COVID-19: clinical features and risk最新文献

{"title":"P93 Comparison of inflammatory profiles between COVID-19 and other acute lower respiratory tract infections: Results from the PREDICT-COVID19 study","authors":"H. Keir, M. Long, Y. Giam, H. Leyah, T. Pembridge, L. Delgado, R. Hull, C. Hughes, A. Gilmour, C. Hocking, B. New, D. Connell, H. Richardson, D. Cassidy, A. Shoemark, J. Chalmers","doi":"10.1136/thorax-2021-btsabstracts.203","DOIUrl":"https://doi.org/10.1136/thorax-2021-btsabstracts.203","url":null,"abstract":"IntroductionCOVID-19 has been reported to induce a ‘cytokine storm’ distinct from other acute respiratory tract infections (LRTIs). Understanding the similarities and differences in inflammatory profiles between SARS-CoV-2 infection and other respiratory infections may aid diagnosis, as well as the potential to repurpose therapies such as steroids and anti-IL-6 receptor antagonists for other respiratory infections.MethodsA prospective observational study of patients in 3 groups 1) PCR confirmed SARS-CoV-2 infection, 2) community-acquired pneumonia (CAP) without SARS-CoV-2, and 3) controls hospitalized for reasons other than infection. Patients were enrolled from a single centre in Dundee, UK. Patients were enrolled within 96 hours of hospital admission. 45 inflammatory biomarkers were measured in blood using the Olink target proteomic based biomarker panel. Additional markers were measured by ELISA/immunoassay and enzyme activity assay as appropriate. Discrimination between groups was evaluated using the area under the receiver operator characteristic curve (AUC).Results294 patients were included (COVID-19 n=176, CAP n=76, controls n=42), mean age 64 (SD±15.2) and 150 subjects were male (51.0%). Using ROC analysis the most discriminating biomarkers for COVID-19 compared to CAP were CXCL-10 (AUC 0.84 95%CI 0.78–0.90 p<0.001), CCL-8 (0.87 95%CI 0.82–0.92, p<0.001), CCL-7 (0.84 95%CI 0.78–0.89, p<0.001), CXCL-11 (0.80 95%CI 0.73–0.88, p<0.001). Further biomarkers included IL-18, IL-7, IL-10 and IL-33. The most discriminating biomarkers for COVID-19 compared to controls were CXCL-10 (0.89 95%CI 0.85–0.93, p<0.001, CCL-7 (0.88 95%CI 0.83–0.92, p<0.001), CCL-8 (0.87 95%CI 0.82–0.92, p<0.001). Further biomarkers included IL-10, CXCL-11 and IL-18. IL-4 was significantly lower in COVID-19 patients compared to controls (0.27 95%CI 0.16–0.38, p<0.001). No significant difference in IL-6 was seen between COVID-19 and CAP (median 21.9pg/ml vs 19.8pg/ml,p=0.59).ConclusionDifferential markers of inflammation were identified between COVID-19, CAP and control samples, indicating distinct immunological pathways. The identification of a similar IL-6 signature between COVID-19 and CAP indicates that IL-6 targeting therapies currently being used to treat COIVD-19 may also be beneficial in the treatment of CAP.","PeriodicalId":266318,"journal":{"name":"COVID-19: clinical features and risk","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129251842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"P97 Disease severity and patient recovery in COVID-19: an observational study comparing first and second wave admissions in London","authors":"A. Saigal, CN Niklewicz, SB Naidu, HM Bintalib, AJ Shah, G. Seligmann, A. Hunter, D. Miller, I. Abubakar, E. Wey, C. Smith, N. Jain, J. Barnett, S. Brill, J. Goldring, H. Jarvis, J. Hurst, M. Lipman, S. Mandal","doi":"10.1136/thorax-2021-btsabstracts.207","DOIUrl":"https://doi.org/10.1136/thorax-2021-btsabstracts.207","url":null,"abstract":"P97 Table 1Demographics and clinical characteristics of participants at hospital admission and follow up for wave 1 and 2 admissions Wave 1 Wave 2 p-value N = 400 N = 400 Demographics and Lifestyle Age (years) (Median, IQR) 61 (50 -74) 61 (51 - 74) 0.59 Male gender (N,%) 247 (61.8%) 237 (59.3%) 0.47 Ethnicity (White) (N,%) 200 (50.0%) 195 (48.8%) 0.001* Smoking status – Never smoker (N,%) 215 (53.8%) 219 (54.8%) 0.58 BMI (kg/m2) (Median, IQR) 26.8 (24.1 - 29.4) 27.7 (24.3 - 31.6) 0.015 Underlying clinical status Clinical Frailty Score (Median, IQR) 2 (2, 4) N = 332 3 (2, 3) N = 384 0.001 Shielding Status (N,%) Extremely vulnerable HCP issued letter 32 (10.1%) 23 (7.2%) 39 (11.2%) 5 (1.4%) 0.001 Covid Admission Severity Parameters Total number of symptoms (Median, IQR) 4 (3 - 6) 3 (2 - 3) <0.0001 NEWS2 score (Median, IQR) 5 (2 - 7) N = 372 4 (3 - 6) N = 379 0.60 TEP status – For full escalation (N,%) 284/365 (77.8%) 361/400 (90.3%) <0.0001 Maximum respiratory support (N,%) CPAP NIV N= 377 10 (2.7%) 2 (0.5%) N = 400 32 (8.0%) 5 (1.3%) <0.0001 Received anti-viral or immunosuppressive drugs (N,%) 23/374 (6.2%) 127/400 (31.8%) <0.0001 ITU admission (N,%) 62/377 (16.5%) 43/400 (10.8%) 0.02 Intubation (N,%) 49/364 (13.5%) 19/400 (4.8%) <0.0001 Pulmonary Embolus (N,%) 22/360 (6.1%) 24/395 (6.1%) 0.98 Follow-up Outcomes N = 322 N = 365 Mental Health Outcomes PHQ2 score ≥ 3 (N,%) 47 (15.4%) 34 (9.9%) 0.04 TSQ score ≥ 5 (N,%) 44 (14.9%) 12 (3.3%) <0.0001 Physical Recovery and Symptoms Not returned to work (N,%) 76 (24.8%) 114 (33.6%) 0.03 Improved Sleep quality (N,%) 168 (61.5%) 265 (78.4%) <0.0001 Improved Fatigue (N,%) 241 (87.6%) 307 (88.7%) 0.91 Improved Cough (N,%) 194 (69.5%) 291 (84.8%) <0.0001 Improved Breathlessness (N,%) 213 (76.1%) 311 (89.6%) <0.0001 Total Number of Symptoms (Median, IQR) 1 (0 - 2) N=314 0 (0 – 1) N=364 Radiology outcomes (N,%) Normalised Significantly Improved Not significantly improved Worsened N=309 211 (68.3%) 55 (17.8%) 2 (0.7%) 30 (9.7%) N=279 187 (67.0%) 65 (23.3%) 13 (4.7%) 14 (5.0%) <0.0001 *p value likely attributable to differences in unknown ethnicityConclusionThese data suggest second wave pa ients, although frailer, presented with fewer symptoms and experienced improved hospital admission trajectory. They demonstrated improved self-reported mental health and physical recovery outcomes despite earlier follow-up, possibly attributed to improved in-hospital treatment. Supporting recovery remains a clinical priority given many patients had not returned to work.ReferenceSaito S, et al. First and second COVID-19 waves in Japan: comparison of disease severity and characteristics. J Infect. 2021;82(4):84-123.","PeriodicalId":266318,"journal":{"name":"COVID-19: clinical features and risk","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131394462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}