied. However, information on short-term all-cause mortality and the factors associated with death in patients who survived the hospitalization period of acute SARS-CoV-2 infection is limited. We analyzed the six-month post-hospitalization mortality rate and possible risk factors of COVID-19 patients in a single center in Brazil. This is a retrospective cohort study focused on a six-month follow-up. The exclusion criteria were death during hospitalization, transference to another hospital, and age under 18. We collected data from the charts of all hospitalized patients from March 2020 to December 2020 with a positive RT-PCR test for SARS-CoV-2, resulting in a sample size of 106 patients. The main outcome was death after hospitalization, whereas comorbidities and demographics were evaluated as risk factors. The crude post-hospitalization death rate was 16%. The first 30 days of follow-up had the highest mortality rate. In a Cox regression model for post-hospitalization mortality, previous chronic kidney disease (HR, 4.06, 95%CI 1.46 - 11.30) and longer hospital stay (HR 1.01, 95%CI 1.00 - 1.02) were the only factors statistically associated with death. In conclusion, a high six-month all-cause mortality was observed. Within the six-month follow-up, a higher risk of death was observed for patients who had prior CKD and longer hospital stay. These findings highlight the importance of more intensive medical surveillance during this period.

Long-term outcomes of the global tuberculosis and COVID-19 co-infection cohort

BACKGROUND

Longitudinal cohort data of patients with tuberculosis (TB) and coronavirus disease 2019 (COVID-19) are lacking. In our global study, we describe long-term outcomes of patients affected by TB and COVID-19.

METHODS

We collected data from 174 centres in 31 countries on all patients affected by COVID-19 and TB between 1 March 2020 and 30 September 2022. Patients were followed-up until cure, death or end of cohort time. All patients had TB and COVID-19; for analysis purposes, deaths were attributed to TB, COVID-19 or both. Survival analysis was performed using Cox proportional risk-regression models, and the log-rank test was used to compare survival and mortality attributed to TB, COVID-19 or both.

RESULTS

Overall, 788 patients with COVID-19 and TB (active or sequelae) were recruited from 31 countries, and 10.8% (n=85) died during the observation period. Survival was significantly lower among patients whose death was attributed to TB and COVID-19 versus those dying because of either TB or COVID-19 alone (p<0.001). Significant adjusted risk factors for TB mortality were higher age (hazard ratio (HR) 1.05, 95% CI 1.03-1.07), HIV infection (HR 2.29, 95% CI 1.02-5.16) and invasive ventilation (HR 4.28, 95% CI 2.34-7.83). For COVID-19 mortality, the adjusted risks were higher age (HR 1.03, 95% CI 1.02-1.04), male sex (HR 2.21, 95% CI 1.24-3.91), oxygen requirement (HR 7.93, 95% CI 3.44-18.26) and invasive ventilation (HR 2.19, 95% CI 1.36-3.53).

CONCLUSIONS

In our global cohort, death was the outcome in >10% of patients with TB and COVID-19. A range of demographic and clinical predictors are associated with adverse outcomes.

Machine learning risk estimation and prediction of death in continuing care facilities using administrative data

In this study, we aimed to identify the factors that were associated with mortality among continuing care residents in Alberta, during the coronavirus disease 2019 (COVID-19) pandemic. We achieved this by leveraging and linking various administrative datasets together. Then, we examined pre-processing methods in terms of prediction performance. Finally, we developed several machine learning models and compared the results of these models in terms of performance. We conducted a retrospective cohort study of all continuing care residents in Alberta, Canada, from March 1, 2020, to March 31, 2021. We used a univariable and a multivariable logistic regression (LR) model to identify predictive factors of 60-day all-cause mortality by estimating odds ratios (ORs) with a 95% confidence interval. To determine the best sensitivity-specificity cut-off point, the Youden index was employed. We developed several machine learning models to determine the best model regarding performance. In this cohort study, increased age, male sex, symptoms, previous admissions, and some specific comorbidities were associated with increased mortality. Machine learning and pre-processing approaches offer a potentially valuable method for improving risk prediction for mortality, but more work is needed to show improvement beyond standard risk factors.

The use of prescription drugs and health care services during the 6-month post-COVID-19 period

COVID-19 and other acute respiratory viruses can have a long-term impact on health. We aimed to assess the common features and differences in the post-acute phase of COVID-19 compared with other non-chronic respiratory infections (RESP) using population-based electronic health data. We applied the self-controlled case series method where prescription drugs and health care utilisation were used as indicators of health outcomes during the six-month-long post-acute period. The incidence rate ratios of COVID-19 and RESP groups were compared. The analysis included 146 314 individuals. Out of 5452 drugs analysed, 14 had increased administration after COVID-19 with drugs for cardiovascular diseases (trimetazidine, metoprolol, rosuvastatin) and psychotropic drugs (alprazolam, zolpidem, melatonin) being most prevalent. The health impact of COVID-19 was more apparent among females and individuals with non-severe COVID-19. The increased risk of exacerbating pre-existing conditions was observed for the COVID-19 group. COVID-19 vaccination did not have effect on drug prescriptions but lowered the health care utilisation during post-acute period. Compared with RESP, COVID-19 increased the use of outpatient services during the post-infection period. The long-term negative impact of COVID-19 on life quality must be acknowledged, and supportive health care and public health services provided.

Epidemiological impacts of post-infection mortality

Infectious diseases may cause some long-term damage to their host, leading to elevated mortality even after recovery. Mortality due to complications from so-called 'long COVID' is a stark illustration of this potential, but the impacts of such post-infection mortality (PIM) on epidemic dynamics are not known. Using an epidemiological model that incorporates PIM, we examine the importance of this effect. We find that in contrast to mortality during infection, PIM can induce epidemic cycling. The effect is due to interference between elevated mortality and reinfection through the previously infected susceptible pool. In particular, robust immunity (via decreased susceptibility to reinfection) reduces the likelihood of cycling; on the other hand, disease-induced mortality can interact with weak PIM to generate periodicity. In the absence of PIM, we prove that the unique endemic equilibrium is stable and therefore our key result is that PIM is an overlooked phenomenon that is likely to be destabilizing. Overall, given potentially widespread effects, our findings highlight the importance of characterizing heterogeneity in susceptibility (via both PIM and robustness of host immunity) for accurate epidemiological predictions. In particular, for diseases without robust immunity, such as SARS-CoV-2, PIM may underlie complex epidemiological dynamics especially in the context of seasonal forcing.

The Role of Vaccination and Face Mask Wearing on COVID-19 Infection and Hospitalization: A Cross-Sectional Study of the MENA Region

Since the emergence of the Coronavirus disease (COVID-19) pandemic, the disease has affected more than 675 million people worldwide, including more than 6.87 million deaths. To mitigate the effects of this pandemic, many countries established control measures to contain its spread. Their riposte was based on a combination of pharmaceutical (vaccination) and non-pharmaceutical (such as facemask wearing, social distancing, and quarantine) measures. In this way, cross-sectional research was conducted in Algeria from 23 December 2021 to 12 March 2022 to investigate the effectiveness of preventative interventions in lowering COVID-19 infection and severity. More specifically, we investigated the link between mask-wearing and infection on one side, and the relationship between vaccination and the risk of hospitalization on the other. For this purpose, we used binary logistic regression modeling that allows learning the role of mask-wearing and vaccination in a heterogeneous society with respect to compliance with barrier measures. This study determined that wearing a mask is equally important for people of all ages. Further, findings revealed that the risk of infection was 0.79 times lower among those who were using masks (odds ratio (OR) = 0.79; confidence interval (CI) 95% = 0.668-0.936; p-value = 0.006). At the same time, vaccination is a necessary preventive measure as the risk of hospitalization increases with age. Compared with those who did not get vaccinated, those who got vaccinated were 0.429 times less likely to end up in the hospital (OR = 0.429; CI95% = 0.273-0.676; p < 0.0001). The model performance demonstrates significant relationships between the dependent and independent variables, with the absence of over-dispersion in both studied models, such as the Akaike Information Criterion (AIC) scores. These findings emphasize the significance of preventative measures and immunization in the battle against the COVID-19 pandemic.

Predictors of Mortality Among Post-COVID-19 Discharged Patients in Northern India: A Case-Control Study

Introduction The post-discharge all-cause mortality of COVID-19 disease is known, but predictors for the same have not been studied as much. The objective of this study was to develop an understanding of predictors of mortality to guide in prioritizing patient care and preventive approaches. Methods This current research is a single-center unmatched case-control study conducted at a tertiary care center in northern India, between April and September 2022. The data were extracted retrospectively from the hospital's electronic medical records of patients with the assistance of trained physicians using a standardized data extraction sheet. Results A total of 184 patients were enrolled and were segregated into two groups, cases and control, with 92 in each. The mean age of patients was 49.3 ± 17.53 years. The mortality group had a higher mean age (53.24 ± 18.53 yrs) as compared to the control group (45.37 ± 15.58 yrs, p=0.002). Bivariate analysis revealed a significant difference in the two groups with respect to O₂ saturation at the time of admission (case - 91.12 ± 12.49 %, control - 95.46 ± 5.01 %, p=0.003); maximum O₂ flow rate (L/min) (case - 11.01 ± 22.2, control - 6.41 ± 13.31, p=0.04); ICU need (p=0.005), cancer (p=0.001), O₂ requirement at discharge (p=0.001) and acute kidney injury (AKI; p=0.007). On multiple regression analysis, cancer (adjusted odds ratio (aOR) - 2.469; 95% CI 1.183-5.150, p=0.016), ICU admission (aOR - 2.446; 95% CI 1.212-4.938, p=0.013), oxygen at discharge (aOR - 2.340; 95% CI 0.971-5.640, p=0.0586) and AKI (aOR - 5.6; 95% CI 2.351- 13.370, p=0.00) only found to be significant. Conclusion Among the patients released from the hospital post-COVID-19 treatment, the following aspects oxygen requirement (2.3 times), malignancy (2.4 times), ICU admission (2.4 times), and AKI (5.6 times) are risk factors of mortality. The presence of these variables would warrant a close follow-up for these patients in order to decrease post-COVID mortality.

Vaccine-induced or hybrid immunity and COVID-19-associated mortality during the Omicron wave

BACKGROUND

It is not yet entirely clear to what extent vaccine-induced or hybrid immunity protects individuals in Germany from death during the omicron wave of the COVID-19 pandemic.

METHODS

In this retrospective study, we evaluated 470 159 cases over age 59 in the German federal state of Bavaria who tested positive for SARS-CoV-2 between 1 January and 30 June 2022. Cox models were used to estimate adjusted hazard ratios (aHR) for dying within 60 days of the infection, depending on sex, age, time point of infection, and a range of immunity levels.

RESULTS

Over the period of observation, 3836 COVID-19-associated deaths were registered (case fatality rate 0.82 %). Risk of death was significantly lower in cases with a higher immunity level than in unvaccinated cases (aHR for a full primary immunity level, if reached less than six months before the time of the infection: 0.30, 95 %-confidence interval [0.23; 0.39]; if reached more than six months before: aHR 0.46 [0.35; 0.60]). A boosted immunity level lowered risk of death even further (if reached less than three months before the infection: aHR 0.17 [0.15; 0.20]; if reached more than three months before: aHR 0.25 [0.21; 0.29]).

CONCLUSION

Among elderly persons in Bavaria, a higher immunity level was associated with a substantial degree of protection against death during the Omicron wave; the strength of protection may have diminished somewhat over time.

Direct and indirect effects of the COVID-19 pandemic on mortality in Switzerland

The direct and indirect impact of the COVID-19 pandemic on population-level mortality is of concern to public health but challenging to quantify. Using data for 2011-2019, we applied Bayesian models to predict the expected number of deaths in Switzerland and compared them with laboratory-confirmed COVID-19 deaths from February 2020 to April 2022 (study period). We estimated that COVID-19-related mortality was underestimated by a factor of 0.72 (95% credible interval [CrI]: 0.46-0.78). After accounting for COVID-19 deaths, the observed mortality was -4% (95% CrI: -8 to 0) lower than expected. The deficit in mortality was concentrated in age groups 40-59 (-12%, 95%CrI: -19 to -5) and 60-69 (-8%, 95%CrI: -15 to -2). Although COVID-19 control measures may have negative effects, after subtracting COVID-19 deaths, there were fewer deaths in Switzerland during the pandemic than expected, suggesting that any negative effects of control measures were offset by the positive effects. These results have important implications for the ongoing debate about the appropriateness of COVID-19 control measures.

Effective strategies against COVID-19 and the importance of infection sequelae

COVID-19 is a serious threat to human health and development. The acute burden of the pandemic includes more than 18.2 million deaths worldwide, and is unprecedented in modern times. This represents only a fraction of the total burden, as it excludes infection sequelae. An effective global strategic paradigm has been missing throughout the pandemic. The 'flattening the curve' approach neglected the importance of infection sequelae, and being centered on healthcare capacity was conceptually contrary to a people-centered health system. In March 2022, the World Health Organization revised its pandemic approach, importantly shifting emphasis away from managing transmission and towards prevention. Despite limitations, this now recognizes the role of infection sequelae, whose impact is becoming clearer in both variety and scale. Drawing on the foundational concepts of Sun Tzu and Carl von Clausewitz, most country approaches do not qualify as strategies, but rather as operational plans. They are also largely ineffective, neglecting infection sequelae, viral evolution dangers and other parameters. The purpose of this article is to summarize the evidence on COVID-19 infection sequelae, and alongside other contextual parameters use this to motivate that infection should be prevented. This is then used to answer the question: What is an effective strategy against COVID-19?

Risk Factors Associated With Six-Month Mortality in Hospitalized COVID-19 Patients: A Single-Institution Study

Background Coronavirus disease 2019 (COVID-19) infection can vary from asymptomatic infection to multi-organ dysfunction. The most serious complication of infection with COVID-19 is death. Various comorbid conditions and inflammatory markers have been associated with an increased risk of mortality, specifically within the immediate post-infection period; however, less is known about long-term mortality outcomes. Objectives Our objective is to determine risk factors associated with six-month mortality in hospitalized COVID-19 patients. Methods This is a single-institution, retrospective study. We included patients hospitalized with COVID-19 from the University of Toledo Medical Center in Toledo, Ohio, who were admitted from March 20, 2020, to June 30, 2021. This study was approved by a biomedical institutional review board at the University of Toledo. Patients with available pre-stored blood samples for laboratory testing were included, and hospital charts were assessed up to six months from the date of a positive COVID-19 test result. Two groups were created based on the mortality outcome at six months from COVID-19 positive test results: survivors and non-survivors. The clinical variables or outcomes and laboratory values were compared between the two groups using non-parametric methods due to the small sample size and non-normality of the data. Either the Mann-Whitney U-test for continuous variables or Fisher's exact test for categorical variables was used for statistical analysis. Results Lactate dehydrogenase (LDH) and D-dimer levels on admission were found to be significantly higher in non-survivors than in survivors. The median high D-dimer level in non-survivors was 5.96 micrograms/milliliter (μg/mL) (interquartile range (IQR): 3.95-11.29 μg/mL) vs 1.82 μg/mL (IQR 1.13-5.55 μg/mL) in survivors (p = 0.019). Median LDH levels were also higher in non-survivors vs survivors, i.e., 621.00 international units per liter (IU/L) (IQR 440.00-849.00 IU/L) vs 328.00 IU/L (IQR 274.00-529.00 IU/L), respectively (p = 0.032). The demographic profile, comorbidity profile, and laboratory data (typically associated with short-term mortality, inflammation, and organ dysfunction) were similar between survivors and non-survivors, except for LDH and D-dimer. Conclusion Higher LDH and D-dimer levels on admission were found to be associated with an increased six-month mortality rate in hospitalized COVID-19 patients. These hematologic data can serve as risk stratification tools to prevent long-term mortality outcomes and provide proactive clinical care in hospitalized COVID-19 patients.

Health-Related Quality of Life and Its Socio-Demographic and Behavioural Correlates during the COVID-19 Pandemic in Estonia

The aim of the study was to analyse health-related quality of life (HRQoL) among the Estonian general population and its socio-demographic and behavioural correlates during the COVID-19 pandemic. Longitudinal data on 1781 individuals from an Estonian rapid-assessment survey on COVID-19 were used. HRQoL was assessed with the EQ-5D-3L in June 2020 (baseline) and in May 2021 (follow-up). The HRQoL index score and its socio-demographic and behavioural variations were analysed using paired t-tests and Tobit regression modelling. Statistically significant declines in mean EQ-5D index scores were observed for all socio-demographic and behavioural variables considered. Most of these changes were due to increased reporting of problems in the pain/discomfort and anxiety/depression health domains. Older age, being unemployed or economically non-active and having financial difficulties were significantly associated with lower HRQoL in both baseline and follow-up measurements. In the follow-up data, women had significantly lower HRQoL compared to men, whereas higher education proved to be the only protective factor regarding HRQoL. Unhealthy dietary habits and low physical activity had a negative impact on the HRQoL score in the follow-up data. These results indicate that the COVID-19 pandemic has had a substantial impact on HRQoL in the Estonian population.