Impact of Dexamethasone on the Pathogen Profile of Critically Ill COVID-19 Patients.

BACKGROUND: Even though several therapeutic options are available, COVID-19 is still lacking a specific treatment regimen. One potential option is dexamethasone, which has been established since the early beginnings of the pandemic. The aim of this study was to determine its effects on the microbiological findings in critically ill COVID-19 patients. METHODS: A multi-center, retrospective study was conducted, in which all the adult patients who had a laboratory-confirmed (PCR) SARS-CoV-2 infection and were treated on intensive care units in one of twenty hospitals of the German Helios network between February 2020-March 2021 were included. Two cohorts were formed: patients who received dexamethasone and those who did not, followed by two subgroups according to the application of oxygen: invasive vs. non-invasive. RESULTS: The study population consisted of 1.776 patients, 1070 of whom received dexamethasone, and 517 (48.3%) patients with dexamethasone were mechanically ventilated, compared to 350 (49.6%) without dexamethasone. Ventilated patients with dexamethasone were more likely to have any pathogen detection than those without (p < 0.026; OR = 1.41; 95% CI 1.04-1.91). A significantly higher risk for the respiratory detection of Klebsiella spp. (p = 0.016; OR = 1.68 95% CI 1.10-2.57) and for Enterobacterales (p = 0.008; OR = 1.57; 95% CI 1.12-2.19) was found for the dexamethasone cohort. Invasive ventilation was an independent risk factor for in-hospital mortality (p < 0.01; OR = 6.39; 95% CI 4.71-8.66). This risk increased significantly in patients aged 80 years or older by 3.3-fold (p < 0.01; OR = 3.3; 95% CI 2.02-5.37) when receiving dexamethasone. CONCLUSION: Our results show that the decision to treat COVID-19 patients with dexamethasone should be a matter of careful consideration as it involves risks and bacterial shifts.

COVID-19 and Severe Acute Respiratory Infections: Monitoring Trends in 421 German Hospitals During the First Four Pandemic Waves.

Introduction: Reliable surveillance systems to monitor trends of COVID-19 case numbers and the associated healthcare burden play a central role in efficient pandemic management. In Germany, the federal government agency Robert-Koch-Institute uses an ICD-code-based inpatient surveillance system, ICOSARI, to assess temporal trends of severe acute respiratory infection (SARI) and COVID-19 hospitalization numbers. In a similar approach, we present a large-scale analysis covering four pandemic waves derived from the Initiative of Quality Medicine (IQM), a German-wide network of acute care hospitals. Methods: Routine data from 421 hospitals for the years 2019-2021 with a "pre-pandemic" period (01-01-2019 to 03-03-2020) and a "pandemic" period (04-03-2020 to 31-12-2021) was analysed. SARI cases were defined by ICD-codes J09-J22 and COVID-19 by ICD-codes U07.1 and U07.2. The following outcomes were analysed: intensive care treatment, mechanical ventilation, in-hospital mortality. Results: Over 1.1 million cases of SARI and COVID-19 were identified. Patients with COVID-19 and additional codes for SARI were at higher risk for adverse outcomes when compared to non-COVID SARI and COVID-19 without any coding for SARI. During the pandemic period, non-COVID SARI cases were associated with 28%, 23% and 27% higher odds for intensive care treatment, mechanical ventilation and in-hospital mortality, respectively, compared to pre-pandemic SARI. Conclusion: The nationwide IQM network could serve as an excellent data source to enhance COVID-19 and SARI surveillance in view of the ongoing pandemic. Future developments of COVID-19/SARI case numbers and associated outcomes should be closely monitored to identify specific trends, especially considering novel virus variants.

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.).

Effects of the COVID-19 Pandemic on Spinal Fusion Procedures for Spinal Infections in a Nationwide Hospital Network in Germany.

BACKGROUND: The full impact of the COVID-19 pandemic on surgical spine care is difficult to assess due to a lack in nationwide evidence from more recent phases of the pandemic. We aimed to describe changes in in-hospital processes associated with spinal fusion procedures in the treatment of spinal infections (SI) during different phases of the pandemic. METHODS: In this retrospective observational study, we examined the in-hospital prevalence and outcomes of spinal fusion procedures for SI (along with patient characteristics, rates of transfer to intensive care units, and mortality rates) during the first four waves of the pandemic compared with the corresponding prepandemic periods in 2019. We used administrative data from a nationwide network of 76 hospitals managing 7% of all in-hospital cases in Germany. RESULTS: We observed no significant change in the prevalence of SI fusion procedures during the pandemic, neither in total numbers (349 vs. 373) nor for each wave separately. On a patient level, we found no differences in age, sex, and the prevalence of paresis, and no relevant differences in associated comorbidities. The rate of mechanical ventilation did not change during any of the examined pandemic waves: it ranged between 9.5 and 18.6% during the pandemic and 3.1 and 16.0% during the corresponding prepandemic control periods. The rate of transfer to intensive care changed only during wave 4 (from 70.4 to 54.8%; p = 0.046) but not in any other pandemic phases. We observed no changes in in-hospital mortality rates (range: 2.9-9.7% vs. 6.2-11.3%) or in duration of hospital stay (range: 26.2-30.8 days vs. 20.8-29.2 days). CONCLUSIONS: The main finding of our study is that within this nationwide network of spine care centers in Germany, the delivery of surgical treatment of SI by means of spinal fusion procedures was maintained throughout the first four waves of the pandemic. Furthermore, there were no relevant changes in patient demographics, in-hospital processes, and mortality rates.

Mortality in cancer patients with SARS-CoV-2 or seasonal influenza: an observational cohort study from a German-wide hospital network.

PURPOSE: At the beginning of the COVID-19 pandemic, SARS-CoV-2 was often compared to seasonal influenza. We aimed to compare the outcome of hospitalized patients with cancer infected by SARS-CoV-2 or seasonal influenza including intensive care unit admission, mechanical ventilation and in-hospital mortality. METHODS: We analyzed claims data of patients with a lab-confirmed SARS-CoV-2 or seasonal influenza infection admitted to one of 85 hospitals of a German-wide hospital network between January 2016 and August 2021. RESULTS: 29,284 patients with COVID-19 and 7442 patients with seasonal influenza were included. Of these, 360 patients with seasonal influenza and 1625 patients with COVID-19 had any kind of cancer. Cancer patients with COVID-19 were more likely to be admitted to the intensive care unit than cancer patients with seasonal influenza (29.4% vs 24.7%; OR 1.31, 95% CI 1.00-1.73 p < .05). No statistical significance was observed in the mechanical ventilation rate for cancer patients with COVID-19 compared to those with seasonal influenza (17.2% vs 13.6% OR 1.34, 95% CI 0.96-1.86 p = .09). 34.9% of cancer patients with COVID-19 and 17.9% with seasonal influenza died (OR 2.45, 95% CI 1.81-3.32 p < .01). Risk factors among cancer patients with COVID-19 or seasonal influenza for in-hospital mortality included the male gender, age, a higher Elixhauser comorbidity index and metastatic cancer. CONCLUSION: Among cancer patients, SARS-CoV-2 was associated with a higher risk for in-hospital mortality than seasonal influenza. These findings underline the need of protective measurements to prevent an infection with either COVID-19 or seasonal influenza, especially in this high-risk population.

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.

Access to Surgery and Quality of Care for Acute Cholecystitis During the COVID-19 Pandemic in 2020 and 2021 - an Analysis of 12,545 Patients from a German-Wide Hospital Network.

PURPOSE: To determine effects on admission, treatment, and outcome for acute cholecystitis during the course of the COVID-19 pandemic in 2020 and 2021. METHODS: Retrospective analysis of claims data from 74 German hospitals. Study periods were defined from March 5, 2020 (start of first wave) to June 20, 2021 (end of third wave) and compared to corresponding control periods (March 2018 to February 2020). All in-patients with acute cholecystitis were included. Distribution of cases, type of surgery, comorbidities, surgical outcome, and length of stay of all cases with acute cholecystitis and cholecystectomy were compared. In addition, we analyzed the type of treatment (non-surgical, cholecystostomy, or cholecystectomy) for all cases with main diagnosis of acute cholecystitis. RESULTS: We could not demonstrate differences in daily admissions over the course of the pandemic (11.2-12.7 patients vs. 11.9-12.6 patients for control periods). Proportion of patients with non-surgical treatment was low and not increased (11.7-17.3% vs. 14.5-18.4%). Cholecystostomy was rare throughout all periods (0-0.5% of all patients). We did not observe an increase in open surgery (proportion of open cholecystectomies 3.4-5.5%). Mortality was generally low (1.5-1.9%) with no differences between periods. Median length of stay was 4 days throughout all periods. CONCLUSION: The numerous restrictions during the COVID-19 pandemic did not result in an increase of admissions or surgery for acute cholecystitis. Laparoscopic cholecystectomy has been safely applied during the pandemic. Our results may assure the ability to maintain high quality of surgical care even in times of disruptions to the health care system.

Changes in nationwide in-hospital stroke care during the first four waves of COVID-19 in Germany.

Introduction: In the early stages of the global COVID-19 pandemic hospital admissions for acute ischemic stroke (AIS) decreased substantially. As health systems have become more experienced in dealing with the pandemic, and as the proportion of the population vaccinated rises, it is of interest to determine whether the prevalence of AIS hospitalization and outcomes from hospitalization have returned to normal. Patients and methods: In this observational, retrospective cohort study, we compared the prevalence and outcomes of AIS during the first four waves of the pandemic to corresponding pre-pandemic periods in 2019 using administrative data collected from a nationwide network of 76 hospitals that manages 7% of all in-hospital cases in Germany. Results: We included 25,821 AIS cases in the study period (2020/2021) and used 26,295 AIS cases as controls (2019). Compared to pre-pandemic numbers, mean daily AIS admissions decreased only during wave 1 (from 39.6 to 34.1; p < 0.01) and wave 2 (from 39.9 to 38.3; p = 0.03) and returned to normal levels during waves 3 and 4. AIS case fatality increased in wave 1 only (from 6.0% to 7.6%; p = 0.03). We observed a consistent decrease in the prevalences of arterial hypertension, diabetes, and obesity among AIS cases throughout the pandemic and no changes in rates of systemic thrombolysis, mechanical thrombectomy, or decompressive craniectomy. The rate of transfer to stroke units increased only during waves 2 (by 4.6%; p < 0.01) and 3 (by 3.0%; p < 0.01). The proportion of patients with coinciding SARS-CoV-2 and AIS was low, peaking at 3.4% in wave 2 and subsequently decreasing to 0.4% in wave 4. Conclusion: In Germany, the COVID-19 pandemic seems to have had a larger effect on nationwide in-hospital AIS care during the early pandemic stages, in which AIS case numbers decreased and case fatality rose. This may reflect a nationwide "learning curve" within health care systems in providing AIS care in times of a pandemic.

Effect of gender, age and vaccine on reactogenicity and incapacity to work after COVID-19 vaccination: a survey among health care workers.

BACKGROUND: The aim of our study was to assess the impact the impact of gender and age on reactogenicity to three COVID-19 vaccine products: Biontech/Pfizer (BNT162b2), Moderna (mRNA-1273) and AstraZeneca (ChAdOx). Additional analyses focused on the reduction in working capacity after vaccination and the influence of the time of day when vaccines were administered. METHODS: We conducted a survey on COVID-19 vaccinations and eventual reactions among 73,000 employees of 89 hospitals of the Helios Group. On May 19th, 2021 all employees received an email, inviting all employees who received at least 1 dose of a COVID-19 to participate using an attached link. Additionally, the invitation was posted in the group's intranet page. Participation was voluntary and non-traceable. The survey was closed on June 21st, 2021. RESULTS: 8375 participants reported on 16,727 vaccinations. Reactogenicity was reported after 74.6% of COVID-19 vaccinations. After 23.0% vaccinations the capacity to work was affected. ChAdOx induced impairing reactogenicity mainly after the prime vaccination (70.5%), while mRNA-1273 led to more pronounced reactions after the second dose (71.6%). Heterologous prime-booster vaccinations with ChAdOx followed by either mRNA-1273 or BNT162b2 were associated with the highest risk for impairment (81.4%). Multivariable analyses identified the factors older age, male gender and vaccine BNT162b as independently associated with lower odds ratio for both, impairing reactogenicity and incapacity to work. In the comparison of vaccine schedules, the heterologous combination ChAdOx + BNT162b or mRNA-1273 was associated with the highest and the homologue prime-booster vaccination with BNT162b with the lowest odds ratios. The time of vaccination had no significant influence. CONCLUSIONS: Around 75% of the COVID-19 vaccinations led to reactogenicity and nearly 25% of them led to one or more days of work loss. Major risk factors were female gender, younger age and the administration of a vaccine other than BNT162b2. When vaccinating a large part of a workforce against COVID-19, especially in professions with a higher proportion of young and women such as health care, employers and employees must be prepared for a noticeable amount of absenteeism. Assuming vaccine effectiveness to be equivalent across the vaccine combinations, to minimize reactogenicity, employees at risk should receive a homologous prime-booster immunisation with BNT162b2. TRIAL REGISTRATION: The study was approved by the Ethic Committee of the Aerztekammer Berlin on May 27th, 2021 (Eth-37/21) and registered in the German Clinical Trials Register (DRKS 00025745). The study was supported by the Helios research grant HCRI-ID 2021-0272.

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.