Vascular Function, Systemic Inflammation, and Coagulation Activation 18 Months after COVID-19 Infection: An Observational Cohort Study.

INTRODUCTION: Among its effect on virtually all other organs, COVID-19 affects the cardiovascular system, potentially jeopardizing the cardiovascular health of millions. Previous research has shown no indication of macrovascular dysfunction as reflected by carotid artery reactivity, but has shown sustained microvascular dysfunction, systemic inflammation, and coagulation activation at 3 months after acute COVID-19. The long-term effects of COVID-19 on vascular function remain unknown. MATERIALS AND METHODS: This cohort study involved 167 patients who participated in the COVAS trial. At 3 months and 18 months after acute COVID-19, macrovascular dysfunction was evaluated by measuring the carotid artery diameter in response to cold pressor testing. Additionally, plasma endothelin-1, von Willebrand factor, Interleukin(IL)-1ra, IL-6, IL-18, and coagulation factor complexes were measured using ELISA techniques. RESULTS: The prevalence of macrovascular dysfunction did not differ between 3 months (14.5%) and 18 months (11.7%) after COVID-19 infection (p = 0.585). However, there was a significant decrease in absolute carotid artery diameter change, 3.5% ± 4.7 vs. 2.7% ± 2.5, p-0.001, respectively. Additionally, levels of vWF:Ag were persistently high in 80% of COVID-19 survivors, reflecting endothelial cell damage and possibly attenuated endothelial function. Furthermore, while levels of the inflammatory cytokines interleukin(IL)-1RA and IL-18 were normalized and evidence of contact pathway activation was no longer present, the concentrations of IL-6 and thrombin:antithrombin complexes were further increased at 18 months versus 3 months (2.5 pg/mL ± 2.6 vs. 4.0 pg/mL ± 4.6, p = 0.006 and 4.9 µg/L ± 4.4 vs. 18.2 µg/L ± 11.4, p < 0.001, respectively). DISCUSSION: This study shows that 18 months after COVID-19 infection, the incidence of macrovascular dysfunction as defined by a constrictive response during carotid artery reactivity testing is not increased. Nonetheless, plasma biomarkers indicate sustained endothelial cell activation (vWF), systemic inflammation (IL-6), and extrinsic/common pathway coagulation activation (FVII:AT, TAT) 18 months after COVID-19 infection.

Prevalence, pathophysiology, prediction and health-related quality of life of long COVID: study protocol of the longitudinal multiple cohort CORona Follow Up (CORFU) study.

INTRODUCTION: The variety, time patterns and long-term prognosis of persistent COVID-19 symptoms (long COVID-19) in patients who suffered from mild to severe acute COVID-19 are incompletely understood. Cohort studies will be combined to describe the prevalence of long COVID-19 symptoms, and to explore the pathophysiological mechanisms and impact on health-related quality of life. A prediction model for long COVID-19 will be developed and internally validated to guide care in future patients. METHODS AND ANALYSIS: Data from seven COVID-19 cohorts will be aggregated in the longitudinal multiple cohort CORona Follow Up (CORFU) study. CORFU includes Dutch patients who suffered from COVID-19 at home, were hospitalised without or with intensive care unit treatment, needed inpatient or outpatient rehabilitation and controls who did not suffer from COVID-19. Individual cohort study designs were aligned and follow-up has been synchronised. Cohort participants will be followed up for a maximum of 24 months after acute infection. Next to the clinical characteristics measured in individual cohorts, the CORFU questionnaire on long COVID-19 outcomes and determinants will be administered digitally at 3, 6, 12, 18 and 24 months after the infection. The primary outcome is the prevalence of long COVID-19 symptoms up to 2 years after acute infection. Secondary outcomes are health-related quality of life (eg, EQ-5D), physical functioning, and the prevalence of thromboembolic complications, respiratory complications, cardiovascular diseases and endothelial dysfunction. A prediction model and a patient platform prototype will be developed. ETHICS AND DISSEMINATION: Approval was obtained from the medical research ethics committee of Maastricht University Medical Center+ and Maastricht University (METC 2021-2990) and local committees of the participating cohorts. The project is supported by ZonMW and EuroQol Research Foundation. Results will be published in open access peer-reviewed scientific journals and presented at (inter)national conferences. TRIAL REGISTRATION NUMBER: NCT05240742.

Life after COVID-19: the road from intensive care back to living - a prospective cohort study.

OBJECTIVES: The aim of the study was to evaluate recovery of participation in post-COVID-19 patients during the first year after intensive care unit (ICU) discharge. The secondary aim was to identify the early determinants associated with recovery of participation. DESIGN: Prospective cohort study. SETTING: COVID-19 post-ICU inpatient rehabilitation in the Netherlands, during the first epidemic wave between April and July 2020, with 1-year follow-up. PARTICIPANTS: COVID-19 ICU survivors ≥18 years of age needing inpatient rehabilitation. MAIN OUTCOME MEASURES: Participation in society was assessed by the 'Utrecht Scale for Evaluation of Rehabilitation-Participation' (USER-P) restrictions scale. Secondary measures of body function impairments (muscle force, pulmonary function, fatigue (Multidimensional Fatigue Inventory), breathlessness (Medical Research Council (MRC) breathlessness scale), pain (Numerical Rating Scale)), activity limitations (6-minute walking test, Patient reported outcomes measurement information system (PROMIS) 8b), personal factors (coping (Utrecht Proactive Coping Scale), anxiety and depression (Hospital Anxiety and Depression Scale), post-traumatic stress (Global Psychotrauma Screen-Post Traumatic Stress Disorder), cognitive functioning (Checklist for Cognitive Consequences after an ICU-admission)) and social factors were used. STATISTICAL ANALYSES: linear mixed-effects model, with recovery of participation levels as dependent variable. Patient characteristics in domains of body function, activity limitations, personal and social factors were added as independent variables. RESULTS: This study included 67 COVID-19 ICU survivors (mean age 62 years, 78% male). Mean USER-P restrictions scores increased over time; mean participation levels increasing from 62.0, 76.5 to 86.1 at 1, 3 and 12 months, respectively. After 1 year, 50% had not fully resumed work and restrictions were reported in physical exercise (51%), household duties (46%) and leisure activities (29%). Self-reported complaints of breathlessness and fatigue, more perceived limitations in daily life, as well as personal factors (less proactive coping style and anxiety/depression complaints) were associated with delayed recovery of participation (all p value <0.05). CONCLUSIONS: This study supports the view that an integral vision of health is important when looking at the long-term consequence of post-ICU COVID-19. Personal factors such as having a less proactive coping style or mental impairments early on contribute to delayed recovery.

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

OBJECTIVES: 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 Spanish Society of Infectious Diseases and Clinical Microbiology (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.

Pulmonary pathophysiology development of COVID-19 assessed by serial Electrical Impedance Tomography in the MaastrICCht cohort.

Patients with SARS-CoV-2 infection present with different lung compliance and progression of disease differs. Measures of lung mechanics in SARS-CoV-2 patients may unravel different pathophysiologic mechanisms during mechanical ventilation. The objective of this prospective observational study is to describe whether Electrical Impedance Tomography (EIT) guided positive end-expiratory pressure (PEEP) levels unravel changes in EIT-derived parameters over time and whether the changes differ between survivors and non-survivors. Serial EIT-measurements of alveolar overdistension, collapse, and compliance change in ventilated SARS-CoV-2 patients were analysed. In 80 out of 94 patients, we took 283 EIT measurements (93 from day 1-3 after intubation, 66 from day 4-6, and 124 from day 7 and beyond). Fifty-one patients (64%) survived the ICU. At admission mean PaO2/FiO2-ratio was 184.3 (SD 61.4) vs. 151.3 (SD 54.4) mmHg, (p = 0.017) and PEEP was 11.8 (SD 2.8) cmH2O vs. 11.3 (SD 3.4) cmH2O, (p = 0.475), for ICU survivors and non-survivors. At day 1-3, compliance was ~ 55 mL/cmH2O vs. ~ 45 mL/cmH2O in survivors vs. non-survivors. The intersection of overdistension and collapse curves appeared similar at a PEEP of ~ 12-13 cmH2O. At day 4-6 compliance changed to ~ 50 mL/cmH2O vs. ~ 38 mL/cmH2O. At day 7 and beyond, compliance was ~ 38 mL/cmH2O with the intersection at a PEEP of ~ 9 cmH2O vs. ~ 25 mL/cmH2O with overdistension intersecting at collapse curves at a PEEP of ~ 7 cmH2O. Surviving SARS-CoV-2 patients show more favourable EIT-derived parameters and a higher compliance compared to non-survivors over time. This knowledge is valuable for discovering the different groups.

Performance of the APOP-screener for predicting in-hospital mortality in older COVID-19 patients: a retrospective study.

BACKGROUND: A variety of prediction models concerning COVID-19 have been proposed since onset of the pandemic, but to this date no gold standard exists. Mortality rates show a sharp increase with advancing age but with the large heterogeneity of this population in terms of comorbidities, vulnerability and disabilities, identifying risk factors is difficult. Therefore, we aimed to research the multidimensional concept of frailty, measured by the Acute Presenting Older Patient (APOP)-screener, as a risk factor for in-hospital mortality in older COVID-19 patients. METHODS: All consecutive patients of 70 years or older, with a PCR confirmed COVID-19 infection and a completed APOP-score, presenting at the Emergency Department (ED) of the Jeroen Bosch Hospital, the Netherlands, between February 27th 2020 and February 1st 2021 were retrospectively included. We gathered baseline characteristics and scored the CCI and CFS from patient records. The primary outcome was in-hospital mortality. RESULTS: A total of 292 patients met the inclusion criteria. Approximately half of the patients were considered frail by the APOP or CFS. 127 patients (43.5%) scored frail on the CFS, 158 (54.1%) scored high risk on the APOP-screener. 79 patients (27.1%) died during their hospital admission. The APOP-screener showed a significantly elevated risk of in-hospital mortality when patients scored both high risk of functional and evidence of cognitive impairment (OR 2.24, 95% 1.18-4.25). Significant elevation of in-hospital mortality was found for the high CCI-scores (≥ 5)(OR 1.78, 95% 1.02-3.11), but not for the highest CFS category (5-9, frail) (OR 1.35, 95% 0.75-2.47). The discriminatory performance of the APOP, CFS and CCI were comparable (AUC resp. 0.59 (0.52-0.66), 0.54 (0.46-0.62) and 0.58 (0.51-0.65)). CONCLUSION: Although the elevated risk for in-hospital mortality found for the most frail patients as scored by the APOP, this instrument has poor discriminatory value. Additionally, the CFS did not show significance in predicting in-hospital mortality and had a poor discriminatory value as well. Therefore, treatment decisions based on frailty or comorbidities alone should be made with caution. Approaching the heterogeneity of the older population by adding frailty as assessed by the APOP-score to existing prediction models may enhance the predictive value of these models.

Outcome in patients undergoing postponed elective surgery during the COVID-19 pandemic (TRACE II): study protocol for a multicentre prospective observational study.

INTRODUCTION: During the COVID-19 pandemic many non-acute elective surgeries were cancelled or postponed around the world. This has created an opportunity to study the effect of delayed surgery on health conditions prior to surgery and postsurgical outcomes in patients with postponed elective surgery. The control group of the Routine Postsurgical Anesthesia Visit to Improve Patient Outcome (TRACE I) study, conducted between 2016 and 2019, will serve as a control cohort. METHODS AND ANALYSIS: TRACE II is an observational, multicentre, prospective cohort study among surgical patients with postponed surgery due to COVID-19 in academic and non-academic hospitals in the Netherlands. We aim to include 2500 adult patients. The primary outcome will be the 30-day incidence of major postoperative complications. Secondary outcome measures include the 30-day incidence of minor postoperative complications, 1 year mortality, length of stay (in hospital, medium care and intensive care), quality of recovery 30 days after surgery and postoperative quality of life up to 1 year following surgery. Multivariable logistic mixed-effects regression analysis with a random intercept for hospital will be used to test group differences on the primary outcome. ETHICS AND DISSEMINATION: Ethical approval was obtained from the Institutional Review Board of Maastricht University Medical Centre+ and Amsterdam UMC. Findings will be presented at national and international conferences, as well as published in peer-reviewed scientific journals, with a preference for open access journals. Data will be made publicly available after publication of the main results. TRIAL REGISTRATION NUMBER: NL8841.

Serial Assessment of Myocardial Injury Markers in Mechanically Ventilated Patients With SARS-CoV-2 (from the Prospective MaastrICCht Cohort).

Myocardial injury in COVID-19 is associated with in-hospital mortality. However, the development of myocardial injury over time and whether myocardial injury in patients with COVID-19 at the intensive care unit is associated with outcome is unclear. This study prospectively investigates myocardial injury with serial measurements over the full course of intensive care unit admission in mechanically ventilated patients with COVID-19. As part of the prospective Maastricht Intensive Care COVID cohort, predefined myocardial injury markers, including high-sensitivity cardiac troponin T (hs-cTnT), N-terminal pro-B-type natriuretic peptide (NT-proBNP), and electrocardiographic characteristics were serially collected in mechanically ventilated patients with COVID-19. Linear mixed-effects regression was used to compare survivors with nonsurvivors, adjusting for gender, age, APACHE-II score, daily creatinine concentration, hypertension, diabetes mellitus, and obesity. In 90 patients, 57 (63%) were survivors and 33 (37%) nonsurvivors, and a total of 628 serial electrocardiograms, 1,565 hs-cTnT, and 1,559 NT-proBNP concentrations were assessed. Log-hs-cTnT was lower in survivors compared with nonsurvivors at day 1 (ß -0.93 [-1.37; -0.49], p <0.001) and did not change over time. Log-NT-proBNP did not differ at day 1 between both groups but decreased over time in the survivor group (ß -0.08 [-0.11; -0.04] p <0.001) compared with nonsurvivors. Many electrocardiographic abnormalities were present in the whole population, without significant differences between both groups. In conclusion, baseline hs-cTnT and change in NT-proBNP were strongly associated with mortality. Two-thirds of patients with COVID-19 showed electrocardiographic abnormalities. Our serial assessment suggests that myocardial injury is common in mechanically ventilated patients with COVID-19 and is associated with outcome.

HEROES V-V-HEmorRhagic cOmplications in Veno-Venous Extracorporeal life Support-Development and internal validation of multivariable prediction model in adult patients.

BACKGROUND: During extracorporeal life support (ECLS), bleeding is one of the most frequent complications, associated with high morbidity and increased mortality, despite continuous improvements in devices and patient care. Risk factors for bleeding complications in veno-venous (V-V) ECLS applied for respiratory support have been poorly investigated. We aim to develop and internally validate a prediction model to calculate the risk for bleeding complications in adult patients receiving V-V ECLS support. METHODS: Data from adult patients reported to the extracorporeal life support organization (ELSO) registry between the years 2010 and 2020 were analyzed. The primary outcome was bleeding complications recorded during V-V ECLS. Multivariable logistic regression with backward stepwise elimination was used to develop the predictive model. The performance of the model was tested by discriminative ability and calibration with receiver operating characteristic curves and visual inspection of the calibration plot. RESULTS: In total, 18 658 adult patients were included, of which 3 933 (21.1%) developed bleeding complications. The prediction model showed a prediction of bleeding complications with an AUC of 0.63. Pre-ECLS arrest, surgical cannulation, lactate, pO2 , HCO3 , ventilation rate, mean airway pressure, pre-ECLS cardiopulmonary bypass or renal replacement therapy, pre-ECLS surgical interventions, and different types of diagnosis were included in the prediction model. CONCLUSIONS: The model is based on the largest cohort of V-V ECLS patients and reveals the most favorable predictive value addressing bleeding events given the predictors that are feasible and when compared to the current literature. This model will help identify patients at risk of bleeding complications, and decision making in terms of anticoagulation and hemostatic management.

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

INTRODUCTION: Coronavirus disease 2019 (COVID-19) has a high burden on the healthcare system. Prediction models may assist in triaging patients. We aimed to assess the value of several prediction models in COVID-19 patients in the emergency department (ED). METHODS: In this retrospective study, ED patients with COVID-19 were included. Prediction models were selected based on their feasibility. Primary outcome was 30-day mortality, secondary outcomes were 14-day mortality and a composite outcome of 30-day mortality and admission to medium care unit (MCU) or intensive care unit (ICU). The discriminatory performance of the prediction models was assessed using an area under the receiver operating characteristic curve (AUC). RESULTS: We included 403 patients. Thirty-day mortality was 23.6%, 14-day mortality was 19.1%, 66 patients (16.4%) were admitted to ICU, 48 patients (11.9%) to MCU, and 152 patients (37.7%) met the composite endpoint. Eleven prediction models were included. The RISE UP score and 4 C mortality scores showed very good discriminatory performance for 30-day mortality (AUC 0.83 and 0.84, 95% CI 0.79-0.88 for both), significantly higher than that of the other models. CONCLUSION: The RISE UP score and 4 C mortality score can be used to recognise patients at high risk for poor outcome and may assist in guiding decision-making and allocating resources.

Serial markers of coagulation and inflammation and the occurrence of clinical pulmonary thromboembolism in mechanically ventilated patients with SARS-CoV-2 infection; the prospective Maastricht intensive care COVID cohort.

BACKGROUND: The incidence of pulmonary thromboembolism is high in SARS-CoV-2 patients admitted to the Intensive Care. Elevated biomarkers of coagulation (fibrinogen and D-dimer) and inflammation (c-reactive protein (CRP) and ferritin) are associated with poor outcome in SARS-CoV-2. Whether the time-course of fibrinogen, D-dimer, CRP and ferritin is associated with the occurrence of pulmonary thromboembolism in SARS-CoV-2 patients is unknown. We hypothesise that patients on mechanical ventilation with SARS-CoV-2 infection and clinical pulmonary thromboembolism have lower concentrations of fibrinogen and higher D-dimer, CRP, and ferritin concentrations over time compared to patients without a clinical pulmonary thromboembolism. METHODS: In a prospective study, fibrinogen, D-dimer, CRP and ferritin were measured daily. Clinical suspected pulmonary thromboembolism was either confirmed or excluded based on computed tomography pulmonary angiography (CTPA) or by transthoracic ultrasound (TTU) (i.e., right-sided cardiac thrombus). In addition, patients who received therapy with recombinant tissue plasminogen activator were included when clinical instability in suspected pulmonary thromboembolism did not allow CTPA. Serial data were analysed using a mixed-effects linear regression model, and models were adjusted for known risk factors (age, sex, APACHE-II score, body mass index), biomarkers of coagulation and inflammation, and anticoagulants. RESULTS: Thirty-one patients were considered to suffer from pulmonary thromboembolism ((positive CTPA (n = 27), TTU positive (n = 1), therapy with recombinant tissue plasminogen activator (n = 3)), and eight patients with negative CTPA were included. After adjustment for known risk factors and anticoagulants, patients with, compared to those without, clinical pulmonary thromboembolism had lower average fibrinogen concentration of - 0.9 g/L (95% CI: - 1.6 - - 0.1) and lower average ferritin concentration of - 1045 µg/L (95% CI: - 1983 - - 106) over time. D-dimer and CRP average concentration did not significantly differ, 561 µg/L (- 6212-7334) and 27 mg/L (- 32-86) respectively. Ferritin lost statistical significance, both in sensitivity analysis and after adjustment for fibrinogen and D-dimer. CONCLUSION: Lower average concentrations of fibrinogen over time were associated with the presence of clinical pulmonary thromboembolism in patients at the Intensive Care, whereas D-dimer, CRP and ferritin were not. Lower concentrations over time may indicate the consumption of fibrinogen related to thrombus formation in the pulmonary vessels.

Validating the RISE UP score for predicting prognosis in patients with COVID-19 in the emergency department: a retrospective study.

OBJECTIVE: To mitigate the burden of COVID-19 on the healthcare system, information on the prognosis of the disease is needed. The recently developed Risk Stratification in the Emergency Department in Acutely ill Older Patients (RISE UP) score has very good discriminatory value for short-term mortality in older patients in the emergency department (ED). It consists of six readily available items. We hypothesised that the RISE UP score could have discriminatory value for 30-day mortality in ED patients with COVID-19. DESIGN: Retrospective analysis. SETTING: Two EDs of the Zuyderland Medical Centre, secondary care hospital in the Netherlands. PARTICIPANTS: The study sample consisted of 642 adult ED patients diagnosed with COVID-19 between 3 March and until 25 May 2020. Inclusion criteria were (1) admission to the hospital with symptoms suggestive of COVID-19 and (2) positive result of the PCR or (very) high suspicion of COVID-19 according to the chest CT scan. OUTCOME: Primary outcome was 30-day mortality, secondary outcome was a composite of 30-day mortality and admission to intensive care unit (ICU). RESULTS: Within 30 days after presentation, 167 patients (26.0%) died and 102 patients (15.9%) were admitted to ICU. The RISE UP score showed good discriminatory value for 30-day mortality (area under the receiver operating characteristic curve (AUC) 0.77, 95% CI 0.73 to 0.81) and for the composite outcome (AUC 0.72, 95% CI 0.68 to 0.76). Patients with RISE UP scores below 10% (n=121) had favourable outcome (zero deaths and six ICU admissions), while those with scores above 30% (n=221) were at high risk of adverse outcome (46.6% mortality and 19.0% ICU admissions). CONCLUSION: The RISE UP score is an accurate prognostic model for adverse outcome in ED patients with COVID-19. It can be used to identify patients at risk of short-term adverse outcome and may help guide decision-making and allocating healthcare resources.

The "sex gap" in COVID-19 trials: a scoping review.

BACKGROUND: Many studies investigate the role of pharmacological treatments on disease course in Corona Virus Disease 2019 (COVID-19). Sex disparities in genetics, immunological responses, and hormonal mechanisms may underlie the substantially higher fatality rates reported in male COVID-19 patients. To optimise care for COVID-19 patients, prophylactic and therapeutic studies should include sex-specific design and analyses. Therefore, in this scoping review, we investigated whether studies on pharmacological treatment in COVID-19 were performed based on a priori sex-specific design or post-hoc sex-specific analyses. METHODS: We systematically searched PubMed, EMBASE, UpToDate, clinical trial.org, and MedRxiv for studies on pharmacological treatment for COVID-19 until June 6th, 2020. We included case series, randomized controlled trials, and observational studies in humans (≥18 years) investigating antiviral, antimalarial, and immune system modulating drugs. Data were collected on 1) the proportion of included females, 2) whether sex stratification was performed (a priori by design or post-hoc), and 3) whether effect modification by sex was investigated. FINDINGS: 30 studies were eligible for inclusion, investigating remdesivir (n = 2), lopinavir/ritonavir (n = 5), favipiravir (n = 1), umifenovir (n = 1), hydroxychloroquine/chloroquine (n = 8), convalescent plasma (n = 6), interleukin-6 (IL-6) pathway inhibitors (n = 5), interleukin-1 (IL-1) pathway inhibitors (n = 1) and corticosteroids (n = 3). Only one study stratified its data based on sex in a post-hoc analysis, whereas none did a priori by design. None of the studies investigated effect modification by sex. A quarter of the studies included twice as many males as females. INTERPRETATION: Analyses assessing potential interference of sex with (side-)effects of pharmacological therapy for COVID-19 are rarely reported. Considering sex differences in case-fatality rates and genetic, immunological, and hormonal mechanisms, studies should include sex-specific analyses in their design to optimise COVID-19 care. FUNDING: None.

Monitoring of Unfractionated Heparin in Severe COVID-19: An Observational Study of Patients on CRRT and ECMO.

Objective Severe cases of coronavirus disease 2019 (COVID-19) can require continuous renal replacement therapy (CRRT) and/or extracorporeal membrane oxygenation (ECMO). Unfractionated heparin (UFH) to prevent circuit clotting is mandatory but monitoring is complicated by (pseudo)-heparin resistance. In this observational study, we compared two different activated partial thromboplastin time (aPTT) assays and a chromogenic anti-Xa assay in COVID-19 patients on CRRT or ECMO in relation to their UFH dosages and acute phase reactants. Materials and Methods The aPTT (optical [aPTT-CS] and/or mechanical [aPTT-STA] clot detection methods were used), anti-Xa, factor VIII (FVIII), antithrombin III (ATIII), and fibrinogen were measured in 342 samples from 7 COVID-19 patients on CRRT or ECMO during their UFH treatment. Dosage of UFH was primarily based on the aPTT-CS with a heparin therapeutic range (HTR) of 50-80s. Associations between different variables were made using linear regression and Bland-Altman analysis. Results Dosage of UFH was above 35,000IU/24 hours in all patients. aPTT-CS and aPTT-STA were predominantly within the HTR. Anti-Xa was predominantly above the HTR (0.3-0.7 IU/mL) and ATIII concentration was >70% for all patients; mean FVIII and fibrinogen were 606% and 7.5 g/L, respectively. aPTT-CS correlated with aPTT-STA ( r 2 = 0.68) with a bias of 39.3%. Correlation between aPTT and anti-Xa was better for aPTT-CS (0.78 ≤ r 2 ≤ 0.94) than for aPTT-STA (0.34 ≤ r 2 ≤ 0.81). There was no general correlation between the aPTT-CS and ATIII, FVIII, fibrinogen, thrombocytes, C-reactive protein, or ferritin. Conclusion All included COVID-19 patients on CRRT or ECMO conformed to the definition of heparin resistance. A patient-specific association was found between aPTT and anti-Xa. This association could not be explained by FVIII or fibrinogen.

Decreased serial scores of severe organ failure assessments are associated with survival in mechanically ventilated patients; the prospective Maastricht Intensive Care COVID cohort.

BACKGROUND: The majority of patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are admitted to the Intensive Care Unit (ICU) for mechanical ventilation. The role of multi-organ failure during ICU admission as driver for outcome remains to be investigated yet. DESIGN AND SETTING: Prospective cohort of mechanically ventilated critically ill with SARS-CoV-2 infection. PARTICIPANTS AND METHODS: 94 participants of the MaastrICCht cohort (21% women) had a median length of stay of 16 days (maximum of 77). After division into survivors (n = 59) and non-survivors (n = 35), we analysed 1555 serial SOFA scores using linear mixed-effects models. RESULTS: Survivors improved one SOFA score point more per 5 days (95% CI: 4-8) than non-survivors. Adjustment for age, sex, and chronic lung, renal and liver disease, body-mass index, diabetes mellitus, cardiovascular risk factors, and Acute Physiology and Chronic Health Evaluation II score did not change this result. This association was stronger for women than men (P-interaction = 0.043). CONCLUSIONS: The decrease in SOFA score associated with survival suggests multi-organ failure involvement during mechanical ventilation in patients with SARS-CoV-2. Surviving women appeared to improve faster than surviving men. Serial SOFA scores may unravel an unfavourable trajectory and guide decisions in mechanically ventilated patients with SARS-CoV-2.

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).

INTRODUCTION: The course of the disease in 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 a SARS-CoV-2 infection. METHODS AND ANALYSIS: Mechanically ventilated patients admitted to the intensive care with a SARS-CoV-2 infection will be included. We will collect clinical variables, vital parameters, laboratory variables, mechanical ventilator settings, chest electrical impedance tomography, ECGs, echocardiography as well as other imaging modalities to assess heterogeneity of the course of a SARS-CoV-2 infection in critically ill patients. The MaastrICCht 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. The 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 study design is expected to enhance aetiological, diagnostic and prognostic understanding of the disease. This paper describes the design of the MaastrICCht. ETHICS AND DISSEMINATION: Ethical approval has been obtained from the medical ethics committee (Medisch Ethische Toetsingscommissie 2020-1565/3 00 523) of the Maastricht University Medical Centre+ (Maastricht UMC+), which will be performed based on the Declaration of Helsinki. During the pandemic, the board of directors of Maastricht UMC+ adopted a policy to inform patients and ask their consent to use the collected data and to store serum samples for COVID-19 research purposes. All study documentation will be stored securely for fifteen years after recruitment of the last patient. The results will be published in peer-reviewed academic journals, with a preference for open access journals, while particularly considering deposition of the manuscripts on a preprint server early. TRIAL REGISTRATION NUMBER: The Netherlands Trial Register (NL8613).

Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal

OBJECTIVE: To review and appraise the validity and usefulness of published and preprint reports of prediction models for diagnosing coronavirus disease 2019 (covid-19) in patients with suspected infection, for prognosis of patients with covid-19, and for detecting people in the general population at increased risk of covid-19 infection or being admitted to hospital with the disease. DESIGN: Living systematic review and critical appraisal by the COVID-PRECISE (Precise Risk Estimation to optimise covid-19 Care for Infected or Suspected patients in diverse sEttings) group. DATA SOURCES: PubMed and Embase through Ovid, up to 1 July 2020, supplemented with arXiv, medRxiv, and bioRxiv up to 5 May 2020. STUDY SELECTION: Studies that developed or validated a multivariable covid-19 related prediction model. DATA EXTRACTION: At least two authors independently extracted data using the CHARMS (critical appraisal and data extraction for systematic reviews of prediction modelling studies) checklist; risk of bias was assessed using PROBAST (prediction model risk of bias assessment tool). RESULTS: 37 421 titles were screened, and 169 studies describing 232 prediction models were included. The review identified seven models for identifying people at risk in the general population; 118 diagnostic models for detecting covid-19 (75 were based on medical imaging, 10 to diagnose disease severity); and 107 prognostic models for predicting mortality risk, progression to severe disease, intensive care unit admission, ventilation, intubation, or length of hospital stay. The most frequent types of predictors included in the covid-19 prediction models are vital signs, age, comorbidities, and image features. Flu-like symptoms are frequently predictive in diagnostic models, while sex, C reactive protein, and lymphocyte counts are frequent prognostic factors. Reported C index estimates from the strongest form of validation available per model ranged from 0.71 to 0.99 in prediction models for the general population, from 0.65 to more than 0.99 in diagnostic models, and from 0.54 to 0.99 in prognostic models. All models were rated at high or unclear risk of bias, mostly because of non-representative selection of control patients, exclusion of patients who had not experienced the event of interest by the end of the study, high risk of model overfitting, and unclear reporting. Many models did not include a description of the target population (n=27, 12%) or care setting (n=75, 32%), and only 11 (5%) were externally validated by a calibration plot. The Jehi diagnostic model and the 4C mortality score were identified as promising models. CONCLUSION: Prediction models for covid-19 are quickly entering the academic literature to support medical decision making at a time when they are urgently needed. This review indicates that almost all pubished prediction models are poorly reported, and at high risk of bias such that their reported predictive performance is probably optimistic. However, we have identified two (one diagnostic and one prognostic) promising models that should soon be validated in multiple cohorts, preferably through collaborative efforts and data sharing to also allow an investigation of the stability and heterogeneity in their performance across populations and settings. Details on all reviewed models are publicly available at https://www.covprecise.org/. Methodological guidance as provided in this paper should be followed because unreliable predictions could cause more harm than benefit in guiding clinical decisions. Finally, prediction model authors should adhere to the TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) reporting guideline. SYSTEMATIC REVIEW REGISTRATION: Protocol https://osf.io/ehc47/, registration https://osf.io/wy245. READERS' NOTE: This article is a living systematic review that will be updated to reflect emerging evidence. Updates may occur for up to two years from the date of original publication. This version is update 3 of the original article published on 7 April 2020 (BMJ 2020;369:m1328). Previous updates can be found as data supplements (https://www.bmj.com/content/369/bmj.m1328/related#datasupp). When citing this paper please consider adding the update number and date of access for clarity.