Analysis of Medication Utilization in Isolated Areas of Fever Clinics During the COVID-19 Epidemic Outbreak: A Multicenter Study in General Hospitals in China (preprint)

Objective: To analyze the demographic characteristics and patterns of medication use among patients in fever clinics (FCs) during the COVID-19 outbreak in China and provide information for COVID-19 treatment. Method: Various-grade general hospitals in China were selected, and patient information was extracted during the initial wave of the COVID-19 epidemic. Demographic characteristics were analyzed, including visit time, age, sampling morbidity rate, and disease distribution. Prescription information from the FC database was extracted to analyze drug use and the rationality of the medication. Result: Between September 1 and December 31, 2022, 41,445 patients received treatment at FCs in 11 included hospitals. After the relaxation of COVID-19 control measures, there was a rapid increase in the number of daily patient visits (peaking >1,000 people/day, with a growth rate of 158.8%). The highest sampling morbidity rate was observed among individuals over 85 years old (>100 person-times/million population), followed by children (60-94 person-times/million population). Respiratory system diseases (39,295 cases) were the most diagnosed, with respiratory system infections (21,201 cases) and fever (15,132 cases) the most common. The proportion and frequency of use of essential national drugs were 34.3% and 73.1%, respectively, while those for the drugs recommended in the national COVID-19 treatment guidelines were 6.1% and 43.2%, respectively. Ibuprofen, acetaminophen, and Lianhua Qingwen had the highest frequency of drug use. The most prescribed drugs by cost were immunoglobulin, azivudine, and cefoperazone sulbactam. The water-electrolyte balance regulator drugs, respiratory system drugs, anti-infective drugs, and traditional Chinese patent drugs were the most frequently used. In contrast, immunomodulators, anti-infectives, and Chinese patent drugs had the largest monetary amounts. There was a significant difference in medication rationality between different hospital grades (P<0.001), with tertiary teaching hospitals having the highest rate. Conclusion: Strict epidemic control measures and the role of FCs played a crucial role in controlling the spread of the COVID-19 epidemic. Patients treated in FCs predominantly suffered from respiratory diseases, with older patients and children identified as high-risk populations. Physicians often choose national guidelines, essential drugs, and traditional Chinese for COVID-19 treatment. Tertiary teaching hospitals played a crucial role during the epidemic outbreak.

An In-Depth Insight into Clinical, Cellular and Molecular Factors in COVID19-Associated Cardiovascular Ailments for Identifying Novel Disease Biomarkers, Drug Targets and Clinical Management Strategies (preprint)

Background: COVID-19 was initially identified as a respiratory system disorder, but it has been discovered to interact with and influence the cardiovascular system. COVID-19-associated cardiovascular (CV) complications are common, resulting in high acute phase mortality and a large number of morbidities in the chronic phase, thus severely impacting patients' quality of life and health outcomes. Nevertheless, clinical, cellular, and molecular biological factors underlying the pathophysiology of cardiovascular complications associated with COVID-19 are poorly understood. Objective: This review investigates putative underlying clinical factors as well as cellular and molecular biological mechanisms by which COVID-19 leads to acute CV complications, including state-of-the-art genomic sequencing-based findings, assessing the long-term CV consequences of COVID-19, and aiming to shed light on developing strategies for differential diagnosis, risk prognostic stratification, prevention, and clinical management of CV sequlea in COVID-19 patients. Methods: For this purpose, a through review of literature and published data was carried out from first report of COVID-19 till October 2023 to find out a comprehensive account of clinical, cellular and molecular genetic factors underlying COVID-19-associated cardiovascular diseases. Results: We found that the relationship between COVID-19 and CV risk is complex and multifaceted. In addition to acute COVID-19 detertriuos effects, COVID-19 survivors may experience long-term CV effects. We provide a detailed account of the involvement of a large number of genomic alterations, microRNAs, and novel viral as well as host proteins in CVDs associated with COVID-19, which has helped identify some novel drug targets to treat COVID-19-related cardiovascular complications. Conclusions: The relationship between COVID-19 and CV risk is complex and multifaceted. While COVID-19 primarily affects the respiratory system, it can also significantly affect CV health. as compared to classical cardiovascular diseases, there are new clinical, cellular and molecular biological factors in CVDs related to COVID-19, that need specific diagnostic assays, prognostic stratification and treatment modules. Therefore, specail care is must taken to treat cardiovascular diseases associated with COVID-19.

The smarty4covid dataset and knowledge base: a framework enabling interpretable analysis of audio signals (preprint)

Harnessing the power of Artificial Intelligence (AI) and m-health towards detecting new bio-markers indicative of the onset and progress of respiratory abnormalities/conditions has greatly attracted the scientific and research interest especially during COVID-19 pandemic. The smarty4covid dataset contains audio signals of cough (4,676), regular breathing (4,665), deep breathing (4,695) and voice (4,291) as recorded by means of mobile devices following a crowd-sourcing approach. Other self reported information is also included (e.g. COVID-19 virus tests), thus providing a comprehensive dataset for the development of COVID-19 risk detection models. The smarty4covid dataset is released in the form of a web-ontology language (OWL) knowledge base enabling data consolidation from other relevant datasets, complex queries and reasoning. It has been utilized towards the development of models able to: (i) extract clinically informative respiratory indicators from regular breathing records, and (ii) identify cough, breath and voice segments in crowd-sourced audio recordings. A new framework utilizing the smarty4covid OWL knowledge base towards generating counterfactual explanations in opaque AI-based COVID-19 risk detection models is proposed and validated.

Transcutaneous Spinal Cord Stimulation Facilitates Respiratory Functional Performance in Patients with Post-acute COVID-19 (preprint)

Background: A growing number of studies have reported Coronavirus disease (COVID-19)-related to both respiratory and central nervous system dysfunctions. This study evaluates the neuromodulatory effects of spinal cord transcutaneous stimulation (scTS) on the respiratory functional state in healthy controls and patients with post-COVID-19 respiratory deficits as a step toward the development of a rehabilitation strategy for these patients.; Methods: In this before-after, interventional, case-controlled clinical study, ten individuals with post-acute COVID-19 respiratory deficits and eight healthy controls received a single twenty-minute-long session of modulated monophasic scTS delivered over the T5 and T10 spinal cord segments. Forced Vital Capacity (FVC), Peak Forced Inspiratory Flow (PIF), Peak Expiratory Flow (PEF), Time-To-Peak of Inspiratory Flow (tPIF), and Time-To-Peak of Expiratory Flow (tPEF) were assessed before and after the intervention; Results: In COVID-19 group, the scTS intervention led to significantly increased PIF (p= .040) and PEF (p= .049) in association with significantly decreased tPIF (p= .035) and tPEF (p= .013). In the Control Group, the exposure to scTS also resulted in significantly increased PIF (p= .010) and significantly decreased tPIF (p= .031). Unlike the results in COVID-19 group, there was significantly decreased PEF (p= .028) in association with significantly increased tPEF (p= .036). There were no changes for FVC after scTS in both groups (p= .67 and p= .503); Conclusions: In post-COVID-19 patients scTS facilitates excitation of both inspiratory and expiratory spinal neural networks leading to an immediate improvement of respiratory functional performance. This neuromodulation approach could be utilized in rehabilitation programs for patients with COVID-19 respiratory deficits.

Characterizing and Predicting Post-Acute Sequelae of SARS CoV-2 infection (PASC) in a Large Academic Medical Center in the US (preprint)

Objective: The growing number of Coronavirus Disease-2019 (COVID-19) survivors who are affected by Post-Acute Sequelae of SARS CoV-2 infection (PACS) represent a worldwide public health challenge. Yet, the novelty of this condition and the resulting limited data on underlying pathomechanisms so far hampered the advancement of effective therapies. Using electronic health records (EHR) data, we aimed to characterize PASC-associated diagnoses and to develop risk prediction models. Methods: In our cohort of 63,675 COVID-19 positive patients seen at Michigan Medicine, 1,724 (2.7 %) had a recorded PASC diagnosis. We used a case control study design comparing PASC cases with 17,205 matched controls and performed phenome-wide association studies (PheWASs) to characterize enriched phenotypes of the post-COVID-19 period and potential PASC pre-disposing phenotypes of the pre-, and acute-COVID-19 periods. We also integrated PASC-associated phenotypes into Phenotype Risk Scores (PheRSs) and evaluated their predictive performance. Results: In the post-COVID-19 period, cases were significantly enriched for known PASC symptoms (e.g., shortness of breath, malaise/fatigue, and cardiac dysrhythmias) but also many musculoskeletal, infectious, and digestive disorders. We found seven phenotypes in the pre-COVID-19 period (irritable bowel syndrome, concussion, nausea/vomiting, shortness of breath, respiratory abnormalities, allergic reaction to food, and circulatory disease) and 69 phenotypes in the acute-COVID-19 period (predominantly respiratory, circulatory, neurological, digestive, and mental health phenotypes) that were significantly associated with PASC. The derived pre-COVID-19 PheRS and acute-COVID-19 PheRS had low accuracy to differentiate cases from controls; however, they stratified risk well, e.g., a combination of the two PheRSs identified a quarter of the COVID-19 positive cohort at a 3.5-fold increased risk for PASC compared to the bottom 50% of their distributions. Conclusions: Our agnostic screen of time stamped EHR data uncovered a plethora of PASC-associated diagnoses across many categories and highlighted a complex arrangement of presenting and likely pre-disposing features -- the latter with a potential for risk stratification approaches. Yet, considerably more work will need to be done to better characterize PASC and its subtypes, especially long-term consequences, and to consider more comprehensive risk models.

Clinical profile of scrub typhus patients during COVID pandemic: A sub-Himalayan single center experience (preprint)

Introduction Scrub typhus is tropical zoonotic disease, commonly presented with multi organ dysfunction and high mortality rate in untreated patients. This study was done to identify clinical features commonly associated with scrub typhus during COVID pandemics, parameters associated with severe scrub typhus and mortality. Methods This retrospective study was done in a tertiary care hospital with a total of 52 admitted scrub typhus positive patients in October 2020 to February 2022. Diagnosis was established by scrub IgM ELISA or Rapid antigen test. The clinical and laboratory data, duration of hospital stay and outcomes were collected. Common clinical and laboratory findings were of descriptive analysis. Factors associated with mortality were analysed using Chi-square test. Results Fever was the most common presenting symptoms on admission (94.2%) followed by respiratory abnormalities (38.46%). Acute kidney injury was the most common organ failure on admission (67.3%), followed by acute liver injury (46.2%) and thrombocytopenia (32.7%). MODS was seen in 46.15%. Of the total, 30.8% were admitted in ICU. Mortality was seen in 7.7% of all patients. On Chi-square analysis, altered mental status and coagulopathy were associated with significant mortality with p value <0.05. Conclusion Scrub typhus can manifest with potentially life-threatening complications such as acute kidney injury, acute liver injury, thrombocytopenia and MODS. The overall case-fatality rate was 7.7%, and presence of altered mental status and coagulopathy were associated with higher mortality. As per literature, COVID has changed few clinical profiles of scrub typhus compared to same center experience before.

Congenital lung malformation patients experience respiratory infections after resection: A population-based cohort study.

PURPOSE: The benefit of elective resection of congenital lung malformations continues to be debated. Proponents of resection endorse a decreased risk of respiratory complications as one indication for surgery. Our study aimed to compare the prevalence of respiratory infections in cases, before and after resection of congenital lung malformations, to controls without a history of congenital lung malformation. METHODS: We performed a retrospective cohort study of children born from 1991 to 2007 who underwent congenital lung malformation resection. Patients were identified from Winnipeg´s Surgical Database of Outcomes and Management (WiSDOM), and a 10:1 date-of-birth matched control group was generated from a population-based administrative data repository. International Classification of Disease codes were used to assess pulmonary infection outcomes. Relative rates (RR) were calculated to compare the frequency of pneumonia, respiratory infections and influenza between cases and controls. RESULTS: We included 31 congenital lung malformation cases and 310 controls. Cases consisted of 14 (45.16%) congenital pulmonary airway malformations, 9 (29.03%) bronchopulmonary sequestrations and 8 (25.81%) hybrid lesions. Before resection, pneumonia was more common in cases than controls (RR 6.85; 95%CI 3.89, 11.9), while the risk of acute respiratory infections (RR 1.21; 95%CI 0.79, 1.79) and influenza (RR 0.46; 95%CI 0.01, 3.22) were similar to controls. Post-resection, the risk of pneumonia (RR 9.75; 5.06, 18.50) was still higher in cases than controls, and respiratory infections (RR 1.77; 95%CI 1.20, 2.53) and influenza (RR 3.98; 95%CI 1.48, 9.36) were more common in cases than controls. CONCLUSION: Our study demonstrated that after resection of congenital lung malformations, children experience more frequent respiratory infections compared to the general population. Resection does not eliminate the increased risk of pneumonia.

Follow-Up CT Patterns of Residual Lung Abnormalities in Severe COVID-19 Pneumonia Survivors: A Multicenter Retrospective Study.

Prior studies variably reported residual chest CT abnormalities after COVID-19. This study evaluates the CT patterns of residual abnormalities in severe COVID-19 pneumonia survivors. All consecutive COVID-19 survivors who received a CT scan 5-7 months after severe pneumonia in two Italian hospitals (Reggio Emilia and Parma) were enrolled. Individual CT findings were retrospectively collected and follow-up CT scans were categorized as: resolution, residual non-fibrotic abnormalities, or residual fibrotic abnormalities according to CT patterns classified following standard definitions and international guidelines. In 225/405 (55.6%) patients, follow-up CT scans were normal or barely normal, whereas in 152/405 (37.5%) and 18/405 (4.4%) patients, non-fibrotic and fibrotic abnormalities were respectively found, and 10/405 (2.5%) had post-ventilatory changes (cicatricial emphysema and bronchiectasis in the anterior regions of upper lobes). Among non-fibrotic changes, either barely visible (n = 110/152) or overt (n = 20/152) ground-glass opacities (GGO), resembling non-fibrotic nonspecific interstitial pneumonia (NSIP) with or without organizing pneumonia features, represented the most common findings. The most frequent fibrotic abnormalities were subpleural reticulation (15/18), traction bronchiectasis (16/18) and GGO (14/18), resembling a fibrotic NSIP pattern. When multiple timepoints were available until 12 months (n = 65), residual abnormalities extension decreased over time. NSIP, more frequently without fibrotic features, represents the most common CT appearance of post-severe COVID-19 pneumonia.

Effects of the COVID-19 Pandemic on Pediatric Nasal Fractures.

OBJECTIVES: Nasal bone fracture is a frequent entity consulted to the otolaryngologists, approximately accounting for 39% of all facial bone fractures. The most frequent mechanisms of injury consist of assault, sport-related injuries, falls, and motor vehicle accidents. In this study, we examined the effects of the COVID-19 pandemic on pediatric nasal fractures. METHODS: Children with nasal fracture who applied to Malatya Training and Research Hospital during the year before the first case and the following year were included in this study. Data of 172 patients for the pre-pandemic period and 79 patients for pandemic were available and included in the study. Demographic information, clinical features, nasal fracture etiology, nasal fracture type, type and time of intervention, and other accompanying pathologies were recorded. RESULTS: While falls was the leading cause of fracture etiology before the pandemic (64 patients [37.21%]), assault seems to be the leading cause during the pandemic period (27 children [34.18%]). In the pre-pandemic period, the intervention for patients with nasal fractures was performed on an average of 5 days, while this period was calculated as an average of 6 days during the pandemic period. When the 2 groups are compared in terms of nasal fracture intervention time, it was seen that the intervention time was statistically significantly later in the pandemic period (P < .001). According to the results of the analysis, the most cases in the pandemic period were seen in the fourth month, which indicated a-month period between 11 June and 11 July. CONCLUSIONS: In conclusion, our number of nasal fracture cases was decreased during the pandemic period compared to the 1-year period before the pandemic. We observed the most common type IIA nasal fracture. We gave outpatient treatment to most of the patients. Our most common cause of fracture was assault. We intervened in our cases in an average of 6 days and preferred closed reduction most frequently. We could not find any study on the same subject in the literature, and we aimed to contribute to the literature with this study.

SARS-CoV-2 Exposed Mesenchymal Stromal Cell from Congenital Pulmonary Airway Malformations: Transcriptomic Analysis and the Expression of Immunomodulatory Genes.

The inflammatory response plays a central role in the complications of congenital pulmonary airway malformations (CPAM) and severe coronavirus disease 2019 (COVID-19). The aim of this study was to evaluate the transcriptional changes induced by SARS-CoV-2 exposure in pediatric MSCs derived from pediatric lung (MSCs-lung) and CPAM tissues (MSCs-CPAM) in order to elucidate potential pathways involved in SARS-CoV-2 infection in a condition of exacerbated inflammatory response. MSCs-lung and MSCs-CPAM do not express angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TRMPSS2). SARS-CoV-2 appears to be unable to replicate in MSCs-CPAM and MSCs-lung. MSCs-lung and MSCs-CPAM maintained the expression of stemness markers MSCs-lung show an inflammatory response (IL6, IL1B, CXCL8, and CXCL10), and the activation of Notch3 non-canonical pathway; this route appears silent in MSCs-CPAM, and cytokine genes expression is reduced. Decreased value of p21 in MSCs-lung suggested no cell cycle block, and cells did not undergo apoptosis. MSCs-lung appears to increase genes associated with immunomodulatory function but could contribute to inflammation, while MSCs-CPAM keeps stable or reduce the immunomodulatory receptors expression, but they also reduce their cytokines expression. These data indicated that, independently from their perilesional or cystic origin, the MSCs populations already present in a patient affected with CPAM are not permissive for SARS-CoV-2 entry, and they will not spread the disease in case of infection. Moreover, these MSCs will not undergo apoptosis when they come in contact with SARS-CoV-2; on the contrary, they maintain their staminality profile.

Long-Term Outcomes of COVID-19 Survivors and an Exploratory Analysis of Factors Associated with Sequela-Free Survival of Patients Treated at Leishenshan Hospital in Wuhan, China (preprint)

Objective: To determine key factors associated with sequela-free survival of patients with COVID-19.Design: Retrospective–prospective observational study.Setting: Leishenshan Hospital in Wuhan, China.Participants: Patients with COVID-19 admitted at Leishenshan Hospital in Wuhan, China between 15 February 2020 and 1 April 2020 and discharged.Main Outcomes: MeasuresSequela-free survival is defined as having none of the long-term sequelae measured with the Activity of Daily Living (ADL) Scale, Modified Medical Research Council (mMRC) Dyspnoea Scale, New York Heart Association (NYHA) classification, Self-rating Depression Scale (SDS), Carcinologic Handicap Index (CHI) and Modified Telephone Interview for Cognitive Status (TICS-M). Multivariable logistic regression was used to examine the key factors of sequela-free survival.ResultsThe follow-up period for the 464 patients was 10 August to 30 September 2020. Of these, 424 patients completed the assessment of all scales. 30.2% (128 of 424) were categorised as sequela-free at follow-up. The most common sequelae were psychosocial problems (254 [57.7%]), respiratory function abnormality (149 [32.6%]) and cardiac function abnormality (98 [21.5%]). Risk factors associated with COVID-19 sequelae were anaemia on admission, longer duration from the onset of symptoms to admission and advanced age, whereas anti-anaemia treatment was a protective factor against sequelae. A haemoglobin level of <113 g/l for female patients or <92 g/l for male patients at admission discriminated a higher risk of any COVID-19 sequelae.Conclusions: Only one third COVID-19 survivors were sequela-free. Anaemia on admission, longer duration from the onset of symptoms to admission and advanced age were the risk factors of any long-term sequela. Anti-anaemia treatment was associated with beneficial outcomes in COVID-19 survivors.Funding: This study was funded by grants to DSS from the National Natural Science Foundation of China (Nos.81771133, 81970995) (DSD grants), Shanghai Shenkang Hospital Development Center Founding (SHDC12017X11), Renji Hospital Clinical Innovation Foundation (PYMDT-007), Shanghai municipal Education Commission-Gaofeng Clinical Medicine Support (20191903), State Key Laboratory of Neuroscience(SKLN－201803), the National Natural Science Foundation of China (No.81701358) (DH grants), the Shanghai Municipal Commission of Health and Family Planning Funding (20184Y0205) (CYC grants) and Renji Hospital founding (RJZZ18-019) (LLH grants).Declaration of Interest: None to declare. Ethical Approval: This study was approved by the Institutional Research Ethics Committee of Renji Hospital, School of Medicine, Shanghai Jiaotong University (ethics committee approval No. KY2020-34).

Methylprednisolone Treatment Versus Standard Supportive Care for Adult Covid19 Mechanically Ventilated, Acute Respiratory Distress Syndrome Patients (preprint)

A myriad of symptoms presented by severely ill mechanically ventilated Covid19 patients has added pressure on the caregivers to explore therapeutic options. Systemic steroids have been reported to therapeutically benefit patients with elevated inflammatory markers, during the severe acute respiratory syndrome, and the Middle East respiratory syndrome outbreak. Covid19 disease is characterized by inflammation of the respiratory system and acute respiratory distress syndrome. Given the lack of specific treatment for Covid19, the aim of the current study was to evaluate the therapeutic benefit of methylprednisolone as an add-on treatment for mechanically ventilated hospitalized COVID19 patients with severe covid pneumonia. Data was collected retrospectively from the electronic patient medical records, and inter-rater reliability was determined to limit selection bias. Descriptive and inferential statistical methods were used to analyze the data. The variables were cross-tabulated with the clinical outcome and the Chi-Square test used to determine association between the outcomes and other independent variables. Patients. Sixty-one percent (43/70) of the Covid19 ARDS patients received standard supportive care, and the remainder were administered. methylprednisolone (40 mg daily to 40 mg q 6 hours). A 28-day all-cause mortality rate, in the methylprednisolone group was 18% (5/27, p < 0.01) significantly lower, compared to the group receiving standard supportive care (51%, 22/43). The median number of days, for the hospital length of stay (18 days), ICU-length of stay (9.5 days), and the number of days intubated (6 days) for the methylprednisolone treated group was significantly lower (p < 0.01), when compared with the standard supportive care group. Methylprednisolone treatment also reduced the C-reactive protein levels, compared to the standard care group on day 7. Our results strengthen the evidence for the role of steroids in reducing mortality, ICU LOS, and ventilator days in mechanically ventilated Covid 19 patients with respiratory distress syndrome.

Epidemiological Characteristics of Common Human Coronaviruses in Korea, 2015-2019 (preprint)

Background: Compared to influenza virus and respiratory syncytial virus, common human coronaviruses (HCoVs) are relatively understudied due to the mild nature of HCoV infection. Given the lack of local epidemiology data on common HCoVs in Korea, we aimed to describe epidemiological characteristics of common HCoVs. Methods: Respiratory viral test results from more than 67,000 respiratory samples from the two data sources, Korea Influenza and Respiratory Viruses Surveillance System (KINRESS, N=58,253) and Seoul National University Children’s Hospital (SNUCH, N=9,589) were analyzed from January 2015 to December 2019. Viral detection was done by the multiplex RT-PCR. Demographics and clinical diagnosis were collected for previously healthy children tested positive for HCoVs in SNUCH. Results: Of the 67,842 samples tested, 1 or more respiratory viruses were detected from 35,459 (52.2%) samples and 2,854 (4.2%) samples were positive for HCoVs (OC43 2.1%, NL63 1.7%, 229E 0.4%). All 3 types were co-circulated during winter months (November to February) with some variation by type. HCoV-OC43 was most prevalent, peaking every winter. HCoV-NL63 circulated with alternate peaks occurring between January-March and November-February. Meanwhile, HCoV-229E had smaller peaks every other winter in 2015/2016 and 2017/2018. From the national surveillance data, HCoV infection was most prevalent among 0 to 1 year old children and older adults aged over 70 years. 18.2% of the HCoV-positive samples were co-detected with other respiratory viruses, with the highest co-detection rate (33.7%) in children 0 to 1 year of age and the lowest co-detection rate (3.6%) in adults ≥70 years old. Upper respiratory tract infection was the most common (60.0%) clinical diagnosis of the 135 previously healthy children. Croup accounted for 17.0% of NL63-positive childrenConclusion: This study described the epidemiological characteristics of 3 types of common HCoVs (OC43, NL63, 229E) in Korea; the highest prevalence of OC43, concurrent circulation during winter, and age difference in HCoV infection and co-detection rate with other respiratory virus. It may be informative to monitor any changes in the epidemiology of common HCoVs as the COVID-19 pandemic continues.

Long-Term Outcomes and Sequelae for 464 COVID-19 Patients Discharged from Leishenshan Hospital in Wuhan, China (preprint)

Background: While coronavirus disease 2019 (COVID-19) has emerged as a global pandemic, millions of COVID-19 patients have recovered and returned to their families and work, although the long-term outcomes remain unknown.Methods: This retrospective–prospective study analysed data for COVID-19 patients discharged from Leishenshan Hospital in Wuhan, China. Long-term outcomes were measured by Activity of Daily Living (ADL) Scale, Modified Medical Research Council (mMRC) Dyspnoea Scale, New York Heart Association (NYHA) classification, Self-rating Depression Scale (SDS), Carcinologic Handicap Index (CHI), and Modified Telephone Interview for Cognitive Status (TICS-M). Multivariable logistic regression was used to examine the risk factors of long-term outcomes.Findings: The follow-up period for the 464 patients was August 10–September 30, 2020. The most common sequelae were psychosocial problems (254 [57·7%]), respiratory function abnormality (149 [32·6%]), and cardiac function abnormality (98 [21·5%]). Rare sequelae were ADL disability (61 [13·3%]); pain (55 [12·5%]); feeding difficulties (54 [12·2%]); dysphonia (46 [10·4%]); and hyposmia (27 [6·1%]), as well as impairment in hearing (40 [9·1%]), vison (37 [8·4%]), swallowing (30 [6·8%]), and gustation (18 [4·1%]). Almost all patients (98·2%) had normal cognitive function. Risk factors associated with ADL disability were advanced age, intensive care unit (ICU) stay, and cancer, which were also associated with respiratory function abnormality. Risk factors associated with cardiac function abnormality were long hospital stay, cancer, and respiratory diseases. Advanced age, ICU stay, and nonischemic heart diseases were associated with psychosocial problems. Compared with female patients, male patients had decreased odds of declined respiratory, cardiac function, depression and anxiety, and pain.Interpretation: Nearly normal ADL, moderate cardiopulmonary function and psychosocial issues, and minor sensory abnormalities were observed in COVID-19 survivors. Advanced age, ICU stay, cancer, and female sex were adverse risk factors in long-term sequelae. These data provide a generalisable estimate of long-term outcomes for COVID-19.Trial Registration: This study was registered in the ClinicalTrial.gov database (NCT04508712).Funding: National Natural Science Foundation of China, Shanghai Shenkang Hospital Development Center, Shanghai municipal Education Commission, State Key Laboratoy of Neuroscience, and Renji Hospital.Declaration of Interests: All authors declare no competing interests.Ethics Approval Statement: This study was approved by the Institutional Research Ethics Committee of Renji Hospital, School of Medicine, Shanghai Jiaotong University (Ethical Committee approval number: KY2020-34). Oral consent was acquired from patients or from their immediate family members in cases of communication disorder or death.

Clinical Features and Laboratory Examination to Identify Severe Patients With COVID-19: A Systematic Review and Meta-analysis (preprint)

Background With the COVID-19 epidemic breakout in China, up to 25% of diagnosed cases are considered to be severe. To effectively predict the progression of COVID-19 via patients’ clinical features at an early stage, the prevalence of these clinical factors and their relationships with severe illness were assessed.Methods In this study, electronic databases (PubMed, Embase, Web of Science and Chinese database) were searched to obtain relevant studies including information on severe patients. Publication bias analysis, sensitivity analysis, prevalence, sensitivity, specificity, likelihood ratio, diagnosis odds ratio calculation, and visualization graphics were achieved through software Review Manager 5.3, STATA 15, Meta-DiSc 1.4 and R.Results Data of 3.547 patients from 24 studies was included in this study. The results revealed that patients with chronic respiratory system diseases (pooled positive likelihood 6.07, 95% CI: 3.12-11.82), chronic renal disease (4.79, 2.04-11.25), cardiovascular disease (3.45, 2.19-5.44), and symptoms of the onset of chest tightness (3.8, 1.44-10.05), shortness of breath (3.18, 2.24-4.51), and diarrhea (2.04, 1.38-3.04) exhibited increased probability of progressing to severe illness. C-reactive protein, ratio of neutrophils to lymphocytes, and erythrocyte sedimentation rate increased a lot in severe patients compared to non-severe. Yet it was found that clinical features including fever, cough, headache, and so on, as well as some comorbidities have little warning value.Conclusions The clinical features, and laboratory examination could be used to estimate the process of infection in COVID-19 patients. The findings contribute to the more efficient prediction of serious illness for patients with COVID-19 to reduce mortality.Systematic Review registrations Not applicable.

An Integrated Framework with Machine Learning and Radiomics for Accurate and Rapid Early Diagnosis of COVID-19 from Chest X-ray (preprint)

Early diagnosis of COVID-19 is considered the first key action to prevent spread of the virus. Currently, reverse transcription-polymerase chain reaction (RT-PCR) is considered as a gold standard point-of-care diagnostic tool. However, several limitations of RT-PCR have been identified, e.g., low sensitivity, cost, long delay in getting results and the need of a professional technician to collect samples. On the other hand, chest X-ray (CXR) is routinely used as a cost-effective diagnostic test for diagnosis and monitoring different respiratory abnormalities and is currently being used as a discriminating tool for COVID-19. However, visual assessment of CXR is not able to distinguish COVID-19 from other lung conditions. Several machine learning algorithms have been proposed to detect COVID-19 directly from CXR images with reasonably good accuracy on a data set that was randomly split into two subsets for training and test. Since these methods require a huge number of images for training, data augmentation with geometric transformation was applied to increase the number of images. It is highly likely that the images of the same patients are present in both the training and test sets resulting in higher accuracies in detection of COVID-19. It is, therefore, vital to assess the performance of COVID-19 detection algorithm on an independent data set with different degrees of the disease before being employed for clinical settings. On the other hand, machine learning techniques that depend on handcrafted features extraction and selection approaches can be trained with smaller data set. The features can also be analyzed separately for various lung conditions. Radiomics features are such kind of handcrafted features that represent heterogeneous appearance of the lung on CXR quantitatively and can be used to distinguish COVID-19 from other lung conditions. Based on this hypothesis, a machine learning based technique is proposed here that is trained on a set of suitable radiomics features (71 features) to detect COVID-19. It is found that Support Vector Machine (SVM) and Ensemble Bagging Model Trees (EBM) trained on these 71 radiomics features can distinguish between COVID-19 and other diseases with an overall sensitivity of 99.6% and 87.8% and specificity of 85% and 97% respectively. Though the performance is comparable for both methods, EBM is more robust across severity levels. Severity, in this case, was scored between 0 to 4 by two experienced radiologists for each lung segment of each CXR image represents the degree of severity of the disease. For the case of 0 severity, sensitivity and specificity of the EBM method are 91.7% and 100% respectively indicating that there are certain radiomics pattern that are not visibly distinguishable. Since the proposed method does not require any manual intervention (e.g., sample collection etc.), it can be integrated with any standard X-ray reporting system to be used as an efficient, cost-effective and rapid early diagnosis device. It can also be deployed in places where quick results of the COVID-19 test are required, e.g., airports, seaports, hospitals, health clinics, etc.

Development of a Coronavirus Disease 2019 Nonhuman Primate Model Using Airborne Exposure (preprint)

Airborne transmission is predicted to be a prevalent route of human exposure with SARS-CoV-2. Aside from African green monkeys, nonhuman primate models that replicate airborne transmission of SARS-CoV-2 have not been investigated. A comprehensive and comparative evaluation of COVID-19 in African green monkeys, rhesus macaques, and cynomolgus macaques following airborne exposure to SARS-CoV-2 was performed to define parameters critical to disease progression and the extent to which they correlate with human COVID-19. Respiratory abnormalities and viral shedding were noted for all animals, indicating successful infection. Cynomolgus macaques developed fever, and thrombocytopenia was measured for African green monkeys and rhesus macaques. Type II pneumocyte hyperplasia and alveolar fibrosis were more frequently observed in lung tissue from cynomolgus macaques and African green monkeys. The data indicate that, in addition to African green monkeys, macaques can be successfully infected by airborne SARS-CoV-2, providing viable macaque natural transmission models for medical countermeasure evaluation. One Sentence Summary Nonhuman primates develop COVID-19 following airborne virus exposure.

Clinical Characteristics and Prognosis of Patients with COVID-19 Combineded with or without Diabetes, Hypertension or Coronary (preprint)

Bcakground: This study was to investigate the clinical characteristics and prognosis of COVID-19 patients combined with or without major chronic diseases like diabetes, hypertension or coronary. Methods: We retrospectively analyzed 183 patients with COVID-19 diagnosed at First People's Hospital of Jiangxia District (FPHJD) in Wuhan, China attended by Affiliated Hospital of Jiangsu University supporting medical team from February 1, 2020 to March 15, 2020. Patients were divided into simple COVID-19 group(n=134), COVID-19 combined with diabetes, hypertension or coronary group(n=49). Besides, COVID-19 patients with diabetes, hypertension or coronary were further classified into severe pneumonia group(n=23) and common pneumonia group(n=26), death group(n=17) and survival group(n=32). The prognosis of COVID-19 patients was evaluated by analyzing the clinical data and the results of laboratory tests. Results: 183 patients were included in this study, of whom 166 were discharged and 16 died in hospital. 49 (26.92%) patients had a comorbidity, with hypertension being the most common [37 (20.33%) patients], followed by diabetes [25 (13.74%) patients] and coronary heart disease [4 (2.2%) patients]. Compared with simple COVID-19 group, the proportion of history of chronic respiratory system disease, age, D-dimer, procalcitonin, C-reactive protein, myoglobin, cardiac troponin I, creatine kinase MB, lactate dehydrogenase, white blood cell count, neutrophil count, neutrophil percentage, blood urea nitrogen, creatinine and mortality rate were significantly higher in COVID-19 combined with chronic diseases group, whereas lymphocyte count, lymphocyte percentage and alanine transferase were significantly lower in COVID-19 combined with chronic diseases group. Among COVID-19 patients with chronic diseases, D-dimer, procalcitonin, C-reactive protein, myoglobin, cardiac troponin I, lactate dehydrogenase, white blood cell count, neutrophil count, neutrophil percentage, blood urea nitrogen, death rate was significantly higher in severe pneumonia group than common pneumonia group. While lymphocyte count and lymphocyte percentage were significantly lower in severe pneumonia group than common pneumonia group. Besides, we found that the proportion of history of chronic respiratory system disease, D-dimer, procalcitonin, myoglobin, cardiac troponin I, creatine kinase MB, lactate dehydrogenase, neutrophil count, neutrophil percentage, blood urea nitrogen were significantly higher in death group compared with survival group, whereas lymphocyte count and lymphocyte percentage were significantly lower in survival group. In COVID-19 combined with chronic diseases group, univariate logistic regression showed that the risk for severe pneumonia were D-dimer, C-reactive protein, lactate dehydrogenase, white blood cell count, neutrophil count and neutrophil percentage. Univariate logistic regression also showed that the risk for death were D-dimer, lactate dehydrogenase, white blood cell count, neutrophil count, neutrophil percentage and blood urea nitrogen. Multivariate regression logistic showed that lactate dehydrogenase were independent risk factors for death among COVID-19 patients combined with chronic diseases. Cox regression analysis showed that compared with simple COVID-19 group, the RR(95% CI) in COVID-19 patients combined with diabetes, hypertension, and coronary were 2.187 (1.141~4.191) for death (P<0.05). Conclusion: Among COVID-19 patients combined with diabetes, hypertension or coronary, the risk factors for severe pneumonia were D-dimer, C-reactive protein, lactate dehydrogenase, white blood cell count, neutrophil count and neutrophil percentage, whereas the risk factors for death were D-dimer, lactate dehydrogenase, white blood cell count, neutrophil count, neutrophil percentage and blood urea nitrogen. Moreover, lactate dehydrogenase were independent risk factors for death. The mortality rate of COVID-19 patients combined with diabetes, hypertension or coronary was higher than that of simple COVID-19 patients.

Respiratory viral panels and pediatric airway evaluation: The role of testing for upper respiratory infections to stratify perioperative risk.

OBJECTIVES: Children admitted with stridor and respiratory distress comprise a complex patient group that requires the otolaryngologist to decide when to assess and intervene with direct laryngoscopy and bronchoscopy (DLB). Historically, the diagnosis of viral upper respiratory tract infection (URTI) can lead to postponement of surgery due to concerns of perioperative complications related to acute illness. Respiratory viral panels (RVP) are often used to confirm the presence of recent or active viral infection and can affect the differential diagnosis of upper airway obstruction. This study examined whether positive RVP testing is associated with perioperative complications and operative findings in pediatric patients undergoing inpatient DLB. METHODS: A retrospective chart review of 132 pediatric patient encounters was performed. Viral testing results, DLB indication, DLB findings, and perioperative complications were compared. RESULTS: Sixty encounters (45.5%) involved a positive RVP, and 72 (54.5%) involved a negative RVP. Those with positive RVP were less likely to have a preoperative structural airway diagnosis (P =.0250) and more likely to have a history of recurrent upper respiratory infections (P =.0464). The most common reason for DLB was the need to assess the airway due to concern for structural pathology. Anatomic abnormalities were seen in a majority of encounters (77.3%) Laryngospasm occurred in 1 (1.7%) RVP positive and 1 (1.4%) RVP negative encounter, and 2 (2.8%) RVP negative encounters required reintubation. No other major complications were observed. No association was noted between RVP results and incidence of major or minor complication. CONCLUSIONS: Major perioperative complications after surgical intervention with DLB for the management of complex, inpatient children with stridor and respiratory distress are rare. RVP positivity, specific pathogens identified on RVP, and presence of URI symptoms were not associated with perioperative complications.

Automated Systems for Detection of COVID-19 Using Chest X-ray Images and Lightweight Convolutional Neural Networks (preprint)

Since December 2019, the appearance of an outbreak of a novel coronavirus disease namely COVID-19 and which is previously known as 2019-nCoV. COVID-19 is a type of coronavirus that leads to the general destruction of respiratory systems and a severe respiratory symptom which are associated with highly Intensive Care Unit (ICU) admissions and death. Like any disease, the early diagnosis of coronavirus leads to limit its wide-spreading and increases the recovery rates of patients. The gold standard of COVID-19 detection is the real-time reverse transcription-polymerase chain reaction (RT-PCR) which has been used by the clinician to discover the presence or absence of this type of virus. The clinicians report that this technique has a low positive rate in the early stage of this disease. Based on this, the clinicians were forced to use another way to help in the early diagnosis of COVID-2019. So, the clinician's attention moved towards the medical imaging modalities especially the computed Tomography (CT) and X-ray chest images. Both modalities show that there is a change in the lungs in the case of COVID-19 that is different from any other type of pneumonic disease. Therefore, this research targeted toward employing different Artificial Intelligence (AI) techniques to propose a system for early detection of COVID-19 using chest X-ray images. These images are classified using different AI algorithms and a combination of them, then their performance was evaluated to recognize the best of them. These algorithms include a convolutional neural network (CNN), Softmax, support vector machine (SVM), Random Forest, and K nearest neighbor (KNN). Here CNN is into two scenarios, the first one to classify the X-ray images using a softmax classifier, and the second one to extract automated features from the images and pass these features to other classifiers (SVM, RFF, and KNN). According to the results, the performance of all classifiers is good and most of them record accuracy, sensitivity, specificity, and precision of more than 98%.