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ObjectiveDevelop and validate models that predict mortality of SARS-CoV-2 infected patients admitted to the hospital. DesignRetrospective cohort study SettingA multicenter cohort across ten Dutch hospitals including patients from February 27 to June 8 2020. ParticipantsSARS-CoV-2 positive patients (age [≥] 18) admitted to the hospital. Main Outcome Measures21-day mortality evaluated by the area under the receiver operatory curve (AUC), sensitivity, specificity, positive predictive value and negative predictive value. The predictive value of age was explored by comparison with age-based rules used in practice and by excluding age from analysis. Results2273 patients were included, of whom 516 had died or discharged to palliative care within 21 days after admission. Five feature sets, including premorbid, clinical presentation and laboratory & radiology values, were derived from 80 features. Additionally, an ANOVA-based data-driven feature selection selected the ten features with the highest F-values: age, number of home medications, urea nitrogen, lactate dehydrogenase, albumin, oxygen saturation (%), oxygen saturation is measured on room air, oxygen saturation is measured on oxygen therapy, blood gas pH and history of chronic cardiac disease. A linear logistic regression (LR) and non-linear tree-based gradient boosting (XGB) algorithm fitted the data with an AUC of 0.81 (95% confidence interval 0.77 to 0.85) and 0.82 (0.79 to 0.85), respectively, using the ten selected features. Both models outperformed age-based decision rules used in practice (AUC of 0.69, 0.65 to 0.74 for age > 70). Furthermore, performance remained stable when excluding age as predictor (AUC of 0.78, 0.75 to 0.81) ConclusionBoth models showed excellent performance and had better test characteristics than age-based decision rules, using ten admission features readily available in Dutch hospitals. The models hold promise to aid decision making during a hospital bed shortage.
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Purpose@#In acute middle cerebral artery (MCA) occlusion, collateral vessels provide retrograde supply to the occluded territory. We hypothesized that such collateral flow reduces perfusion of the non-occluded donor region (steal effect). @*Materials and Methods@#Patients with an MCA occlusion with opacification of both ipsi- and contralateral anterior cerebral arteries (ACA) on angiography prior to endovascular treatment were selected. Arteriovenous transit time (AVTT) for both ACA territories was compared for different grades of collateral supply to the MCA territory. In addition, the influence of diabetes and hypertension was analyzed. After successful revascularization, AVTT was re-assessed to determine reversibility. @*Results@#Forty-one patients were analyzed. An AVTT of 8.6 seconds (standard deviation [SD] 2.4 seconds) was seen in the ACA territory of the affected hemisphere in comparison to 6.6 seconds (SD 2.1 seconds) for the contralateral side (P<0.001). A more prolonged (but not significant) AVTT was seen in cases with a higher collateral grade. No difference in AVTT was seen in patients with diabetes or hypertension. After successful MCA revascularization, AVTT delay was 7.4 seconds (SD 2.1 seconds). @*Conclusion@#A cerebral steal effect occurs in patients with an acute MCA occlusion, probably related to augmented flow to the penumbra area.