Background
Recent trials with dexamethasone and hydrocortisone have demonstrated benefit in patients with coronavirus disease 2019 (COVID‐19). Data on methylprednisolone are limited.
Methods
Retrospective cohort of consecutive adults with severe COVID‐19 pneumonia on high‐flow oxygen (FiO2 ≥ 50%) admitted to an academic centre in New York, from 1 March to 15 April 2020. We used inverse probability of treatment weights to estimate the effect of methylprednisolone on clinical outcomes and intensive care resource utilization.
Results
Of 447 patients, 153 (34.2%) received methylprednisolone and 294 (65.8%) received no corticosteroids. At 28 days, 102 patients (22.8%) had died and 115 (25.7%) received mechanical ventilation. In weighted analyses, risk for death or mechanical ventilation was 37% lower with methylprednisolone (hazard ratio 0.63; 95% CI 0.47‐0.86; P = .003), driven by less frequent mechanical ventilation (subhazard ratio 0.56; 95% CI 0.40‐0.79; P = .001); mortality did not differ between groups. The methylprednisolone group had 2.8 more ventilator‐free days (95% CI 0.5‐5.1; P = .017) and 2.6 more intensive care‐free days (95% CI 0.2‐4.9; P = .033) during the first 28 days. Complication rates were not higher with methylprednisolone.
Conclusions
In nonintubated patients with severe COVID‐19 pneumonia, methylprednisolone was associated with reduced need for mechanical ventilation and less‐intensive care resource utilization without excess complications.
Background
The global Coronavirus Disease 2019 (COVID-19) pandemic offers the opportunity to assess how hospitals managed the care of hospitalized patients with varying demographics and clinical presentation. The goal of this study is to demonstrate the impact of densely populated residential areas on hospitalization and to identify predictors of length of stay and mortality in hospitalized patients with COVID-19 in one of the hardest hit counties internationally.
Methods
This is a single-center cohort study of 1325 sequentially hospitalized patients with COVID-19 in New York between March 2, 2020 to May 11, 2020. Geospatial distribution of study patients’ residence relative to population density in the region were mapped and data analysis included hospital length of stay, need and duration of invasive mechanical ventilation (IMV), and mortality. Logistic regression models were constructed to predict discharge dispositions in the remaining active study patients.
Results
The median age of the study cohort was 62 years (IQR - 49-75), and more than half were male (57%) with history of hypertension (60%), obesity (41%), and diabetes (42%). Geographic residence of the study patients was disproportionately associated with areas of higher population density (rs=0.235, p=0.004), with noted “hot spots” in the region. Study patients were predominantly hypertensive (MAP>90mmHg (670, 51%)) on presentation with lymphopenia (590, 55%), hyponatremia (411, 31%), and kidney dysfunction (eGFR&60ml/min/1.73m 2 (381, 29%)). Of the patients with a disposition (1188/1325), 15% (182/1188) required IMV and 21% (250/1188) developed acute kidney injury. In patients on IMV, median hospital length of stay in survivors (22 days; 16.5-29.5) was significantly longer than non-survivors (15 days; 10-23.75), but this was not due to prolonged time on the ventilator. The overall mortality in all hospitalized patients was 15% and in patients receiving IMV was 48%, which is predicted to minimally rise from 48% to 49% based on logistic regression models constructed to project the disposition in the remaining patients on the ventilator. Acute kidney injury during hospitalization (ORE=3.23) was the strongest predictor of mortality in patients requiring IMV.
Conclusions
This is the first study to collectively utilize the demographics, clinical characteristics and hospital course of COVID-19 patients to identify predictors of poor outcomes that can be used for resource allocation in future waves of the pandemic.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.