Visualization of the medial forebrain bundle using diffusion tensor imaging

Diffusion tensor imaging is a technique that enables physicians the portrayal of white matter tracts in vivo. We used this technique in order to depict the medial forebrain bundle (MFB) in 15 consecutive patients between 2012 and 2015. Men and women of all ages were included. There were six women and nine men. The mean age was 58.6 years (39–77). Nine patients were candidates for an eventual deep brain stimulation. Eight of them suffered from Parkinson‘s disease and one had multiple sclerosis. The remaining six patients suffered from different lesions which were situated in the frontal lobe. These were 2 metastasis, 2 meningiomas, 1 cerebral bleeding, and 1 glioblastoma. We used a 3DT1-sequence for the navigation. Furthermore T2- and DTI- sequences were performed. The FOV was 200 × 200 mm2, slice thickness 2 mm, and an acquisition matrix of 96 × 96 yielding nearly isotropic voxels of 2 × 2 × 2 mm. 3-Tesla-MRI was carried out strictly axial using 32 gradient directions and one b0-image. We used Echo-Planar-Imaging (EPI) and ASSET parallel imaging with an acceleration factor of 2. b-value was 800 s/mm2. The maximal angle was 50°. Additional scanning time was < 9 min. We were able to visualize the MFB in 12 of our patients bilaterally and in the remaining three patients we depicted the MFB on one side. It was the contralateral side of the lesion. These were 2 meningiomas and one metastasis. Portrayal of the MFB is possible for everyday routine for neurosurgical interventions. As part of the reward circuitry it might be of substantial importance for neurosurgeons during deep brain stimulation in patients with psychiatric disorders. Surgery in this part of the brain should always take the preservation of this white matter tract into account

Predicting responders to prone positioning in mechanically ventilated patients with COVID-19 using machine learning

Background: For mechanically ventilated critically ill COVID-19 patients, prone positioning has quickly become an important treatment strategy, however, prone positioning is labor intensive and comes with potential adverse effects. Therefore, identifying which critically ill intubated COVID-19 patients will benefit may help allocate labor resources. Methods: From the multi-center Dutch Data Warehouse of COVID-19 ICU patients from 25 hospitals, we selected all 3619 episodes of prone positioning in 1142 invasively mechanically ventilated patients. We excluded episodes longer than 24 h. Berlin ARDS criteria were not formally documented. We used supervised machine learning algorithms Logistic Regression, Random Forest, Naive Bayes, K-Nearest Neighbors, Support Vector Machine and Extreme Gradient Boosting on readily available and clinically relevant features to predict success of prone positioning after 4 h (window of 1 to 7 h) based on various possible outcomes. These outcomes were defined as improvements of at least 10% in PaO2/FiO2 ratio, ventilatory ratio, respiratory system compliance, or mechanical power. Separate models were created for each of these outcomes. Re-supination within 4 h after pronation was labeled as failure. We also developed models using a 20 mmHg improvement cut-off for PaO2/FiO2 ratio and using a combined outcome parameter. For all models, we evaluated feature importance expressed as contribution to predictive performance based on their relative ranking. Results: The median duration of prone episodes was 17 h (11-20, median and IQR, N = 2632). Despite extensive modeling using a plethora of machine learning techniques and a large number of potentially clinically relevant features, discrimination between responders and non-responders remained poor with an area under the receiver operator characteristic curve of 0.62 for PaO2/FiO2 ratio using Logistic Regression, Random Forest and XGBoost. Feature importance was inconsistent between models for different outcomes. Notably, not even being a previous responder to prone positioning, or PEEP-levels before prone positioning, provided any meaningful contribution to predicting a successful next proning episode. Conclusions: In mechanically ventilated COVID-19 patients, predicting the success of prone positioning using clinically relevant and readily available parameters from electronic health records is currently not feasible. Given the current evidence base, a liberal approach to proning in all patients with severe COVID-19 ARDS is therefore justified and in particular regardless of previous results of proning. Keywords: Acute respiratory distress syndrome; COVID-19; Mechanical ventilation

Predicting COVID-19 prognosis in the ICU remained challenging: external validation in a multinational regional cohort

Objective: Many prediction models for Coronavirus Disease 2019 (COVID-19) have been developed. External validation is mandatory before implementation in the Intensive Care Unit (ICU). We selected and validated prognostic models in the Euregio Intensive Care COVID (EICC) cohort. Study design and setting: In this multinational cohort study, routine data from COVID-19 patients admitted to ICUs within the Euregio Meuse-Rhine were collected from March to August 2020. COVID-19 models were selected based on model type, predictors, outcomes, and reporting. Furthermore, general ICU scores were assessed. Discrimination was assessed by area under the receiver operating characteristic curves (AUCs) and calibration by calibration-in-the-large and calibration plots. A random-effects meta-analysis was used to pool results. Results: 551 patients were admitted. Mean age was 65.4±11.2 years, 29% were female, and ICU mortality was 36%. Nine out of 238 published models were externally validated. Pooled AUCs were between 0.53 and 0.70 and calibration-in-the-large between -9% and 6%. Calibration plots showed generally poor but, for the 4C Mortality score and SEIMC score, moderate calibration. Conclusion: Of the nine prognostic models that were externally validated in the EICC cohort, only two showed reasonable discrimination and moderate calibration. For future pandemics, better models based on routine data are needed to support admission decision-making

Anxiety of Final Semester Students: Mini Review

Students often experience events that may cause anxiety in the final stages of their lectures, especially at the stage of writing a thesis. Our literature review research aims to find out about anxiety in students and its prevention efforts. Approximately 80% of students who experience anxiety during thesis exams are recorded. Our literature research finds that prevention efforts are needed, including increasing individual student awareness to reduce negative thoughts and trying to focus thoughts and attention on positive things. In addition, universities need to provide adequate health facilities, including psychological assistance

Better COVID-19 Intensive Care Unit survival in females, independent of age, disease severity, comorbidities, and treatment

Although male Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) patients have higher Intensive Care Unit (ICU) admission rates and a worse disease course, a comprehensive analysis of female and male ICU survival and underlying factors such as comorbidities, risk factors, and/or anti-infection/inflammatory therapy administration is currently lacking. Therefore, we investigated the association between sex and ICU survival, adjusting for these and other variables. In this multicenter observational cohort study, all patients with SARS-CoV-2 pneumonia admitted to seven ICUs in one region across Belgium, The Netherlands, and Germany, and requiring vital organ support during the first pandemic wave were included. With a random intercept for a center, mixed-effects logistic regression was used to investigate the association between sex and ICU survival. Models were adjusted for age, Acute Physiology and Chronic Health Evaluation II (APACHE II) score, comorbidities, and anti-infection/inflammatory therapy. Interaction terms were added to investigate effect modifications by sex with country and sex with obesity. A total of 551 patients (29% were females) were included. Mean age was 65.4 ± 11.2 years. Females were more often obese and smoked less frequently than males (p-value 0.001 and 0.042, respectively). APACHE II scores of females and males were comparable. Overall, ICU mortality was 12% lower in females than males (27% vs 39% respectively, p-value  0.23 and 0.84, respectively). ICU survival in female SARS-CoV-2 patients was higher than in male patients, independent of age, disease severity, smoking, obesity, comorbidities, anti-infection/inflammatory therapy, and country. Sex-specific biological mechanisms may play a role, emphasizing the need to address diversity, such as more sex-specific prediction, prognostic, and therapeutic approach strategies

Differences and Similarities Among COVID-19 Patients Treated in Seven ICUs in Three Countries Within One Region:An Observational Cohort Study

To investigate healthcare system–driven variation in general characteristics, interventions, and outcomes in coronavirus disease 2019 (COVID-19) patients admitted to the ICU within one Western European region across three countries. DESIGN: Multicenter observational cohort study. SETTING: Seven ICUs in the Euregio Meuse-Rhine, one region across Belgium, The Netherlands, and Germany. PATIENTS: Consecutive COVID-19 patients supported in the ICU during the first pandemic wave. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Baseline demographic and clinical characteristics, laboratory values, and outcome data were retrieved after ethical approval and data-sharing agreements. Descriptive statistics were performed to investigate country-related practice variation. From March 2, 2020, to August 12, 2020, 551 patients were admitted. Mean age was 65.4 ± 11.2 years, and 29% were female. At admission, Acute Physiology and Chronic Health Evaluation II scores were 15.0 ± 5.5, 16.8 ± 5.5, and 15.8 ± 5.3 (p = 0.002), and Sequential Organ Failure Assessment scores were 4.4 ± 2.7, 7.4 ± 2.2, and 7.7 ± 3.2 (p < 0.001) in the Belgian, Dutch, and German parts of Euregio, respectively. The ICU mortality rate was 22%, 42%, and 44%, respectively (p < 0.001). Large differences were observed in the frequency of organ support, antimicrobial/inflammatory therapy application, and ICU capacity. Mixed-multivariable logistic regression analyses showed that differences in ICU mortality were independent of age, sex, disease severity, comorbidities, support strategies, therapies, and complications. CONCLUSIONS: COVID-19 patients admitted to ICUs within one region, the Euregio Meuse-Rhine, differed significantly in general characteristics, applied interventions, and outcomes despite presumed genetic and socioeconomic background, admission diagnosis, access to international literature, and data collection are similar. Variances in healthcare systems’ organization, particularly ICU capacity and admission criteria, combined with a rapidly spreading pandemic might be important drivers for the observed differences. Heterogeneity between patient groups but also healthcare systems should be presumed to interfere with outcomes in coronavirus disease 2019