e 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 score can accurately stratify patients with pneumonia in different COVID-19 risk categories.
Although this model has been shown to be a useful risk assessment tool for COVID-19 pneumonia, it may miss-label some patients. Indeed, forty-one (33.6%) patients of the negative COVID-19 subgroup presented a PSIC score ≥ 10, but the meaning of these findings may be somewhat misleading considering the sensitivity of the rRT-PCR test.
Furthermore, the PSIC score was proposed with no description of the methods used for the determination of score variables, grade scoring system and score cut-off, probably due to the need of fast interventions in the setting of a public health emergency.
This study presented several limitations. First, it was a retrospective analysis. Secondly, it included a limited number of patients reflecting the reality of a single-center department. Not all patients admitted to the ward were included in the validation cohort. Most patients were excluded due to lack of chest CT images since not all were considered to present criteria for the performance of a CT-scan when the clinical picture and the chest radiography were sufficiently informative and the CT radiation risks and costs were considered to outcome its benefits. Other patients were excluded due to a lack of information on other variables such as PCT and urinary antigen tests. However, it should be noted that the study was developed during the initial phase of COVID-19 in Portugal when diagnostic protocols were still being implemented and the exams were requested according to clinical presentation. Results in this study rely on the SARS-CoV-2 rRT-PCR test for the confirmation of positive COVID-19 cases. However, this test presents a sensitivity of approximately 66% - 80%  , which means that a considerable number of positive cases may have not been identified. Moreover, collected samples for the SARS-CoV-2 test were from Naso and oropharyngeal swabs, which present a lower diagnostic yield compared to lower airway samples . The authors hypothesized