No abstract

Summary.  Background: Fatal bleeding is a serious consequence of anticoagulant therapy, but factors associated with fatal bleeding during the first 3 months of treatment of venous thromboembolism (VTE) are uncertain. Methods: Using data from RIETE, an ongoing registry of consecutive patients with acute VTE, we assessed risk factors for fatal bleeding among all patients. We then used this information to derive a clinical model that would stratify a patient’s risk of fatal bleeding during the first 3 months of treatment. Results: Of 24 395 patients, 546 (2.24%) had a major bleed and 135 (0.55%) had a fatal bleed. The gastrointestinal tract was the most common site (40% of fatal bleeds), followed by intracranial bleeding (25%). Fatal bleeding was independently associated with the following factors at the time of VTE diagnosis: age >75 years (OR, 2.16), metastatic cancer (OR, 3.80), immobility ≥ 4 days (OR, 1.99), a major bleed within the past 30 days (OR, 2.64), an abnormal prothrombin time (OR, 2.09), a platelet count < 100 × 109 L−1 (OR, 2.23), creatinine clearance < 30 mL min−1 (OR, 2.27), anemia (OR, 1.54), and distal deep vein thrombosis (OR, 0.39). INR at the time of bleeding is not known. A clinical prediction rule for risk of fatal bleeding that included nine baseline factors was derived. Fatal bleeding occurred in 0.16% (95% CI, 0.11–0.23) of the low‐risk, 1.06% (95% CI, 0.85–1.30) of the moderate‐risk, and 4.24% (95% CI, 2.76–6.27) of the high‐risk category. Conclusions: Patient characteristics and laboratory variables can identify patients at high risk for fatal bleeding during treatment of VTE.

We hypothesized that neurally adjusted ventilatory assist (NAVA) compared to conventional lung-protective mechanical ventilation (MV) decreases duration of MV and mortality in patients with acute respiratory failure (ARF). Methods: We carried out a multicenter, randomized, controlled trial in patients with ARF from several etiologies. Intubated patients ventilated for ≤ 5 days expected to require MV for ≥ 72 h and able to breathe spontaneously were eligible for enrollment. Eligible patients were randomly assigned based on balanced treatment assignments with a computerized randomization allocation sequence to two ventilatory strategies: (1) lung-protective MV (control group), and (2) lung-protective MV with NAVA (NAVA group). Allocation concealment was maintained at all sites during the trial. Primary outcome was the number of ventilator-free days (VFDs) at 28 days. Secondary outcome was all-cause hospital mortality. All analyses were done according to the intention-to-treat principle. Results: Between March 2014 and October 2019, we enrolled 306 patients and randomly assigned 153 patients to the NAVA group and 153 to the control group. Median VFDs were higher in the NAVA than in the control group (22 vs. 18 days; between-group difference 4 days; 95% confidence interval [CI] 0 to 8 days; p = 0.016). At hospital discharge, 39 (25.5%) patients in the NAVA group and 47 (30.7%) patients in the control group had died (between-group difference − 5.2%, 95% CI − 15.2 to 4.8, p = 0.31). Other clinical, physiological or safety outcomes did not differ significantly between the trial groups. Conclusion: NAVA decreased duration of MV although it did not improve survival in ventilated patients with ARF.

A simple 9-point score based on the values of age, PaO2/FIO2 ratio, and plateau pressure calculated at 24 hours on protective ventilation after acute respiratory distress syndrome diagnosis could be used in real time for rating prognosis of acute respiratory distress syndrome patients with high probability.

The accuracy of the score in this validation cohort was similar to the accuracy found in the index study. Interestingly, it performed better for predicting gastrointestinal than intracranial fatal bleeding.

Most deaths in acute respiratory distress syndrome patients are not directly related to lung damage but to extrapulmonary multisystem organ failure. It would be challenging to prove that specific lung-directed therapies have an effect on overall survival.

OBJECTIVES: To develop a scoring model for stratifying patients with acute respiratory distress syndrome into risk categories (Stratification for identification of Prognostic categories In the acute RESpiratory distress syndrome score) for early prediction of death in the ICU, independent of the underlying disease and cause of death. DESIGN: A development and validation study using clinical data from four prospective, multicenter, observational cohorts. SETTING: A network of multidisciplinary ICUs. PATIENTS: One-thousand three-hundred one patients with moderate-to-severe acute respiratory distress syndrome managed with lung-protective ventilation. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The study followed Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis guidelines for prediction models. We performed logistic regression analysis, bootstrapping, and internal-external validation of prediction models with variables collected within 24 hours of acute respiratory distress syndrome diagnosis in 1,000 patients for model development. Primary outcome was ICU death. The Stratification for identification of Prognostic categories In the acute RESpiratory distress syndrome score was based on patient’s age, number of extrapulmonary organ failures, values of end-inspiratory plateau pressure, and ratio of Pao 2 to Fio 2 assessed at 24 hours of acute respiratory distress syndrome diagnosis. The pooled area under the receiver operating characteristic curve across internal-external validations was 0.860 (95% CI, 0.831–0.890). External validation in a new cohort of 301 acute respiratory distress syndrome patients confirmed the accuracy and robustness of the scoring model (area under the receiver operating characteristic curve = 0.870; 95% CI, 0.829–0.911). The Stratification for identification of Prognostic categories In the acute RESpiratory distress syndrome score stratified patients in three distinct prognostic classes and achieved better prediction of ICU death than ratio of Pao 2 to Fio 2 at acute respiratory distress syndrome onset or at 24 hours, Acute Physiology and Chronic Health Evaluation II score, or Sequential Organ Failure Assessment scale. CONCLUSIONS: The Stratification for identification of Prognostic categories In the acute RESpiratory distress syndrome score represents a novel strategy for early stratification of acute respiratory distress syndrome patients into prognostic categories and for selecting patients for therapeutic trials.

Sepsis is a common cause of acute respiratory distress syndrome (ARDS) associated with a high mortality. A panel of biomarkers (BMs) to identify septic patients at risk for developing ARDS, or at high risk of death, would be of interest for selecting patients for therapeutic trials, which could improve ARDS diagnosis and treatment, and survival chances in sepsis and ARDS. We measured nine protein BMs by ELISA in serum from 232 adult septic patients at diagnosis (152 required invasive mechanical ventilation and 72 had ARDS). A panel including the BMs RAGE, CXCL16 and Ang-2, plus PaO2/FiO2, was good in predicting ARDS (area under the curve = 0.88 in total septic patients). Best performing panels for ICU death are related to the presence of ARDS, need for invasive mechanical ventilation, and pulmonary/extrapulmonary origin of sepsis. In all cases, the use of BMs improved the prediction by clinical markers. Our study confirms the relevance of RAGE, Ang-2, IL-1RA and SP-D, and is novel supporting the inclusion of CXCL16, in BMs panels for predicting ARDS diagnosis and ARDS and sepsis outcome.