Early Recognition of Low-Risk SARS-CoV-2 Pneumonia: A Model Validated With Initial Data and Infectious Diseases Society of America/American Thoracic Society Minor Criteria

Abstract

Background: A shortage of beds in ICUs and conventional wards during the COVID-19 pandemic led to a collapse of health care resources.

Research question: Can admission data and minor criteria by the Infectious Diseases Society of America (IDSA) and the American Thoracic Society (ATS) help identify patients with low-risk SARS-CoV-2 pneumonia?

Study design and methods: This multicenter cohort study included 1,274 patients in a derivation cohort and 830 (first wave) and 754 (second wave) patients in two validation cohorts. A multinomial regression analysis was performed on the derivation cohort to compare the following patients: those admitted to the ward (assessed as low risk); those admitted to the ICU directly; those transferred to the ICU after general ward admission; and those who died. A regression analysis identified independent factors for low-risk pneumonia. The model was subsequently validated.

Results: In the derivation cohort, similarities existed among those either directly admitted or transferred to the ICU and those who died. These patients could, therefore, be merged into one group. Five independently associated factors were identified as being predictors of low risk (not dying and/or requiring ICU admission) (ORs, with 95% CIs): peripheral blood oxygen saturation/Fio₂ > 450 (0.233; 0.149-0.364); < 3 IDSA/ATS minor criteria (0.231; 0.146-0.365); lymphocyte count > 723 cells/mL (0.539; 0.360-0.806); urea level < 40 mg/dL (0.651; 0.426-0.996); and C-reactive protein level < 60 mg/L (0.454; 0.285-0.724). The areas under the curve were 0.802 (0.769-0.835) in the derivation cohort, and 0.779 (0.742-0.816) and 0.801 (0.757-0.845) for the validation cohorts (first and second waves, respectively).

Interpretation: Initial biochemical findings and the application of < 3 IDSA/ATS minor criteria make early identification of low-risk SARS-CoV-2 pneumonia (approximately 80% of hospitalized patients) feasible. This scenario could facilitate and streamline health care resource allocation for patients with COVID-19.

Keywords: COVID-19; IDSA/ATS; SARS-CoV-2; pneumonia; risk profiling.

Figure 1

Multinomial regression analysis results presented as OR and 95% CI for the two logit models: direct ICU admission (A) and ICU transfer from ward + deaths (B). Ward admission is used as the reference category. CRP = C-reactive protein; IDSA/ATS = Infectious Diseases Society of America/American Thoracic Society; Spo₂ = peripheral blood oxygen saturation.

Figure 2

AUROC values for the derivation and validation cohorts. AUROC = area under the receiver-operating characteristic curve.

Figure 3

A, Estimated probabilities of low-risk pneumonia according to the number of predictive factors that are met. B, Nomogram in the best clinical scenario. C, Nomogram in the worst clinical scenario. Instructions for the interpretation of nomograms: locate the patient’s IDSA/ATS criteria number on the IDSA/ATS minor criteria axis. Draw a line straight upward to the points axis to determine how many points toward the probability of nonclinical deterioration the patient receives for his or her criteria number. Repeat the process for each variable. Sum the points achieved for each of the predictors. Locate the final sum on the total axis. Draw a line straight down to find the patient’s probability nonclinical deterioration (ICU admission or death). In the figure, maximum probability of nonclinical deterioration is marked on the probabilities axis (91%) corresponding to a patient with all the characteristics in the right-side category (dots in blue). CRP = C-reactive protein; IDSA/ATS = Infectious Diseases Society of America/American Thoracic Society; Spo₂ = peripheral blood oxygen saturation/ Fio₂.