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.

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.

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.

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.

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.

Exploring relationships between in-hospital mortality and hospital case volume using random forest: results of a cohort study based on a nationwide sample of German hospitals, 2016-2018.

BACKGROUND: Relationships between in-hospital mortality and case volume were investigated for various patient groups in many empirical studies with mixed results. Typically, those studies relied on (semi-)parametric statistical models like logistic regression. Those models impose strong assumptions on the functional form of the relationship between outcome and case volume. The aim of this study was to determine associations between in-hospital mortality and hospital case volume using random forest as a flexible, nonparametric machine learning method. METHODS: We analyzed a sample of 753,895 hospital cases with stroke, myocardial infarction, ventilation > 24 h, COPD, pneumonia, and colorectal cancer undergoing colorectal resection treated in 233 German hospitals over the period 2016-2018. We derived partial dependence functions from random forest estimates capturing the relationship between the patient-specific probability of in-hospital death and hospital case volume for each of the six considered patient groups. RESULTS: Across all patient groups, the smallest hospital volumes were consistently related to the highest predicted probabilities of in-hospital death. We found strong relationships between in-hospital mortality and hospital case volume for hospitals treating a (very) small number of cases. Slightly higher case volumes were associated with substantially lower mortality. The estimated relationships between in-hospital mortality and case volume were nonlinear and nonmonotonic. CONCLUSION: Our analysis revealed strong relationships between in-hospital mortality and hospital case volume in hospitals treating a small number of cases. The nonlinearity and nonmonotonicity of the estimated relationships indicate that studies applying conventional statistical approaches like logistic regression should consider these relationships adequately.

Patient-Level and Hospital-Level Risk Factors for In-Hospital Mortality in Patients Ventilated for More Than 24 Hours: Results of a Nationwide Cohort Study.

BACKGROUND: Prolonged ventilation is associated with a high risk of death. This study investigated both patient-level and hospital-level risk factors for in-hospital mortality in patients ventilated for more than 24 hours. METHODS: The analyses were conducted in the framework of a German national multicenter retrospective cohort study. Patient and hospital characteristics were examined using descriptive statistics. Risk factors of in-hospital mortality were analyzed using multilevel robust Poisson regressions for binary outcomes. Potential effect modifications were examined by stratified analyses. RESULTS: The sample includes 95 672 cases of patients ventilated >24 hours in 163 hospitals covering the period 2016 to 2017. According to the results of multilevel Poisson regressions, main patient-level risk factors for in-hospital mortality were age (per year relative risk [RR] = 1.021, 95% CI = 1.020-1.023), stroke (RR = 1.459; 95% CI = 1.361-1.563), emergency case admission (RR = 1.273, 95% CI = 1.156-1.403), and transfer from another hospital (RR = 1.169, 95% CI = 1.084-1.261). The individual risk of in-hospital death was positively associated with hospital size (RR of hospitals with 600-799 beds vs <100 beds = 1.412, 95% CI = 1.095-1.820) and negatively related to cumulated ventilation patient time (per 1000 days RR = 0.995, 95% CI = 0.993-0.996). University hospital status was identified as an effect modifier, particularly with regard to the patients' admission reasons. The RR of in-hospital death in patients admitted after transfer from another hospital was higher in university hospitals (RR = 1.456, 95% CI = 1.298-1.634) compared to nonuniversity hospitals (RR = 1.077, 95% CI = 1.019-1.139). Likewise, patients admitted as emergency case had a higher relative risk in university hospitals (RR = 1.619, 95% CI = 1.359-1.929) than in nonuniversity hospitals (RR = 1.141, 95% CI = 1.080-1.205). CONCLUSION: By providing evidence on multiple patient-level and hospital-level risk factors for in-hospital mortality in patients ventilated for more than 24 hours, this large multicenter study has main implications for quality assessment of clinical care and the adequate specification of risk adjustment models. The revealed effect modifications indicate the relevance of stratified analyses.

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.

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.

[Has the COVID19 Pandemic Changed the Emergency Situation in German Clinics? A Nationwide Analysis of Routine Data from 73 Acute Hospitals]. / Hat die COVID-19-Pandemie das Notfallgeschehen in deutschen Kliniken verändert? Eine bundesweite Analyse von Routinedaten aus 73 Akutkrankenhäusern.

COVID-19 has led to profound changes in the world as we have known it. Due to the sharp increase in intensive care, COVID patients, elective admissions and interventions have been postponed. But emergencies such as myocardial infarction have also decreased. The present study deals with the effects of the COVID pandemic on visceral surgical emergencies on the basis of 5 indicator operations. Routine data from 73 acute hospitals of the Helios Group were evaluated for this purpose. The interventions that were carried out between March 13, 2020 and March 12, 2021 were included. The data was compared with the period from March 13, 2019 to March 12, 2020. The number of interventions in serious emergencies (ileus, mesenteric ischemia and ulcer perforation) has remained constant. However, the length of stay in hospital in the pandemic year 2020 was significantly shorter than in the reference year 2019. The number of cholecystectomies and appendectomies in the pandemic year was significantly lower than in the reference year 2019. The outcome parameters intensive care, invasive ventilation and hospital mortality were comparable for the two periods for these interventions.

Catheter ablation of ventricular arrhythmias and in-hospital mortality: insights from the German-wide Helios hospital network of 5052 cases.

AIMS: Catheter ablation (CA) of ventricular arrhythmias is one of the most challenging electrophysiological interventions with an increasing use over the last years. Several benefits must be weighed against the risk of potentially life-threatening complications which necessitates a steady reevaluation of safety endpoints. Therefore, the aims of this study were (i) to investigate overall in-hospital mortality in patients undergoing such procedures and (ii) to identify variables associated with in-hospital mortality in a German-wide hospital network. METHODS AND RESULTS: Between January 2010 and September 2018, administrative data provided by 85 Helios hospitals were screened for patients with main or secondary discharge diagnosis of ventricular tachycardia (VT) or premature ventricular contractions (PVCs) in combination with an arrhythmia-related CA using ICD- and OPS codes. In 5052 cases (mean age 60.9 ± 14.3 years, 30.1% female) of 30 different hospitals, in-hospital mortality was 1.27% with a higher mortality in patients ablated for VT (1.99%, n = 2, 955) compared to PVC (0.24%, n = 2, 097, P < 0.01). Mortality rates were 2.06% in patients with ischaemic heart disease (IHD, n = 2, 137), 1.47% in patients with non-ischaemic structural heart disease (NIHD, n = 1, 224), and 0.12% in patients without structural heart disease (NSHD, n = 1, 691). Considering different types of hospital admission, mortality rates were 0.35% after elective (n = 2, 825), 1.60% after emergency admission/hospital transfer <24 h (n = 1, 314) and 3.72% following delayed hospital transfer >24 h after initial admission (n = 861, P < 0.01 vs. elective admission and emergency admission/hospital transfer <24 h). In multivariable analysis, a delayed hospital transfer >24 h [odds ratio (OR) 2.28, 95% confidence interval (CI) 1.59-3.28, P < 0.01], the occurrence of procedure-related major adverse events (OR 6.81, 95% CI 2.90-16.0, P < 0.01), Charlson Comorbidity Index (CCI, OR 2.39, 95% CI 1.56-3.66, P < 0.01) and its components congestive heart failure (OR 8.04, 95% CI 1.71-37.8, P < 0.01), and diabetes mellitus (OR 1.59, 95% CI 1.13-2.22, P < 0.01) were significantly associated with in-hospital death. CONCLUSIONS: We reported in-hospital mortality rates after CA of ventricular arrhythmias in the largest multicentre, administrative dataset in Germany which can be implemented in quality management programs. Aside from comorbidities, a delayed hospital transfer to a CA performing centre is associated with an increased in-hospital mortality. This deserves further studies to determine the optimal management strategy.

In-hospital mortality of patients with atrial arrhythmias: insights from the German-wide Helios hospital network of 161 502 patients and 34 025 arrhythmia-related procedures.

Aims: Atrial fibrillation (AFib) and atrial flutter (AFlut) are common arrhythmias with increased use of invasive procedures. A steady re-evaluation of relevant safety endpoints is recommended and both quality management and pay-for-performance programs are evolving. Therefore, the aims of this study were (i) to investigate and report overall in-hospital mortality and mortality of invasive arrhythmia-related procedures and (ii) to identify mortality predictors in a German-wide hospital network. Methods and results: Administrative data provided by 78 Helios hospitals between 2010 and 2017 were examined using International Statistical Classification of Diseases and Related Health Problems- and Operations and Procedures-codes to identify patients with AFib or AFlut as main discharge diagnosis or secondary diagnosis combined with invasive arrhythmia-related interventions. In 161 502 patients, in-hospital mortality was 0.6% with a significant decrease from 0.75% to 0.5% (P < 0.01) during the observational period. In multivariable analysis, age [odds ratio (OR) 2.69, 95% confidence interval (CI) 2.36-3.05; P < 0.01], high centre volume (OR 0.57, 95% CI 0.50-0.65; P < 0.01), emergency hospital admission (OR 1.57, 95% CI 1.38-1.79; P < 0.01), and Charlson Comorbidity Index (CCI, OR 4.95, 95% CI 4.50-5.44; P < 0.01) were found as independent predictors of in-hospital mortality. Mortality rates were 0.05% for left atrial catheter ablation (CA, n = 21 744), 0.3% for right atrial CA (n = 9972), and 0.56% for implantation of a left atrial appendage occluder (n = 2309), respectively. Conclusion: We analysed for the first time in-hospital mortality rates of patients with atrial arrhythmias in a German-wide, multi-centre administrative dataset. This allows feasible, comparable, and up-to-date performance measurement of clinically important endpoints in a real-world setting which may contribute to quality management programs and towards value-based healthcare.

Cardiac tamponade in catheter ablation of atrial fibrillation: German-wide analysis of 21 141 procedures in the Helios atrial fibrillation ablation registry (SAFER).

Aims: Catheter ablation is an established therapy in patients with symptomatic atrial fibrillation (AF) with increasing popularity. Pericardial effusion requiring intervention (PE) is one of the most threatening adverse outcomes. The aim of this study was to examine rates of PE after catheter ablation in a large 'real-world' data set in a German-wide hospital network. Methods and results: Using ICD and OPS codes, administrative data of 85 Helios hospitals from 2010 to 2017 was used to identify AF catheter ablation cases [Helios atrial fibrillation ablation registry (SAFER)]. PE occurred in 0.9% of 21 141 catheter ablation procedures. Patients with PE were significantly older, to a higher percentage female, had more frequently hypertension, mild liver disease, diabetes with chronic complications, and renal disease. Low hospital volume (<50 procedures per year) and radiofrequency ablation (vs. cryoablation) were significantly associated with PE. Using two logistic regression models, age, female gender, hypertension, mild liver disease, diabetes with chronic complications, renal disease, low hospital volume, and radiofrequency ablation remained independent predictors for PE. Conclusion: Overall PE rate was 0.9%. Predictors for PE occurrence involved factors ascribed to the patient (age, gender, comorbidities), the type of catheter ablation (radiofrequency), and the institution (low-volume centres).

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.

Patient Characteristics and Outcomes of Hospitalized Chronic Kidney Disease Patients with and without Type 2 Diabetes Mellitus: Observations from the German Claims Data-Based Cohort of the CaReMe-CKD Multinational Study.

Introduction: Type 2 diabetes mellitus (T2DM) is a leading cause of chronic kidney disease (CKD) globally. Both conditions substantially worsen patients' prognosis. Current data on German in-hospital CKD cohorts are scarce. The multinational CaReMe study was initiated to evaluate the current epidemiology and healthcare burden of cardiovascular, renal and metabolic diseases. In this substudy, we share real-world data on CKD inpatients stratified for coexisting T2DM derived from a large German hospital network. Methods: This study used administrative data of inpatient cases from 89 Helios hospitals from 01/01/2016 to 28/02/2022. Data were extracted from ICD-10-encoded discharge diagnoses and OPS-encoded procedures. The first case meeting a previously developed CKD definition (defined by ICD-10- and OPS-codes) was considered the index case for a particular patient. Subsequent hospitalizations were analysed for readmission statistics. Patient characteristics and pre-defined endpoints were stratified for T2DM at index case. Results: In total, 48,011 patients with CKD were included in the present analysis (mean age ± standard deviation, 73.8 ± 13.1 years; female, 44%) of whom 47.9% had co-existing T2DM. Patients with T2DM were older (75 ± 10.6 vs 72.7 ± 14.9 years, p < 0.001), but gender distribution was similar to patients without T2DM. The burden of cardiovascular disease was increased in patients with T2DM, and index and follow-up in-hospital mortality rates were higher. Non-T2DM patients were characterised by more advanced CKD at baseline. Patients with T2DM had consistently higher readmission numbers for all events of interest, except for readmissions due to kidney failure/dialysis, which were more common in non-T2DM patients. Conclusion: In this study, we present recent data on hospitalized patients with CKD in Germany. In this CKD cohort, nearly half had T2DM, which substantially affected cardiovascular disease burden, rehospitalization frequency and mortality. Interestingly, non-diabetic patients had more advanced underlying renal disease, which affected renal outcomes.

Characteristics and outcome of hospitalized patients with heart failure stratified for chronic kidney disease.

AIMS: Heart failure (HF) and chronic kidney disease (CKD) place significant challenges on the healthcare system, and their co-existence is associated with shared adverse outcomes. The multinational CaReMe project was initiated to provide contemporary, real-world epidemiological data on cardiovascular and reno-metabolic diseases. Utilizing data from the German CaReMe cohort, we characterize a multicentric HF population and describe in-hospital outcomes stratified for co-morbid CKD. METHODS AND RESULTS: This retrospective, observational study analysed administrative data from inpatient cases hospitalized in 87 German Helios hospitals between 1 January 2016 and 31 August 2022. The first hospitalization of patients aged ≥18 years with a primary discharge diagnosis of HF, based on ICD-10 codes, were considered the index cases, and subsequent hospitalizations were considered as readmissions. Baseline characteristics and outcomes were stratified for co-morbid CKD using ICD-10-encoding from the index cases. Cox regression was utilized for readmission endpoints and in-hospital mortality. In total, 174 829 index cases (mean age 79 ± 15 years, 49.9% female) were included; of these, 55.0% had coexisting CKD. Patients with CKD were older, suffered from worse HF-related symptoms, had a higher co-morbidity burden, and in-hospital mortality was increased at index and during follow-up. Prevalent CKD was associated with higher rehospitalization rates and was an independent predictor for in-hospital death. CONCLUSIONS: Within this HF inpatient cohort from a multicentric German database, CKD was diagnosed in more than half of the patients and was associated with increased in-hospital mortality at baseline and during follow-up. Rehospitalizations were observed earlier and more frequently in patients with HF and co-morbid CKD.