Showing papers in "Annals of Translational Medicine in 2020"

Global low back pain prevalence and years lived with disability from 1990 to 2017: estimates from the Global Burden of Disease Study 2017.

Abstract: Background Low back pain (LBP) is a common musculoskeletal problem globally. Updating the prevalence and burden of LBP is important for researchers and policy makers. This paper presents, compares and contextualizes the global prevalence and years lived with disability (YLDs) of LBP by age, sex and region, from 1990 to 2017. Methods Data were extracted from the GBD (the Global Burden of Disease, Injuries, and Risk Factors Study) 2017 Study. Age, sex and region-specific analyses were conducted to estimate the global prevalence and YLDs of LBP, with the uncertainty intervals (UIs). Results The age-standardized point prevalence of LBP was 8.20% (95% UI: 7.31-9.10%) in 1990 and decreased slightly to 7.50% (95% UI: 6.75-8.27%) in 2017. The prevalent numbers of people with LBP at any one point in time in 1990 was 377.5 million, and this increased to 577.0 million in 2017. Age-standardized prevalence of LBP was higher in females than males. LBP prevalence increased with age, and peaked around the ages of 80 to 89 years, and then decreased slightly. Global YLDs were 42.5 million (95% UI: 30.2 million-57.2 million) in 1990 and increased by 52.7% to 64.9 million (95% UI: 46.5 million-87.4 million) in 2017. YLDs were also higher in females than males and increased initially with age; they peaked at 35-39 years of age in 1990, before decreasing, whereas in 2017, they peaked at 45-49 years of age, before decreasing. Western Europe had the highest number of LBP YLDs. Conclusions Globally, LBP is the leading global cause of YLDs. Greater attention is urgently needed to mitigate this increasing burden and the impact it is having on health and social systems.

Chinese expert consensus on the perinatal and neonatal management for the prevention and control of the 2019 novel coronavirus infection (First edition)

Abstract: Since December 2019, there has been an outbreak of novel coronavirus (2019-nCoV) infection in China. Two cases of neonates with positive 2019-nCoV tests have been reported. Due to the immature immune system and the possibility of vertical transmission from mother to infant, neonates have become a high-risk group susceptible to 2019-nCoV, which emphasize a close cooperation from both perinatal and neonatal pediatrics. In neonatal intensive care unit (NICU), to prevent and control infection, there should be practical measures to ensure the optimal management of children potentially to be infected. According to the latest 2019-nCoV national management plan and the actual situation, the Chinese Neonatal 2019-nCoV expert working Group has put forward measures on the prevention and control of neonatal 2019-nCoV infection.

A bibliometric analysis using VOSviewer of publications on COVID-19

Abstract: Background As a global pandemic, COVID-19 has aroused great concern in the last few months and a growing number of related researches have been published. Therefore, a bibliometric analysis of these publications may provide a direction of hot topics and future research trends.

A review of the application of deep learning in medical image classification and segmentation

Abstract: Big medical data mainly include electronic health record data, medical image data, gene information data, etc. Among them, medical image data account for the vast majority of medical data at this stage. How to apply big medical data to clinical practice? This is an issue of great concern to medical and computer researchers, and intelligent imaging and deep learning provide a good answer. This review introduces the application of intelligent imaging and deep learning in the field of big data analysis and early diagnosis of diseases, combining the latest research progress of big data analysis of medical images and the work of our team in the field of big data analysis of medical imagec, especially the classification and segmentation of medical images.

Nosocomial infections among patients with COVID-19, SARS and MERS: A rapid review and meta-analysis

Abstract: Background COVID-19, a disease caused by SARS-CoV-2 coronavirus, has now spread to most countries and regions of the world. As patients potentially infected by SARS-CoV-2 need to visit hospitals, the incidence of nosocomial infection can be expected to be high. Therefore, a comprehensive and objective understanding of nosocomial infection is needed to guide the prevention and control of the epidemic. Methods We searched major international and Chinese databases: Medicine, Web of Science, Embase, Cochrane, CBM (China Biology Medicine disc), CNKI (China National Knowledge Infrastructure) and Wanfang database for case series or case reports on nosocomial infections of COVID-19, SARS (severe acute respiratory syndromes) and MERS (Middle East respiratory syndrome) from their inception to March 31st, 2020. We conducted a meta-analysis of the proportion of nosocomial infection patients in the diagnosed patients, occupational distribution of nosocomial infection medical staff. Results We included 40 studies. Among the confirmed patients, the proportions of nosocomial infections with early outbreaks of COVID-19, SARS, and MERS were 44.0%, 36.0%, and 56.0%, respectively. Of the confirmed patients, the medical staff and other hospital-acquired infections accounted for 33.0% and 2.0% of COVID-19 cases, 37.0% and 24.0% of SARS cases, and 19.0% and 36.0% of MERS cases, respectively. Nurses and doctors were the most affected among the infected medical staff. The mean numbers of secondary cases caused by one index patient were 29.3 and 6.3 for SARS and MERS, respectively. Conclusions The proportion of nosocomial infection in patients with COVID-19 was 44% in the early outbreak. Patients attending hospitals should take personal protection. Medical staff should be awareness of the disease to protect themselves and the patients.

Coronavirus disease 2019 (COVID-19): the portrait of a perfect storm

Abstract: The "novel" coronavirus disease 2019 (abbreviated "COVID-19") is the third coronavirus outbreak emerging during the past two decades. This infectious disease, sustained by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has been recently declared a global pandemic by the World Health Organization. Despite the concerning epidemiological burden, many people, including some policymakers, are underestimating this pandemic and are remaining enigmatically inactive against a human pathology which, for a combination of reasons, can be reasonably defined as a perfect storm (i.e., the "wrong virus" at the "wrong time"). These many paradigmatic aspects include SARS-CoV-2 structure and peculiar biology of infection, high risk of inter-human transmission, long incubation time combined with early and sustained viral load, existence of asymptomatic or mildly-symptomatic carriers, viral shedding for days after symptom relief, unfavorable progression towards respiratory distress and death in up to 5-10% of patients thus causing dramatic healthcare challenges, as well as environmental contamination. Last but not least, the combination of the current case fatality rate with the extraordinary number of people that could be potentially infected by SARS-CoV-2 would permit to estimate that the worldwide deaths for COVID-19 may even approximate those recorded during World War II if appropriate restrictive measures for preventing human-to-human transmission are not readily undertaken. Everybody should be inexcusably aware that this is not a drill, and that the consequences of inadequate action will be tragedy.

Early estimation of the case fatality rate of COVID-19 in mainland China: A data-driven analysis

Abstract: Background An ongoing outbreak of pneumonia caused by a novel coronavirus [severe acute respiratory syndrome coronavirus (SARS-CoV)-2], named COVID-19, hit a major city of China, Wuhan in December 2019 and subsequently spread to other provinces/regions of China and overseas. Several studies have been done to estimate the basic reproduction number in the early phase of this outbreak, yet there are no reliable estimates of case fatality rate (CFR) for COVID-19 to date. Methods In this study, we used a purely data-driven statistical method to estimate the CFR in the early phase of the COVID-19 outbreak. Daily numbers of laboratory-confirmed COVID-19 cases and deaths were collected from January 10 to February 3, 2020 and divided into three clusters: Wuhan city, other cities of Hubei province, and other provinces of mainland China. Simple linear regression model was applied to estimate the CFR from each cluster. Results We estimated that CFR during the first weeks of the epidemic ranges from 0.15% (95% CI: 0.12-0.18%) in mainland China excluding Hubei through 1.41% (95% CI: 1.38-1.45%) in Hubei province excluding the city of Wuhan to 5.25% (95% CI: 4.98-5.51%) in Wuhan. Conclusions Our early estimates suggest that the CFR of COVID-19 is lower than the previous coronavirus epidemics caused by SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV).

Machine learning-based CT radiomics method for predicting hospital stay in patients with pneumonia associated with SARS-CoV-2 infection: a multicenter study

Abstract: Background The coronavirus disease 2019 (COVID-19) has become a global challenge since the December 2019. The hospital stay is one of the prognostic indicators, and its predicting model based on CT radiomics features is important for assessing the patients' clinical outcome. The study aimed to develop and test machine learning-based CT radiomics models for predicting hospital stay in patients with COVID-19 pneumonia. Methods This retrospective, multicenter study enrolled patients with laboratory-confirmed SARS-CoV-2 infection and their initial CT images from 5 designated hospitals in Ankang, Lishui, Lanzhou, Linxia, and Zhenjiang between January 23, 2020 and February 8, 2020. Patients were classified into short-term (≤10 days) and long-term hospital stay (>10 days). CT radiomics models based on logistic regression (LR) and random forest (RF) were developed on features from pneumonia lesions in first four centers. The predictive performance was evaluated in fifth center (test dataset) on lung lobe- and patients-level. Results A total of 52 patients were enrolled from designated hospitals. As of February 20, 21 patients remained in hospital or with non-findings in CT were excluded. Therefore, 31 patients with 72 lesion segments were included in analysis. The CT radiomics models based on 6 second-order features were effective in discriminating short- and long-term hospital stay in patients with COVID-19 pneumonia, with areas under the curves of 0.97 (95% CI, 0.83-1.0) and 0.92 (95% CI, 0.67-1.0) by LR and RF, respectively, in test. The LR and RF model showed a sensitivity and specificity of 1.0 and 0.89, 0.75 and 1.0 in test respectively. As of February 28, a prospective cohort of six discharged patients were all correctly recognized as long-term stay using RF and LR models. Conclusions The machine learning-based CT radiomics features and models showed feasibility and accuracy for predicting hospital stay in patients with COVID-19 pneumonia.

Preliminary study to identify severe from moderate cases of COVID-19 using combined hematology parameters

Abstract: Background: The third fatal coronavirus is the novel coronavirus (SARS-CoV-2) that causes novel coronavirus pneumonia (COVID-19) which first broke out in December 2019 Patients will develop rapidly if there is no any intervention, so the risk identification of severe patients is critical The aim of this study was to investigate the characteristics and rules of hematology changes in patients with COVID-19, and to explore the possibility differentiating moderate and severe patients using conventional hematology parameters or combined parameters Methods: The clinical data of 45 moderate and severe type patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in Jingzhou Central Hospital from January 23 to February 13, 2020 were collected The epidemiological indexes, clinical symptoms, and laboratory test results of the patients were retrospectively analyzed Those parameters with significant differences between moderate and severe cases were analyzed, and the combination parameters with the best diagnostic performance were selected using the linear discriminant analysis (LDA) method Results: Of the 45 patients with the novel 2019 corona virus (COVID-19) (35 moderate and 10 severe cases), 23 were male and 22 were female, with ages ranging from 16 to 62 years The most common clinical symptoms were fever (89%) and dry cough (60%) As the disease progressed, white blood cell count (WBC), neutrophil count, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), red blood cell distribution width-coefficient of variation (RDW-CV), and red cell volume distribution width-standard deviation (RDW-SD) parameters in the severe group were significantly higher than those in the moderate group (P<0 05);meanwhile, lymphocyte count (Lym#), eosinophil count (Eos#), high fluorescent cell percentage (HFC%), red blood cell count (RBC), hemoglobin (HGB), and hematocrit (HCT) parameters in the severe group were significantly lower than those in the moderate group (P<0 05) For NLR parameter, it's area under the curve (AUC), cutoff, sensitivity and specificity were 0 890, 13 39, 83 3% and 82 4% respectively;meanwhile, for PLR parameter, it's AUC, cutoff, sensitivity and specificity were 0 842, 267 03, 83 3% and 74 0% respectively The combined parameters of NLR and RDW-SD had the best diagnostic efficiency (AUC =0 938), and when the cutoff value was 1 046, the sensitivity and the specificity were 90 0% and 84 7% respectively, followed by the combined parameter NLR&RDW-CV (AUC =0 923) When the cut-off value was 0 62, the sensitivity and the specificity for distinguishing severe type from moderate cases of COVID-19 were 90 0% and 82 4% respectively Conclusions: The combined NLR and RDW-SD parameter is the best hematology index It may help clinicians to predict the severity of COVID-19 patients and can be used as a useful indicator to help prevent and control the epidemic

Which lessons shall we learn from the 2019 novel coronavirus outbreak

Abstract: Two decades after the severe acute respiratory syndrome (SARS), and one decade after the middle east respiratory syndrome (MERS), a new outbreak of respiratory illness sustained by a member of the coronavirus (CoV) family has been first identified in Wuhan (Hubei Province, China), and is rapidly spreading around the world (1,2). The pathogen, temporarily defined 2019 novel coronavirus (2019-nCoV), is a positive-sense RNA, 29903-bp betacoronavirus, first isolated in the Wuhan seafood market on January 7, 2020 (3), and which is highly homologous to the previous SARS CoV (4). Unlike the other two previous CoV zoonotic diseases caused by SARSCoV and MERS-CoV, transferred from bats to humans through civets and dromedary camels, respectively, it has been recently suggested that snakes may have been the intermediate reservoirs of 2019-nCoV between bats and humans (5). The possibility of human-to-human transmission of 2019-nCoV has been documented (6), whilst it is still unclear whether the pathogen can be transmitted during the incubation period, which is apparently comprised between 2–14 days (7). According to the last report of the World Health Organization (WHO), published on February 2, 2020, the outbreak is rapidly spreading, within and outside China (Figure 1) (8). Overall, 14,557 cases of 2019-nCoV infection have been diagnosed in 23 worldwide countries (14,411 cases in China, but also 20 in Japan, 19 in Thailand, 12 in Australia, 8 in the US, 8 in Germany, 6 in France and 2 in Italy, among others), 2110 of which (~15%) have been classified as severe in China. A total number of 305 deaths have been recorded so far (304 in China and 1 abroad), thus accounting for a ~2.1% mortality rate (8). Despite the death rate may still be underestimated due to uncertainty on the true number of infections and the ongoing clinical progression of diseased cases, this value appears substantially lower than those earlier reported for both SARS (~9.6%) and MERS (~34.4%) (9). This evidence is in keeping with a preliminary hypothesis that the severity of this new syndrome may be lower than that of SARS and MERS, thus amplifying the likelihood of human-to-human transmission (e.g., infected people are more likely to bear mild symptoms, and hence to circulate and spread the virus) (7). Although more data would need to be collected for accurately portend the recent 2019-nCoV outbreak, the clinical features have been recently described in 41 Chinese patients hospitalized in Wuhan, where the infection has begun (10). Briefly, the mean age of patients was 49 (interquartile range, 41-58) years, male sex was prevalent (73%), and nearly half of patients had an underlying pathology (20% diabetes, 15% hypertension or cardiovascular disease). The most frequent symptoms included fever (98%), cough (76%), dyspnoea (55%), myalgia (44%), whilst headache (8%) and diarrhoea (3%) were less common. Notably, all patients developed pneumonia, confirmed by the presence of abnormal chest CT findings. The most frequent complications were acute respiratory distress syndrome (29%), and acute cardiac injury (12%). Thirty two percent of these patients ought to be admitted to the intensive care unit, whilst 15% of them died. According to the last WHO report, the clinical picture of patients diagnosed outside China is substantially similar, with a mean age of infection onset of 45 (range, 2 to 74) years, and a higher prevalence of men vs. women (71% vs. 29%) (8). The median period between first onset of the 48

Clinical characteristics of recovered COVID-19 patients with re-detectable positive RNA test

Abstract: Background The characteristics, significance and potential cause of positive SARS-CoV-2 diagnoses in recovered coronavirus disease 2019 (COVID-19) patients post discharge (re-detectable positive, RP) remained elusive. Methods A total of 262 COVID-19 patients discharged from January 23 to February 25, 2020 were enrolled into this study. RP and non-RP (NRP) patients were grouped according to disease severity, and the characterization at re-admission was analyzed. SARS-CoV-2 RNA and plasma antibody levels were measured, and all patients were followed up for at least 14 days, with a cutoff date of March 10, 2020. Results A total of 14.5% of RP patients were detected. These patients were characterized as young and displayed mild and moderate conditions compared to NRP patients while no severe patients were RP. RP patients displayed fewer symptoms but similar plasma antibody levels during their hospitalization compared to NRP patients. Upon hospital readmission, these patients showed no obvious symptoms or disease progression. All 21 close contacts of RP patients were tested negative for viral RNA and showed no suspicious symptoms. Eighteen out of 24 of RNA-negative samples detected by the commercial kit were tested positive for viral RNA using a hyper-sensitive method, suggesting that these patients were potential carriers of the virus after recovery from COVID-19. Conclusions Our results indicated that young patients, with a mild diagnosis of COVID-19 are more likely to display RP status after discharge. These patients show no obvious symptoms or disease progression upon re-admission. More sensitive RNA detection methods are required to monitor these patients. Our findings provide information and evidence for the management of convalescent COVID-19 patients.

Incidence of patients with bone metastases at diagnosis of solid tumors in adults: a large population-based study.

Abstract: Background Bones are one of the most common metastatic sites for solid malignancies. Bone metastases can significantly increase mortality and decrease the quality of life of cancer patients. In the United States, around 350,000 people die each year from bone metastases. This study aimed to analyze and update the incidence and prognosis of bone metastases with solid tumors at the time of cancer diagnosis and its incidence rate for each solid cancer. Methods We used the Surveillance, Epidemiology, and End Results (SEER) database to find patients diagnosed with solid cancers originating from outside the bones and joints between 2010 and 2016. Data were stratified by age, sex, and race. Patients with a tumor in situ or with an unknown bone metastases stage were excluded. We then selected most of the sites where cancer often occurred, leaving 2,207,796 patients for the final incidence analysis. For the survival analysis, patients were excluded if they were diagnosed at their autopsy or on their death certificate, or had unknown follow-ups. The incidence of bone metastases and overall survival was compared between patients with different primary tumor sites. Results We identified 2,470,634 patients, including 426,594 patients with metastatic disease and 113,317 patients with bone metastases, for incidence analysis. The incidence of bone metastases among the metastatic subset was 88.74% in prostate cancer, 53.71% in breast cancer, and 38.65% in renal cancer. In descending order of incidence, there were patients with other cancers in the genitourinary system (except for renal, bladder, prostate, and testicular cancer) (37.91%), adenocarcinoma of the lung (ADC) (36.86%), other gynecologic cancers (36.02%), small-cell lung cancer (SCLC) (34.56%), non-small cell lung cancer not otherwise specified and others [NSCLC (NOS/others)] (33.55%), and bladder (31.08%) cancers. The rate of bone metastases is 23.19% in SCLC, 22.50% in NSCLC (NOS/others), 20.28% in ADC, 8.44% in squamous cell carcinoma of the lung (SCC), and 4.11% in bronchioloalveolar carcinoma [NSCLC (BAC)]. As for the digestive system, the overall bone metastases rate was 7.99% in the esophagus, 4.47% in the gastric cancer, 4.42% in the hepatobiliary cancer, 3.80% in the pancreas, 3.26% in other digestive organs, 1.24% in the colorectum, and 1.00% in the anus. Overall, the incidence rate of bone metastases among the entire cohort in breast and prostate cancer was 3.73% and 5.69%, respectively. Conclusions The results of this study provide population-based estimates for the incidence rates of patients with bone metastases at initial diagnosis of their solid tumor. The findings can help clinicians to early detect bone metastases by bone screening to anticipate the occurrence of symptoms and favorably improve the prognosis.

COVID-19: unravelling the clinical progression of nature's virtually perfect biological weapon

Abstract: Coronavirus disease 2019 (COVID-19) pandemic has shocked the world and caused morbidity and mortality on an unprecedented level in the era of modern medicine. Evidence generated to-date on the virulence and pathogenicity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) suggests that COVID-19 may be considered a perfect storm, caused by a nature's virtually perfect biological weapon. This conclusion is supported by an updated analysis of pathogenesis and clinical progression of this infectious disease. It is now readily apparent that COVID-19 is not a clear-cut disorder, but is instead a gradually evolving pathology, characterized by a series of stages sustained by different molecular and biological mechanisms. The disease can hence be divided in at least five different phases (incubation, respiratory, pro-inflammatory, pro-thrombotic, and death or remission). Whilst the virus triggers direct cytopathic injury during the initial stage of illness, in the following evolving phases, it is the host itself that undergoes an almost suicidal reaction, sustained, amplified and maintained by the immune, complement and hemostatic systems. Another peculiar property making SARS-CoV-2 a devious and vicious pathogen is the biophysical structure of its receptor biding domain, which needs to be primed by human proteases, thus being less efficiently targetable by the host immune system. The unique pathophysiology of COVID-19 requires the customization of therapy by individual patient characteristics and according to the phase-specific, evolving derangement of the multiple biological pathways.

Comprehensive update on current outbreak of novel coronavirus infection (2019-nCoV)

Abstract: Recently, a new coronavirus disease (COVID-19) has emerged as a respiratory infection with significant concern for global public health hazards. With an initial suspicion of the animal to the human transmission for earlier cases, now the paradigm has shifted towards human to human transmission via droplets, contacts and/or through fomites. with each passing day, more and more confirmed cases are being reported worldwide which has alarmed the global authorities including World Health Organization (WHO), Centers for Disease Control and Prevention (CDC) and the National Health Commission of the People’s Republic of China to take immediate action in order to reduce the transmission and subsequent mortalities associated with COVID-19 to as minimum as possible. Unfortunately, like the previous Coronavirus outbreaks, there is no definite antiviral therapy for the treatment of confirmed cases and hence preventing ourselves from contracting 2019-nCoV is the best way to prevent it from becoming pandemic. Herein, we aim to discuss the latest updates on the origin, genomic characteristics, diagnosis, treatment options and current efforts being made by international health organizations with regards to the 2019-nCoV outbreak.

Deep learning for detecting corona virus disease 2019 (COVID-19) on high-resolution computed tomography: A pilot study

Abstract: Background: To evaluate the diagnostic efficacy of Densely Connected Convolutional Networks (DenseNet) for detection of COVID-19 features on high resolution computed tomography (HRCT). Methods: The Ethic Committee of our institution approved the protocol of this study and waived the requirement for patient informed consent. Two hundreds and ninety-five patients were enrolled in this study (healthy person: 149; COVID-19 patients: 146), which were divided into three separate non-overlapping cohorts (training set, n=135, healthy person, n=69, patients, n=66; validation set, n=20, healthy person, n=10, patients, n=10; test set, n=140, healthy person, n=70, patients, n=70). The DenseNet was trained and tested to classify the images as having manifestation of COVID-19 or as healthy. A radiologist also blindly evaluated all the test images and rechecked the misdiagnosed cases by DenseNet. Receiver operating characteristic curves (ROC) and areas under the curve (AUCs) were used to assess the model performance. The sensitivity, specificity and accuracy of DenseNet model and radiologist were also calculated. Results: The DenseNet algorithm model yielded an AUC of 0.99 (95% CI: 0.958-1.0) in the validation set and 0.98 (95% CI: 0.972-0.995) in the test set. The threshold value was selected as 0.8, while for validation and test sets, the accuracies were 95% and 92%, the sensitivities were 100% and 97%, the specificities were 90% and 87%, and the F1 values were 95% and 93%, respectively. The sensitivity of radiologist was 94%, the specificity was 96%, while the accuracy was 95%. Conclusions: Deep learning (DL) with DenseNet can accurately classify COVID-19 on HRCT with an AUC of 0.98, which can reduce the miss diagnosis rate (combined with radiologists' evaluation) and radiologists' workload.

Clinical features of severe patients infected with 2019 novel coronavirus: a systematic review and meta-analysis

Abstract: Background: 2019 novel coronavirus disease (COVID-19) has posed significant threats to public health To identify and treat the severe and critical patients with COVID-19 is the key clinical problem to be solved The present study aimed to evaluate the clinical characteristics of severe and non-severe patients with COVID-19 Methods: We searched independently studies and retrieved the data that involved the clinical characteristics of severe and non-severe patients with COVID-19 through database searching Two authors independently retrieved the data from the individual studies, assessed the study quality with Newcastle-Ottawa Scale and analyzed publication bias by Begg's test We calculated the odds ratio (OR) of groups using fixed or random-effect models Results: Five studies with 5,328 patients confirmed with COVID-19 met the inclusion criteria Severe patents were older and more common in dyspnea, vomiting or diarrhea, creatinine >104 micromol/L, procalcitonin >/=0 05 ng/mL, lymphocyte count <1 5x10(9)/L and bilateral involvement of chest CT Severe patents had higher risk on complications including acute cardiac injury (OR 13 48;95% CI, 3 60 to 50 47, P<0 001) or acute kidney injury (AKI) (OR 11 55;95% CI, 3 44 to 38 77, P<0 001), acute respiratory distress syndrome (ARDS) (OR 26 12;95% CI, 11 14 to 61 25, P<0 001), shock (OR 53 17;95% CI, 12 54 to 225 4, P<0 001) and in-hospital death (OR 45 24;95% CI, 19 43 to 105 35, P<0 001) Severe group required more main interventions such as received antiviral therapy (OR 1 69;95% CI, 1 23 to 2 32, P=0 001), corticosteroids (OR 5 07;95% CI, 3 69 to 6 98, P<0 001), CRRT (OR 37 95;95% CI, 7 26 to 198 41, P<0 001) and invasive mechanical ventilation (OR 129 35;95% CI, 25 83 to 647 68, P<0 001) Conclusions: Severe patients with COVID-19 had more risk of clinical characteristics and multiple system organ complications Even received more main interventions, severe patients had higher risk of mortality

Molecular subtypes and precision treatment of triple-negative breast cancer

Abstract: Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype. Despite the progress made in precision treatment of cancer patients, targeted treatment is still at its early stage in TNBC, and chemotherapy remains the standard treatment. With the advances in next generation sequencing technology, genomic and transcriptomic analyses have provided deeper insight into the inter-tumoral heterogeneity of TNBC. Much effort has been made to classify TNBCs into different molecular subtypes according to genetic aberrations and expression signatures and to uncover novel treatment targets. In this review, we summarized the current knowledge regarding the molecular classification of TNBC and explore the future paradigm for using molecular classification to guide the development of precision treatment and clinical practice.

The effect of RAS blockers on the clinical characteristics of COVID-19 patients with hypertension

Abstract: Background Coronavirus disease 2019 (COVID-19), caused by a novel coronavirus (designated as SARS-CoV-2) has become a pandemic worldwide. Based on the current reports, hypertension may be associated with increased risk of sever condition in hospitalized COVID-19 patients. Angiotensin-converting enzyme 2 (ACE2) was recently identified to functional receptor of SARS-CoV-2. Previous experimental data revealed ACE2 level was increased following treatment with ACE inhibitors (ACEIs) and angiotensin receptor blockers (ARBs). Currently doctors concern whether these commonly used renin-angiotensin system (RAS) blockers-ACEIs/ARBs may increase the severity of COVID-19. Methods We extracted data regarding 50 hospitalized hypertension patients with laboratory confirmed COVID-19 in the Renmin Hospital of Wuhan University from Feb 7 to Mar 03, 2020. These patients were grouped into RAS blockers group (Group A, n=20) and non-RAS blockers group (Group B, n=30) according to the basic blood pressure medications. All patients continued to use pre-admission antihypertensive drugs. Clinical severity (symptoms, laboratory and chest CT findings, etc.), clinical course, and short time outcome were analyzed after hospital admission. Results Ten (50%) and seventeen (56.7%) of the Group A and Group B participants were males (P=0.643), and the average age was 52.65±13.12 and 67.77±12.84 years (P=0.000), respectively. The blood pressure of both groups was under effective control. There was no significant difference in clinical severity, clinical course and in-hospital mortality between Group A and Group B. Serum cardiac troponin I (cTnI) (P=0.03), and N-terminal (NT)-pro hormone BNP (NT-proBNP) (P=0.04) showed significant lower level in Group A than in Group B. But the patients with more than 0.04ng/mL or elevated NT-proBNP level had no statistical significance between the two groups. In patients over 65 years or under 65 years, cTnI or NT-proBNP level showed no difference between the two groups. Conclusions We observed there was no obvious difference in clinical characteristics between RAS blockers and non-RAS blockers groups. These data suggest ACEIs/ARBs may have few effects on increasing the clinical severe conditions of COVID-19.

Guidelines for the diagnosis and treatment of osteoarthritis in China (2019 edition)

Abstract: Osteoarthritis (OA) is a degenerative disease of middle-aged and elderly people, contributed a higher burden of disease in China and the world. In 2017, under the support of the Rheumatology and Immunology Expert Committee of the Cross-Strait Medical and Health Exchange Association. The objective was to develop an evidence-based diagnosis and treatment guideline for OA in China based on emerging new evidence. The guideline was registered at International Practice Guidelines Registry Platform (IPGRP-2018CN028). The grading of recommendations assessment, development and evaluation (GRADE) approach was used to rate the quality of evidence and the strength of recommendations, and the RIGHT (Reporting Items for Practice Guidelines in Healthcare) checklist was followed to report the guideline. The guideline provides recommendations for the OA diagnosis, disease risks monitoring and evaluate, treatment purpose and physical, medical and surgical interventions. This guideline is intended to serve as a tool for Chinese clinicians for the best decisions-making on diagnosis and treatment of OA.

A profiling analysis on the receptor ACE2 expression reveals the potential risk of different type of cancers vulnerable to SARS-CoV-2 infection

Abstract: Background The new coronavirus pneumonia (NCP) is now causing a severe public health emergency. The novel coronavirus 2019 (2019-nCoV) infected individuals by binding human angiotensin converting enzyme II (ACE2) receptor. ACE2 is widely expressed in multiple organs including respiratory, cardiovascular, digestive and urinary systems in healthy individuals. These tissues with high expression level of ACE2 seemed to be more vulnerable to SARS-CoV-2 infection. Recently, it has been reported that patients with tumors were likely to be more susceptible to SARS-CoV-2 infection and indicated poor prognosis. Methods The tissue atlas database and the blood atlas were used to analyze the distribution of ACE2 in human tissues or organs of cancers and normal samples. Starbase dataset was applied to predict the prognosis of cancers according to expression level of ACE2. Results In this study, we demonstrated a landscape profiling analysis on expression level of ACE2 in pan-cancers and showed the risky of different type of cancers to SARS-CoV-2 according to the expression level of ACE2. In addition, we found that ACE2 was both differential expression and related to the prognosis only in liver hepatocellular carcinoma (LIHC). Relative high expression of ACE2 indicated a favorable prognosis in LIHC, but they might be more susceptible to SARS-CoV-2. Conclusions We indeed emphasized that LIHC patients with high expression level of ACE2 should be more cautious of the virus infection. Our study might provide a potential clue for preventing infection of SARS-CoV-2 in cancers.

Imitation dynamics in the mitigation of the novel coronavirus disease (COVID-19) outbreak in Wuhan, China from 2019 to 2020

Abstract: Background The coronavirus disease 2019 (COVID-19) was first identified in Wuhan, China on December 2019 in patients presenting with atypical pneumonia. Although 'city-lockdown' policy reduced the spatial spreading of the COVID-19, the city-level outbreaks within each city remain a major concern to be addressed. The local or regional level disease control mainly depends on individuals self-administered infection prevention actions. The contradiction between choice of taking infection prevention actions or not makes the elimination difficult under a voluntary acting scheme, and represents a clash between the optimal choice of action for the individual interest and group interests. Methods We develop a compartmental epidemic model based on the classic susceptible-exposed-infectious-recovered model and use this to fit the data. Behavioral imitation through a game theoretical decision-making process is incorporated to study and project the dynamics of the COVID-19 outbreak in Wuhan, China. By varying the key model parameters, we explore the probable course of the outbreak in terms of size and timing under several public interventions in improving public awareness and sensitivity to the infection risk as well as their potential impact. Results We estimate the basic reproduction number, R 0, to be 2.5 (95% CI: 2.4-2.7). Under the current most realistic setting, we estimate the peak size at 0.28 (95% CI: 0.24-0.32) infections per 1,000 population. In Wuhan, the final size of the outbreak is likely to infect 1.35% (95% CI: 1.00-2.12%) of the population. The outbreak will be most likely to peak in the first half of February and drop to daily incidences lower than 10 in June 2020. Increasing sensitivity to take infection prevention actions and the effectiveness of infection prevention measures are likely to mitigate the COVID-19 outbreak in Wuhan. Conclusions Through an imitating social learning process, individual-level behavioral change on taking infection prevention actions have the potentials to significantly reduce the COVID-19 outbreak in terms of size and timing at city-level. Timely and substantially resources and supports for improving the willingness-to-act and conducts of self-administered infection prevention actions are recommended to reduce to the COVID-19 associated risks.

COVID-19 will stimulate a new coronavirus research breakthrough: A 20-year bibliometric analysis

Abstract: Background: COVID-19 is currently rampant in China, causing unpredictable harm to humans. This study aimed to quantitatively and qualitatively investigate the research trends on coronaviruses using bibliometric analysis to identify new prevention strategies. Methods: All relevant publications on coronaviruses were extracted from 2000–2020 from the Web of Science database. An online analysis platform of literature metrology, bibliographic item co-occurrence matrix builder (BICOMB) and CiteSpace software were used to analyse the publication trends. VOSviewer was used to analyse the keywords and research hotspots and compare COVID-19 information with SARS and MERS information. Results: We found a total of 9,760 publications related to coronaviruses published from 2000 to 2020. The Journal of Virology has been the most popular journal in this field over the past 20 years. The United States maintained a top position worldwide and has provided a pivotal influence, followed by China. Among all the institutions, the University of Hong Kong was regarded as a leader for research collaboration. Moreover, Professors Yuen KY and Peiris JSM made great achievements in coronavirus research. We analysed the keywords and identified 5 coronavirus research hotspot clusters. Conclusions: We considered the publication information regarding different countries, institutions, authors, journals, etc. by summarizing the literature on coronaviruses over the past 20 years. We analysed the studies on COVID-19 and the SARS and MERS coronaviruses. Notably, COVID-19 must become the research hotspot of coronavirus research, and clinical research on COVID-19 may be the key to defeating this epidemic.

Apelin/Elabela-APJ: a novel therapeutic target in the cardiovascular system

Abstract: Apelin and Elabela (ELA) are endogenous ligands of angiotensin domain type 1 receptor-associated proteins (APJ). Apelin/ELA-APJ signal is widely distributed in the cardiovascular system of fetuse and adult. The signal is involved in the development of the fetal heart and blood vessels and regulating vascular tension in adults. This review described the effects of apelin/ELA-APJ on fetal (vasculogenesis and angiogenesis) and adult cardiovascular function [vascular smooth muscle cell (VSMC) proliferation, vasodilation, positive myodynamia], and relative diseases [eclampsia, hypertension, pulmonary hypertension, heart failure (HF), myocardial infarction (MI), atherosclerosis, etc.] in detail. The pathways of apelin/ELA-APJ regulating cardiovascular function and cardiovascular-related diseases are summarized. The drugs developed based on apelin and ELA suggests APJ is a prospective strategy for cardiovascular disease therapy.

Identification of m6A-related genes and m6A RNA methylation regulators in pancreatic cancer and their association with survival.

Abstract: Background N6-methyladenosine (m6A) modification holds an important position in tumorigenesis and metastasis because it can change gene expression and even function in multiple levels including RNA splicing, stability, translocation and translation. In present study, we aim to conducted comprehensive investigation on m6A RNA methylation regulators and m6A-related genes in pancreatic cancer and their association with survival time. Methods Based on Univariate Cox regression analysis, protein-protein interaction analysis, LASSO Cox regression, a risk prognostic model, STRING, Spearman and consensus clustering analysis, data from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) database was used to analyze 15 m6A RNA methylation regulators that were widely reported and 1,393 m6A-related genes in m6Avar. Results We found that 283 candidate m6A RNA methylation-related genes and 4 m6A RNA methylation regulatory factors, including RNA binding motif protein 15 (RBM15), methyltransferase like 14 (METTL14), fat mass and obesity-associated protein (FTO), and α-ketoglutarate-dependent dioxygenase AlkB homolog 5 (ALKBH5), differed significantly among different stages of the American Joint Committee on Cancer (AJCC) staging system. Protein-protein interaction analysis indicated epidermal growth factor receptor (EGFR), plectin-1 (PLEC), BLM RecQ like helicase (BLM), and polo like kinase 1 (PLK1) were closely related to other genes and could be considered as hub genes in the network. The results of LASSO Cox regression and the risk prognostic model indicated that AJCC stage, stage T and N, KRAS mutation status and x8q23.3 CNV fragment mutation differed significantly between the high-risk and the low-risk subgroups. The AUCs of 1 to 5 years after surgery were all more than 0.7 and increased year by year. Finally, we found KRAS mutation status and AJCC stage differed significantly among these groups after TCGA samples divided into subgroups with k=7. Moreover, we identified four m6A RNA methylation related genes expressed significantly differently among these seven subgroups, including collagen type VII alpha 1 chain (COL7A1), branched chain amino acid transaminase 1 (BCAT1), zinc finger protein 596 (ZNF596), and PLK1. Conclusions Our study systematically analyzed the m6A RNA methylation related genes, including expression, protein-protein interaction, potential function, and prognostic value and provides important clues to further research on the function of RNA m6A methylation and its related genes in pancreatic cancer.

Combined use of the neutrophil-to-lymphocyte ratio and CRP to predict 7-day disease severity in 84 hospitalized patients with COVID-19 pneumonia: A retrospective cohort study

Abstract: Background Coronavirus disease 2019 (COVID-19) has spread rapidly worldwide from Wuhan. An easy-to-use index capable of the early identification of inpatients who are at risk of becoming critically ill is urgently needed in clinical practice. Hence, the aim of this study was to explore an easy-to-use nomogram and a model to triage patients into risk categories to determine the likelihood of developing a critical illness. Methods A retrospective cohort study was conducted. We extracted data from 84 patients with laboratory-confirmed COVID-19 from one designated hospital. The primary endpoint was the development of severe/critical illness within 7 days after admission. Predictive factors of this endpoint were selected by LASSO Cox regression model. A nomogram was developed based on selected variables. The predictive performance of the derived nomogram was evaluated by calibration curves and decision curves. Additionally, the predictive performances of individual and combined variables under study were evaluated by receiver operating characteristic curves. The developed model was also tested in a separate validation set with 71 laboratory-confirmed COVID-19 patients. Results None of the 84 inpatients were lost to follow-up in this retrospective study. The primary endpoint occurred in 23 inpatients (27.4%). The neutrophil-to-lymphocyte ratio (NLR) and C-reactive protein (CRP) were selected as the final prognostic factors. A nomogram was developed based on the NLR and CRP. The calibration curve and decision curve indicated that the constructed nomogram model was clinically useful. The AUCs for the NLR, CRP and Combined Index in both training set and validation sets were 0.685 (95% CI: 0.574-0.783), 0.764 (95% CI: 0.659-0.850), 0.804 (95% CI: 0.702-0.883), and 0.881 (95% CI: 0.782-0.946), respectively. Conclusions Our results demonstrated that the nomogram and Combined Index calculated from the NLR and CRP are potential and reliable predictors of COVID-19 prognosis and can triage patients at the time of admission.

Clinical characteristics of children with COVID-19: A rapid review and meta-analysis

Abstract: Background Most guidelines on COVID-19 published so far include recommendations for patients regardless of age. Clinicians need a more accurate understanding of the clinical characteristics of children with COVID-19. Methods We searched studies reporting clinical characteristics in children with COVID-19 published until March 31, 2020. We screened the literature, extracted the data and evaluated the risk of bias and quality of evidence of the included studies. We combined some of the outcomes (symptoms) in a single-arm meta-analysis using a random-effects model. Results Our search retrieved 49 studies, including 25 case reports, 23 case series and one cohort study, with a total of 1,667 patients. Our meta-analysis showed that most children with COVID-19 have mild symptoms. Eighty-three percent of the children were within family clusters of cases, and 19% had no symptoms. At least 7% with digestive symptoms. The main symptoms of children were fever [48%, 95% confidence interval (CI): 39%, 56%] and cough (39%, 95% CI: 30%, 48%). The lymphocyte count was below normal level in only 15% (95% CI: 8%, 22%) of children which is different from adult patients. 66% (95% CI: 55%, 77%) of children had abnormal findings in CT imaging. Conclusions Most children with COVID-19 have only mild symptoms, and many children are asymptomatic. Fever and cough are the most common symptoms in children. Vomiting and diarrhea were not common in children. The lymphocyte count is usually within the normal range in children.

Public health education for parents during the outbreak of COVID-19: A rapid review

Abstract: Background It is well-known that public health education plays a crucial role in the prevention and control of emerging infectious diseases, but how health providers should advise families and parents to obtain health education information is a challenging question. With coronavirus disease 2019 (COVID-19) spreading around the world, this rapid review aims to answer that question and thus to promote evidence-based decision making in health education policy and practice. Methods We systematically searched the literature on health education during COVID-19, severe acute respiratory syndrome (SARS) and middle east respiratory syndrome (MERS) epidemics in Medline (via PubMed), Cochrane Library, EMBASE, Web of Science, China Biology Medicine disc (CBM), China National Knowledge Infrastructure (CNKI), and Wanfang Data from their inception until March 31, 2020. The potential bias of the studies was assessed by Joanna Briggs Institute Prevalence Critical Appraisal Tool. Results Of 1,067 papers found, 24 cross-sectional studies with a total of 35,967 participants were included in this review. The general public lacked good knowledge of SARS and MERS at the early stage of epidemics. Some people's knowledge, attitude and practice (KAP) of COVID-19 had been improved, but the health behaviors of some special groups including children and their parents need to be strengthened. Negative emotions including fear and stigmatization occurred during the outbreaks. Reliable health information was needed to improve public awareness and mental health for infectious diseases. Health information from nonprofit, government and academic websites was more accurate than privately owned commercial websites and media websites. Conclusions For educating and cultivating children, parents should obtain information from the official websites of authorities such as the World Health Organization (WHO) and national Centers for Disease Control, or from other sources endorsed by these authorities, rather than from a general search of the internet or social media.

Metabolic reprograming of tumor-associated macrophages.

Abstract: A large body of scientific evidence corroborated by clinical and animal model experiments indicates that tumor-associated macrophages (TAMs) play a crucial role in tumor development and progression. TAMs are a key immune cell type present in tumor microenvironment (TME) and associated with poor prognosis, drug resistance, enhanced angiogenesis and metastasis in cancer. TAMs are a phenotypically diverse population of myeloid cells which display tremendous plasticity and dynamic metabolic nature. A complete interpretation of pro-tumoral and anti-tumoral metabolic switch in TAMs is essential to understand immune evasion mechanisms in cancer. Recent studies have also implicated epigenetic mechanisms as significantly regulators of TAM functions. In this review we provide an overview of metabolic circuitry in TAMs, its impact on immune effector cells and interventions aimed at rewiring the metabolic circuits in TAMs. Mechanisms responsible for TAM polarization in cancer are also discussed.

The role of ferroptosis regulators in the prognosis, immune activity and gemcitabine resistance of pancreatic cancer.

Abstract: Background Ferroptosis is a novel form of regulated cell death that can inhibit the progression of chemotherapy-resistant tumors. However, the types of cancer most susceptible to ferroptosis induction and the role of ferroptosis regulators in cancers, especially pancreatic cancer, remain unclear. Methods RNA sequencing data of 31 cancers were collected from The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx). A nomogram integrating patients' clinical information and risk scores based on the expression levels of ferroptosis regulators was depicted. Correlations among the activity levels of 29 immunity-associated gene sets, immune scores, infiltrating immune cells and key ferroptosis regulators were assessed. Results We performed a pan-cancer analysis and identified 14 distinct cancers that may show a robust response to ferroptosis inducers. Interestingly, the Xc-complex, which is the major target of ferroptosis induction, was upregulated in gemcitabine-resistant pancreatic cancer cells (P<0.05). Furthermore, we focused on the role of ferroptosis regulators in mediating the survival of patients with pancreatic cancer and constructed a prognostic model with good accuracy (AUC =0.713). We also correlated elevated sensitivity to ferroptosis with higher scores for CD8+ T cells (P<0.001), the type two interferon response (P<0.001) and immune checkpoints (P<0.05). Conclusions We hypothesized that the ferroptosis pathway plays an important role in the prognosis of pancreatic cancer. Immuno- and chemotherapy combined with a ferroptosis inducer is a feasible therapeutic approach for pancreatic cancer.

Red cell distribution width (RDW): a prognostic indicator of severe COVID-19

Abstract: Background: The global mortality rate for coronavirus disease 2019 (COVID-19) is 3.68%, but the mortality rate for critically ill patients is as high as 50%. Therefore, the exploration of prognostic predictors for patients with COVID-19 is vital for prompt clinical intervention. Our study aims to explore the predictive value of hematological parameters in the prognosis of patients with severe COVID-19. Methods: Ninety-eight patients who were diagnosed with COVID-19 at Jingzhou Central Hospital and Central Hospital of Wuhan, Hubei Province, were included in this study. Results: The median age of the patients was 59 [28-80] years; the median age of patients with a good prognosis was 56 [28-79] years, and the median age of patients with a poor outcome was 67 [35-80] years. The patients in the poor outcome group were older than the patients in the good outcome group (P<0.05). The comparison of hematological parameters showed that lymphocyte count (Lym#), red blood cells (RBCs), hemoglobin (HGB), hematocrit (HCT), mean corpuscular volume (MCV), and mean corpuscular hemoglobin (MCH) were significantly lower in the poor outcome group than in the good outcome group (P<0.05). Further, the red cell volume distribution width-CV (RDW-CV) and red cell volume distribution width-SD (RDW-SD) were significantly higher in the poor outcome group than in the good outcome group (P<0.0001). Receiver operating characteristic (ROC) curves showed RDW-SD, with an area under the ROC curve (AUC) of 0.870 [95% confidence interval (CI) 0.796-0.943], was the most significant single parameter for predicting the prognosis of severe patients. When the cut-off value was 42.15, the sensitivity and specificity of RDW-SD for predicting the prognosis of severe patients were 73.1% and 80.2%, respectively. Reticulocyte (RET) channel results showed the RET level was significantly higher in critical patients than in moderate patients and severe patients (P<0.05), which may be one cause of the elevated RDW in patients with a poor outcome. Conclusions: In this study, the hematological parameters of COVID-19 patients were statistically analyzed. RDW was found to be a prognostic predictor for patients with severe COVID-19, and the increase in RET may contribute to elevated RDW.