Clinical and chest CT features as a predictive tool for COVID-19 clinical progress: introducing a novel semi-quantitative scoring system.

OBJECTIVE

Proposing a scoring tool to predict COVID-19 patients' outcomes based on initially assessed clinical and CT features.

METHODS

All patients, who were referred to a tertiary-university hospital respiratory triage (March 27-April 26, 2020), were highly clinically suggestive for COVID-19 and had undergone a chest CT scan were included. Those with positive rRT-PCR or highly clinically suspicious patients with typical chest CT scan pulmonary manifestations were considered confirmed COVID-19 for additional analyses. Patients, based on outcome, were categorized into outpatient, ordinary-ward admitted, intensive care unit (ICU) admitted, and deceased; their demographic, clinical, and chest CT scan parameters were compared. The pulmonary chest CT scan features were scaled with a novel semi-quantitative scoring system to assess pulmonary involvement (PI).

RESULTS

Chest CT scans of 739 patients (mean age = 49.2 ± 17.2 years old, 56.7% male) were reviewed; 491 (66.4%), 176 (23.8%), and 72 (9.7%) cases were managed outpatient, in an ordinary ward, and ICU, respectively. A total of 439 (59.6%) patients were confirmed COVID-19 cases; their most prevalent chest CT scan features were ground-glass opacity (GGO) (93.3%), pleural-based peripheral distribution (60.3%), and multi-lobar (79.7%), bilateral (76.6%), and lower lobes (RLL and/or LLL) (89.1%) involvement. Patients with lower SpO, advanced age, RR, total PI score or PI density score, and diffuse distribution or involvement of multi-lobar, bilateral, or lower lobes were more likely to be ICU admitted/expired. After adjusting for confounders, predictive models found cutoffs of age ≥ 53, SpO ≤ 91, and PI score ≥ 8 (15) for ICU admission (death). A combination of all three factors showed 89.1% and 95% specificity and 81.9% and 91.4% accuracy for ICU admission and death outcomes, respectively. Solely evaluated high PI score had high sensitivity, specificity, and NPV in predicting the outcome as well.

CONCLUSION

We strongly recommend patients with age ≥ 53, SpO ≤ 91, and PI score ≥ 8 or even only high PI score to be considered as high-risk patients for further managements and care plans.

KEY POINTS

• Chest CT scan is a valuable tool in prioritizing the patients in hospital triage. • A more accurate and novel 35-scale semi-quantitative scoring system was designed to predict the COVID-19 patients' outcome. • Patients with age ≥ 53, SpO ≤ 91, and PI score ≥ 8 or even only high PI score should be considered high-risk patients.