Current hotspot and study trend of innate immunity in COVID-19: a bibliometric analysis from 2020 to 2022.

Background: Since the coronavirus disease 2019 (COVID-19) has spread throughout the world, many studies on innate immunity in COVID-19 have been published, and great progress has been achieved, while bibliometric analysis on hotspots and research trends in this field remains lacking. Methods: On 17 November 2022, articles and reviews on innate immunity in COVID-19 were recruited from the Web of Science Core Collection (WoSCC) database after papers irrelevant to COVID-19 were further excluded. The number of annual publications and the average citations per paper were analyzed by Microsoft Excel. Bibliometric analysis and visualization of the most prolific contributors and hotspots in the field were performed by VOSviewer and CiteSpace software. Results: There were 1,280 publications that met the search strategy on innate immunity in COVID-19 and were published from 1 January 2020 to 31 October 2022. Nine hundred thirteen articles and reviews were included in the final analysis. The USA had the highest number of publications (Np) at 276 and number of citations without self-citations (Nc) at 7,085, as well as an H-index of 42, which contributed 30.23% of the total publications, followed by China (Np: 135, Nc: 4,798, and H-index: 23) with 14.79% contribution. Regarding Np for authors, Netea, Mihai G. (Np: 7) from the Netherlands was the most productive author, followed by Joosten, Leo A. B. (Np: 6) and Lu, Kuo-Cheng (Np: 6). The Udice French Research Universities had the most publications (Np: 31, Nc: 2,071, H-index: 13), with an average citation number (ACN) at 67. The journal Frontiers in Immunology possessed the most publications (Np: 89, Nc: 1,097, ACN: 12.52). "Evasion" (strength 1.76, 2021-2022), "neutralizing antibody" (strength 1.76, 2021-2022), "messenger RNA" (strength 1.76, 2021-2022), "mitochondrial DNA" (strength 1.51, 2021-2022), "respiratory infection" (strength 1.51, 2021-2022), and "toll-like receptors" (strength 1.51, 2021-2022) were the emerging keywords in this field. Conclusion: The study on innate immunity in COVID-19 is a hot topic. The USA was the most productive and influential country in this field, followed by China. The journal with the most publications was Frontiers in Immunology. "Messenger RNA," "mitochondrial DNA," and "toll-like receptors" are the current hotspots and potential targets in future research.

Case report: New insights into persistent chronic pelvic pain syndrome with comorbid somatic symptom disorder.

Chronic pelvic pain syndrome (CPPS) is generally defined as pain in the pelvic area that persisted for 3-6 months or longer. The pain can be constant or episodic and functionally disabling. Any dysfunction of the central nervous system can lead to central sensitization, which enhances and maintains pain as well as other symptoms that are mediated by the central nervous system. It occurs in subgroups of nearly every chronic pain condition and is characterized by multifocal pain and co-occurring somatic symptoms. Somatic symptom disorder (SSD) is defined as a condition in which having one or more somatic symptoms, such as excessive worries, pressure, and catastrophic events. These symptoms can be very disruptive to a patient's life and can cause significant distress. SSD cases with severe symptoms frequently undergo repeated medical investigations and the symptoms often lead patients to seek emergency medical treatment and consult with specialists repeatedly, which is a source of frustration for patients and clinicians. Here we report a case that Asian female with persistent CPPS with comorbid SSD, who got in trouble for up to 8 years. This case reminds clinicians to pay excessive attention to the diagnosis of CPPS with comorbid SSD after recovery from acute COVID-19, with hope of raising awareness in the identification of SSD and present new insight into appropriate treatment for each woman who suffers from it.

Case report: New insights into persistent chronic pelvic pain syndrome with comorbid somatic symptom disorder

Chronic pelvic pain syndrome (CPPS) is generally defined as pain in the pelvic area that persisted for 3–6 months or longer. The pain can be constant or episodic and functionally disabling. Any dysfunction of the central nervous system can lead to central sensitization, which enhances and maintains pain as well as other symptoms that are mediated by the central nervous system. It occurs in subgroups of nearly every chronic pain condition and is characterized by multifocal pain and co-occurring somatic symptoms. Somatic symptom disorder (SSD) is defined as a condition in which having one or more somatic symptoms, such as excessive worries, pressure, and catastrophic events. These symptoms can be very disruptive to a patient's life and can cause significant distress. SSD cases with severe symptoms frequently undergo repeated medical investigations and the symptoms often lead patients to seek emergency medical treatment and consult with specialists repeatedly, which is a source of frustration for patients and clinicians. Here we report a case that Asian female with persistent CPPS with comorbid SSD, who got in trouble for up to 8 years. This case reminds clinicians to pay excessive attention to the diagnosis of CPPS with comorbid SSD after recovery from acute COVID-19, with hope of raising awareness in the identification of SSD and present new insight into appropriate treatment for each woman who suffers from it.

Addressing psychosomatic issues after lifting the COVID-19 policy in China: A wake-up call.

The Coronavirus has infected up to 900 million people as of 11 Jan 2023 in China Mainland, which is more than 60% of the population. The sudden and unprecedented nature of pandemic has resulted in a range of psychosomatic issues among the population. These issues can manifest in a variety of ways and it is important to address these issues as they can have serious consequences for individuals' mental and physical health. The lifting of lockdown measures in China presents an opportunity to address these issues and provide support to those who have been affected.

A systematic review and meta-analysis on prevalence of and risk factors associated with depression, anxiety and insomnia in infectious diseases, including COVID-19: a call to action.

Infectious disease epidemics have become more frequent and more complex during the 21st century, posing a health threat to the general public and leading to psychological symptoms. The current study was designed to investigate the prevalence of and risk factors associated with depression, anxiety and insomnia symptoms during epidemic outbreaks, including COVID-19. We systematically searched the PubMed, Embase, Web of Science, OVID, Medline, Cochrane databases, bioRxiv and medRxiv to identify studies that reported the prevalence of depression, anxiety or insomnia during infectious disease epidemics, up to August 14th, 2020. Prevalence of mental symptoms among different populations including the general public, health workers, university students, older adults, infected patients, survivors of infection, and pregnant women across all types of epidemics was pooled. In addition, prevalence of mental symptoms during COVID-19 was estimated by time using meta-regression analysis. A total of 17,506 papers were initially retrieved, and a final of 283 studies met the inclusion criteria, representing a total of 948,882 individuals. The pooled prevalence of depression ranged from 23.1%, 95% confidential intervals (95% CI: [13.9-32.2]) in survivors to 43.3% (95% CI: [27.1-59.6]) in university students, the pooled prevalence of anxiety ranged from 25.0% (95% CI: [12.0-38.0]) in older adults to 43.3% (95% CI: [23.3-63.3]) in pregnant women, and insomnia symptoms ranged from 29.7% (95% CI: [24.4-34.9]) in the general public to 58.4% (95% CI: [28.1-88.6]) in university students. Prevalence of moderate-to-severe mental symptoms was lower but had substantial variation across different populations. The prevalence of mental problems increased over time during the COVID-19 pandemic among the general public, health workers and university students, and decreased among infected patients. Factors associated with increased prevalence for all three mental health symptoms included female sex, and having physical disorders, psychiatric disorders, COVID infection, colleagues or family members infected, experience of frontline work, close contact with infected patients, high exposure risk, quarantine experience and high concern about epidemics. Frequent exercise and good social support were associated with lower risk for these three mental symptoms. In conclusion, mental symptoms are common during epidemics with substantial variation across populations. The population-specific psychological crisis management are needed to decrease the burden of psychological problem and improve the mental wellbeing during epidemic.

Statistical Analysis and Machine Learning Prediction of Disease Outcomes for COVID-19 and Pneumonia Patients.

The Coronavirus Disease 2019 (COVID-19) has spread all over the world and impacted many people's lives. The characteristics of COVID-19 and other types of pneumonia have both similarities and differences, which confused doctors initially to separate and understand them. Here we presented a retrospective analysis for both COVID-19 and other types of pneumonia by combining the COVID-19 clinical data, eICU and MIMIC-III databases. Machine learning models, including logistic regression, random forest, XGBoost and deep learning neural networks, were developed to predict the severity of COVID-19 infections as well as the mortality of pneumonia patients in intensive care units (ICU). Statistical analysis and feature interpretation, including the analysis of two-level attention mechanisms on both temporal and non-temporal features, were utilized to understand the associations between different clinical variables and disease outcomes. For the COVID-19 data, the XGBoost model obtained the best performance on the test set (AUROC = 1.000 and AUPRC = 0.833). On the MIMIC-III and eICU pneumonia datasets, our deep learning model (Bi-LSTM_Attn) was able to identify clinical variables associated with death of pneumonia patients (AUROC = 0.924 and AUPRC = 0.802 for 24-hour observation window and 12-hour prediction window). The results highlighted clinical indicators, such as the lymphocyte counts, that may help the doctors to predict the disease progression and outcomes for both COVID-19 and other types of pneumonia.

Efficacy and practice of facemask use in general population: a systematic review and meta-analysis.

In recent decades, respiratory infections, including SARS, HINI and the currently spreading COVID-19, caused by various viruses such as influenza and coronavirus have seriously threatened human health. It has generated inconsistent recommendations on the mandatory use of facemasks across countries on a population level due to insufficient evidence on the efficacy of facemask use among the general population. This meta-analysis aimed to explore (1) the efficacy of facemask use on preventing respiratory infections, and (2) the perceptions, intentions, and practice about facemask use among the general population worldwide. We searched PubMed, MEDLINE, Web of Science, Cochrane, bioRxiv, and medRxiv databases since inception to August 17, 2020. From 21,341 records identified, eight RCTs on facemask in preventing infections and 78 studies on perception, intention, and practice of facemask use among the general population were included in the analysis. The meta-analysis of RCTs found a significant protective effect of facemask intervention (OR = 0.84; 95% CI = 0.71-0.99; I2 = 0%). This protective effect was even more pronounced when the intervention duration was more than two weeks (OR = 0.76; 95% CI = 0.66-0.88; I2 = 0%). The meta-analysis of observational studies on perception, intention, and practice on facemask use showed that 71% of respondents perceived facemasks to be effective for infection prevention, 68% of respondents would wear facemasks, and 54% of respondents wore facemasks for preventing respiratory infections. Differences in perception, intention, and practice behavior of facemask use in different regions may be related to the impact of respiratory infections, regional culture, and policies. The governments and relevant organizations should make effort to reduce the barriers in the use of facemasks.

ACE2 and TMPRSS2 in human saliva can adsorb to the oral mucosal epithelium.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is primarily transmitted through droplets. All human tissues with the angiotensin-converting enzyme 2 (ACE2) and transmembrane protease serines 2 (TRMPRSS2) are potential targets of SARS-CoV-2. The role of saliva in SARS-CoV-2 transmission remains obscure. In this study, we attempted to reveal ACE2 and TRMPRSS2 protein expression in human parotid, submandibular, and sublingual glands (three major salivary glands). Then, the binding function of spike protein to ACE2 in three major salivary glands was detected. The expression of ACE2 and TMPRSS2 in human saliva from parotid glands were both examined. Exogenous recombined ACE2 and TMPRSS2 anchoring and fusing to oral mucosal epithelial cells in vitro were also unraveled. ACE2 and TMPRSS2 were found mainly to be expressed in the cytomembrane and cytoplasm of epithelial cells in the serous acinus cells in parotid and submandibular glands. Our research also discovered that the spike protein of SARS-CoV-2 binds to ACE2 in salivary glands in vitro. Furthermore, exogenous ACE2 and TMPRSS2 can anchor and fuse to oral mucosa in vitro. Thus, the expression of ACE2 and TMPRSS2 in human saliva might have implications for SARS-CoV-2 infection.

A systematic review and meta-analysis on the prevalence of stigma in infectious diseases, including COVID-19: a call to action.

Infectious diseases, including COVID-19, are crucial public health issues and may lead to considerable fear among the general public and stigmatization of, and discrimination against, specific populations. This meta-analysis aimed to estimate the pooled prevalence of stigma in infectious disease epidemics. We systematically searched PubMed, PsycINFO, Embase, MEDLINE, Web of Science, and Cochrane databases since inception to June 08, 2021, and reported the prevalence of stigma towards people with infectious diseases including SARS, H1N1, MERS, Zika, Ebola, and COVID-19. A total of 50 eligible articles were included that contributed 51 estimates of prevalence in 92722 participants. The overall pooled prevalence of stigma across all populations was 34% [95% CI: 28-40%], including enacted stigma (36% [95% CI: 28-44%]) and perceived stigma (31% [95% CI: 22-40%]). The prevalence of stigma in patients, community population, and health care workers, was 38% [95% CI: 12- 65%], 36% [95% CI: 28-45%], and 30% [95% CI: 20-40%], respectively. The prevalence of stigma in participants from low- and middle-income countries was 37% [95% CI: 29-45%], which is higher than that from high-income countries (27% [95% CI: 18-36%]) though this difference was not statistically significant. A similar trend of prevalence of stigma was also observed in individuals with lower education (47% [95% CI: 23-71%]) compared to higher education level (33% [95% CI: 23-4%]). These findings indicate that stigma is a significant public health concern, and effective and comprehensive interventions are needed to counteract the damaging effects of the infodemics during infectious disease epidemics, including COVID-19, and reduce infectious disease-related stigma.

Fuzzy System Based Medical Image Processing for Brain Disease Prediction.

The present work aims to explore the performance of fuzzy system-based medical image processing for predicting the brain disease. The imaging mechanism of NMR (Nuclear Magnetic Resonance) and the complexity of human brain tissues cause the brain MRI (Magnetic Resonance Imaging) images to present varying degrees of noise, weak boundaries, and artifacts. Hence, improvements are made over the fuzzy clustering algorithm. A brain image processing and brain disease diagnosis prediction model is designed based on improved fuzzy clustering and HPU-Net (Hybrid Pyramid U-Net Model for Brain Tumor Segmentation) to ensure the model safety performance. Brain MRI images collected from a Hospital, are employed in simulation experiments to validate the performance of the proposed algorithm. Moreover, CNN (Convolutional Neural Network), RNN (Recurrent Neural Network), FCM (Fuzzy C-Means), LDCFCM (Local Density Clustering Fuzzy C-Means), and AFCM (Adaptive Fuzzy C-Means) are included in simulation experiments for performance comparison. Results demonstrate that the proposed algorithm has more nodes, lower energy consumption, and more stable changes than other models under the same conditions. Regarding the overall network performance, the proposed algorithm can complete the data transmission tasks the fastest, basically maintaining at about 4.5 s on average, which performs remarkably better than other models. A further prediction performance analysis reveals that the proposed algorithm provides the highest prediction accuracy for the Whole Tumor under DSC (Dice Similarity Coefficient), reaching 0.936. Besides, its Jaccard coefficient is 0.845, proving its superior segmentation accuracy over other models. In a word, the proposed algorithm can provide higher accuracy, a more apparent denoising effect, and the best segmentation and recognition effect than other models while ensuring energy consumption. The results can provide an experimental basis for the feature recognition and predictive diagnosis of brain images.

Site-specific N-glycosylation Characterization of Recombinant SARS-CoV-2 Spike Proteins.

The glycoprotein spike (S) on the surface of severe acute respiratory syndrome coronavirus (SARS-CoV-2) is a determinant for viral invasion and host immune response. Herein, we characterized the site-specific N-glycosylation of S protein at the level of intact glycopeptides. All 22 potential N-glycosites were identified in the S-protein protomer and were found to be preserved among the 753 SARS-CoV-2 genome sequences. The glycosites exhibited glycoform heterogeneity as expected for a human cell-expressed protein subunit. We identified masses that correspond to 157 N-glycans, primarily of the complex type. In contrast, the insect cell-expressed S protein contained 38 N-glycans, completely of the high-mannose type. Our results revealed that the glycan types were highly determined by the differential processing of N-glycans among human and insect cells, regardless of the glycosites' location. Moreover, the N-glycan compositions were conserved among different sizes of subunits. Our study indicates that the S protein N-glycosylation occurs regularly at each site, albeit the occupied N-glycans were diverse and heterogenous. This N-glycosylation landscape and the differential N-glycan patterns among distinct host cells are expected to shed light on the infection mechanism and present a positive view for the development of vaccines and targeted drugs.

Prevalence of posttraumatic stress disorder after infectious disease pandemics in the twenty-first century, including COVID-19: a meta-analysis and systematic review.

Pandemics have become more frequent and more complex during the twenty-first century. Posttraumatic stress disorder (PTSD) following pandemics is a significant public health concern. We sought to provide a reliable estimate of the worldwide prevalence of PTSD after large-scale pandemics as well as associated risk factors, by a systematic review and meta-analysis. We systematically searched the MedLine, Embase, PsycINFO, Web of Science, CNKI, WanFang, medRxiv, and bioRxiv databases to identify studies that were published from the inception up to August 23, 2020, and reported the prevalence of PTSD after pandemics including sudden acute respiratory syndrome (SARS), H1N1, Poliomyelitis, Ebola, Zika, Nipah, Middle Eastern respiratory syndrome coronavirus (MERS-CoV), H5N1, and coronavirus disease 2019 (COVID-19). A total of 88 studies were included in the analysis, with 77 having prevalence information and 70 having risk factors information. The overall pooled prevalence of post-pandemic PTSD across all populations was 22.6% (95% confidence interval (CI): 19.9-25.4%, I2: 99.7%). Healthcare workers had the highest prevalence of PTSD (26.9%; 95% CI: 20.3-33.6%), followed by infected cases (23.8%: 16.6-31.0%), and the general public (19.3%: 15.3-23.2%). However, the heterogeneity of study findings indicates that results should be interpreted cautiously. Risk factors including individual, family, and societal factors, pandemic-related factors, and specific factors in healthcare workers and patients for post-pandemic PTSD were summarized and discussed in this systematic review. Long-term monitoring and early interventions should be implemented to improve post-pandemic mental health and long-term recovery.

Community evidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission through air.

BACKGROUND: Nine COVID-19 (Corona Virus Disease, 2019) cases were observed in one community in Guangzhou. All the cases lived in three vertically aligned units of one building sharing the same piping system, which provided one unique opportunity to examine the transmission mode of SARS-CoV-2. METHODS: We interviewed the cases on the history of travelling and close contact with the index patients. Respiratory samples from all the cases were collected for viral phylogenetic analyses. A simulation experiment in the building and a parallel control experiment in a similar building were then conducted to investigate the possibility of transmission through air. RESULTS: Index patients living in Apartment 15-b had a travelling history in Wuhan, and four cases who lived in Apartment 25-b and 27-b were subsequently diagnosed. Phylogenetic analyses showed that virus of all the patients were from the same strain of the virus. No close contacts between the index cases and other families indicated that the transmission might not occur through droplet and close contacts. Airflow detection and simulation experiment revealed that flushing the toilets could increase the speed of airflow in the pipes and transmitted the airflow from Apartment 15-b to 25-b and 27-b. Reduced exhaust flow rates in the infected building might have contributed to the outbreak. CONCLUSIONS: The outbreak of COVID-19 in this community could be largely explained by the transmission through air, and future efforts to prevent the infection should take the possibility of transmission through air into consideration. A disconnected drain pipe and exhaust pipe for toilet should be considered in the architectural design to help prevent possible virus spreading through the air.

Sewage as a Possible Transmission Vehicle During a Coronavirus Disease 2019 Outbreak in a Densely Populated Community: Guangzhou, China, April 2020.

BACKGROUND: Sewage transmission of SARS-CoV-2 has never been demonstrated. During a COVID-19 outbreak in Guangzhou, China in April 2020, we investigated the mode of transmission. METHODS: We collected clinical and environmental samples from quarantined residents and their environment for RT-PCR testing and genome sequencing. A case was a resident with a positive RT-PCR test regardless of symptoms. We conducted a retrospective cohort study of all residents of cases' buildings to identify risk factors. RESULTS: We found 8 cases (onset: 5-21 April). During incubation period, cases 1 and 2 frequented market T where a COVID-19 outbreak was ongoing; cases 3-8 never visited market T, lived in separate buildings and never interacted with cases 1 and 2. Working as a janitor or wastepicker (RR = 13; 95% CIexact, 2.3-180), not changing to clean shoes (RR = 7.4; 95% CIexact, 1.8-34) and handling dirty shoes by hand (RR = 6.3; 95% CIexact, 1.4-30) after returning home were significant risk factors. RT-PCR detected SARS-CoV-2 in 19% of 63 samples from sewage puddles or pipes, and 24% of 50 environmental samples from cases' apartments. Viruses from the squat toilet and shoe-bottom dirt inside the apartment of cases 1 and 2 were homologous with those from cases 3-8 and the sewage. Sewage from the apartment of cases 1 and 2 leaked out of a cracked pipe onto streets. Rainfall after the onset of cases 1 and 2 flooded the streets. CONCLUSIONS: SARS-CoV-2 might spread by sewage, highlighting the importance of sewage management during outbreaks.

Efficacy analysis of hyperbaric oxygen therapy in the treatment of severe coronavirus disease 2019 patients

Objective To explore the potential mechanisms underlying the prominent efficiency of hyperbaric oxygen therapy (HBOT) in the treatment of severe coronavirus disease 2019 (COVID-19) patients. Methods Five COVID-19 patients, aged from 24 to 69 years old, received HBOT after routine therapies failed to stop the deterioration and progressive hypoxemia in General Hospital of the Yangtze River Shipping. The procedure of HBOT was as follows: compressed to 2.0 ATA (0.1 MPa gauge pressure, patient 1) or 1.6 ATA (0.06 MPa gauge pressure, patient 2-5) at a constant rate for 15 min, maintained for 90 min (first treatment) or 60 min (subsequent treatment), then decompressed to normal pressure for 20 min, once a day;the patients inhaled oxygen with the mask of Built-in-Breathing System continuously;and HBOT was ended when the daily mean pulse oxygen saturation (SpO2) in wards was above 95% for two days. The symptoms, respiratory rate (RR), SpO2, arterial blood gas analysis, blood routine, coagulation function, high-sensitivity C-reactive protein (hs-CRP) and chest computed tomography (CT) were collected. Paired t test was used to compare each index before and after treatment. Results After the first HBOT, the symptoms and signs of the five patients began to improve. Supine breathlessness disappeared after HBOT for four times, and digestive tract symptoms completely disappeared and only mild chest pain and breathlessness at rest and in motion remained after HBOT for five times. After finishing HBOT, the RR of the patients was significanlty lower than that before HBOT ([20.80±2.28] min-1 vs [27.20±5.40] min-1, P<0.05). After finishing HBOT, daily SpO2 in wards was increased day by day, and the daily mean SpO2 recovered to more than 95% after the first, second, third, third and sixth HBOT in the five patients, respectively. After the first HBOT decompression, SpO2 was (93.60±0.07)%, which was signficantly higher than that before HBOT ([73.20±6.42] %) (P<0.05). SpO2 values before compression of the second and third HBOT were signficantly higher than that before the first HBOT (both P<0.05). There was no significant difference in the SpO2 immediately before and after the third HBOT (P>0.05). Before HBOT, the arterial partial pressure of carbon dioxide (PaCO2) of the patients was (31.48±3.40) mmHg (1 mmHg=0.133 kPa), which was lower than the normal range (35-45 mmHg). After finishing HBOT, arterial partial pressure of oxygen ([130.20±18.58] mmHg), arterial oxygen saturation ([98.40±0.55]%), lymphocyte proportion (0.207 8±0.074 2) and lymphocyte count ([1.09±0.24]×109/L) were significantly higher than those before HBOT ([61.60±15.24] mmHg, [73.20±6.43]%, 0.094 6±0.062 1, and [0.61± 0.35]×109/L), while the levels of fibrinogen ([2.97±0.27] g/L) and hs-CRP ([7.76±6.95] mg/L) were significantly lower than those before HBOT ([4.45±0.94] g/L and [30.36±1.27] mg/L) (all P<0.05). The levels of lacttic acid and D-dimer were decreased after HBOT versus before HBOT ([1.13±0.10] mmol/L vs [2.16±1.71] mmol/L, [0.42±0.13] mg/L vs [1.84±1.29] mg/L), but the differences were not significant (both P>0.05). All the five patients had typical lung CT imaging changes of severe COVID-19 before HBOT, which were improved after HBOT. Conclusion Systemic hypoxia induced by persistent hypoxemia may be the main reason for the deterioration of severe COVID-19. The respiratory dysfunction of COVID-19 is mainly alveolar gas exchange dysfunction. HBOT may be the best way to correct the progressive hypoxemia which can not be controlled by atmospheric oxygen supply in severe COVID-19 patients. HBOT can provide enough oxygen supply for the continuous hypoxia tissues, and is beneficial to the recovery of immune function, circulatory function and stress level, so as to improve the condition of patients.

Effects of Clinical Factors on Medical Burden in Non-Severe COVID-19 Patients (preprint)

Background: To date, the medical resources and the important clinical risk factors of non-severe patients with the 2019 coronavirus disease (COVID-19) have not been investigated.Methods: we retrospectively analyszed 104 patients with COVID-19 admitted to the isolation ward in Hubei, China, from February to March 2020. The general information, clinical symptoms, blood test and CT imaging characteristics were analyzed. Results: The median length of stay (LOS) is 14 days, and the cost of hospitalization (COH) is ＄2,522.86. The main influencing factors include the following：① CT imaging: lesions of the lungs were bilateral and multiple. The range of involved and interstitial changes affect the medical burden significantly (P=0.009 and P=0.013, respectively); ②Treatments: Patients were more severe with high flow nasal cannula oxygen therapy (HFNC) or used methylprednisolone more than 1mg / kg; ③ Blood test indicators: lymphocyte (LC) count level <1,000 and increased LDH (Lactate dehydrogenase) level have impact on medical burden; ④ These indicators have significant impact on medical resource after regression analysis except for LDH.Conclusions: The hospitalization cost of non-severe COVID-19 is higher than that of the common CAP patients. The main influencing factors are multiple extensive interstitial changes on CT scans, absolute lymphocyte level <1,000, use of high-dose methylprednisolone and HFNC.

Aerosol and Surface Distribution of Severe Acute Respiratory Syndrome Coronavirus 2 in Hospital Wards, Wuhan, China, 2020.

To determine distribution of severe acute respiratory syndrome coronavirus 2 in hospital wards in Wuhan, China, we tested air and surface samples. Contamination was greater in intensive care units than general wards. Virus was widely distributed on floors, computer mice, trash cans, and sickbed handrails and was detected in air ≈4 m from patients.