key: cord-0818802-wap59myy
authors: Nachtigall, Irit; Lenga, Pavlina; Jóźwiak, Katarzyna; Thürmann, Petra; Meier-Hellmann, Andreas; Kuhlen, Ralf; Brederlau, Joerg; Bauer, Torsten; Tebbenjohanns, Juergen; Schwegmann, Karin; Hauptmann, Michael; Dengler, Julius
title: Clinical course and factors associated with outcomes among 1904 patients hospitalized with COVID-19 in Germany: an observational study
date: 2020-08-18
journal: Clin Microbiol Infect
DOI: 10.1016/j.cmi.2020.08.011
sha: 9619f35ea6bf20b44e15da9fad7570f0d4eed794
doc_id: 818802
cord_uid: wap59myy

OBJECTIVES: The coronavirus disease 2019 (COVID-19) pandemic situation in Germany is unique among large European countries in that incidence and case fatality rate are distinctly lower. We describe the clinical course and examine factors associated with outcomes among patients hospitalized with COVID-19 in Germany. METHODS: In this retrospective cohort study we included patients with COVID-19 admitted to a national network of German hospitals between February 12, and June 12, 2020. We examined demographic characteristics, comorbidities and clinical outcomes. RESULTS: We included 1904 patients with a median age of 73 years, and 48.5% (924/1904) were female. The mortality rate was 17% (317/1835; 95% confidence interval [CI] 16-19), the rate of admission to the intensive care unit (ICU) 21% (399/1860; 95% CI 20–23), and the rate of invasive mechanical ventilation 14% (250/1850: 95% CI 12–15). The most prominent risk factors for death were male sex (hazard ratio [HR] 1.45; 95% CI 1.2-1.8), preexisting lung disease (HR 1.61; 95% CI 1.20-2.16), and increased patient age (HR 4.1 [95% CI 2.6–6.6] for age >79 years versus <60 years). Among patients admitted to the ICU, the mortality rate was 29% (109/374; 95% CI 25–34) and higher in ventilated (33% [77/235; 95% CI 27-39]) than in non-ventilated ICU patients (23% [32/139; 95% CI 16-30]; p<0.05). CONCLUSIONS: In this nationwide series of patients hospitalized with COVID-19 in Germany, in-hospital and ICU mortality rates were substantial. The most prominent risk factors for death were male sex, preexisting lung disease, and increased patient age.

The outbreak of coronavirus disease 2019 in Germany differs from other countries in certain aspects. First, the estimated incidence of COVID-19 in Germany (0.85%) is distinctly lower than in other large European countries with similar demographic and economic structure, such as Spain (5.5%), Italy (4.6%), the UK (5.1%), France (3.4%), or Belgium (8.0%). 1 Second, in Germany, the pandemic has been associated with a substantially lower case fatality rate (CFR) of 4.6% compared with Spain (11.3%), Italy (14.4%), the UK (15.5%), and even neighbouring countries such as France (14.6%) and Belgium (15.8%). 2 These comparably low figures may be due to non-pharmaceutical interventions against COVID-19 being more effective in Germany than in other European countries. 1 However, Germany's lower incidence of COVID-19 and the resulting lack of population immunity may render the German population more vulnerable to a potential second wave of the pandemic. It is unclear whether there is an association between a lower incidence of COVID-19 and a low CFR. In examining this issue, one of the major limitations is that, to date, no comprehensive nationwide clinical data on COVID-19 have emerged from Germany. Such evidence may be important in understanding whether the course of COVID-19 in a country with a lower disease burden may differ from that observed in other countries and may shed light on methods to prevent a second wave of infection or limit its impact on the population. We therefore describe clinical characteristics of all patients with COVID-19 admitted to a nationwide German hospital network and report risk factors associated with patient outcomes.

This retrospective multicenter observational clinical study consecutively enrolled all patients admitted with laboratory-confirmed COVID-19 to any of the 86 hospitals of the Helios network. As the largest private health care provider in Germany, the Helios network accounts for 6.5% of patient hospitalizations nationwide and represents small and large as well as general and academic hospitals in rural and urban areas in 13 of the 16 federal states of Germany (Fig. S1 ). 3 During this study, patients with COVID-19 were admitted to 75 network hospitals; the remaining 11 centers did not see any COVID-19 patients. The study was approved by the internal review board of the Brandenburg Medical School (Neuruppin, Germany) on March 24, 2020 (E01-20200319) and registered with the German Clinical Trials Register (DRKS00021161). Individual informed consent was waived based on the retrospective nature of this study. The inclusion criteria were laboratory-confirmed COVID-19 and admission to a hospital within the Helios network. The only exclusion criterion was a lack of J o u r n a l P r e -p r o o f laboratory-confirmation of COVID-19. The study endpoints were process variables, such as admission to the ICU and use of invasive mechanical ventilation, and outcome variables such as length of stay and death from any cause.

Eligible patients were admitted between February 12, 2020, and June 12, 2020 and had laboratoryconfirmed COVID-19 according to the WHO interim guidance. 4 The diagnosis was based on real time reverse transcription polymerase chain reaction of nasal and pharyngeal swab specimens. Of the 1933 eligible patients, 29 were excluded since they had been transferred from other hospitals and data on the preceding hospitalization were not available. For three patients we used the date of the positive COVID-19 test as time of admission since they had been hospitalized for other reasons prior to the study period. For 25 patients with hospital stay in two different time periods we used only information on the first one. Demographic, clinical, laboratory, management and outcome data were collected from the paper medical records by trained hospital staff and entered into a separate registry, which serves as an addition to our hospitals' routine infection control system. Registry data were consecutive and compared with routine administrative healthcare data and inconsistencies were resolved by individual review of medical records. More details are provided in the online Supplementary Material.

Continuous variables were summarized using medians and interquartile ranges (IQR); categorical variables were summarized with counts and percentages. Mortality rate was the percentage of patients who died while in hospital relative to all patients discharged (alive or dead). Mortality rate on ICU was the percentage of patients who died on ICU relative to all patients ever admitted to ICU who had been discharged (alive or dead). We also calculated the percentage of patients who were admitted to ICU relative to all patients currently on ICU or discharged (alive or dead), and the percentage of patients who were invasively mechanically ventilated relative to all patients currently being ventilated or discharged (alive or dead). Confidence intervals for percentages were based on the exact binomial distribution. Cumulative incidences and hazard ratios (HR) for time to the following endpoints were calculated: admission to the ICU, invasive mechanical ventilation, and death (among all patients and among those admitted to the ICU). Time at risk started at the date of hospitalization and ended at the date of ICU admission, the start of invasive mechanical ventilation, and the date of death, depending on the outcome studied. For the analyses of J o u r n a l P r e -p r o o f mortality among patients admitted to the ICU, time at risk started at the date of ICU admission. Patients were censored at date of last updated information. All survival analyses were conducted using competing risk models that considered hospital discharge a competing event. For endpoints other than mortality, death was considered a competing event.

Multivariable proportional hazards models were used to assess associations of clinical characteristics with cause-specific incidences, 5 

We provide analyses of 1904 consecutive patients with laboratory confirmed COVID-19 admitted to 75 hospitals in Germany. The in-hospital mortality rate was 17% and the risk of death was higher for older age, male sex and preexisting cardiovascular or lung disease. Men were also more likely to be admitted to the ICU and to receive invasive mechanical ventilation. The rate of ICU admission was 21% and that of invasive mechanical ventilation 14%. Among patients admitted to the ICU, we observed a mortality rate of 29% and a higher risk of death among patients receiving invasive mechanical ventilation. Germany stem from a study that selectively examined health insurance claims data of one specific insurance fund (AOK). 7 While this study included more than 10.000 patients, its generalizability to the German population may be limited, since AOK members are known to have a higher prevalence of chronic diseases, such as hypertension, diabetes and coronary artery disease. 8 Indeed, in our study, which consecutively included all patients irrespective of insurance fund, the prevalence of diabetes was 15% compared to 28% in the AOK-study. This may contribute to a higher mortality rate in the AOK-study (22%) compared to our study (17%).

The incidence of COVID-19 in Germany is estimated to be substantially lower than in other large European countries, 1 as is the overall CFR. 2 In addition, Germany's health infrastructure may be more resistant to overburdening due to comparably ample hospital bed and ICU bed capacity. 9,10 For example, Germany's ICU bed capacity is 29 per 100.000 population, which is substantially higher than in most European countries, such as Belgium (16), France (12), the UK (7), Italy (13) , and Spain (10) . 10 Even though the benefit of a high ICU bed capacity is uncertain in this current global pandemic, 11 health care professionals in China and Italy have suggested that avoiding strain on ICU bed capacity may directly impact on disease outcomes. 12, 13 Descriptions of the clinical course of COVID-19 on a national scale are scarce. A recent nationwide series from the UK examined 20.133 patients hospitalized with COVID-19. 14 The authors describe mortality rates of 26% among all patients and 32% among patients on ICU or high dependency units, J o u r n a l P r e -p r o o f These numbers are slightly higher than those observed in our study, which may be explained by differences in age distributions among patients receiving invasive mechanical ventilation.

Another nationwide study from China describes 1.099 patients hospitalized with COVID-19. 15 The ICU admission rate was 5.0%, 2.3% received mechanical ventilation and 1.4% died. These figures are up to 10-fold lower than those observed in the UK and in our cohort, which may be explained by the Chinese study's strikingly lower median age of 47 years. Regionally limited case series from China describe older patient cohorts with poorer outcomes compared to the national study. [16] [17] [18] Other large clinical series on COVID-19 emerged from narrow geographic locations with high infection rates. In the Lombardy region, 13 among 1.591 consecutive patients admitted to the ICU, the total mortality rate was 26%, which is comparable to the mortality rate among ICU patients in our study. Another large clinical case series on COVID-19 originates from the New York City metropolitan area 19 and presents outcomes for 2.634 patients, of which 14% were admitted to the ICU, which is comparable to 20% observed in our study.

The fact that hospitalized patients in our study were older than those in cluster regions with massive outbreaks may suggest that, in Germany, a higher proportion of older patients with COVID-19 was admitted to hospitals. This may have been facilitated by a large pool of vacant hospital beds. In addition, more widespread COVID-19 testing ability in Germany than in other countries 20 may have led to improved identification of older patients with flu-like symptoms, who may have otherwise gone unnoticed and remained in their usual environment as potential viral spreaders. Considering that in other countries a large source of transmission were long-term and elderly care facilities, 21, 22 Germany may have avoided such outbreaks by being able to isolate even older symptomatic patients by hospitalizing them. The fact that in our study patients older than 79 years were at highest risk of death, but at decreased risk of admission to the ICU or initiation of invasive mechanical ventilation, suggests strict implementation of DNI orders, which appear to have been common in this age group in our study.

Our study has several limitations. First, it focuses exclusively on hospitalized patients and our findings can therefore not be generalized to patients displaying either no or only mild symptoms of COVID-19. Second, we focus on patients with laboratory-confirmed COVID-19 and do not include cases with typical clinical symptoms but negative test results. Third, information on comorbidities was limited due to the nature of the hospital infection control registry and in keeping with national data protection laws; however, in review of the literature we are unlikely to have missed key predictors for our endpoints. Finally, we used a limited control sample to estimate that patients older than 79 years were less likely to be admitted to the ICU than their younger peers due to DNI orders.

In conclusion, in-hospital and ICU mortality rates among patients with COVID-19 were substantial in this nationwide series. The most prominent risk factors for death were male sex, preexisting lung disease, and increased patient age. 

Estimating the Effects of Non-Pharmaceutical

Clinical management of severe acute respiratory infection when novel coronavirus (2019-nCoV) infection is suspected: interim guidance

A proportional hazards model for the subdistribution of a competing risk

Case characteristics, resource use, and outcomes of 10 021 patients with COVID-19 admitted to 920 German hospitals: an observational study

Structural differences between health insurance funds and their impact on health services research: results from the Bertelsmann Health-Care Monitor

Hospital Beds (indicator)

The variability of critical care bed numbers in Europe

ICU beds: less is more? Not sure

Association of Public Health Interventions With the Epidemiology of the COVID-19 Outbreak in Wuhan, China

Baseline Characteristics and Outcomes of 1591

Patients Infected With SARS-CoV-2 Admitted to ICUs of the Lombardy Region, Italy

Features of 20 133 UK patients in hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: prospective observational cohort study

Clinical Characteristics of Coronavirus disease in China

Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study

Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study

Clinical characteristics of 138 Hospitalized patients With

Novel Coronavirus-Infected Pneumonia in Wuhan, China

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Epidemiology of Covid-19 in a Long-Term Care Facility in King County, Washington

Abbreviations: ICU, intensive care unit; IMV, invasive mechanical ventilation; FU, follow up; CI, confidence interval; ref, reference. a Mean follow-up for all patients, gender and age based on 1904 patients and for symptoms and comorbidities based on 1709 patients. b Hazard ratios adjusted for all variables listed in table and calculated with data of 1709 patients

Table 3. Mortality rate among all hospitalized patients and among patients admitted to the ICU

We would like to thank the members of the nursing and medical staff at all HELIOS hospitals for their efforts in caring for patients in these difficult times. We also thank all hygiene specialists involved in this study. 

J o u r n a l P r e -p r o o f Data are n (%) or median (IQR). Abbreviations: IQR, interquartile range. *Information on symptoms and comorbidities was available for 1709 patients a Diabetes mellitus defined as prolonged high blood sugar levels due to metabolic disorders, such as Type 1 diabetes and Type 2 diabetes. b Malignancy defined as any cancer (malign tumor) with potential invasion of or spreading to other parts of the body, such as glioblastoma, stomach cancer, colorectal cancer, melanoma, renal cancer, breast cancer or prostate cancer, among others. C Cardiovascular disease defined as any cardiac injury, such as myocardial infarction, angina pectoris, hypertensive heart disease, cardiomyopathy, aortic aneurysms, congenital heart disease, or peripheral heart disease, among others. d Lung disease defined as any respiratory tract disease, such as lung injury, chronic obstructive lung disease, asthma, bronchiectasis, chronic bronchitis, or pulmonary tuberculosis, among others. J o u r n a l P r e -p r o o f