Use of Intravenous Albumin: A Guideline From the International Collaboration for Transfusion Medicine Guidelines.

BACKGROUND: Albumin is used commonly across a wide range of clinical settings to improve hemodynamics, to facilitate fluid removal, and to manage complications of cirrhosis. The International Collaboration for Transfusion Medicine Guidelines developed guidelines for the use of albumin in patients requiring critical care, undergoing cardiovascular surgery, undergoing kidney replacement therapy, or experiencing complications of cirrhosis. STUDY DESIGN AND METHODS: Cochairs oversaw the guideline development process and the panel included researchers, clinicians, methodologists, and a patient representative. The evidence informing this guideline arises from a systematic review of randomized clinical trials and systematic reviews, in which multiple databases were searched (inception through November 23, 2022). The panel reviewed the data and formulated the guideline recommendations using Grading of Recommendations Assessment, Development, and Evaluation methodology. The guidelines were revised after public consultation. RESULTS: The panel made 14 recommendations on albumin use in adult critical care (three recommendations), pediatric critical care (one recommendation), neonatal critical care (two recommendations), cardiovascular surgery (two recommendations), kidney replacement therapy (one recommendation), and complications of cirrhosis (five recommendations). Of the 14 recommendations, two recommendations had moderate certainty of evidence, five recommendations had low certainty of evidence, and seven recommendations had very low certainty of evidence. Two of the 14 recommendations suggested conditional use of albumin for patients with cirrhosis undergoing large-volume paracentesis or with spontaneous bacterial peritonitis. Twelve of 14 recommendations did not suggest albumin use in a wide variety of clinical situations where albumin commonly is transfused. INTERPRETATION: Currently, few evidence-based indications support the routine use of albumin in clinical practice to improve patient outcomes. These guidelines provide clinicians with actionable recommendations on the use of albumin.

Predictors for extubation failure in COVID-19 patients using a machine learning approach.

INTRODUCTION: Determining the optimal timing for extubation can be challenging in the intensive care. In this study, we aim to identify predictors for extubation failure in critically ill patients with COVID-19. METHODS: We used highly granular data from 3464 adult critically ill COVID patients in the multicenter Dutch Data Warehouse, including demographics, clinical observations, medications, fluid balance, laboratory values, vital signs, and data from life support devices. All intubated patients with at least one extubation attempt were eligible for analysis. Transferred patients, patients admitted for less than 24 h, and patients still admitted at the time of data extraction were excluded. Potential predictors were selected by a team of intensive care physicians. The primary and secondary outcomes were extubation without reintubation or death within the next 7 days and within 48 h, respectively. We trained and validated multiple machine learning algorithms using fivefold nested cross-validation. Predictor importance was estimated using Shapley additive explanations, while cutoff values for the relative probability of failed extubation were estimated through partial dependence plots. RESULTS: A total of 883 patients were included in the model derivation. The reintubation rate was 13.4% within 48 h and 18.9% at day 7, with a mortality rate of 0.6% and 1.0% respectively. The grandient-boost model performed best (area under the curve of 0.70) and was used to calculate predictor importance. Ventilatory characteristics and settings were the most important predictors. More specifically, a controlled mode duration longer than 4 days, a last fraction of inspired oxygen higher than 35%, a mean tidal volume per kg ideal body weight above 8 ml/kg in the day before extubation, and a shorter duration in assisted mode (< 2 days) compared to their median values. Additionally, a higher C-reactive protein and leukocyte count, a lower thrombocyte count, a lower Glasgow coma scale and a lower body mass index compared to their medians were associated with extubation failure. CONCLUSION: The most important predictors for extubation failure in critically ill COVID-19 patients include ventilatory settings, inflammatory parameters, neurological status, and body mass index. These predictors should therefore be routinely captured in electronic health records.