Chest CT in COVID-19 at the ED: Validation of the COVID-19 Reporting and Data System (CO-RADS) and CT Severity Score
2020; Elsevier BV; Volume: 159; Issue: 3 Linguagem: Inglês
10.1016/j.chest.2020.11.026
ISSN1931-3543
AutoresArthur W. E. Lieveld, Kaoutar Azijli, Bernd P. Teunissen, Rutger M. van Haaften, Ruud S. Kootte, Inge A. H. van den Berk, S F B van der Horst, Carlijn de Gans, Peter M. van de Ven, Prabath W.B. Nanayakkara,
Tópico(s)Advanced X-ray and CT Imaging
ResumoBackgroundCT is thought to play a key role in coronavirus disease 2019 (COVID-19) diagnostic workup. The possibility of comparing data across different settings depends on the systematic and reproducible manner in which the scans are analyzed and reported. The COVID-19 Reporting and Data System (CO-RADS) and the corresponding CT severity score (CTSS) introduced by the Radiological Society of the Netherlands (NVvR) attempt to do so. However, this system has not been externally validated.Research QuestionWe aimed to prospectively validate the CO-RADS as a COVID-19 diagnostic tool at the ED and to evaluate whether the CTSS is associated with prognosis.Study Design and MethodsWe conducted a prospective, observational study in two tertiary centers in The Netherlands, between March 19 and May 28, 2020. We consecutively included 741 adult patients at the ED with suspected COVID-19, who received a chest CT and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) PCR (PCR). Diagnostic accuracy measures were calculated for CO-RADS, using PCR as reference. Logistic regression was performed for CTSS in relation to hospital admission, ICU admission, and 30-day mortality.ResultsSeven hundred forty-one patients were included. We found an area under the curve (AUC) of 0.91 (CI, 0.89-0.94) for CO-RADS using PCR as reference. The optimal CO-RADS cutoff was 4, with a sensitivity of 89.4% (CI, 84.7-93.0) and specificity of 87.2% (CI, 83.9-89.9). We found a significant association between CTSS and hospital admission, ICU admission, and 30-day mortality; adjusted ORs per point increase in CTSS were 1.19 (CI, 1.09-1.28), 1.23 (1.15-1.32), 1.14 (1.07-1.22), respectively. Intraclass correlation coefficients for CO-RADS and CTSS were 0.94 (0.91-0.96) and 0.82 (0.70-0.90).InterpretationOur findings support the use of CO-RADS and CTSS in triage, diagnosis, and management decisions for patients presenting with possible COVID-19 at the ED. CT is thought to play a key role in coronavirus disease 2019 (COVID-19) diagnostic workup. The possibility of comparing data across different settings depends on the systematic and reproducible manner in which the scans are analyzed and reported. The COVID-19 Reporting and Data System (CO-RADS) and the corresponding CT severity score (CTSS) introduced by the Radiological Society of the Netherlands (NVvR) attempt to do so. However, this system has not been externally validated. We aimed to prospectively validate the CO-RADS as a COVID-19 diagnostic tool at the ED and to evaluate whether the CTSS is associated with prognosis. We conducted a prospective, observational study in two tertiary centers in The Netherlands, between March 19 and May 28, 2020. We consecutively included 741 adult patients at the ED with suspected COVID-19, who received a chest CT and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) PCR (PCR). Diagnostic accuracy measures were calculated for CO-RADS, using PCR as reference. Logistic regression was performed for CTSS in relation to hospital admission, ICU admission, and 30-day mortality. Seven hundred forty-one patients were included. We found an area under the curve (AUC) of 0.91 (CI, 0.89-0.94) for CO-RADS using PCR as reference. The optimal CO-RADS cutoff was 4, with a sensitivity of 89.4% (CI, 84.7-93.0) and specificity of 87.2% (CI, 83.9-89.9). We found a significant association between CTSS and hospital admission, ICU admission, and 30-day mortality; adjusted ORs per point increase in CTSS were 1.19 (CI, 1.09-1.28), 1.23 (1.15-1.32), 1.14 (1.07-1.22), respectively. Intraclass correlation coefficients for CO-RADS and CTSS were 0.94 (0.91-0.96) and 0.82 (0.70-0.90). Our findings support the use of CO-RADS and CTSS in triage, diagnosis, and management decisions for patients presenting with possible COVID-19 at the ED. Take-home PointsResearch Question: We aimed to prospectively validate the coronavirus disease 2019 (COVID-19) Reporting and Data System (CO-RADS) at the ED to be able to compare COVID-19 CT data across different settings and countries. We also evaluated whether the corresponding CT severity score (CTSS) was associated with prognosis.Results: We observed that CO-RADS had an area under the curve compared with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) polymerase chain reaction (PCR) of 0.91 (CI, 0.89-0.94). After correcting for confounders, the CTSS was significantly positively associated with hospital and ICU admission and mortality. We observed good-to-excellent interobserver agreement for CO-RADS and CTSS and no steep learning curve.Interpretation: Our findings support the use of CO-RADS and CTSS in triage, diagnosis, and management decisions for patients presenting with suspected COVID-19 at the ED.FOR EDITORIAL COMMENT, SEE PAGE 906 Research Question: We aimed to prospectively validate the coronavirus disease 2019 (COVID-19) Reporting and Data System (CO-RADS) at the ED to be able to compare COVID-19 CT data across different settings and countries. We also evaluated whether the corresponding CT severity score (CTSS) was associated with prognosis. Results: We observed that CO-RADS had an area under the curve compared with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) polymerase chain reaction (PCR) of 0.91 (CI, 0.89-0.94). After correcting for confounders, the CTSS was significantly positively associated with hospital and ICU admission and mortality. We observed good-to-excellent interobserver agreement for CO-RADS and CTSS and no steep learning curve. Interpretation: Our findings support the use of CO-RADS and CTSS in triage, diagnosis, and management decisions for patients presenting with suspected COVID-19 at the ED. FOR EDITORIAL COMMENT, SEE PAGE 906 The coronavirus disease 2019 (COVID-19) pandemic continues to put tremendous stress on health-care systems and societies worldwide. With second waves flaring up globally,1Coronavirus Update (Live)—Worldometers.https://www.worldometers.info/coronavirus/Google Scholar,2Johns Hopkins Coronavirus Resource CenterCOVID-19 Map.https://coronavirus.jhu.edu/map.htmlGoogle Scholar swift and accurate diagnosis is essential to profile patients and allocate scarce resources adequately. This is still hampered by limited sensitivity and availability of severe acute repiratory syndrome coronavirus 2 (SARS-CoV-2) polymerase chain reaction (PCR).3Sethuraman N, Jeremiah SS, Ryo A. Interpreting diagnostic tests for SARS-CoV-2. JAMA. 323(22):2249-2251.Google Scholar, 4Abbasi J. The promise and peril of antibody testing for COVID-19.JAMA. 2020; 323: 1881-1883Crossref PubMed Scopus (147) Google Scholar, 5Wang W. Xu Y. Gao R. et al.Detection of SARS-CoV-2 in different types of clinical specimens.JAMA. 2020; 323: 1843-1844PubMed Google Scholar More importantly, PCR does not give any insight into pulmonary involvement, whereas pneumonia is the most common cause of severe morbidity and mortality in COVID-19.6Zhou F. Yu T. Du R. et al.Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study.Lancet. 2020; 395: 1054-1062Abstract Full Text Full Text PDF PubMed Scopus (18962) Google Scholar,7Guan W. Ni Z. Hu Y. et al.Clinical characteristics of coronavirus disease 2019 in China.N Engl J Med. 2020; 382: 1708-1720Crossref PubMed Scopus (20519) Google Scholar Chest imaging may play a key role in COVID-19 triage and diagnosis, as well as stratification of disease severity.8Rubin G.D. Haramati L.B. Kanne J.P. et al.The role of chest imaging in patient management during the COVID-19 pandemic: a multinational consensus statement from the Fleischner Society.Radiology. 2020; : 201365Crossref PubMed Scopus (638) Google Scholar, 9Simpson S. Kay F.U. Abbara S. et al.Radiological Society of North America Expert Consensus Statement on Reporting Chest CT Findings Related to COVID-19. Endorsed by the Society of Thoracic Radiology, the American College of Radiology, and RSNA.J Thorac Imaging. 2020; 35: 219-227Crossref PubMed Scopus (457) Google Scholar, 10Chou R. Pappas M. Buckley D. et al.Use of chest imaging in COVID-19: a rapid advice guide.https://apps.who.int/iris/bitstream/handle/10665/332326/WHO-2019-nCoV-Clinical-Radiology_imaging-Web_Annex_A-2020.1-eng.pdfGoogle Scholar Conventional chest radiography unfortunately has limited sensitivity for COVID-19 pneumonia. In retrospective studies, sensitivity of chest CT for COVID-19 is excellent, and it may even be greater than that of PCR.10Chou R. Pappas M. Buckley D. et al.Use of chest imaging in COVID-19: a rapid advice guide.https://apps.who.int/iris/bitstream/handle/10665/332326/WHO-2019-nCoV-Clinical-Radiology_imaging-Web_Annex_A-2020.1-eng.pdfGoogle Scholar, 11Ai T. Yang Z. Hou H. et al.Correlation of chest CT and RT-PCR testing in coronavirus disease 2019 (COVID-19) in China: a report of 1014 cases.Radiology. 2020; 296: E32-E40Crossref PubMed Scopus (3956) Google Scholar, 12Pan F. Ye T. Sun P. et al.Time course of lung changes at chest CT during recovery from coronavirus disease 2019 (COVID-19).Radiology. 2020; 295: 715-721Crossref PubMed Scopus (1892) Google Scholar CTs are helpful in the diagnostic process at the ED, because the results are available almost immediately, and alternative diagnoses may be identified. In addition, using a semiquantitative CT severity score (CTSS) is reported to correlate with disease severity, and it might be used as a prognostic marker.12Pan F. Ye T. Sun P. et al.Time course of lung changes at chest CT during recovery from coronavirus disease 2019 (COVID-19).Radiology. 2020; 295: 715-721Crossref PubMed Scopus (1892) Google Scholar, 13Li K. Wu J. Wu F. et al.The clinical and chest CT features associated with severe and critical COVID-19 pneumonia.Invest Radiol. 2020; 55: 327-331Crossref PubMed Scopus (836) Google Scholar, 14Li K. Fang Y. Li W. et al.CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19).Eur Radiol. 2020; 30: 4407-4416Crossref PubMed Scopus (494) Google Scholar, 15Wong H.Y.F. Lam H.Y.S. Fong A.H.-T. et al.Frequency and distribution of chest radiographic findings in COVID-19 positive patients.Radiology. 2020; 296: E72-E78Crossref PubMed Scopus (972) Google Scholar, 16Xiong Y. Sun D. Liu Y. et al.Clinical and high-resolution CT features of the COVID-19 infection: comparison of the initial and follow-up changes.Invest Radiol. 2020; 55: 332-339Crossref PubMed Scopus (323) Google Scholar, 17Liu Z. Jin C. Wu C.C. et al.Association between initial chest CT or clinical features and clinical course in patients with coronavirus disease 2019 pneumonia.Korean J Radiol. 2020; 21: 736-745Crossref PubMed Scopus (50) Google Scholar Studies on using CT as an initial diagnostic modality are mostly retrospective in nature and from China, possibly reducing their generalizability to other regions. Although the CT characteristics of COVID-19 have been documented properly, no universal agreement exists on a systematic and reproducible way of evaluating and reporting CT abnormalities in patients with (suspected) COVID-19, which makes it difficult to compare data across different settings.8Rubin G.D. Haramati L.B. Kanne J.P. et al.The role of chest imaging in patient management during the COVID-19 pandemic: a multinational consensus statement from the Fleischner Society.Radiology. 2020; : 201365Crossref PubMed Scopus (638) Google Scholar,9Simpson S. Kay F.U. Abbara S. et al.Radiological Society of North America Expert Consensus Statement on Reporting Chest CT Findings Related to COVID-19. Endorsed by the Society of Thoracic Radiology, the American College of Radiology, and RSNA.J Thorac Imaging. 2020; 35: 219-227Crossref PubMed Scopus (457) Google Scholar,18Bao C. Liu X. Zhang H. Li Y. Liu J. Coronavirus disease 2019 (COVID-19) CT findings: a systematic review and meta-analysis.J Am Coll Radiol. 2020; 17: 701-709Abstract Full Text Full Text PDF PubMed Scopus (291) Google Scholar, 19Salehi S. Abedi A. Balakrishnan S. Gholamrezanezhad A. Coronavirus disease 2019 (COVID-19): a systematic review of imaging findings in 919 patients.AJR Am J Roentgenol. 2020; 215: 87-93Crossref PubMed Scopus (1020) Google Scholar, 20Prokop M. van Everdingen W. van Rees Vellinga T. et al.CO-RADS: a categorical CT assessment scheme for patients with suspected COVID-19: definition and evaluation.Radiology. 2020; 296: E97-E104Crossref PubMed Scopus (583) Google Scholar, 21Zhu J. Zhong Z. Li H. et al.CT imaging features of 4121 patients with COVID-19: a meta-analysis.J Med Virol. 2020; 92: 891-902Crossref PubMed Scopus (93) Google Scholar The Radiological Society of the Netherlands (NVvR) recently introduced such a method, the COVID-19 Reporting and Data System (CO-RADS), which is largely based on the recommendations of the Radiological Society of North America.9Simpson S. Kay F.U. Abbara S. et al.Radiological Society of North America Expert Consensus Statement on Reporting Chest CT Findings Related to COVID-19. Endorsed by the Society of Thoracic Radiology, the American College of Radiology, and RSNA.J Thorac Imaging. 2020; 35: 219-227Crossref PubMed Scopus (457) Google Scholar,20Prokop M. van Everdingen W. van Rees Vellinga T. et al.CO-RADS: a categorical CT assessment scheme for patients with suspected COVID-19: definition and evaluation.Radiology. 2020; 296: E97-E104Crossref PubMed Scopus (583) Google Scholar,22Zimmerman M. Handreiking Standaardverslag CT-thorax COVID inclusief CO-RADS en CT-score.https://www.radiologen.nl/secties/netwerk-covid-19/documenten/handreiking-standaardverslag-ct-thorax-covid-inclusief-co-radsGoogle Scholar The CO-RADS is meant to be used for patients with moderate to severe symptoms of (suspected) COVID-19. It employs a scoring system from 0 to 5 to classify pulmonary involvement from very unlikely to very likely, respectively (e-Table 1). In 105 patients, the NVvR found a very good performance for predicting COVID-19 (area under the curve [AUC] of 0.91 (CI, 0.85-0.97).20Prokop M. van Everdingen W. van Rees Vellinga T. et al.CO-RADS: a categorical CT assessment scheme for patients with suspected COVID-19: definition and evaluation.Radiology. 2020; 296: E97-E104Crossref PubMed Scopus (583) Google Scholar In addition, interobserver agreement was substantial. Although these results are encouraging, a prospective external validation of the CO-RADS or any other CT classification system for COVID-19 is lacking.Table 1Patient CharacteristicsPatient CharacteristicsAll Patients (N = 741)SARS-CoV-2 PCR Positive (n = 235)SARS-CoV-2 PCR Negative (n = 506)P Value Age, mean (SD)62.1(17.2)62.5 (14.6)61.9 (18.4).655 Male, No. (%)417 (56.3)136 (57.9)281 (55.5).209 Admission, No. (%)580 (78.3)208 (88.5)372 (73.5).000 Admission IC, No. (%)84 (11.3)44 (18.7)40 (7.9).000 30 days mortality, No. (%)74 (10.0)33 (14.0)41 (8.1).001 In-hospital mortality, No. (%)54 (7.3)28 (11.9)26 (5.1).000 Duration of symptoms, days (SD)6.7 (7.2)7.9 (4.6)6.0 (8.2).001Co-morbidities, No. (%) Asthma49 (6.6)16 (6.8)33 (6.5).77 Chronic cardiovascular disease197 (26.6)50 (21.3)147 (29.1).000 COPD (GOLD > 2)128 (17.3)27 (11.5)101 (20.0).000 Current malignancy107 (14.4)15 (6.4)92 (18.2).000 Diabetes mellitus189 (25.5)69 (29.4)120 (23.7).002 Hypertension292 (39.4)107 (45.5)185 (36.6).000Observations and laboratory results at presentation CRP (mg/L), median (IQR)44.0 (86.5)69.0 (86.0)28.0 (79.3).76 PCT0.1 (0.28)0.13 (0.22)0.1 (0.35).002 Positive blood culture, No. (%)36 (4.9)1 (0.4)35 (6.9).000 Modified early warning score, mean (SD)2.86 (1.8)3.0 (1.7)2.8 (1.8).076 Temperature (°C), mean (SD)36.9 (1.3)37.5 (1.1)36.7 (1.3).259 Respiratory rate, mean (SD)22.7 (7.9)24.9 (8.0)21.7 (7.7).070 Saturation levels, mean (SD)95.2 (5.6)94.1 (6.1)95.7 (5.3).281 Oxygen therapy, No. (%)255 (34.9)111 (47.8)144 (28.9).002 Intubation, No. (%)68 (9.2)39 (16.6)29 (5.7).000P values in bold are < .05.CRP = C-reactive protein; GOLD = Global Initiative for Chronic Obstructive Lung Disease; IC = intensive care; IQR = interquartile range; PCR = polymerase chain reaction; PCT = procalcitonin; SARS-CoV-2 = severe acute respiratory syndrome coronavirus 2. Open table in a new tab P values in bold are < .05. CRP = C-reactive protein; GOLD = Global Initiative for Chronic Obstructive Lung Disease; IC = intensive care; IQR = interquartile range; PCR = polymerase chain reaction; PCT = procalcitonin; SARS-CoV-2 = severe acute respiratory syndrome coronavirus 2. In this observational study, we therefore set out to prospectively validate the CO-RADS in two tertiary hospitals in The Netherlands. Furthermore, in accordance with recent research recommendations from the World Health Organization (WHO),23World Health OrganizationUse of chest imaging in COVID-19.https://www.who.int/publications-detail-redirect/use-of-chest-imaging-in-covid-19Google Scholar we analyzed whether the CTSS was associated with hospital admission, ICU admission, and mortality. This is a real-life, prospective, observational study. Patients were recruited consecutively from the EDs of the two university hospitals in Amsterdam, the Netherlands, between March 19 and May 28, 2020. The study was approved by the Medical Ethics Review Committee of the Amsterdam University Medical Centers, location VUmc. An opt-out recruitment procedure was used to obtain consent for participation in the study. All patients 18 years of age and older who visited the ED with suspected COVID-19 according to the WHO and Dutch Centre for Infectious Disease Control case definition (including either fever, malaise, respiratory symptoms, GI symptoms, or loss of taste and smell) were potentially eligible. Patients were included if they received a PCR and chest CT with CO-RADS score. Exclusion criteria were age younger than 18 years, unwillingness to give verbal consent, or a CO-RADS 6 score (Fig 1). All patients with suspected COVID-19 received a regular medical workup and a chest CT if deemed appropriate by the treating physician or according to local clinical protocol. Local protocol, based on Dutch Federation of Medical Specialists and WHO COVID-19 recommendations, dictated that physicians could perform a CT in a case of moderate to severe symptoms.23World Health OrganizationUse of chest imaging in COVID-19.https://www.who.int/publications-detail-redirect/use-of-chest-imaging-in-covid-19Google Scholar,24Federatie Medisch SpecialistenHandreiking 'Diagnostiek bij verdenking COVID-19 en opname-indicatie.https://www.demedischspecialist.nl/nieuws/handreiking-%E2%80%98diagnostiek-bij-verdenking-covid-19-en-opname-indicatie%E2%80%99Google Scholar In a case with mild symptoms, physicians could forego additional imaging. Hospital admission criteria were saturation < 94% or respiratory rate > 20 breaths/min. ICU admission criteria were deterioration despite conventional respiratory support, patients requiring mechanical ventilation, or multi-organ failure. Admission decisions were not made based on CT data. All admitted patients with (suspected) COVID-19 were discussed daily in a multidisciplinary team (MDT), consisting of consultants in infectious disease, respiratory disease, and microbiology. The MDT decided on the final diagnosis, but it was not blinded for the CT results. The CTs were assessed by our local radiologists with varying degrees of experience. The radiologists had regular access to clinical information but did not have access to the PCR results, because CT scanning and reporting were done early after ED admission, before PCR results were available. The likelihood of COVID-19 pneumonia was reported according to the CO-RADS classification system (e-Table 1).20Prokop M. van Everdingen W. van Rees Vellinga T. et al.CO-RADS: a categorical CT assessment scheme for patients with suspected COVID-19: definition and evaluation.Radiology. 2020; 296: E97-E104Crossref PubMed Scopus (583) Google Scholar,22Zimmerman M. Handreiking Standaardverslag CT-thorax COVID inclusief CO-RADS en CT-score.https://www.radiologen.nl/secties/netwerk-covid-19/documenten/handreiking-standaardverslag-ct-thorax-covid-inclusief-co-radsGoogle Scholar Details on how the CTs were made are available in the e-Appendix under e-Methods. To quantify pulmonary involvement, every CT with a CO-RADS of 3 or higher was graded according to the CTSS.25Chang Y.-C. Yu C.-J. Chang S.-C. et al.Pulmonary sequelae in convalescent patients after severe acute respiratory syndrome: evaluation with thin-section CT.Radiology. 2005; 236: 1067-1075Crossref PubMed Scopus (244) Google Scholar This is a visual assessment of the percentage of disease involvement in each lobe (e-Table 2). The total CTSS is the sum of the individual lobar scores and can range from 0 (no involvement) to 25 (maximum involvement). A naso- or oropharynx PCR was performed in all patients presenting to the ED, according to WHO standards. In case of a negative or inconclusive test result and high clinical suspicion of COVID-19, a nasopharynx or oropharynx PCR was repeated or sputum or bronchoalvealar lavage if available and possible, as indicated by the MDT. As the primary outcome, sensitivity, specificity, predictive values, likelihood ratios, area under the receiver operating characteristic curve, and diagnostic accuracy were calculated for CO-RADS. For CTSS, we calculated the same measures, and ORs for hospital admission, ICU admission, and mortality. Continuous variables were summarized by mean and SD, or by medians and interquartile range. Differences between groups were tested using the independent-samples t test, Mann Whitney U test, χ2 test or Fisher exact test as appropriate. A two-sided significance level of 5% was used, and 95% CIs were reported for all analyses. Discriminatory ability of CO-RADS and CTSS was determined by the area under the receiver operating characteristic curve. The optimal cutoff value was determined by the Youden's index. Diagnostic measures were subsequently calculated.For CTSS, we also employed a "gray zone" approach. A gray zone represents a predictive test of poor accuracy, with a sensitivity and specificity 2 (e-Table 4). Eleven (44%) of them had a symptom duration of less than 3 days. Eighteen patients (72%) were admitted, seven (28%) patients received oxygen, and only two (8%) patients needed ICU treatment. Sixty-five patients had a false-positive CT scan (CO-RADS ≥ 4, but negative PCR), compared with PCR. Forty-six of those patients were still classified as having COVID-19 by the MDT; the remaining diagnoses are summarized in e-Table 5. The most common alternative diagnoses were bacterial pneumonia and decompensated heart failure (e-Table 6). The CUSUM plots in center 1 showed no strong upward or downward inflections, indicating a steady performance over time. For center 2, an upward inflection was seen after the 80th COVID-negative patient was included (corresponding to the 161th consecutive patient included), showing a temporary increase in the false-positive rate (e-Fig 5). The CTSS was determined in 304 (patients, who had a CO-RADS ≥ 3. Stratified according to three disease severity groups—(1) discharge home from ED, (2) hospital admission, or (3) ICU admission—we found a significant difference in mean CTSS; 5.5 (SD, 3.6), 9.4 (SD, 4.9), and 14.8 (SD, 4.8), respectively. Logistic regression showed a significant positive association between CTSS (per point increase) and hospital admission, ICU admission, and 30-day mortality (Table 3). These associations stayed significant after correcting for potential confounders age, sex, and the aforementioned co-morbidities, with adjusted OR of 1.18 (CI, 1.09-1.28); 1.23 (CI, 1.15-1.32); and 1.14 (CI, 1.07-1.22) respectively.Table 3CTSS Logistic RegressionAssociation between CT-severity score and hospital admissionCrude AnalysisAdjusted AnalysisaAdjusted for age, sex, co-morbidities (cardiovascular disease, COPD, asthma, high BP).OR (95% CI)P ValueOR (95% CI)P ValueCT severity score1.18 (1.09-1.27).0001.18 (1.09-1.28).000Association between CT-severity score and ICU admissionCrude AnalysisAdjusted AnalysisaAdjusted for age, sex, co-morbidities (cardiovascular disease, COPD, asthma, high BP).OR (95% CI)P ValueOR (95% CI)P ValueCT-severity score1.23 (1.16-1.32).0001.23 (1.15-1.32).000Association between CT-severity score and 30-day mortalityCrude AnalysisAdjusted AnalysisaAdjusted for age, sex, co-morbidities (cardiovascular disease, COPD, asthma, high BP).OR (95% CI)P ValueOR (95% CI)P ValueCT-severity score1.12 (1.05-1.19).0011.14 (1.07-1.22).000OR and CI of the association between CT-severity score (CTSS) and hospital admission, ICU admission, and 30-day mortality per point increase in CTSS.a Adjusted for age, sex, co-morbidities (cardiovascular disease, COPD, asthma, high BP). Open table in a new tab OR and CI of the association between CT-severity score (CTSS) and hospital admission, ICU admission, and 30-day mortali
Referência(s)