Structural causal model with expert augmented knowledge to estimate the effect of oxygen therapy on mortality in the ICU.

Recent advances in causal inference techniques, more specifically, in the theory of structural causal models, provide the framework for identifying causal effects from observational data in cases where the causal graph is identifiable, i.e., the data generation mechanism can be recovered from the joint distribution. However, no such studies have been performed to demonstrate this concept with a clinical example. We present a complete framework to estimate the causal effects from observational data by augmenting expert knowledge in the model development phase and with a practical clinical application. Our clinical application entails a timely and essential research question, the effect of oxygen therapy intervention in the intensive care unit (ICU). The result of this project is helpful in a variety of disease conditions, including severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) patients in the ICU. We used data from the MIMIC-III database, a widely used health care database in the machine learning community with 58,976 admissions from an ICU in Boston, MA, to estimate the oxygen therapy effect on morality. We also identified the model's covariate-specific effect on oxygen therapy for more personalized intervention.

ZINC USE IS ASSOCIATED WITH IMPROVED OUTCOMES IN COVID-19: RESULTS FROM THE CRUSH-COVID REGISTRY

B Introduction: b Previous work has shown correlations of zinc deficiency and poor outcomes in COVID-19 patients.i Little is known, however, about the use of zinc supplementation and its potential benefits in hospitalized COVID-19 positive individuals. B Conclusions: b Zinc use may be associated with improved clinical outcomes in hospitalized COVID-19 patients. [Extracted from the article] Copyright of Critical Care Medicine is the property of Lippincott Williams & Wilkins and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

A PANDEMIC WITHIN AN EPIDEMIC: EVALUATION OF COVID-19 IN THE OBESE POPULATION

B Conclusion: b This supports the growing body of evidence that obesity has the potential to serve as an independent predictor for outcomes of COVID-19 patients. Evidence has shown increased morbidity and mortality among obese COVID-19 patients. Patients were stratified into healthy weight (BMI < 25), overweight (BMI 25 - 29.9), obese (BMI 30 -39.9), and morbidly obese (BMI > 40) categories. [Extracted from the article] Copyright of Critical Care Medicine is the property of Lippincott Williams & Wilkins and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Aspirin Use Is Associated With Decreased Mechanical Ventilation, Intensive Care Unit Admission, and In-Hospital Mortality in Hospitalized Patients With Coronavirus Disease 2019.

BACKGROUND: Coronavirus disease-2019 (COVID-19) is associated with hypercoagulability and increased thrombotic risk in critically ill patients. To our knowledge, no studies have evaluated whether aspirin use is associated with reduced risk of mechanical ventilation, intensive care unit (ICU) admission, and in-hospital mortality. METHODS: A retrospective, observational cohort study of adult patients admitted with COVID-19 to multiple hospitals in the United States between March 2020 and July 2020 was performed. The primary outcome was the need for mechanical ventilation. Secondary outcomes were ICU admission and in-hospital mortality. Adjusted hazard ratios (HRs) for study outcomes were calculated using Cox-proportional hazards models after adjustment for the effects of demographics and comorbid conditions. RESULTS: Four hundred twelve patients were included in the study. Three hundred fourteen patients (76.3%) did not receive aspirin, while 98 patients (23.7%) received aspirin within 24 hours of admission or 7 days before admission. Aspirin use had a crude association with less mechanical ventilation (35.7% aspirin versus 48.4% nonaspirin, P = .03) and ICU admission (38.8% aspirin versus 51.0% nonaspirin, P = .04), but no crude association with in-hospital mortality (26.5% aspirin versus 23.2% nonaspirin, P = .51). After adjusting for 8 confounding variables, aspirin use was independently associated with decreased risk of mechanical ventilation (adjusted HR, 0.56, 95% confidence interval [CI], 0.37-0.85, P = .007), ICU admission (adjusted HR, 0.57, 95% CI, 0.38-0.85, P = .005), and in-hospital mortality (adjusted HR, 0.53, 95% CI, 0.31-0.90, P = .02). There were no differences in major bleeding (P = .69) or overt thrombosis (P = .82) between aspirin users and nonaspirin users. CONCLUSIONS: Aspirin use may be associated with improved outcomes in hospitalized COVID-19 patients. However, a sufficiently powered randomized controlled trial is needed to assess whether a causal relationship exists between aspirin use and reduced lung injury and mortality in COVID-19 patients.

Predictors and outcomes of healthcare-associated infections in COVID-19 patients.

INTRODUCTION: Healthcare-associated infections (HAI) after viral illnesses are important sources of morbidity and mortality. This has not been extensively studied in hospitalized COVID-19 patients. METHODS: This study included all COVID-19-positive adult patients (≥18 years) hospitalized between 01 March and 05 August 2020 at the current institution. The Centers for Disease Control and Prevention definition of HAI in the acute care setting was used. The outcomes that were studied were rates and types of infections and in-hospital mortality. Several multivariable logistic regression models were constructed to examine characteristics associated with development of HAI. RESULTS: Fifty-nine (3.7%) of 1565 patients developed 140 separate HAIs from 73 different organisms: 23 were Gram-positive, 39 were Gram-negative and 11 were fungal. Patients who developed HAI did not have higher odds of death (OR 0.85, 95% CI 0.40-1.81, p = 0.69). HAIs were associated with the use of tocilizumab (OR 5.04, 95% CI 2.4-10.6, p < 0.001), steroids (OR 3.8, 95% CI 1.4-10, p = 0.007), hydroxychloroquine (OR 3.0, 95% CI 1.0-8.8, p = 0.05), and acute kidney injury requiring hemodialysis (OR 3.7, 95% CI 1.1-12.8, p = 0.04). CONCLUSIONS: HAI were common in hospitalized Covid-19 patients. Tocilizumab and steroids were associated with increased risk of HAIs.