Hyperglycemia and glucose variability are associated with worse survival in mechanically ventilated COVID-19 patients: the prospective Maastricht Intensive Care Covid Cohort (preprint)

Data on hyperglycemia and glucose variability in relation to diabetes mellitus, either known or unknown in ICU-setting in COVID-19, are scarce. We prospectively studied daily glucose variables and mortality in strata of diabetes mellitus and glycosylated hemoglobin among mechanically ventilated COVID-19 patients. We used linear-mixed effect models in mechanically ventilated COVID-19 patients to investigate mean and maximum difference in glucose concentration per day over time. We compared ICU survivors and non-survivors and tested for effect-modification by pandemic wave 1 and 2, diabetes mellitus, and admission HbA1c. Among 232 mechanically ventilated COVID-19 patients, 21.1% had known diabetes mellitus, whereas 16.9% in wave 2 had unknown diabetes mellitus. Non-survivors had higher mean glucose concentrations (ß 0.62 mmol/l; 95%CI 0.20–1.06; P = 0.004) and higher maximum differences in glucose concentrations per day (ß 0.85 mmol/l; 95%CI 0.37–1.33; P = 0.001). Effect modification by wave, history of diabetes mellitus and admission HbA1c in associations between glucose and survival was not present. Effect of higher mean glucose concentrations was modified by pandemic wave (wave 1 (ß 0.74; 95% CI 0.24–1.23) mmol/l vs. wave 2 ß 0.37 (95%CI 0.25–0.98) mmol/l). Hyperglycemia and glucose variability are associated with mortality in mechanically ventilated COVID-19 patients irrespective of the presence of diabetes mellitus.

Performance of prediction models for short term outcome in COVID-19 patients in the emergency department: a retrospective study (preprint)

IntroductionCoronavirus disease 2019 (COVID-19) has a high burden on the healthcare system and demands information on the outcome early after admission to the emergency department (ED). Previously developed prediction models may assist in triaging patients when allocating healthcare resources. We aimed to assess the value of several prediction models when applied to COVID-19 patients in the ED. MethodsAll consecutive COVID-19 patients who visited the ED of a combined secondary/tertiary care center were included. Prediction models were selected based on their feasibility. The primary outcome was 30-day mortality, secondary outcomes were 14-day mortality, and a composite outcome of 30-day mortality and admission to the medium care unit (MCU) or the intensive care unit (ICU). The discriminatory performance of the prediction models was assessed using an area under the receiver operating characteristic curve (AUC). ResultsA total of 403 ED patients were diagnosed with COVID-19. Within 30 days, 95 patients died (23.6%), 14-day mortality was 19.1%. Forty-eight patients (11.9%) were admitted to the MCU, 66 patients (16.4%) to the ICU and 152 patients (37.7%) met the composite endpoint. Eleven models were included: RISE UP score, 4C mortality score, CURB-65, MEWS, REMS, abbMEDS, SOFA, APACHE II, CALL score, ACP index and Host risk factor score. The RISE UP score and 4C mortality score showed a very good discriminatory performance for 30-day mortality (AUC 0.83 and 0.84 respectively, 95% CI 0.79-0.88 for both), for 14-day mortality (AUC 0.83, 95% CI: 0.79-0.88, for both) and for the composite outcome (AUC 0.79 and 0.77 respectively, 95% CI 0.75-0.84). The discriminatory performance of the RISE UP score and 4C mortality score was significantly higher compared to that of the other models. ConclusionThe RISE UP score and 4C mortality score have good discriminatory performance in predicting adverse outcome in ED patients with COVID-19. These prediction models can be used to recognize patients at high risk for short-term poor outcome and may assist in guiding clinical decision-making and allocating healthcare resources.

Anti-C5a Antibody (IFX-1) Treatment of Severe COVID-19: An Exploratory Phase 2 Randomized Controlled Trial (preprint)

Background: Severe coronavirus disease 2019 (Covid-19) is characterized by inflammation and coagulation in the presence of complement activation. Methods: We conducted an explorative phase 2 randomized, open label first part of an adaptive phase 2/3 trial of intravenous IFX-1, a monoclonal antibody selectively blocking the anaphylatoxin C5a, in adults with severe Covid-19. Patients were randomized between IFX-1 plus best supportive care (BSC) or BSC only. Results: 30 patients underwent randomization: 15 assigned to IFX-1 and 15 to BSC. PaO2/FiO2 ratio improvement on day 5, chosen as primary outcome parameter, did not show significant differences between groups. However, IFX-1 treatment was associated with consistent trends of improvement as evidenced by lower mortality rate, reduction in renal impairment, normalization of lymphocyte counts, and lowering of plasma lactate dehydrogenase concentrations. Kaplan-Meier estimates of mortality by 28 days were 13% for IFX-1 and 27% for BSC (HR for death, 0.56; 95%CI 0.09-3.74). Serious adverse events rates were comparable between groups but the rate of pulmonary embolisms was three-fold lower in the IFX-1 group (13%) compared to BSC group (40%). IFX-1 treatment was associated with significant increase of D-dimer levels suggesting a potential pro-fibrinolytic activity of anti-C5a treatment. Conclusion: In this exploratory part of the study, C5a inhibition with IFX-1 was shown to be safe in severe Covid-19. PaO2/FiO2 ratio at day five was comparable between groups, but consistent signals of benefit including a lower 28-day all-cause mortality rate, lower rate in impaired kidney function and a lower rate of pulmonary embolism warrant investigating C5a-inhibition with IFX-1 within a phase 3 trial.Trial Registration: This trial has been registered with the NIH, U.S. National Library of Medicine at ClinicalTrials.gov (NCT04333420). Funding Statement: The trial is funded by InflaRx GmbH.Declaration of Interests: NR and RG are founders, active officers and executive directors of InflaRx (InflaRx GmbH, InflaRx Pharmaceuticals Inc. and InflaRx N.V.) and hold shares and stock options in InflaRx. KP is Global Head of Clinical Development of InflaRx and holds stock options in InflaRx. SR is employee at Metronomia, a contracted statistical service provider for InflaRx. MW is supported by grants from the German Research Foundation, SFB-TR84 C6 and C9 and by the German Ministry of Education and Research in the framework of the CAPSyS (01ZX1304B) and the PROVID project (FKZ 01KI20160A). DvdB reports receiving departmental honoraria for serving on a scientific advisory board for InflaRx in 2017, paid to Amsterdam UMC. All other authors have no Conflict of Interest. Ethics Approval Statement: The study protocol was approved by the institutional review board of the Academic Medical Center, part of Amsterdam UMC, Amsterdam, the Netherlands (IRB: 2020_067#B2020179). If direct informed consent of patients was not feasible, patients could be included with a deferred consent procedure. All patients or their legally authorized representatives gave written informed consent for the study.

Serial measurements in COVID-19-induced acute respiratory disease to unravel heterogeneity of the disease course: design of the Maastricht Intensive Care COVID cohort; MaastrICCht (preprint)

BackgroundThe course of the disease in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in mechanically ventilated patients is unknown. To unravel the clinical heterogeneity of the SARS-CoV-2 infection in these patients, we designed the prospective observational Maastricht Intensive Care COVID cohort; MaastrICCht. We incorporated serial measurements that harbour aetiological, diagnostic and predictive information. The study aims to investigate the heterogeneity of the natural course of critically ill patients with SARS-CoV-2 infection. Study populationMechanically ventilated patients admitted to the Intensive Care with SARS- CoV-2 infection. Main messageWe will collect clinical variables, vital parameters, laboratory variables, mechanical ventilator settings, chest electrical impedance tomography, electrocardiograms, echocardiography as well as other imaging modalities to assess heterogeneity of the natural course of SARS-CoV-2 infection in critically ill patients. The MaastrICCht cohort is, also designed to foster various other studies and registries and intends to create an open-source database for investigators. Therefore, a major part of the data collection is aligned with an existing national Intensive Care data registry and two international COVID-19 data collection initiatives. Additionally, we create a flexible design, so that additional measures can be added during the ongoing study based on new knowledge obtained from the rapidly growing body of evidence. ConclusionThe spread of the COVID-19 pandemic requires the swift implementation of observational research to unravel heterogeneity of the natural course of the disease of SARS- CoV-2 infection in mechanically ventilated patients. Our design is expected to enhance aetiological, diagnostic and prognostic understanding of the disease. This paper describes the design of the MaastrICCht cohort. Strengths and limitations of this studyO_LISerial measurements that characterize the disease course of SARS-CoV-2 infection in mechanically ventilated patients C_LIO_LIData collection and analysis according to a predefined protocol C_LIO_LIFlexible, evolving design enabling the study of multiple aspects of SARS-CoV-2 infection in mechanically ventilated patients C_LIO_LISingle centre, including only ICU patients C_LI