A turning point in COVID-19 severity and fatality during the pandemic: A national cohort study in Qatar (preprint)

Background: This study assessed the evolution of COVID-19 severity and fatality by utilizing rigorous and standardized criteria that were consistently applied throughout the pandemic in Qatar. Methods: A national cohort study was conducted on Qataris, using data on COVID-19 acute-care and ICU hospitalizations, as well as severe, critical, and fatal COVID-19 cases classified according to the World Health Organization criteria. Results: The cumulative incidence of severe, critical, or fatal COVID-19 after 3.14 years of follow-up was 0.45% (95% CI: 0.43-0.47%). The incidence rate for severe, critical, or fatal COVID-19 throughout the pandemic was 1.43 (95% CI: 1.35-1.50) per 1,000 person-years. In the pre-omicron phase, first omicron wave, and combined phases, it was 2.01 (95% CI: 1.90-2.13), 3.70 (95% CI: 3.25-4.22), and 2.18 (95% CI: 2.07-2.30) per 1,000 person-years, respectively. The post-first omicron phase saw a drastic drop to 0.10 (95% CI: 0.08-0.14) per 1,000 person-years, a 95.4% reduction. Among all severe, critical, and fatal cases, 99.5% occurred during the primary infection. The cumulative incidence of fatal COVID-19 was 0.042% (95% CI: 0.036-0.050%), with an incidence rate of 0.13 (95% CI: 0.11-0.16) per 1,000 person-years. In the post-first omicron phase, the incidence rate of fatal COVID-19 decreased by 90.0% compared to earlier stages. Both severity and fatality exhibited an exponential increase with age and a linear increase with the number of coexisting conditions. Conclusions: The conclusion of the first omicron wave was a turning point in the severity of the pandemic. While vaccination and enhanced case management reduced severity gradually, the rapid accumulation of natural immunity during the initial omicron wave appears to have played the crucial role in driving this shift in severity.

Predictive biomarkers of ICU and mechanical ventilation duration in critically-ill COVID19 patients (preprint)

Background: Detection of early metabolic changes in critically-ill COVID-19 patients under invasive mechanical ventilation (IMV) at the intensive care unit (ICU) could predict recovery patterns and help in disease management. Methods: Targeted metabolomics of serum samples from 39 COVID-19 patients under IMV in ICU was performed within 48 hours of intubation and a week later. A generalized linear model (GLM) was used to identify, at both time points, metabolites and clinical traits that predict the length of stay (LOS) at ICU (short ≤14 days /long >14 days) as well as the duration under IMV. All models were initially trained on a set of randomly selected individuals and validated on the remaining individuals in the cohort. Further validation in recently published Metabolomics data of COVID-19 severity was performed. Results: A model based on hypoxanthine and betaine measured at first time point was best at predicting whether a patient is likely to experience a short or long stay at ICU (AUC=0.92). A further model based on kynurenine, 3-methylhistidine, Ornithine, p-Cresol sulfate and C24.0 sphingomyelin, measured one-week later, accurately predicted the duration of IMV (Pearson correlation=0.94). Both predictive models outperformed APACHE II scores and differentiated COVID-19 severity in published data. Conclusion: This study has identified specific metabolites that can predict in advance LOS and IMV, which could help in the management of COVID-19 cases at ICU.

Are commercial antibody assays substantially underestimating SARS-CoV-2 ever infection? An analysis on a population-based sample in a high exposure setting (preprint)

BackgroundPerformance of three automated commercial serological IgG-based assays was investigated for assessing SARS-CoV-2 ever (past or current) infection in a population-based sample in a high exposure setting. MethodsPCR and serological testing was performed on 394 individuals. ResultsSARS-CoV-2-IgG seroprevalence was 42.9% (95% CI 38.1%-47.8%), 40.6% (95% CI 35.9%-45.5%), and 42.4% (95% CI 37.6%-47.3%) using the CL-900i, VidasIII, and Elecsys assays, respectively. Between the three assays, overall, positive, and negative percent agreements ranged between 93.2%-95.7%, 89.3%-92.8%, and 93.8%-97.8%, respectively; Cohen kappa statistic ranged from 0.86-0.91; and 35 specimens (8.9%) showed discordant results. Among all individuals, 12.5% (95% CI 9.6%-16.1%) had current infection, as assessed by PCR. Of these, only 34.7% (95% CI 22.9%-48.7%) were seropositive by at least one assay. A total of 216 individuals (54.8%; 95% CI 49.9%-59.7%) had evidence of ever infection using antibody testing and/or PCR during or prior to this study. Of these, only 78.2%, 74.1%, and 77.3% were seropositive in the CL-900i, VidasIII, and Elecsys assays, respectively. ConclusionsAll three assays had comparable performance and excellent agreement, but missed at least 20% of individuals with past or current infection. Commercial antibody assays can substantially underestimate ever infection, more so when infection rates are high.