Comparison of post-COVID-19 symptoms in patients infected with the SARS-CoV-2 variants delta and omicron-results of the Cross-Sectoral Platform of the German National Pandemic Cohort Network (NAPKON-SUEP).

PURPOSE: The influence of new SARS-CoV-2 variants on the post-COVID-19 condition (PCC) remains unanswered. Therefore, we examined the prevalence and predictors of PCC-related symptoms in patients infected with the SARS-CoV-2 variants delta or omicron. METHODS: We compared prevalences and risk factors of acute and PCC-related symptoms three months after primary infection (3MFU) between delta- and omicron-infected patients from the Cross-Sectoral Platform of the German National Pandemic Cohort Network. Health-related quality of life (HrQoL) was determined by the EQ-5D-5L index score and trend groups were calculated to describe changes of HrQoL between different time points. RESULTS: We considered 758 patients for our analysis (delta: n = 341; omicron: n = 417). Compared with omicron patients, delta patients had a similar prevalence of PCC at the 3MFU (p = 0.354), whereby fatigue occurred most frequently (n = 256, 34%). HrQoL was comparable between the groups with the lowest EQ-5D-5L index score (0.75, 95% CI 0.73-0.78) at disease onset. While most patients (69%, n = 348) never showed a declined HrQoL, it deteriorated substantially in 37 patients (7%) from the acute phase to the 3MFU of which 27 were infected with omicron. CONCLUSION: With quality-controlled data from a multicenter cohort, we showed that PCC is an equally common challenge for patients infected with the SARS-CoV-2 variants delta and omicron at least for the German population. Developing the EQ-5D-5L index score trend groups showed that over two thirds of patients did not experience any restrictions in their HrQoL due to or after the SARS-CoV-2 infection at the 3MFU. CLINICAL TRAIL REGISTRATION: The cohort is registered at ClinicalTrials.gov since February 24, 2021 (Identifier: NCT04768998).

Postmortem Minimally Invasive Autopsy in Critically Ill COVID-19 Patients at the Bedside: A Proof-of-Concept Study at the ICU.

BACKGROUND: Economic restrictions and workforce cuts have continually challenged conventional autopsies. Recently, the COVID-19 pandemic has added tissue quality and safety requirements to the investigation of this disease, thereby launching efforts to upgrade autopsy strategies. METHODS: In this proof-of-concept study, we performed bedside ultrasound-guided minimally invasive autopsy (US-MIA) in the ICU of critically ill COVID-19 patients using a structured protocol to obtain non-autolyzed tissue. Biopsies were assessed for their quality (vitality) and length of biopsy (mm) and for diagnosis. The efficiency of the procedure was monitored in five cases by recording the time of each step and safety issues by swabbing personal protective equipment and devices for viral contamination. FINDINGS: Ultrasound examination and tissue procurement required a mean time period of 13 min and 54 min, respectively. A total of 318 multiorgan biopsies were obtained from five patients. Quality and vitality standards were fulfilled, which not only allowed for specific histopathological diagnosis but also the reliable detection of SARS-CoV-2 virions in unexpected organs using electronic microscopy and RNA-expressing techniques. INTERPRETATION: Bedside multidisciplinary US-MIA allows for the fast and efficient acquisition of autolytic-free tissue and offers unappreciated potential to overcome the limitations of research in postmortem studies.

Platelet aggregates detected using quantitative phase imaging associate with COVID-19 severity.

BACKGROUND: The clinical spectrum of acute SARS-CoV-2 infection ranges from an asymptomatic to life-threatening disease. Considering the broad spectrum of severity, reliable biomarkers are required for early risk stratification and prediction of clinical outcomes. Despite numerous efforts, no COVID-19-specific biomarker has been established to guide further diagnostic or even therapeutic approaches, most likely due to insufficient validation, methodical complexity, or economic factors. COVID-19-associated coagulopathy is a hallmark of the disease and is mainly attributed to dysregulated immunothrombosis. This process describes an intricate interplay of platelets, innate immune cells, the coagulation cascade, and the vascular endothelium leading to both micro- and macrothrombotic complications. In this context, increased levels of immunothrombotic components, including platelet and platelet-leukocyte aggregates, have been described and linked to COVID-19 severity. METHODS: Here, we describe a label-free quantitative phase imaging approach, allowing the identification of cell-aggregates and their components at single-cell resolution within 30 min, which prospectively qualifies the method as point-of-care (POC) testing. RESULTS: We find a significant association between the severity of COVID-19 and the amount of platelet and platelet-leukocyte aggregates. Additionally, we observe a linkage between severity, aggregate composition, and size distribution of platelets in aggregates. CONCLUSIONS: This study presents a POC-compatible method for rapid quantitative analysis of blood cell aggregates in patients with COVID-19.

The human body produces a series of immune responses when it gets infected with SARS-CoV-2, the virus that causes COVID-19. One of these responses involves platelets, the blood clotting factor sticking to immune cells to form cell aggregates in the bloodstream. We aimed to understand the significance of these cell aggregates in COVID-19 disease progression. A quantitative imaging approach was used to investigate the number and components of these cell aggregates in SARS-CoV-2 infected patient blood. We observed blood from severe COVID-19 patients was associated with higher numbers and specific composition of cell aggregates. Our method can potentially support the risk stratification of severe patients to prevent complications in COVID-19 and other medical disorders, where immune cells are shown to aggregate.

Are enterococcal bloodstream infections an independent risk factor for a poorer 5-year survival or just a marker for severity of illness?-The Munich multicentric enterococci cohort.

IMPORTANCE: The present study provides a substantial contribution to literature, showing that patients with enterococcal bloodstream infections (BSI) have a lower survival rate than those with Escherichia coli (E. coli) bloodstream infections after adjusting for 17 limiting prognostic factors and excluding patients with a limited life expectancy [metastatic tumor disease, Charlson Comorbidity Index (CCI) (greater than or equal to) 5]. This difference in the 5-year long-term survival was mainly driven by Enterococcus faecium (ECFM) bloodstream infections, with vancomycin resistance not being a significant contributing factor. Our findings imply that E. faecium bloodstream infections seem to be an independent risk factor for poor long-term outcomes. As such, future research should confirm this relationship and prioritize investigating its causality through prospective studies.

Covid-19 triage in the emergency department 2.0: how analytics and AI transform a human-made algorithm for the prediction of clinical pathways.

The Covid-19 pandemic has pushed many hospitals to their capacity limits. Therefore, a triage of patients has been discussed controversially primarily through an ethical perspective. The term triage contains many aspects such as urgency of treatment, severity of the disease and pre-existing conditions, access to critical care, or the classification of patients regarding subsequent clinical pathways starting from the emergency department. The determination of the pathways is important not only for patient care, but also for capacity planning in hospitals. We examine the performance of a human-made triage algorithm for clinical pathways which is considered a guideline for emergency departments in Germany based on a large multicenter dataset with over 4,000 European Covid-19 patients from the LEOSS registry. We find an accuracy of 28 percent and approximately 15 percent sensitivity for the ward class. The results serve as a benchmark for our extensions including an additional category of palliative care as a new label, analytics, AI, XAI, and interactive techniques. We find significant potential of analytics and AI in Covid-19 triage regarding accuracy, sensitivity, and other performance metrics whilst our interactive human-AI algorithm shows superior performance with approximately 73 percent accuracy and up to 76 percent sensitivity. The results are independent of the data preparation process regarding the imputation of missing values or grouping of comorbidities. In addition, we find that the consideration of an additional label palliative care does not improve the results.

Transpulmonary thermodilution: A revised correction formula for global end-diastolic volume index derived after femoral indicator injection.

PURPOSE: Transpulmonary thermodilution (TPTD) is usually performed by jugular indicator injection. In clinical practice, femoral venous access is often used instead, resulting in substantial overestimation of global end-diastolic volume index (GEDVI). A correction formula compensates for that. The objective of this study is to first evaluate the efficacy of the currently implemented correction function and then further improve this formula. METHODS: The performance of the established correction formula was investigated in our prospectively collected dataset of 98 TPTD measurements from 38 patients with both, jugular and femoral venous access. Subsequently, a new correction formula was developed: cross validation revealed the favourite covariate combination and a general estimating equation provided the final version, which was tested in a retrospective validation on an external dataset. RESULTS: Investigating the current correction function revealed a considerable reduction of bias compared to no correction. Concerning the objective of formula development, the covariate combination of GEDVI obtained after femoral indicator injection, age and body surface area is even favoured, when compared to the parameters of the previously published correction formula, as a further reduction of mean absolute error (68 vs. 61 ml/m2), a better correlation (0.90 vs. 0.91) and an increased adjusted R2 (0.72 vs 0.78) is noticed in the cross validation results. Of particular clinical importance is, that more measurements were correctly assigned to the same GEDVI category (decreased / normal / increased) using the revised formula, compared with the gold standard of jugular indicator injection (72.4 vs. 74.5%). In a retrospective validation, the newly developed formula showed a greater reduction of bias (to 2 vs. 6 %) than the currently implemented formula. CONCLUSIONS: The currently implemented correction function partly compensates for GEDVI overestimation. Applying the new correction formula on GEDVI measured after femoral indicator administration enhances the informative value and reliability of this preload parameter.

Validation of the SACOV-19 score for identifying patients at risk of complicated or more severe COVID-19: a prospective study.

PURPOSE: Identification of patients at risk of complicated or more severe COVID-19 is of pivotal importance, since these patients might require monitoring, antiviral treatment, and hospitalization. In this study, we prospectively evaluated the SACOV-19 score for its ability to predict complicated or more severe COVID-19. METHODS: In this prospective multicenter study, we included 124 adult patients with acute COVID-19 in three German hospitals, who were diagnosed in an early, uncomplicated stage of COVID-19 within 72 h of inclusion. We determined the SACOV-19 score at baseline and performed a follow-up at 30 days. RESULTS: The SACOV-19 score's AUC was 0.816. At a cutoff of > 3, it predicted deterioration to complicated or more severe COVID-19 with a sensitivity of 94% and a specificity of 55%. It performed significantly better in predicting complicated COVID-19 than the random tree-based SACOV-19 predictive model, the CURB-65, 4C mortality, or qCSI scores. CONCLUSION: The SACOV-19 score is a feasible tool to aid decision making in acute COVID-19.

Accuracy of hemodynamic parameters derived by GE E-PiCCO in comparison with PiCCO® in patients admitted to the intensive care unit.

To evaluate the agreement and accuracy of a novel advanced hemodynamic monitoring (AHM) device, the GE E-PiCCO module, with the well-established PiCCO® device in intensive care patients using pulse contour analysis (PCA) and transpulmonary thermodilution (TPTD). A total of 108 measurements were performed in 15 patients with AHM. Each of the 27 measurement sequences (one to four per patient) consisted of a femoral and a jugular indicator injection via central venous catheters (CVC) and measurement using both PiCCO (PiCCO® Jug and Fem) and GE E-PiCCO (GE E-PiCCO Jug and Fem) devices. For statistical analysis, Bland-Altman plots were used to compare the estimated values derived from both devices. The cardiac index measured via PCA (CIpc) and TPTD (CItd) was the only parameter that fulfilled all a priori-defined criteria based on bias and the limits of agreement (LoA) by the Bland-Altman method as well as the percentage error by Critchley and Critchley for all three comparison pairs (GE E-PiCCO Jug vs. PiCCO® Jug, GE E-PiCCO Fem vs. PiCCO® Fem, and GE E-PiCCO Fem vs. GE E-PiCCO Jug), while the GE E-PiCCO did not accurately estimate EVLWI, SVRI, SVV, and PPV values measured via the jugular and femoral CVC compared with values assessed by PiCCO®. Consequently, measurement discrepancy should be considered on evaluation and interpretation of the hemodynamic status of patients admitted to the ICU when using the GE E-PiCCO module instead of the PiCCO® device.

Consistency as a Data Quality Measure for German Corona Consensus Items Mapped from National Pandemic Cohort Network Data Collections.

BACKGROUND: As a national effort to better understand the current pandemic, three cohorts collect sociodemographic and clinical data from coronavirus disease 2019 (COVID-19) patients from different target populations within the German National Pandemic Cohort Network (NAPKON). Furthermore, the German Corona Consensus Dataset (GECCO) was introduced as a harmonized basic information model for COVID-19 patients in clinical routine. To compare the cohort data with other GECCO-based studies, data items are mapped to GECCO. As mapping from one information model to another is complex, an additional consistency evaluation of the mapped items is recommended to detect possible mapping issues or source data inconsistencies. OBJECTIVES: The goal of this work is to assure high consistency of research data mapped to the GECCO data model. In particular, it aims at identifying contradictions within interdependent GECCO data items of the German national COVID-19 cohorts to allow investigation of possible reasons for identified contradictions. We furthermore aim at enabling other researchers to easily perform data quality evaluation on GECCO-based datasets and adapt to similar data models. METHODS: All suitable data items from each of the three NAPKON cohorts are mapped to the GECCO items. A consistency assessment tool (dqGecco) is implemented, following the design of an existing quality assessment framework, retaining their-defined consistency taxonomies, including logical and empirical contradictions. Results of the assessment are verified independently on the primary data source. RESULTS: Our consistency assessment tool helped in correcting the mapping procedure and reveals remaining contradictory value combinations within COVID-19 symptoms, vital signs, and COVID-19 severity. Consistency rates differ between the different indicators and cohorts ranging from 95.84% up to 100%. CONCLUSION: An efficient and portable tool capable of discovering inconsistencies in the COVID-19 domain has been developed and applied to three different cohorts. As the GECCO dataset is employed in different platforms and studies, the tool can be directly applied there or adapted to similar information models.

Statistical biases due to anonymization evaluated in an open clinical dataset from COVID-19 patients.

Anonymization has the potential to foster the sharing of medical data. State-of-the-art methods use mathematical models to modify data to reduce privacy risks. However, the degree of protection must be balanced against the impact on statistical properties. We studied an extreme case of this trade-off: the statistical validity of an open medical dataset based on the German National Pandemic Cohort Network (NAPKON), which was prepared for publication using a strong anonymization procedure. Descriptive statistics and results of regression analyses were compared before and after anonymization of multiple variants of the original dataset. Despite significant differences in value distributions, the statistical bias was found to be small in all cases. In the regression analyses, the median absolute deviations of the estimated adjusted odds ratios for different sample sizes ranged from 0.01 [minimum = 0, maximum = 0.58] to 0.52 [minimum = 0.25, maximum = 0.91]. Disproportionate impact on the statistical properties of data is a common argument against the use of anonymization. Our analysis demonstrates that anonymization can actually preserve validity of statistical results in relatively low-dimensional data.

Association between IgG responses against the nucleocapsid proteins of alphacoronaviruses and COVID-19 severity.

Understanding immune responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is crucial to contain the COVID-19 pandemic. Using a multiplex approach, serum IgG responses against the whole SARS-CoV-2 proteome and the nucleocapsid proteins of endemic human coronaviruses (HCoVs) were measured in SARS-CoV-2-infected donors and healthy controls. COVID-19 severity strongly correlated with IgG responses against the nucleocapsid (N) of SARS-CoV-2 and possibly with the number of viral antigens targeted. Furthermore, a strong correlation between COVID-19 severity and serum responses against N of endemic alpha- but not betacoronaviruses was detected. This correlation was neither caused by cross-reactivity of antibodies, nor by a general boosting effect of SARS-CoV-2 infection on pre-existing humoral immunity. These findings raise the prospect of a potential disease progression marker for COVID-19 severity that allows for early stratification of infected individuals.

Hospitalized patients dying with SARS-CoV-2 infection-An analysis of patient characteristics and management in ICU and general ward of the LEOSS registry.

BACKGROUND: COVID-19 is a severe disease with a high need for intensive care treatment and a high mortality rate in hospitalized patients. The objective of this study was to describe and compare the clinical characteristics and the management of patients dying with SARS-CoV-2 infection in the acute medical and intensive care setting. METHODS: Descriptive analysis of dying patients enrolled in the Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS), a non-interventional cohort study, between March 18 and November 18, 2020. Symptoms, comorbidities and management of patients, including palliative care involvement, were compared between general ward and intensive care unit (ICU) by univariate analysis. RESULTS: 580/4310 (13%) SARS-CoV-2 infected patients died. Among 580 patients 67% were treated on ICU and 33% on a general ward. The spectrum of comorbidities and symptoms was broad with more comorbidities (≥ four comorbidities: 52% versus 25%) and a higher age distribution (>65 years: 98% versus 70%) in patients on the general ward. 69% of patients were in an at least complicated phase at diagnosis of the SARS-CoV-2 infection with a higher proportion of patients in a critical phase or dying the day of diagnosis treated on ICU (36% versus 11%). While most patients admitted to ICU came from home (71%), patients treated on the general ward came likewise from home and nursing home (44% respectively) and were more frequently on palliative care before admission (29% versus 7%). A palliative care team was involved in dying patients in 15%. Personal contacts were limited but more often documented in patients treated on ICU (68% versus 47%). CONCLUSION: Patients dying with SARS-CoV-2 infection suffer from high symptom burden and often deteriorate early with a demand for ICU treatment. Therefor a demand for palliative care expertise with early involvement seems to exist.

SARS-CoV-2 viral load dynamics in immunocompromised critically ill patients on remdesivir treatment.

The relationship between SARS-CoV-2 quantitative viral load and risk of disease progression, morbidity such as long- COVID or mortality in immunosuppressed, remains largely undefined in COVID-19 patients. Critically ill immunosuppressed patients potentially benefit from remdesivir treatment because of the prolonged course of their infection. Four critically ill immunocompromised patients and the impact of remdesivir on viral dynamics in lower respiratory samples were studied. Bronchoalveolar lavage (BAL) samples were assessed to measure SARS-CoV-2 quantitative viral load using real-time PCR. Corresponding plasma levels of remdesivir and its metabolite GS-441524 were determined. Mean virus load of 39.74 x 107 geq/ml (±33.25 x 107 geq/ml) on day 1 dropped significantly (p<0.008) to 3.54 x 106 geq/ml (±6.93 x 106 geq/ml) on day 3 and to 1.4 x 105 geq/ml (±2.35 x 105 geq/ml) on day 5 of remdesivir treatment. Mean virus load dropped below <1% between day 1 and 5 of remdesivir treatment. Parent prodrug remdesivir and also GS441524 metabolite levels of antiviral activity in our patients were far in excess of EC 50. Our data present that remdesivir treatment potentially reduces the SARS-CoV-2 viral load in immunosuppressed critically ill patients. However, the implication of viral load reduction on morbidity and mortality needs further investigation.

CMV seropositivity is a potential novel risk factor for severe COVID-19 in non-geriatric patients.

BACKGROUND: COVID-19 has so far affected more than 250 million individuals worldwide, causing more than 5 million deaths. Several risk factors for severe disease have been identified, most of which coincide with advanced age. In younger individuals, severe COVID-19 often occurs in the absence of obvious comorbidities. Guided by the finding of cytomegalovirus (CMV)-specific T cells with some cross-reactivity to SARS-CoV-2 in a COVID-19 intensive care unit (ICU) patient, we decided to investigate whether CMV seropositivity is associated with severe or critical COVID-19. Herpes simplex virus (HSV) serostatus was investigated as control. METHODS: National German COVID-19 bio-sample and data banks were used to retrospectively analyze the CMV and HSV serostatus of patients who experienced mild (n = 101), moderate (n = 130) or severe to critical (n = 80) disease by IgG serology. We then investigated the relationship between disease severity and herpesvirus serostatus via statistical models. RESULTS: Non-geriatric patients (< 60 years) with severe COVID-19 were found to have a very high prevalence of CMV-seropositivity, while CMV status distribution in individuals with mild disease was similar to the prevalence in the German population; interestingly, this was not detectable in older patients. Prediction models support the hypothesis that the CMV serostatus, unlike HSV, might be a strong biomarker in identifying younger individuals with a higher risk of developing severe COVID-19, in particular in absence of other co-morbidities. CONCLUSIONS: We identified 'CMV-seropositivity' as a potential novel risk factor for severe COVID-19 in non-geriatric individuals in the studied cohorts. More mechanistic analyses as well as confirmation of similar findings in cohorts representing the currently most relevant SARS-CoV-2 variants should be performed shortly.

Risk factors for Herpes simplex virus (HSV) and Cytomegalovirus (CMV) infections in critically-ill COVID-19 patients.

Background: To assess the prevalence of Herpes simplex and Cytomegalovirus infection in respiratory samples of critically-ill COVID-19 patients, its role in outcome and mortality and the influence of dexamethasone treatment in the early stage of SARS-CoV-2 infection. Methods: All mechanically ventilated COVID-19 patients treated on ICU between March 2020 and January 2021 were included. Respiratory specimens were tested for Herpes simplex virus (HSV) type 1, 2 and Cytomegalovirus (CMV) by quantitative real-time PCR. Clinical parameters were compared in the cohorts with and without HSV-1- infection. Results: 134 patients with a median age of 72.5 years (73.0% male, n=98) were included. HSV-1 reactivation occurred in 61 patients (45.5%), after median 9 (7-13) days of mechanical ventilation. The main factor for reactivation was length of stay on ICU (24 days vs 13 days, p<0.001) and duration of mechanical ventilation (417 vs 214 hours, p<0.001). Treatment with dexamethasone and a history of immunosuppression did not associate with HSV-infection in the univariate analysis (39 vs 41, p=0.462 and 27.9% vs 23.3%, p=0.561, respectively). Both ICU and hospital mortality were not significantly different in the cohorts with and without HSV-infection (57.4% vs 45.2%, p=0.219). Conclusions: Our study shows a high prevalence of HSV-infection in critically-ill COVID-19 patients which was unexpectedly higher than the prevalence of CMV-infections and unrelated to dexamethasone treatment. The main risk factors for HSV and CMV in the studied cohorts were the length of ICU stay and duration of mechanical ventilation. Therefore, we recommend routine monitoring of critically ill COVID-19 patients for these viral co-infections and consider treatment in those patients.