Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 20 de 33
Filter
Add filters

Year range
1.
2nd International Conference on Big Data and Artificial Intelligence and Software Engineering (ICBASE) ; : 673-678, 2021.
Article in English | English Web of Science | ID: covidwho-1883119

ABSTRACT

Electromyography has been extensively used in a variety of fields. By using feature extraction to detect and analyze the surface EMG signal of Electromyography, muscle fatigue caused by daily life workout could be detected more timely. Here we intend to utilize this feature of using feature extraction on electromyography to offer professional advice for at home work out due to the deduction of outing caused by COVID-19. In this work, multiple time window (MTW) features have been used to distinguish the surface electromyography (sEMG) signals between muscle fatigue during arm movements by using Python. The sEMG signals are monitored from the biceps muscle of 3 healthy subjects. 4 window functions named boxcar function, hamming function, blackman function, and kaiser function and 24 features are extracted. 4 classifiers named Decision Tree, Random Forest, Support Vector Machine, and Naive Bayes are used in this research. The classifier using MTW features compared with the classifier without MTW feature. The Random Forest classifier has the greatest accuracy of 95.16%.

2.
22nd IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD-Fall) ; : 187-190, 2021.
Article in English | Web of Science | ID: covidwho-1853484

ABSTRACT

In this paper, we modified a low-cost and rapid method to detect chest X-rays based on MobileNet. Because MobileNet is a lightweight neural network, we modified and optimized backpropagation learning to train the model. In the subsequent COVID-19, pneumonia, and normal tests, the recognition accuracy reached 99.14%, which greatly improved the performance of the model.Our scheme can produce an effective model suitable for low-performance mobile devices.

3.
2nd International Conference on Big Data and Artificial Intelligence and Software Engineering, ICBASE 2021 ; : 673-678, 2021.
Article in English | Scopus | ID: covidwho-1759066

ABSTRACT

Electromyography has been extensively used in a variety of fields. By using feature extraction to detect and analyze the surface EMG signal of Electromyography, muscle fatigue caused by daily life workout could be detected more timely. Here we intend to utilize this feature of using feature extraction on electromyography to offer professional advice for at home work out due to the deduction of outing caused by COVID-19. In this work, multiple time window (MTW) features have been used to distinguish the surface electromyography (sEMG) signals between muscle fatigue during arm movements by using Python. The sEMG signals are monitored from the biceps muscle of 3 healthy subjects. 4 window functions named boxcar function, hamming function, blackman function, and kaiser function and 24 features are extracted. 4 classifiers named Decision Tree, Random Forest, Support Vector Machine, and Naïve Bayes are used in this research. The classifier using MTW features compared with the classifier without MTW feature. The Random Forest classifier has the greatest accuracy of 95.16%. © 2021 IEEE.Allrights reserved

4.
PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-330195

ABSTRACT

Objective: Real-world data have been critical for rapid-knowledge generation throughout the COVID-19 pandemic. To ensure high-quality results are delivered to guide clinical decision making and the public health response, as well as characterize the response to interventions, it is essential to establish the accuracy of COVID-19 case definitions derived from administrative data to identify infections and hospitalizations. Methods: Electronic Health Record (EHR) data were obtained from the clinical data warehouse of the Yale New Haven Health System (Yale, primary site) and 3 hospital systems of the Mayo Clinic (validation site). Detailed characteristics on demographics, diagnoses, and laboratory results were obtained for all patients with either a positive SARS-CoV-2 PCR or antigen test or ICD-10 diagnosis of COVID-19 (U07.1) between April 1, 2020 and March 1, 2021. Various computable phenotype definitions were evaluated for their accuracy to identify SARS-CoV-2 infection and COVID-19 hospitalizations. Results: Of the 69,423 individuals with either a diagnosis code or a laboratory diagnosis of a SARS-CoV-2 infection at Yale, 61,023 had a principal or a secondary diagnosis code for COVID-19 and 50,355 had a positive SARS-CoV-2 test. Among those with a positive laboratory test, 38,506 (76.5%) and 3449 (6.8%) had a principal and secondary diagnosis code of COVID-19, respectively, while 8400 (16.7%) had no COVID-19 diagnosis. Moreover, of the 61,023 patients with a COVID-19 diagnosis code, 19,068 (31.2%) did not have a positive laboratory test for SARS-CoV-2 in the EHR. Of the 20 cases randomly sampled from this latter group for manual review, all had a COVID-19 diagnosis code related to asymptomatic testing with negative subsequent test results. The positive predictive value (precision) and sensitivity (recall) of a COVID-19 diagnosis in the medical record for a documented positive SARS-CoV-2 test were 68.8% and 83.3%, respectively. Among 5,109 patients who were hospitalized with a principal diagnosis of COVID-19, 4843 (94.8%) had a positive SARS-CoV-2 test within the 2 weeks preceding hospital admission or during hospitalization. In addition, 789 hospitalizations had a secondary diagnosis of COVID-19, of which 446 (56.5%) had a principal diagnosis consistent with severe clinical manifestation of COVID-19 (e.g., sepsis or respiratory failure). Compared with the cohort that had a principal diagnosis of COVID-19, those with a secondary diagnosis had a more than 2-fold higher in-hospital mortality rate (13.2% vs 28.0%, P<0.001). In the validation sample at Mayo Clinic, diagnosis codes more consistently identified SARS-CoV-2 infection (precision of 95%) but had lower recall (63.5%) with substantial variation across the 3 Mayo Clinic sites. Similar to Yale, diagnosis codes consistently identified COVID-19 hospitalizations at Mayo, with hospitalizations defined by secondary diagnosis code with 2-fold higher in-hospital mortality compared to those with a primary diagnosis of COVID-19. Conclusions: COVID-19 diagnosis codes misclassified the SARS-CoV-2 infection status of many people, with implications for clinical research and epidemiological surveillance. Moreover, the codes had different performance across two academic health systems and identified groups with different risks of mortality. Real-world data from the EHR can be used to in conjunction with diagnosis codes to improve the identification of people infected with SARS-CoV-2.

5.
Journal of Travel & Tourism Marketing ; 38(9):917-934, 2021.
Article in English | Web of Science | ID: covidwho-1621376

ABSTRACT

This study draws on life history theory to rationalize how tourism enterprises make decisions and evolve during the COVID-19 pandemic. Using a case study approach, the current work improvises the house of trade-off paradox as a visual metaphoric framework that integrates three major dyadic trade-off pairs along with four organizational resource configuration aspects. This inquiry further synthesizes the wheel of selection strategy to pinpoint a mechanism in which tourism agencies mutate to adapt to a new normal based on acute environmental shocks. We further provide practical implications for operators with valuable insights germane to post-pandemic recovery.

6.
Respirology ; 26(SUPPL 3):18-19, 2021.
Article in English | EMBASE | ID: covidwho-1583447

ABSTRACT

Background: In 2020, the coronavirus disease 2019 began spreading widely across the world. We aim to study the biological changes of SARS-CoV-2 infected Vero cells using high-throughput sequencing data, which will be helpful for vaccine development and drug screening. Methods: The data GSE153940 was obtained from the Gene Expression Omnibus database. R software was used to screen out differentially expressed genes and perform Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. The protein-protein interaction network was built by STRING. Cytoscape 3.7.2 was applied for the visualization of the protein-protein interaction network and the identification of the hub genes. GraphPad Prism 8.4.3 was used to perform the statistical analysis to verify the obtained central genes. Results: A total of 3640 differentially expressed genes were obtained. The most significant enrichment items of Gene Ontology in the biological process, cellular component, and molecular function were the regulation of mRNA metabolic process, organelle inner membrane, and cadherin binding respectively. Ten enrichment pathways were identified by the Kyoto Encyclopedia of Genes and Genomes analyses. A protein-protein interaction network with 328 nodes and 498 edges was established. Six hub genes were screened out, among which four genes (MRPS7, DAP3, CHCHD1 and MRPL3) were confirmed to be statistically significant. Conclusions: Our results suggest that mitochondrial activity has a significant role in the process of SARS-CoV-2 infecting Vero E6 cells. Further experimental studies are needed to obtain abundant data to verify the predicted results of the bioinformatics analysis.

7.
Annals of the Academy of Medicine, Singapore ; 50(11):818-826, 2021.
Article in English | MEDLINE | ID: covidwho-1558253

ABSTRACT

INTRODUCTION: Inappropriate attendances (IAs) to emergency departments (ED) create an unnecessary strain on healthcare systems. With decreased ED attendance during the COVID-19 pandemic, this study postulates that there are less IAs compared to before the pandemic and identifies factors associated with IAs. METHODS: We performed a retrospective review of 29,267 patient presentations to a healthcare cluster in Singapore from 7 April 2020 to 1 June 2020, and 36,370 patients within a corresponding period in 2019. This time frame coincided with local COVID-19 lockdown measures. IAs were defined as patient presentations with no investigations required, with patients eventually discharged from the ED. IAs in the 2020 period during the pandemic were compared with 2019. Multivariable logistic regression was performed to identify factors associated with IAs. RESULTS: There was a decrease in daily IAs in 2020 compared to 2019 (9.91+/-3.06 versus 24.96+/-5.92, P<0.001). IAs were more likely with self-referrals (adjusted odds ratio [aOR] 1.58, 95% confidence interval [CI] 1.50-1.66) and walk-ins (aOR 4.96, 95% CI 4.59-5.36), and those diagnosed with non-specific headache (aOR 2.08, 95% CI 1.85-2.34), or non-specific low back pain (aOR 1.28, 95% CI 1.15-1.42). IAs were less likely in 2020 compared to 2019 (aOR 0.67, 95% CI 0.65-0.71) and older patients (aOR 0.79 each 10 years, 95% CI 0.78-0.80). CONCLUSION: ED IAs decreased during COVID-19. The pandemic has provided a unique opportunity to examine factors associated with IAs.

8.
European Heart Journal ; 42(SUPPL 1):3287, 2021.
Article in English | EMBASE | ID: covidwho-1554427

ABSTRACT

Cardiac injury is common in hospitalized and non-hospitalized COVID- 19 patients, for which systemic inflammation stress is one of the causes (Topol, 2020). Although rare, COVID-19 cases that SARS-CoV-2 infecting cardiomyocytes (CMs) have been reported. In vitro, SARS-CoV-2 infection of human induced-pluripotent-cells derived CMs triggered innate immune responses and induced apoptosis (Bojkova et al., 2020;Chen et al., 2020). Therefore, the current literature indicates that the heart is attacked by SARS-CoV-2 directly or indirectly;however, the underlying mechanism remains largely unknown. Involved in the pathogenesis of heart diseases, Toll-like receptors (TLR) are a family of pattern recognition receptors that sense the pathogenic stimuli and signal the cardiac residential cells to cope with harsh conditions (Yu and Feng, 2018). Among the best characterized TLR signaling pathways is TLR4/NF-kB axis (Lu et al., 2008), in which TLR4 convey the danger signals through its down stream kinases, such as TAK1 and TBK1, to activate NF-kB. SARS-CoV-2 Spike protein is well known for its role of mediating virus entry into host cells, but its immunogenic role has not been clearly defined. Recently, we have found that SARS-CoV-2 Spike protein directly interacts with TLR4 and activates NFkB transcriptional activity. Pharmaceutically blocking either TBK1 or TAK1 attenuates Spike protein's immunogenic activity. To pinpoint Spike protein's role in the heart, we generated an AAV to specifically express a truncated Spike protein (S1-TM) in the CMs. Our data show that expressing S1-TM in CMs induces cardiac hypertrophy and decreases heart systolic function in mice. On the molecular level, Spike protein increases RelA (p65 subunit of the NF-kB complex) and activates the expression of pro-inflammatory cytokine genes. In summary, our study suggests that Spike protein directly interacts with TLR4 to trigger innate immune signaling, and that Spike protein induced CM innate immune responses might be one of the underlying mechanisms of cardiac injury in COVID-19.

9.
American Journal of Gastroenterology ; 116(SUPPL):S1482, 2021.
Article in English | EMBASE | ID: covidwho-1534902

ABSTRACT

Introduction: Coronavirus disease 2019 (COVID-19) dysregulates the immune response and promotes overwhelming levels of inflammation. Data is scarce on the consequent effects of COVID-19 on the immune system and whether patients with COVID-19 are more prone to developing inflammatory bowel disease (IBD). We report two cases of previously healthy patients with a family history of IBD and recent COVID-19 diagnoses who were subsequently diagnosed with Crohn's disease. Case Description/Methods: Case 1: A previously healthy 17-year-old female presented with fever, bloody diarrhea, and weight loss. The patient had a diagnosis of COVID-19 from one month prior and a family history of Crohn's disease in her father. She underwent colonoscopy, which revealed ulcerations in terminal ileum and throughout the colon. Pathology demonstrated acute and chronic inflammation as well as chronic post-inflammatory changes throughout the colon and terminal ileum. She was diagnosed with Crohn's ileocolitis and treated with steroids followed by infliximab with a good clinical response. Case 2: A previously healthy 19-year-old male presented with recurrent abdominal pain and non-bloody diarrhea of two months. The patient had numerous first-degree relatives with Crohn's disease and a recent diagnosis of COVID-19 six months prior. Subsequent colonoscopy demonstrated a terminal ileum stricture with scarring and denuded mucosa. Pathology illustrated markedly active chronic ileitis. Magnetic resonance enterography (MRE) showed small bowel obstruction related to a long segment of active inflammation and stricturing within the terminal ileum. The patient was diagnosed with Crohn's disease and treated with steroids followed by adalimumab with marked improvement. Discussion: In our two cases, both patients were previously healthy aside from a recent COVID-19, and both had family history of Crohn's disease. IBD is thought to develop in patients with a genetic predisposition whose immune systems encounter an environmental trigger that promotes the inappropriate inflammation to normal intestine. New infections have been implicated as possible trigger events culminating in the pathogenesis seen in IBD. COVID-19 may represent one type of infection that drives new IBD development, especially given its known dysregulatory effects on the immune system. Whether our patients' new diagnoses of Crohn's disease were related to their recent COVID-19 infection remains unclear, and large epidemiological studies are required to investigate further.

10.
Gaodeng Xuexiao Huaxue Xuebao/Chemical Journal of Chinese Universities ; 42(11):3509-3518, 2021.
Article in English | Scopus | ID: covidwho-1524547

ABSTRACT

Rapid detection of body fluid severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) antibody is an effective strategy for infection therapeutic effect of coronavirus disease(COVID-19). Most detection methods require relatively large equipment, which limited their on-site application. Lateral flow immunoassay(LFIA) can be used to qualitative antibody detection based on the aggregation of gold nanoparticles (Au NPs), which exhibits just one-color change and cannot realize rapid quantitative detection without the help of additional equipment. In this study, a high-resolution multicolor colorimetric strategy was developed and applied to assessing antibody concentration at a glance based on etching of gold nanorods(Au NRs). Firstly, SARS-CoV-2 recombinant antigen was immobilized on the surface of the 96-wells. Then, horseradish peroxidase(HRP)-labeled second antibody combined with antibody to form an antigen-antibody-secondary antibody complex on the well surface, which has direct relationship with antibody concentration in the sample and can be used to oxidize 3, 3', 5, 5'-tetramethylbenzidine(TMB) to form TMB2+ at the presence of HRP. The generation of TMB2+ efficiently etch Au NRs to produce multicolor solution. The etching result in vivid color changes in the system has a relationship with the amount of SARS-CoV-2 IgM antibody. Under the optimal conditions, the proposed strategy exhibited a linear response in the 5.00―200 IU concentration range, and a detection limit of 1.29 IU for SARS-CoV-2 IgM antibody, with high sensitivity and specificity. This assay is prospective for the on-site semi-quantitative visual detection of SARS-CoV-2 IgM antibody concentration in the COVID-19 therapeutic process. © 2021, Editorial Department of Chem. J. Chinese Universities. All right reserved.

11.
International Journal of Contemporary Hospitality Management ; 2021.
Article in English | Scopus | ID: covidwho-1475973

ABSTRACT

Purpose: This study aims to move beyond the current understanding of corporate social responsibility (CSR) to propose the concept of just-in-time (JIT) CSR as a metaphor that reflects hospitality operators’ endeavors to expedite socially responsible measures to both internal and external organizational stakeholders during times when functional and emotional supports are urgently needed. Design/methodology/approach: This research used a qualitative approach in two studies. Study 1 engaged a media analysis to better grasp the knowledge of the research problem at hand. Study 2 involved interviews from stakeholders to assess their emotions and perceptions of meanings of major contents discerned from the first study. Findings: This research highlights a process in which operators’ CSR practices (e.g. for business practices, for organizational strategy and for stakeholder well-being) during the COVID-19 crisis are imbued with connotative meanings (e.g. place-as-safety, place-as-partnership and place-as-warmth) that ultimately give shape to three core outcomes (e.g. individual rejoinder, brand resonance and societal resilience). Research limitations/implications: While JIT CSR is not an antidote for all devastations caused by COVID-19, it is posited as a needed mechanism that operators could use to ameliorate the situation and to go beyond their own stake to bring a broader array of societal benefits to humanity. Originality/value: This research underscores how hospitality operators expedite crisis responses to the pandemic, and how their societal objectives transform the image of a place from a commercial venue into a place imbued with meaning associated with safety, partnership and warmth. © 2021, Emerald Publishing Limited.

13.
5th International Joint Conference on Asia-Pacific Web and Web-Age Information Management, APWeb-WAIM 2021 ; 12858 LNCS:140-145, 2021.
Article in English | Scopus | ID: covidwho-1437168

ABSTRACT

Suicide ideation detection on social media is a challenging problem due to its implicitness. In this paper, we present an approach to detect suicide ideation on social media based on a BERT-LSTM model with Adversarial and Multi-task learning (BLAM). More specifically, BLAM combines BERT model with Bi-LSTM model to extract deeper and richer features. Furthermore, emotion classification is utilized as an auxiliary task to perform multi-task learning, which enriches the extracted features with emotion information that enhances the identification of suicide. In addition, BLAM generates adversarial noise by adversarial learning improving the generalization ability of the model. Extensive experiments conducted on our collected Suicide Ideation Detection (SID) dataset demonstrate the competitive superiority of BLAM compared with the state-of-the-art methods. © 2021, Springer Nature Switzerland AG.

14.
IEEE Sensors Journal ; 2021.
Article in English | Scopus | ID: covidwho-1416223

ABSTRACT

An ultra-thin and highly sensitive SARS-CoV-2 detection platform was demonstrated using a nano-porous anodic aluminum oxide (AAO) membrane. The membrane surface was functionalized to enable efficient trapping and identification of SARS-CoV-2 genomic targets through DNA-DNA and DNA-RNA hybridization. To immobilize the probe oligonucleotides on the AAO membrane, the pore surface was first coated with the linking reagents, 3-aminopropyltrimethoxysilane (APTMS) and glutaraldehyde (GA), by a compact vacuum infiltration module. After that, complementary target oligos with fluorescent modifier was pulled and infiltrated into the nano-fluidic channels formed by the AAO pores. The fluorescent signal applying the AAO membrane sensors was two orders stronger than a flat glass template. In addition, the dependence between the nano-pore size and the fluorescent intensity was evaluated. The optimized pore diameter d is 200 nm, which can accommodate the assembled oligonucleotide and aminosilane layers without blocking the AAO nano-fluidic channels. Our DNA functionalized membrane sensor is an accurate and high throughput platform supporting rapid virus tests, which is critical for population-wide diagnostic applications result in a page being rejected by search engines. Ensure that your abstract reads well and is grammatically correct. IEEE

15.
Journal of Landscape Research ; 13(4):29-36, 2021.
Article in English | Academic Search Complete | ID: covidwho-1368070

ABSTRACT

In a new round of urban renewal, China's urban space expansion is shifting from incremental development to inventory mining. Residents' demands for improvement of community material environment and community cultural identity are increasing. Meantime, affected by the COVID-19 pandemic in 2019, community resilience has become an urgent problem to be solved in urban communities. Based on resilience theory, TOD theory and other planning concepts, the paper analyzes the vulnerability of Shanghai Caoyang river ring area, and puts forward a multi-level community resilience improvement strategy, including increasing diversified public service facilities, building public pedestrian network, and reshaping public open space to improve the stability, adaptability and resilience of the community, in order to build the development path of resilient communities. The study will provide inspiration for future microrenewal of communities and promote the sustainable development of urban communities. [ABSTRACT FROM AUTHOR] Copyright of Journal of Landscape Research is the property of WuChu (USA - China) Science & Culture Media Corporation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

16.
16th Ieee International Conference on Control, Automation, Robotics and Vision ; : 779-783, 2020.
Article in English | Web of Science | ID: covidwho-1271432

ABSTRACT

Due to the outbreak of the novel coronavirus (or known as COVID-19), people are advised to wear masks when they stay outdoors in many countries. This could result in difficulty for some public safety surveillance systems involving face detection or tracking. Therefore, the development of face detection and tracking algorithms for people wearing face masks is particularly important. In this paper, a real-time tracking algorithm for people with or without face masks is proposed. This algorithm is trained on public face datasets with faces without masks. Although the training does not involve face images of people wearing face masks, we show that the proposed algorithm is robust as it is able to perform well in face tracking for people wearing face masks. We also discuss the possible scenarios where the algorithm could lose track of the target when experimenting in tracking masked faces. This can motivate future research in this area.

17.
Letters in Drug Design & Discovery ; 18(4):355-364, 2021.
Article in Chinese | Web of Science | ID: covidwho-1256217

ABSTRACT

Background: The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has attracted worldwide attention due to its high infectivity and pathogenicity. Objective: The purpose of this study is to develop drugs with therapeutic potentials for COVID-19. Methods: we selected the crystal structure of 3CL pm to perform virtual screening against natural products in the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Then, molecular dynamics (MD) simulation was carried out to explore the binding mode between compounds and 3CL pro. Results and Discussion: A total of 6 candidates with good theoretical binding affinity to 3CL pm were identified. The binding mode after MD shows that hydrogen bonding and hydrophobic interaction play an important role in the binding process. Finally, based on the free binding energy analysis, the candidate natural product Gypenoside LXXV may bind to 3CL pm with high binding affinity. Conclusion: The natural product Gypenoside LXXV may have good potential anti-SARS-COV-2 activity.

18.
Scientific Reports ; 11(1):9315, 2021.
Article in English | MEDLINE | ID: covidwho-1210218

ABSTRACT

A critical step in effective care and treatment planning for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause for the coronavirus disease 2019 (COVID-19) pandemic, is the assessment of the severity of disease progression. Chest x-rays (CXRs) are often used to assess SARS-CoV-2 severity, with two important assessment metrics being extent of lung involvement and degree of opacity. In this proof-of-concept study, we assess the feasibility of computer-aided scoring of CXRs of SARS-CoV-2 lung disease severity using a deep learning system. Data consisted of 396 CXRs from SARS-CoV-2 positive patient cases. Geographic extent and opacity extent were scored by two board-certified expert chest radiologists (with 20+ years of experience) and a 2nd-year radiology resident. The deep neural networks used in this study, which we name COVID-Net S, are based on a COVID-Net network architecture. 100 versions of the network were independently learned (50 to perform geographic extent scoring and 50 to perform opacity extent scoring) using random subsets of CXRs from the study, and we evaluated the networks using stratified Monte Carlo cross-validation experiments. The COVID-Net S deep neural networks yielded R[Formula: see text] of [Formula: see text] and [Formula: see text] between predicted scores and radiologist scores for geographic extent and opacity extent, respectively, in stratified Monte Carlo cross-validation experiments. The best performing COVID-Net S networks achieved R[Formula: see text] of 0.739 and 0.741 between predicted scores and radiologist scores for geographic extent and opacity extent, respectively. The results are promising and suggest that the use of deep neural networks on CXRs could be an effective tool for computer-aided assessment of SARS-CoV-2 lung disease severity, although additional studies are needed before adoption for routine clinical use.

20.
Journal of Clinical Oncology ; 39(3 SUPPL), 2021.
Article in English | EMBASE | ID: covidwho-1147263

ABSTRACT

Background: Chemoradiotherapy followed byradical surgery is standard treatment for patients with locally advanced rectal cancer(LARC). Short-course radiotherapy (SCRT), either with immediate or delayed surgery, providessimilar oncological results compared with long-course radiotherapy with delayed surgery.Delayed surgery with the addition of neoadjuvant immunotherapy may bring betterdownstaging effect and minimize the risk of distant relapse. We conducted this single-armphase 2 trial to investigate the efficacy and safety of SCRT combined with subsequentcapecitabine and oxaliplatin (CAPOX) plusCamrelizumab (anti-PD-1 antibody) followed bydelayed surgery in patients with LARC. Methods: Patients with histologically confirmed T3-4 N0 M0 or T1-4 N+ M0 rectal cancer, previouslyuntreated disease, and ECOG performancestatus of 0-1, received SCRT (5×5 Gy) withsubsequent two 21-day cycles of CAPOX(oxaliplatin 130 mg/m2 ivgtt, d1;capecitabine1000 mg/m2 po bid, d1-14) plus Camrelizumab(200 mg iv drip, d1) after 1 week, followed byradical surgery after 1 week. Adjuvant therapy was decided by the investigator. The primaryendpoint was pathological complete response(pCR) rate, defined as the absence of viabletumor cells in the primary tumor and lymphnodes. The study is ongoing to follow up thesurvival outcomes and obtain the results of nextgeneration sequencing and PD-L1 expression.The data cutoff date was September 8, 2020. Results: From November 2019 to September2020, a targeted number of patients (n = 29)were enrolled and are expected to complete thesurgery by November 2020. The median age was 57 (range 31-73) years, 55% (16/29) of patients had ECOG performance status of 1, and the median distance from tumor to the anal verge was 5 (range, 1.9-9) cm. At data cutoff, 10 patients had undergone the surgery, with R0 resection rate of 100%. The pCR rate was 60% (6/10), including 56% (5/9) for those with mismatch repair-proficient, and 100% (1/1) for those with mismatch repair-deficient. Of 4 patients without pCR, 2 only received one cycle of CAPOX plus Camrelizumab due to the outbreak of COVID-19 in Wuhan, and 1 had signet-ring cell rectal carcinoma. At data cutoff, 20 patients had received at least one dose of Camrelizumab. Immune-related adverse events (irAEs) were all grade 1-2, and the most common irAE was reactive cutaneous capillary endothelial proliferation in 10 (50%) of 20 patients. Postoperative bleeding and infection occurred in 1 (10%) and 2 (20%) of 10 patients, respectively. No treatment-related death was observed. Conclusions: SCRT combined with subsequent CAPOX plus Camrelizumab followed by delayed surgery showed promising pCR rate with good tolerance in patients with LARC, regardless of the mismatch repair status, suggesting a candidate strategy for the neoadjuvant therapy.

SELECTION OF CITATIONS
SEARCH DETAIL