Dynamic zero-COVID strategy in controlling COVID-19 in Shanghai, China: A cost-effectiveness analysis.

BACKGROUND: The sustainability and generalizability of China's dynamic zero-COVID strategy on eliminating SARS-CoV-2 transmission has casted doubt globally, mainly because it has exacted high social and economic cost. This study aimed to estimate the disease burden during the first wave of Omicron in China and compared the cost-effectiveness of implementing a Real-world strategy (adjusted dynamic zero-COVID strategy) with two simulated strategies (routine and stricter dynamic zero-COVID strategy) to inform appropriate strategies for COVID-19 pandemic control. METHODS: A dynamic state-transition simulation model was developed to compare the health and cost outcomes between different dynamic zero-COVID strategies. Omicron-related healthcare costs were estimated from the societal perspective. Epidemiological parameter values were derived from data of real-world or generated by model calibration; costs and effectiveness parameter values were informed either by local data or published literature. The primary outcomes were total social cost, disability adjusted life-years (DALYs) and net monetary benefit (NMB). Deterministic sensitivity analyses (DSA) and scenario analyses were performed to assess the model robustness. RESULTS: The first wave of Omicron in Shanghai resulted in 47,646 DALYs lost and 415 billion RMB losses. At a willingness-to-pay threshold of 173,630 RMB (the GDP per capita of Shanghai in 2021) per DALY saved, the Real-world strategy was considered as the most cost-effective strategy due to its highest NMB (-407 billion). Results from DSA confirmed the robustness of our findings. CONCLUSION: Our finding supported the Real-world strategy taken by the Shanghai Municipal Government between March 1 and May 21, 2022 to control the first wave of Omicron outbreak. Moreover, our results indicated that whether the Stricter dynamic zero-COVID strategy is worth implementing at the beginning of the COVID-19 outbreak mainly depended on the infection rate of COVID-19 among primary contacts. Our analysis provides important evidence to inform policy makers to make appropriate decisions regarding COVID-19 pandemic management.

COVID-19 inhibits spermatogenesis in the testes by inducing cellular senescence.

Introduction: COVID-19 (SARS-CoV-2) has been linked to organ damage in humans since its worldwide outbreak. It can also induce severe sperm damage, according to research conducted at numerous clinical institutions. However, the exact mechanism of damage is still unknown. Methods: In this study, testicular bulk-RNA-seq Data were downloaded from three COVID-19 patients and three uninfected controls from GEO to evaluate the effect of COVID-19 infection on spermatogenesis. Relative expression of each pathway and the correlation between genes or pathways were analyzed by bioinformatic methods. Results: By detecting the relative expression of each pathway and the correlation between genes or pathways, we found that COVID-19 could induce testicular cell senescence through MAPK signaling pathway. Cellular senescence was synergistic with MAPK pathway, which further affected the normal synthesis of cholesterol and androgen, inhibited the normal synthesis of lactate and pyruvate, and ultimately affected spermatogenesis. The medications targeting MAPK signaling pathway, especially MAPK1 and MAPK14, are expected to be effective therapeutic medications for reducing COVID-19 damage to spermatogenesis. Conclusion: These results give us a new understanding of how COVID-19 inhibits spermatogenesis and provide a possible solution to alleviate this damage.

The impact of COVID lockdown on glycaemic control in paediatric patients with type 1 diabetes: A systematic review and meta-analysis of 22 observational studies.

Introduction: The COVID lockdown has posted a great challenge to paediatric patients with type 1 diabetes (T1D) and their caregivers on the disease management. This systematic review and meta-analysis sought to compare the glycaemic control among paediatric patients with T1D (aged under 18 years) pre- during, and post-lockdown period. Methods and materials: We did a systematic search of three databases (PubMed, Embase, and the WHO COVID-19 Global literature) for the literature published between 1 Jan 2019 to 10 Sep 2022. Studies meeting the following inclusion criteria were eligible for this study: (1) a COVID-19 related study; (2) inclusion of children aged 18 years old or under with established T1D; (3) comparing the outcomes of interest during or after the COVID lockdown with that before the lockdown. Study endpoints included mean difference (MD) in HbA1c, blood glucose, time in range (TIR, 70-180 mg/dl), time above range (TAR, >180mg/dl), time below range (TBR,<70mg/dl) and glucose variability (coefficient of variation [CV]) between pre-lockdown and during lockdown and/or between pre- and post-lockdown period. The MD and its corresponding 95% CI of each endpoint were pooled using random-effect model considering the potential between-study heterogeneity in COVID restrictions and T1D management. Results: Initial search identified 4488 records and 22 studies with 2106 paediatric patients with T1D were included in the final analysis. Compared with pre-lockdown period, blood glucose was significantly decreased by 0.11 mmol/L (95%CI: -0.18, -0.04) during lockdown period and by 0.42 mmol/L (95%CI: -0.73, -0.11) after lockdown. The improvement was also found for TIR, TAR, TBR, and CV during and post-lockdown (all p values<0.05) except for the post-lockdown TBR (p =0.35). No significant change in HbA1c was observed during and post- lockdown period when compared with the pre-lockdown value. There was moderate to high between-study heterogeneity for most of the analyses. Conclusion: Compared with pre-lockdown period, there was significant improvement in T1D paediatric patients' glucose metrics during and post-lockdown. The underlying reasons for this positive impact warrant further investigation to inform future paediatric diabetes management. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022359213.

Understanding the Attitudes and Willingness of Adult Chinese Patients with Rheumatic Diseases Towards COVID-19 Vaccination.

Background: The SARS-CoV-2 pandemic has imposed substantial health and economic burdens on the societies. COVID-19 vaccination is the most effective method of controlling the epidemic. This study assessed the attitude, willingness, and related factors of adult patients with rheumatic diseases (RDs) in China towards COVID-19 vaccination and identified their reasons for being vaccinated. Methods:  A cross-sectional survey was administered to patients with rheumatic diseases from July 18 to August 18, 2021, using an online questionnaire. Logistic regression analysis was performed to examine the data. Results: We analyzed data drawn from 464 participants who provided valid responses. A total of 324 (69.83%) RD patients were not willing to be vaccinated, of which 76.97% believed that COVID-19 vaccination might exacerbate the diseases symptoms. Logistic regression analysis showed that a combination of experiencing systemic damage, being in the acute attack stage of the disease, and fear of the adverse impact of vaccination on rheumatism, etc., were the predominant factors affecting the intentional vaccination rate in adult patients with rheumatic diseases (p < 0.05). Conclusion: The COVID-19 intentional vaccination rate was relatively low in adult Chinese patients with RD. Public health education and the dissemination of government scientific data for patients with RD should be enhanced to increase COVID-19 vaccination rates.

An artificial intelligence-based radiomics model for differential diagnosis between coronavirus disease 2019 and other viral pneumonias

OBJECTIVE: To set up a differential diagnosis radiomics model to identify coronavirus disease 2019 (COVID-19) and other viral pneumonias based on an artificial intelligence (AI) approach that utilizes computed tomography (CT) images. MATERIALS AND METHODS: This retrospective multi-center research involved 225 patients with COVID-19 and 265 patients with other viral pneumonias. The least absolute shrinkage and selection operator algorithm was used for the optimized features selection from 1218 radiomics features. Finally, a logistic regression (LR) classifier was applied to construct different diagnosis models. The receiver operating characteristic curve analysis was applied to evaluate the accuracy of different models. RESULTS: The patients were divided into a training set (313 of 392, 80%), an internal test set (79 of 392, 20%) and an external test set (n = 98). Thirteen features were selected to build the machine learning-based CT radiomics models. LR classifiers performed well in the training set (area under the curve [AUC] = 0.91), internal test set (AUC = 0.94), and external test set (AUC = 0.91). Delong tests suggested there was no significant difference between training and the two test sets (P > 0.05). CONCLUSION: The use of an AI-based radiomics model enables rapid discrimination of patients with COVID-19 from other viral infections, which can aid better surveillance and control during a pneumonia outbreak.

Does aspirin have an effect on risk of death in patients with COVID-19? A meta-analysis.

PURPOSE: The coronavirus disease 2019 (COVID-19) pandemic has shown unprecedented impact world-wide since the eruption in late 2019. Importantly, emerging reports suggest an increased risk of thromboembolism development in patients with COVID-19. Meanwhile, it is found that aspirin reduced mortality in critically ill patients with non-COVID-19 acute respiratory distress syndrome. Therefore, a meta-analysis was performed to investigate the effects of aspirin on COVID-19 mortality. METHODS: A systematic literature search was conducted in 10 electronic databases and 4 registries. Random effects models were used to calculate pooled relative risks (RRs) with 95% confidence intervals (Cis) to estimate the effect of aspirin on COVID-19 mortality. Relevant subgroup analyses and sensitivity analyses were also performed. RESULTS: The results showed that aspirin use was associated with a reduction in COVID-19 mortality (adjusted RR 0.69; 95% CI 0.50-0.95; P < 0.001). Subgroup analysis found that the low-dose group was associated with a reduced COVID-19 mortality (adjusted RR 0.64; 95% CI 0.48-0.85; P < 0.01). Aspirin use was associated with reduced COVID-19 mortality in Europe and America (crude RR 0.71; 95% CI 0.52-0.98; P = 0.04), and results from cohort studies suggested that aspirin use was a protective factor for COVID-19 mortality (adjusted RR 0.73; 95% CI 0.52-0.99; P = 0.04). Meanwhile, aspirin use was not associated with bleeding risk (crude RR 1.22; 95% CI 0.80-1.87; P = 0.96). CONCLUSIONS: This meta-analysis found that aspirin use was associated with a reduction in mortality in patients with COVID-19 and not with an increased risk of bleeding.

Abrupt emissions reductions during COVID-19 contributed to record summer rainfall in China.

Record rainfall and severe flooding struck eastern China in the summer of 2020. The extreme summer rainfall occurred during the COVID-19 pandemic, which started in China in early 2020 and spread rapidly across the globe. By disrupting human activities, substantial reductions in anthropogenic emissions of greenhouse gases and aerosols might have affected regional precipitation in many ways. Here, we investigate such connections and show that the abrupt emissions reductions during the pandemic strengthened the summer atmospheric convection over eastern China, resulting in a positive sea level pressure anomaly over northwestern Pacific Ocean. The latter enhanced moisture convergence to eastern China and further intensified rainfall in that region. Modeling experiments show that the reduction in aerosols had a stronger impact on precipitation than the decrease of greenhouse gases did. We conclude that through abrupt emissions reductions, the COVID-19 pandemic contributed importantly to the 2020 extreme summer rainfall in eastern China.

Status, trends, and prospects of the channel catfish industry in China and the impact of the COVID-19 epidemic

In 1984, the Fisheries Research Institute of Hubei Province first introduced channel catfish from the US to China. Since then, the production of China's channel catfish has undergone volatile changes. In 2003, as a substitute for Pangasius fillets from Vietnam, the export volume of channel catfish-processed products increased considerably. In recent years, the Chinese channel catfish industry has shifted from dependence on American and European markets to dominance in Chinese markets. It is expected that the continuing impact of the Covid-19 epidemic in China and the development of the global pandemic will significantly affect the channel catfish farming sector in China. This paper outlines China's channel catfish industry's development, markets, costs, and benefits and provides some suggestions for its development.

The Correlation Between COVID-19 Activities and Climate Factors in Different Climate Types Areas.

OBJECTIVE: To investigate the epidemiological characteristics of human infection with corona virus disease 2019 (COVID-19) in Moscow, Lima, Kuwait, and Singapore to analyze the effects of climate factors on the incidence of COVID-19. METHODS: Collect the daily incidence of COVID-19 and related climate data in four areas, construct a negative binomial regression model, and analyze the correlation between the incidence of COVID-19 and meteorological factors. RESULTS: AH was the climate factor affecting the incidence of COVID-19 in Moscow, Lima, and Singapore; Ta and RH were the climate factors affecting the incidence of COVID-19 in Kuwait. CONCLUSIONS: The incidence of COVID-19 in four areas were all associated with the humidity, and climate factors should be taken into consideration when epidemic prevention measures are taken, and environment humidification may be a feasible approach to decrease COVID-19 virus transmission.

Stressors and the adaptation of telemedicine for women on poly(ADP-ribose) polymerase (PARP) inhibitor maintenance during the COVID-19 pandemic

Poly(ADP-ribose) polymerase inhibitor maintenance (PARPm) therapy is now available to all women with advanced ovarian cancer following response to initial chemotherapy. As the COVID-19 pandemic has resulted in unprecedented challenges for cancer patients, we aimed to evaluate the unique experience for women on maintenance PARP inhibitors. Women with a current or prior diagnosis of ovarian cancer completed an online survey focusing on treatment interruptions and quality of life (QOL). QOL was measured with the Cancer Worry Scale and Hospital Anxiety and Depression Scale. The survey was distributed through survivor networks and social media. The chi-square and ANOVA test were used with a Bonferroni correction to account for multiple comparison testing. Six hundred and three women, from 41 states, visited the survey website between March 30 and April 13, 2020 and 525 (87%) completed the survey and provided information on current treatment status. Sixty-four women (12%) were on PARPm, 153 (29%) on other anti-cancer therapy and 308 (59%) on no treatment. Other anticancer therapies included intravenous chemotherapy (61, 40%), anti-angiogenic (29, 19%), hormonal (25, 16%), oral chemotherapy (12, 8%), immunotherapy (10, 6.5%) and other (16, 10%). There were no differences among women on PARPm, no treatment or other treatment for disease stage, medical comorbidities, COVID-19 symptoms or treatment delays. Women on PARPm were more likely to be self-described as immunocompromised versus women not on treatment (79% vs. 34%, P<0.001) and women on hormonal therapy (79% vs. 40%, P=0.002) and similar to women on oral -anti-cancer therapy (78% vs. 58%, P=0.336). Women on PARPm were more likely to use telemedicine versus women not on treatment (44% vs. 16%, P<0.001) and had similar use of telemedicine compared to all other treatment groups. For women on PARPm, higher cancer worry scores were associated with increased use of telemedicine (used telemedicine - 14.4 vs. did not use telemedicine - 13.3, P=0.007). There were no significant differences in reported cancer worry, anxiety or depression between women on PARPm, other anti-cancer therapy and no treatment. [Display omitted] The COVID-19 crisis is impacting cancer care and it is critical that providers consider and address the unique stressors facing women with ovarian cancer during this challenging time. Women on PARPm, in particular, perceive themselves as immunocompromised, perhaps making them more open to alternative means of care delivery, as demonstrated by their willingness to adopt telemedicine. Women with ovarian cancer on PARPm report similar cancer worry, anxiety and depression to women not on treatment and those on other anti-cancer treatment. [ABSTRACT FROM AUTHOR] Copyright of Gynecologic Oncology is the property of Academic Press Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Leveraging health information technology to collect family cancer history: a systematic review and meta-analysis

Collection of an accurate and comprehensive family cancer history (FCH) can help to identify millions of individuals at risk-for familial cancer syndromes. However, there are no formal guidelines for FCH collection and, as a result, there is wide variability in in strategies employed and accuracy of family health history across medical systems. Information technology (IT) provides a promising solution, a tool that has been shown to improve clinical documentation, workflows, quality of care, patient safety, communication and clinical decision support, and that can be completed remotely and safely during a pandemic. The aim of this study is to evaluate the literature on existing strategies whereby medical providers utilize information technology (IT) to assemble FCH. A systematic search of online databases (PubMed, EMBASE, MEDLINE, and the Cochrane Library) between 1980 and 2020 was performed. Meta-analysis was used to estimate pooled results across studies. Statistical heterogeneity was assessed through the chi-square test (i.e., Cochrane Q test) and the inconsistency statistic (I2). A random effects analysis was used to calculate the pooled proportions and means. The comprehensive search produced 4005 publications. Thirty-two peer-reviewed studies met inclusion criteria. Twenty-seven distinct IT tools were evaluated which included the following categories: electronic survey administered prior to visit (21, 65.6%), electronic survey administered via tablet in the medical office (6, 18.8%), electronic survey via kiosk (4, 12.5%) and animated virtual counselor (1, 3.1%). Among the 196,566 included patients, 87.0% completed the FCH tool (electronic survey prior to the visit - 85.0 %;electronic survey in the medical office - 89.0 %). The time required for survey completion was 35.2 minutes (CI 14.3 -56.2). Twelve percent of patients (n=11,093) were referred for genetic assessment based on the output of the FCH tool. Among the studied methods of FCH collection, 7 (21.9%) had the capacity to interface directly with the patient's electronic medical record. [Display omitted] The rapidly advancing field of germline cancer genetics coupled with a growing emphasis on disease prevention and incorporation of technology into medical care algorithms prior to and accelerated by the COVID-19 pandemic make utilization of IT strategies for collection of FCH a promising option. Our systematic review and meta-analysis found that electronic FCH collection can be completed successfully by patients in a time efficient manner. This information may be useful as many healthcare systems continue to restructure the way in which patients interact with their healthcare teams. [ABSTRACT FROM AUTHOR] Copyright of Gynecologic Oncology is the property of Academic Press Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Factors contributing to treatment delays among Medicaid-insured patients with gynecologic malignancies during COVID-19 in New York City

When New York City (NYC) emerged as a COVID-19 epicenter, hospitals and clinicians were forced to quickly change practice models of health care delivery. We sought to determine the impact of COVID-19 on treatment delays that occurred during the peak of the pandemic among low-income gynecologic oncology patients in NYC. Medicaid-insured patients receiving gynecologic oncology care at two affiliated centers between March 15 and April 15, 2020 were identified for telephone interview. Eligible patients included those with precancerous or cancerous gynecologic diseases or hereditary breast and ovarian cancer (HBOC) syndromes. Demographics, clinical characteristics, and reasons for treatment delays were identified through self-report and confirmed with chart review at the time of interview and at 6-month follow up. Outcomes were classified as delays in the following: surgery, adjuvant treatment (chemotherapy/radiation), and surveillance visits. Of the 158 eligible patients identified, 100 completed the interview. A total of 47 patients experienced an average treatment delay of 85.3 days (range: 7-210): surveillance visit (n=33), surgery (n=10), chemotherapy (n=3), radiation (n=1). Within this group, the median age was 58 years (range: 19-86). Self-identified race included: African-American (23.5%), Hispanic (31.9%), non-Hispanic White (17%), Asian (9.1%), Other (8.5%). The majority of patients (80.9%) had an annual income < $40,000. Clinically relevant surveillance delays occurred in 3 patients. A delayed diagnosis of vulvar cancer due to missed biopsy (follow up at 49 days) and 2 patients with delayed diagnosis of recurrent ovarian/primary peritoneal cancer;one died from disease and the other is undergoing chemotherapy. Surgical delays were identified in 10 patients: high grade cervical/vulvar dysplasia (n=3);endometrial intraepithelial neoplasia (EIN) (n=2);endometrial cancer (n=2);risk reducing surgery for HBOC syndromes (n=2);metastatic gastrointestinal adenocarcinoma to the ovary (n=1). Among the patients with endometrial cancer, one procedure delayed by 1 week was able to proceed and one transferred care. No upstaging of cancer diagnosis resulted from delays. Chemotherapy delays occurred in 3 patients with an average delay of 47.7 days. Of these patients, 2 were found to have progression of disease resulting in death (n=1) and decision to pursue hospice (n=1);one had a personal COVID-19 diagnosis. A delay in radiation treatment of 70 days was reported in 2.1% (n=1). A total of 9 patients were lost to follow up. Characteristics of patients lost to follow up include Hispanic/Latino race/ethnicity, essential worker, living with children in a high COVID-positive area (37.5%, n=3) or individuals who experienced a change in employment status (25%;n=2). [Display omitted] COVID-19 resulted in significant treatment delays among Medicaid-insured gynecologic oncology patients. As we continue to minimize clinical encounters, interventions aimed at providing timely oncology care during the COVID-19 pandemic is essential to prevent widening disparities in low-income populations. [ABSTRACT FROM AUTHOR] Copyright of Gynecologic Oncology is the property of Academic Press Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Decreased inhibition of exosomal miRNAs on SARS-CoV-2 replication underlies poor outcomes in elderly people and diabetic patients.

Elderly people and patients with comorbidities are at higher risk of COVID-19 infection, resulting in severe complications and high mortality. However, the underlying mechanisms are unclear. In this study, we investigate whether miRNAs in serum exosomes can exert antiviral functions and affect the response to COVID-19 in the elderly and people with diabetes. First, we identified four miRNAs (miR-7-5p, miR-24-3p, miR-145-5p and miR-223-3p) through high-throughput sequencing and quantitative real-time PCR analysis, that are remarkably decreased in the elderly and diabetic groups. We further demonstrated that these miRNAs, either in the exosome or in the free form, can directly inhibit S protein expression and SARS-CoV-2 replication. Serum exosomes from young people can inhibit SARS-CoV-2 replication and S protein expression, while the inhibitory effect is markedly decreased in the elderly and diabetic patients. Moreover, three out of the four circulating miRNAs are significantly increased in the serum of healthy volunteers after 8-weeks' continuous physical exercise. Serum exosomes isolated from these volunteers also showed stronger inhibitory effects on S protein expression and SARS-CoV-2 replication. Our study demonstrates for the first time that circulating exosomal miRNAs can directly inhibit SARS-CoV-2 replication and may provide a possible explanation for the difference in response to COVID-19 between young people and the elderly or people with comorbidities.

Financial toxicity, mental health, and gynecologic cancer treatment: The effect of the COVID-19 pandemic among low-income women in New York City.

BACKGROUND: New York City (NYC) emerged as an epicenter of the COVID-19 pandemic, and marginalized populations were affected at disproportionate rates. The authors sought to determine the impact of COVID-19 on cancer treatment, anxiety, and financial distress among low-income patients with gynecologic cancer during the peak of the NYC pandemic. METHODS: Medicaid-insured women who were receiving gynecologic oncology care at 2 affiliated centers were contacted by telephone interviews between March 15 and April 15, 2020. Demographics and clinical characteristics were obtained through self-report and retrospective chart review. Financial toxicity, anxiety, and cancer worry were assessed using modified, validated surveys. RESULTS: In total, 100 patients completed the telephone interview. The median age was 60 years (range, 19-86 years), and 71% had an annual income <$40,000. A change in employment status and early stage cancer (stage I and II) were associated with an increase in financial distress (P < .001 and P = .008, respectively). Early stage cancer and telehealth participation were significantly associated with increased worry about future finances (P = .017 and P = .04, respectively). Lower annual income (<$40,000) was associated with increased cancer worry and anxiety compared with higher annual income (>$40,000; P = .036 and P = .017, respectively). When controlling for telehealth participation, income, primary language, and residence in a high COVID-19 prevalence area, a delay in medical care resulted in a 4-fold increased rate of anxiety (P = .023, 95% CI, 1.278-14.50). Race was not significantly associated with increased financial distress, cancer worry, or anxiety. CONCLUSIONS: Low socioeconomic status was the most common risk factor for increased financial distress, cancer worry, and anxiety. Interventions aimed at improving access to timely oncology care should be implemented during this ongoing pandemic.

Alteration of Autonomic Nervous System Is Associated With Severity and Outcomes in Patients With COVID-19.

BACKGROUND: Previous studies suggest that coronavirus disease 2019 (COVID-19) is a systemic infection involving multiple systems, and may cause autonomic dysfunction. OBJECTIVE: To assess autonomic function and relate the findings to the severity and outcomes in COVID-19 patients. METHODS: We included consecutive patients with COVID-19 admitted to the 21st COVID-19 Department of the east campus of Renmin Hospital of Wuhan University from February 6 to March 7, 2020. Clinical data were collected. Heart rate variability (HRV), N-terminal pro-B-type natriuretic peptide (NT-proBNP), D-dimer, and lymphocytes and subsets counts were analysed at two time points: nucleic-acid test positive and negative. Psychological symptoms were assessed after discharge. RESULTS: All patients were divided into a mild group (13) and a severe group (21). The latter was further divided into two categories according to the trend of HRV. Severe patients had a significantly lower standard deviation of the RR intervals (SDNN) (P < 0.001), standard deviation of the averages of NN intervals (SDANN) (P < 0.001), and a higher ratio of low- to high-frequency power (LF/HF) (P = 0.016). Linear correlations were shown among SDNN, SDANN, LF/HF, and laboratory indices (P < 0.05). Immune function, D-dimer, and NT-proBNP showed a consistent trend with HRV in severe patients (P < 0.05), and severe patients without improved HRV parameters needed a longer time to clear the virus and recover (P < 0.05). CONCLUSION: HRV was associated with the severity of COVID-19. The changing trend of HRV was related to the prognosis, indicating that HRV measurements can be used as a non-invasive predictor for clinical outcome.

Distribution Atlas of COVID-19 Pneumonia on Computed Tomography: A Deep Learning Based Description.

Objectives: To construct a distribution atlas of coronavirus disease 2019 (COVID-19) pneumonia on computed tomography (CT) and further explore the difference in distribution by location and disease severity through a retrospective study of 484 cases in Jiangsu, China. Methods: All patients diagnosed with COVID-19 from January 10 to February 18 in Jiangsu Province, China, were enrolled in our study. The patients were further divided into asymptomatic/mild, moderate, and severe/critically ill groups. A deep learning algorithm was applied to the anatomic pulmonary segmentation and pneumonia lesion extraction. The frequency of opacity on CT was calculated, and a color-coded distribution atlas was built. A further comparison was made between the upper and lower lungs, between bilateral lungs, and between various severity groups. Additional lesion-based radiomics analysis was performed to ascertain the features associated with the disease severity. Results: A total of 484 laboratory-confirmed patients with 945 repeated CT scans were included. Pulmonary opacity was mainly distributed in the subpleural and peripheral areas. The distances from the opacity to the nearest parietal/visceral pleura were shortest in the asymptomatic/mild group. More diffused lesions were found in the severe/critically ill group. The frequency of opacity increased with increased severity and peaked at about 3-4 or 7-8 o'clock direction in the upper lungs, as opposed to the 5 or 6 o'clock direction in the lower lungs. Lesions with greater energy, more circle-like, and greater surface area were more likely found in severe/critically ill cases than the others. Conclusion: This study constructed a detailed distribution atlas of COVID-19 pneumonia and compared specific patterns in different parts of the lungs at various severities. The radiomics features most associated with the severity were also found. These results may be valuable in determining the COVID-19 sub-phenotype. Supplementary Information: The online version contains supplementary material available at 10.1007/s43657-021-00011-4.