Effects of Etomidate on Postintubation Hypotension, Inflammatory Markers, and Mortality in Critically Ill Patients with COVID-19: An International, Multicenter, Retrospective Study.

OBJECTIVE: To evaluate the association of etomidate with postintubation hypotension, inflammation, and mortality in critically ill patients with COVID-19. DESIGN: International, multicenter, retrospective study. PARTICIPANTS: Critically ill patients hospitalized specifically for COVID-19 from three major academic institutions in the US and Europe. MAIN OUTCOME AND MEASURES: Patients were allocated into the etomidate (ET) group or another induction agent (OA) group. The primary outcome was postintubation hypotension. Secondary outcomes included postintubation inflammatory status, in-hospital mortality, and mortality at 30 days. RESULTS: 171 patients with a median age of 68 (IQR 58-73) years were included (ET, n = 98; OA, n = 73). Etomidate was associated with lower postintubation mean arterial pressure [74.33 (64-85) mm Hg versus 81.84 (69.75-94.25) mm Hg, p = 0.005] compared to other agents. No statistically significant differences were generally observed in inflammatory markers between the two groups at 7- and 14-days after admission to the intensive care unit. In-hospital mortality [77 (79%) versus 41 (56%), p = 0.003] and mortality at 30-days [78 (80%) versus 43 (59%), p = 0.006] were higher in the ET group. In multivariate logistic regression analysis, only etomidate (p = 0.009) and postintubation mean arterial pressure (p < 0.001) had a statistically significant effect on mortality, in contrast to stress-dose steroids (p = 0.301), after adjusting for creatinine (p = 0.695), blood urea nitrogen (p = 0.153), age (p = 0.055), oxygen saturation of hemoglobin (SpO2) (p = 0.941), and fraction of inspired oxygen (FiO2) (p = 0.712). CONCLUSIONS: Administration of a single-bolus dose of etomidate in critically ill patients with COVID-19 is associated with lower postintubation mean arterial pressure and higher in-hospital and 30-day mortality compared to other induction agents.

Circulating MR-proADM levels, as an indicator of endothelial dysfunction, for early risk stratification of mid-term mortality in COVID-19 patients.

OBJECTIVES: Thromboinflammation, resulting from a complex interaction between thrombocytopathy, coagulopathy, and endotheliopathy, contributes to increased mortality in COVID-19 patients. MR-proADM, as a surrogate of adrenomedullin system disruption, leading to endothelial damage, has been reported as a promising biomarker for short-term prognosis. We evaluated the role of MR-proADM in the mid-term mortality in COVID-19 patients. METHODS: A prospective, observational study enrolling COVID-19 patients from August to October 2020. A blood sample for laboratory test analysis was drawn on arrival in the emergency department. The primary endpoint was 90-day mortality. The area under the curve (AUC) and Cox regression analyses were used to assess discriminatory ability and association with the endpoint. RESULTS: A total of 359 patients were enrolled, and the 90-day mortality rate was 8.9%. ROC AUC for MR-proADM predicting 90-day mortality was 0.832. An optimal cutoff of 0.80 nmol/L showed a sensitivity of 96.9% and a specificity of 58.4%, with a negative predictive value of 99.5%. Circulating MR-proADM levels (inverse transformed), after adjusting by a propensity score including eleven potential confounders, were an independent predictor of 90-day mortality (HR: 0.162 [95% CI: 0.043-0.480]) CONCLUSIONS: Our data confirm that MR-proADM has a role in the mid-term prognosis of COVID-19 patients and might assist physicians with risk stratification.

Identification of COVID-19 patients at risk of hospital admission and mortality: a European multicentre retrospective analysis of mid-regional pro-adrenomedullin.

BACKGROUND: Mid-Regional pro-Adrenomedullin (MR-proADM) is an inflammatory biomarker that improves the prognostic assessment of patients with sepsis, septic shock and organ failure. Previous studies of MR-proADM have primarily focussed on bacterial infections. A limited number of small and monocentric studies have examined MR-proADM as a prognostic factor in patients infected with SARS-CoV-2, however there is need for multicenter validation. An evaluation of its utility in predicting need for hospitalisation in viral infections was also performed. METHODS: An observational retrospective analysis of 1861 patients, with SARS-CoV-2 confirmed by RT-qPCR, from 10 hospitals across Europe was performed. Biomarkers, taken upon presentation to Emergency Departments (ED), clinical scores, patient demographics and outcomes were collected. Multiclass random forest classifier models were generated as well as calculation of area under the curve analysis. The primary endpoint was hospital admission with and without death. RESULTS: Patients suitable for safe discharge from Emergency Departments could be identified through an MR-proADM value of ≤ 1.02 nmol/L in combination with a CRP (C-Reactive Protein) of ≤ 20.2 mg/L and age ≤ 64, or in combination with a SOFA (Sequential Organ Failure Assessment) score < 2 if MR-proADM was ≤ 0.83 nmol/L regardless of age. Those at an increased risk of mortality could be identified upon presentation to secondary care with an MR-proADM value of > 0.85 nmol/L, in combination with a SOFA score ≥ 2 and LDH > 720 U/L, or in combination with a CRP > 29.26 mg/L and age ≤ 64, when MR-proADM was > 1.02 nmol/L. CONCLUSIONS: This international study suggests that for patients presenting to the ED with confirmed SARS-CoV-2 infection, MR-proADM in combination with age and CRP or with the patient's SOFA score could identify patients at low risk where outpatient treatment may be safe.

Circulating suPAR associates with severity and in-hospital progression of COVID-19.

BACKGROUND: COVID-19 disease progression is characterized by hyperinflammation and risk stratification may aid in early aggressive treatment and advanced planning. The aim of this study was to assess whether suPAR and other markers measured at hospital admission can predict the severity of COVID-19. METHODS: The primary outcome measure in this international, multi-centre, prospective, observational study with adult patients hospitalized primarily for COVID-19 was the association of WHO Clinical Progression Scale (WHO-CPS) with suPAR, ferritin, CRP, albumin, LDH, eGFR, age, procalcitonin, and interleukin-6. Admission plasma suPAR levels were determined using the suPARnostic® ELISA and suPARnostic® Turbilatex assays. RESULTS: Seven hundred and sixty-seven patients, 440 (57.4%) males and 327 (42.6%) females, were included with a median age of 64 years. Log-suPAR levels significantly correlated with WHO-CPS score, with each doubling of suPAR increasing the score by one point (p < .001). All the other markers were also correlated with WHO-CPS score. Admission suPAR levels were significantly lower in survivors (7.10 vs. 9.63, 95% CI 1.47-3.59, p < .001). A linear model (SALGA) including suPAR, serum albumin, serum lactate dehydrogenase, eGFR, and age can best estimate the WHO-CPS score and survival. Combining all five parameters in the SALGA model can improve the accuracy of discrimination with an AUC of 0.80 (95% CI: 0.759-0.836). CONCLUSIONS: suPAR levels significantly correlated with WHO-CPS score, with each doubling of suPAR increasing the score by one point. The SALGA model may serve as a quick tool for predicting disease severity and survival at admission.

Dabigatran in patients with atrial fibrillation after COVID-19 hospitalization: an update of the ANIBAL protocol.

COVID-19 increases the risk of atrial fibrillation (AF) and thrombotic complications, particularly in severe cases, leading to higher mortality rates. Anticoagulation is the cornerstone to reduce thromboembolic risk in patients with AF. Considering the risk of hepatotoxicity in patients with severe COVID-19 as well as the risk of drug-drug interactions, drug-induced hepatotoxicity and bleeding, the ANIBAL protocol was developed to facilitate the anticoagulation approach at discharge after COVID-19 hospitalization. However, since the publication of the original algorithm, relevant changes have occurred. First, treatment of COVID-19 pneumonia has been modified with the use of dexamethasone or remdesivir during the first week in patients that require oxygen therapy, and of dexamethasone and/or tocilizumab or baricitinib during the second week in patients that necessitate supplementary oxygen or with a high inflammation state, respectively. On the other hand, metabolic syndrome is common in patients with AF as well as metabolic-associated fatty liver disease, and this could negatively impact the prognosis of patients with COVID-19, including high transaminase levels in patients treated with immunomodulators. The EHRA guidelines update also introduce some interesting changes in drug-drug interaction patterns with the reduction of the level of the interaction with dexamethasone, which is of paramount importance in this clinical context. Considering the new information, the protocol, named ANIBAL II, has been updated. In this new protocol, the anticoagulant of choice in patients with AF after COVID-19 hospitalization is provided according to three scenarios: with/without dexamethasone treatment at discharge and normal hepatic function, transaminases ≤2 times the upper limit of normal, or transaminases >2 times the upper limit of normal.

Circulating levels of calprotectin, a signature of neutrophil activation in prediction of severe respiratory failure in COVID-19 patients: a multicenter, prospective study (CalCov study).

OBJECTIVE: Severe COVID-19 is characterized by a dysregulated immune response in which neutrophils play a critical role. Calprotectin reflects neutrophil activation and is involved in the self-amplifying thrombo-inflammatory storm in severe COVID-19. We aimed to evaluate the role of calprotectin in early prediction of severity in COVID-19 patients. METHODS: This was a multicenter prospective observational study enrolling consecutive adult COVID-19 patients. On arrival to emergency department, blood samples were collected for laboratory tests, including serum calprotectin. The primary outcome was severe respiratory failure requiring invasive mechanical ventilation and the secondary outcome was need for Intensive Care Unit (ICU) admission. RESULTS: Study population included 395 patients, 57 (14.4%) required invasive mechanical ventilation and 100 (25.3%) were admitted to ICU. Median serum calprotectin levels were significantly higher in intubated (3.73 mg/L vs. 2.63 mg/L; p < 0.001) and ICU patients (3.48 mg/L vs. 2.60 mg/L; p = 0.001). Calprotectin showed a significant accuracy to predict the need for invasive mechanical ventilation (ROC AUC 0.723) and ICU admission (ROC AUC 0.650). In multivariate analysis, serum calprotectin was an independent predictor of invasive mechanical ventilation (OR 1.161) and ICU admission (OR 1.068). CONCLUSION: Serum calprotectin can be used as an early predictor of severity in COVID-19 patients.

The importance of being external. methodological insights for the external validation of machine learning models in medicine.

Background and Objective Medical machine learning (ML) models tend to perform better on data from the same cohort than on new data, often due to overfitting, or co-variate shifts. For these reasons, external validation (EV) is a necessary practice in the evaluation of medical ML. However, there is still a gap in the literature on how to interpret EV results and hence assess the robustness of ML models. METHODS: We fill this gap by proposing a meta-validation method, to assess the soundness of EV procedures. In doing so, we complement the usual way to assess EV by considering both dataset cardinality, and the similarity of the EV dataset with respect to the training set. We then investigate how the notions of cardinality and similarity can be used to inform on the reliability of a validation procedure, by integrating them into two summative data visualizations. RESULTS: We illustrate our methodology by applying it to the validation of a state-of-the-art COVID-19 diagnostic model on 8 EV sets, collected across 3 different continents. The model performance was moderately impacted by data similarity (Pearson ρ = 0.38, p< 0.001). In the EV, the validated model reported good AUC (average: 0.84), acceptable calibration (average: 0.17) and utility (average: 0.50). The validation datasets were adequate in terms of dataset cardinality and similarity, thus suggesting the soundness of the results. We also provide a qualitative guideline to evaluate the reliability of validation procedures, and we discuss the importance of proper external validation in light of the obtained results. CONCLUSIONS: In this paper, we propose a novel, lean methodology to: 1) study how the similarity between training and validation sets impacts the generalizability of a ML model; 2) assess the soundness of EV evaluations along three complementary performance dimensions: discrimination, utility and calibration; 3) draw conclusions on the robustness of the model under validation. We applied this methodology to a state-of-the-art model for the diagnosis of COVID-19 from routine blood tests, and showed how to interpret the results in light of the presented framework.

Harmonized D-dimer levels upon admission for prognosis of COVID-19 severity: Results from a Spanish multicenter registry (BIOCOVID-Spain study).

Coagulopathy is a key feature of COVID-19 and D-dimer has been reported as a predictor of severity. However, because D-dimer test results vary considerably among assays, resolving harmonization issues is fundamental to translate findings into clinical practice. In this retrospective multicenter study (BIOCOVID study), we aimed to analyze the value of harmonized D-dimer levels upon admission for the prediction of in-hospital mortality in COVID-19 patients. All-cause in-hospital mortality was defined as endpoint. For harmonization of D-dimer levels, we designed a model based on the transformation of method-specific regression lines to a reference regression line. The ability of D-dimer for prediction of death was explored by receiver operating characteristic curves analysis and the association with the endpoint by Cox regression analysis. Study population included 2663 patients. In-hospital mortality rate was 14.3%. Harmonized D-dimer upon admission yielded an area under the curve of 0.66, with an optimal cut-off value of 0.945 mg/L FEU. Patients with harmonized D-dimer ≥ 0.945 mg/L FEU had a higher mortality rate (22.4% vs. 9.2%; p < 0.001). D-dimer was an independent predictor of in-hospital mortality, with an adjusted hazard ratio of 1.709. This is the first study in which a harmonization approach was performed to assure comparability of D-dimer levels measured by different assays. Elevated D-dimer levels upon admission were associated with a greater risk of in-hospital mortality among COVID-19 patients, but had limited performance as prognostic test.

Urine biomarkers for the prediction of mortality in COVID-19 hospitalized patients.

Risk factors associated with severity and mortality attributable to COVID-19 have been reported in different cohorts, highlighting the occurrence of acute kidney injury (AKI) in 25% of them. Among other, SARS-CoV-2 targets renal tubular cells and can cause acute renal damage. The aim of the present study was to evaluate the usefulness of urinary parameters in predicting intensive care unit (ICU) admission, mortality and development of AKI in hospitalized patients with COVID-19. Retrospective observational study, in a tertiary care hospital, between March 1st and April 19th, 2020. We recruited adult patients admitted consecutively and positive for SARS-CoV-2. Urinary and serum biomarkers were correlated with clinical outcomes (AKI, ICU admission, hospital discharge and in-hospital mortality) and evaluated using a logistic regression model and ROC curves. A total of 199 COVID-19 hospitalized patients were included. In AKI, the logistic regression model with a highest area under the curve (AUC) was reached by the combination of urine blood and previous chronic kidney disease, with an AUC of 0.676 (95%CI 0.512-0.840; p = 0.023); urine specific weight, sodium and albumin in serum, with an AUC of 0.837 (95% CI 0.766-0.909; p < 0.001) for ICU admission; and age, urine blood and lactate dehydrogenase levels in serum, with an AUC of 0.923 (95%CI 0.866-0.979; p < 0.001) for mortality prediction. For hospitalized patients with COVID-19, renal involvement and early alterations of urinary and serum parameters are useful as prognostic factors of AKI, the need for ICU admission and death.

Cardiac troponin and COVID-19 severity: Results from BIOCOVID study.

BACKGROUND: Myocardial injury is a common finding in COVID-19 strongly associated with severity. We analysed the prevalence and prognostic utility of myocardial injury, characterized by elevated cardiac troponin, in a large population of COVID-19 patients, and further evaluated separately the role of troponin T and I. METHODS: This is a multicentre, retrospective observational study enrolling patients with laboratory-confirmed COVID-19 who were hospitalized in 32 Spanish hospitals. Elevated troponin levels were defined as values above the sex-specific 99th percentile upper reference limit, as recommended by international guidelines. Thirty-day mortality was defined as endpoint. RESULTS: A total of 1280 COVID-19 patients were included in this study, of whom 187 (14.6%) died during the hospitalization. Using a nonspecific sex cut-off, elevated troponin levels were found in 344 patients (26.9%), increasing to 384 (30.0%) when a sex-specific cut-off was used. This prevalence was significantly higher (42.9% vs 21.9%; P < .001) in patients in whom troponin T was measured in comparison with troponin I. Sex-specific elevated troponin levels were significantly associated with 30-day mortality, with adjusted odds ratios (ORs) of 3.00 for total population, 3.20 for cardiac troponin T and 3.69 for cardiac troponin I. CONCLUSION: In this multicentre study, myocardial injury was a common finding in COVID-19 patients. Its prevalence increased when a sex-specific cut-off and cardiac troponin T were used. Elevated troponin was an independent predictor of 30-day mortality, irrespective of cardiac troponin assay and cut-offs to detect myocardial injury. Hence, the early measurement of cardiac troponin may be useful for risk stratification in COVID-19.

Characteristics and laboratory findings on admission to the emergency department among 2873 hospitalized patients with COVID-19: the impact of adjusted laboratory tests in multicenter studies. A multicenter study in Spain (BIOCOVID-Spain study).

Identification of predictors for severe disease progression is key for risk stratification in COVID-19 patients. We aimed to describe the main characteristics and identify the early predictors for severe outcomes among hospitalized patients with COVID-19 in Spain. This was an observational, retrospective cohort study (BIOCOVID-Spain study) including COVID-19 patients admitted to 32 Spanish hospitals. Demographics, comorbidities and laboratory tests were collected. Outcome was in-hospital mortality. For analysis, laboratory tests values were previously adjusted to assure the comparability of results among participants. Cox regression was performed to identify predictors. Study population included 2873 hospitalized COVID-19 patients. Nine variables were independent predictors for in-hospital mortality, including creatinine (Hazard ratio [HR]:1.327; 95% Confidence Interval [CI]: 1.040-1.695, p = .023), troponin (HR: 2.150; 95% CI: 1.155-4.001; p = .016), platelet count (HR: 0.994; 95% CI: 0.989-0.998; p = .004) and C-reactive protein (HR: 1.037; 95% CI: 1.006-1.068; p = .019). This is the first multicenter study in which an effort was carried out to adjust the results of laboratory tests measured with different methodologies to guarantee their comparability. We reported a comprehensive information about characteristics in a large cohort of hospitalized COVID-19 patients, focusing on the analytical features. Our findings may help to identify patients early at a higher risk for an adverse outcome.

MR-proADM as marker of endotheliitis predicts COVID-19 severity.

BACKGROUND: Early identification of patients at high risk of progression to severe COVID-19 constituted an unsolved challenge. Although growing evidence demonstrates a direct association between endotheliitis and severe COVID-19, the role of endothelial damage biomarkers has been scarcely studied. We investigated the relationship between circulating mid-regional proadrenomedullin (MR-proADM) levels, a biomarker of endothelial dysfunction, and prognosis of SARS-CoV-2-infected patients. METHODS: Prospective observational study enrolling adult patients with confirmed COVID-19. On admission to emergency department, a blood sample was drawn for laboratory test analysis. Primary and secondary endpoints were 28-day all-cause mortality and severe COVID-19 progression. Area under the curve (AUC) and multivariate regression analysis were employed to assess the association of the biomarker with the established endpoints. RESULTS: A total of 99 patients were enrolled. During hospitalization, 25 (25.3%) cases progressed to severe disease and the 28-day mortality rate was of 14.1%. MR-proADM showed the highest AUC to predict 28-day mortality (0.905; [CI] 95%: 0.829-0.955; P < .001) and progression to severe disease (0.829; [CI] 95%: 0.740-0.897; P < .001), respectively. MR-proADM plasma levels above optimal cut-off (1.01 nmol/L) showed the strongest independent association with 28-day mortality risk (hazard ratio [HR]: 10.470, 95% CI: 2.066-53.049; P < .005) and with progression to severe disease (HR: 6.803, 95% CI: 1.458-31.750; P = .015). CONCLUSION: Mid-regional proadrenomedullin was the biomarker with highest performance for prognosis of death and progression to severe disease in COVID-19 patients and represents a promising predictor for both outcomes, which might constitute a potential tool in the assessment of prognosis in early stages of this disease.

Dabigatran, the oral anticoagulant of choice at discharge in patients with non-valvular atrial fibrillation and COVID-19 infection: the ANIBAL protocol.

Atrial fibrillation is a frequent complication among patients with severe coronavirus disease-2019 (COVID-19) infection. Both direct and indirect mechanisms through COVID-19 have been described to explain this relationship. COVID-19 infection increases the risk of developing both arterial and venous thrombotic complications through systemic coagulation activation, leading to increased mortality. Chronic oral anticoagulation is essential to reduce the thromboembolic risk among AF patients. Switching to low-molecular-weight heparin has been recommended during hospitalization for COVID-19 infection. Of note, at discharge, the prescription of direct oral anticoagulants may offer some advantages over vitamin K antagonists. However, oral anticoagulants should only be prescribed after the consideration of drug-drug interactions with antiviral therapies as well as of the risk of hepatotoxicity, which is common among individuals with severe COVID-19 pneumonia. Not all anticoagulants have the same risk of hepatotoxicity; dabigatran has shown a good efficacy and safety profile and could have a lower risk of hepatotoxicity. Furthermore, its metabolism by cytochrome P450 is absent and it has a specific reversal agent. Therefore, dabigatran may be considered as a first-line choice for oral anticoagulation at discharge after COVID-19 infection. In this review, the available information on the antithrombotic management of AF patients at discharge after COVID-19 infection is updated. In addition, a practical algorithm, considering renal and liver function, which facilitates the anticoagulation choice at discharge is presented.