Predicting progression to severe COVID-19 using the PAINT score.

OBJECTIVES: One of the major challenges in treating patients with coronavirus disease 2019 (COVID-19) is predicting the severity of disease. We aimed to develop a new score for predicting progression from mild/moderate to severe COVID-19. METHODS: A total of 239 hospitalized patients with COVID-19 from two medical centers in China between February 6 and April 6, 2020 were retrospectively included. The prognostic abilities of variables, including clinical data and laboratory findings from the electronic medical records of each hospital, were analysed using the Cox proportional hazards model and Kaplan-Meier methods. A prognostic score was developed to predict progression from mild/moderate to severe COVID-19. RESULTS: Among the 239 patients, 216 (90.38%) patients had mild/moderate disease, and 23 (9.62%) progressed to severe disease. After adjusting for multiple confounding factors, pulmonary disease, age > 75, IgM, CD16+/CD56+ NK cells and aspartate aminotransferase were independent predictors of progression to severe COVID-19. Based on these five factors, a new predictive score (the 'PAINT score') was established and showed a high predictive value (C-index = 0.91, 0.902 ± 0.021, p < 0.001). The PAINT score was validated using a nomogram, bootstrap analysis, calibration curves, decision curves and clinical impact curves, all of which confirmed its high predictive value. CONCLUSIONS: The PAINT score for progression from mild/moderate to severe COVID-19 may be helpful in identifying patients at high risk of progression.

Additional Value of Non-contrast Chest CT in the Prediction of Adverse Cardiovascular Events in Patients With Novel Coronavirus Disease 2019 (COVID-19).

Background: Coronavirus disease 2019 (COVID-19) has outbroken in China and subsequently spread worldwide since the end of 2019. Chest computed tomography (CT) plays an important role in the diagnosis of lung diseases, but its value in the diagnosis of cardiac injury remains unknown. Methods: We enrolled 241 consecutive hospitalized patients (aged 61 ± 16 years, 115 males) with laboratory-confirmed COVID-19 at Renmin Hospital of Wuhan University from January 11 to March 2, 2020. They were divided into two groups according to whether major adverse cardiovascular events (MACEs) occurred during the follow-up. The anteroposterior diameter of the left atrium (LAD), the length of the left ventricle (LV), and cardiothoracic ratio (CTR) were measured. The values of myocardial CT were also recorded. Results: Of 241 patients, 115 patients (47.7%) had adverse cardiovascular events. Compared with no MACEs, patients with MACEs were more likely to have bilateral lesions (95.7% vs. 86.5%, p = 0.01). In multivariable analysis, bronchial wall thickening would increase the odds of MACEs by 13.42 (p = 0.01). LAD + LV and CTR was the best predictor for MACEs (area under the curve = 0.88, p < 0.001) with a sensitivity of 82.6% and a specificity of 80.2%. Plasma high-sensitivity troponin I levels in patients with cardiac injury showed a moderate negative correlation with minimum CT value (R 2 = -0.636, p < 0.001). Conclusions: Non-contrast chest CT can be a useful modality for detection cardiac injury and provide additional value to predict MACEs in COVID-19 patients.

Association between NT-proBNP Level and the Severity of COVID-19 Pneumonia.

In this study, we investigated the association between the plasma NT-proBNP level at admission and the severity of COVID-19 pneumonia. For this retrospective, single-centre cohort study, we enrolled consecutive patients from February 9 to March 4, 2020, in a COVID-19 ward of Hubei General Hospital (East Branch) in Wuhan, which is a government-assigned centre for COVID-19 treatment. Diagnosis was confirmed by microbiological and radiographic findings following the interim guidance of the World Health Organization (WHO). A total of 91 (92.9%) patients were finally included in this study. The median age of the patients was 61 years (IQR, 47-69), and 39 (43.0%) of them were male. Two cases of death were reported (2.3%). Twenty-three patients (25.3%) had NT-proBNP levels above 300 pg/ml. Higher NT-proBNP levels were associated with worse PSI and CT scores. The natural logarithm of the NT-proBNP level was positively correlated with the PSI and CT scores (PSI score: r S = 0.396, P=0.001; CT score: r S = 0.440, P < 0.001). Patients with NT-proBNP ≥300 pg/ml showed a potential risk for higher mortality than patients with NT-proBNP <300 pg/ml (mortality rate, 8.7% vs. 0%; P=0.062). The plasma NT-proBNP level of COVID-19 patients was significantly related to the severity of pneumonia.

The role of SARC-F scale in predicting progression risk of COVID-19 in elderly patients: a prospective cohort study in Wuhan.

BACKGROUND: Since the outbreak of COVID-19, it has been documented that old age and underlying illnesses are associated with poor prognosis among COVID-19 patients. However, it is unknown whether sarcopenia, a common geriatric syndrome, is associated with poor prognosis among older COVID-19 patients. The aim of our prospective cohort study is to investigate the association between sarcopenia risk and severe disease among COVID-19 patients aged ≥60 years. METHOD: A prospective cohort study of 114 hospitalized older patients (≥60 years) with confirmed COVID-19 pneumonia between 7 February, 2020 and 6 April, 2020. Epidemiological, socio-demographic, clinical and laboratory data on admission and outcome data were extracted from electronic medical records. All patients were assessed for sarcopenia on admission using the SARC-F scale and the outcome was the development of the severe disease within 60 days. We used the Cox proportional hazards model to identify the association between sarcopenia and progression of disease defined as severe cases in a total of 2908 person-days. RESULT: Of 114 patients (mean age 69.52 ± 7.25 years, 50% woman), 38 (33%) had a high risk of sarcopenia while 76 (67%) did not. We found that 43 (38%) patients progressed to severe cases. COVID-19 patients with higher risk sarcopenia were more likely to develop severe disease than those without (68% versus 22%, p < 0.001). After adjustment for demographic and clinical factors, higher risk sarcopenia was associated with a higher hazard of severe condition [hazard ratio = 2.87 (95% CI, 1.33-6.16)]. CONCLUSION: We found that COVID-19 patients with higher sarcopenia risk were more likely to develop severe condition. A clinician-friendly assessment of sarcopenia could help in early warning of older patients at high-risk with severe COVID-19 pneumonia.

Association between D-dimer level and chest CT severity score in patients with SARS-COV-2 pneumonia.

The elevated level of D-dimer and its relationship with poor outcomes in SARS-COV-2 pneumonia patients have been demonstrated. In addition to a hypercoagulable state, D-dimer is also a biomarker of inflammation. We investigated the relationship between D-dimer level and chest computed tomography (CT) severity score, which could reflect the severity of inflammation in SARS-COV-2 pneumonia patients. We retrospectively enrolled 86 consecutive SARS-COV-2 pneumonia patients. CT severity scores were computed to quantify the overall lung involvement. The D-dimer level among CT score tertiles and the association of the D-dimer level with CT score were analyzed. Our results showed that the median D-dimer level was 0.70 mg/L (IQR 0.35-1.76). 42 patients (48.8%) had D-dimer levels above the median level. The D-dimer levels were significantly different across CT score tertiles (0.37 mg/l [IQR 0.31-0.87], 0.66 mg/l [IQR 0.39-1.43], 1.83 mg/l [IQR 0.85-4.41], P < 0.001). The natural logarithm of the D-dimer level was significantly associated with the CT score (rs = 0.586, P < 0.001). In conclusion, the D-dimer level may be associated with the severity of inflammation of SARS-COV-2 pneumonia prior to coagulopathy/thrombosis. This could be an additional explanation for the mechanism of the relationship between elevated D-dimer level and higher mortality.

Elevated cardiac biomarkers may be effective prognostic predictors for patients with COVID-19: A multicenter, observational study.

PURPOSE: The coronavirus disease 19 (COVID-19) has become a global health event. Cardiac biomarkers like creatine kinase isoenzyme (CK-MB), myoglobin, and high-sensitivity troponin T were usually elevated in early stages. This study aimed to investigate whether the elevated cardiac biomarkers could become effective prognostic predictors for COVID-19 patients. METHODS: The present study involved 357 COVID-19 patients. The potential predictors for two study outcomes (in-hospital death and recovery status) in 28 days were selected by LASSO regression analysis. Prognostic values of cardiac biomarkers selected were evaluated using the receiver operating characteristic curve (ROC) and the area under ROC (AUC). RESULTS: After 28-day follow-up, overall 357 patients were divided into death group (n = 25) and survival group (n = 332), or non-recovery group (n = 43) and recovery group (n = 314). The LASSO regression analysis showed elevated CK-MB and myoglobin were independent risk predictors for in-hospital death, and CK-MB and myoglobin were also independent risk predictors for non-recovery. The AUC of CK-MB and myoglobin for in-hospital death were 0.862 (95%CL: 0.804-0.920, p < 0.001) and 0.838 respectively (95%CL: 0.729-0.947, p < 0.001). The AUC of CK-MB and myoglobin for non-recovery were 0.839 (95%CL: 0.786-0.892, p < 0.001) and 0.841 (95%CL: 0.765-0.918, p < 0.001) respectively. We also found AUC of combined use of CK-MB and myoglobin for in-hospital death and non-recovery were 0.883 (95CL: 0.813-0.952, p < 0.001), and 0.873 (95%CL: 0.817-0.930, p < 0.001) respectively. CONCLUSIONS: In patients with COVID-19, elevated CK-MB and myoglobin on admission may be effective predictors for adverse outcomes, and combined use of CK-MB and myoglobin had a better performance for prediction.

Nomogram for Predicting COVID-19 Disease Progression Based on Single-Center Data: Observational Study and Model Development.

BACKGROUND: In late December 2019, a pneumonia caused by SARS-CoV-2 was first reported in Wuhan and spread worldwide rapidly. Currently, no specific medicine is available to treat infection with COVID-19. OBJECTIVE: The aims of this study were to summarize the epidemiological and clinical characteristics of 175 patients with SARS-CoV-2 infection who were hospitalized in Renmin Hospital of Wuhan University from January 1 to January 31, 2020, and to establish a tool to identify potential critical patients with COVID-19 and help clinical physicians prevent progression of this disease. METHODS: In this retrospective study, clinical characteristics of 175 confirmed COVID-19 cases were collected and analyzed. Univariate analysis and least absolute shrinkage and selection operator (LASSO) regression were used to select variables. Multivariate analysis was applied to identify independent risk factors in COVID-19 progression. We established a nomogram to evaluate the probability of progression of the condition of a patient with COVID-19 to severe within three weeks of disease onset. The nomogram was verified using calibration curves and receiver operating characteristic curves. RESULTS: A total of 18 variables were considered to be risk factors after the univariate regression analysis of the laboratory parameters (P<.05), and LASSO regression analysis screened out 10 risk factors for further study. The six independent risk factors revealed by multivariate Cox regression were age (OR 1.035, 95% CI 1.017-1.054; P<.001), CK level (OR 1.002, 95% CI 1.0003-1.0039; P=.02), CD4 count (OR 0.995, 95% CI 0.992-0.998; P=.002), CD8 % (OR 1.007, 95% CI 1.004-1.012, P<.001), CD8 count (OR 0.881, 95% CI 0.835-0.931; P<.001), and C3 count (OR 6.93, 95% CI 1.945-24.691; P=.003). The areas under the curve of the prediction model for 0.5-week, 1-week, 2-week and 3-week nonsevere probability were 0.721, 0.742, 0.87, and 0.832, respectively. The calibration curves showed that the model had good prediction ability within three weeks of disease onset. CONCLUSIONS: This study presents a predictive nomogram of critical patients with COVID-19 based on LASSO and Cox regression analysis. Clinical use of the nomogram may enable timely detection of potential critical patients with COVID-19 and instruct clinicians to administer early intervention to these patients to prevent the disease from worsening.

The Prognostic Nutritional Index is associated with mortality of COVID-19 patients in Wuhan, China.

BACKGROUND: Declared as pandemic by WHO, the coronavirus disease 2019 (COVID-19) pneumonia has brought great damage to human health. The uncontrollable spread and poor progression of COVID-19 have attracted much attention from all over the world. We designed this study to develop a prognostic nomogram incorporating Prognostic nutritional index (PNI) in COVID-19 patients. METHODS: Patients confirmed with COVID-19 and treated in Renmin Hospital of Wuhan University from January to February 2020 were included in this study. We used logistic regression analysis to find risk factors of mortality in these patients. A prognostic nomogram was constructed and receiver operating characteristics (ROC) curve was drawn to evaluate the predictive value of PNI and this prognostic model. RESULTS: Comparison of baseline characteristics showed non-survivors had higher age (P < .001), male ratio (P = .038), neutrophil-to-lymphocyte ratio (NLR) (P < .001), platelet-to-lymphocyte ratio (PLR) (P < .001), and PNI (P < .001) than survivors. In the multivariate logistic regression analysis, independent risk factors of mortality in COVID-19 patients included white blood cell (WBC) (OR 1.285, P = .039), PNI (OR 0.790, P = .029), LDH (OR 1.011, P < .015). These three factors were combined to build the prognostic model. Area under the ROC curve (AUC) of only PNI and the prognostic model was 0.849 (95%Cl 0.811-0.888) and 0.950 (95%Cl 0.922-0.978), respectively. And calibration plot showed good stability of the prognostic model. CONCLUSION: This research indicates PNI is independently associated with the mortality of COVID-19 patients. Prognostic model incorporating PNI is beneficial for clinicians to evaluate progression and strengthen monitoring for COVID-19 patients.

The association between frailty and severe disease among COVID-19 patients aged over 60 years in China: a prospective cohort study.

BACKGROUND: The coronavirus disease 2019 (COVID-19) has been a pandemic worldwide. Old age and underlying illnesses are associated with poor prognosis among COVID-19 patients. However, whether frailty, a common geriatric syndrome of reduced reserve to stressors, is associated with poor prognosis among older COVID-19 patients is unknown. The aim of our study is to investigate the association between frailty and severe disease among COVID-19 patients aged ≥ 60 years. METHODS: A prospective cohort study of 114 hospitalized older patients (≥ 60 years) with confirmed COVID-19 pneumonia was conducted between 7 February 2020 and 6 April 2020. Epidemiological, demographic, clinical, laboratory, and outcome data on admission were extracted from electronic medical records. All patients were assessed for frailty on admission using the FRAIL scale, in which five components are included: fatigue, resistance, ambulation, illnesses, and loss of weight. The outcome was the development of the severe disease within 60 days. We used the Cox proportional hazards models to identify the unadjusted and adjusted associations between frailty and severe illness. The significant variables in univariable analysis were included in the adjusted model. RESULTS: Of 114 patients, (median age, 67 years; interquartile range = 64-75 years; 57 [50%] men), 39 (34.2%), 39 (34.2%), and 36 (31.6%) were non-frail, pre-frail, and frail, respectively. During the 60 days of follow-up, 43 severe diseases occurred including eight deaths. Four of 39 (10.3%) non-frail patients, 15 of 39 (38.5%) pre-frail patients, and 24 of 36 (66.7%) frail patients progressed to severe disease. After adjustment of age, sex, body mass index, haemoglobin, white blood count, lymphocyte count, albumin, CD8+ count, D-dimer, and C-reactive protein, frailty (HR = 7.47, 95% CI 1.73-32.34, P = 0.007) and pre-frailty (HR = 5.01, 95% CI 1.16-21.61, P = 0.03) were associated with a higher hazard of severe disease than the non-frail. CONCLUSIONS: Frailty, assessed by the FRAIL scale, was associated with a higher risk of developing severe disease among older COVID-19 patients. Our findings suggested that the use of a clinician friendly assessment of frailty could help in early warning of older patients at high-risk with severe COVID-19 pneumonia.

Peripheral blood CD4+ cell counts but not CD3+ and CD8+ cell counts are reduced in SARS-CoV-2 infection.

BACKGROUND: The world is facing the global spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). T cell-induced immune responses during acute SARS-CoV-2 infection have rarely been reported. METHODS: We use cell counting chips and PCR arrays to offer the first insights into the T cell involved in the course of acute SARS-CoV-2 infection. All consecutive patients with suspected SARS-CoV-2 infection treated at the designated hospital between January 2020 and February 2020 were recruited for the study, and cases were confirmed by real-time RT-PCR. Baseline characteristics for inpatients were prospectively collected and analyzed. RESULTS: 96 patients with suspected SARS-CoV-2 infection in our center were screened for inclusion in the study. The median age of the patients was 39.0 years, and 47 (49.0%) were female. Multivariate logistic regression analysis showed that only the CD4+ cell counts were significantly lower in the infection group and slightly higher in the control group. Receiver operating characteristic curve analysis showed good discrimination power between subjects with and subjects without infection. LIMITATIONS: This is a single-center study of patients with a specific ethnic background and lacks a mechanism. CONCLUSIONS: These findings imply the importance of CD4+ T cells (but not CD8+ and CD3+ T cells) in SARS-CoV-2 infection associated pneumonia and indicate that CD4+ T cells might be important for the control of SARS-CoV-2.