Current best evidence for clinical care (more info)
STUDY OBJECTIVE: The goal of this study is to create a predictive, interpretable model of early hospital respiratory failure among emergency department (ED) patients admitted with coronavirus disease 2019 (COVID-19).
METHODS: This was an observational, retrospective, cohort study from a 9-ED health system of admitted adult patients with severe acute respiratory syndrome coronavirus 2 (COVID-19) and an oxygen requirement less than or equal to 6 L/min. We sought to predict respiratory failure within 24 hours of admission as defined by oxygen requirement of greater than 10 L/min by low-flow device, high-flow device, noninvasive or invasive ventilation, or death. Predictive models were compared with the Elixhauser Comorbidity Index, quick Sequential [Sepsis-related] Organ Failure Assessment, and the CURB-65 pneumonia severity score.
RESULTS: During the study period, from March 1 to April 27, 2020, 1,792 patients were admitted with COVID-19, 620 (35%) of whom had respiratory failure in the ED. Of the remaining 1,172 admitted patients, 144 (12.3%) met the composite endpoint within the first 24 hours of hospitalization. On the independent test cohort, both a novel bedside scoring system, the quick COVID-19 Severity Index (area under receiver operating characteristic curve mean 0.81 [95% confidence interval {CI} 0.73 to 0.89]), and a machine-learning model, the COVID-19 Severity Index (mean 0.76 [95% CI 0.65 to 0.86]), outperformed the Elixhauser mortality index (mean 0.61 [95% CI 0.51 to 0.70]), CURB-65 (0.50 [95% CI 0.40 to 0.60]), and quick Sequential [Sepsis-related] Organ Failure Assessment (0.59 [95% CI 0.50 to 0.68]). A low quick COVID-19 Severity Index score was associated with a less than 5% risk of respiratory decompensation in the validation cohort.
CONCLUSION: A significant proportion of admitted COVID-19 patients progress to respiratory failure within 24 hours of admission. These events are accurately predicted with bedside respiratory examination findings within a simple scoring system.
| Discipline / Specialty Area | Score |
|---|---|
| Hospital Doctor/Hospitalists | |
| Internal Medicine | |
| Emergency Medicine | |
| Infectious Disease | |
| Respirology/Pulmonology | |
COVID-19 rapidly filled ICUs in the spring of 2020. Many patients who appeared well with horrendous oxygen saturations were (probably needlessly) intubated. A prognostic score predicting which patients would benefit from intubation (and hence ICU-level care) is essential as another surge of COVID-19 emerges concurrent with influenza season in the autumn-winter of 2020. The Quick COVID-19 Severity Index is a first step, but requires external validation. In addition, methodologic concerns about this index include: (a) reliability of respiratory rate (a foundation of the score) is unquestionably poor (many citations, for one example see https://www.sciencedirect.com/science/article/pii/S088394411731331X?via%3Dihub); (b) the components of the index seem elementary and if ED clinicians are not already using them to determine risk for decompensation, it would be astonishing; and (c) only 14 ultimately required intubation or NIPPV, which are the outcomes I am most interested in predicting.
This is an excellently derived and validated tool that can be used to determine risk for deterioration in coronavirus patients evaluated in the emergency department.
Very timely and important despite limited ability to extensively validate.
This study developed and validated a simple predictive model for ED patients with COVID-19 infection, which may turn out to be quite useful. Before widespread use, it needs prospective validation in a broader range of settings.
Not sure the operating characteristics are good enough to affect practice above clinical judgment. Validation in a different setting should be done.
An easily applied severity index (respiratory rate, pulse ox, and oxygen needs) was found to accurately identify ED patients with Covid-19 who would rapidly deteriorate after admission and who therefore should be admitted directly to intensive care settings.
This is much simpler than most of the prognostic tools I have seen (although I probably have not seen all of them), and it would be good to validate in a geographically distinct area.
Very interesting analysis demonstrating an easy analysis to predict "decompensation to respiratory failure" in patients with COVID-19.
An interesting approach to a prediction validation tool. Although they derive from a large data set (~900 patients) and test the tool in ~250 patients, they fail to truly give us a sense of how well the test performed for both negative and positive predictive values. The key variable that had an outsize effect on the score was O2 flow rate. This is not a surprise to those of us taking care of COVID patients in terms of predicting respiratory failure.
A tool that offers easy calculation of early (<24 h) respiratory risk. However, I do agree with the authors regarding how useful the tool is as no studies compares this to clinical gestalt.