Long-term support of COVID-19 patients with veno-venous extracorporeal membrane oxygenation: Complications, predictors of mortality and long-term outcome

Objectives: Treatment of severe respiratory distress syndrome (ARDS) due to COVID-19 by veno-venous extracorporeal membrane oxygenation (VV-ECMO) had a mortality of up to 70% in Germany. Many patients with COVID-19 need VV-ECMO support longer than 28 days (long-term VV-ECMO). Evidence on mortality, complications during intensive care, functional status after discharge and mortality-predictors for patients supported with long-term VV-ECMO is lacking. Method(s): Retrospective study of 137 consecutive patients treated with VV-ECMO for ARDS due to COVID-19 at University Hospital Regensburg from March 2020 to March 2022. Result(s): 38% (n=52;87% male) of patients needed longterm VV-ECMO support. In these, SOFA score (median [IQR]) at ECMO initiation was 9 [8-11], age 58.2 [50.6- 62.5] years, PaO2/FiO2-ratio 67 [52-88] mmHg, pCO262 [52-74] mmHg, Murray-Score 3.3 [3.0-3.6] and PEEP 15 [13 - 16] cmH2O. Duration of long-term support was 45 [35-65] days. 26 (50%) patients were discharged from the ICU. Only one patient died after hospital discharge. At VVECMO initiation, baseline characteristics did not differ between deceased and survivors. Complications were frequent (acute kidney injury: 31/52, renal replacement therapy: 14/52, pulmonary embolism: 21/52, intracranial hemorrhage 8/52, major bleeding 34/52 and secondary sclerosing cholangitis: 5/52) and more frequent in the deceased. Karnofsky index (normal 100) after rehabilitation was 70 [57.5-82.5]. Twelve of the 18 patients discharged from rehabilitation had a satisfactory quality of life according to their own subjective assessment. Four patients required nursing support. Mortality-predictors within the first 30 days on VV-ECMO only observed in those who deceased later, were: Bilirubin >5mg/dl for > 7 days, pulmonary compliance <10ml/mbar for >14 days, and repeated serum concentrations of interleukin 8 >150ng/L. Conclusion(s): Long-term extracorporeal lung support in patients with COVID-19 resulted in 50 % survival and subsequently lead to a satisfactory quality of life and functionality in the majority of patients. It should preferably be performed in experienced centers because of a high incidence of complications. Several findings during the early course were associated with late mortality but need validation in large prospective studies.

COVIDAL: A Machine Learning Classifier for Digital COVID-19 Diagnosis in German Hospitals

For the fight against the COVID-19 pandemic, it is particularly important to map the course of infection, in terms of patients who have currently tested SARS-CoV-2 positive, as accurately as possible. In hospitals, this is even more important because resources have become scarce. Although polymerase chain reaction (PCR) and point of care (POC) antigen testing capacities have been massively expanded, they are often very time-consuming and cost-intensive and, in some cases, lack appropriate performance. To meet these challenges, we propose the COVIDAL classifier for AI-based diagnosis of symptomatic COVID-19 subjects in hospitals based on laboratory parameters. We evaluate the algorithm's performance by unique multicenter data with approximately 4,000 patients and an extraordinary high ratio of SARS-CoV-2-positive patients. We analyze the influence of data preparation, flexibility in optimization targets, as well as the selection of the test set on the COVIDAL outcome. The algorithm is compared with standard AI, PCR, POC antigen testing and manual classifications of seven physicians by a decision theoretic scoring model including performance metrics, turnaround times and cost. Thereby, we define health care settings in which a certain classifier for COVID-19 diagnosis is to be applied. We find sensitivities, specificities, and accuracies of the COVIDAL algorithm of up to 90 percent. Our scoring model suggests using PCR testing for a focus on performance metrics. For turnaround times, POC antigen testing should be used. If balancing performance, turnaround times, and cost is of interest, as, for example, in the emergency department, COVIDAL is superior based on the scoring model. © 2023 Association for Computing Machinery.

COVID-19 in cancer patients: Clinical characteristics and outcome-a first analysis of the LEOSS registry

Introduction: Since the emergence of the novel coronavirus SARS-CoV-2 in December 2019 in Wuhan, cases of the associated disease COVID-19 are seen worldwide. To collect clinical data of the pandemic the international, multicenter Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS) registry was established. Here, we present a first description of cancer patients with COVID-19 from LEOSS. Patients and Methods: We retrospectively analyzed a cohort of 283 patients (pts) with cancer and COVID-19 from a total of 1808 pts enrolled between March 6th, 2020, and June 26th, 2020. Baseline characteristics include socio-demographics, comorbidity according to Charlson Comor-bidity Index (CCI), ECOG and outcome of COVID-19. Clinical manifestation of COVID-19 was described in four phases: uncomplicated (asymptomatic/mild symptoms), complicated (need for oxygen supplementation), critical (need for life supporting therapy) and recovery (clinical improvement/discharge). Result(s): Median observational period was 11 (range 0-48) days, median inpatients stay 12.5 (range 0-72) days. Most patients were aged 66 years or older (75.5%), 112 (39.5%) pts were female. Median CCI was 4 (0-15), 46/119 (16.5%) pts had an ECOG >2. Solid tumors were seen in 61%, lymphoma and leukemia in 14.5% and 10.5% respectively. One hundred and seven pts (38%) had an active malignant disease and 76 (27%) had received anti-cancer treatment within the last 3 months. In 181 (64%) pts COVID-19 remained in the uncomplicated phase whereas 93 (33%) pts developed a complicated or critical phase. Sixty-three (22.5%) pts required intensive care, 35 out of 63 needed mechanical ventilation. A total of 79 (28%) pts died, 67 (23.5%) from COVID-19. Median survival was 33 days and worse compared to non-cancer pts (non-cancer pts: med. survival not reached, p-value < 0.001). Conclusion(s): As expected, cancer patients hospitalized for COVID-19 frequently have severe disease and an adverse outcome. To confrm these results, age-and comorbidity adjusted analysis are needed. An update of the analysis will be presented at the DGHO Annual Meeting.

Coronavirus disease 2019 is associated with multi-lineage, morphologic changes in peripheral blood cells

Introduction: The clinical course of coronavirus disease 2019 (COVID-19) varies from mild symptoms to acute respiratory distress syndrome, hyper-infammation and coagulation disorder. The hematopoietic system plays a critical role in the observed hyperinfammation, particularly in severely ill patients. Method(s): We conducted a prospective diagnostic study performing a blood differential analyzing morphologic changes in peripheral blood of COVID-19 patients. COVID-19 associated morphologic changes were defned in a training cohort and subsequently validated in a second cohort (n=45). Morphologic aberrations were further analyzed by electron microscopy (EM) and fow cytometry of lymphocytes was performed. Result(s): We included 45 COVID-19 patients in our study (median age 58 years;82% on intensive care unit). The blood differential showed a specific pattern of pronounced multi-lineage aberrations in lymphocytes (80% of patients) and monocytes (91%). 84%, 98%, and 98% of patients exhibited aberrations in granulopoiesis, erythropoiesis and thrombopoiesis, respectively. Electron microscopy revealed the ultrastructural equivalents of the observed changes and confrmed the multi-lineage aberrations already seen by light microscopy. Conclusion(s): The morphologic pattern caused by COVID-19 is characteristic and underlines the serious perturbation of the hematopoietic system. We defned a hematologic COVID-19 pattern to facilitate further independent diagnostic analysis and to investigate the impact on the he-matologic system during the clinical course of COVID-19 patients.

COVID-19 in cancer patients - higher inflammatory response in patients with active cancer

Background: Active cancer has been identified as an independent risk factor for severity and mortality in COVID-19. However, direct comparisons of SARS-CoV-2 infected patients (pts) with active and non-active cancers remain scarce. Method(s): We retrospectively analyzed a cohort of pts with cancer with confirmed SARS-CoV-2 infection, enrolled 03/16/2020 - 07/31/2021. Data on demographics, cancer and laboratory findings were collected. Descriptive and subsequent regression analysis was performed. Endpoints were progression to severe COVID-19 and infection-associated mortality. Result(s): In total, 987 pts with cancer (510 active vs 477 non-active) were included in our analysis. Majority was male and > 55 years, with a higher number of elderly pts with non-active cancer. CCI was 4.75 vs 3.85 in pts with active and non-active cancer (p<0.001). Localized solid tumors were reported in 38 vs 79% (p<0.001), metastasized in 37.5 vs 5.5% (p<0.001) and hematological diseases in 37.5 vs 19.5% (p<0.001) pts with active and non-active cancer, respectively. At virus detection, majority of pts showed mild to moderate symptoms, while deterioration to severe COVID-19 was slightly more common in pts with active cancer (19% vs 16%;p=0.284). COVID-19 related mortality was significantly higher in pts with active cancer (24% vs 17.5%, p<0.001). In line, severe cytopenia and an increase of inflammatory markers were common findings in pts with active cancer at baseline, particularly in those who developed severe infection or died. Multivariate analysis revealed that ferritin (14.24 [2.1-96], p=0.006) and CRP (2.85 [1.02-8.02], p=0.046) were associated with severe COVID-19 and infection-related mortality. In pts with non-active cancer, association was seen for ferritin only (4.1 [1.51-11.17], p=0.006). Conclusion(s): Comparing pts with active and non-active cancer, mortality rate was significantly higher in pts with active cancer. Also inflammatory markers were significantly increased assuming higher levels of inflammation may play a role in adverse outcome of COVID-19 in pts with active cancer.

External Validation of the 4C Mortality Score and the qSOFA for Different Variants of Concerns of SARS-CoV-2 Using Data of the NAPKON Cross-Sectoral Cohort Platform (SUEP)

Background. Numerous predictive clinical scores with varying discriminatory performance have been developed in the context of the current coronavirus disease 2019 (COVID-19) pandemic. To support clinical application, we test the transferability of the frequently applied 4C mortality score (4C score) to the German prospective Cross-Sectoral Platform (SUEP) of the National Pandemic Cohort Network (NAPKON) compared to the non COVID-19 specific quick sequential organ failure assessment score (qSOFA). Our project aims to externally validate these two scores, stratified for the most prevalent variants of concerns (VOCs) of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) in Germany. Methods. A total of 685 adults with polymerase chain reaction (PCR)-detected SARS-CoV-2 infection were included from NAPKON-SUEP. Patients were recruited from 11/2020 to 03/2022 at 34 university and non-university hospitals across Germany. Missing values were complemented using multiple imputation. Predictive performance for in-hospital mortality at day of baseline visit was determined by area under the curve (AUC) with 95%-confidence interval (CI) stratified by VOCs of SARS-CoV-2 (alpha, delta, omicron) (Figure 1). Figure 1: Study flow chart with inclusion criteria and methodological workflow. Results. Preliminary results suggest a high predictive performance of the 4C score for in-hospital mortality (Table 1). This applies for the overall cohort (AUC 0.813 (95%CI 0.738-0.888)) as well as the VOC-strata (alpha: AUC 0.859 (95%CI 0.748-0.970);delta: AUC 0.769 (95%CI 0.657-0.882);omicron: AUC 0.866 (95%CI 0.724-1.000)). The overall mortality rates across the defined 4C score risk groups are 0.3% (low), 3.2% (intermediate), 11.6% (high), and 49.5% (very high). The 4C score performs significantly better than the qSOFA (Chi2-test: p=0.001) and the qSOFA does not seem to be a suitable tool in this context. Table 1: Discriminatory performance of the 4C Mortality Score and the qSOFA score within the validation cohort NAPKON-SUEP stratified by the Variant of Concerns of SARS-CoV- 2. Conclusion. Despite its development in the early phase of the pandemic and improved treatment, external validation of the 4C score in NAPKON-SUEP indicates a high predictive performance for in-hospital mortality across all VOCs. However, since the qSOFA was not specifically designed for this predictive issue, it shows low discriminatory performance, as in other validation studies. Any interpretations regarding the omicron stratum are limited due to the sample size.

[Epidemiology of SARS-CoV-2/COVID-19]. / Epidemiologie von SARS-CoV-2/COVID 19: Aktueller Stand.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a beta coronavirus, which first appeared in 2019 and rapidly spread causing a worldwide pandemic. Here we present a nonsystematic review of the current knowledge on its epidemiological features. The SARS-CoV­2 replicates mainly in the upper and lower respiratory tract and is mainly transmitted by droplets and aerosols from asymptomatic and symptomatic infected subjects. The estimate for the basic reproduction number (R0) is between 2 and 3 and the median incubation period is 6 days (range 2-14 days). Similar to the related coronaviruses SARS and Middle East respiratory syndrome (MERS), superspreading events play an important role in spreading the disease. The majority of infections run an uncomplicated course but 5-10% of those infected develop pneumonia or a systemic inflammation leading to hospitalization, respiratory and potentially multiorgan failure. The most important risk factors for a complicated disease course are age, hypertension, diabetes, chronic cardiovascular and pulmonary diseases and immunodeficiency. The current infection fatality rate over all age groups is between 0.5% and 1% and the rate rises after the sixth decade of life. Nosocomial transmission and infections in medical personnel have been reported. A drastic reduction of social contacts has been implemented in many countries with outbreaks of SARS-CoV­2, leading to rapid reductions in R0. Most interventions have used bundles and which of the measures have been more effective is still unknown. Using mathematical models an incidence of 0.4%-1.8% can be estimated for the first wave in Germany.

COVID-19 in cancer patients: clinical characteristics and outcome-an analysis of the LEOSS registry.

INTRODUCTION: Since the early SARS-CoV-2 pandemic, cancer patients have been assumed to be at higher risk for severe COVID-19. Here, we present an analysis of cancer patients from the LEOSS (Lean European Open Survey on SARS-CoV-2 Infected Patients) registry to determine whether cancer patients are at higher risk. PATIENTS AND METHODS: We retrospectively analyzed a cohort of 435 cancer patients and 2636 non-cancer patients with confirmed SARS-CoV-2 infection, enrolled between March 16 and August 31, 2020. Data on socio-demographics, comorbidities, cancer-related features and infection course were collected. Age-, sex- and comorbidity-adjusted analysis was performed. Primary endpoint was COVID-19-related mortality. RESULTS: In total, 435 cancer patients were included in our analysis. Commonest age category was 76-85 years (36.5%), and 40.5% were female. Solid tumors were seen in 59% and lymphoma and leukemia in 17.5% and 11% of patients. Of these, 54% had an active malignancy, and 22% had recently received anti-cancer treatments. At detection of SARS-CoV-2, the majority (62.5%) presented with mild symptoms. Progression to severe COVID-19 was seen in 55% and ICU admission in 27.5%. COVID-19-related mortality rate was 22.5%. Male sex, advanced age, and active malignancy were associated with higher death rates. Comparing cancer and non-cancer patients, age distribution and comorbidity differed significantly, as did mortality (14% vs 22.5%, p value < 0.001). After adjustments for other risk factors, mortality was comparable. CONCLUSION: Comparing cancer and non-cancer patients, outcome of COVID-19 was comparable after adjusting for age, sex, and comorbidity. However, our results emphasize that cancer patients as a group are at higher risk due to advanced age and pre-existing conditions.

[Epidemiology of SARS-CoV-2 infection and COVID-19]. / Epidemiologie von SARS-CoV-2-Infektion und COVID-19.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a new ß­Coronavirus that was first detected in 2019 in Wuhan, China. In the ensuing months it has been transmitted worldwide. Here the authors present the current knowledge on the epidemiology of this virus. SARS-CoV­2 replicates mainly in the upper and lower respiratory tract and is primarily transmitted by droplets from asymptomatic and symptomatic infected subjects. The estimate for the basic reproduction number (R) is currently between 2 and 3, while the incubation period is 6 (median, range 2-14) days. Although most infections are uncomplicated, 5-10% of cases develop pneumonia, which can lead to hospitalization, respiratory failure and multiorgan failure. Risk factors for a complicated disease course include age, hypertension, chronic cardiovascular and pulmonary disease and immunodeficiency. The overall case fatality rate is 1.4%, with the rate rising in the sixth decade of life. Nosocomial and infections in medical personnel have been reported. Drastic reductions in social contact have been implemented in many countries with outbreaks of SARS-CoV­2, leading to rapid reductions in R. Which of the measures have been effective is still unknown.