Impact of adrenomedullin levels on clinical risk stratification and outcome in subarachnoid haemorrhage.

PURPOSE: To use classification tree analysis to identify risk factors for nonsurvival in a neurological patients with subarachnoid haemorrhage (SAH) and to propose a clinical model for predicting of mortality. METHODS: Prospective study of SAH admitted to a Critical Care Department and Stroke Unit over a 2-year period. Middle region of pro-ADM plasma levels (MR-proADM) was measured in EDTA plasma within the first 24 hours of hospital admission using the automatic immunofluorescence test. A regression tree was made to identify prognostic models for the development of mortality at 90 days. RESULTS: Ninety patients were included. The mean MR-proADM plasma value in the samples analysed was 0.78 ± 0.41 nmol/L. MR-proADM plasma levels were significantly associated with mortality at 90 days (1.05 ± 0.51 nmol/L vs 0.64 ± 0.25 nmol/L; P < .001). Regression tree analysis provided an algorithm based on the combined use of clinical variables and one biomarker allowing accurate mortality discrimination of three distinct subgroups with high risk of 90-day mortality ranged from 75% to 100% (AUC 0.9; 95% CI 0.83-0.98). CONCLUSIONS: The study established a model (APACHE II, MR-proADM and Hunt&Hess) to predict fatal outcomes in patients with SAH. The proposed decision-making algorithm may help identify patients with a high risk of mortality.

Early Tracheostomy for Managing ICU Capacity During the COVID-19 Outbreak: A Propensity-Matched Cohort Study.

BACKGROUND: During the first wave of the COVID-19 pandemic, shortages of ventilators and ICU beds overwhelmed health care systems. Whether early tracheostomy reduces the duration of mechanical ventilation and ICU stay is controversial. RESEARCH QUESTION: Can failure-free day outcomes focused on ICU resources help to decide the optimal timing of tracheostomy in overburdened health care systems during viral epidemics? STUDY DESIGN AND METHODS: This retrospective cohort study included consecutive patients with COVID-19 pneumonia who had undergone tracheostomy in 15 Spanish ICUs during the surge, when ICU occupancy modified clinician criteria to perform tracheostomy in Patients with COVID-19. We compared ventilator-free days at 28 and 60 days and ICU- and hospital bed-free days at 28 and 60 days in propensity score-matched cohorts who underwent tracheostomy at different timings (≤ 7 days, 8-10 days, and 11-14 days after intubation). RESULTS: Of 1,939 patients admitted with COVID-19 pneumonia, 682 (35.2%) underwent tracheostomy, 382 (56%) within 14 days. Earlier tracheostomy was associated with more ventilator-free days at 28 days (≤ 7 days vs > 7 days [116 patients included in the analysis]: median, 9 days [interquartile range (IQR), 0-15 days] vs 3 days [IQR, 0-7 days]; difference between groups, 4.5 days; 95% CI, 2.3-6.7 days; 8-10 days vs > 10 days [222 patients analyzed]: 6 days [IQR, 0-10 days] vs 0 days [IQR, 0-6 days]; difference, 3.1 days; 95% CI, 1.7-4.5 days; 11-14 days vs > 14 days [318 patients analyzed]: 4 days [IQR, 0-9 days] vs 0 days [IQR, 0-2 days]; difference, 3 days; 95% CI, 2.1-3.9 days). Except hospital bed-free days at 28 days, all other end points were better with early tracheostomy. INTERPRETATION: Optimal timing of tracheostomy may improve patient outcomes and may alleviate ICU capacity strain during the COVID-19 pandemic without increasing mortality. Tracheostomy within the first work on a ventilator in particular may improve ICU availability.