Characteristics and outcomes of ambulatory patients with suspected COVID-19 at a respiratory referral center

Abstract

Rationale: SARS-CoV-2 continues to cause a global pandemic and management of COVID-19 in outpatient settings remains challenging.

Objective: We sought to describe characteristics of patients with chronic respiratory disease (CRD) experiencing symptoms consistent with COVID-19, who were seen in a novel Acute Respiratory Clinic, prior to widely available testing, emergence of variants, COVID-19 vaccination, and post-vaccination (breakthrough) SARS-CoV-2 infections.

Methods: Retrospective electronic medical record data were analyzed from 907 adults with presumed COVID-19 seen between March 16, 2020 and January 7, 2021. Data included demographics, comorbidities, medications, vital signs, laboratory tests, pulmonary function tests, patient disposition, and co-infections. The overdispersed data (aod) R package was used to create a logit model using COVID-19 diagnosis by PCR as the dichotomous outcome variable. Univariate, conventional multivariate and elastic net machine learning were used to analyze data.

Results: Male gender, elevated baseline temperature, and respiratory rate predicted COVID-19 diagnosis. Eosinopenia, neutrophilia, and lymphocytosis were also associated with COVID-19 diagnosis. However, asthma and COPD diagnoses were not associated with SARS-CoV-2 PCR positive test. Male gender, low oxygen saturation, and lower forced expiratory volume in 1 s (FEV₁) were associated with higher hospital referral.

Conclusions: CRD patients with acute respiratory symptoms in the ambulatory setting were more likely to have COVID-19 if male, febrile and tachypneic. Patients with lower pre-morbid FEV₁ and lower SPO₂ are more likely to be referred to the hospital. A composite of vitals sigs and WBC differential help risk stratify CRD patients seeking care for presumed COVID-19.

Keywords: Ambulatory respiratory infections; COVID-19; Clinical prediction.

Fig. 1

ARC Patients Recruited and Analyzed (March 16, 2020–January 7, 2021). Data analyzed on all available values. Of all 907 ARC patients seen between March 16, 2020 and January 7, 2021, 154 were diagnosed with COVID-19, of whom 135 were discharged home. Fifteen were referred for ED evaluation and 10 hospitalized. There is overlap between disposition to ED and Hospital. Of the 10 patients hospitalized, 7 were admitted from the ED, 2 were directly admitted, and 1 patient we could not ascertain by which of these routes they were hospitalized. Additionally, one patient seen in the ED refused admission. Missing data is noted in the figure.

Fig. 2

A–C, Receiver operating characteristic curves (ROCs) for discrimination between COVID-19 positive (n = 154) and negative (n = 753) cases based on multiple variable analysis (MVA) of (A) vital sign data (AUC 0.64), which included SPO2, HR, SBP, DBP, RR, and temperature; (B) laboratory (lab) data (AUC 0.69), which included WBC, %neutrophils, %lymphocytes, and %eosinophils; and (C) vital sign and lab data (AUC 0.71), which included temperature, and labs described. Yellow line is logistic fit for positive cohort. Vital signs and labs individually and together correlated with COVID-19. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 3

Variable Importance Plot (VIP) for variables selected by the elastic net method for the prediction of testing positive for COVID in 405 subjects with complete data. Variables are located on the y-axis and relative importance to predicting COVID (+) status is located on the x-axis (the higher the number, the more important the variable). Temperature, male sex, and RR together may predict COVID-19 in subjects evaluated for acute respiratory symptoms.