RESUMEN
Background: The COVID-19 pandemic continues to overwhelm intensive care units (ICUs) worldwide, and improved prediction of mortality among COVID-19 patients could assist decision making in the ICU setting. In this work, we report on the development and validation of a dynamic mortality model specifically for critically ill COVID-19 patients and discuss its potential utility in the ICU. Methods: We collected electronic medical record (EMR) data from 3222 ICU admissions with a COVID-19 infection from 25 different ICUs in the Netherlands. We extracted daily observations of each patient and fitted both a linear (logistic regression) and non-linear (random forest) model to predict mortality within 24 h from the moment of prediction. Isotonic regression was used to re-calibrate the predictions of the fitted models. We evaluated the models in a leave-one-ICU-out (LOIO) cross-validation procedure. Results: The logistic regression and random forest model yielded an area under the receiver operating characteristic curve of 0.87 [0.85; 0.88] and 0.86 [0.84; 0.88], respectively. The recalibrated model predictions showed a calibration intercept of -0.04 [-0.12; 0.04] and slope of 0.90 [0.85; 0.95] for logistic regression model and a calibration intercept of -0.19 [-0.27; -0.10] and slope of 0.89 [0.84; 0.94] for the random forest model. Discussion: We presented a model for dynamic mortality prediction, specifically for critically ill COVID-19 patients, which predicts near-term mortality rather than in-ICU mortality. The potential clinical utility of dynamic mortality models such as benchmarking, improving resource allocation and informing family members, as well as the development of models with more causal structure, should be topics for future research.
RESUMEN
High-dose methotrexate (MTX) induced acute kidney injury can lead to sustained high systemic MTX levels and severe toxicity. A 39-year-old man with lymphoblastic T-cell lymphoma was admitted to our intensive care unit with elevated serum creatinine and prolonged high serum MTX levels. Standard supportive care was complemented by the addition of a relatively novel agent, glucarpidase, which rapidly lowered the extracellular levels of MTX. Several case series support this effect of glucarpidase, but no randomised controlled trial has been performed to show this leads to better outcome. Furthermore, glucarpidase might negatively affect leucovorin rescue therapy. Lastly, glucarpidase carries a significant financial burden. Based on the current evidence we cannot recommend glucarpidase until further research elucidates its role in the treatment of MTX toxicity. There is no randomised clinical evidence to support its use in severe cases and theoretical evidence suggests that after prolonged exposure to high MTX levels glucarpidase administration is unable to reverse high intracellular MTX. We recommend that new randomised controlled studies be aimed at early administration of glucarpidase in patients with high MTX levels shortly after administration to prevent direct toxic effects of MTX on kidney function and further uptake into cells.