Age and Comorbidity Burden of Patients Critically Ill with COVID-19 Affect Both Access to and Outcome of Ventilation Therapy in Intensive Care Units.

During the COVID-19 pandemic, large numbers of elderly, multimorbid people required treatment in intensive care units. This study investigated how the inherent patient factors age and comorbidity burden affected the treatment strategy and the outcome achieved. Retrospective analysis of data from intensive care patients enrolled in the Lean European Open Survey on SARS-CoV2-Infected Patients (LEOSS) cohort found that a patient's age and comorbidity burden in fact influenced their mortality rate and the use of ventilation therapy. Evidence showed that advanced age and multimorbidity were associated with the restrictive use of invasive ventilation therapies, particularly ECMO. Geriatric patients with a high comorbidity burden were clustered in the sub-cohort of non-ventilated ICU patients characterized by a high mortality rate. The risk of death generally increased with older age and accumulating comorbidity burden. Here, the more aggressive an applied procedure, the younger the age in which a majority of patients died. Clearly, geriatric, multimorbid COVID-19 patients benefit less from invasive ventilation therapies. This implies the need for a holistic approach to therapy decisions, taking into account the patient's wishes.

Disease severity in hospitalized COVID-19 patients: comparing routine surveillance with cohort data from the LEOSS study in 2020 in Germany.

INTRODUCTION: Studies investigating risk factors for severe COVID-19 often lack information on the representativeness of the study population. Here, we investigate factors associated with severe COVID-19 and compare the representativeness of the dataset to the general population. METHODS: We used data from the Lean European Open Survey on SARS-CoV-2 infected patients (LEOSS) of hospitalized COVID-19 patients diagnosed in 2020 in Germany to identify associated factors for severe COVID-19, defined as progressing to a critical disease stage or death. To assess the representativeness, we compared the LEOSS cohort to cases of hospitalized patients in the German statutory notification data of the same time period. Descriptive methods and Poisson regression models were used. RESULTS: Overall, 6672 hospitalized patients from LEOSS and 132,943 hospitalized cases from the German statutory notification data were included. In LEOSS, patients above 76 years were less likely represented (34.3% vs. 44.1%). Moreover, mortality was lower (14.3% vs. 21.5%) especially among age groups above 66 years. Factors associated with a severe COVID-19 disease course in LEOSS included increasing age, male sex (adjusted risk ratio (aRR) 1.69, 95% confidence interval (CI) 1.53-1.86), prior stem cell transplantation (aRR 2.27, 95% CI 1.53-3.38), and an elevated C-reactive protein at day of diagnosis (aRR 2.30, 95% CI 2.03-2.62). CONCLUSION: We identified a broad range of factors associated with severe COVID-19 progression. However, the results may be less applicable for persons above 66 years since they experienced lower mortality in the LEOSS dataset compared to the statutory notification data.

COVID-19 Severity and Thrombo-Inflammatory Response Linked to Ethnicity.

Although there is strong evidence that SARS-CoV-2 infection is associated with adverse outcomes in certain ethnic groups, the association of disease severity and risk factors such as comorbidities and biomarkers with racial disparities remains undefined. This retrospective study between March 2020 and February 2021 explores COVID-19 risk factors as predictors for patients' disease progression through country comparison. Disease severity predictors in Germany and Japan were cardiovascular-associated comorbidities, dementia, and age. We adjusted age, sex, body mass index, and history of cardiovascular disease comorbidity in the country cohorts using a propensity score matching (PSM) technique to reduce the influence of differences in sample size and the surprisingly young, lean Japanese cohort. Analysis of the 170 PSM pairs confirmed that 65.29% of German and 85.29% of Japanese patients were in the uncomplicated phase. More German than Japanese patients were admitted in the complicated and critical phase. Ethnic differences were identified in patients without cardiovascular comorbidities. Japanese patients in the uncomplicated phase presented a suppressed inflammatory response and coagulopathy with hypocoagulation. In contrast, German patients exhibited a hyperactive inflammatory response and coagulopathy with hypercoagulation. These differences were less pronounced in patients in the complicated phase or with cardiovascular diseases. Coagulation/fibrinolysis-associated biomarkers rather than inflammatory-related biomarkers predicted disease severity in patients with cardiovascular comorbidities: platelet counts were associated with severe illness in German patients. In contrast, high D-dimer and fibrinogen levels predicted disease severity in Japanese patients. Our comparative study indicates that ethnicity influences COVID-19-associated biomarker expression linked to the inflammatory and coagulation (thrombo-inflammatory) response. Future studies will be necessary to determine whether these differences contributed to the less severe disease progression observed in Japanese COVID-19 patients compared with those in Germany.

Invasiveness of Ventilation Therapy Is Associated to Prevalence of Secondary Bacterial and Fungal Infections in Critically Ill COVID-19 Patients.

Superinfections are a fundamental critical care problem, and their significance in severe COVID-19 cases needs to be determined. This study analyzed data from the Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS) cohort focusing on intensive care patients. A retrospective analysis of patient data from 840 cases of COVID-19 with critical courses demonstrated that co-infections were frequently present and were primarily of nosocomial origin. Furthermore, our analysis showed that invasive therapy procedures accompanied an increased risk for healthcare-associated infections. Non-ventilated ICU patients were rarely affected by secondary infections. The risk of infection, however, increased even when non-invasive ventilation was used. A further, significant increase in infection rates was seen with the use of invasive ventilation and even more so with extracorporeal membrane oxygenation (ECMO) therapy. The marked differences among ICU techniques used for the treatment of COVID-19-induced respiratory failure in terms of secondary infection risk profile should be taken into account for the optimal management of critically ill COVID-19 patients, as well as for adequate antimicrobial therapy.

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.

Obesity and Impaired Metabolic Health Increase Risk of COVID-19-Related Mortality in Young and Middle-Aged Adults to the Level Observed in Older People: The LEOSS Registry.

Advanced age, followed by male sex, by far poses the greatest risk for severe COVID-19. An unresolved question is the extent to which modifiable comorbidities increase the risk of COVID-19-related mortality among younger patients, in whom COVID-19-related hospitalization strongly increased in 2021. A total of 3,163 patients with SARS-COV-2 diagnosis in the Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS) cohort were studied. LEOSS is a European non-interventional multi-center cohort study established in March 2020 to investigate the epidemiology and clinical course of SARS-CoV-2 infection. Data from hospitalized patients and those who received ambulatory care, with a positive SARS-CoV-2 test, were included in the study. An additive effect of obesity, diabetes and hypertension on the risk of mortality was observed, which was particularly strong in young and middle-aged patients. Compared to young and middle-aged (18-55 years) patients without obesity, diabetes and hypertension (non-obese and metabolically healthy; n = 593), young and middle-aged adult patients with all three risk parameters (obese and metabolically unhealthy; n = 31) had a similar adjusted increased risk of mortality [OR 7.42 (95% CI 1.55-27.3)] as older (56-75 years) non-obese and metabolically healthy patients [n = 339; OR 8.21 (95% CI 4.10-18.3)]. Furthermore, increased CRP levels explained part of the elevated risk of COVID-19-related mortality with age, specifically in the absence of obesity and impaired metabolic health. In conclusion, the modifiable risk factors obesity, diabetes and hypertension increase the risk of COVID-19-related mortality in young and middle-aged patients to the level of risk observed in advanced age.

A Comparison of Germany and the United Kingdom Indicates That More SARS-CoV-2 Circulation and Less Restrictions in the Warm Season Might Reduce Overall COVID-19 Burden.

(1) Background: Between March 2020 and January 2022 severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) caused five infection waves in Europe. The first and the second wave was caused by wildtype SARS-CoV-2, while the following waves were caused by the variants of concern Alpha, Delta, and Omicron respectively. (2) Methods: In the present analysis, the first four waves were compared in Germany and the UK, in order to examine the COVID-19 epidemiology and its modulation by non-pharmaceutical interventions (NPI). (3) Results: The number of COVID-19 patients on intensive care units and the case fatality rate were used to estimate disease burden, the excess mortality to assess the net effect of NPI and other measures on the population. The UK was more severely affected by the first and the third wave while Germany was more affected by the second wave. The UK had a higher excess mortality during the first wave, afterwards the excess mortality in both countries was nearly identical. While most NPI were lifted in the UK in July 2021, the measures were kept and even aggravated in Germany. Nevertheless, in autumn 2021 Germany was much more affected, nearly resulting in a balanced sum of infections and deaths compared to the UK. Within the whole observation period, in Germany the number of COVID-19 patients on ICUs was up to four times higher than in the UK. Our results show that NPI have a limited effect on COVID-19 burden, seasonality plays a crucial role, and a higher virus circulation in a pre-wave situation could be beneficial. (4) Conclusions: Although Germany put much more effort and resources to fight the pandemic, the net balance of both countries was nearly identical, questioning the benefit of excessive ICU treatments and of the implementation of NPI, especially during the warm season.

COVID-19 mortality in cirrhosis is determined by cirrhosis-associated comorbidities and extrahepatic organ failure: Results from the multinational LEOSS registry.

BACKGROUND AND OBJECTIVE: International registries have reported high mortality rates in patients with liver disease and COVID-19. However, the extent to which comorbidities contribute to excess COVID-19 mortality in cirrhosis is controversial. METHODS: We used the multinational Lean European Open Survey on SARS-CoV-2-infected patients (LEOSS) to identify patients with cirrhosis documented between March 2020 and March 2021, when the wild-type and alpha variant were predominant. We compared symptoms, disease progression and mortality after propensity score matching (PSM) for age, sex, obesity, smoking status, and concomitant diseases. Mortality was also compared with that of patients with spontaneous bacterial peritonitis (SBP) without SARS-CoV-2 infection, a common bacterial infection and well-described precipitator of acute-on-chronic liver failure. RESULTS: Among 7096 patients with SARS-CoV-2 infection eligible for analysis, 70 (0.99%) had cirrhosis, and all were hospitalized. Risk factors for severe COVID-19, such as diabetes, renal disease, and cardiovascular disease were more frequent in patients with cirrhosis. Case fatality rate in patients with cirrhosis was 31.4% with the highest odds of death in patients older than 65 years (43.6% mortality; odds ratio [OR] 4.02; p = 0.018), Child-Pugh class C (57.1%; OR 4.00; p = 0.026), and failure of two or more organs (81.8%; OR 19.93; p = 0.001). After PSM for demographics and comorbidity, the COVID-19 case fatality of patients with cirrhosis did not significantly differ from that of matched patients without cirrhosis (28.8% vs. 26.1%; p = 0.644) and was similar to the 28-day mortality in a comparison group of patients with cirrhosis and SBP (33.3% vs. 31.5%; p = 1.000). CONCLUSIONS: In immunologically naïve patients with cirrhosis, mortality from wild-type SARS-CoV-2 and the alpha variant is high and is largely determined by cirrhosis-associated comorbidities and extrahepatic organ failure.

Corrigendum to "Machine Learning Based Prediction of COVID-19 Mortality Suggests Repositioning of Anticancer Drug for Treating Severe Cases"[Artificial Intelligence in Life Sciences] 1(2021), 100020.

[This corrects the article DOI: 10.1016/j.ailsci.2021.100020.].

Machine Learning Based Prediction of COVID-19 Mortality Suggests Repositioning of Anticancer Drug for Treating Severe Cases.

Despite available vaccinations COVID-19 case numbers around the world are still growing, and effective medications against severe cases are lacking. In this work, we developed a machine learning model which predicts mortality for COVID-19 patients using data from the multi-center 'Lean European Open Survey on SARS-CoV-2-infected patients' (LEOSS) observational study (>100 active sites in Europe, primarily in Germany), resulting into an AUC of almost 80%. We showed that molecular mechanisms related to dementia, one of the relevant predictors in our model, intersect with those associated to COVID-19. Most notably, among these molecules was tyrosine kinase 2 (TYK2), a protein that has been patented as drug target in Alzheimer's Disease but also genetically associated with severe COVID-19 outcomes. We experimentally verified that anti-cancer drugs Sorafenib and Regorafenib showed a clear anti-cytopathic effect in Caco2 and VERO-E6 cells and can thus be regarded as potential treatments against COVID-19. Altogether, our work demonstrates that interpretation of machine learning based risk models can point towards drug targets and new treatment options, which are strongly needed for COVID-19.

Development and validation of a simplified risk score for the prediction of critical COVID-19 illness in newly diagnosed patients.

Scores to identify patients at high risk of progression of coronavirus disease (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), may become instrumental for clinical decision-making and patient management. We used patient data from the multicentre Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS) and applied variable selection to develop a simplified scoring system to identify patients at increased risk of critical illness or death. A total of 1946 patients who tested positive for SARS-CoV-2 were included in the initial analysis and assigned to derivation and validation cohorts (n = 1297 and n = 649, respectively). Stability selection from over 100 baseline predictors for the combined endpoint of progression to the critical phase or COVID-19-related death enabled the development of a simplified score consisting of five predictors: C-reactive protein (CRP), age, clinical disease phase (uncomplicated vs. complicated), serum urea, and D-dimer (abbreviated as CAPS-D score). This score yielded an area under the curve (AUC) of 0.81 (95% confidence interval [CI]: 0.77-0.85) in the validation cohort for predicting the combined endpoint within 7 days of diagnosis and 0.81 (95% CI: 0.77-0.85) during full follow-up. We used an additional prospective cohort of 682 patients, diagnosed largely after the "first wave" of the pandemic to validate the predictive accuracy of the score and observed similar results (AUC for the event within 7 days: 0.83 [95% CI: 0.78-0.87]; for full follow-up: 0.82 [95% CI: 0.78-0.86]). An easily applicable score to calculate the risk of COVID-19 progression to critical illness or death was thus established and validated.

Neurological symptoms and complications in predominantly hospitalized COVID-19 patients: Results of the European multinational Lean European Open Survey on SARS-Infected Patients (LEOSS).

BACKGROUND AND PURPOSE: During acute coronavirus disease 2019 (COVID-19) infection, neurological signs, symptoms and complications occur. We aimed to assess their clinical relevance by evaluating real-world data from a multinational registry. METHODS: We analyzed COVID-19 patients from 127 centers, diagnosed between January 2020 and February 2021, and registered in the European multinational LEOSS (Lean European Open Survey on SARS-Infected Patients) registry. The effects of prior neurological diseases and the effect of neurological symptoms on outcome were studied using multivariate logistic regression. RESULTS: A total of 6537 COVID-19 patients (97.7% PCR-confirmed) were analyzed, of whom 92.1% were hospitalized and 14.7% died. Commonly, excessive tiredness (28.0%), headache (18.5%), nausea/emesis (16.6%), muscular weakness (17.0%), impaired sense of smell (9.0%) and taste (12.8%), and delirium (6.7%) were reported. In patients with a complicated or critical disease course (53%) the most frequent neurological complications were ischemic stroke (1.0%) and intracerebral bleeding (ICB; 2.2%). ICB peaked in the critical disease phase (5%) and was associated with the administration of anticoagulation and extracorporeal membrane oxygenation (ECMO). Excessive tiredness (odds ratio [OR] 1.42, 95% confidence interval [CI] 1.20-1.68) and prior neurodegenerative diseases (OR 1.32, 95% CI 1.07-1.63) were associated with an increased risk of an unfavorable outcome. Prior cerebrovascular and neuroimmunological diseases were not associated with an unfavorable short-term outcome of COVID-19. CONCLUSION: Our data on mostly hospitalized COVID-19 patients show that excessive tiredness or prior neurodegenerative disease at first presentation increase the risk of an unfavorable short-term outcome. ICB in critical COVID-19 was associated with therapeutic interventions, such as anticoagulation and ECMO, and thus may be an indirect complication of a life-threatening systemic viral infection.

Angiotensin II receptor blocker intake associates with reduced markers of inflammatory activation and decreased mortality in patients with cardiovascular comorbidities and COVID-19 disease.

AIMS: Patients with cardiovascular comorbidities have a significantly increased risk for a critical course of COVID-19. As the SARS-CoV2 virus enters cells via the angiotensin-converting enzyme receptor II (ACE2), drugs which interact with the renin angiotensin aldosterone system (RAAS) were suspected to influence disease severity. METHODS AND RESULTS: We analyzed 1946 consecutive patients with cardiovascular comorbidities or hypertension enrolled in one of the largest European COVID-19 registries, the Lean European Open Survey on SARS-CoV-2 (LEOSS) registry. Here, we show that angiotensin II receptor blocker intake is associated with decreased mortality in patients with COVID-19 [OR 0.75 (95% CI 0,59-0.96; p = 0.013)]. This effect was mainly driven by patients, who presented in an early phase of COVID-19 at baseline [OR 0,64 (95% CI 0,43-0,96; p = 0.029)]. Kaplan-Meier analysis revealed a significantly lower incidence of death in patients on an angiotensin receptor blocker (ARB) (n = 33/318;10,4%) compared to patients using an angiotensin-converting enzyme inhibitor (ACEi) (n = 60/348;17,2%) or patients who received neither an ACE-inhibitor nor an ARB at baseline in the uncomplicated phase (n = 90/466; 19,3%; p<0.034). Patients taking an ARB were significantly less frequently reaching the mortality predicting threshold for leukocytes (p<0.001), neutrophils (p = 0.002) and the inflammatory markers CRP (p = 0.021), procalcitonin (p = 0.001) and IL-6 (p = 0.049). ACE2 expression levels in human lung samples were not altered in patients taking RAAS modulators. CONCLUSION: These data suggest a beneficial effect of ARBs on disease severity in patients with cardiovascular comorbidities and COVID-19, which is linked to dampened systemic inflammatory activity.

Gastrointestinal bleeding and endoscopic findings in critically and non-critically ill patients with corona virus disease 2019 (COVID-19): Results from Lean European Open Survey on SARS-CoV-2 (LEOSS) and COKA registries.

BACKGROUND: Corona virus disease 2019 (COVID-19) patients are at increased risk for thromboembolic events. It is unclear whether the risk for gastrointestinal (GI) bleeding is also increased. METHODS: We considered 4128 COVID-19 patients enrolled in the Lean European Open Survey on SARS-CoV-2 (LEOSS) registry. The association between occurrence of GI bleeding and comorbidities as well as medication were examined. In addition, 1216 patients from COKA registry were analyzed focusing on endoscopy diagnostic findings. RESULTS: A cumulative number of 97 patients (1.8%) with GI bleeding were identified in the LEOSS registry and COKA registry. Of 4128 patients from the LEOSS registry, 66 patients (1.6%) had a GI bleeding. The rate of GI bleeding in patients with intensive care unit (ICU) admission was 4.5%. The use of therapeutic dose of anticoagulants showed a significant association with the increased incidence of bleeding in the critical phase of disease. The Charlson comorbidity index and the COVID-19 severity index were significantly higher in the group of patients with GI bleeding than in the group of patients without GI bleeding (5.83 (SD = 2.93) vs. 3.66 (SD = 3.06), p < 0.01 and 3.26 (SD = 1.69) vs. 2.33 (SD = 1.53), p < 0.01, respectively). In the COKA registry 31 patients (2.5%) developed a GI bleeding. Of these, the source of bleeding was identified in upper GI tract in 21 patients (67.7%) with ulcer as the most frequent bleeding source (25.8%, n = 8) followed by gastroesophageal reflux (16.1%, n = 5). In three patients (9.7%) GI bleeding source was located in lower GI tract caused mainly by diverticular bleeding (6.5%, n = 2). In seven patients (22.6%) the bleeding localization remained unknown. CONCLUSION: Consistent with previous research, comorbidities and disease severity correlate with the incidence of GI bleeding. Also, therapeutic anticoagulation seems to be associated with a higher risk of GI bleeding. Overall, the risk of GI bleeding seems not to be increased in COVID-19 patients.

All-cause mortality and disease progression in SARS-CoV-2-infected patients with or without antibiotic therapy: an analysis of the LEOSS cohort.

PURPOSE: Reported antibiotic use in coronavirus disease 2019 (COVID-19) is far higher than the actual rate of reported bacterial co- and superinfection. A better understanding of antibiotic therapy in COVID-19 is necessary. METHODS: 6457 SARS-CoV-2-infected cases, documented from March 18, 2020, until February 16, 2021, in the LEOSS cohort were analyzed. As primary endpoint, the correlation between any antibiotic treatment and all-cause mortality/progression to the next more advanced phase of disease was calculated for adult patients in the complicated phase of disease and procalcitonin (PCT) ≤ 0.5 ng/ml. The analysis took the confounders gender, age, and comorbidities into account. RESULTS: Three thousand, six hundred twenty-seven cases matched all inclusion criteria for analyses. For the primary endpoint, antibiotic treatment was not correlated with lower all-cause mortality or progression to the next more advanced (critical) phase (n = 996) (both p > 0.05). For the secondary endpoints, patients in the uncomplicated phase (n = 1195), regardless of PCT level, had no lower all-cause mortality and did not progress less to the next more advanced (complicated) phase when treated with antibiotics (p > 0.05). Patients in the complicated phase with PCT > 0.5 ng/ml and antibiotic treatment (n = 286) had a significantly increased all-cause mortality (p = 0.029) but no significantly different probability of progression to the critical phase (p > 0.05). CONCLUSION: In this cohort, antibiotics in SARS-CoV-2-infected patients were not associated with positive effects on all-cause mortality or disease progression. Additional studies are needed. Advice of local antibiotic stewardship- (ABS-) teams and local educational campaigns should be sought to improve rational antibiotic use in COVID-19 patients.

Pre-medication with oral anticoagulants is associated with better outcomes in a large multinational COVID-19 cohort with cardiovascular comorbidities.

AIMS: Coagulopathy and venous thromboembolism are common findings in coronavirus disease 2019 (COVID-19) and are associated with poor outcome. Timely initiation of anticoagulation after hospital admission was shown to be beneficial. In this study we aim to examine the association of pre-existing oral anticoagulation (OAC) with outcome among a cohort of SARS-CoV-2 infected patients. METHODS AND RESULTS: We analysed the data from the large multi-national Lean European Open Survey on SARS-CoV-2 infected patients (LEOSS) from March to August 2020. Patients with SARS-CoV-2 infection were eligible for inclusion. We retrospectively analysed the association of pre-existing OAC with all-cause mortality. Secondary outcome measures included COVID-19-related mortality, recovery and composite endpoints combining death and/or thrombotic event and death and/or bleeding event. We restricted bleeding events to intracerebral bleeding in this analysis to ensure clinical relevance and to limit reporting errors. A total of 1 433 SARS-CoV-2 infected patients were analysed, while 334 patients (23.3%) had an existing premedication with OAC and 1 099 patients (79.7%) had no OAC. After risk adjustment for comorbidities, pre-existing OAC showed a protective influence on the endpoint death (OR 0.62, P = 0.013) as well as the secondary endpoints COVID-19-related death (OR 0.64, P = 0.023) and non-recovery (OR 0.66, P = 0.014). The combined endpoint death or thrombotic event tended to be less frequent in patients on OAC (OR 0.71, P = 0.056). CONCLUSIONS: Pre-existing OAC is protective in COVID-19, irrespective of anticoagulation regime during hospital stay and independent of the stage and course of disease.

Specific Risk Factors for Fatal Outcome in Critically Ill COVID-19 Patients: Results from a European Multicenter Study.

(1) Background: The aim of our study was to identify specific risk factors for fatal outcome in critically ill COVID-19 patients. (2) Methods: Our data set consisted of 840 patients enclosed in the LEOSS registry. Using lasso regression for variable selection, a multifactorial logistic regression model was fitted to the response variable survival. Specific risk factors and their odds ratios were derived. A nomogram was developed as a graphical representation of the model. (3) Results: 14 variables were identified as independent factors contributing to the risk of death for critically ill COVID-19 patients: age (OR 1.08, CI 1.06-1.10), cardiovascular disease (OR 1.64, CI 1.06-2.55), pulmonary disease (OR 1.87, CI 1.16-3.03), baseline Statin treatment (0.54, CI 0.33-0.87), oxygen saturation (unit = 1%, OR 0.94, CI 0.92-0.96), leukocytes (unit 1000/µL, OR 1.04, CI 1.01-1.07), lymphocytes (unit 100/µL, OR 0.96, CI 0.94-0.99), platelets (unit 100,000/µL, OR 0.70, CI 0.62-0.80), procalcitonin (unit ng/mL, OR 1.11, CI 1.05-1.18), kidney failure (OR 1.68, CI 1.05-2.70), congestive heart failure (OR 2.62, CI 1.11-6.21), severe liver failure (OR 4.93, CI 1.94-12.52), and a quick SOFA score of 3 (OR 1.78, CI 1.14-2.78). The nomogram graphically displays the importance of these 14 factors for mortality. (4) Conclusions: There are risk factors that are specific to the subpopulation of critically ill COVID-19 patients.

Prediction of COVID-19 deterioration in high-risk patients at diagnosis: an early warning score for advanced COVID-19 developed by machine learning.

PURPOSE: While more advanced COVID-19 necessitates medical interventions and hospitalization, patients with mild COVID-19 do not require this. Identifying patients at risk of progressing to advanced COVID-19 might guide treatment decisions, particularly for better prioritizing patients in need for hospitalization. METHODS: We developed a machine learning-based predictor for deriving a clinical score identifying patients with asymptomatic/mild COVID-19 at risk of progressing to advanced COVID-19. Clinical data from SARS-CoV-2 positive patients from the multicenter Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS) were used for discovery (2020-03-16 to 2020-07-14) and validation (data from 2020-07-15 to 2021-02-16). RESULTS: The LEOSS dataset contains 473 baseline patient parameters measured at the first patient contact. After training the predictor model on a training dataset comprising 1233 patients, 20 of the 473 parameters were selected for the predictor model. From the predictor model, we delineated a composite predictive score (SACOV-19, Score for the prediction of an Advanced stage of COVID-19) with eleven variables. In the validation cohort (n = 2264 patients), we observed good prediction performance with an area under the curve (AUC) of 0.73 ± 0.01. Besides temperature, age, body mass index and smoking habit, variables indicating pulmonary involvement (respiration rate, oxygen saturation, dyspnea), inflammation (CRP, LDH, lymphocyte counts), and acute kidney injury at diagnosis were identified. For better interpretability, the predictor was translated into a web interface. CONCLUSION: We present a machine learning-based predictor model and a clinical score for identifying patients at risk of developing advanced COVID-19.

Nine Months of COVID-19 Pandemic in Europe: A Comparative Time Series Analysis of Cases and Fatalities in 35 Countries.

(1) Background: to describe the dynamic of the pandemic across 35 European countries over a period of 9 months. (2) Methods: a three-phase time series model was fitted for 35 European countries, predicting deaths based on SARS-CoV-2 incidences. Hierarchical clustering resulted in three clusters of countries. A multiple regression model was developed predicting thresholds for COVID-19 incidences, coupled to death numbers. (3) Results: The model showed strongly connected deaths and incidences during the waves in spring and fall. The corrected case-fatality rates ranged from 2% to 20.7% in the first wave, and from 0.5% to 4.2% in the second wave. If the incidences stay below a threshold, predicted by the regression model (R2=85.0%), COVID-19 related deaths and incidences were not necessarily coupled. The clusters represented different regions in Europe, and the corrected case-fatality rates in each cluster flipped from high to low or vice versa. Severely and less severely affected countries flipped between the first and second wave. (4) Conclusions: COVID-19 incidences and related deaths were uncoupled during the summer but coupled during two waves. Once a country-specific threshold of infections is reached, death numbers will start to rise, allowing health care systems and countries to prepare.