Objective We aimed to estimate the incidence of cerebral sinus and venous thrombosis (CVT) within 1 month from first dose administration and the frequency of vaccine‐induced immune thrombotic thrombocytopenia (VITT) as the underlying mechanism after vaccination with BNT162b2, ChAdOx1, and mRNA‐1273, in Germany. Methods A web‐based questionnaire was e‐mailed to all departments of neurology. We requested a report of cases of CVT occurring within 1 month of a COVID‐19 vaccination. Other cerebral events could also be reported. Incidence rates of CVT were calculated by using official statistics of 9 German states. Results A total of 45 CVT cases were reported. In addition, 9 primary ischemic strokes, 4 primary intracerebral hemorrhages, and 4 other neurological events were recorded. Of the CVT patients, 35 (77.8%) were female, and 36 (80.0%) were younger than 60 years. Fifty‐three events were observed after vaccination with ChAdOx1 (85.5%), 9 after BNT162b2 (14.5%) vaccination, and none after mRNA‐1273 vaccination. After 7,126,434 first vaccine doses, the incidence rate of CVT within 1 month from first dose administration was 0.55 (95% confidence interval [CI] = 0.38–0.78) per 100,000 person‐months (which corresponds to a risk of CVT within the first 31 days of 0.55 per 100,000 individuals) for all vaccines and 1.52 (95% CI = 1.00–2.21) for ChAdOx1 (after 2,320,535 ChAdOx1 first doses). The adjusted incidence rate ratio was 9.68 (95% CI = 3.46–34.98) for ChAdOx1 compared to mRNA‐based vaccines and 3.14 (95% CI = 1.22–10.65) for females compared to non‐females. In 26 of 45 patients with CVT (57.8%), VITT was graded highly probable. Interpretation Given an incidence of 0.02 to 0.15 per 100,000 person‐months for CVT in the general population, these findings point toward a higher risk for CVT after ChAdOx1 vaccination, especially for women. ANN NEUROL 2021

The colonization rate for computer keyboard and mouse of a PDMS with potentially pathogenic microorganisms is greater than that of other user interfaces in a surgical ICU. These fomites may be additional reservoirs for the transmision of microorganisms and become vectors for cross-transmission of nosocomial infections in the ICU setting.

BackgroundComputerized clinical trial recruitment support is one promising field for the application of routine care data for clinical research. The primary task here is to compare the eligibility criteria defined in trial protocols with patient data contained in the electronic health record (EHR). To avoid the implementation of different patient definitions in multi-site trials, all participating research sites should use similar patient data from the EHR. Knowledge of the EHR data elements which are commonly available from most EHRs is required to be able to define a common set of criteria. The objective of this research is to determine for five tertiary care providers the extent of available data compared with the eligibility criteria of randomly selected clinical trials.MethodsEach participating study site selected three clinical trials at random. All eligibility criteria sentences were broken up into independent patient characteristics, which were then assigned to one of the 27 semantic categories for eligibility criteria developed by Luo et al. We report on the fraction of patient characteristics with corresponding structured data elements in the EHR and on the fraction of patients with available data for these elements. The completeness of EHR data for the purpose of patient recruitment is calculated for each semantic group.Results351 eligibility criteria from 15 clinical trials contained 706 patient characteristics. In average, 55% of these characteristics could be documented in the EHR. Clinical data was available for 64% of all patients, if corresponding data elements were available. The total completeness of EHR data for recruitment purposes is 35%. The best performing semantic groups were ‘age’ (89%), ‘gender’ (89%), ‘addictive behaviour’ (74%), ‘disease, symptom and sign’ (64%) and ‘organ or tissue status’ (61%). No data was available for 6 semantic groups.ConclusionsThere exists a significant gap in structure and content between data documented during patient care and data required for patient eligibility assessment. Nevertheless, EHR data on age and gender of the patient, as well as selected information on his disease can be complete enough to allow for an effective support of the manual screening process with an intelligent preselection of patients and patient data.

Knowledge of these risk factors should increase the anesthesiologist's attention to decide for the necessity to employ prophylactic or therapeutic techniques or drugs to prevent the neonate from any risk resulting of hypotension of the mother.

Although secondary data analyses have been established in recent years in health research, explicit recommendations for standardized, transparent and complete reporting of secondary data analyses do not exist as yet. Therefore, between 2009 and 2014, a first proposal for a specific reporting standard for secondary data analysis was developed (STROSA 1). Parallel to this national process in Germany, an international reporting standard for routine data analysis was initiated in 2013 (RECORD). Nevertheless, because of the specific characteristics of the German health care system as well as specific data protection requirements, the need for a specific German reporting standard for secondary data analyses became evident. Therefore, STROSA was revised and tested by a task force of 15 experts from the working group Collection and Use of Secondary Data (AGENS) of the German Society for Social Medicine and Prevention (DGSMP) and the German Society for Epidemiology (DGEpi) as well as from the working group Validation and Linkage of Secondary Data of the German Network for Health Services Research (DNVF). The consensus STROSA-2 checklist includes 27 criteria, which should be met in the reporting of secondary data analysis from Germany. The criteria have been illustrated and clarified with specific explanations and examples of good practice. The STROSA reporting standard aims at stimulating a wider scientific discussion on the practicability and completeness of the checklist. After further discussions and possibly resulting modifications, STROSA shall be implemented as a reporting standard for secondary data analyses from Germany. This will guarantee standardized and complete information on secondary data analyses enabling assessment of their internal and external validity.