CoVA: An Acuity Score for Outpatient Screening that Predicts Coronavirus Disease 2019 Prognosis
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Abstract
Background
We sought to develop an automatable score to predict hospitalization, critical illness, or death for patients at risk for coronavirus disease 2019 (COVID-19) presenting for urgent care.
Methods
We developed the COVID-19 Acuity Score (CoVA) based on a single-center study of adult outpatients seen in respiratory illness clinics or the emergency department. Data were extracted from the Partners Enterprise Data Warehouse, and split into development (n = 9381, 7 March–2 May) and prospective (n = 2205, 3–14 May) cohorts. Outcomes were hospitalization, critical illness (intensive care unit or ventilation), or death within 7 days. Calibration was assessed using the expected-to-observed event ratio (E/O). Discrimination was assessed by area under the receiver operating curve (AUC).
Results
In the prospective cohort, 26.1%, 6.3%, and 0.5% of patients experienced hospitalization, critical illness, or death, respectively. CoVA showed excellent performance in prospective validation for hospitalization (expected-to-observed ratio [E/O]: 1.01; AUC: 0.76), for critical illness (E/O: 1.03; AUC: 0.79), and for death (E/O: 1.63; AUC: 0.93). Among 30 predictors, the top 5 were age, diastolic blood pressure, blood oxygen saturation, COVID-19 testing status, and respiratory rate.
Conclusions
CoVA is a prospectively validated automatable score for the outpatient setting to predict adverse events related to COVID-19 infection.
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SciScore for 10.1101/2020.06.17.20134262: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources We also looked at the time course of adverse events as a function of CoVA score over 4 weeks (28 days) following initial presentation to the RIC or ED to understand the properties of CoVA score. CoVAsuggested: (COVA, RRID:SCR_005175)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:The study also has limitations. First, our study is from a single center, with patient …
SciScore for 10.1101/2020.06.17.20134262: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources We also looked at the time course of adverse events as a function of CoVA score over 4 weeks (28 days) following initial presentation to the RIC or ED to understand the properties of CoVA score. CoVAsuggested: (COVA, RRID:SCR_005175)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:The study also has limitations. First, our study is from a single center, with patient demographics specific to MGH, Boston. Nevertheless, important biological parameters in the predictive model are universal and increase the likelihood that the model will generalize. Second, although RIC clinics were established for patients with suspicion for COVID-19, patients seen in the ED were seen for a variety of reasons. Nevertheless COVID-19 was and for now remains a universal concern for patients seen in the ED, and we excluded patients prior to the onset of COVID-19 in Boston (March 7, 2020), therefore our model is relevant for screening during times of high alert for COVID-19. Finally, we did not include lab test values, since they were typically not available. Among the few studies of inpatients, inclusion of lab tests appears to improve model performance. In conclusion, the COVID-19 Acuity Score (CoVA) represents a well-calibrated, discriminative, prospectively validated, and interpretable score for assessing the risk for adverse events for outpatients presenting with possible COVID-19 infection.
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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