ABSTRACT
Rationale: Deficiencies exist in the communication of prognosis for patients requiring prolonged mechanical ventilation (PMV) from COVID-19 pneumonia, in part because of clinician uncertainty about the natural history of disease and observational cohort studies with variable outcomes. In order to address this gap for PMV patients, we developed a modified clinical prediction model based on the ProVent-14 model to predict in-hospital mortality for patients receiving at least 14 days of mechanical ventilation for acute respiratory distress syndrome (ARDS) from COVID-19. Methods: We evaluated 107 patients with COVID-19 requiring PMV (at least 14 days of mechanical ventilation (MV)) at 2 tertiary care medical centers in the US in a retrospective observational cohort study. On day 14 of MV, we collected data for the original ProVent-14 variables (age, platelet count, requirement for vasopressors, non-trauma admission, and dialysis requirement). We also collected data for 2 other potential predictor variables (extra-corporeal membrane oxygenation (ECMO) on day 14 and neutrophil to lymphocyte ratio). Model Development: Logistic regression models were used to evaluate the performance of the ProVent-14 variables with the outcome inhospital mortality. We then assessed successive models adding variable combinations including requirement of ECMO and neutrophil to lymphocyte ratio on day 14 to predict inhospital mortality. We assessed discrimination of the models by measuring the area under the receiver operating characteristic curve (AUC). We assessed calibration by the Hosmer-Lemeshow goodness of fit statistic. Results: The AUC for the model using original Provent-14 variables was 0.78 (trauma omitted for N=1). The most parsimonious model using the additional variables includes risk factors age 50-64 and ≥65;platelet count <100, and requirement for vasopressors, renal replacement or ECMO on day 14 of MV. The area under the curve for this model is 0.83. Calibration for the modified parsimonious model is provided in the table below (Goodness-of-fit statistic p=0.80). Dichotomized neutrophil to lymphocyte ratio on day 14 (N:L>15) improves the model slightly AUC=0.83, Goodness-of-fit p=0.61, though this variable was available for only 60% of the cohort. Conclusion: A modified clinical prediction model based on the previously validated ProVent-14 model is a simple method to accurately identify patients with ARDS from COVID-19 requiring PMV who are at high risk of in-hospital mortality. Further validation of model performance in a larger population and including long-term survival is warranted.
ABSTRACT
INTRODUCTION: Severe acute respiratory failure is a common complication of COVID-19, with refractory hypoxemia being a hallmark finding in severe illness and a common cause of mortality. With limited therapeutic strategies, management centers on good supportive care. Prone positioning has been shown to improve oxygenation and survival in patients with moderate-to-severe acute respiratory distress syndrome (ARDS) but the impact of prone positioning in COVID-19 with severe hypoxemia is unknown. This study aims to examine the response to proning as a predictor of COVID-19 related mortality. METHODS: This is a single-center, retrospective analysis of critically ill patients with COVID-19 confirmed by PCR. Patients were included if they were invasively ventilated, and if supportive care included prone positioning for management of refractory hypoxemia. Data points collected include demographics, ventilator settings, rates of mortality and progression to ECMO, ventilator-days, and time between symptom onset and intubation, hospital and ICU admission. Endpoints included response in oxygenation (PaO2:FiO2) and mortality. RESULTS: Forty-nine patients were included in the analysis. The average age was 56.9, and 61% of the patients were male. Patients had an average of 19 ventilator-days (2-52), 21 ICU-days (4-54), 26 hospital-days (8-65), an ECMO rate of 27%, and a mortality rate of 55%. Of the 22 survivors, there was an average increase in PaO2:FiO2 by 108, 93.1, and 93 for each of the first three pronations respectively. For the 27 nonsurvivors, there was an average increase in PaO2:FiO2 by 76.1, 84.3, and 50.9 for the first three pronations. The difference in improvement in PaO2:FiO2 was not statistically significant between survivors and non-survivors. There was no inflection point that could be determined that provided a high sensitivity and specificity to predict mortality or need for ECMO based on response to pronation at any of the time points. CONCLUSIONS: Proning improves PaO2:FiO2 in patients with severe hypoxemia related to COVID-19. Survivors in our study had a numerically greater response to proning, but this finding was not statistically significant. The clinical significance remains unclear. Larger studies assessing the efficacy of proning in critically ill patients with COVID-19 are needed.