C proposed a risk model that confers a relative score (grade) to ten variables, including demographic, clinical, analytical and imaging data. The score’s main objective is to determine which patients with lower airway infection present a higher probability of SARS-CoV-2 infection. However, this score has not yet been validated. This study aimed at validating this clinical risk score for SARS-CoV-2 infection, applicable to inpatients with pneumonia. Most patients admitted for pneumonia were males, with a mean age of 69.90 ± 17.83 years old, and most (87.6%) presented comorbidities which is concordant with the epidemiological COVID-19 studies’ findings, suggesting a higher incidence of hospital admission in this subgroup of patients   . However, other respiratory pathogens can also present a higher incidence of severe disease in the elderly subpopulations with comorbidities  . Indeed, when comparing positive and negative SARS-CoV-2 rRT-PCR subgroups, male gender and comorbidities were equally found in both conditions.
According to recent publications, the most common comorbidities in COVID-19 patients are hypertension, obesity and diabetes   , which is also in agreement with our findings. Of note, obesity was not analyzed in this study since it was not included in the PSIC score.
When comparing positive and negative SARS-CoV-2 rRT-PCR subgroups, typical chest CT features, exposure to a positive SARS-CoV-2 patient and PCT < 0.5 ng/mL were significantly more prevalent in the positive SARS-CoV-2 rRT-PCR subgroup.
The logistic regression analysis revealed that typical chest CT features and contact with a positive case were the most significant independent variables in predicting a positive rRT-PCR-SARS-CoV-2 test, which partially agrees with the relative scoring system proposed by the PSIC. This is also concordant with other studies’ findings, which have demonstrated that typical chest CT features present higher sensitivity in the early detection of COVID-19 pneumonia . Interestingly, 37 (30.3%) patients in the negative subgroup presented typical CT features.
Twenty-one percent of patients presented with fever and dry cough and when comparing subgroups these symptoms were more prevalent in the positive group (34.8% vs 18.0%, p = 0.069), with a p-value close to the threshold of statistical significance suggesting these might play a role in the prediction a positive test in wider sample size studies.
Lymphopenia has been associated with severe coronavirus disease  . Nevertheless, its role in predicting infection may be somewhat limited since in this study, the presence of lymphopenia (<1200/uL) didn’t determine a significantly increased risk of a positive SARS-CoV-2 test.
The aged study population and the development of lymphopenia in other viral infections and medical conditions may have accounted for these findings since ≥50% of patients in both groups presented this condition. This suggests that the relative scoring system proposed by the PSIC might need adjustment in the weight of this variable for this subpopulation.
Only a small percentage of patients tested positive for other respiratory viruses and presented positive urinary antigen tests and the prevalence of negative results was similar between the positive and negative rRT-PCR-SARS-CoV-2 subgroups, which seems to preclude these variables from being good infection discriminators. However, these can be useful tools for diagnosing co-infection, which may imply different treatment strategies. Importantly, in our study, co-infection was found in 39.0% of patients, including other respiratory viruses and bacteria. This finding may have also contributed to the non-significant results in CRP, PCT and LDH levels.
According to our results, the best score cut-off value was between 10 and 11, which is in accordance with the one proposed by the original authors. In this study, most (86.9%) of the positive SARS-CoV-2 patients presented a score ≥ 10 and the mean PSIC score was significantly higher in the confirmed COVID-19 subgroup.
The ROC curve analysis illustrated that the PSIC s