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1.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-329901

ABSTRACT

Background: Establishing the optimal treatment for COVID-19 patients remains challenging. Specifically, immunocompromised and pre-diseased patients are at high risk for severe disease course and face limited therapeutic options. Convalescent plasma has been considered as therapeutic approach, but reliable data are lacking, especially for high-risk patients. Methods: We performed a retrospective analysis of 55 hospitalized COVID-19 patients with high risk for disease progression, primarily due to immunosuppression from cancer, solid organ transplantation, autoimmune disease, dialysis. A matched-pairs analysis (1:4) was performed with 220 patients from the Lean European Open Survey on SARS-CoV-2-infected Patients (LEOSS) who were treated or not treated with convalescent plasma. Results: Both cohorts, had high mortality (UKD 41.8%, LEOSS 34.1%). A matched-pairs analysis showed no significant effect on mortality. CP administration before the formation of pulmonary infiltrates showed the lowest mortality in both cohorts (10%), whereas mortality in the complicated phase was 27.8%. CP administration during the critical phase revealed the highest mortality;UKD 60.9%, LEOSS 48.3%. Conclusion: In our cohort of SARS-CoV-2 infected patients with severe comorbidities CP did not significantly reduce mortality in a retrospective matched pairs analysis. However, our data supports the concept that a reduction in mortality is achievable when CP is administered early.

2.
EuropePMC;
Preprint in English | EuropePMC | ID: ppcovidwho-328632

ABSTRACT

The German government initiated the Network University Medicine (NUM) in early 2020 to improve national research activities on the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic. To this end, 36 German Academic Medical Centers started to collaborate on 13 projects, with the largest being the National Pandemic Cohort Network (NAPKON). The NAPKON’s goal is creating the most comprehensive Coronavirus Disease 2019 (COVID-19) cohort in Germany. Within NAPKON, adult and pediatric patients are observed in three complementary cohort platforms (Cross-Sectoral, High-Resolution and Population-Based) from the initial infection until up to three years of follow-up. Study procedures comprise comprehensive clinical and imaging diagnostics, quality-of-life assessment, patient-reported outcomes and biosampling. The three cohort platforms build on four infrastructure core units (Interaction, Biosampling, Epidemiology, and Integration) and collaborations with NUM projects. Key components of the data capture, regulatory, and data privacy are based on the German Centre for Cardiovascular Research. By December 01, 2021, 34 university and 34 non-university hospitals have enrolled 4,241 patients with local data quality reviews performed on 2,812 (66%). 47% were female, the median age was 53 (IQR: 38-63)) and 3 pediatric cases were included. 30% of patients were hospitalized, 11% admitted to an intensive care unit, and 4% of patients deceased while enrolled. 7,143 visits with biosampling in 3,595 patients were conducted by November 29, 2021. In this overview article, we summarize NAPKON’s design, relevant milestones including first study population characteristics, and outline the potential of NAPKON for German and international research activities. Trial registration: · https://clinicaltrials.gov/ct2/show/NCT04768998· https://clinicaltrials.gov/ct2/show/NCT04747366· https://clinicaltrials.gov/ct2/show/NCT04679584

4.
Artif Intell Life Sci ; 1: 100020, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1588542

ABSTRACT

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.

5.
Eur J Neurol ; 28(12): 3925-3937, 2021 12.
Article in English | MEDLINE | ID: covidwho-1515204

ABSTRACT

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.


Subject(s)
COVID-19 , Neurodegenerative Diseases , Stroke , Headache , Humans , SARS-CoV-2
6.
Non-conventional in English | MEDLINE, Grey literature | ID: grc-750534

ABSTRACT

Solid organ transplantation is a lifesaving routine procedure. In the wake of the COVID-19 pandemic, procurement and transplantation programs in many countries experienced a considerable reduction of organ donation and transplantation by up to 90% caused by an capacity overload of health care providers but also for fear of increased COVID-19 related risks for transplant recipients acquired by viral transmissions from donor to recipient or early after transplantation. Competition for intensive care capacity for severely ill COVID-19 patients versus transplant recipients and organ donors could also have played a role. In Germany, early pandemic management with high capacity testing including all potential organ donors, marked extension of intensive care capacities, structural health care system with a relatively high number of hospitals with intensive care units (1248) as well as transplant centers (40) with high capacities and regional organization of organ donation and transplantation may have been advantageous.

7.
Gesundheitswesen ; 83(S 01): S45-S53, 2021 Nov.
Article in German | MEDLINE | ID: covidwho-1500783

ABSTRACT

OBJECTIVE: The Coronavirus Disease-2019 (COVID-19) pandemic has brought opportunities and challenges, especially for health services research based on routine data. In this article we will demonstrate this by presenting lessons learned from establishing the currently largest registry in Germany providing a detailed clinical dataset on Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infected patients: the Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS). METHODS: LEOSS is based on a collaborative and integrative research approach with anonymous recruitment and collection of routine data and the early provision of data in an open science context. The only requirement for inclusion was a SARS-CoV-2 infection confirmed by virological diagnosis. Crucial strategies to successfully realize the project included the dynamic reallocation of available staff and technical resources, an early and direct involvement of data protection experts and the ethics committee as well as the decision for an iterative and dynamic process of improvement and further development. RESULTS: Thanks to the commitment of numerous institutions, a transsectoral and transnational network of currently 133 actively recruiting sites with 7,227 documented cases could be established (status: 18.03.2021). Tools for data exploration on the project website, as well as the partially automated provision of datasets according to use cases with varying requirements, enabled us to utilize the data collected within a short period of time. Data use and access processes were carried out for 97 proposals assigned to 27 different research areas. So far, nine articles have been published in peer-reviewed international journals. CONCLUSION: As a collaborative effort of the whole network, LEOSS developed into a large collection of clinical data on COVID-19 in Germany. Even though in other international projects, much larger data sets could be analysed to investigate specific research questions through direct access to source systems, the uniformly maintained and technically verified documentation standard with many discipline-specific details resulted in a large valuable data set with unique characteristics. The lessons learned while establishing LEOSS during the current pandemic have already created important implications for the design of future registries and for pandemic preparedness and response.


Subject(s)
COVID-19 , Pandemics , Germany/epidemiology , Health Services Research , Humans , Pandemics/prevention & control , Registries , SARS-CoV-2
8.
PLoS One ; 16(10): e0258684, 2021.
Article in English | MEDLINE | ID: covidwho-1480452

ABSTRACT

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.


Subject(s)
Angiotensin Receptor Antagonists/administration & dosage , COVID-19 , Hypertension , Registries , SARS-CoV-2/metabolism , Adult , Aged , Aged, 80 and over , Angiotensin-Converting Enzyme Inhibitors/administration & dosage , Biomarkers/blood , COVID-19/blood , COVID-19/drug therapy , COVID-19/mortality , Comorbidity , Disease-Free Survival , Female , Humans , Hypertension/blood , Hypertension/drug therapy , Hypertension/mortality , Inflammation/blood , Inflammation/drug therapy , Inflammation/mortality , Male , Middle Aged , Severity of Illness Index , Survival Rate
9.
United European Gastroenterol J ; 9(9): 1081-1090, 2021 11.
Article in English | MEDLINE | ID: covidwho-1469560

ABSTRACT

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.


Subject(s)
COVID-19/epidemiology , Endoscopy, Gastrointestinal , Gastrointestinal Hemorrhage/epidemiology , Adolescent , Adult , Aged , Aged, 80 and over , Anticoagulants/adverse effects , Child , Child, Preschool , Comorbidity , Critical Illness , Diverticular Diseases/diagnosis , Europe/epidemiology , Female , Gastroesophageal Reflux/complications , Gastrointestinal Hemorrhage/etiology , Hospitalization , Humans , Infant , Intensive Care Units , Male , Middle Aged , Peptic Ulcer/diagnosis , Registries , Severity of Illness Index , Young Adult
10.
J Clin Med ; 10(17)2021 Aug 27.
Article in English | MEDLINE | ID: covidwho-1374437

ABSTRACT

(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.

11.
Infection ; 50(2): 359-370, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1316346

ABSTRACT

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.


Subject(s)
COVID-19 , Early Warning Score , Area Under Curve , COVID-19/diagnosis , Humans , Machine Learning , Retrospective Studies , SARS-CoV-2
12.
Math Biosci ; 339: 108648, 2021 09.
Article in English | MEDLINE | ID: covidwho-1294054

ABSTRACT

Non-pharmaceutical interventions (NPIs) are important to mitigate the spread of infectious diseases as long as no vaccination or outstanding medical treatments are available. We assess the effectiveness of the sets of non-pharmaceutical interventions that were in place during the course of the Coronavirus disease 2019 (Covid-19) pandemic in Germany. Our results are based on hybrid models, combining SIR-type models on local scales with spatial resolution. In order to account for the age-dependence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), we include realistic prepandemic and recently recorded contact patterns between age groups. The implementation of non-pharmaceutical interventions will occur on changed contact patterns, improved isolation, or reduced infectiousness when, e.g., wearing masks. In order to account for spatial heterogeneity, we use a graph approach and we include high-quality information on commuting activities combined with traveling information from social networks. The remaining uncertainty will be accounted for by a large number of randomized simulation runs. Based on the derived factors for the effectiveness of different non-pharmaceutical interventions over the past months, we provide different forecast scenarios for the upcoming time.


Subject(s)
COVID-19 , Communicable Disease Control , Models, Statistical , Social Network Analysis , Spatial Analysis , Age Factors , COVID-19/prevention & control , COVID-19/transmission , Communicable Disease Control/methods , Communicable Disease Control/standards , Communicable Disease Control/statistics & numerical data , Germany , Humans
14.
Lancet Reg Health Eur ; 6: 100122, 2021 Jul.
Article in English | MEDLINE | ID: covidwho-1233525

ABSTRACT

BACKGROUND: While the leading symptoms during coronavirus disease 2019 (COVID-19) are acute and the majority of patients fully recover, a significant fraction of patients now increasingly experience long-term health consequences. However, most data available focus on health-related events after severe infection and hospitalisation. We present a longitudinal, prospective analysis of health consequences in patients who initially presented with no or minor symptoms of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) infection. Hence, we focus on mild COVID-19 in non-hospitalised patients. METHODS: 958 Patients with confirmed SARS-CoV-2 infection were observed from April 6th to December 2nd 2020 for long-term symptoms and SARS-CoV-2 antibodies. We identified anosmia, ageusia, fatigue or shortness of breath as most common, persisting symptoms at month 4 and 7 and summarised presence of such long-term health consequences as post-COVID syndrome (PCS). Predictors of long-term symptoms were assessed using an uni- and multivariable logistic regression model. FINDINGS: We observed 442 and 353 patients over four and seven months after symptom onset, respectively. Four months post SARS-CoV-2 infection, 8•6% (38/442) of patients presented with shortness of breath, 12•4% (55/442) with anosmia, 11•1% (49/442) with ageusia and 9•7% (43/442) with fatigue. At least one of these characteristic symptoms was present in 27•8% (123/442) and 34•8% (123/353) at month 4 and 7 post-infection, respectively. A lower baseline level of SARS-CoV-2 IgG, anosmia and diarrhoea during acute COVID-19 were associated with higher risk to develop long-term symptoms. INTERPRETATION: The on-going presence of either shortness of breath, anosmia, ageusia or fatigue as long-lasting symptoms even in non-hospitalised patients was observed at four and seven months post-infection and summarised as post-COVID syndrome (PCS). The continued assessment of patients with PCS will become a major task to define and mitigate the socioeconomic and medical long-term effects of COVID-19. FUNDING: COVIM:"NaFoUniMedCovid19"(FKZ: 01KX2021).

15.
Infection ; 49(4): 725-737, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1182343

ABSTRACT

PURPOSE: The ongoing pandemic caused by the novel severe acute respiratory coronavirus 2 (SARS-CoV-2) has stressed health systems worldwide. Patients with chronic kidney disease (CKD) seem to be more prone to a severe course of coronavirus disease (COVID-19) due to comorbidities and an altered immune system. The study's aim was to identify factors predicting mortality among SARS-CoV-2-infected patients with CKD. METHODS: We analyzed 2817 SARS-CoV-2-infected patients enrolled in the Lean European Open Survey on SARS-CoV-2-infected patients and identified 426 patients with pre-existing CKD. Group comparisons were performed via Chi-squared test. Using univariate and multivariable logistic regression, predictive factors for mortality were identified. RESULTS: Comparative analyses to patients without CKD revealed a higher mortality (140/426, 32.9% versus 354/2391, 14.8%). Higher age could be confirmed as a demographic predictor for mortality in CKD patients (> 85 years compared to 15-65 years, adjusted odds ratio (aOR) 6.49, 95% CI 1.27-33.20, p = 0.025). We further identified markedly elevated lactate dehydrogenase (> 2 × upper limit of normal, aOR 23.21, 95% CI 3.66-147.11, p < 0.001), thrombocytopenia (< 120,000/µl, aOR 11.66, 95% CI 2.49-54.70, p = 0.002), anemia (Hb < 10 g/dl, aOR 3.21, 95% CI 1.17-8.82, p = 0.024), and C-reactive protein (≥ 30 mg/l, aOR 3.44, 95% CI 1.13-10.45, p = 0.029) as predictors, while renal replacement therapy was not related to mortality (aOR 1.15, 95% CI 0.68-1.93, p = 0.611). CONCLUSION: The identified predictors include routinely measured and universally available parameters. Their assessment might facilitate risk stratification in this highly vulnerable cohort as early as at initial medical evaluation for SARS-CoV-2.


Subject(s)
COVID-19/complications , COVID-19/mortality , Renal Insufficiency, Chronic/complications , SARS-CoV-2 , Adolescent , Adult , Aged, 80 and over , Cohort Studies , Comorbidity , Humans , Logistic Models , Middle Aged , Renal Insufficiency, Chronic/immunology , Risk Factors , Young Adult
17.
Infection ; 49(1): 63-73, 2021 Feb.
Article in English | MEDLINE | ID: covidwho-812468

ABSTRACT

PURPOSE: Knowledge regarding patients' clinical condition at severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection is sparse. Data in the international, multicenter Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS) cohort study may enhance the understanding of COVID-19. METHODS: Sociodemographic and clinical characteristics of SARS-CoV-2-infected patients, enrolled in the LEOSS cohort study between March 16, 2020, and May 14, 2020, were analyzed. Associations between baseline characteristics and clinical stages at diagnosis (uncomplicated vs. complicated) were assessed using logistic regression models. RESULTS: We included 2155 patients, 59.7% (1,287/2,155) were male; the most common age category was 66-85 years (39.6%; 500/2,155). The primary COVID-19 diagnosis was made in 35.0% (755/2,155) during complicated clinical stages. A significant univariate association between age; sex; body mass index; smoking; diabetes; cardiovascular, pulmonary, neurological, and kidney diseases; ACE inhibitor therapy; statin intake and an increased risk for complicated clinical stages of COVID-19 at diagnosis was found. Multivariable analysis revealed that advanced age [46-65 years: adjusted odds ratio (aOR): 1.73, 95% CI 1.25-2.42, p = 0.001; 66-85 years: aOR 1.93, 95% CI 1.36-2.74, p < 0.001; > 85 years: aOR 2.38, 95% CI 1.49-3.81, p < 0.001 vs. individuals aged 26-45 years], male sex (aOR 1.23, 95% CI 1.01-1.50, p = 0.040), cardiovascular disease (aOR 1.37, 95% CI 1.09-1.72, p = 0.007), and diabetes (aOR 1.33, 95% CI 1.04-1.69, p = 0.023) were associated with complicated stages of COVID-19 at diagnosis. CONCLUSION: The LEOSS cohort identified age, cardiovascular disease, diabetes and male sex as risk factors for complicated disease stages at SARS-CoV-2 diagnosis, thus confirming previous data. Further data regarding outcomes of the natural course of COVID-19 and the influence of treatment are required.


Subject(s)
COVID-19/epidemiology , Cardiovascular Diseases/epidemiology , Diabetes Mellitus/epidemiology , Kidney Diseases/epidemiology , Lung Diseases/epidemiology , Pandemics , Adolescent , Adult , Age Factors , Aged , Aged, 80 and over , Angiotensin-Converting Enzyme Inhibitors/adverse effects , Body Mass Index , COVID-19/diagnosis , COVID-19/physiopathology , COVID-19/virology , Cardiovascular Diseases/diagnosis , Cardiovascular Diseases/physiopathology , Cardiovascular Diseases/virology , Cohort Studies , Comorbidity , Diabetes Mellitus/diagnosis , Diabetes Mellitus/physiopathology , Diabetes Mellitus/virology , Europe/epidemiology , Female , Humans , Hydroxymethylglutaryl-CoA Reductase Inhibitors/adverse effects , Kidney Diseases/diagnosis , Kidney Diseases/physiopathology , Kidney Diseases/virology , Logistic Models , Lung Diseases/diagnosis , Lung Diseases/physiopathology , Lung Diseases/virology , Male , Middle Aged , SARS-CoV-2/pathogenicity , Severity of Illness Index , Sex Factors
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