Effects of the COVID-19 pandemic on acute coronary syndromes in Germany during the first wave: the COVID-19 collateral damage study.

BACKGROUND: Reports about the influence of the COVID-19 pandemic on the number of hospital admissions and in-hospital mortality during the first wave between March and May 2020 showed conflicting results and are limited by single-center or limited regional multicenter datasets. Aim of this analysis covering all German federal states was the comprehensive description of hospital admissions and in-hospital mortality during the first wave of the COVID-19 pandemic. METHODS AND RESULTS: We conducted an observational study on hospital routine data (§21 KHEntgG) and included patients with the main diagnosis of acute myocardial infarction (ICD 21 and ICD 22). A total of 159 hospitals included 36,329 patients in the database, with 12,497 patients admitted with ST-elevation myocardial infarction (STEMI) and 23,832 admitted with non-ST-elevation myocardial infarction (NSTEMI). There was a significant reduction in the number of patients admitted with STEMI (3748 in 2020, 4263 in 2019 and 4486 in 2018; p < 0.01) and NSTEMI (6957 in 2020, 8437 in 2019 and 8438 in 2020; p < 0.01). These reductions were different between the Federal states of Germany. Percutaneous coronary intervention was performed more often in 2020 than in 2019 (odds ratio 1.13, 95% confidence interval [CI] 1.06-1.21) and 2018 (odds ratio 1.20, 95% CI 1.12-1.29) in NSTEMI and more often than in 2018 (odds ratio 1.26, 95% CI 1.10-1.43) in STEMI. The in-hospital mortality did not differ between the years for STEMI and NSTEMI, respectively. CONCLUSIONS: In this large representative sample size of hospitals in Germany, we observed significantly fewer admissions for NSTEMI and STEMI during the first COVID-19 wave, while quality of in-hospital care and in-hospital mortality were not affected. Admissions for STEMI and NSTEMI during the months March to May over 3 years and corresponding in-hospital mortality for patients with STEMI and NSTEMI in 159 German hospitals. (p-value for admissions 2020 versus 2019 and 2018: < 0.01; p-value for mortality: n.s.).

Changing trends of patient characteristics and treatment pathways during the COVID-19 pandemic: A cross-sectional analysis of 72,459 inpatient cases from the German Helios database.

Background: This study compared patient profiles and clinical courses of SARS-CoV-2 infected inpatients over different pandemic periods. Methods: In a retrospective cross-sectional analysis, we examined administrative data of German Helios hospitals using ICD-10-codes at discharge. Inpatient cases with SARS-CoV-2 infection admitted between 03/04/2020 and 07/19/2022 were included irrespective of the reason for hospitalization. All endpoints were timely assigned to admission date for trend analysis. The first pandemic wave was defined by change points in time-series of incident daily infections and compared with different later pandemic phases according to virus type predominance. Results: We included 72,459 inpatient cases. Patients hospitalized during the first pandemic wave (03/04/2020-05/05/2020; n = 1,803) were older (68.5 ± 17.2 vs. 64.4 ± 22.6 years, p < 0.01) and severe acute respiratory infections were more prevalent (85.2 vs. 53.3%, p < 0.01). No differences were observed with respect to distribution of sex, but comorbidity burden was higher in the first pandemic wave. The risk of receiving intensive care therapy was reduced in all later pandemic phases as was in-hospital mortality when compared to the first pandemic wave. Trend analysis revealed declines of mean age and Elixhauser comorbidity index over time as well as a decline of the utilization of intensive care therapy, mechanical ventilation and in-hospital mortality. Conclusion: Characteristics and outcomes of inpatients with SARS-CoV-2 infection changed throughout the observational period. An ongoing evaluation of trends and care pathways will allow for the assessment of future demands.

Characteristics and outcomes of COVID-19 patients during B.1.1.529 (Omicron) dominance compared to B.1.617.2 (Delta) in 89 German hospitals.

BACKGROUND: The SARS-CoV-2 variant B.1.1.529 (Omicron) was first described in November 2021 and became the dominant variant worldwide. Existing data suggests a reduced disease severity with Omicron infections in comparison to B.1.617.2 (Delta). Differences in characteristics and in-hospital outcomes of COVID-19 patients in Germany during the Omicron period compared to Delta are not thoroughly studied. ICD-10-code-based severe acute respiratory infections (SARI) surveillance represents an integral part of infectious disease control in Germany. METHODS: Administrative data from 89 German Helios hospitals was retrospectively analysed. Laboratory-confirmed SARS-CoV-2 infections were identified by ICD-10-code U07.1 and SARI cases by ICD-10-codes J09-J22. COVID-19 cases were stratified by concomitant SARI. A nine-week observational period between December 6, 2021 and February 6, 2022 was defined and divided into three phases with respect to the dominating virus variant (Delta, Delta to Omicron transition, Omicron). Regression analyses adjusted for age, gender and Elixhauser comorbidities were applied to assess in-hospital patient outcomes. RESULTS: A total cohort of 4,494 inpatients was analysed. Patients in the Omicron dominance period were younger (mean age 47.8 vs. 61.6; p < 0.01), more likely to be female (54.7% vs. 47.5%; p < 0.01) and characterized by a lower comorbidity burden (mean Elixhauser comorbidity index 5.4 vs. 8.2; p < 0.01). Comparing Delta and Omicron periods, patients were at significantly lower risk for intensive care treatment (adjusted odds ratio 0.72 [0.57-0.91]; p = 0.005), mechanical ventilation (adjusted odds ratio 0.42 [0.31-0.57]; p < 0.001), and in-hospital mortality (adjusted odds ratio 0.42 [0.32-0.56]; p < 0.001). This also applied mostly to the separate COVID-SARI group. During the Delta to Omicron transition, case numbers of COVID-19 without SARI exceeded COVID-SARI for the first time in the pandemic's course. CONCLUSION: Patient characteristics and outcomes differ during the Omicron dominance period as compared to Delta suggesting a reduced disease severity with Omicron infections. SARI surveillance might play a crucial role in assessing disease severity of future SARS-CoV-2 variants.

European Society of Cardiology guidance for the diagnosis and management of cardiovascular disease during the COVID-19 pandemic: part 1-epidemiology, pathophysiology, and diagnosis.

AIMS: Since its emergence in early 2020, the novel severe acute respiratory syndrome coronavirus 2 causing coronavirus disease 2019 (COVID-19) has reached pandemic levels, and there have been repeated outbreaks across the globe. The aim of this two-part series is to provide practical knowledge and guidance to aid clinicians in the diagnosis and management of cardiovascular disease (CVD) in association with COVID-19. METHODS AND RESULTS: A narrative literature review of the available evidence has been performed, and the resulting information has been organized into two parts. The first, reported here, focuses on the epidemiology, pathophysiology, and diagnosis of cardiovascular (CV) conditions that may be manifest in patients with COVID-19. The second part, which will follow in a later edition of the journal, addresses the topics of care pathways, treatment, and follow-up of CV conditions in patients with COVID-19. CONCLUSION: This comprehensive review is not a formal guideline but rather a document that provides a summary of current knowledge and guidance to practicing clinicians managing patients with CVD and COVID-19. The recommendations are mainly the result of observations and personal experience from healthcare providers. Therefore, the information provided here may be subject to change with increasing knowledge, evidence from prospective studies, and changes in the pandemic. Likewise, the guidance provided in the document should not interfere with recommendations provided by local and national healthcare authorities.

A Comparative Analysis of In-Hospital Mortality per Disease Groups in Germany Before and During the COVID-19 Pandemic From 2016 to 2020.

Importance: Throughout the ongoing SARS-CoV-2 pandemic, it has been critical to understand not only the viral disease itself but also its implications for the overall health care system. Reports about excess mortality in this regard have mostly focused on overall death counts during specific pandemic phases. Objective: To investigate hospitalization rates and compare in-hospital mortality rates with absolute mortality incidences across a broad spectrum of diseases, comparing 2020 data with those of prepandemic years. Design, Setting, and Participants: Retrospective, cross-sectional, multicentric analysis of administrative data from 5 821 757 inpatients admitted from January 1, 2016, to December 31, 2020, to 87 German Helios primary to tertiary care hospitals. Exposures: Exposure to SARS-CoV-2. Main Outcomes and Measures: Administrative data were analyzed from January 1, 2016, to March 31, 2021, as a consecutive sample for all inpatients. Disease groups were defined according to International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10; German modification) encoded main discharge diagnoses. Incidence rate ratios (IRRs) for hospital admissions and hospital mortality counts, as well as relative mortality risks (RMRs) comparing 2016-2019 with 2020 (exposure to the SARS-CoV-2 pandemic), were calculated with Poisson regression with log-link function. Results: Data were examined for 5 821 757 inpatients (mean [SD] age, 56.4 [25.3] years; 51.5% women), including 125 807 in-hospital deaths. Incidence rate ratios for hospital admissions were associated with a significant reduction for all investigated disease groups (IRR, 0.82; 95% CI, 0.79-0.86; P < .001). After adjusting for age, sex, the Elixhauser Comorbidity Index score, and SARS-CoV-2 infections, RMRs were associated with an increase in infectious diseases (RMR, 1.28; 95% CI, 1.21-1.34; P < .001), musculoskeletal diseases (RMR, 1.19; 95% CI, 1.04-1.36; P = .009), and respiratory diseases (RMR, 1.09; 95% CI, 1.05-1.14; P < .001) but not for the total cohort (RMR, 1.00; 95% CI, 0.99-1.02; P = .66). Regarding in-hospital mortality, IRR was associated with an increase within the ICD-10 chapter of respiratory diseases (IRR, 1.28; 95% CI, 1.13-1.46; P < .001) in comparing 2020 with 2016-2019, in contrast to being associated with a reduction in IRRs for the overall cohort and several other subgroups. After exclusion of patients with SARS-CoV-2 infections, IRRs were associated with a reduction in absolute in-hospital mortality for the overall cohort (IRR, 0.78; 95% CI, 0.72-0.84; P < .001) and the subgroup of respiratory diseases (IRR, 0.83; 95% CI, 0.74-0.92; P < .001). Conclusions and Relevance: This cross-sectional study of inpatients from a multicentric German database suggests that absolute in-hospital mortality for 2020 across disease groups was not higher compared with previous years. Higher IRRs of in-hospital deaths observed in patients with respiratory diseases were likely associated with individuals with SARS-CoV-2 infections.

[Psychiatric Emergency Admissions and Inpatient Length of Stay Before and During the COVID-19 Pandemic in Germany]. / Psychiatrische Notfallaufnahmen und stationäre Aufenthaltsdauer vor und während der COVID-19-Pandemie in Deutschland.

OBJECTIVE: The impact of the COVID-19 year on the number of daily psychiatric emergency admissions and length of stay was compared with previous years. METHODS: In a retrospective study, the four quarters of 2020 of several psychiatric hospitals in Germany were statistically compared with the respective quarters of 2018 and 2019. RESULTS: A total of 73,412 cases was analyzed. In the 2nd quarter of 2020, the number of daily admissions was significantly lower as compared to the control period (59.1 vs. 70.7; incidence rate ratio [95 % confidence interval] 0.81 [0.69; 0.96]; p = 0.012). Length of stay was numerically but not significantly different as compared to the control periods. CONCLUSION: The COVID-19 pandemic had a strong impact on inpatient psychiatric care. In the future, multimodal care structures must ensure the care of severely mentally ill people in crisis situations.

SARS-CoV-2 rapid antigen testing in the healthcare sector: A clinical prediction model for identifying false negative results.

OBJECTIVES: SARS-CoV-2 rapid antigen tests (RAT) provide fast identification of infectious patients when RT-PCR results are not immediately available. We aimed to develop a prediction model for identification of false negative (FN) RAT results. METHODS: In this multicenter trial, patients with documented paired results of RAT and RT-PCR between October 1st 2020 and January 31st 2021 were retrospectively analyzed regarding clinical findings. Variables included demographics, laboratory values and specific symptoms. Three different models were evaluated using Bayesian logistic regression. RESULTS: The initial dataset contained 4,076 patients. Overall sensitivity and specificity of RAT was 62.3% and 97.6%. 2,997 cases with negative RAT results (FN: 120; true negative: 2,877; reference: RT-PCR) underwent further evaluation after removal of cases with missing data. The best-performing model for predicting FN RAT results containing 10 variables yielded an area under the curve of 0.971. Sensitivity, specificity, PPV and NPV for 0.09 as cut-off value (probability for FN RAT) were 0.85, 0.99, 0.7 and 0.99. CONCLUSION: FN RAT results can be accurately identified through ten routinely available variables. Implementation of a prediction model in addition to RAT testing in clinical care can provide decision guidance for initiating appropriate hygiene measures and therefore helps avoiding nosocomial infections.

Expected and observed in-hospital mortality in heart failure patients before and during the COVID-19 pandemic: Introduction of the machine learning-based standardized mortality ratio at Helios hospitals.

BACKGROUND: Reduced hospital admission rates for heart failure (HF) and evidence of increased in-hospital mortality were reported during the COVID-19 pandemic. The aim of this study was to apply a machine learning (ML)-based mortality prediction model to examine whether the latter is attributable to differing case mixes and exceeds expected mortality rates. METHODS AND RESULTS: Inpatient cases with a primary discharge diagnosis of HF non-electively admitted to 86 German Helios hospitals between 01/01/2016 and 08/31/2020 were identified. Patients with proven or suspected SARS-CoV-2 infection were excluded. ML-based models were developed, tuned, and tested using cases of 2016-2018 (n = 64,440; randomly split 75%/25%). Extreme gradient boosting showed the best model performance indicated by a receiver operating characteristic area under the curve of 0.882 (95% confidence interval [CI]: 0.872-0.893). The model was applied on data sets of 2019 and 2020 (n = 28,556 cases) and the hospital standardized mortality ratio (HSMR) was computed as the observed to expected death ratio. Observed mortality rates were 5.84% (2019) and 6.21% (2020), HSMRs based on an individual case-based mortality probability were 100.0 (95% CI: 93.3-107.2; p = 1.000) for 2019 and 99.3 (95% CI: 92.5-106.4; p = .850) for 2020. Within subgroups of age or hospital volume, there were no significant differences between observed and expected deaths. When stratified for pandemic phases, no excess death during the COVID-19 pandemic was observed. CONCLUSION: Applying an ML algorithm to calculate expected inpatient mortality based on administrative data, there was no excess death above expected event rates in HF patients during the COVID-19 pandemic.

Hospitalisations for emergency-sensitive conditions in Germany during the COVID-19 pandemic: insights from the German-wide Helios hospital network.

BACKGROUND: While there are numerous reports that describe emergency care during the early COVID-19 pandemic, there is scarcity of data for later stages. This study analyses hospitalisation rates for 37 emergency-sensitive conditions in the largest German-wide hospital network during different pandemic phases. METHODS: Using claims data of 80 hospitals, consecutive cases between 1 January and 17 November 2020 were analysed and compared with a corresponding period in 2019. Incidence rate ratios (IRRs) comparing the two periods were calculated using Poisson regression to model the number of hospitalisations per day. RESULTS: There was a reduction in hospitalisations between 12 March and 13 June 2020 (coinciding with the first pandemic wave) with 32 807 hospitalisations (349.0/day) as opposed to 39 379 (419.0/day) in 2019 (IRR 0.83, 95% CI 0.82 to 0.85, p<0.01). During the following period (14 June-17 November 2020, including the start of second wave), hospitalisations were reduced from 63 799 (406.4/day) in 2019 to 59 910 (381.6/day) in 2020, but this reduction was not as pronounced (IRR 0.94, 95% CI 0.93 to 0.95, p<0.01). During the first wave hospitalisations for acute myocardial infarction, aortic aneurysm/dissection, pneumonitis, paralytic ileus/intestinal obstruction and pulmonary embolism declined but subsequently increased compared with the corresponding periods in 2019. In contrast, hospitalisations for sepsis, pneumonia, obstructive pulmonary disease and intracranial injuries were reduced during the entire observation period. CONCLUSIONS: There was an overall reduction of absolute hospitalisations for emergency-sensitive conditions in Germany during the first 10 months of the COVID-19 pandemic with heterogeneous effects on different disease categories. The increase in hospitalisations for acute myocardial infarction, aortic aneurysm/dissection and pulmonary embolism requires attention and further studies.

Potential Contributors to Increased Pulmonary Embolism Hospitalizations During the COVID-19 Pandemic: Insights From the German-Wide Helios Hospital Network.

Background: After the first COVID-19 infection wave, a constant increase of pulmonary embolism (PE) hospitalizations not linked with active PCR-confirmed COVID-19 was observed, but potential contributors to this observation are unclear. Therefore, we analyzed associations between changes in PE hospitalizations and (1) the incidence of non-COVID-19 pneumonia, (2) the use of computed tomography pulmonary angiography (CTPA), (3) volume depletion, and (4) preceding COVID-19 infection numbers in Germany. Methods: Claims data of Helios hospitals in Germany were used, and consecutive cases with a hospital admission between May 6 and December 15, 2020 (PE surplus period), were analyzed and compared to corresponding periods covering the same weeks in 2016-2019 (control period). We analyzed the number of PE cases in the target period with multivariable Poisson general linear mixed models (GLMM) including (a) cohorts of 2020 versus 2016-2019, (b) the number of cases with pneumonia, (c) CTPA, and (d) volume depletion and adjusted for age and sex. In order to associate the daily number of PE cases in 2020 with the number of preceding SARS-CoV-2 infections in Germany, we calculated the average number of daily infections (divided by 10,000) occurring between 14 up to 90 days with increasing window sizes before PE cases and modeled the data with Poisson regression. Results: There were 2,404 PE hospitalizations between May 6 and December 15, 2020, as opposed to 2,112-2,236 (total 8,717) in the corresponding 2016-2019 control periods (crude rate ratio [CRR] 1.10, 95% CI 1.05-1.15, P < 0.01). With the use of multivariable Poisson GLMM adjusted for age, sex, and volume depletion, PE cases were significantly associated with the number of cases with pneumonia (CRR 1.09, 95% CI 1.07-1.10, P < 0.01) and with CTPA (CRR 1.10, 95% CI 1.09-1.10, P < 0.01). The increase of PE cases in 2020 compared with the control period remained significant (CRR 1.07, 95% CI 1.02-1.12, P < 0.01) when controlling for those factors. In the 2020 cohort, the number of preceding average daily COVID-19 infections was associated with increased PE case incidence in all investigated windows, i.e., including preceding infections from 14 to 90 days. The best model (log likelihood -576) was with a window size of 4 days, i.e., average COVID-19 infections 14-17 days before PE hospitalization had a risk of 1.20 (95% CI 1.12-1.29, P < 0.01). Conclusions: There is an increase in PE cases since early May 2020 compared to corresponding periods in 2016-2019. This surplus was significant even when controlling for changes in potential modulators such as demographics, volume depletion, non-COVID-19 pneumonia, CTPA use, and preceding COVID-19 infections. Future studies are needed (1) to investigate a potential causal link for increased risk of delayed PE with preceding SARS-CoV-2 infection and (2) to define optimal screening for SARS-CoV-2 in patients presenting with pneumonia and PE.

Impact of COVID-19 pandemic on involuntary and urgent inpatient admissions for psychiatric disorders in a German-wide hospital network.

The impact of COVID-19 on urgent and involuntary inpatient admissions, as well as coercive measures, has not been assessed so far. A retrospective study was performed analyzing claims data for inpatient psychiatric admissions between 2018 and 2020 (total n = 64,502) from a large German Hospital network. Whilst the total number of urgent admissions decreased in 2020 (12,383) as compared to 2019 (13,493) and 2018 (13,469), a significant increase in the percentage of urgent admissions was observed in 2020 (62.9%) as compared to 2019 (60.6%) and 2018 (59.7%). Compared to this study period, Odds ratio (OR) for proportion were 0.87 (0.84, 0.91) and 0.91 (0.87, 0.95) for 2018 and 2019, respectively (both p < 0.00001). Percentage of involuntary psychiatric admissions also significantly increased in 2020 and OR compared to this study period ranged from 0.86 (0.81, 0.93) in 2019 (p < 0.0001) to 0.88 (0.82, 0.95) in 2018 (p < 0.001). Proportion of coercive measures significantly increased in 2020 as compared to 2019 (p = 0.004). Taken together, the present study shows an increase in the proportion of involuntary and urgent psychiatric admissions during the whole pandemic year 2020 as compared to 2018 and 2019. The long-term impact of these COVID-19 pandemic-related trends on psychiatric health care needs to be assessed in further studies.

Emergency hospital admissions for psychiatric disorders in a German-wide hospital network during the COVID-19 outbreak.

PURPOSE: Psychiatric emergency hospital admissions for distinct psychiatric disorders and length of inpatient stay in the hospital during the Coronavirus disease 2019 (COVID-19) outbreak have not been thoroughly assessed. METHODS: A retrospective study was performed analyzing claims data from a large German Hospital network during the COVID-19 outbreak (study period: March 13-May 21, 2020) as compared to periods directly before the outbreak (same year control: January 1-March 12, 2020) and one year earlier (previous year control: March 13-May 21, 2019). RESULTS: A total of 13,151 emergency hospital admissions for psychiatric diagnoses were included in the analysis. For all psychiatric diagnoses combined, emergency admissions significantly decreased during the study period with mean (interquartile range) incidence rate ratios (IRRs) of 0.68 (0.65, 0.71) and 0.70 (0.67, 0.73) as compared to the same and previous year controls, respectively (both p < 0.00001). IRR ranged from 0.56 for mood affective disorders (F30-F39) to 0.75 for mental disorders due to psychoactive substance use (F10-F19; all p < 0.00001). Mean (standard deviation) length of hospital stay for all psychiatric diagnoses was significantly shorter during the study period [9.8 (11.6) days] as compared to same [14.7 (18.7) days] and previous [16.4 (23.9) days] year controls (both p < 0.00001). CONCLUSION: Both emergency hospital admissions and length of hospital stay significantly decreased for psychiatric disorders during the COVID-19 outbreak. It needs to be assessed in further studies whether healthcare systems will face increased demand for the provision of mental health care in the nearer future.

Utilization of in- and outpatient hospital care in Germany during the Covid-19 pandemic insights from the German-wide Helios hospital network.

BACKGROUND: During the early phase of the Covid-19 pandemic, reductions of hospital admissions with a focus on emergencies have been observed for several medical and surgical conditions, while trend data during later stages of the pandemic are scarce. Consequently, this study aims to provide up-to-date hospitalization trends for several conditions including cardiovascular, psychiatry, oncology and surgery cases in both the in- and outpatient setting. METHODS AND FINDINGS: Using claims data of 86 Helios hospitals in Germany, consecutive cases with an in- or outpatient hospital admission between March 13, 2020 (the begin of the "protection" stage of the German pandemic plan) and December 10, 2020 (end of study period) were analyzed and compared to a corresponding period covering the same weeks in 2019. Cause-specific hospitalizations were defined based on the primary discharge diagnosis according to International Statistical Classification of Diseases and Related Health Problems (ICD-10) or German procedure classification codes for cardiovascular, oncology, psychiatry and surgery cases. Cumulative hospitalization deficit was computed as the difference between the expected and observed cumulative admission number for every week in the study period, expressed as a percentage of the cumulative expected number. The expected admission number was defined as the weekly average during the control period. A total of 1,493,915 hospital admissions (723,364 during the study and 770,551 during the control period) were included. At the end of the study period, total cumulative hospitalization deficit was -10% [95% confidence interval -10; -10] for cardiovascular and -9% [-10; -9] for surgical cases, higher than -4% [-4; -3] in psychiatry and 4% [4; 4] in oncology cases. The utilization of inpatient care and subsequent hospitalization deficit was similar in trend with some variation in magnitude between cardiovascular (-12% [-13; -12]), psychiatry (-18% [-19; -17]), oncology (-7% [-8; -7]) and surgery cases (-11% [-11; -11]). Similarly, cardiovascular and surgical outpatient cases had a deficit of -5% [-6; -5] and -3% [-4; -3], respectively. This was in contrast to psychiatry (2% [1; 2]) and oncology cases (21% [20; 21]) that had a surplus in the outpatient sector. While in-hospital mortality, was higher during the Covid-19 pandemic in cardiovascular (3.9 vs. 3.5%, OR 1.10 [95% CI 1.06-1.15], P<0.01) and in oncology cases (4.5 vs. 4.3%, OR 1.06 [95% CI 1.01-1.11], P<0.01), it was similar in surgical (0.9 vs. 0.8%, OR 1.06 [95% CI 1.00-1.13], P = 0.07) and in psychiatry cases (0.4 vs. 0.5%, OR 1.01 [95% CI 0.78-1.31], P<0.95). CONCLUSIONS: There have been varying changes in care pathways and in-hospital mortality in different disciplines during the Covid-19 pandemic in Germany. Despite all the inherent and well-known limitations of claims data use, this data may be used for health care surveillance as the pandemic continues worldwide. While this study provides an up-to-date analysis of utilization of hospital care in the largest German hospital network, short- and long-term consequences are unknown and deserve further studies.

Admission rates and care pathways in patients with atrial fibrillation during the COVID-19 pandemic-insights from the German-wide Helios hospital network.

AIMS: Several reports indicate lower rates of emergency admissions in the cardiovascular sector and reduced admissions of patients with chronic diseases during the Coronavirus SARS-CoV-2 (COVID-19) pandemic. The aim of this study was therefore to evaluate numbers of admissions in incident and prevalent atrial fibrillation and flutter (AF) and to analyse care pathways in comparison to 2019. METHODS: A retrospective analysis of claims data of 74 German Helios hospitals was performed to identify consecutive patients hospitalized with a main discharge diagnosis of AF. A study period including the start of the German national protection phase (13 March 2020 to 16 July 2020) was compared to a previous year control cohort (15 March 2019 to 18 July 2019), with further sub-division into early and late phase. Incidence rate ratios (IRRs) were calculated. Numbers of admission per day (A/day) for incident and prevalent AF and care pathways including readmissions, numbers of transesophageal echocardiogram (TEE), electrical cardioversion (CV), and catheter ablation (CA) were analysed. RESULTS: During the COVID-19 pandemic, there was a significant decrease in total AF admissions both in the early (44.4 vs. 77.5 A/day, IRR 0.57 [95% confidence interval (CI) 0.54-0.61], P < 0.01) and late (59.1 vs. 63.5 A/day, IRR 0.93 [95% CI 0.90-0.96], P < 0.01) phases, length of stay was significantly shorter (3.3 ± 3.1 nights vs. 3.5 ± 3.6 nights, P < 0.01), admissions were more frequently in high-volume centres (77.0% vs. 75.4%, P = 0.02), and frequency of readmissions was reduced (21.7% vs. 23.6%, P < 0.01) compared to the previous year. Incident AF admission rates were significantly lower both in the early (21.9 admission per day vs. 41.1 A/day, IRR 0.53 [95% CI 0.48-0.58]) and late (35.5 vs. 39.3 A/day, IRR 0.90 [95% CI 0.86-0.95]) phases, whereas prevalent admissions were only lower in the early phase (22.5 vs. 36.4 A/day IRR 0.62 [95% CI 0.56-0.68]), but not in the late phase (23.6 vs. 24.2 A/day IRR 0.97 [95% CI 0.92-1.03]). Analysis of care pathways showed reduced numbers of TEE during the early phase [34.7% vs. 41.4%, odds ratio (OR) 0.74 [95% CI 0.64-0.86], P < 0.01], but not during the late phase (39.9% vs. 40.2%, OR 0.96 [95% CI 0.88-1.03], P = 0.26). Numbers of CV were comparable during early (40.6% vs. 39.7%, OR 1.08 [95% CI 0.94-1.25], P = 0.27) and late (38.6% vs. 37.5%, OR 1.06 [95% CI 0.98-1.14], P = 0.17) phases, compared to the previous year, respectively. Numbers of CA were comparable during the early phase (21.6% vs. 21.1%, OR 0.98 [95% CI 0.82-1.17], P = 0.82) with a distinct increase during the late phase (22.9% vs. 21.5%, OR 1.05 [95% CI 0.96-1.16], P = 0.28). CONCLUSION: During the COVID-19 pandemic, AF admission rates declined significantly, with a more pronounced reduction in incident than in prevalent AF. Overall AF care was maintained during early and late pandemic phases with only minor changes, namely less frequent use of TEE. Confirmation of these findings in other study populations and identification of underlying causes are required to ensure optimal therapy in patients with AF during the COVID-19 pandemic.