EASIX, Modified EASIX and Simplified EASIX as an Early Predictor for Intensive Care Unit Admission and Mortality in Severe COVID-19 Patients.

COVID-19 receives a lot of attention due to its threat to global public health. Research is ongoing to find universal methods to assess the baseline health status of a patient to determine prognosis and management strategies. This study aims to assess the predictive potential of the EASIX (Endothelial Activation and Stress Index) and two of its modifications (mEASIX and sEASIX) in terms of the need for admission to the ICU (intensive care unit), the use of IMV (invasive mechanical ventilation) and death due to COVID-19. The medical data of 370 severely ill patients hospitalised in the COVID-19 departments of the Regional Specialist Hospital in Wroclaw (Poland), including the ICU, were analysed retrospectively. The mortality rate in the group studied was 65.7% (243 cases). In the case of all three indices, EASIX, mEASIX and sEASIX, there was a statistically significant correlation between the need for admission to the ICU (p = 0.026, p = 0.019, p = 0.001, respectively) and the risk of death (p < 0.001). In terms of the risk of death, the high values of the assessed indices (EASIX ≥ 2.36, mEASIX ≥ 704.03, sEASIX ≥ 3.81) were characterised by low sensitivity (≤40%), high specificity (approximately 90%) and low NPV (negative predictive value) (approximately 40%) with high PPV (positive predictive value) (approximately 80%). Due to the ease of implementation and the low cost of performing basic laboratory tests, the above-mentioned indices can be used as an additional, but not universal tool for the initial assessment of the health condition of patients admitted to the hospital.

EASIX, Modified EASIX and Simplified EASIX as an Early Predictor for Intensive Care Unit Admission and Mortality in Severe COVID-19 Patients

COVID-19 receives a lot of attention due to its threat to global public health. Research is ongoing to find universal methods to assess the baseline health status of a patient to determine prognosis and management strategies. This study aims to assess the predictive potential of the EASIX (Endothelial Activation and Stress Index) and two of its modifications (mEASIX and sEASIX) in terms of the need for admission to the ICU (intensive care unit), the use of IMV (invasive mechanical ventilation) and death due to COVID-19. The medical data of 370 severely ill patients hospitalised in the COVID-19 departments of the Regional Specialist Hospital in Wroclaw (Poland), including the ICU, were analysed retrospectively. The mortality rate in the group studied was 65.7% (243 cases). In the case of all three indices, EASIX, mEASIX and sEASIX, there was a statistically significant correlation between the need for admission to the ICU (p = 0.026, p = 0.019, p = 0.001, respectively) and the risk of death (p < 0.001). In terms of the risk of death, the high values of the assessed indices (EASIX ≥2.36, mEASIX ≥704.03, sEASIX ≥3.81) were characterised by low sensitivity (≤40%), high specificity (approximately 90%) and low NPV (negative predictive value) (approximately 40%) with high PPV (positive predictive value) (approximately 80%). Due to the ease of implementation and the low cost of performing basic laboratory tests, the above-mentioned indices can be used as an additional, but not universal tool for the initial assessment of the health condition of patients admitted to the hospital.

SARS-CoV-2 Viral RNA Is Detected in the Bone Marrow in Post-Mortem Samples Using RT-LAMP.

Since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in late 2019, viral RNA has been detected in several different human tissues and organs. This study reports the detection of SARS-CoV-2 RNA in the bone marrow. Post-mortem samples were taken in a sterile manner during two forensic autopsies from the nasopharyngeal region, vitreous humor, cerebrospinal fluid, and bone marrow. SARS-CoV-2 was subsequently diagnosed via Genomtec® SARS-CoV-2 EvaGreen® RT-LAMP CE-IVD Duo Kit. In both postmortem patients, SARS-CoV-2 RNA was detected in bone marrow samples. However, both the vitreous humor and cerebrospinal fluid from the same patients gave negative results using the same test system. The evidence of viral RNA in the bone marrow, along with other reports supports the thesis that SARS-CoV-2 infections are systemic in nature, the consequences of which would profoundly influence both the testing and survival of patients.

When Conventional Oxygen Therapy Fails-The Effectiveness of High-Flow Nasal Oxygen Therapy in Patients with Respiratory Failure in the Course of COVID-19.

High-flow nasal oxygen (HFNO) is recommended as a first-line treatment in patients with acute hypoxemic respiratory failure due to COVID-19. We assessed the effectiveness of HFNO and predictors of failure and death. The medical records of 200 consecutive adult patients treated with HFNO were analysed. Ninety-two patients (46%) were successfully cured, 52 (26%) required noninvasive ventilation, and 61 (30.5%) received intubation. Overall mortality was 40.5%. Risk factors of HFNO ineffectiveness were: SpO2 ≤ 90% with conventional oxygen therapy (HR 0.32, 95% CI 0.19-0.53, p < 0.001), SpO2 ≤ 74% without oxygen therapy (HR 0.44, 95% CI 0.27-0.71, p < 0.001), an age ≥ 60, comorbidities, biomarkers (C-reactive protein, procalcitonin, creatinine, lactate dehydrogenase), duration of symptoms before admission to hospital ≤ 9 days, start of treatment with HFNO ≤ 4 days. The multivariate logistic regression models (age ≥ 60, comorbidities, C-reactive protein concentration and SpO2 with oxygen therapy) revealed a high predictive value of death and HFNO failure (AUC 0.851, sensitivity 0.780, specificity 0.802; AUC 0.800, sensitivity 0.776, specificity 0.739, respectively). HFNO is a safe method for treating acute hypoxemic respiratory failure, with effectiveness reaching nearly 50%. Low values of SpO2 without and during oxygen therapy seem to be good diagnostic tools for predicting death and HFNO failure.

The chest radiographic scoring system in initial diagnosis of COVID-19: Is a radiologist needed?

BACKGROUND: Lung imaging, next to a polymerase chain reaction (PCR) test, is a key diagnostic tool in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The degree of abnormalities correlates with clinical outcome. Imaging of the lungs using chest radiography (CXR) at the peak of a pandemic is considered a basic diagnostic tool at the triage stage. The CXR images are less characteristic than computed tomography (CT) and should be interpreted with a combination of clinical findings. OBJECTIVES: Comparison of the usefulness of 2 CXR severity scores to evaluate the presence/severity of inflammation in the course of COVID-19 and the possibility of a non-radiologist to interpret the image independently. MATERIAL AND METHODS: Retrospective analysis of the medical records of 152 consecutive patients (aged 19-96, 73 men), infected with SARS-CoV-2, confirmed using real-time PCR (RT-PCR). Five-point and twelve-point CXR severity scoring systems were used (independently by a radiologist and a referring physician) to assess the severity of inflammation. RESULTS: In 77 of 152 cases, the CXR revealed features of inflammation. Bilateral abnormalities were found in 48/77 (62.3%) cases. Statistically, the lower lobes were involved more often than the upper ones (p < 0.001) and the left lobe more often than the right one (p < 0.001). The intensity of the abnormalities using both scales correlated with the persistence of symptoms (p = 0.0133 and p = 0.0403). A positive and statistically significant correlation was found between both scales and dyspnea, decreased oxygen saturation, elevated C-reactive protein (CRP), ferritin, D-dimer, lactate dehydrogenase, and alanine aminotransferase activity. The interobserver agreement analysis did not show a statistically significant difference in the CXR severity score using the five-point (B = 0.8345, kappa = 0.82; p = 0.1480) or the twelve-point scale (B = 0.8219, kappa = 0.77; p = 0.0502). CONCLUSIONS: The CXR severity score is a useful tool to assess the inflammation in the initial diagnosis of coronavirus disease 2019 (COVID-19). Quantifying lung abnormalities accurately may be performed by a referring physician. Both CXR severity scales correlate well with clinical parameters.

Value of quantitative analysis in lung computed tomography in patients severely ill with COVID-19.

INTRODUCTION: Quantitative computed tomography (QCT) is used to objectively assess the degree of parenchymal impairment in COVID-19 pneumonia. MATERIALS AND METHODS: Retrospective study on 61 COVID-19 patients (severe and non-severe; 33 men, age 63+/-15 years) who underwent a CT scan due to tachypnea, dyspnoea or desaturation. QCT was performed using VCAR software. Patients' clinical data was collected, including laboratory results and oxygenation support. The optimal cut-off point for CT parameters for predicting death and respiratory support was performed by maximizing the Youden Index in a receiver operating characteristic (ROC) curve analysis. RESULTS: The analysis revealed significantly greater progression of changes: ground-glass opacities (GGO) (31,42% v 13,89%, p<0.001), consolidation (11,85% v 3,32%, p<0.001) in patients with severe disease compared to non-severe disease. Five lobes were involved in all patients with severe disease. In non-severe patients, a positive correlation was found between severity of GGO, consolidation and emphysema and sex, tachypnea, chest x-ray (CXR) score on admission and laboratory parameters: CRP, D-dimer, ALT, lymphocyte count and lymphocyte/neutrophil ratio. In the group of severe patients, a correlation was found between sex, creatinine level and death. ROC analysis on death prediction was used to establish the cut-off point for GGO at 24.3% (AUC 0.8878, 95% CI 0.7889-0.9866; sensitivity 91.7%, specificity 75.5%), 5.6% for consolidation (AUC 0.7466, 95% CI 0.6009-0.8923; sensitivity 83.3%, specificity 59.2%), and 37.8% for total (GGO+consolidation) (AUC 0.8622, 95% CI 0.7525-0.972; sensitivity 75%, specificity 83.7%). The cut-off point for predicting respiratory support was established for GGO at 18.7% (AUC 0.7611, 95% CI 0.6268-0.8954; sensitivity 87.5%, specificity 64.4%), consolidation at 3.88% (AUC 0.7438, 95% CI 0.6146-0.8729; sensitivity 100%, specificity 46.7%), and total at 23.5% (AUC 0.7931, 95% CI 0.673-0.9131; sensitivity 93.8%, specificity 57.8%). CONCLUSION: QCT is a good diagnostic tool which facilitates decision-making regarding intensification of oxygen support and transfer to an intensive care unit in patients severely ill with COVID-19 pneumonia. QCT can make an independent and simple screening tool to assess the risk of death, regardless of clinical symptoms. Usefulness of QCT to predict the risk of death is higher than to assess the indications for respiratory support.