Retrospective, Observational Analysis on the Impact of SARS-CoV-2 Variant Omicron in Hospitalized Immunocompromised Patients in a German Hospital Network-The VISAGE Study.

AIMS: Endemic SARS-CoV-2 infections still burden the healthcare system and represent a considerable threat to vulnerable patient cohorts, in particular immunocompromised (IC) patients. This study aimed to analyze the in-hospital outcome of IC patients with severe SARS-CoV-2 infection in Germany. METHODS: This retrospective, observational study, analyzed administrative data from inpatient cases (n = 146,324) in 84 German Helios hospitals between 1 January 2022 and 31 December 2022 with regard to in-hospital outcome and health care burden in IC patients during the first 12 months of Omicron dominance. As the primary objective, in-hospital outcomes of patients with COVID-19-related severe acute respiratory infection (SARI) were analyzed by comparing patients with (n = 2037) and without IC diagnoses (n = 14,772). Secondary analyses were conducted on IC patients with (n = 2037) and without COVID-19-related SARI (n = 129,515). A severe in-hospital outcome as a composite endpoint was defined per the WHO definition if one of the following criteria were met: intensive care unit (ICU) treatment, mechanical ventilation (MV), or in-hospital death. RESULTS: In total, 12% of COVID-related SARI cases were IC patients, accounting for 15% of ICU admissions, 15% of MV use, and 16% of deaths, resulting in a higher prevalence of severe in-hospital courses in IC patients developing COVID-19-related SARI compared to non-IC patients (Odds Ratio, OR = 1.4, p < 0.001), based on higher in-hospital mortality (OR = 1.4, p < 0.001), increased need for ICU treatment (OR = 1.3, p < 0.001) and mechanical ventilation (OR = 1.2, p < 0.001). Among IC patients, COVID-19-related SARI profoundly increased the risk for severe courses (OR = 4.0, p < 0.001). CONCLUSIONS: Our findings highlight the vulnerability of IC patients to severe COVID-19. The persistently high prevalence of severe outcomes in these patients in the Omicron era emphasizes the necessity for continuous in-hospital risk assessment and monitoring of IC patients.

A Comparison of Different Intensive Care Unit Definitions Derived from the German Administrative Data Set: A Methodological, Real-World Data Analysis from 86 Helios Hospitals.

Background: The intensive care unit (ICU) is a scarce resource in all health care systems, necessitating a well-defined utilization. Therefore, benchmarks are essential; and yet, they are limited due to heterogenous definitions of what an ICU is. This study analyzed the case distribution, patient characteristics, and hospital course and outcomes of 6,204,093 patients in the German Helios Hospital Group according to 10 derived ICU definitions. We aimed to set a baseline for the development of a nationwide, uniform ICU definition. Methods: We analyzed ten different ICU definitions: seven derived from the German administrative data set of claims data according to the German Hospital Remuneration Act, three definitions were taken from the Helios Hospital Group's own bed classification. For each ICU definition, the size of the respective ICU population was analyzed. Due to similar patient characteristics for all ten definitions, we selected three indicator definitions to additionally test statistically against IQM. Results: We analyzed a total of 5,980,702 completed hospital cases, out of which 913,402 referred to an ICU criterion (14.7% of all cases). A key finding is the significant variability in ICU population size, depending on definitions. The most restrictive definition of only mechanical ventilation (DOV definition) resulted in 111,966 (1.9%) cases; mechanical ventilation plus typical intensive care procedure codes (IQM definition) resulted in 210,147 (3.5%) cases; defining each single bed individually as ICU or IMC (ICUá´§IMC definition) resulted in 411,681 (6.9%) cases; and defining any coded length of stay at ICU (LOSi definition) resulted in 721,293 (12.1%) cases. Further testing results for indicator definitions are reported. Conclusions: The size of the population, utilization rates, outcomes, and capacity assumptions clearly depend on the definition of ICU. Therefore, the underlying ICU definition should be stated when making any comparisons. From previous studies, we anticipated that 25-30% of all ICU patients should be mechanically ventilated, and therefore, we conclude that the ICUá´§IMC definition is the most plausible approximation. We suggest a mandatory application of a clearly defined ICU term for all hospitals nationwide for improved benchmarking and data analysis.

Artificial intelligence-based identification of left ventricular systolic dysfunction from 12-lead electrocardiograms: external validation and advanced application of an existing model.

Aims: The diagnostic application of artificial intelligence (AI)-based models to detect cardiovascular diseases from electrocardiograms (ECGs) evolves, and promising results were reported. However, external validation is not available for all published algorithms. The aim of this study was to validate an existing algorithm for the detection of left ventricular systolic dysfunction (LVSD) from 12-lead ECGs. Methods and results: Patients with digitalized data pairs of 12-lead ECGs and echocardiography (at intervals of ≤7 days) were retrospectively selected from the Heart Center Leipzig ECG and electronic medical records databases. A previously developed AI-based model was applied to ECGs and calculated probabilities for LVSD. The area under the receiver operating characteristic curve (AUROC) was computed overall and in cohorts stratified for baseline and ECG characteristics. Repeated echocardiography studies recorded ≥3 months after index diagnostics were used for follow-up (FU) analysis. At baseline, 42 291 ECG-echocardiography pairs were analysed, and AUROC for LVSD detection was 0.88. Sensitivity and specificity were 82% and 77% for the optimal LVSD probability cut-off based on Youden's J. AUROCs were lower in ECG subgroups with tachycardia, atrial fibrillation, and wide QRS complexes. In patients without LVSD at baseline and available FU, model-generated high probability for LVSD was associated with a four-fold increased risk of developing LVSD during FU. Conclusion: We provide the external validation of an existing AI-based ECG-analysing model for the detection of LVSD with robust performance metrics. The association of false positive LVSD screenings at baseline with a deterioration of ventricular function during FU deserves a further evaluation in prospective trials.

Changes in frailty among patients hospitalized for spine pathologies during the COVID-19 pandemic in Germany-a nationwide observational study.

PURPOSE: In spine care, frailty is associated with poor outcomes. The aim of this study was to describe changes in frailty in spine care during the coronavirus disease 2019 (COVID-19) pandemic and their relation to surgical management and outcomes. METHODS: Patients hospitalized for spine pathologies between January 1, 2019, and May 17, 2022, within a nationwide network of 76 hospitals in Germany were retrospectively included. Patient frailty, types of surgery, and in-hospital mortality rates were compared between pandemic and pre-pandemic periods. RESULTS: Of the 223,418 included patients with spine pathologies, 151,766 were admitted during the pandemic and 71,652 during corresponding pre-pandemic periods in 2019. During the pandemic, the proportion of high-frailty patients increased from a range of 5.1-6.1% to 6.5-8.8% (p < 0.01), while the proportion of low frailty patients decreased from a range of 70.5-71.4% to 65.5-70.1% (p < 0.01). In most phases of the pandemic, the Elixhauser comorbidity index (ECI) showed larger increases among high compared to low frailty patients (by 0.2-1.8 vs. 0.2-0.8 [p < 0.01]). Changes in rates of spine surgery were associated with frailty, most clearly in rates of spine fusion, showing consistent increases among low frailty patients (by 2.2-2.5%) versus decreases (by 0.3-0.8%) among high-frailty patients (p < 0.02). Changes in rates of in-hospital mortality were not associated with frailty. CONCLUSIONS: During the COVID-19 pandemic, the proportion of high-frailty patients increased among those hospitalized for spine pathologies in Germany. Low frailty was associated with a rise in rates of spine surgery and high frailty with comparably larger increases in rates of comorbidities.

Trends in frailty in brain tumor care during the COVID-19 pandemic in a nationwide hospital network in Germany.

PURPOSE: Among brain tumor patients, frailty is associated with poor outcomes. The COVID-19 pandemic has led to increased frailty in the general population. To date, evidence on changes in frailty among brain tumor patients during the pandemic is lacking. We aimed to compare frailty among brain tumor patients in Germany during the COVID-19 pandemic to the pre-pandemic era and to assess potential effects on brain tumor care. METHODS: In this retrospective observational study, we compared frailty among brain tumor patients hospitalized during the COVID-19 pandemic in years 2020 through 2022 to pre-pandemic years 2016 through 2019 based on administrative data from a nationwide network of 78 hospitals in Germany. Using the Hospital Frailty Risk Score (HFRS), frailty was categorized as low, intermediate, or high. We examined changes in frailty, patient demographics, the burden of comorbidity, rates of surgery, and mortality rates for different frailty groups during the pandemic and compared them to pre-pandemic levels. RESULTS: Of the 20,005 included hospitalizations for brain tumors, 7979 were during the pandemic (mean age 60.0 years (± 18.4); females: 49.8%), and 12,026 in the pre-pandemic period (mean age: 59.0 years [± 18.4]; females: 49.2%). Average daily admissions decreased from 8.2 (± 5.1) during pre-pandemic years to 7.3 (± 4.5) during the pandemic (p < 0.01). The overall median HFRS decreased from 3.1 (IQR: 0.9-7.3) during the pre-pandemic years to 2.6 (IQR: 0.3-6.8) during the pandemic (p < 0.01). At the same time, the Elixhauser Comorbidity Index (ECI) decreased from 17.0 (± 12.4) to 16.1 (± 12.0; p < 0.01), but to a larger degree among high compared to low frailty cases (by 1.8 vs. 0.3 points; p = 0.04). In the entire cohort, the mean length of stay was significantly shorter in the pandemic period (9.5 days [± 10.7]) compared with pre-pandemic levels (10.2 days [± 11.8]; p < 0.01) with similar differences in the three frailty groups. Rates of brain tumor resection increased from 29.9% in pre-pandemic years to 36.6% during the pandemic (p < 0.001) without differences between frailty levels. Rates of in-hospital mortality did not change during the pandemic (6.1% vs. 6.7%, p = 0.07), and there was no interaction with frailty. CONCLUSION: Even though our findings are limited in that the HFRS is validated only for patients ≥ 75 years of age, our study among patients of all ages hospitalized for brain tumors in Germany suggests a marked decrease in levels of frailty and in the burden of comorbidities during the COVID-19 pandemic.

Neurosurgical care for patients with high-grade gliomas during the coronavirus disease 2019 pandemic: Analysis of routine billing data of a German nationwide hospital network.

Background: Little is known about delivery of neurosurgical care, complication rate and outcome of patients with high-grade glioma (HGG) during the coronavirus disease 2019 (Covid-19) pandemic. Methods: This observational, retrospective cohort study analyzed routine administrative data of all patients admitted for neurosurgical treatment of an HGG within the Helios Hospital network in Germany. Data of the Covid-19 pandemic (March 1, 2020-May 31, 2022) were compared to the pre-pandemic period (January 1, 2016-February 29, 2020). Frequency of treatment and outcome (in-hospital mortality, length of hospital stay [LOHS], time in intensive care unit [TICU] and ventilation outside the operating room [OR]) were separately analyzed for patients with microsurgical resection (MR) or stereotactic biopsy (STBx). Results: A total of 1763 patients underwent MR of an HGG (648 patients during the Covid-19 pandemic; 1115 patients in the pre-pandemic period). 513 patients underwent STBx (182 [pandemic]; 331 patients [pre-pandemic]). No significant differences were found for treatment frequency (MR: 2.95 patients/week [Covid-19 pandemic] vs. 3.04 patients/week [pre-pandemic], IRR 0.98, 95% CI: 0.89-1.07; STBx (1.82 [Covid-19 pandemic] vs. 1.86 [pre-pandemic], IRR 0.96, 95% CI: 0.80-1.16, P > .05). Rates of in-hospital mortality, infection, postoperative hemorrhage, cerebral ischemia and ventilation outside the OR were similar in both periods. Overall LOHS was significantly shorter for patients with MR and STBx during the Covid-19 pandemic. Conclusions: The Covid-19 pandemic did not affect the frequency of neurosurgical treatment of patients with an HGG based on data of a large nationwide hospital network in Germany. LOHS was significantly shorter but quality of neurosurgical care and outcome was not altered during the Covid-19 pandemic.

Decompressive Surgery in the Treatment of Acute Ischemic Stroke during the First Four Waves of the COVID-19 Pandemic in Germany: A Nationwide Observational Cohort Study.

BACKGROUND: The COVID-19 pandemic has significantly affected acute ischemic stroke (AIS) care. In this study, we examined the effects of the pandemic on neurosurgical AIS care by means of decompressive surgery (DS). METHODS: In this retrospective observational study, we compared the characteristics, in-hospital processes, and in-hospital mortality rates among patients hospitalized for AIS during the first four waves of the pandemic (between January 1, 2020 and October 26, 2021) versus the corresponding periods in 2019 (prepandemic). We used administrative data from a nationwide hospital network in Germany. RESULTS: Of the 177 included AIS cases with DS, 60 were from 2019 and 117 from the first four pandemic waves. Compared with the prepandemic levels, there were no changes in weekly admissions for DS during the pandemic. The same was true for patient age (range: 51.7-60.4 years), the number of female patients (range: 33.3-57.1%), and the prevalence of comorbidity, as measured by the Elixhauser Comorbidity Index (range: 13.2-20.0 points). Also, no alterations were observed in transfer to the intensive care unit (range: 87.0-100%), duration of in-hospital stay (range: 14.6-22.7 days), and in-hospital mortality rates (range: 11.8-55.6%). CONCLUSION: In Germany, compared with the prepandemic levels, AIS patients undergoing DS during the first four waves of the pandemic showed no changes in demographics, rates of comorbidity, and in-hospital mortality rates. This is in contrast to previous evidence on patients with less critical types of AIS not requiring DS and underlines the uniqueness of the subgroup of AIS patients requiring DS. Our findings suggests that these patients, in contrast to AIS patients in general, were unable to forgo hospitalization during the COVID-19 pandemic. Maintaining the delivery of DS is an essential aspect of AIS care during a pandemic.

The Postoperative Utilization of Intensive Care Beds After Visceral Surgery Procedures.

BACKGROUND: The necessary number of intensive care beds has been under debate in recent years. This study aims to provide a descriptive analysis of postoperative intensive care for visceral surgery patients based on three indicator procedures, with particular attention to the frequency and duration of intensive care among these patients, trends in the occupancy of intensive care units, and the course during the COVID-19 pandemic. METHODS: Routine data from inpatient cases of the Helios group (24 888 cases from 71 acute care hospitals) from 01.01.2016 to 31.12.2021 were analyzed retrospectively. The indicator procedures were colorectal resection, surgery for gastric carcinoma, and left pancreatic resection. RESULTS: Routine data reveal a decline in the utilization of intensive care by these patients over the years, e.g., after colorectal resection, from 84.2% in 2016 to 63.1% in 2021. The percentage of patients requiring mechanical ventilation declined to a small extent as well (2016: 10.3%; 2021: 8.9%). In-hospital mortality remained stable in the range of 4.1% to 5.2%. The number of gastric carcinomas operated on fell from 355 in 2016 to 239 in 2021, while the number of left pancreatic resections remained stable in the range of 147 to 172 per year. CONCLUSION: In the hospitals studied, visceral surgery patients still commonly undergo intensive care postoperatively, at a rate that is declining slowly over the years. No adjustments were made for age, sex, or Elixhauser comorbidity index.

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.

A Digital Infrastructure for Cardiovascular Patient Care Based on Mobile Health Data and Patient-Reported Outcomes: Concept Details of the Helios TeleWear Project Including Preliminary Experiences.

BACKGROUND: Mobile health (mHealth) approaches are already having a fundamental impact on clinical practice in cardiovascular medicine. A variety of different health apps and wearable devices for capturing health data such as electrocardiograms (ECGs) exist. However, most mHealth technologies focus on distinct variables without integrating patients' quality of life, and the impact on clinical outcome measures of implementing those digital solutions into cardiovascular health care is still to be determined. OBJECTIVE: Within this document, we describe the TeleWear project, which was recently initiated as an approach for contemporary patient management integrating mobile-collected health data and the standardized mHealth-guided measurement of patient-reported outcomes (PROs) in patients with cardiovascular disease. METHODS: The specifically designed mobile app and clinical frontend form the central elements of our TeleWear infrastructure. Because of its flexible framework, the platform allows far-reaching customization with the possibility to add different mHealth data sources and respective questionnaires (patient-reported outcome measures). RESULTS: With initial focus on patients with cardiac arrhythmias, a feasibility study is currently carried out to assess wearable-recorded ECG and PRO transmission and its evaluation by physicians using the TeleWear app and clinical frontend. First experiences made during the feasibility study yielded positive results and confirmed the platform's functionality and usability. CONCLUSIONS: TeleWear represents a unique mHealth approach comprising PRO and mHealth data capturing. With the currently running TeleWear feasibility study, we aim to test and further develop the platform in a real-world setting. A randomized controlled trial including patients with atrial fibrillation that investigates PRO- and ECG-based clinical management based on the established TeleWear infrastructure will evaluate its clinical benefits. Widening the spectrum of health data collection and interpretation beyond the ECG and use of the TeleWear infrastructure in different patient subcohorts with focus on cardiovascular diseases are further milestones of the project with the ultimate goal to establish a comprehensive telemedical center entrenched by mHealth.

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.

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.

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.

[Dissemination of fast-track concepts in Germany]. / Verbreitung von Fast-Track-Konzepten in Deutschland.

BACKGROUND: Fast-track concepts have fundamentally changed the perioperative care of patients in the last 30 years. Sufficient evidence is available for these concepts. OBJECTIVE: The aim of this article is to evaluate the dissemination of fast-track concepts in Germany based on routine data. MATERIAL AND METHODS: A retrospective analysis of all colorectal resections performed at the Helios Clinics in 2016-2021 was carried out. These were analyzed with respect to the length of hospital stay, intensive care unit occupancy, ventilation proportion, mortality, complication rate and access approach. RESULTS AND DISCUSSION: A transfer to the intensive medical care unit is still the standard in Germany after colorectal resection. For oncological colorectal resection, in particular, two thirds of the patients are still perioperatively treated on the intensive care unit. The duration of inpatient hospital stay for colorectal resection is still excessively long in international comparisons and has also only diminished slowly in recent years (e.g. colon cancer 2016: 18.6 ± 11.9 days and 2021: 13.8 ± 9.3 days). The proportion of open surgical interventions is declining but still accounts for a relevant proportion even 30 years after the implementation of laparoscopy (e.g. colon cancer 2016: 71.10% and 2021: 56.44%). Therefore, the care of patients with colorectal resection still does not seem to be implemented according to the fast-track principle.

Machine learning-derived prediction of in-hospital mortality in patients with severe acute respiratory infection: analysis of claims data from the German-wide Helios hospital network.

BACKGROUND: Severe acute respiratory infections (SARI) are the most common infectious causes of death. Previous work regarding mortality prediction models for SARI using machine learning (ML) algorithms that can be useful for both individual risk stratification and quality of care assessment is scarce. We aimed to develop reliable models for mortality prediction in SARI patients utilizing ML algorithms and compare its performances with a classic regression analysis approach. METHODS: Administrative data (dataset randomly split 75%/25% for model training/testing) from years 2016-2019 of 86 German Helios hospitals was retrospectively analyzed. Inpatient SARI cases were defined by ICD-codes J09-J22. Three ML algorithms were evaluated and its performance compared to generalized linear models (GLM) by computing receiver operating characteristic area under the curve (AUC) and area under the precision-recall curve (AUPRC). RESULTS: The dataset contained 241,988 inpatient SARI cases (75 years or older: 49%; male 56.2%). In-hospital mortality was 11.6%. AUC and AUPRC in the testing dataset were 0.83 and 0.372 for GLM, 0.831 and 0.384 for random forest (RF), 0.834 and 0.382 for single layer neural network (NNET) and 0.834 and 0.389 for extreme gradient boosting (XGBoost). Statistical comparison of ROC AUCs revealed a better performance of NNET and XGBoost as compared to GLM. CONCLUSION: ML algorithms for predicting in-hospital mortality were trained and tested on a large real-world administrative dataset of SARI patients and showed good discriminatory performances. Broad application of our models in clinical routine practice can contribute to patients' risk assessment and quality management.

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.