ABSTRACT
Background: The coronavirus disease 2019 (COVID-19) pandemic demands reliable prognostic models for estimating the risk of long COVID. We developed and validated a prediction model to estimate the probability of known common long COVID symptoms at least 60 days after acute COVID-19. Methods: The prognostic model was built based on data from a multicentre prospective Swiss cohort study. Included were adult patients diagnosed with COVID-19 between February and December 2020 and treated as outpatients, at ward or intensive/intermediate care unit. Perceived long-term health impairments, including reduced exercise tolerance/reduced resilience, shortness of breath and/or tiredness (REST), were assessed after a follow-up time between 60 and 425 days. Predictors were selected out of twelve candidate predictors based on three reliable methods, namely the augmented backward elimination (ABE) method, the adaptive best-subset selection (ABESS) method and model-based recursive partitioning (MBRP) approach. Model performance was assessed with the scaled Brier score, concordance c statistic and calibration plot. The final prognostic model was determined based on best model performance. Results: In total 2799 patients were included in the analysis, of which 1588 patients were in the derivation cohort and 1211 patients in the validation cohort. The REST prevalence was similar between the cohorts with 21.6% (n = 343) in the derivation cohort and 22.1% (n = 268) in the validation data. The same predictors were selected with the ABE and ABESS variable selection method. The final prognostic model was based on the ABE and ABESS selected predictors. The corresponding model discrimination in the validation cohort was 0.78 (95% CI: 0.75 to 0.81), calibration slope was 0.92 (95% CI: 0.78 to 1.06) and calibration intercept was -0.06 (95% CI: -0.22 to 0.09). A patient’s probability of developing REST symptoms \hat{y} = exp(S) / (1 + exp(S)) can be calculated with S = −4.947 + 0.349 × number of acute COVID-19 symptoms + 0.339 × severity of acute COVID-19 ward + 1.737 × severity of acute COVID-19 intensive or intermediate care + 0.128 × feeling of stress at home + 0.013 × age at presentation + 0.352 × female sex + 0.346 × presence of at least one cardiovascular risk factor − 0.097 × responsible for childcare/family member + 0.022 × body mass index, with feeling of stress at home ranges from 1 (no stress) to 10 (maximum stress) and responsibility for childcare/family member ranges from 1 (no responsibility/not applicable) to 6 (full responsibility). Conclusion: The proposed model is reliable to identify COVID-19 infected patients at risk for REST symptoms. Before implementing the prognostic model in daily clinical practice, the conduct of an impact study is recommended.
Subject(s)
COVID-19ABSTRACT
Background Women are overrepresented amongst individuals suffering from post-acute sequelae of SARS-CoV-2 infection (PASC). Biological (sex) as well as sociocultural (gender) differences between women and men might account for this imbalance, yet their impact on PASC is unknown. Methods and Findings By using Bayesian models comprising >200 co-variates, we assessed the impact of social context in addition to biological data on PASC in a multi-centre prospective cohort study of 2927 (46% women) individuals in Switzerland. Women more often reported at least one persistent symptom than men (43.5% vs 32.0% of men, p<0.001) six (IQR 5–9) months after SARS-CoV-2 infection. Adjusted models showed that women with personality traits stereotypically attributed to women were most often affected by PASC (OR 2.50[1.25-4.98], p<0.001), in particular when they were living alone (OR 1.84[1.25-2.74]), had an increased stress level (OR 1.06[1.03-1.09]), had undergone higher education (OR 1.30[1.08-1.54]), preferred pre-pandemic physical greeting over verbal greeting (OR 1.71[1.44-2.03]), and had experienced an increased number of symptoms during index infection (OR 1.27[1.22-1.33]). Conclusion Besides gender- and sex-sensitive biological parameters, sociocultural variables play an important role in producing sex differences in PASC. Our results indicate that predictor variables of PASC can be easily identified without extensive diagnostic testing and are targets of interventions aiming at stress coping and social support.
Subject(s)
COVID-19ABSTRACT
Critically ill COVID-19 patients are characterized by a severely dysregulated cytokine profile and elevated neutrophil counts, which are thought to contribute to disease severity. However, to date it remains unclear how neutrophils contribute to pathophysiology during COVID-19. Here, we assessed the impact of the dysregulated cytokine profile on the tightly regulated cell death program of neutrophils. We show that in a subpopulation of neutrophils, canonical apoptosis was skewed towards rapidly occurring necroptosis. This phenotype was characterized by abrogated caspase-8 activity and increased RIPK1 levels, favoring execution of necroptosis via the RIPK1-RIPK3-MLKL axis, as further confirmed in COVID-19 biopsies. Moreover, reduction of sFas-L levels in COVID-19 patients and hence decreased signaling to Fas directly increased RIPK1 levels and correlated with disease severity. Our results suggest an important role for Fas signaling in the regulation of cell death program ambiguity via the ripoptosome in neutrophils during COVID-19 and a potential therapeutic target to curb inflammation and thus influence disease severity and outcome.
Subject(s)
Critical Illness , Inflammation , COVID-19ABSTRACT
COVID-19 displays diverse disease severities and symptoms. Elevated inflammation mediated by hypercytokinemia induces a detrimental dysregulation of immune cells. However, there is limited understanding of how SARS-CoV-2 pathogenesis impedes innate immune signaling and function against secondary bacterial infections. We assessed the influence of COVID-19 hypercytokinemia on the functional responses of neutrophils and monocytes upon bacterial challenges from acute and corresponding recovery COVID-19 ICU patients. We show that severe hypercytokinemia in COVID-19 patients correlated with bacterial superinfections. Neutrophils and monocytes from acute COVID-19 patients showed severely impaired microbicidal capacity, reflected by abrogated ROS and MPO production as well as reduced NETs upon bacterial challenges. We observed a distinct pattern of cell surface receptor expression on both neutrophils and monocytes leading to a suppressive autocrine and paracrine signaling during bacterial challenges. Our data provide insights into the innate immune status of COVID-19 patients mediated by their hypercytokinemia and its transient effect on immune dysregulation upon subsequent bacterial infections