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Backround: In February 2021, the first formal evidence and consensus-based (S3) guidelines for the inpatient treatment of patients with COVID-19 were published in Germany and have been updated twice during 2021. The aim of the present study is to re-evaluate the dissemination pathways and strategies for ICU staff (first evaluation in December 2020 when previous versions of consensus-based guidelines (S2k) were published) and question selected aspects of guideline adherence of standard care for patients with COVID-19 in the ICU. Methods: We conducted an anonymous online survey among German intensive care staff from 11 October 2021 to 11 November 2021. We distributed the survey via e-mail in intensive care facilities and requested redirection to additional intensive care staff (snowball sampling). Results: There was a difference between the professional groups in the number, selection and qualitative assessment of information sources about COVID-19. Standard operating procedures were most frequently used by all occupational groups and received a high quality rating. Physicians preferred sources for active information search (e.g., medical journals), while nurses predominantly used passive consumable sources (e.g., every-day media). Despite differences in usage behaviour, the sources were rated similarly in terms of the quality of the information on COVID-19. The trusted organizations have not changed over time. The use of guidelines was frequently stated and highly recommended. The majority of the participants reported guideline-compliant treatment. Nevertheless, there were certain variations in the use of medication as well as the criteria chosen for discontinuing non-invasive ventilation (NIV) compared to guideline recommendations. Conclusions: An adequate external source of information for nursing staff is lacking, the usual sources of physicians are only appropriate for the minority of nursing staff. The self-reported use of guidelines is high.
Background
Severe COVID-19 induced acute respiratory distress syndrome (ARDS) often requires extracorporeal membrane oxygenation (ECMO). Recent German health insurance data revealed low ICU survival rates. Patient characteristics and experience of the ECMO center may determine intensive care unit (ICU) survival. The current study aimed to identify factors affecting ICU survival of COVID-19 ECMO patients.
Methods
673 COVID-19 ARDS ECMO patients treated in 26 centers between January 1st 2020 and March 22nd 2021 were included. Data on clinical characteristics, adjunct therapies, complications, and outcome were documented. Block wise logistic regression analysis was applied to identify variables associated with ICU-survival.
Results
Most patients were between 50 and 70 years of age. PaO\(_{2}\)/FiO\(_{2}\) ratio prior to ECMO was 72 mmHg (IQR: 58–99). ICU survival was 31.4%. Survival was significantly lower during the 2nd wave of the COVID-19 pandemic. A subgroup of 284 (42%) patients fulfilling modified EOLIA criteria had a higher survival (38%) (p = 0.0014, OR 0.64 (CI 0.41–0.99)). Survival differed between low, intermediate, and high-volume centers with 20%, 30%, and 38%, respectively (p = 0.0024). Treatment in high volume centers resulted in an odds ratio of 0.55 (CI 0.28–1.02) compared to low volume centers. Additional factors associated with survival were younger age, shorter time between intubation and ECMO initiation, BMI > 35 (compared to < 25), absence of renal replacement therapy or major bleeding/thromboembolic events.
Conclusions
Structural and patient-related factors, including age, comorbidities and ECMO case volume, determined the survival of COVID-19 ECMO. These factors combined with a more liberal ECMO indication during the 2nd wave may explain the reasonably overall low survival rate. Careful selection of patients and treatment in high volume ECMO centers was associated with higher odds of ICU survival.
Background: The COVID-19 pandemic has led to a flood of — often contradictory — evidence. HCWs had to develop strategies to locate information that supported their work. We investigated the information-seeking of different HCW groups in Germany. Methods: In December 2020, we conducted online surveys on COVID-19 information sources, strategies, assigned trustworthiness, and barriers — and in February 2021, on COVID-19 vaccination information sources. Results were analyzed descriptively; group comparisons were performed using χ\(^2\)-tests. Results: For general COVID-19-related medical information (413 participants), non-physicians most often selected official websites (57%), TV (57%), and e-mail/newsletters (46%) as preferred information sources — physicians chose official websites (63%), e-mail/newsletters (56%), and professional journals (55%). Non-physician HCWs used Facebook/YouTube more frequently. The main barriers were insufficient time and access issues. Non-physicians chose abstracts (66%), videos (45%), and webinars (40%) as preferred information strategy; physicians: overviews with algorithms (66%), abstracts (62%), webinars (48%). Information seeking on COVID-19 vaccination (2700 participants) was quite similar, however, with newspapers being more often used by non-physicians (63%) vs. physician HCWs (70%). Conclusion: Non-physician HCWs more often consulted public information sources. Employers/institutions should ensure the supply of professional, targeted COVID-19 information for different HCW groups.
Vaccination hesitancy is a threat to herd immunity. Healthcare workers (HCWs) play a key role in promoting Coronavirus disease 2019 (COVID-19) vaccination in the general population. We therefore aimed to provide data on COVID-19 vaccination acceptance/hesitancy among German HCWs. For this exploratory, cross-sectional study, an online survey was conducted in February 2021. The survey included 54 items on demographics; previous vaccination behavior; trust in vaccines, physicians, the pharmaceutical industry and health politics; fear of adverse effects; assumptions regarding the consequences of COVID-19; knowledge about vaccines; and information seeking behavior. Odds ratios with 95% confidence intervals were calculated and chi-square tests were performed. Four thousand five hundred surveys were analyzed. The overall vaccination acceptance was 91.7%. The age group ≤20 years showed the lowest vaccination acceptance. Factors associated with vaccination hesitancy were lack of trust in authorities and pharmaceutical companies. Attitudes among acquaintances were associated with vaccination hesitancy too. Participants with vaccination hesitancy more often obtained information about COVID-19 vaccines via messenger services or online video platforms and underperformed in the knowledge test. We found high acceptance amongst German HCWs. Several factors associated with vaccination hesitancy were identified which could be targeted in HCW vaccination campaigns.
Background: Acute respiratory failure is the most important organ dysfunction of COVID-19 patients. While non-invasive ventilation (NIV) and high-flow nasal cannula (HFNC) oxygen are frequently used, efficacy and safety remain uncertain. Benefits and harms of awake prone positioning (APP) in COVID-19 patients are unknown. Methods: We searched for randomized controlled trials (RCTs) comparing HFNC vs. NIV and APP vs. standard care. We meta-analyzed data for mortality, intubation rate, and safety. Results: Five RCTs (2182 patients) were identified. While it remains uncertain whether HFNC compared to NIV alters mortality (RR: 0.92, 95% CI 0.65–1.33), HFNC may increase rate of intubation or death (composite endpoint; RR 1.22, 1.03–1.45). We do not know if HFNC alters risk for harm. APP compared to standard care probably decreases intubation rate (RR 0.83, 0.71–0.96) but may have little or no effect on mortality (RR: 1.08, 0.51–2.31). Conclusions: Certainty of evidence is moderate to very low. There is no compelling evidence for either HFNC or NIV, but both carry substantial risk for harm. The use of APP probably has benefits although mortality appears unaffected.
(1) Background: Health care workers (HCWs) play a key role in increasing anti-COVID vaccination rates. Fear of potential side effects is one of the main reasons for vaccine hesitancy. We investigated which side effects are of concern to HCWs and how these are associated with vaccine hesitancy. (2) Methods: Data were collected in an online survey in February 2021 among HCWs from across Germany with 4500 included participants. Free-text comments on previously experienced vaccination side effects, and fear of short- and long-term side effects of the COVID-19 vaccination were categorized and analyzed. (3) Results: Most feared short-term side effects were vaccination reactions, allergic reactions, and limitations in daily life. Most feared long-term side effects were (auto-) immune reactions, neurological side effects, and currently unknown long-term consequences. Concerns about serious vaccination side effects were associated with vaccination refusal. There was a clear association between refusal of COVID-19 vaccination in one's personal environment and fear of side effects. (4) Conclusions: Transparent information about vaccine side effects is needed, especially for HCW. Especially when the participants' acquaintances advised against vaccination, they were significantly more likely to fear side effects. Thus, further education of HCW is necessary to achieve good information transfer in clusters as well.
Background
Intensive Care Resources are heavily utilized during the COVID-19 pandemic. However, risk stratification and prediction of SARS-CoV-2 patient clinical outcomes upon ICU admission remain inadequate. This study aimed to develop a machine learning model, based on retrospective & prospective clinical data, to stratify patient risk and predict ICU survival and outcomes.
Methods
A Germany-wide electronic registry was established to pseudonymously collect admission, therapeutic and discharge information of SARS-CoV-2 ICU patients retrospectively and prospectively. Machine learning approaches were evaluated for the accuracy and interpretability of predictions. The Explainable Boosting Machine approach was selected as the most suitable method. Individual, non-linear shape functions for predictive parameters and parameter interactions are reported.
Results
1039 patients were included in the Explainable Boosting Machine model, 596 patients retrospectively collected, and 443 patients prospectively collected. The model for prediction of general ICU outcome was shown to be more reliable to predict “survival”. Age, inflammatory and thrombotic activity, and severity of ARDS at ICU admission were shown to be predictive of ICU survival. Patients’ age, pulmonary dysfunction and transfer from an external institution were predictors for ECMO therapy. The interaction of patient age with D-dimer levels on admission and creatinine levels with SOFA score without GCS were predictors for renal replacement therapy.
Conclusions
Using Explainable Boosting Machine analysis, we confirmed and weighed previously reported and identified novel predictors for outcome in critically ill COVID-19 patients. Using this strategy, predictive modeling of COVID-19 ICU patient outcomes can be performed overcoming the limitations of linear regression models.
Trial registration “ClinicalTrials” (clinicaltrials.gov) under NCT04455451.
Introduction:
Coronavirus disease (COVID-19) has recently dominated scientific literature. Incomplete understanding and a lack of data concerning the pathophysiology, epidemiology, and optimal treatment of the disease has resulted in conflicting recommendations. Adherence to existing guidelines and actual treatment strategies have thus far not been studied systematically. We hypothesized that capturing the variance in care would lead to the discovery of aspects that need further research and—in case of proven benefits of interventions not being performed—better communication to care providers.
Methods:
This article is based on a quantitative and qualitative cross-sectional mixed-methods online survey among intensive-care physicians in Germany during the COVID-19 pandemic by the CEOsys (COVID-19 Evidence Ecosystem) network, endorsed by the German Interdisciplinary Association for Intensive Care and Emergency Medicine (DIVI) conducted from December 3 to 31 December 2020.
Results:
We identified several areas of care with an especially high variance in treatment among hospitals in Germany. Crucially, 51.5% of the participating ICUs (n = 205) reported using intubation as a last resort for respiratory failure in COVID-19 patients, while 21.8% used intubation early after admission. Furthermore, 11.5% considered extracorporeal membrane oxygenation (ECMO) in awake patients. Finally, 72.3% of respondents used the ARDS-network-table to titrate positive end-expiratory-pressure (PEEP) levels, with 36.9% choosing the low-PEEP table and 41.8% the high-PEEP table.
Conclusions:
We found that significant differences exist between reported treatment strategies and that adherence to published guidelines is variable. We describe necessary steps for future research based on our results highlighting significant clinical variability in care.