Mid-Regional Pro-Adrenomedullin, Methemoglobin and Carboxyhemoglobin as Prognosis Biomarkers in Critically Ill Patients with COVID-19: An Observational Prospective Study

Depto. de MedicinaFac. de MedicinaTRUEpu

Usefulness of midregional proadrenomedullin to predict poor outcome in patients with community acquired pneumonia.

midregional proadrenomedullin (MR-proADM) is a prognostic biomarker in patients with community-acquired pneumonia (CAP). We sought to confirm whether MR-proADM added to Pneumonia Severity Index (PSI) improves the potential prognostic value of PSI alone, and tested to what extent this combination could be useful in predicting poor outcome of patients with CAP in an Emergency Department (ED).Consecutive patients diagnosed with CAP were enrolled in this prospective, single-centre, observational study. We analyzed the ability of MR-proADM added to PSI to predict poor outcome using receiver operating characteristic (ROC) curves, logistic regression and risk reclassification and comparing it with the ability of PSI alone. The primary outcome was "poor outcome", defined as the incidence of an adverse event (ICU admission, hospital readmission, or mortality at 30 days after CAP diagnosis).226 patients were included; 33 patients (14.6%) reached primary outcome. To predict primary outcome the highest area under curve (AUC) was found for PSI (0.74 [0.64-0.85]), which was not significantly higher than for MR-proADM (AUC 0.72 [0.63-0.81, p > 0.05]). The combination of PSI and MR-proADM failed to improve the predictive potential of PSI alone (AUC 0.75 [0.65-0.85, p=0.56]). Ten patients were appropriately reclassified when the combined PSI and MR-proADM model was used as compared with the model of PSI alone. Net reclassification improvement (NRI) index was statistically significant (7.69%, p = 0.03) with an improvement percentage of 3.03% (p = 0.32) for adverse event, and 4.66% (P = 0.02) for no adverse event.MR-proADM in combination with PSI may be helpful in individual risk stratification for short-term poor outcome of CAP patients, allowing a better reclassification of patients compared with PSI alone

MR-proADM and CAP severity.

<p>Fig 2a. Relationship between MR-proADM and severity as established by the PSI. Analysis performed with the Jonckheere-Terpstra trend test. Tau b: Kendall’s rank correlation. p: level of statistical significance. Fig 2b. MR-proADM levels according to hospital admission, bacteremia, ICU admission, hospital readmission and 30-day mortality.</p

ROC curves for predicting adverse event.

<p>Fig 3a. ROC curves for different biomarkers and PSI. Fig 3b. ROC curves for the PSI & MR-proADM prediction model compared to PSI</p

Kaplan-Meier survival curves at 90-days mortality according to MR-proADM quartiles.

<p>Kaplan-Meier survival curves at 90-days mortality according to MR-proADM quartiles.</p

Multivariate predictive models of adverse event and 90-day mortality.

<p>MaxM: Maximum Model: includes significant independent variables in the univariate analysis with AUC higher than 0.7.</p><p>OR: Odds Ratio and HR: Hazard Ratio.</p><p>CI 95%: confidence interval of 95%.</p><p>p: level of statistical significance.</p><p>AIC: Akaike Information Criterion (better fit of the model when AIC lower).</p><p>McFadden´s and Atkinson R2: proportion of uncertainty data explained by the model.</p><p>Calibration χ2 (p value): Hosmer and Lemeshow test.</p><p>Multivariate predictive models of adverse event and 90-day mortality.</p

Baseline characteristics of the NACURG cohort.

<p>Differences between patients who died and those who survived were assessed by Cox regression survival analysis for independent continuous variables, and a Kaplan-Meyer survival curve with log-rank tests for independent categorical variables. Differences between patients with or without adverse event were assessed by the Student t test or the non-parametric Mann-Whitney U test for continuous variables and the [χ²] test or the Fisher exact test for dichotomous categorical variables.</p><p>*p: degree of statistical significance.</p><p>**Lactate levels only available for 122 patients (54%) and not therefore included in the multivariate analysis.</p><p>***The percentage of readmissions out of the total number of patients discharged (221; 4 patients died while in hospital and 1 was still inpatient at 30 days).</p><p>Relationship between different independent variables and adverse event and 90-day mortality after consulting the Emergency Department.</p

Patients included in the study.

<p>Patients included in the study.</p

ROC curves for predicting 90-day mortality.

<p>Fig 5a. ROC curves for different biomarkers and PSI. Fig 5b. ROC curves for the PSI & MR-proADM prediction model compared to PSI.</p

Study protocol for investigating the clinical performance of an automated blood test for glial fibrillary acidic protein and ubiquitin carboxy-terminal hydrolase L1 blood concentrations in elderly patients with mild traumatic BRAIN Injury and reference values (BRAINI-2 Elderly European study): a prospective multicentre observational study

International audienceIntroduction:Two blood brain-derived biomarkers, glial fibrillar acidic protein (GFAP) and ubiquitin carboxy-terminal hydrolase L1 (UCH-L1), can rule out intracranial lesions in patients with mild traumatic brain injury (mTBI) when assessed within the first 12 hours. Most elderly patients were excluded from previous studies due to comorbidities. Biomarker use in elderly population could be affected by increased basal levels. This study will assess the performance of an automated test for measuring serum GFAP and UCH-L1 in elderly patients to predict the absence of intracranial lesions on head CT scans after mTBI, and determine both biomarkers reference values in a non-TBI elderly population. Methods and analysis This is a prospective multicentre observational study on elderly patients (≥65 years) that will be performed in Spain, France and Germany. Two patient groups will be included in two independent substudies. (1) A cohort of 2370 elderly patients (1185<80 years and 1185≥80 years; BRAINI2-ELDERLY DIAGNOSTIC AND PROGNOSTIC STUDY) with mTBI and a brain CT scan that will undergo blood sampling within 12 hours after mTBI. The primary outcome measure is the diagnostic performance of GFAP and UCH-L1 measured using an automated assay for discriminating between patients with positive and negative findings on brain CT scans. Secondary outcome measures include the performance of both biomarkers in predicting early (1 week) and midterm (3 months) neurological status and quality of life after trauma. (2) A cohort of 480 elderly reference participants (BRAINI2-ELDERLY REFERENCE STUDY) in whom reference values for GFAP and UCHL1 will be determined. Ethics and dissemination Ethical approval was obtained from the Institutional Review Boards of Hospital 12 de Octubre in Spain (Re#22/027) and Southeast VI (Clermont Ferrand Hospital) (Re# 22.01782.000095) in France. The study’s results will be presented at scientific meetings and published in peer-review publications. Trial registration number NCT05425251