Early COVID-19 Patients Research Articles

Immunological Misfiring and Sex Differences/Similarities in Early COVID-19 Studies: Missed Opportunities of Making a Real IMPACT.

COVID-19-associated intensive care unit (ICU) admissions were recognized as critical health issues that contributed to morbidity and mortality in SARS-CoV-2-infected patients. Severe symptoms in COVID-19 patients are often accompanied by cytokine release syndrome. Here, we analyzed publicly available data from the Yale IMPACT cohort to address immunological misfiring and sex differences in early COVID-19 patients. In 2020, SARS-CoV-2 was considered far more pathogenic and lethal than other circulating respiratory viruses, and the inclusion of SARS-CoV-2 negative patients in IMPACT cohorts confounds many findings. We ascertained the impact of several important biological variables such as days from symptom onset (DFSO); pre-existing risk factors, including obesity; and early COVID-19 treatments on significantly changed immunological measures in ICU-admitted COVID-19 patients that survived versus those that did not. Deceased patients had 19 unique measures that were not shared with ICU patients including increased granzyme-B-producing GzB+CD8+ T cells and interferon-γ. Male COVID-19 patients in ICU experienced many more changes in immunological and clinical measures than female ICU patients (25% vs. ~16%, respectively). A total of 13/124 measures including CCL5, CCL17, IL-18, IFNα2, Fractalkine, classical monocytes, T cells, and CD4Temra exhibited significant sex differences in female vs. male COVID-19 patients. A total of nine measures including IL-21, CCL5, and CD4Temra differed significantly between female and male healthy controls. Immunosuppressed patients experienced the most decreases in CD4Temra and CD8Tem cell numbers. None of the early COVID-19 treatments were effective in reducing levels of IL-6, a major component of the cytokine storm. Obesity (BMI >30) was the most impactful risk factor for COVID-19-related deaths and worst clinical outcomes. Our analysis highlights the contribution of biological sex, risk factors, and early treatments with respect to COVID-19-related ICU admission and progression to morbidity and mortality.

The Relationship Between Natural Medicine Use and Recovery Time in Early Adult COVID-19 Patients

COVID-19 is a single-stranded RNA virus that infects through droplets. Drug consumption is one of the factors that affect the recovery of COVID-19 patients. The drug that has become a trend in the world is the use of natural ingredients, but people do not know whether it is effective in shortening the recovery time. Therefore, it is necessary to conduct research related to the relationship between the use of natural ingredients with the length of recovery of COVID-19 patients in early adulthood. This study used an analytical observational design with a cross-sectional method on 94 respondents in the Grogol Village area. Respondents fill out questionnaires via Google form and fill out questionnaires directly. Bivariate analysis of data using SPSS version 29. A total of 50 subjects consumed natural medicines (53.2%), namely jamu (58%), and 34 of them consumed almost every day (68%). There was no significant relationship between the use of natural medicine with the length of recovery of COVID-19 patients in early adulthood

Early Fluvoxamine Reduces the Risk for Clinical Deterioration in Symptomatic Outpatients with COVID-19: A Real-World, Retrospective, before-after Analysis.

Fluvoxamine, a selective serotonin reuptake inhibitor with anti-inflammatory properties, has gained attention as a repurposed drug to treat COVID-19. We aimed to explore the potential benefit of fluvoxamine on outpatients with early SARS-CoV-2 infection. We performed a retrospective study of fluvoxamine adult outpatients with symptomatic COVID-19 disease of early onset (<5 days), in the context of an infectious diseases private practice, between September-December 2021, in Greece. Patients with disease duration ≥5 days, dyspnea and/or hypoxemia with oxygen saturation <94% in room air and pregnancy were excluded from the analysis. In total, 103 patients, 54 males/49 females with a median age of 47 years (39-56), were included in this study. Patient characteristics were balanced before and after the introduction of fluvoxamine. Two patients in the fluvoxamine arm (3.8%; 95% CI 0.4-13) had clinical deterioration compared to 8 patients in the standard of care group (16%; 95% CI 7.2-29.1, p < 0.04). After controlling for age, sex, body mass index > 30 and vaccination status, fluvoxamine was independently associated with a lower risk of clinical deterioration (adj. OR 0.12; 95% CI 0.02-0.70, p < 0.02). Adding on fluvoxamine to treatment for early symptomatic COVID-19 patients may protect them from clinical deterioration and hospitalization, and it is an appealing low-cost, low-toxicity option in the community setting and warrants further investigation.

Polydopamine Nanoparticles-Based Three-Line Lateral Flow Immunoassay for COVID-19 Detection.

Currently, the global trend of several hundred thousand new confirmed COVID-19 patients per day has not abated significantly. Serological antibody detection has become an important tool for the self-screening of people. While the most commonly used colorimetric lateral flow immunoassay (LFIA) methods for the detection of COVID-19 antibodies are limited by low sensitivity and a lack of quantification ability. This leads to poor accuracy in the screening of early COVID-19 patients. Therefore, it is necessary to develop an accurate and sensitive autonomous antibody detection technique that will effectively reduce the COVID-19 infection rate. Here, we developed a three-line LFIA immunoassay based on polydopamine (PDA) nanoparticles for COVID-19 IgG and IgM antibodies detection to determine the degree of infection. The PDA-based three-line LFIA has a detection limit of 1.51 and 2.34 ng/mL for IgM and IgG, respectively. This assay reveals a good linearity for both IgM and IgG antibodies detection and is also able to achieve quantitative detection by measuring the optical density of test lines. In comparison, the commercial AuNP-based LFIA showed worse quantification results than the developed PDA-based LFIA for low-concentration COVID-19 antibody samples, making it difficult to distinguish between negative and positive samples. Therefore, the developed PDA-based three-line LFIA platform has the accurate quantitative capability and high sensitivity, which could be a powerful tool for the large-scale self-screening of people.

Evaluation of coagulation parameters according to serum CRP levels in early stage COVID-19 patients

Evaluation of coagulation parameters according to serum CRP levels in early stage COVID-19 patients

Association between treatment failure and hospitalization after receipt of neutralizing monoclonal antibody treatment for COVID-19 outpatients

BackgroundNeutralizing monoclonal antibodies (mAbs) are highly effective in reducing hospitalization and mortality among early symptomatic COVID-19 patients in clinical trials and real-world data. While resistance to some mAbs has since emerged among new variants, characteristics associated with treatment failure of mAbs remain unknown.MethodsThis multicenter, observational cohort study included patients with COVID-19 who received mAb treatment between November 20, 2020, and December 9, 2021. We utilized electronic health records from a statewide health system plus state-level vaccine and mortality data. The primary outcome was mAb treatment failure, defined as hospitalization or death within 28 days of a positive SARS-CoV-2 test.ResultsCOVID-19 mAb was administered to 7406 patients. Hospitalization within 28 days of positive SARS-CoV-2 test occurred in 258 (3.5%) of all patients who received mAb treatment. Ten patients (0.1%) died within 28 days, and all but one were hospitalized prior to death. Characteristics associated with treatment failure included having two or more comorbidities excluding obesity and immunocompromised status (adjusted odds ratio [OR] 3.71, 95% confidence interval [CI] 2.52–5.56), lack of SARS-CoV-2 vaccination (OR 2.73, 95% CI 2.01–3.77), non-Hispanic black race/ethnicity (OR 2.21, 95% CI 1.20–3.82), obesity (OR 1.79, 95% CI 1.36–2.34), one comorbidity (OR 1.68, 95% CI 1.11–2.57), age ≥ 65 years (OR 1.62, 95% CI 1.13–2.35), and male sex (OR 1.56, 95% CI 1.21–2.02). Immunocompromised status (none, mild, or moderate/severe), pandemic phase, and type of mAb received were not associated with treatment failure (all p > 0.05).ConclusionsComorbidities, lack of prior SARS-CoV-2 vaccination, non-Hispanic black race/ethnicity, obesity, age ≥ 65 years, and male sex are associated with treatment failure of mAbs.

Classification of lungs infected COVID-19 images based on inception-ResNet

ObjectiveNowadays, COVID-19 is spreading rapidly worldwide, and seriously threatening lives . From the perspective of security and economy, the effective control of COVID-19 has a profound impact on the entire society. An effective strategy is to diagnose earlier to prevent the spread of the disease and prompt treatment of severe cases to improve the chance of survival. MethodsThe method of this paper is as follows: Firstly, the collected data set is processed by chest film image processing, and the bone removal process is carried out in the rib subtraction module. Then, the set preprocessing method performed histogram equalization, sharpening, and other preprocessing operations on the chest film. Finally, shallow and high-level feature mapping through the backbone network extracts the processed chest radiographs. We implement the self-attention mechanism in Inception-Resnet, perform the standard classification, and identify chest radiograph diseases through the classifier to realize the auxiliary COVID-19 diagnosis process at the medical level, all in an effort to further enhance the classification performance of the convolutional neural network. Numerous computer simulations demonstrate that the Inception-Resnet convolutional neural network performs CT image categorization and enhancement with greater efficiency and flexibility than conventional segmentation techniques. ResultsThe experimental COVID-19 CT dataset obtained in this paper is the new data for CT scans and medical imaging of normal, early COVID-19 patients and severe COVID-19 patients from Jinyintan hospital. The experiment plots the relationship between model accuracy, model loss and epoch, using ACC, TPR, SPE, F1 score and G-mean to measure the image maps of patients with and without the disease. Statistical measurement values are obtained by Inception-Resnet are 88.23%, 83.45%, 89.72%, 95.53% and 88.74%. The experimental results show that Inception-Resnet plays a more effective role than other image classification methods in evaluation indicators, and the method has higher robustness, accuracy and intuitiveness. ConclusionWith CT images in the clinical diagnosis of COVID-19 images being widely used and the number of applied samples continuously increasing, the method in this paper is expected to become an additional diagnostic tool that can effectively improve the diagnostic accuracy of clinical COVID-19 images.

An explanatory analytics framework for early detection of chronic risk factors in pandemics

Timely decision-making in national and global health emergencies such as pandemics is critically important from various aspects. Especially, early identification of risk factors of contagious viral diseases can lead to efficient management of limited healthcare resources and saving lives by prioritizing at-risk patients. In this study, we propose a hybrid artificial intelligence (AI) framework to identify major chronic risk factors of novel, contagious diseases as early as possible at the time of pandemics. The proposed framework combines evolutionary search algorithms with machine learning and the novel explanatory AI (XAI) methods to detect the most critical risk factors, use them to predict patients at high risk of mortality, and analyze the risk factors at the individual level for each high-risk patient. The proposed framework was validated using data from a repository of electronic health records of early COVID-19 patients in the US. A chronological analysis of the chronic risk factors identified using our proposed approach revealed that those factors could have been identified months before they were determined by clinical studies and/or announced by the United States health officials.

Pulmonary surfactant and COVID-19: A new synthesis.

COVID-19 pathogenesis poses paradoxes difficult to explain with traditional physiology. For instance, since type II pneumocytes are considered the primary cellular target of SARS-CoV-2; as these produce pulmonary surfactant (PS), the possibility that insufficient PS plays a role in COVID-19 pathogenesis has been raised. However, the opposite of predicted high alveolar surface tension is found in many early COVID-19 patients: paradoxically normal lung volumes and high compliance occur, with profound hypoxemia. That 'COVID anomaly' was quickly rationalised by invoking traditional vascular mechanisms-mainly because of surprisingly preserved alveolar surface in early hypoxemic cases. However, that quick rejection of alveolar damage only occurred because the actual mechanism of gas exchange has long been presumed to be non-problematic, due to diffusion through the alveolar surface. On the contrary, we provide physical chemical evidence that gas exchange occurs by an process of expansion and contraction of the three-dimensional structures of PS and its associated proteins. This view explains anomalous observations from the level of cryo-TEM to whole individuals. It encompasses results from premature infants to the deepest diving seals. Once understood, the COVID anomaly dissolves and is straightforwardly explained as covert viral damage to the 3D structure of PS, with direct treatment implications. As a natural experiment, the SARS-CoV-2 virus itself has helped us to simplify and clarify not only the nature of dyspnea and its relationship to pulmonary compliance, but also the fine detail of the PS including such features as water channels which had heretofore been entirely unexpected. For a long time, physical, colloid and surface chemistry have not intersected with physiology and cell biology as much as we might have hoped. The reasons are starting to become clear. The discipline of physical chemistry suffered from serious unrecognised omissions that rendered it ineffective. These foundational defects included omission of specific ion molecular forces and hydration effects. The discipline lacked a predictive theory of self-assembly of lipids and proteins. Worse, theory omitted any role for dissolved gases, O2, N2, CO2, and their existence as stable nanobubbles above physiological salt concentration. Recent developments have gone some way to explaining the foam-like lung surfactant structures and function. It delivers O2/N2 as nanobubbles, and efflux of CO2, and H2O nanobubbles at the alveolar surface. Knowledge of pulmonary surfactant structure allows an explanation of the mechanism of corona virus entry, and differences in infectivity of different variants. CO2 nanobubbles, resulting from metabolism passing through the molecular frit provided by the glycocalyx of venous tissue, forms the previously unexplained foam which is the endothelial surface layer. CO2 nanobubbles turn out to be lethal to viruses, providing a plausible explanation for the origin of 'Long COVID'. Circulating nanobubbles, stable above physiological 0.17 M salt drive various enzyme-like activities and chemical reactions. Awareness of the microstructure of Pulmonary Surfactant and that nanobubbles of (O2/N2) and CO2 are integral to respiratory and circulatory physiology provides new insights to the COVID-19 and other pathogen activity.

The effect of casirivimab with imdevimab on disease progression in nonsevere COVID-19 patients in a single hospital in Japan.

BackgroundRecent randomized trials have revealed that neutralizing monoclonal antibodies can reduce disease progression in mild–moderate COVID‐19 patients. However, no studies have investigated the effect of neutralizing monoclonal antibodies on clinical outcomes in Japan.MethodsA single‐center retrospective and prospective cohort study was conducted. All consecutive febrile nonsevere COVID‐19 patients with at least one risk factor were included. The primary outcome was progression to severe COVID‐19. Severe COVID‐19 cases were defined as patients requiring oxygen therapy and dexamethasone. The differences in the primary outcomes between the patients who were treated with casirivimab with imdevimab (treatment group) and those who were not (control group) were compared using the chi‐squared test.ResultsA total of 128 patients were included. Of those, the mean age was 53.6 years old (SD 9.9), and 52 (40.6%) were women. Fifty‐three patients were treated with casirivimab with imdevimab, and 75 patients were given the standard treatment only. The primary outcome occurred in eight (15.1%) of the 53 patients in the treatment group and 33 (44.0%) of the 75 patients in the control group (odd ratio [OR] 0.23, 95% CI 0.09 to 0.55). The multivariate analysis revealed that the use of casirivimab with imdevimab (OR 0.21, 95% CI 0.08 to 0.54) was the only independent risk factor associated with progression to severe COVID‐19. No patients died during hospitalization in either group.ConclusionSimilar to other countries, casirivimab with imdevimab significantly reduced disease progression in early nonsevere COVID‐19 patients with fever and risk factors in Japan.

504. Case SEries: Nasal Antimicrobial Photodisinfection (APDT) as Treatment Protocol for Asymptomatic and Early Stage COVID-19 Patients

BackgroundTargeted reduction of SARS-CoV-2 viral load in the nose may mitigate the severity of lower tract respiratory disease as well as reduce hospitalization and mortality rates. Nasal Photodisinfection has been deployed for 10 years in Canadian hospitals reducing post-surgical infections. The objective of thiswork was to demonstrate effectiveness of APDT in early stage COVID-19 and asymptomatic carriers.MethodsA cohort of 40 COVID-19 positive patients were treated with nasal photodisinfection (Steriwave) at a private clinic. All patients were previously identified by PCR as SARS-CoV-2 positive and admitted into the treatment cohort. BD rapid antigen nares testing was used before and after Photodisinfection treatment. Of the 40 patients, 13 were female and 27 were male. Age range was 9- 56 years of age. Treatment involved 3-4 applications of photosensitizer and 16-24 minutes per patient of treatment time. Patients were followed up within 24 hours, 48 hours as well as day 5 and 6 and day 10/11. Patients filled out a COVID-19 score card.ResultsResults demonstrated APDT was capable of significant and rapid viral load reduction in COVID-19 carriers. 100% of patients were converted from positive rapid antigen test to negative. 60% of patients reported fever resolution within 24 hours. Fever resolution occurred in 100% of patients within 48hours. Moreover, results demonstrated accelerated resolution of COVID-19 symptoms and significantly improved mental health benefits from reduction of COVID-19 related stress and anxiety. None of the patients experienced severe symptoms and no patients were hospitalized. Safety outcomes demonstrated no patient safety issues with only minor transient side effects (rhinorrhea, sneezing) observed. Moreover, the treatment procedure was pain-free and well tolerated by all patients.ConclusionPhotodisinfection-based nasal decolonization anti-viral efficacy was demonstrated with improved outcomes for all patients treated in this case series. Significant rapid viral load reduction was confirmed by rapid antigen tests in all patients. More clinical studies are warranted in support of Photodisinfection based therapy for upper respiratory infections such as COVID-19.Disclosures All Authors: No reported disclosures

Social Support and Connective Affordances: Examining Responses to Early Covid-19 Patient Support Seeking on Microblogs

ABSTRACT Focusing on the new Super-Topics Platform (STP) of Weibo, this study examined microblog users’ responses to the support seeking of early Covid-19 patients suffering the first outbreak in China. A total of 853 patients’ support-seeking messages, along with 81,000 comments to 270 patients’ help-requests, were crawled and analyzed. Results showed that content characteristics influenced endorsing, sharing, and commenting by users. Furthermore, the study identified three types of social support present in Weibo viewers’ comments: emotional, informational, and diffusional supports. These social support types were inherently linked to the connective affordances, which are more inclusive than paralinguistic digital affordances, of microblogs.

Soetomo Covid-19 Score As An Early Identification Tools of Covid-19 Patients in Surabaya, Indonesia

Background Clinical prediction scores support the assessment of patients to limit the COVID-19 outbreak. Soetomo COVID-19 Score (SCS) has been used to determine further diagnostic and patient zoning purposes in our hospital. We aimed to evaluate the SCS characteristics and its capability to determine those with COVID-19 infection. Methods The score was evaluated using retrospective analysis from March 2020 to January 2021, which was undertaken on patients who had taken SARS CoV-2 PCR swab at Dr. Soetomo General Hospital, Surabaya. Descriptive, Chi-Square, and Mann-Whitney tests were analysed to evaluate the comparison among PCR SARS CoV-2 swab results. Receiver operating characteristic was carried out to determine the SS discrimination capability. Results Of 454 subjects participating in the study, 32.8% of them were confirmed COVID-19. They had a lower leukocyte level and a higher median total of SCS (10010?9448 cells/mm3). Most of the SCS characteristics showed significant results according to the swab results. SCS had a good discrimination capacity (AUC 82.5%, 95% CI 78.2-86.8%; p<0.001). Total SCS 12.5 was the optimal cut-off point to discriminate suspected COVID-19 patients with good sensitivity (89.3%) and specificity (78.4%). Conclusions The newly developed SCS is a considerable tool for an early COVID-19 patients identification.

Beginnings of coinhibition.

Costimulatory and coinhibitory mechanisms appear to be involved throughout immune responses to control their specificity and level. Many mechanisms operate; therefore, various theoretical models should be considered complementary rather than competing. One such coinhibitory model, pictured in 1971, involves the crosslinking of antigen receptors with inhibitory Fc receptors by antigen/antibody complexes. This model was prompted by observations that the Fc portion of antibody was required for potent suppression of immune responses by antibody. The signal via the antigen receptor wakes up T or B cells, providing specificity, while costimulators and coinhibitors stimulate or inhibit these awoken cells. The recent observations that administration of monoclonal anti-SARS-CoV-2 spike antibodies in early COVID-19 patients inhibits the induction of clinically damaging autoimmune antibodies suggest they may provide negative Fc signals that are blocked in COVID-19 patients. Furthermore, the reduced ability of SARS-CoV-2 antigen to localize to germinal centres in COVID-19 patients also suggests a block in binding of the Fc of antibody bound to antigen on FcγRIIb of follicular dendritic cells. The distinction between self and foreign is made not only at the beginning of immune responses but also throughout, and involves multiple mechanisms and models. There are past beginnings (history of models) and current and future beginnings for solving serious clinical problems (such as COVID-19) and different types of models used for understanding the complexities of fundamental immunology.

Self-collected oral, nasal and saliva samples yield sensitivity comparable to professionally collected oro-nasopharyngeal swabs in SARS-CoV-2 diagnosis among symptomatic outpatients

IntroductionContaining COVID-19 requires broad-scale testing. However, sample collection requires qualified personnel and protective equipment and may cause transmission. We assessed the sensitivity of SARS-CoV-2-rtPCR applying three self-sampling techniques as compared to professionally collected oro-nasopharyngeal samples (cOP/NP). MethodsFrom 62 COVID-19 outpatients, we obtained: (i) multi-swab, MS; (ii) saliva sponge combined with nasal vestibula, SN; (iii) gargled water, GW; (iv) professionally collected cOP/NP (standard). We compared ct-values for E-gene and ORF1ab and analysed variables reducing sensitivity of self-collecting procedures. ResultsThe median ct-values for E-gene and ORF1ab obtained in cOP/NP samples were 20.7 and 20.2, in MS samples 22.6 and 21.8, in SN samples 23.3 and 22.3, and in GW samples 30.3 and 29.8, respectively. MS and SN samples showed sensitivities of 95.2% (95%CI, 86.5-99.0) and GW samples of 88.7% (78.1-95.3). Sensitivity was inversely correlated with ct-values, and became <90% for samples obtained more than 8 days after symptom onset. For MS and SN samples, false negativity was associated with language problems, sampling errors, and symptom duration. ConclusionConclusions from this study are limited to the sensitivity of self-sampling in mildly to moderately symptomatic patients. Still, self-collected oral/nasal/saliva samples can facilitate up-scaling of testing in early symptomatic COVID-19 patients if operational errors are minimized.

Clinico-epidemiological profile of early cases of Covid-19 in state of Haryana, India

Background: Covid -19 disease is caused by novel coronavirus known as SARS CoV 2. Coronaviruses are known to cause disease in humans which can be a common cold or a serious pneumonia. SARS Cov 2 is a new variant of coronavirus which was never reported in humans before detection of cluster of cases of pneumonia in Wuhan on 31st December, 2019.Objective: The study was conducted with the objective to find out clinico- epidemiological profiles of early Covid-19 patients in state of Haryana, India and to find out knowledge about covid appropriate behaviors among covid 19 patients. Methods: All the covid-19 cases in the five districts of Haryana were enumerated from March 2020 to May 2020. These Covid-19 cases were contacted telephonically and those who gave their consent to participate in the study were asked to fill interview schedule. Observations: There were 356 covid cases reported in five districts attached to PGIMS, Rohtak. Out of total,254 subjects participated in the study, there were 60.6 % males and 39.4% females who participated in the study. Blood groups of all the participants were also enquired and it was observed that B +ve was most common (19.7%) blood group followed by A+ve (16.5%) and O +ve (15.7%). Conclusion: It can be concluded by the study that majority of the subjects were males, overweight and blood group A &amp; B were the most common blood groups. It was observed that 75.2 % participants were aware about the use of mask, social distancing, hand hygiene and cough etiquettes.

Impact of SARS-CoV-2 infection on the recovery of peripheral blood mononuclear cells by density gradient

SARS-CoV-2 virus infection is responsible for coronavirus disease (COVID-19), which is characterised by a hyperinflammatory response that plays a major role in determining the respiratory and immune-mediated complications of this condition. While isolating peripheral blood mononuclear cells (PBMCs) from whole blood of COVID-19 patients by density gradient centrifugation, we noticed some changes in the floating properties and in the sedimentation of the cells on density medium. Investigating this further, we found that in early phase COVID-19 patients, characterised by reduced circulating lymphocytes and monocytes, the PBMC fraction contained surprisingly high levels of neutrophils. Furthermore, the neutrophil population exhibited alterations in the cell size and in the internal complexity, consistent with the presence of low density neutrophils (LDNs) and immature forms, which may explain the shift seen in the floating abilities and that may be predictive of the severity of the disease. The percentage of this subset of neutrophils found in the PBMC band was rather spread (35.4 ± 27.2%, with a median 28.8% and IQR 11.6–56.1, Welch’s t-test early phase COVID-19 versus blood donor healthy controls P < 0.0001). Results confirm the presence of an increased number of LDNs in patients with early stage COVID-19, which correlates with disease severity and may be recovered by centrifugation on a density gradient together with PBMCs.

Factors affecting the survival of early COVID-19 patients in South Korea: An observational study based on the Korean National Health Insurance big data

ObjectivesThis study aimed to identify the survival rate and explore factors affecting survival among early COVID-19 patients in South Korea. MethodsData reported by the Korea Disease Control and Prevention Agency (KDCA), up to 15 July, when COVID-19 was confirmed were used as research data in connection with the National Health Insurance Service’s (NHIS) national health information database. The final analysis targets were 12,646 confirmed patients and 303 deaths. The survival rate of patients with COVID-19 was estimated through Kaplan-Meier survival analysis. Cox proportional hazard regression analysis was performed to search for factors affecting survival. ResultsWhen looking at the survival rate by age group for men and women, the 28-day survival rate for men aged >80 years was 77% and 73% at 42 days, while 83% and 81% for women. Men had a worse survival rate than women. For chronic diseases, the highest risk of mortality was observed in malignant neoplasms of the respiratory and urogenital systems, followed by diseases of the urinary system and diabetes. ConclusionsThe number of COVID-19 deaths was highest the next day after initial diagnosis. The case fatality rate was high in males, older age, and chronic diseases.

Add-on Ayurveda Treatment for Early Stage COVID-19: A Single Center Retrospective Cohort Study From Gujarat, India.

The retrospective cohort study aimed to evaluate the clinical outcomes of Ayurveda treatment exposure as an add-on to conventional care in early stage COVID-19 patients admitted at Samaras COVID care center, Ahmedabad, India. Conventional care included Vitamin-c, Azithromycin, and Paracetamol. Ayurveda formulations used as add-on were Dashamula and Pathyadi decoctions along with Trikatu powder, Sanshamani tablet, AYUSH-64 tablet AND Yastimadhu Ghana tablet for oral administration. Considering Add-on Ayurveda medicines as exposure of interest, patients who received Add-on Ayurveda medicines at least for 7 days were included in the exposed group while those who received only conventional care in unexposed group. Data was collected through record review and telephonic interviews. The outcomes of interest were the development of symptoms, duration of symptomatic phase in those progressing to symptomatic stage and mortality. Total 762 participants were included-[541 (71%) in the exposed group and 221 (29%) in the unexposed. Progression to symptomatic phase did not differ significantly between groups [27.6% in exposed, 24.6% in unexposed, adjusted RR 0.85; 95% CI 0.6-1.2]. The total duration of symptomatic phase among those progressing to the symptomatic stage was significantly decreased in the exposed group (x¯ = 3.66 ± 1.55 days in exposed (n = 133); x¯ = 5.34 ± 3.35 days in unexposed (n = 61), p < 0.001). No mortality was observed in either of the groups. Ayurveda Treatment as adjunctive to conventional care reduced the duration of symptomatic phase in early stage COVID-19 as compared to standalone conventional care. Add-on Ayurveda treatment has promising potential for management of early stage COVID-19.

A Prediction Model Based on Machine Learning for Diagnosing the Early COVID-19 Patients

Objective: To improve the timeliness for the early COVID-19 infection diagnosis, it is essential to develop a decision- making tool to assist early diagnosis of COVID-19 patients in fever clinics. Materials and methods: This paper aims at extracting risk factors from clinical data of 912 early COVID-19 infected patients and utilizing four types of traditional machine learning approaches including Logistic Regression (LR), Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF) and a deep learning-based method for diagnosis of early COVID-19. Results: The results show that the LR predictive model presents a higher specificity rate of 0.95, an Area Under the receiver operating Curve (AUC) of 0.971 and an improved sensitivity rate of 0.82, which makes it optimal for the screening of early COVID-19 infection. We also perform the verification for generality of the best model (LR predictive model) among Zhejiang population, and analyse the contribution of the factors to the predictive models. Discussions: Under the background of COVID-19 pandemic, the early diagnosis of COVID-19 still face severe challenges, a decision-making tool assisting early diagnosis of COVID-19 patients is vital for fever clinics. Conclusions: Our manuscript describes and highlights the ability of machine learning methods for improving the accuracy and timeliness of early COVID-19 infection diagnosis. The higher AUC of our LR-base predictive model makes it a more conducive method for assisting COVID-19 diagnosis. The optimal model has been encapsulated as a mobile application (APP) and implemented in some hospitals in Zhejiang Province.