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Background:
Factors influencing access to stroke unit (SU) care and data on quality of SU care in Germany are scarce. We investigated characteristics of patients directly admitted to a SU as well as patient-related and structural factors influencing adherence to predefined indicators of quality of acute stroke care across hospitals providing SU care.
Methods:
Data were derived from the German Stroke Registers Study Group (ADSR), a voluntary network of 9 regional registers for monitoring quality of acute stroke care in Germany. Multivariable logistic regression analyses were performed to investigate characteristics influencing direct admission to SU. Generalized Linear Mixed Models (GLMM) were used to estimate the influence of structural hospital characteristics (percentage of patients admitted to SU, year of SU-certification, and number of stroke and TIA patients treated per year) on adherence to predefined quality indicators.
Results:
In 2012 180,887 patients were treated in 255 hospitals providing certified SU care participating within the ADSR were included in the analysis; of those 82.4% were directly admitted to a SU. Ischemic stroke patients without disturbances of consciousness (p < .0001), an interval onset to admission time ≤3 h (p < .0001), and weekend admission (p < .0001) were more likely to be directly admitted to a SU. A higher proportion of quality indicators within predefined target ranges were achieved in hospitals with a higher proportion of SU admission (p = 0.0002). Quality of stroke care could be maintained even if certification was several years ago.
Conclusions:
Differences in demographical and clinical characteristics regarding the probability of SU admission were observed. The influence of structural characteristics on adherence to evidence-based quality indicators was low.
Background: Proportions of patients dying from the coronavirus disease-19 (COVID-19) vary between different countries. We report the characteristics; clinical course and outcome of patients requiring intensive care due to COVID-19 induced acute respiratory distress syndrome (ARDS).
Methods: This is a retrospective, observational multicentre study in five German secondary or tertiary care hospitals. All patients consecutively admitted to the intensive care unit (ICU) in any of the participating hospitals between March 12 and May 4, 2020 with a COVID-19 induced ARDS were included.
Results: A total of 106 ICU patients were treated for COVID-19 induced ARDS, whereas severe ARDS was present in the majority of cases. Survival of ICU treatment was 65.0%. Median duration of ICU treatment was 11 days; median duration of mechanical ventilation was 9 days. The majority of ICU treated patients (75.5%) did not receive any antiviral or anti-inflammatory therapies. Venovenous (vv) ECMO was utilized in 16.3%. ICU triage with population-level decision making was not necessary at any time. Univariate analysis associated older age, diabetes mellitus or a higher SOFA score on admission with non-survival during ICU stay.
Conclusions: A high level of care adhering to standard ARDS treatments lead to a good outcome in critically ill COVID-19 patients.
Background: Urinary tract infections (UTIs) are a common cause of prescribing antibiotics in family medicine. In Germany, about 40% of UTI-related prescriptions are second-line antibiotics, which contributes to emerging resistance rates. To achieve a change in the prescribing behaviour among family physicians (FPs), this trial aims to implement the guideline recommendations in German family medicine.
Methods/design: In a randomized controlled trial, a multimodal intervention will be developed and tested in family practices in four regions across Germany. The intervention will consist of three elements: information on guideline recommendations, information on regional resistance and feedback of prescribing behaviour for FPs on a quarterly basis. The effect of the intervention will be compared to usual practice. The primary endpoint is the absolute difference in the mean of prescribing rates of second-line antibiotics among the intervention and the control group after 12 months. To detect a 10% absolute difference in the prescribing rate after one year, with a significance level of 5% and a power of 86%, a sample size of 57 practices per group will be needed. Assuming a dropout rate of 10%, an overall number of 128 practices will be required. The accompanying process evaluation will provide information on feasibility and acceptance of the intervention.
Discussion: If proven effective and feasible, the components of the intervention can improve adherence to antibiotic prescribing guidelines and contribute to antimicrobial stewardship in ambulatory care.