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Clin Res Cardiol ; 2022 Dec 24.
Article in English | MEDLINE | ID: covidwho-2174097


BACKGROUND: Myocarditis in context of a SARS-CoV-2 infection is vividly discussed in the literature. Real-world data however are sparse, and relevance of the myocarditis diagnosis to outcome in coronavirus disease (COVID-19) is unclear. PATIENTS AND METHODS: Retrospective analysis of 75,304 patients hospitalized in Germany with myocarditis between 2007 and 2020 is reported by DESTATIS. Patients hospitalized between 01/2016 and 12/2019 served as reference cohort for the COVID-19 patients hospitalized in 2020. RESULTS: A total of 75,304 patients were hospitalized between 2007 and 2020 (age 42.5 years, 30.1% female, hospital mortality 2.4%). In the reference cohort, 24,474 patients (age 42.8 years, 29.5% female, hospital mortality 2.2%) were registered. In 2020, annual myocarditis hospitalizations dropped by 19.6% compared to reference (4921 vs. 6119 annual hospitalization), of which 443/4921 (9.0%) were connected to COVID-19. In 2020, hospital mortality of myocarditis in non-COVID-19 patients increased significantly compared to reference (2.9% vs. 2.2%, p = 0.008, OR 1.31, 95% CI 1.08-1.60). In COVID-19 myocarditis, hospital mortality was even higher compared to reference (13.5% vs. 2.2%, p < 0.001, OR 6.93, 95% CI 5.18-9.18). CONCLUSION: The burden of patients with myocarditis and COVID-19 in 2020 was low. Hospital mortality was more than sixfold higher in patients with myocarditis and COVID-19 compared to those with myocarditis but without COVID-19.

Clin Res Cardiol ; 2022 Oct 06.
Article in English | MEDLINE | ID: covidwho-2048251


BACKGROUND: The COVID-19 pandemic led to extensive restrictions in Germany in 2020, including the postponement of elective interventions. We examined the impact on ST-elevation myocardial infarction (STEMI) as an acute and non-postponable disease. METHODS: Using German national records, all STEMI between 2017 and 2020 were identified. Using the number of STEMI cases between 2017 and 2019, we created a forecast for 2020 and compared it with the observed number of STEMI in 2020. RESULTS: From 2017 to 2020, 248,062 patients were treated for STEMI in Germany. Mean age was 65.21 years and 28.36% were female. When comparing forecasted and observed STEMI in 2020, a correlation can be seen: noticeable fewer STEMI were treated in those weeks respectively months with an increasing COVID-19 hospitalization rate (monthly percentage decrease in STEMI: March - 14.85%, April - 13.39%, November - 11.92%, December - 22.95%). At the same time, the crude in-hospital mortality after STEMI increased significantly at the peaks of the first and second waves (relative risk/RR of monthly in-hospital mortality: April RR = 1.11 [95% CI 1.02; 1.21], November RR = 1.13 [1.04; 1.24], December RR = 1.16 [1.06; 1.27]). CONCLUSION: The COVID-19 pandemic led to a noticeable decrease in the number of STEMI interventions in Germany at the peaks of the first and second waves in 2020, corresponding to an increase in COVID-19 hospitalizations. At the same time, in-hospital mortality after STEMI increased significantly in these phases. Impact of the COVID-19 pandemic on STEMI numbers and in-hospital mortality in Germany. Relative difference between forecasted and observed STEMI numbers (above figure), the relative risk of in-hospital mortality (middle figure) as well as number of new hospital admissions for COVID-19 per million inhabitants according to Roser et al.27 (bottom figure).

BMC Med Res Methodol ; 20(1): 206, 2020 08 11.
Article in English | MEDLINE | ID: covidwho-705522


BACKGROUND: The clinical progress of patients hospitalized due to COVID-19 is often associated with severe pneumonia which may require intensive care, invasive ventilation, or extracorporeal membrane oxygenation (ECMO). The length of intensive care and the duration of these supportive therapies are clinically relevant outcomes. From the statistical perspective, these quantities are challenging to estimate due to episodes being time-dependent and potentially multiple, as well as being determined by the competing, terminal events of discharge alive and death. METHODS: We used multistate models to study COVID-19 patients' time-dependent progress and provide a statistical framework to estimate hazard rates and transition probabilities. These estimates can then be used to quantify average sojourn times of clinically important states such as intensive care and invasive ventilation. We have made two real data sets of COVID-19 patients (n = 24* and n = 53**) and the corresponding statistical code publically available. RESULTS: The expected lengths of intensive care unit (ICU) stay at day 28 for the two cohorts were 15.05* and 19.62** days, while expected durations of mechanical ventilation were 7.97* and 9.85** days. Predicted mortality stood at 51%* and 15%**. Patients mechanically ventilated at the start of the example studies had a longer expected duration of ventilation (12.25*, 14.57** days) compared to patients non-ventilated (4.34*, 1.41** days) after 28 days. Furthermore, initially ventilated patients had a higher risk of death (54%* and 20%** vs. 48%* and 6%**) after 4 weeks. These results are further illustrated in stacked probability plots for the two groups from time zero, as well as for the entire cohort which depicts the predicted proportions of the patients in each state over follow-up. CONCLUSIONS: The multistate approach gives important insights into the progress of COVID-19 patients in terms of ventilation duration, length of ICU stay, and mortality. In addition to avoiding frequent pitfalls in survival analysis, the methodology enables active cases to be analyzed by allowing for censoring. The stacked probability plots provide extensive information in a concise manner that can be easily conveyed to decision makers regarding healthcare capacities. Furthermore, clear comparisons can be made among different baseline characteristics.

Adenosine Monophosphate/analogs & derivatives , Alanine/analogs & derivatives , Betacoronavirus/drug effects , Coronavirus Infections/prevention & control , Critical Care/statistics & numerical data , Length of Stay/statistics & numerical data , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Respiration, Artificial/methods , Adenosine Monophosphate/therapeutic use , Alanine/therapeutic use , Algorithms , Antiviral Agents/therapeutic use , Betacoronavirus/physiology , COVID-19 , Cohort Studies , Compassionate Use Trials/methods , Coronavirus Infections/mortality , Coronavirus Infections/virology , Critical Care/methods , Humans , Intensive Care Units/statistics & numerical data , Models, Theoretical , Pneumonia, Viral/mortality , Pneumonia, Viral/virology , SARS-CoV-2 , Survival Analysis , Survival Rate , Time Factors