Interleukin-6 in SARS-CoV2 risk stratification

Introduction: Since the emergence of COVID19, a broad spectrum of presentation has been described, from the absence of symptoms to critical illness. Some studies show that increased levels of interleukin-6 (IL-6) are correlated with increased mortality and disease severity. Objective(s): To establish the value of IL-6 as an early predictor of severity in SARS-CoV2 infection. Method(s): Prospective study with IL-6 assay as part of the initial study of patients with SARS-CoV2 infection, between 20/10/2021 and 31/01/2022. Two groups were created (I: without hospitalization;II: with hospitalization). Exclusion criteria: chronic respiratory disease, rheumatologic disease and/or inflammatory bowel disease;time between dosing and hospitalization >=72h. Statistics (SPSS v28): Mann Whitney test, AUROC, Spearman correlation. Result(s): Sample of 117 patients (after excluding 10). Group I: 80 patients, 38 (47.5%) were male;mean age of 46.40 +/- 18.85 years old (18-88). Group II: 37 patients, 24 (64.9%) were male;mean age of 72.35 +/- 15.39 years old (29-96). Mean hospital stay of 19.49 +/- 17.02 days;9 (24.3%) were admitted to the ICU. Significantly higher IL-6 values in group II (p<0.001), showing good discriminating power regarding the probability of hospitalization (AUC=0.888;p<0.001) and a statistically significant (p=0.02) positive correlation (0.380) with the length of stay. The optimal cut-off value of IL-6 to establish the need for hospitalization, in our sample, was 12.4 pg/mL (Sensitivity: 97%;Specificity: 69%;Youden index: 0.66). Conclusion(s): IL-6 levels were significantly higher in patients requiring hospitalization and correlated with length of hospital stay. Larger studies are needed to validate its use in risk stratification.

Does the accuracy of clinician diagnosis of COVID-19 compared to RT-PCR in adults depend on the number and severity of comorbidities?

Background: Due to the high transmissibility of SARS-Cov-2, the virus causing COVID-19, accurate diagnostic methods are essential for effective infection control, but the gold standard method of real-time polymerase chain reaction (RT-PCR) is costly, slow, and test capacity has at times been insufficient. Method(s): Diagnosis data were retrieved from registers, based on positive RT-PCR or ICD-10 codes set by clinicians. Through linkage to a population-representative adult cohort in Sweden, we assessed the accuracy of clinician diagnosis against RT-PCR, stratified by number and severity of comorbidities. Result(s): A total of 42,621 subjects were included. Of these, 6,560 had COVID-19. Clinician diagnosis was found in 5,705 subjects, while 3,936 had a positive RT-PCR and 3,081 got diagnosed with both methods. Of those with at least one comorbidity, sensitivity for clinician diagnosis ranged from 69% (95% CI 44-86) for those with two "severe" comorbidities (diabetes and chronic obstructive pulmonary disease) to 84% (95% CI 73-91) for those with two "moderately severe" comorbidities (asthma and hypertension). Specificity was > 90% for all comorbidity groups. Youden's index increased slightly with the number of comorbidities in both "severe" and "moderately severe" categories, but for those with "light" comorbidities (eczema, rhinitis, sleep disorders), it was the lowest with >=2 comorbidities (69% (95% CI 66-72)). Youden's index was 71% (95% CI 70-72) for those with no comorbidities and 71% (95% 69-73) for the whole cohort. Conclusion(s): Clinicians identify non-cases to a high degree, but RT-PCR is needed for adequate sensitivity, regardless of comorbidity.

The ability of Lung High-Resolution Computed Tomography Severity Score to early identify COVID-19 patients who need respiratory support. A retrospective analysis of a monocentric Italian COVID-19 cohort

Objectives: to evaluate the relationship of a quantitative severity score (SS) of lung involvement, derived from nonenhanced Chest High-Resolution Computed Tomography (HRCT), with COVID-19 disease severity and the ability to early identify patients who need respiratory support with continuous positive airway pressure (CPAP) and/or noninvasive mechanical ventilation (NIMV) during follow-up. Method(s): We retrospectively evaluated a cohort of consecutive enrolled patients hospitalized for COVID-19 in an academic hospital in Rome during the first spread of SARS-CoV2 infection. All the enrolled patients underwent HRCT at admission and standardized evaluation of the SS. The study outcome was the need of CPAP and/or NIMV during follow-up. Result(s): We enrolled 39 patients with a median disease duration of 5 days. The median (25degree-75degree percentile) SS at baseline was 5 (2-7). We grouped patients according to tertile distribution of SS. Median pO2/FIO2 ratio progressively decreased from low SS group (SS 0-3) to high SS group, p 0.02. SS positively correlated with pneumonia prognostic scores SOFA (r=0.36, p 0.044) and MEWS (r = 0.33, p 0.038). The SS ROC AUC in predicting the need of respiratory support was 0.74 (95% CI, 0.58-0.90). Using 5 as Youden index cut-off, the sensitivity and specificity of SS were 0.83 and 0.59 respectively. Conclusion(s): The SS obtained from baseline lung CT is related to the clinical and laboratory severity of lung involvement in COVID-19 and with the impairment of gas exchange.

Title Lung ultrasound vs. CT scan for the assessment of post-ICU long COVID

Introduction: Long COVID includes signs and symptoms after acute COVID-19 [1]. Lung ultrasound (LUS) is increasingly used for lung assessment [2], but many patients still undergo traditional imaging (chest CT) for long COVID evaluation. Aims and objectives: To test the capability of LUS to identify post-ICU COVID-19 patients with significant alterations at chest CT scan. Method(s): Single-center retrospective study on post-ICU patients in recovery phase of long COVID. Patients were included if they had a complete LUS with computation of the LUS score and chest CT performed during the follow-up evaluation at least one month after hospital discharge. CT were classified by an expert radiologist as significant if focal/diffuse involvement was observed, as not significant if lung aeration was normal. Result(s): 40 patients were included so far (age 60.0 [51.0-66.0], males 73.8%, BMI 29.1 [27.7 - 29.4] kg/m2). Significant CTs were 15 (37.5%);LUS score was higher in these patients (7.0 [4.0-9.0] vs. 0.0 [0.0-4.0];p=0.0004). LUS score had an area under the ROC curve of 0.8347 [95% CI 0.7033-0.9662] for significant CT (Youden index cut off point >=3, sensitivity 86.7%, specificity of 70.8%). Conclusion(s): LUS score accurately identifies post-ICU long COVID patients with significant alterations at CT scan.

Prognostic value of the SII Systemic Immune-Inflammation Index a novel biomarker in coronavirus disease 2019 patient's disease progression to fatality

Objective: To identify a novel biomarker with high prognostic value SII Systemic Immune-Inflammation Index in the disease progression of COVID-19 patients with its cost effectiveness and less time consuming. Methodology: This cross-sectional study was carried out from November 2021 to February 2022 at the Mardan Medical Complex, Khyber Pakhtunkhwah, Pakistan. The receiver operating characteristic (ROC) curve analysis was used to discover the ideal cut-off values for predictors for disease severity stage, i.e. asymptomatic, mild, moderate, severe, critical, based on their greatest Youden's index. The SII (platelet X neutrophil count/lymphocyte counts) formula was used to compute the systemic immune inflammation index. Result(s): Of the 311 cases studied, 233 were included;155 (66.52%) were male and 78 (33.47%) females. Median age was 38 years (IQR: 18 - 79). Patients had a significant increase in various blood parameters, with an increase in SII index between admission and hospitalization. Normal patients had a SII median 398 (IQR: 312 - 567) upon admission, while abnormal patients had a SII median 659 (IQR: 475 - 1540). Throughout hospitalization, SII index of asymptomatic patients median was 684 (IQR: 470 - 933);cut-off value >= 358, mild patients median 909 (IQR: 183 - 1930);cut-off value >= 501, moderate patients median >= 992 (IQR: 248 - 6099);cut-off value >= 903, severe patients median 1063 (IQR: 104 - 5014);cut-off value >= 1147, critical patients median 1230 (IQR: 100 - 8438);cut-off value >= 1481. Conclusion(s): SII was found to be a significant predictor of COVID-19 patients' severity progression to fatality as an independent prognostic factor. SII is being recommended as a low-cost and less time-consuming blood test for COVID-19 patients.Copyright © 2023, Pakistan Medical Association. All rights reserved.

Comparison of clinician diagnosis of COVID-19 against real-time polymerase chain reaction in a general adult population

Background: Whilst the gold standard real-time polymerase chain reaction (RT-PCR) is costly and can take time to obtain results, there is a dearth of data comparing clinician diagnosis based on recommended ICD codes and RTPCR. Aim(s): In this study, we compared clinician diagnosis of COVID-19 with RT-PCR in a general adult population and evaluated any differences in accuracy by age, gender, pre-COVID-19 BMI, and obstructive airway diseases. Material(s) and Method(s): Data from a cohort of 42,621 adult-representative samples in Sweden, included 5705 clinician-diagnosed and 3936 RT-PCR-diagnosed COVID-19 patients. Using RT-PCR as the reference standard, estimates of the accuracy of clinician's diagnosis were determined. Result(s): The sensitivity and specificity of clinician diagnosis in identifying COVID-19 was 78% (95%CI 77-80%) and 93% (95%CI 93-93%), respectively. The positive predictive value was 54% (95%CI 53-55%), negative predictive value was 98% (95%CI 98-98%) and the Youden's Index was 71% (95%CI 70-72%). These accuracy measures were similar between men and women, across age groups, BMI categories, and between patients with and without asthma. However, while the specificity, negative predictive value, and Youden's index were similar between patients with and without COPD, the sensitivity was slightly higher in patients with COPD (84%, 95%CI 74-90%) than those without (78%, 95%CI 77-79%) COPD. Conclusion(s): The accuracy of clinician's diagnosis for COVID-19 is adequate, regardless of gender, age, pre-COVID19 BMI, asthma, and COPD, thus can be used for screening purposes to supplement RT-PCR.

Comparison of clinician diagnosis of COVID-19 with real time polymerase chain reaction in an adult-representative population in Sweden.

BACKGROUND: Due to the high transmissibility of SARS-CoV-2, accurate diagnosis is essential for effective infection control, but the gold standard, real-time reverse transcriptase-polymerase chain reaction (RT-PCR), is costly, slow, and test capacity has at times been insufficient. We compared the accuracy of clinician diagnosis of COVID-19 against RT-PCR in a general adult population. METHODS: COVID-19 diagnosis data by 30th September 2021 for participants in an ongoing population-based cohort study of adults in Western Sweden were retrieved from registers, based on positive RT-PCR and clinician diagnosis using recommended ICD-10 codes. We calculated accuracy measures of clinician diagnosis using RT-PCR as reference for all subjects and stratified by age, gender, BMI, and comorbidity collected pre-COVID-19. RESULTS: Of 42,621 subjects, 3,936 (9.2%) and 5705 (13.4%) had had COVID-19 identified by RT-PCR and clinician diagnosis, respectively. Sensitivity and specificity of clinician diagnosis against RT-PCR were 78% (95%CI 77-80%) and 93% (95%CI 93-93%), respectively. Positive predictive value (PPV) was 54% (95%CI 53-55%), while negative predictive value (NPV) was 98% (95%CI 98-98%) and Youden's index 71% (95%CI 70-72%). These estimates were similar between men and women, across age groups, BMI categories, and between patients with and without asthma. However, while specificity, NPV, and Youden's index were similar between patients with and without chronic obstructive pulmonary disease (COPD), sensitivity was slightly higher in patients with (84% [95%CI 74-90%]) than those without (78% [95%CI 77-79%]) COPD. CONCLUSIONS: The accuracy of clinician diagnosis for COVID-19 is adequate, regardless of gender, age, BMI, and asthma, and thus can be used for screening purposes to supplement RT-PCR.

Evaluation of the performance of two commercial SARS-CoV-2 neutralizing antibody test kits

Objective To evaluate the performance of two commercial EIA kits for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) neutralizing antibodies. Methods Two commercial SARS-CoV-2 neutralizing antibody ELISA test kits (A and B) were used to detect serum panel consists of the following sera: 44 collected before vaccination, 120 collected one month after vaccination and 64 collected six months after recovery from convalescent patients of COVID-19. In the meantime, the above samples were also taken for live virus micro-neutralization test (micro-NT) indicated as the 50% neutralization antibody titer (NT50 ) . The consistency of qualitative and quantitative results between the two commercial kits and live virus neutralization test was analyzed. Results Taking the micro-NT results as the standard, the positive coincidence rates of A and B kits were 97. 40% and 100. 00%, respectively;the negative coincidence rates were 97. 30% and 95. 95%, respectively;the Youden indices were 0. 95 and 0. 96, respectively. Furthermore, quantitative analysis indicated that the correlation coefficients between A and B kits and micro-NT results were 0. 24 (P<0. 05) and 0. 52 (P<0. 000 1) for samples collected after vaccination, respectively;while the correlation coefficients were 0. 81 (P<0. 000 1) and 0. 89 (P<0. 000 1) for convalescent serum samples, respectively. Conclusions The results obtained by the two commercial neutralizing antibody detection kits were in good agreement with the qualitative results of micro-NT. The neutralizing antibody titers in convalescent serum samples detected by the two kits showed a stronger correlation with the micro-NT results. © 2022 Society of Microbiology and Immunology. All rights reserved.

PERFORMANCE of the KOBAYASHI SCORE and MODIFIED KOBAYASHI SCORE in PREDICTING RESISTANCE to INTRAVENOUS IMMUNOGLOBULIN in PATIENTS with PEDIATRIC INFLAMMATORY MULTISYSTEM SYNDROME ASSOCIATED with SARS-COV-2

Background: Pediatric Infammatory Multisystem Syndrome Associated With SARS-CoV-2 (PIMS) is a new insidious disease which in several points may mimic Kawasaki disease. Patients diagnosed with one of the aforementioned conditions are initially treated with intravenous immunoglobulin (IVIG). However, up to 20% of children diagnosed with Kawasaki disease appear to be resistant to such therapy. Similarly, substantial portion of PIMS patients requires second line treatment including systemic glucocorticoids. There are several calculative models, including the Kobayashi Score, which are utilized to predict patients' response to such treatment. To our best knowledge, the scoring systems derived from Kawasaki disease have not yet been assessed whether they can fulfl similar role in PIMS patients. Objectives: There were two essential questions to be addressed in the study: (1) Can the Kobayashi Score be utilized in making clinical decisions regarding concomitant treatment in PIMS patients? (2) Is there any modifcation that may increase the accuracy of the original score? Methods: First step of the study involved 19 patients diagnosed with PIMS between July 2020 and June 2021. The statistical analysis including each parameter of the Kobayashi Score has been performed in order to determine potential alterations of the score. Then, the numerous variants of modifed score have been compared in terms of their positive and negative predictive values in order to determine new PIMS IVIG Resistance Score (PIRS). In the next phase of the study, both scores have been validated in the second cohort involving 16 patients diagnosed with PIMS between July and December 2021. The fnal assessment has been performed in the unifed study group (35 PIMS patients). Results: The Kobayashi Score (see Table 1) signifcantly differentiated PIMS patients in terms of good response or resistance to IVIG (p=0.03967). However, the score returned a few false positive (3 out of 9) and false negative (2 out of 10) results. After step-by-step verifcation of clinical and laboratory parameters, authors developed a tentative PIRS (see Table 1) including the following criteria: hyponatremia, days of fever and platelet count (derived from the Kobayashi Score but with different cut-off levels) supplemented with procalcitonin level and percentage of lymphocytes. In the validatory phase of the study, both scores had equal accuracy to predict treatment response. The analysis of receiver operating characteristic curve in the unifed study group has shown better performance of PIRS (Youden index 0,72) than the Kobayashi Score (Youden index 0,49). Conclusion: The Kobayashi Score is worth being considered to estimate the risk of resistance to IVIG in PIMS patients. Nonetheless, it is not free from false positive and false negative results. The postulated modifed score called PIRS can become a promising alternative but it requires further validation in larger cohorts of patients.

Serum LDH: a potential surrogate to chest radiograph in pediatric Covid-19 patients to reduce radiation exposure

Background: Chest radiographs are frequently used to evaluate pediatric patients with COVID-19 infection during the current pandemic. Despite the minimal radiation dose associated with chest radiography, children are far more sensitive to ionizing radiation's carcinogenic effects than adults. This study aimed to examine whether serum biochemical markers could be potentially used as a surrogate for imaging findings to reduce radiation exposure. Methods: The retrospective posthoc analysis of 187 pediatric patients who underwent initial chest radiographs and serum biochemical parameters on the first day of emergency department admission. The cohort was separated into two groups according to whether or not the initial chest radiograph revealed evidence of pneumonia. Spearman's rank correlation was used to connect serum biochemical markers with observations on chest radiographs. The Student's t-test was employed for normally distributed data, and for non-normally distributed data, the Mann–Whitney U test was used. A simple binary logistic regression was used to determine the importance of LDH in predicting chest radiographs. The discriminating ability of LDH in predicting chest radiographs was determined using receiver operating characteristics (ROC) analysis. The cut-off value was determined using Youden's test. Interobserver agreement was quantified using the Cohen k coefficient. Results: 187 chest radiographs from 187 individual pediatric patients (95 boys and 92 girls;mean age ± SD, 10.1 ± 6.0 years;range, nine months–18 years) were evaluated. The first group has 103 patients who did not have pneumonia on chest radiographs, while the second group contains 84 patients who had evidence of pneumonia on chest radiographs. GGO, GGO with consolidation, consolidation, and peri-bronchial thickening were deemed radiographic evidence of pneumonia in group 2 patients. Individuals in group 2 with radiological indications of pneumonia had significantly higher LDH levels (p = 0.001) than patients in group 1. The Spearman's rank correlation coefficient between LDH and chest radiography score is 0.425, showing a significant link. With a p-value of < 0.001, the simple binary logistic regression analysis result validated the relevance of LDH in predicting chest radiography. An abnormal chest radiograph was related to LDH > 200.50 U/L (AUC = 0.75), according to the ROC method. Interobserver agreement between the two reviewers was almost perfect for chest radiography results in both groups (k = 0.96, p = 0.001). Conclusion: This study results show that, compared to other biochemical indicators, LDH has an 80.6% sensitivity and a 62% specificity for predicting abnormal chest radiographs in a pediatric patient with confirmed COVID-19 infection. It also emphasizes that biochemical measures, rather than chest radiological imaging, can detect the pathogenic response to COVID-19 infection in the chest earlier. As a result, we hypothesized LDH levels might be potentially used instead of chest radiography in children with COVID-19, reducing radiation exposure.

RDW : useful prognostic marker in acute COVID -19 infection

COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has been associated with over 5 million deaths worldwide since December 2019. Red cell distribution width (RDW) is a routine full blood count parameter that reflects the level of change in size between red cells (anisocytosis) and has been widely researched as an independent predictor of mortality in different hospital settings, including critically ill patients with sepsis. This study aims to investigate if RDW results on admission may be used as a prognostic marker in patients with acute COVID-19 infection. This retrospective study included 81 hospitalised patients with COVID-19 at the General Hospital in Jersey (Channel Islands, UK), subject to inclusion criteria. Differences between groups were calculated using the t test if data were normally distributed, otherwise the Mann-Whitney test was used. p < 0.05 was considered significant for all tests. Area under curve (AUC) and the 95% confidence interval (CI) were determined to establish optimal cut-off point that maximised sensitivity and specificity to predict death by the Youden's index. Logistic regression was then used to determine the odds of in-hospital mortality. Non-survivors were found to be significantly older (median age: 82 years;overall range: 50-94 vs. 74 years;overall range: 28-92 in survivors;p = 0.003) and presented with higher RDW when compared with survivors (14.1 vs. 13.4;p = 0.028). A total of 63 patients (78%) received ward-based care, while 18 patients (22%) required intensive care. Men accounted for most deaths (males: 16 deaths, 59.3% vs. females: 11 deaths, 40.7%), although the mortality rate in males and females was undistinguishable (males: 33.3% vs. females: 33.3%). Multivariate logistic analysis demonstrated that RDW >14% on admission was associated with a 5-fold increased mortality risk in hospitalised patients with COVID-19 (OR = 5.335 [95% CI 1.524-18.674];p = 0.009). This association was shown to be independent of age and other potential confounders such as lymphocyte count, white cells, or creatinine levels. This study confirms the prognostic potential of RDW in hospitalised patients with COVID-19. Identifying patients with higher risk of in-hospital mortality may enable prioritisation of resources and targeted treatments, which could ultimately improve outcomes.

The prognostic accuracy of neutrophillymphocyte ratio in COVID-19 patients

Aims/Objectives/Background COVID-19 is a newly emerging pandemic viral disease. Multiple management guidelines were introduced;nevertheless, their efficacy is still under debate. Thus, the presences of prognostic factors are essential for predicting which patients will need more invasive treatments. The study aims to investigate the prognostic accuracy of neutrophil-lymphocyte ratio in COVID-19 infection. Methods/Design This is a prospective study done in Al-Ain Hospital in the United Arab Emirates. All the Covid-19 patients presenting to the hospital were enrolled over one month from 20/3 to 20/4/2020. We gathered information about their age, sex, mode of transmission and calculated their Neutrophils/Lymphocytes ratio (NLR) from the first complete blood picture on admission. We divided the patients into two groups: those aged 50 years and above and those aged less than 50 years. We chose the best NLR cutoff value based on the Youden index and receiver operating characteristic (ROC) curve analysis. The target endpoint was the presence or absence of intensive care unit (ICU) admission. Results/Conclusions The study revealed that 48 patients (14%) needed ICU admission, while 296 patients (86%) were admitted to a ward or quarantine facilities. When the patient's age was > 50, and NLR was ≥ 3.10, it showed a sensitivity of 95.24% and a specificity of 92.86% for predicting the need for ICU admission. When NLR was ≥ 4.21, and the patient's age was < 50, the sensitivity and specificity were 70.3% and 93.7%, respectively. NLR proved to be highly specific and sensitive in helping to identify patients who need more invasive care among people over 50 years of age with COVID-19. Additionally, it can be used as a ruling out gadget for low-risk patients among people under 50 years old.

Utilizing the Charleston Comorbidity Index as an Independent Predictor for Outcomes in SARS-Cov-2 Positive Patients

Background. Since COVID-19 was declared a pandemic, it has seemed that the virus is nondiscriminatory causing 3.73 million deaths worldwide. The Charleston Comorbidity Index (CCI) is a scoring system predicting the one-year mortality for patients with a range of comorbid conditions and is widely used as a predictor of prognosis and survival for a range of pathologies. This study aims to assess if there is an impact of comorbidity burden on COVID-19 patients by utilizing their CCI score. Charleston Comorbidity Index Score Scoring system for Charleston Comorbidity Index (CCI). Plus 1 point for every decade age 50 years and over, maximum 4 points. Higher scores indicate a more severe condition and consequently, a worse prognosis. Methods. Multicenter, retrospective review of patients diagnosed with COVID-19 from January 2020 to September 2020 throughout the HCA Healthcare system. CCI scores for all COVID-19 positive patients were calculated and logistic regression analysis was performed to predict hospitalization and ICU admission by CCI controlling for age, sex and race. A multinomial regression model was also performed to predict discharge status by CCI controlling for age, sex and race. ROC curves to indicate the CCI cut-off point for each outcome (hospitalization, ICU admission and mortality) was performed, and Youden's Index was used to identify the optimal point. Results. In the study timeframe, 92,800 patients were diagnosed with COVID-19 and of those, 48,270 were hospitalized. A one-point increase in CCI was associated with higher odds of hospitalization [OR 1.718;95% CI 1.696-1.74]. The threshold for significance to predict hospitalization was a CCI of 1.5 (AUC 0.804, Youden Index 0.48) with a specificity (73%) and sensitivity (75%). A one-point increase in CCI was associated with 1.444 higher odds of an ICU admission (95% CI 1.134-1.155). A one-point increase in CCI significantly increased the odds of discharge to hospice compared to any discharge other than hospice [OR 1.162;95% CI 1.142-1.182]). A one-point increase in CCI score was associated with 1.188 higher odds of in-hospital mortality (95% CI, 1.173-1.203) with a CCI threshold of 3.5 having the highest specificity (50.9%) and sensitivity (79.9%) to predict mortality outcome (AUC 0.704, Youden Index 0.31). Conclusion. In conclusion CCI score is an adequate predictor of hospitalization and in-hospital mortality but less so in predicting ICU admission in COVID-19 positive patients.

Development a Novel Score (SAD-60) for Predicting Mortality in Hospitalised Patients with COVID-19 Pneumonia: A Multicenter Retrospective Study of 1013 Patients

Background. We aimed to explore a novel risk score to predict mortality in hospitalised patients with COVID-19 pneumonia. In additoon, we compared the accuracy of the novel risk score with CURB-65, qSOFA and NEWS2 scores. Methods. The study was conducted in hospitalised patients with laboratory and radiologically confirmed COVID-19 pneumonia between November 1, 2020 and November 30, 2020. In this retrospective multicenter study. independent predictors were identified using multivariate logistic regression analysis. A receiver operating characteristics (ROC) analysis with area under the curve (AUC) was used to evaluate the performance of the novel score. The optimal cut-off points of the candidate variables were calculated by the Youden's index of ROC curve. Mortality was defined as all cause in-hospital death. Results. A total of 1013 patients with COVID-19 were included. The mean age was 60,5 ±14,4 years, and 581 (57,4%) patients were male. In-hospital death was occured in 124 (12,2%) patients. Multivariate analysis revealed that peripheral capillary oxygen saturation (SpO2), albumin, D-dimer, and age were independent predictors for mortality (Table). A novel scoring model was named as SAD-60 (SpO2, Albumin, D-dimer, ≥60 years old). SAD-60 score (0,776) had the highest AUC compared to CURB-65 (0,753), NEWS2 (0,686), and qSOFA (0,628) scores (Figure). Conclusion. We demonstrated that SAD-60 score had a promising predictive capacity for mortality in hospitalised patients with COVID-19. Univariate and multivariate analysis of factors predicting mortality Comparison of CURB-65, qSOFA, NEWS-2 and SAD-60 for predicting pneumonia mortality in hospitalised patients with COVID-19 by ROC analysis.

Meta-Analysis of D-Dimer, hsCRP and Cytokines in COVID-19 Severe/Critical Patients in China

Objective: To analyze the relationship between D-dimer, inflammatory markers, cytokines and disease severity, and the possibility of early identification of COVID-19 critical type patients. Methods: PubMed, EMBASE and CNKI databases were searched by computer, and references of related reviews and systematic reviews were manually searched as supplements. The retrieval deadline is February 9, 2021. According to the inclusion and exclusion criteria, the literatures were screened and the quality was evaluated, and then the data were extracted for meta-analysis. The fixed/random effects model was used to calculate the weighted mean difference (WMD) and 95% CI to evaluate whether the levels of D-dimer, hsCRP, IL-6, IL-8, IL-10 and TNF-α in critical type patients were statistically different from those in severe type patients. If there were statistical differences, logistic regression analysis was used, and establish the receiver operating characteristic curve (ROC) and area under the curve (AUC) of each index for the diagnosis of critical type patients. The best diagnostic value of COVID-19 critical type patients was calculated by Youden index. Results: A total of 3519 literatures entered the screening process. According to the inclusion and exclusion criteria, 40 articles were finally included in this study, and all of them were high-quality studies after evaluation. The results of meta-analysis showed that the levels of D-dimer, hsCRP, IL-6, IL-8 and IL-10 in critical type group were significantly higher than those in severe type group (P<0.05). Based on ROC curve, the AUC of D-dimer was 0.785 (95% CI: 0.671-0.899), AUC of hsCRP was 0.884 (95% CI: 0.632-1.000), AUC of IL-6 was 0.819 (95% CI: 0.700-0.939), which had diagnostic significance for critical type patients (P<0.05). The optimal diagnostic threshold of D-dimer was ≥2.00 mg/L (sensitivity 89.3%, specificity 64.0%);the optimal diagnostic threshold of hsCRP was ≥64.22 mg/L (sensitivity 75.0%, specificity 100%);the optimal diagnostic threshold of IL-6 was ≥33.01 ng/L (sensitivity 68.0%, specificity 92.0%). Conclusion: The levels of D-dimer, hsCRP, IL-6, IL-8 and IL-10 in COVID-19 critical type patients were significantly higher than those in severe type patients. Our results might be helpful in identify and risk reduction of mortality in critical types patients infected with COVID-19. Disclosures: No relevant conflicts of interest to declare.

Pediatric COVID-19-associated hyper-inflammation score: The virus registry predictive analytic study

INTRODUCTION: Several adult and pediatric studies demonstrate a correlation between elevated inflammatory markers and COVID-19 disease severity. The Society of Critical Care Medicine (SCCM) Discovery Viral Infection and Respiratory Illness Universal Study (VIRUS) COVID-19 registry was used to develop Pediatric COVID Hyperinflammation Syndrome (PcHIS) score and evaluate the association between PcHIS and severe COVID illness in children. METHODS: Children under 18 years of age hospitalized due to COVID-19 were filtered from VIRUS registry (NCT 04323787). Neonates and children incidentally positive for COVID were excluded. For the development of PcHIS score we used 7 variables: fever, hematologic dysfunction (platelet, leucocyte count), elevated ferritin, elevated D-dimer, cytokinemia (CRP, procalcitonin, IL-6), hepatic injury (ALT, AST, albumin) and elevated cardiac enzymes (BNP, Troponin). ROC curves were generated for each variable to choose the best discriminatory (J point of Youden Index) value for identification of severe disease (anyone requiring respiratory support more than O2 by NC, vasoactive meds, ECMO, or dialysis). Each abnormal value got one point and the additive PcHIS score was calculated for the best discriminatory score for identification of severe disease (using ROC). RESULTS: Out of a total of 1123 patients aged < 18 years with COVID-19 in the registry, 722 were included for PcHIS development;rest had missing data. A 1/3rd in the cohort had severe COVID disease. Odds of severe disease were higher with fever > 39°C (OR1.5;CI1.05-2.14), presence of any hematologic dysfunction (platelets < 250k/μL or WBC > 6650/μL) (OR 7.12;CI 2.52-20.05), cytokinemia (CRP >6.7 mg/dL or procalcitonin > 3.4) (OR 4.99;CI 3.05-8.17), ferritin level > 270 mg/dL (OR 3.87;CI 2.38-6.28), elevated cardiac enzymes (BNP > 685 or Troponin > 0.03) (OR 3.08;CI1.96-4.85), hepatic injury (AST >50 or ALT >40 or albumin< 3.5 g/dL) (OR 3.25;CI 2.16-5.0), D-dimer > 2000 ng/ml (OR 2.46;CI1.59-3.8). A PcHIS score of 2.5 had a sensitivity of 69.2% and a specificity of 62.1% with ROC area under curve of 0.70 (95% CI: 0.66-0.74;p< 0.001). CONCLUSIONS: PcHIS score may be calculated from early laboratory data and is useful in predicting severe disease in children with COVID-19. Its role in clinical practice needs to be determined in a prospective study.