A mask-guided attention deep learning model for COVID-19 diagnosis based on an integrated CT scan images database

The global extent of COVID-19 mutations and the consequent depletion of hospital resources highlighted the necessity of effective computer-assisted medical diagnosis. COVID-19 detection mediated by deep learning models can help diagnose this highly contagious disease and lower infectivity and mortality rates. Computed tomography (CT) is the preferred imaging modality for building automatic COVID-19 screening and diagnosis models. It is well-known that the training set size significantly impacts the performance and generalization of deep learning models. However, accessing a large dataset of CT scan images from an emerging disease like COVID-19 is challenging. Therefore, data efficiency becomes a significant factor in choosing a learning model. To this end, we present a multi-task learning approach, namely, a mask-guided attention (MGA) classifier, to improve the generalization and data efficiency of COVID-19 classification on lung CT scan images. The novelty of this method is compensating for the scarcity of data by employing more supervision with lesion masks, increasing the sensitivity of the model to COVID-19 manifestations, and helping both generalization and classification performance. Our proposed model achieves better overall performance than the single-task (without MGA module) baseline and state-of-the-art models, as measured by various popular metrics.

Assessment of the Risk and Symptoms of SARS-CoV-2 Infection Among Healthcare Workers During the Omicron Transmission Period: A Multicentric Study from Four Hospitals of Mainland China.

Purpose: The SARS-CoV-2 omicron variant emerged and spread rapidly among the population in the early stage of China's normalized prevention and control in December 2022. Healthcare workers (HCWs) are particularly exposed to SARS-CoV-2, it is important to evaluate the impact of the omicron pandemic on HCWs in China. Methods: A self-administered online survey was conducted on infected HCWs from four hospitals of Taizhou. A total of 748 HCWs received the survey via DingTalk, and 328 responded to the questionnaire. The risk factors were investigated using univariate and multivariate logistic regression analysis. Results: By December 20, 2022, 748 HCWs tested positive by PCR, and the infection rate was 11.4% (748/6581). Among 328 respondents, the most common symptoms were cough (88.4%), fever (83.5%), runny nose (77.1%), sore throat (73.2%), headache (70.1%), muscle aches (67.1%), and fatigue (53.4%). 69.8% (229/328) of the participants had five or more major onset symptoms, while no severe case was observed. The multivariate analysis indicated that the poor sleep quality (OR = 2.29, 95% CI: 1.31-4.02, P = 0.004) was an independent risk factor for more major onset symptoms, while wore gloves ≥95% times in working (OR = 0.49, 95% CI: 0.28-0.85, P = 0.011) was significantly related to fewer symptoms. In addition, 239 (72.9%) recipients reported high fever (temperature ≥38.5°C), less common cold (≤3 vs >3 times/year, OR = 2.20, 95% CI: 1.05-4.65, P = 0.038) was significantly associated with high fever. Conclusion: Our findings imply rapid transmissibility of omicron and multiple-onset symptoms among HCWs. Improved autoimmunity and self-protection measures for HCWs may be helpful in controlling infection and clinical symptoms. Our results provide empirical reference values for improved countermeasures and protective measures for major public health emergencies.

A KdV-SIR equation and its analytical solutions: An application for COVID-19 data analysis.

To describe the time evolution of infected persons associated with an epidemic wave, we recently derived the KdV-SIR equation that is mathematically identical to the Kortewegde Vries (KdV) equation in the traveling wave coordinate and that represents the classical SIR model under a weakly nonlinear assumption. This study further discusses the feasibility of applying the KdV-SIR equation and its analytical solutions together with COVID-19 data in order to estimate a peak time for a maximum number of infected persons. To propose a prediction method and to verify its performance, three types of data were generated based on COVID-19 raw data, using the following procedures: (1) a curve fitting package, (2) the empirical mode decomposition (EMD) method, and (3) the 28-day running mean method. Using the produced data and our derived formulas for ensemble forecasts, we determined various estimates for growth rates, providing outcomes for possible peak times. Compared to other methods, our method mainly relies on one parameter, σo (i.e., a time independent growth rate), which represents the collective impact of a transmission rate (ß) and a recovery rate (ν). Utilizing an energy equation that describes the relationship between the time dependent and independent growth rates, our method offers a straightforward alternative for estimating peak times in ensemble predictions.

Efficacy of the neutralizing antibodies after the booster dose on SARS-CoV-2 Omicron variant and a two-year longitudinal antibody study on Wild Type convalescents.

OBJECTIVES: Waning vaccine-induced immunity and emergence of new severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) variants which may lead to immune escape, pose a major threat to the COVID-19 pandemic. Currently, enhanced efficacy of the neutralization antibodies (NAb) produced after the booster dose of vaccinations against the Omicron variant is the main focus of vaccine strategy research. In this study we have analyzed the potency of the NAbs and IgGs produced after the third vaccine dose in patients infected with Omicron variant and wild-type (WT) SARS-CoV-2. METHODS: We enrolled 75 patients with Omicron variant breakthrough infections, and 87 patients with WT infections. We recorded the clinical characteristics and vaccination information of all patients and measured the NAb and anti-S1 (spike protein) + N (nucleocapsid protein) IgG-binding antibodies against SARS-CoV-2 in serum samples of Omicron variant-infected patients at admission, and patients with WT COVID-19 infection from the time of admission and discharge, and one-year to two-years follow-ups. RESULTS: Our results demonstrated higher NAb levels, fewer clinical symptoms, and faster viral shedding in Omicron variant infected patients vaccinated with the booster dose. Hybrid immunity (natural infection plus vaccination) induces higher NAb levels than vaccine-only immunity. NAb and IgG levels decreased significantly at one-year follow-up in WT convalescents with natural infection. The NAb and IgG levels in booster-vaccinated COVID-19 patients were higher than those in two-dose-vaccinated patients. CONCLUSION: Our results suggest that booster vaccinations are required to improve the level of protective NAbs. Moreover, our data provide important evidence for vaccination strategies based on existing vaccines.

Using multi-focus group method as an effective tool for eliciting business system requirements: Verified by a case study.

This research aims to explore the multi-focus group method as an effective tool for systematically eliciting business requirements for business information system (BIS) projects. During the COVID-19 crisis, many businesses plan to transform their businesses into digital businesses. Business managers face a critical challenge: they do not know much about detailed system requirements and what they want for digital transformation requirements. Among many approaches used for understanding business requirements, the focus group method has been used to help elicit BIS needs over the past 30 years. However, most focus group studies about research practices mainly focus on a particular disciplinary field, such as social, biomedical, and health research. Limited research reported using the multi-focus group method to elicit business system requirements. There is a need to fill this research gap. A case study is conducted to verify that the multi-focus group method might effectively explore detailed system requirements to cover the Case Study business's needs from transforming the existing systems into a visual warning system. The research outcomes verify that the multi-focus group method might effectively explore the detailed system requirements to cover the business's needs. This research identifies that the multi-focus group method is especially suitable for investigating less well-studied, no previous evidence, or unstudied research topics. As a result, an innovative visual warning system was successfully deployed based on the multi-focus studies for user acceptance testing in the Case Study mine in Feb 2022. The main contribution is that this research verifies the multi-focus group method might be an effective tool for systematically eliciting business requirements. Another contribution is to develop a flowchart for adding to Systems Analysis & Design course in information system education, which may guide BIS students step by step on using the multi-focus group method to explore business system requirements in practice.

Proteomics Investigation of Diverse Serological Patterns in COVID-19.

Serum antibodies IgM and IgG are elevated during Coronavirus Disease 2019 (COVID-19) to defend against viral attacks. Atypical results such as negative and abnormally high antibody expression were frequently observed whereas the underlying molecular mechanisms are elusive. In our cohort of 144 COVID-19 patients, 3.5% were both IgM and IgG negative, whereas 29.2% remained only IgM negative. The remaining patients exhibited positive IgM and IgG expression, with 9.3% of them exhibiting over 20-fold higher titers of IgM than the others at their plateau. IgG titers in all of them were significantly boosted after vaccination in the second year. To investigate the underlying molecular mechanisms, we classed the patients into four groups with diverse serological patterns and analyzed their 2-year clinical indicators. Additionally, we collected 111 serum samples for TMTpro-based longitudinal proteomic profiling and characterized 1494 proteins in total. We found that the continuously negative IgM and IgG expression during COVID-19 were associated with mild inflammatory reactions and high T cell responses. Low levels of serum IgD, inferior complement 1 activation of complement cascades, and insufficient cellular immune responses might collectively lead to compensatory serological responses, causing overexpression of IgM. Serum CD163 was positively correlated with antibody titers during seroconversion. This study suggests that patients with negative serology still developed cellular immunity for viral defense and that high titers of IgM might not be favorable to COVID-19 recovery.

Parameters and Morphological Changes of Erythrocytes and Platelets of COVID-19 Subjects: A Longitudinal Cohort Study.

Purpose: Information about dynamic changes occurring in the parameters and morphology of erythrocytes and platelets during the coronavirus disease 2019 (COVID-19) infection and convalescence is scarce. To explore potential associations between dynamic erythrocyte and platelet parameters, morphological changes, and the course or severity of the disease is essential. Patients and Methods: From January 17th, 2020, to February 20th, 2022, we followed up on 35 patients with non-severe and 11 patients with severe COVID-19 following their discharge. We collected clinical features, dynamic complete blood count (CBC), and peripheral blood smears (PBS) and analyzed parameter and morphological changes of erythrocytes and platelets depending on the course or severity of the disease. The course of the disease included four periods, namely onset (T1), discharge (T2), 1-year follow-up (T3), and 2-year follow-up (T4). Results: Red blood cell (RBC) counts and hemoglobin were the lowest in T2, followed by T1, and lower in T1 and T2 than in T3 and T4. Inversely, the red blood cell distribution width (RDW) was the highest in T2, followed by T1, and higher than in T3 and T4. Compared to non-severe patients, the platelet of severe patients was lower in T1 and T2. In contrast, the mean platelet volume (MPV) and platelet distribution width (PDW) tended to be higher in severe patients. Similarly, anisocytosis was more common in peripheral blood smears at early stages and in severe patients. Finally, large platelets were more common in severe patients. Conclusion: Anisocytosis of erythrocytes and large platelets are found in patients with severe COVID-19, these changes may help primary hospitals to identify patients with a high risk of severe COVID-19 at an early stage.

Heath management app use in Parkinson's disease and quality of life during the COVID-19 pandemic.

BACKGROUND: Social distancing during the COVID-19 pandemic affected follow-up visits and medication availability for patients with Parkinson's disease (PD). As a promising strategy to deal with these challenges, the implementation of health management smartphone apps was accelerated. However, whether more intense use of such apps could improve the quality of life (QoL) for PD patients during the COVID-19 pandemic was unknown. METHODS: Using a PD management app, this observational study assessed changes in QoL, as determined by PD Questionnaire 8 (PDQ-8), among PD patients before (Jan 20, 2019 to Oct 6, 2019) and after the beginning of the COVID-19 lockdown (Jan 20, 2020 to Oct 6, 2020). According to adherence to use of the app, participants were divided into low adherence, moderate adherence, and high adherence groups. A total of 4979 PD patients registered in the app, and 226 PD patients were enrolled, including 57 patients with low adherence, 112 with moderate adherence and 57 with high adherence. A generalized linear model was used to evaluate the change of PDQ-8 scores across these three different adherence groups. RESULTS: After the COVID-19 lockdown (1-year follow-up), the PDQ-8 scores are reduced by 0.8 (95% CI, 0.3-1.4) in all participants (P = 0.004). After adjustment for age, gender, education, disease duration and levodopa equivalent dose, PDQ-8 scores significantly less reduced in the high adherence group (0.3; 95% CI, 0.6-1.2) compared to the low adherence (1.9; 95% CI, 0.7-3.1) (P = 0.040) and moderate adherence groups (0.6; 95% CI, 0.2-1.3) (P = 0.012). CONCLUSIONS: A health management smartphone-based app might be a way to both measure and improve QoL among PD patients, provided that sufficient adherence is achieved.

The COVID-19 pandemic had an enormous impact on the lives of people living with Parkinson's disease (PD), given social distancing measures, and reduced access to healthcare. As a way to mitigate this, the use of health management apps was accelerated. However, there is a lack of studies on whether the use of such apps could over time affect the quality of life of people living with PD. Here, we analyzed changes in the quality of life of people living with PD using a health management app, before and after social distancing. We found that patients with high adherence to use of the app experienced a lower reduction of their quality of life. Using a health management smartphone app represents a novel approach that might help patients with PD improve their quality of life.

Longitudinal observation of viral load in patients infected with Omicron variant and its relationship with clinical symptoms.

Objective: In 2022, a new coronavirus variant (Omicron) infection epidemic broke out in Shanghai, China. However, it is unclear whether the duration of this omicron variant is different from that of the prototype strain. Methods: We retrospectively analyzed 157 cases of Omicron variant infection in Taizhou Public Health Center from March 29, 2022, to April 18, 2022, and observed the dynamics of nucleic acid Ct values during the admission and discharge of patients. Clinical and laboratory indicators of these patients were also obtained. Results: Compared to the prototype strain, the Omicron variant showed a broad population susceptibility in infected individuals (regardless of age and presence of underlying disease) and had slight damage to the immune system and renal function; the viral loads peaked was 2-3 days from disease onset; the median duration of omicron variant was 15-18 days; the nucleic acid Ct value of nasopharyngeal swabs of infected patients is lower than that of throat swabs, and the Ct value of oropharyngeal swabs is unstable during the recovery period. Conclusion: Therefore, we found that the time to peak viral load of this Omicron variant was 2-3 days after the onset of the disease, and the duration was 15-18 days; symptomatic patients had higher viral load and longer hospitalization time. This finding will provide a basis for understanding omicron variants and formulating the national prevention and control strategy.

Physical condition, psychological status, and posttraumatic stress disorder among recovered COVID-19 subjects: A mediation analysis.

The physical condition of individuals who contracted COVID-19 had a profound influence on mitigating the physical and psychological impact of the disease and the symptoms of posttraumatic stress disorder (PTSD). Little attention has been focused on the influence of physical condition on PTSD among recovered COVID-19 subjects. This study explored the relationship between physical and psychological status and PTSD and the potential mechanisms. Questionnaires were completed by 73 (50.7%, 73/144) COVID-19 recovered subjects who were diagnosed in Taizhou, Zhejiang, China. We conducted a face-to-face survey from January 17 to March 10, 2020. The mediation analysis approach was applied in this research. Our data show that recovered COVID-19 subjects who were in better physical condition exhibited fewer psychological problems [B (95%CI), (-1.65 -3.04, -0.26)] and lower PTSD [B (95%CI), -6.13 (-9.43, -2.83)]. In addition, the worse the psychological status of recovered COVID-19 subjects was, the stronger the PTSD (B [95%CI], 0.58 [0.02, 1.14]). Moreover, psychological status could significantly mediate the impact of physical condition on PTSD (ß1θ2 = -0.87). Together, COVID-19 recovered subjects who have better physical condition could decrease their PTSD, and the worse the physical condition of COVID-19 recovered subjects would increase their psychological problems. Our finding about psychological status could significantly mediate the impact of the physical condition on PTSD might be useful for medical institutions and the government seeking to help with the follow-up rehabilitation training of recovered COVID-19 subjects.

Longitudinal observation of viral load in patients infected with Omicron variant and its relationship with clinical symptoms

Objective In 2022, a new coronavirus variant (Omicron) infection epidemic broke out in Shanghai, China. However, it is unclear whether the duration of this omicron variant is different from that of the prototype strain. Methods We retrospectively analyzed 157 cases of Omicron variant infection in Taizhou Public Health Center from March 29, 2022, to April 18, 2022, and observed the dynamics of nucleic acid Ct values during the admission and discharge of patients. Clinical and laboratory indicators of these patients were also obtained. Results Compared to the prototype strain, the Omicron variant showed a broad population susceptibility in infected individuals (regardless of age and presence of underlying disease) and had slight damage to the immune system and renal function;the viral loads peaked was 2-3 days from disease onset;the median duration of omicron variant was 15-18 days;the nucleic acid Ct value of nasopharyngeal swabs of infected patients is lower than that of throat swabs, and the Ct value of oropharyngeal swabs is unstable during the recovery period. Conclusion Therefore, we found that the time to peak viral load of this Omicron variant was 2-3 days after the onset of the disease, and the duration was 15-18 days;symptomatic patients had higher viral load and longer hospitalization time. This finding will provide a basis for understanding omicron variants and formulating the national prevention and control strategy.

A prediction model for COVID-19 liver dysfunction in patients with normal hepatic biochemical parameters.

Coronavirus disease 2019 (COVID-19) patients with liver dysfunction (LD) have a higher chance of developing severe and critical disease. The routine hepatic biochemical parameters ALT, AST, GGT, and TBIL have limitations in reflecting COVID-19-related LD. In this study, we performed proteomic analysis on 397 serum samples from 98 COVID-19 patients to identify new biomarkers for LD. We then established 19 simple machine learning models using proteomic measurements and clinical variables to predict LD in a development cohort of 74 COVID-19 patients with normal hepatic biochemical parameters. The model based on the biomarker ANGL3 and sex (AS) exhibited the best discrimination (time-dependent AUCs: 0.60-0.80), calibration, and net benefit in the development cohort, and the accuracy of this model was 69.0-73.8% in an independent cohort. The AS model exhibits great potential in supporting optimization of therapeutic strategies for COVID-19 patients with a high risk of LD. This model is publicly available at https://xixihospital-liufang.shinyapps.io/DynNomapp/.

Physical condition, psychological status, and posttraumatic stress disorder among recovered COVID-19 subjects: A mediation analysis

The physical condition of individuals who contracted COVID-19 had a profound influence on mitigating the physical and psychological impact of the disease and the symptoms of posttraumatic stress disorder (PTSD). Little attention has been focused on the influence of physical condition on PTSD among recovered COVID-19 subjects. This study explored the relationship between physical and psychological status and PTSD and the potential mechanisms. Questionnaires were completed by 73 (50.7%, 73/144) COVID-19 recovered subjects who were diagnosed in Taizhou, Zhejiang, China. We conducted a face-to-face survey from January 17 to March 10, 2020. The mediation analysis approach was applied in this research. Our data show that recovered COVID-19 subjects who were in better physical condition exhibited fewer psychological problems [B (95%CI), (−1.65 −3.04, −0.26)] and lower PTSD [B (95%CI), −6.13 (−9.43, −2.83)]. In addition, the worse the psychological status of recovered COVID-19 subjects was, the stronger the PTSD (B [95%CI], 0.58 [0.02, 1.14]). Moreover, psychological status could significantly mediate the impact of physical condition on PTSD (β1θ2 = −0.87). Together, COVID-19 recovered subjects who have better physical condition could decrease their PTSD, and the worse the physical condition of COVID-19 recovered subjects would increase their psychological problems. Our finding about psychological status could significantly mediate the impact of the physical condition on PTSD might be useful for medical institutions and the government seeking to help with the follow-up rehabilitation training of recovered COVID-19 subjects.

Differences Between Omicron Infections and Fever Outpatients: Comparison of Clinical Manifestations and Initial Routine Hematology Indicators.

Purpose: We evaluated the differences between patients with SARS-CoV-2 Omicron variant infections and Fever outpatients, so that prevention and control measures can be taken in time. Patients and Methods: This study retrospectively analyzed 65 patients with SARS-CoV-2 Omicron variant. Sixty-nine age- and sex-matched Fever outpatients were enrolled during the same period of time. We also reanalyzed data from 81 SARS-CoV-2 Wild-Type-infected patients. We compared the clinical characteristics and initial indexes of routine tests among the 3 groups. Results: A total of 93.8% of the patients with Omicron infections had clinical symptoms, and the major symptoms were cough, fever and pharyngalgia. Pharyngalgia was a specific manifestation in Omicron group compared to Wild-Type group. The white blood cell of the Omicron group was lower than that of the Fever group [5.0 (3.6-6.1) vs 10.1 (7.6-12.9) ×109/L, P < 0.001]. The neutrophil count in Omicron group was lower than that in Fever and Wild-Type group [2.6 (1.8-3.9) vs 8.1 (5.9-10.9), P < 0.001; 2.6 (1.8-3.9) vs 3.4 (2.5-4.7) ×109/L, P < 0.001]. The white blood cell and neutrophil counts were lower in Omicron group than in the Fever group. The top 5 major symptoms were fever, cough, pharyngalgia, headache and expectoration. Conclusion: There are differences between the patients with Omicron infections and Fever outpatients, both in clinical manifestations and initial routine hematology indicators. We hope to provide some clues for early identification combined with a history of living in the epidemic area.

Clinical practice of rapid antigen tests for SARS-CoV-2 Omicron variant: A single-center study in China.

Responding to the fast-spreading SARS-CoV-2 Omicron variant, to improve screening efficiency, rapid antigen tests (RATs) were first added as a supplementary detection method in China in mid-March, 2022. What and how big a role RATs should play need to be supported by clinical data. Here, RAT performance and relevant factors in comparison with nucleic acid amplification tests (NAATs) were assessed in Omicron-infected inpatients. From the NAAT results, nasopharyngeal swabs (NPs) performed better than oropharyngeal swabs (OPs). RATs tested on NAAT positive NPs performed better than those with OP-positive samples. The RAT positivity rate was strongly associated with high levels of N and OFR1ab genes, especially in NPs where patients also had significantly longer hospital stays and shorter days from symptom onset to RAT testing. Self-performed RATs had a detection accuracy that was comparable to professionally performed RATs when the subjects were well guided. The antigen negative rate of the studied patients was 100% at discharge. These findings suggest that, in addition to a supplementary detection role, RATs can be an important strategy for evaluating the disease progression of Omicron-infected inpatients. This study provides important clinical data to support better rules regarding RATs under China's COVID-19 prevention and control policy.

Integration of protein context improves protein-based COVID-19 patient stratification.

BACKGROUND: Classification of disease severity is crucial for the management of COVID-19. Several studies have shown that individual proteins can be used to classify the severity of COVID-19. Here, we aimed to investigate whether integrating four types of protein context data, namely, protein complexes, stoichiometric ratios, pathways and network degrees will improve the severity classification of COVID-19. METHODS: We performed machine learning based on three previously published datasets. The first was a SWATH (sequential window acquisition of all theoretical fragment ion spectra) MS (mass spectrometry) based proteomic dataset. The second was a TMTpro 16plex labeled shotgun proteomics dataset. The third was a SWATH dataset of an independent patient cohort. RESULTS: Besides twelve proteins, machine learning also prioritized two complexes, one stoichiometric ratio, five pathways, and five network degrees, resulting a 25-feature panel. As a result, a model based on the 25 features led to effective classification of severe cases with an AUC of 0.965, outperforming the models with proteins only. Complement component C9, transthyretin (TTR) and TTR-RBP (transthyretin-retinol binding protein) complex, the stoichiometric ratio of SAA2 (serum amyloid A proteins 2)/YLPM1 (YLP Motif Containing 1), and the network degree of SIRT7 (Sirtuin 7) and A2M (alpha-2-macroglobulin) were highlighted as potential markers by this classifier. This classifier was further validated with a TMT-based proteomic data set from the same cohort (test dataset 1) and an independent SWATH-based proteomic data set from Germany (test dataset 2), reaching an AUC of 0.900 and 0.908, respectively. Machine learning models integrating protein context information achieved higher AUCs than models with only one feature type. CONCLUSION: Our results show that the integration of protein context including protein complexes, stoichiometric ratios, pathways, network degrees, and proteins improves phenotype prediction.

The Correlation Between Triglyceride-Glucose Index and SARS-CoV-2 RNA Re-Positive in Discharged COVID-19 Patients.

Objective: Facing the challenge to manage the SARS-CoV-2 RNA re-positive in discharged COVID-19 patients, it is necessary to explore the limited early risk factors for identifying SARS-CoV-2 RNA re-positive. The triglyceride and glucose index (TyG) has been developed as a surrogate marker of insulin resistance. This study aims to evaluate the correlation of the TyG index with the re-positive of COVID-19. Methods: A total of 144 COVID-19 patients from Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University (China) were enrolled in this study. All of them were discharged after recovery according to the guidelines. We compared the clinical characteristics and laboratory indexes of re-positive and non-re-positive COVID-19 patients, and analyzed the early risk factors for identifying SARS-CoV-2 RNA re-positive. Results: During the follow-up, a total of 18 patients were tested re-positive for SARS-CoV-2 RNA. Re-positive COVID-19 patients had higher proportion of abidol (P=0.018), antibiotic use (P=0.024) and hepatitis-based diseases (P=0.042), and higher heart rate (P=0.011) at admission (P=0.026), while lower TyG index (P=0.036), eGFR (P=0.034), TG (P=0.015) and C1q (P=0.023). Multivariate logistic regression analysis showed that TyG index was an independent risk factor for the re-positive of SARS-CoV-2 RNA (P=0.005). TyG index was significantly correlated with Glu (P<0.001), TG (P<0.001) and HDL-C (P<0.001). In addition, it was found that TyG index decreased at SARS-CoV-2 RNA positive stage and increased at negative stage (P<0.05). Conclusion: TyG index may be a valuable marker for identifying the re-positive of COVID-19 patients and may play a role in determining the stage of the patient's disease. We hope to provide a reliable theoretical basis for clinical prediction and effective control of re-positive episodes, and to provide a breakthrough for further research on the causes of re-positive episodes and the immune mechanism of the virus.

Quality of Life and Mental Health Status in Recovered COVID-19 Subjects at Two Years after Infection in Taizhou, China: A Longitudinal Cohort Study.

According to previous studies, mental status in 1-year COVID-19 survivors might range from 6-43%. Longer-term psychological consequences in recovered COVID-19 subjects are unknown, so we analyzed longer-term quality of life and mental status in recovered COVID-19 subjects at 2 years after infection. Among 144 recovered COVID-19 subjects in the Taizhou region, 73 and 45 completed face-to-face follow-ups at the first year and second year after infection, respectively, with a 61.7% follow-up rate. The questionnaire, which was administered at both follow-ups, included questions about quality of life, psychological health, and post-traumatic stress disorder (PTSD). The Mann-Whitney U test was used to the differences of each scale between the first and second year. Among the 45 people who completed both follow-up visits, the incidence of psychological problems was 4.4% (2/45) in the first year, and no new psychological abnormalities were observed in the second year. Quality of life improved, while the General Health Questionnaire (GHQ-12) and Impact of Event Scale-Revised (IES-R) scores did not improve over time. The incidence of mental disorders was lower than those in previous studies. Multidisciplinary management for COVID-19 in this study hospital may have reduced the frequency to a certain extent. However, among those with mental health problems, such problems may exist for a long time, and long-term attention should be given to the psychological status of recovered COVID-19 subjects.