Advances in COVID-19 and Cancer

This retrospective cohort study aimed to evaluate the association between ambulatory status at discharge and six-month post-discharge mortality among adults with coronavirus disease (COVID-19). We analyzed data from 398 patients aged over 18 admitted to a tertiary hospital in South Korea between December 2019 and June 2022. Patients were classified into two groups based on their ambulatory status at discharge: ambulatory (able to walk independently, n = 286) and non-ambulatory (unable to walk independently, requiring wheelchair or bed-bound, n = 112). Our analysis revealed that six-month survival rates were significantly higher in the ambulatory group (94.2%) compared to the non-ambulatory group (84.4%). Multivariate analysis identified ambulatory status at discharge (p = 0.047) and pre-existing malignancy (p = 0.007) as significant prognostic factors for post-discharge survival. This study highlights that the ability to walk independently at discharge is a crucial predictor of six-month survival in COVID-19 patients. These findings emphasize the need for interventions to improve the physical performance of non-ambulatory patients, potentially enhancing their survival prospects. This underscores the importance of targeted rehabilitation and physical therapy for the comprehensive care of COVID-19 survivors. Full article

Background: Plasma levels of von Willebrand factor (VWF) are significantly elevated in patients with coronavirus disease 2019 (COVID-19). However, dynamic changes and prognostic value of this biomarker in hospitalized patients with COVID-19 have not been determined. Methods: A total of 124 patients infected with SARS-CoV-2 were prospectively recruited for the study. Serial blood samples were obtained at the time of admission (D1), 3–4 days following standard-care treatments (D2), and 1–2 days prior to discharge or any time collected prior to death (D3). Plasma VWF antigen, ADAMTS13 antigen, and ADAMTS13 proteolytic activity, as well as the ratio of VWF/ADAMTS13 were determined, followed by various statistical analyses. Results: On admission, plasma levels of VWF in COVID-19 patients were significantly elevated compared with those in the healthy controls, but no statistical significance was detected among patients with different disease severity. Plasma ADAMTS13 activity but not its antigen levels were significantly lower in patients with severe or critical COVID-19 compared with that in other patient groups. Interestingly, the ratios of plasma VWF antigen to ADAMTS13 antigen were significantly higher in patients with severe or critical COVID-19 than in those with mild to moderate disease. More importantly, plasma levels of VWF and the ratios of VWF/ADAMTS13 were persistently elevated in patients with COVID-19 throughout hospitalization. Kaplan–Meier and Cox proportional hazard regression analyses demonstrated that an increased plasma level of VWF or ratio of VWF/ADAMTS13 at D2 and D3 was associated with an increased mortality rate. Conclusions: Persistent endotheliopathy, marked by the elevated levels of plasma VWF or VWF/ADAMTS13 ratio, is present in all hospitalized patients following SARS-CoV-2 infection, which is strongly associated with mortality. Full article

The aim of the study was to develop a computerized method for distinguishing COVID-19-affected cases from cases of pneumonia. This task continues to be a real challenge in the practice of diagnosing COVID-19 disease. In the study, a new approach was proposed, using a comprehensive set of diagnostic information (CSDI) including, among other things, medical history, demographic data, signs and symptoms of the disease, and laboratory results. These data have the advantage of being much more reliable compared with data based on a single source of information, such as radiological imaging. On this basis, a comprehensive process of building predictive models was carried out, including such steps as data preprocessing, feature selection, training, and evaluation of classification models. During the study, 9 different methods for feature selection were used, while the grid search method and 12 popular classification algorithms were employed to build classification models. The most effective model achieved a classification accuracy (ACC) of 85%, a sensitivity (TPR) equal to 83%, and a specificity (TNR) of 88%. The model was built using the random forest method with 15 features selected using the recursive feature elimination selection method. The results provide an opportunity to build a computer system to assist the physician in the diagnosis of the COVID-19 disease. Full article

Objective: To evaluate the neutrophil-to-lymphocyte ratio (NLR) values’ possible predictive role in fatal and severe cases of COVID-19 disease in pregnant women. Design and data collection: A case-control study was conducted with the inclusion of 45 pregnant COVID-19 patients. All the data were obtained from the hospital information system of Semmelweis University by two of the authors. Results: Statistical analyses showed that NLR values were significantly higher in patients with fatal COVID-19 compared to those who survived the disease, with or without mechanical ventilation. The study also assessed whether NLR values measured on the first day of hospitalization or at their peak provided better markers of disease severity. While both the first-day and peak NLR values were evaluated in patients who did not survive the disease, only the peak NLR values had predictive value regarding patient death. Conclusion: Based on our results, the peak NLR values appear to be useful markers of COVID-19 severity, with a cut-off value of 18.05. However, the authors suggest and hope that larger sample size studies will be conducted to further validate the findings of their research. Full article

Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2)-infection is associated with an extremely variable disease course. When interstitial pneumonia (IP) occurs, it can lead to acute respiratory distress syndrome and death. Serum Krebs von den Lungen-6 (KL-6) is an established marker of IP, but its role as a marker of SARS-CoV-2 pneumonia is debated. This bicentric study included 157 patients with SARS-CoV-2 pneumonia. The WHO Ordinal Scale for Clinical Improvement (0–10 points) was used to classify the clinical course. Serum samples were collected at admission, and on days 3 and 7 of hospitalization. KL-6 was measured by using automated chemiluminescence immunoassay. A total of 68 patients developed a severe SARS-CoV-2 pneumonia, 135 of them required oxygen, and 15 died during hospitalization. The patients requiring non-invasive ventilation, invasive ventilation, or extracorporeal membrane oxygenation had significantly higher serum KL-6 levels at admission. The serum KL-6 levels were tendentially higher in patients who died than in those who survived. Logistic regression identified serum KL-6 at a cut-off of 335 U/mL at admission as a significant predictor of severe SARS-CoV-2 pneumonia outcome. Serum KL-6 seems to be a candidate biomarker for the clinical routine to stratify patients with SARS-CoV-2 pneumonia for the risk of a severe disease outcome or death. Full article

Objective: The objective of this article is to develop a robust method for forecasting the transition from endemic to epidemic phases in contagious diseases using COVID-19 as a case study. Methods: Seven indicators are proposed for detecting the endemic/epidemic transition: variation coefficient, entropy, dominant/subdominant spectral ratio, skewness, kurtosis, dispersion index and normality index. Then, principal component analysis (PCA) offers a score built from the seven proposed indicators as the first PCA component, and its forecasting performance is estimated from its ability to predict the entrance in the epidemic exponential growth phase. Results: This score is applied to the retro-prediction of endemic/epidemic transitions of COVID-19 outbreak in seven various countries for which the first PCA component has a good predicting power. Conclusion: This research offers a valuable tool for early epidemic detection, aiding in effective public health responses. Full article

Since the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant was first discovered, several variants showing different infectivity and immune responses have emerged globally. As the conventional method, whole-genome sequencing following polymerase chain reaction (PCR) is currently used for diagnosis of SARS-CoV-2 mutations. However, these conventional PCR-based direct DNA sequencing methods are time-consuming, complicated, and require expensive DNA sequencing modules. Here, we developed a fluorometric method for the accurate detection of a single missense mutation of U to G in the spike (S) gene that changes leucine to arginine (L452R) in SARS-CoV-2 genomic RNA. Our method for the detection of single-nucleotide mutations (SNM) in the viral RNA genome includes RNA sequence-dependent DNA ligation and tandem isothermal gene amplification methods, such as strand displacement amplification (SDA) and rolling circle amplification (RCA) generating G-quadruplex (GQ). In the presence of SNM in the viral RNA, ligation of both ends of the probe DNAs occurs between 5′-phosphorylated hairpin DNA and linear probe DNA that can discriminate a single base mismatch. The ligated DNAs were then extended to generate long-stem hairpin DNAs that are subjected to the first isothermal gene amplification (SDA). SDA produces multitudes of short ssDNA from the long-stem hairpin DNAs, which then serve as primers by annealing to circular padlock DNA for the second isothermal gene amplification (RCA). RCA produces a long stretch of ssDNA containing GQ structures. Thioflavin T (ThT) is then intercalated into GQ and emits green fluorescence, which allows the fluorometric identification of SARS-CoV-2 variants. This fluorometric analysis sensitively distinguished SNM in the L452R variant of SARS-CoV-2 RNA as low as 10 pM within 2 h. Hence, this fluorometric detection method using ligation-assisted tandem isothermal gene amplification can be applied for the diagnosis of SARS-CoV-2 SNM variants with high accuracy and sensitivity, without the need for cumbersome whole-genome DNA sequencing. Full article

Introduction: The effectiveness of extracorporeal membrane oxygenation (ECMO) in treating COVID-19 patients has been variable. To gain a better insight, we examined the outcomes of ECMO in COVID-19 patients using data from the 2020 National Inpatient Sample database. Methods: We analyzed data from adult hospital admissions where COVID-19 was the primary diagnosis. The primary outcome was all-cause inpatient mortality. Secondary outcomes were length of stay (LOS), cost, and discharge disposition. Results: We identified 1,048,025 COVID-19 admissions, of which 98,528 were on mechanical ventilation (MV), and only 1.8% received ECMO. In-hospital mortality of mechanically ventilated patients who received ECMO was 49%, compared to 59% with no ECMO (p < 0.001). ECMO treatment was associated with a reduced risk of mortality (HR = 0.67, p < 0.0001, CI 0.57–0.79) even after adjustment for confounders and other comorbidities. Patients on ECMO had significantly extended hospital stays and were more likely to be discharged to an acute care facility. Younger and male patients were more likely to receive ECMO treatment. Females had a lower mortality risk, while race and obesity were not associated with an increased risk of death. Conclusion: ECMO treatment may offer survival benefits in severe COVID-19. Based on our findings, we suggest early ECMO treatment for patients with a high mortality risk. Full article

Coronavirus disease 2019 (COVID-19) is a contagious illness worldwide. While guidelines for the treatment of COVID-19 have been established, the understanding of the relationship among neutralizing antibodies, cytokines, and the combined use of antiviral medications, steroid drugs, and convalescent plasma therapy remains limited. Here, we investigated the connection between the immunological response and the efficacy of convalescent plasma therapy in COVID-19 patients with moderate-to-severe pneumonia. The study included a retrospective analysis of 49 patients aged 35 to 57. We conducted clinical assessments to determine antibody levels, biochemical markers, and cytokine levels. Among the patients, 48 (98%) were discharged, while one died. We observed significantly higher levels of anti-nucleocapsid, anti-spike, and neutralizing antibodies on days 3, 7, and 14 after the transfusion compared to before treatment. Serum CRP and D-dimer levels varied significantly across these four time points. Moreover, convalescent plasma therapy demonstrated an immunoregulatory effect on cytokine parameters, with significant differences in IFN-β, IL-6, IL-10, and IFN-α levels observed at different sampling times. Evaluating the cytokine signature, along with standard clinical and laboratory parameters, may help to identify the onset of a cytokine storm in COVID-19 patients and determine the appropriate indication for anti-cytokine treatment. Full article

While pediatric COVID-19 is rarely severe, a small fraction of children infected with SARS-CoV-2 go on to develop multisystem inflammatory syndrome (MIS-C), with substantial morbidity. An objective method with high specificity and high sensitivity to identify current or imminent MIS-C in children infected with SARS-CoV-2 is highly desirable. The aim was to learn about an interpretable novel cytokine/chemokine assay panel providing such an objective classification. This retrospective study was conducted on four groups of pediatric patients seen at multiple sites of Texas Children’s Hospital, Houston, TX who consented to provide blood samples to our COVID-19 Biorepository. Standard laboratory markers of inflammation and a novel cytokine/chemokine array were measured in blood samples of all patients. Group 1 consisted of 72 COVID-19, 70 MIS-C and 63 uninfected control patients seen between May 2020 and January 2021 and predominantly infected with pre-alpha variants. Group 2 consisted of 29 COVID-19 and 43 MIS-C patients seen between January and May 2021 infected predominantly with the alpha variant. Group 3 consisted of 30 COVID-19 and 32 MIS-C patients seen between August and October 2021 infected with alpha and/or delta variants. Group 4 consisted of 20 COVID-19 and 46 MIS-C patients seen between October 2021 andJanuary 2022 infected with delta and/or omicron variants. Group 1 was used to train an L1-regularized logistic regression model which was tested using five-fold cross validation, and then separately validated against the remaining naïve groups. The area under receiver operating curve (AUROC) and F1-score were used to quantify the performance of the cytokine/chemokine assay-based classifier. Standard laboratory markers predict MIS-C with a five-fold cross-validated AUROC of 0.86 ± 0.05 and an F1 score of 0.78 ± 0.07, while the cytokine/chemokine panel predicted MIS-C with a five-fold cross-validated AUROC of 0.95 ± 0.02 and an F1 score of 0.91 ± 0.04, with only sixteen of the forty-five cytokines/chemokines sufficient to achieve this performance. Tested on Group 2 the cytokine/chemokine panel yielded AUROC = 0.98 and F1 = 0.93, on Group 3 it yielded AUROC = 0.89 and F1 = 0.89, and on Group 4 AUROC = 0.99 and F1 = 0.97. Adding standard laboratory markers to the cytokine/chemokine panel did not improve performance. A top-10 subset of these 16 cytokines achieves equivalent performance on the validation data sets. Our findings demonstrate that a sixteen-cytokine/chemokine panel as well as the top ten subset provides a highly sensitive, and specific method to identify MIS-C in patients infected with SARS-CoV-2 of all the major variants identified to date. Full article