1542. MR-proADM Biomarker Predicts COVID-19 Clinical Outcomes: a US-based Cohort Study
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ABSTRACT: Background
Mid-regional proadrenomedullin (MR-proADM) is a biomarker released following endothelial damage. Our study aimed to investigate baseline MR-proADM as a predictor of a wider range of clinical outcomes of varying severity in patients admitted with COVID-19 from a US-based multicenter trial. Outcomes Within 28 days Stratified by Binary MR-proADM (Cutoff 0.87 Nmol/L), Number of Events (percentage)
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PROVIDER: S-EPMC9751617 | biostudies-literature | 2022 Dec
REPOSITORIES: biostudies-literature
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Project description:BackgroundSerum mid-regional proadrenomedullin (MR-proADM) has emerged as a marker of organ failure (mainly lungs and kidneys) and poor prognosis in patients admitted to intensive care (IC); some reports also suggest it and other markers, such as Krebs von den Lungen-6 (KL-6) and interleukin-6 (IL-6), as a prognostic biomarker of COVID-19. The aim of the study was to evaluate the performance MR-proADM in hospitalized COVID-19 patients for predicting in-hospital mortality and need for non-invasive or invasive respiratory support.MethodsWe enrolled 74 patients hospitalized in the COVID Unit of Siena Hospital from March to May 2020, for whom serum samples were available on admission for assay of MR-proADM, KL-6 and IL-6. Demographic data, comorbidities, medical history and clinical laboratory data on days 1-3 of admission and Simplified Acute Physiology Score and Simplified Organ Failure Assessment scores calculated at day 1 were collected retrospectively, as well as mortality and IC admission data.Results12 patients died in hospital (16%) and 14 patients were admitted to IC (19%). Serum concentrations of MR-proADM on admission and on day 1 were higher among non-survivors than among survivors (p = 0.015 and p = 0.045, respectively), while those on day 3 were not significantly different. Patients needing respiratory support had higher MR-proADM concentrations on admission than the others (p = 0.046), and those requiring invasive mechanical ventilation had higher MR-proADM on day 1 (p = 0.017). Serum concentrations of KL-6 and IL-6 were significantly higher in non-survivors (p = 0.03 and p = 0.004, respectively). ROC curve analysis showed that serum MR-proADM on day 1 had the best accuracy in predicting death and/or IC admission (AUC = 0.9583, p = 0.0006); the combination of all three biomarkers further improved the accuracy of prediction of death or IC admission (AUC = 0.9793; p = 0.00004).ConclusionsOur data sustain the potential of serum MR-proADM as a reliable prognostic biomarker of hospitalized COVID-19 patients and confirms the utility of the three markers in the management and risk stratification of hospitalized patients. The markers are collected mini-invasively and are quick to analyze and cost-effective.
| S-EPMC10296224 | biostudies-literature
Project description:BackgroundMid-regional proadrenomedullin (MR-proADM) is a biomarker released following endothelial damage. Studies have shown a correlation in predicting coronavirus disease 2019 (COVID-19) outcomes with MR-proADM levels. Our study aimed to investigate baseline MR-proADM as a predictor of a wider range of clinical outcomes of varying severity in patients admitted with COVID-19, and to compare to other biomarkers.MethodsData from the Boston Area COVID-19 Consortium (BACC) Bay Tocilizumab Trial was used in this study. Patients with biomarker determinations, and not admitted to the intensive care unit (ICU) on admission, were included. MR-proADM cutoff of 0.87 nmol/L was assessed in predicting clinical outcomes.ResultsOf 182 patients, 11.0% were mechanically ventilated or dead within 28 days. Of patients with MR-proADM >0.87 nmol/L, 21.1% were mechanically ventilated or dead within 28 days, compared with 4.5% of those with MR-proADM ≤0.87 nmol/L (P < .001). The sensitivity, specificity, negative predictive value, and positive predictive value of MR-proADM cutoff of 0.87 nmol/L in predicting mechanical ventilation or death were 75%, 65%, 95%, and 21%, respectively, with an area under the receiver operating characteristic curve of 0.76. On multivariable logistic regression analysis, MR-proADM >0.87 nmol/L was independently associated with mechanical ventilation or death, ICU admission, prolonged hospitalization beyond day 4, and day 4 COVID-19 ordinal scale equal to or worse than day 1.ConclusionsMR-proADM functions as a valuable biomarker for the early risk stratification and detection of severe disease progression of patients with COVID-19. In the prediction of death, MR-proADM performed better compared to many other commonly used biomarkers.
| S-EPMC9439577 | biostudies-literature
Project description: Not available
| S-BSST1135 | biostudies-other
Project description: Not available
| S-BSST563 | biostudies-other
Project description:PurposeInformation regarding the use of lung ultrasound (LUS) in patients with Coronavirus disease 2019 (COVID-19) is quickly accumulating, but its use for risk stratification and outcome prediction has yet to be described. We performed the first systematic and comprehensive LUS evaluation of consecutive patients hospitalized with COVID-19 infection, in order to describe LUS findings and their association with clinical course and outcome.MethodsBetween 21/03/2020 and 04/05/2020, 120 consecutive patients admitted to the Tel Aviv Medical Center due to COVID-19, underwent complete LUS within 24 h of admission. A second exam was performed in case of clinical deterioration. LUS score of 0 (best)-36 (worst) was assigned to each patient. LUS findings were compared with clinical data.ResultsThe median baseline total LUS score was 15, IQR [7-20]. Baseline LUS score was 0-18 in 80 (67%) patients, and 19-36 in 40 (33%) patients. The majority had patchy pleural thickening (n = 100; 83%), or patchy subpleural consolidations (n = 93; 78%) in at least one zone. The prevalence of pleural thickening, subpleural consolidations and the total LUS score were all correlated with severity of illness on admission. Clinical deterioration was associated with increased follow-up LUS scores (p = 0.0009), mostly due to loss of aeration in anterior lung segments. The optimal cutoff point for LUS score was 18 (sensitivity = 62%, specificity = 74%). Both mortality and need for invasive mechanical ventilation were increased with baseline LUS score > 18 compared to baseline LUS score 0-18. Unadjusted hazard ratio of death for LUS score was 1.08 per point [1.02-1.16], p = 0.008; Unadjusted hazard ratio of the composite endpoint (death or need for invasive mechanical ventilation) for LUS score was 1.12 per point [1.05-1.2], p = 0.0008.ConclusionHospitalized patients with COVID-19, at all clinical grades, present with pathological LUS findings. Baseline LUS score strongly correlates with the eventual need for invasive mechanical ventilation and is a strong predictor of mortality. Routine use of LUS may guide patients' management strategies, as well as resource allocation in case of surge capacity.
| S-EPMC7454549 | biostudies-literature
Project description:We perform shotgun transcriptome sequencing of human RNA obtained from nasopharyngeal swabs of patients with COVID-19, and identify a molecular signature associated with disease severity
2020-12-19 | GSE162835 | GEO
Project description:BackgroundMid-regional pro-adrenomedullin (MR-proADM) is useful for risk stratification in patients with sepsis and respiratory infections. The study's purpose was to assess the available data and determine the association between MR-proADM levels and mortality in COVID-19 participants.MethodsA comprehensive literature search of medical electronic databases was performed including PubMed, Web of Science, Scopus, Cochrane, and grey literature for relevant data published from 1 January 2020, to 20 November 2022. Mean differences (MD) with 95% confidence intervals (CI) were calculated.ResultsFourteen studies reported MR-proADM levels in survivors vs. non-survivors of COVID-19 patients. Pooled analysis showed that MR-proADM level in the survivor group was 0.841 ± 0.295 nmol/L for patients who survive COVID-19, compared to 1.692 ± 0.761 nmol/L for non-survivors (MD = -0.78; 95%CI: -0.92 to -0.64; p < 0.001).ConclusionsThe main finding of this study is that mortality of COVID-19 is linked to MR-proADM levels, according to this meta-analysis. The use of MR-proADM might be extremely beneficial in triaging, assessing probable therapy escalation, predicting potential complications during therapy or significant clinical deterioration of patients, and avoiding admission which may not be necessary. Nevertheless, in order to confirm the obtained data, it is necessary to conduct large prospective studies that will address the potential diagnostic role of MR-proADM as a marker of COVID-19 severity.KEY MESSAGESSeverity of COVID-19 seems to be linked to MR-proADM levels and can be used as a potential marker for predicting a patient's clinical course.The use of MR-proADM might be beneficial in triaging, assessing probable therapy escalation, predicting potential complications during therapy or significant clinical deterioration of patients, and avoiding admission which may not be necessary.For patients with COVID-19, MR-proADM may be an excellent prognostic indicator because it is a marker of endothelial function that may predict the precise impact on the equilibrium between vascular relaxation and contraction and lowers platelet aggregation inhibitors, coagulation inhibitors, and fibrinolysis activators in favor of clotting factors.
| S-EPMC9828692 | biostudies-literature
Project description:ObjectiveTo develop a vocal biomarker for fatigue monitoring in people with COVID-19.DesignProspective cohort study.SettingPredi-COVID data between May 2020 and May 2021.ParticipantsA total of 1772 voice recordings were used to train an AI-based algorithm to predict fatigue, stratified by gender and smartphone's operating system (Android/iOS). The recordings were collected from 296 participants tracked for 2 weeks following SARS-CoV-2 infection.Primary and secondary outcome measuresFour machine learning algorithms (logistic regression, k-nearest neighbours, support vector machine and soft voting classifier) were used to train and derive the fatigue vocal biomarker. The models were evaluated based on the following metrics: area under the curve (AUC), accuracy, F1-score, precision and recall. The Brier score was also used to evaluate the models' calibrations.ResultsThe final study population included 56% of women and had a mean (±SD) age of 40 (±13) years. Women were more likely to report fatigue (p<0.001). We developed four models for Android female, Android male, iOS female and iOS male users with a weighted AUC of 86%, 82%, 79%, 85% and a mean Brier Score of 0.15, 0.12, 0.17, 0.12, respectively. The vocal biomarker derived from the prediction models successfully discriminated COVID-19 participants with and without fatigue.ConclusionsThis study demonstrates the feasibility of identifying and remotely monitoring fatigue thanks to voice. Vocal biomarkers, digitally integrated into telemedicine technologies, are expected to improve the monitoring of people with COVID-19 or Long-COVID.Trial registration numberNCT04380987.
| S-EPMC9684280 | biostudies-literature
Project description:ObjectivesPoint-of-care ultrasound (POCUS) detects the pulmonary manifestations of COVID-19 and may predict patient outcomes.MethodsWe conducted a prospective cohort study at four hospitals from March 2020 to January 2021 to evaluate lung POCUS and clinical outcomes of COVID-19. Inclusion criteria included adult patients hospitalized for COVID-19 who received lung POCUS with a 12-zone protocol. Each image was interpreted by two reviewers blinded to clinical outcomes. Our primary outcome was the need for intensive care unit (ICU) admission versus no ICU admission. Secondary outcomes included intubation and supplemental oxygen usage.ResultsN = 160 patients were included. Among critically ill patients, B-lines (94 vs 76%; P < .01) and consolidations (70 vs 46%; P < .01) were more common. For scans collected within 24 hours of admission (N = 101 patients), early B-lines (odds ratio [OR] 4.41 [95% confidence interval, CI: 1.71-14.30]; P < .01) or consolidations (OR 2.49 [95% CI: 1.35-4.86]; P < .01) were predictive of ICU admission. Early consolidations were associated with oxygen usage after discharge (OR 2.16 [95% CI: 1.01-4.70]; P = .047). Patients with a normal scan within 24 hours of admission were less likely to require ICU admission (OR 0.28 [95% CI: 0.09-0.75]; P < .01) or supplemental oxygen (OR 0.26 [95% CI: 0.11-0.61]; P < .01). Ultrasound findings did not dynamically change over a 28-day scanning window after symptom onset.ConclusionsLung POCUS findings detected within 24 hours of admission may provide expedient risk stratification for important COVID-19 clinical outcomes, including future ICU admission or need for supplemental oxygen. Conversely, a normal scan within 24 hours of admission appears protective. POCUS findings appeared stable over a 28-day scanning window, suggesting that these findings, regardless of their timing, may have clinical implications.
| S-EPMC8661628 | biostudies-literature
Project description:ObjectivesThromboinflammation, 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.MethodsA 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.ResultsA 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.
| S-EPMC8400460 | biostudies-literature