Observational studyAnnals of emergency medicine2020
Development and Validation of the Quick COVID-19 Severity Index: A Prognostic Tool for Early Clinical Decompensation.
Observational study in Annals of emergency medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 169 papers, 4 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
169 citing papers in PubMed, 4 syntheses or guidelines pooled it, 304 citations in OpenAlex.
- Pooled it
- Use of artificial intelligence in predicting in-hospital cardiac and respiratory arrest in an acute care environment-implications for clinical practice.Frontiers in medical technology · 2025Pooled it
- Prognostic models in COVID-19 infection that predict severity: a systematic review.European journal of epidemiology · 2023Pooled it
- Exacerbation of neurological symptoms and COVID-19 severity in patients with preexisting neurological disorders and COVID-19: A systematic review.Clinical neurology and neurosurgery · 2021Pooled it
- Trial
- Trial
- Effectiveness of Telemedicine vs Face-to-Face Consultation in Fighting COVID-19: Retrospective Cohort Study of Adult Patients With COVID-19 in a Primary Care Setting.Journal of medical Internet research · 2026Article
- Comparison of the performance of four clinical prediction rules for mortality in patients with COVID-19.PloS one · 2026Article
- Machine learning-based prediction of intensive care unit admission in COVID-19 patients presenting with mild respiratory failure.Frontiers in medicine · 2026Article
- Assessment of the integrity of real-time electronic health record data used in clinical research.PloS one · 2026Article
- Blood pro-thrombotic analytes and platelet activation are associated with post-acute sequelae of COVID-19.BMC infectious diseases · 2025Observational
- Exploring the association between happy hypoxia and Coronavirus disease 2019 in the triage phase.Future science OA · 2025Article
- Evaluating the predictive performance of PIRO score against six clinical prediction scores for COVID-19 outcomes in the emergency department.Scientific reports · 2025Article
- Performance of Risk Scores in SARS-CoV-2 Infection: A Retrospective Study.International journal of environmental research and public health · 2025Observational
- Prehospital Performance of Five Early Warning Scores to Predict Long-Term Mortality in Patients with Suspected Respiratory Infections.Diagnostics (Basel, Switzerland) · 2025Article
- Evaluation of physiological severity scores for predicting COVID-19 disease progression: a retrospective study.BMC infectious diseases · 2025Article
- Prediction models based on machine learning algorithms for COVID-19 severity risk.BMC public health · 2025Article
- Accuracy of early warning scores for predicting clinical worsening in COPD patients.ERJ open research · 2025Article
- The Complete Blood Count Sepsis Index Using Monocyte Distribution Width for Early Detection of Sepsis in Patients Without Obvious Signs.Critical care explorations · 2025Observational
- Different Modalities in the Management of Post-COVID-19 Olfactory Dysfunction.Indian journal of otolaryngology and head and neck surgery : official publication of the Association of Otolaryngologists of India · 2025Article
109 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
STUDY
objectiveThe 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).
methodsThis 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.
resultsDuring 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.
conclusionA 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.