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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.
Topics in Antiviral Medicine ; 30(1 SUPPL):37-38, 2022.
Article in English | EMBASE | ID: covidwho-1880239

ABSTRACT

Background: Post-Acute Sequelae of SARS-CoV-2 (PASC) is characterized by persistent symptoms negatively impacting quality of life several weeks after SARS-CoV-2 diagnosis. Proposed risk factors include older age, female sex, comorbidities, and severe COVID-19, including hospitalization and oxygen requirement. Yet, associations of these factors with prolonged symptoms remain poorly understood globally. Methods: The global, observational cohort study HVTN 405/HPTN 1901 characterizes the clinical and immunologic course in the first year after SARS-CoV-2 infection among adults. The cohort was categorized by infection severity (asymptomatic;symptomatic with no oxygen requirement [NOR];non-invasive oxygen requirement [NIOR];or invasive oxygen requirement [IOR]). A regression model was applied to estimate geometric mean ratios (GMR) for duration and odds ratios (OR) for persistence of symptoms. Results: 759 participants from Peru (25.2%), USA (26.0%), Republic of South Africa (RSA, 37.7%), and non-RSA Sub-Saharan Africa (11.2%) were enrolled a median of 51 (IQR 35-66) days post-diagnosis, from May 2020 to Mar 2021. 53.8% were female, 69.8% were <55yo (median 44yo, IQR 33-58) and identified as non-Hispanic Black (42.7%), Hispanic (27.9%) or non-Hispanic White (15.8%). Comorbidities included obesity (42.8%), hypertension (24%), diabetes (14%), HIV infection (11.6%) and lung disease (7.5%). 76.2% were symptomatic (NOR 47.4%;NIOR 22.9%;and IOR 5.8%). Among symptomatic participants, median acute COVID-19 duration was 20 days (IQR 11-35);43.3% had ≥1 persistent symptom after COVID-19 resolution (39.8% NOR;49.1 % NIOR+IOR;p=0.037);16.8% reported ≥1 symptom >42 days (14.0% NOR;21.6% NIOR+IOR;p=0.025). Symptom duration was not associated with age or sex assigned at birth but was associated with disease severity (GMR 2.09;95%CI 1.5-2.91, p<0.001 for NIOR vs NOR;not significant for IOR vs NIOR), lung disease (GMR 2.43;95%CI 1.42-4.16, p=0.001), and global region (p<0.05, see Figure 1). Prolonged viral shedding was associated with persistent diarrhea (OR 6.59;95%CI 1.65-26.86;p=0.008). Conclusion: A recovery course consistent with PASC was significantly associated with infection severity, lung disease, and region. Regional differences in symptom profiles and duration may be influenced by viral diversity, genetic, or cultural factors and likely reflect disparities in healthcare access and interventions. Better understanding PASC associations may improve clinical assessment and management globally.

3.
Zhonghua Yu Fang Yi Xue Za Zhi ; 56(5): 659-667, 2022 May 06.
Article in Chinese | MEDLINE | ID: covidwho-1875840

ABSTRACT

Coronavirus disease 19 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 has spread all over the world. Streptococcus pneumoniae as a common pathogen of community-acquired pneumonia shares similar high-risk susceptible populations with COVID-19. Streptococcus pneumoniae co-infection is a key risk factor for severe COVID-19 and death. Pneumococcal vaccination has a beneficial impact on reducing the incidence and mortality of COVID-19. The vaccination rate of streptococcus pneumoniae is still low in China. Streptococcus pneumoniae vaccination may be one of effective strategies in the management of COVID-19 for high-risk population such as the elderly and those who have underlying chronic diseases.


Subject(s)
COVID-19 , Coinfection , Pneumococcal Infections , Aged , Humans , Pneumococcal Infections/prevention & control , Streptococcus pneumoniae , Vaccination
4.
Acupuncture and Electro-Therapeutics Research ; 47(1):81-90, 2022.
Article in English | EMBASE | ID: covidwho-1862959

ABSTRACT

Objective: To explore the early warning signs of deterioration of patients with COVID-19. Methods: The data of thirty-six patients who were admitted to Handan Infectious Disease Hospital was collected. The clinical features and laboratory testing were analyzed retrospectively. The initial laboratory testing included blood chemistries, blood routine, D-dimer, coagulation function, etc. The patients were divided into mild/common group and severe/critical group. Results: The lymphocyte count, monocyte count, hemoglobin, and albumin levels in severe/critical group were lower compared with those in mild/common group, while the fibrinogen was higher. The lymphocyte count and monocyte count were positively correlated with hemoglobin, pre-albumin respectively. Conclusion: In conclusion, patients with lower initial prealbumin and hemoglobin level were more likely to progress into severe conditions. Decreased prealbumin and hemoglobin, combined with lymphocyte count and monocyte count, could be the early warning signs of deterioration of patients with COVID-19.

5.
2022 International Conference on Machine Learning and Knowledge Engineering, MLKE 2022 ; : 306-309, 2022.
Article in English | Scopus | ID: covidwho-1861136

ABSTRACT

Under the serious influence of COVID-19, online teaching has become a mainstream teaching mode. During the online teaching, it is difficult for teachers to evaluate and intervene in students' learning in real time. Therefore, for students who lack self-control, it is possible to be stuck in low learning efficiency and even failure of course assessment. How to obtain valid information of students' learning status in time during the online teaching process is a hot research topic at present. This paper proposes a feedback service for teaching based on educational data mining. It can, through a reasonable analysis of the data submitted in form of students' homework, accurately screen out students who have difficulties in learning a certain course and give directions to achieve the purpose of optimizing the teaching. © 2022 IEEE.

6.
Journal of Heart and Lung Transplantation ; 41(4):S131-S131, 2022.
Article in English | Web of Science | ID: covidwho-1849444
7.
6th IEEE International Conference on Data Science in Cyberspace, DSC 2021 ; : 635-639, 2021.
Article in English | Scopus | ID: covidwho-1831756

ABSTRACT

Advanced Persistent Threat (APT) attack activities with the theme of COVID-19 and vaccine are also growing rapidly. The target of APT attack has gradually expanded from government agencies to vaccine manufacturers, medical industry and so on. What's more, APT groups have a strict organizational structure and professional division of labor and malware delivered by the same APT groups are similar. Classifying malware samples into known APT groups in time can minimize losses as soon as possible and keep relevant industries vigilant. In our paper, we proposed a multi-classification method of APT malware based on Adaboost and LightGBM. We collect real APT malware samples that have been delivered by 12 known APT groups. The API call sequence of each APT malware is obtained through the sandbox. For the relationship between adjacent APIs, we use TF-IDF algorithm combined with bi-gram. Then, Adaboost algorithm is used to select out the important API features, which form the target feature subset. Finally, we use the above subset combined with LightGBM ensemble algorithm to train multiple classifiers, named Ada-LightGBM. The experimental results show that our method is superior to the single Adaboost and LightGBM method. The classifier has good recognition performance for the test samples. © 2021 IEEE.

8.
27th International Conference on Database Systems for Advanced Applications, DASFAA 2022 ; 13247 LNCS:263-271, 2022.
Article in English | Scopus | ID: covidwho-1826245

ABSTRACT

In this work, we focus on ive summarization methods for assisting medical researchers in effectively managing information. Particularly, we introduce a COVID-19-related summarization dataset (COVID-SUM) and propose a novel Keyword-aware Attention ive Summarization (KAAS) model. The KAAS model consists of two encoders and one decoder. As for the encoders, one is a standard article encoder built on transformer layers, while the other one is a hierarchical keyword encoder that first encodes the words in a keyword using BiLSTM, and then passes the keyword representations to a transformer layer to connect the keywords in an example. Additionally, a decoder with keyword-focused attention is utilized to further direct the decoding process to generate comprehensive summaries of the scientific articles. We benchmark several summarization methods on the new COVID-SUM dataset and release this dataset in the hope to promote advances to summarization in the COVID-19 medical area (https://github.com/ccip-author/COVID-SUM/releases ). Furthermore, we evaluate the KAAS on COVID-SUM, ArXiv, and PubMed datasets. Experimental results demonstrate that KAAS outperforms several state-of-the-art models on these datasets. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

9.
13th International Conference on Semantic Web Applications and Tools for Health Care and Life Sciences, SWAT4HCLS 2022 ; 3127:108-117, 2022.
Article in English | Scopus | ID: covidwho-1823711

ABSTRACT

Emergence of the Coronavirus 2019 Disease has highlighted further the need for timely support for clinicians as they manage severely ill patients. We combine Semantic Web technologies with Deep Learning for Natural Language Processing with the aim of converting human-readable best evidence/ practice for COVID-19 into that which is computer-interpretable. We present the results of experiments with 1212 clinical ideas (medical terms and expressions) from two UK national healthcare services specialty guides for COVID-19 and three versions of two BMJ Best Practice documents for COVID-19. The paper seeks to recognise and categorise clinical ideas, performing a Named Entity Recognition (NER) task, with an ontology providing extra terms as context and describing the intended meaning of categories understandable by clinicians. The paper investigates: 1) the performance of classical NER using MetaMap versus NER with fine-tuned BERT models;2) the integration of both NER approaches using a lightweight ontology developed in close collaboration with senior doctors;and 3) the easy interpretation by junior doctors of the main classes from the ontology once populated with NER results. We report the NER performance and the observed agreement for human audits. Copyright © 2022 for this paper by its authors.

10.
PubMed; 2020.
Preprint in English | PubMed | ID: ppcovidwho-333542

ABSTRACT

BACKGROUND: In response to supply shortages during the COVID-19 pandemic, N95 filtering facepiece respirators (FFRs or "masks"), which are typically single-use devices in healthcare settings, are routinely being used for prolonged periods and in some cases decontaminated under "reuse" and "extended use" policies. However, the reusability of N95 masks is often limited by degradation or breakage of elastic head bands and issues with mask fit after repeated use. The purpose of this study was to develop a frame for N95 masks, using readily available materials and 3D printing, which could replace defective or broken bands and improve fit. RESULTS: An iterative design process yielded a mask frame consisting of two 3D-printed side pieces, malleable wire links that users press against their face, and cut lengths of elastic material that go around the head to hold the frame and mask in place. Volunteers (n= 41;average BMI= 25.5), of whom 31 were women, underwent qualitative fit with and without mask frames and one or more of four different brands of FFRs conforming to US N95 or Chinese KN95 standards. Masks passed qualitative fit testing in the absence of a frame at rates varying from 48 - 92% (depending on mask model and tester). For individuals for whom a mask passed testing, 75-100% (average = 86%) also passed testing with a frame holding the mask in place. Among users for whom a mask failed in initial fit testing, 41% passed using a frame. Success varied with mask model and across individuals. CONCLUSIONS: The use of mask frames can prolong the lifespan of N95 and KN95 masks by serving as a substitute for broken or defective bands without adversely affecting fit. Frames also have the potential to improve fit for some individuals who cannot fit existing masks. Frames therefore represent a simple and inexpensive way of extending the life and utility of PPE in short supply. For clinicians and institutions interested in mask frames, designs and specifications are provided without restriction for use or modification. To ensure adequate performance in clinical settings, qualitative fit testing with user-specific masks and frames is required.

11.
PubMed; 2020.
Preprint in English | PubMed | ID: ppcovidwho-333508

ABSTRACT

BACKGROUND: Serological tests are crucial tools for assessments of SARS-CoV-2 exposure, infection and potential immunity. Their appropriate use and interpretation require accurate assay performance data. METHOD: We conducted an evaluation of 10 lateral flow assays (LFAs) and two ELISAs to detect anti-SARS-CoV-2 antibodies. The specimen set comprised 128 plasma or serum samples from 79 symptomatic SARS-CoV-2 RT-PCR-positive individuals;108 pre-COVID-19 negative controls;and 52 recent samples from individuals who underwent respiratory viral testing but were not diagnosed with Coronavirus Disease 2019 (COVID-19). Samples were blinded and LFA results were interpreted by two independent readers, using a standardized intensity scoring system. RESULTS: Among specimens from SARS-CoV-2 RT-PCR-positive individuals, the percent seropositive increased with time interval, peaking at 81.8-100.0% in samples taken >20 days after symptom onset. Test specificity ranged from 84.3-100.0% in pre-COVID-19 specimens. Specificity was higher when weak LFA bands were considered negative, but this decreased sensitivity. IgM detection was more variable than IgG, and detection was highest when IgM and IgG results were combined. Agreement between ELISAs and LFAs ranged from 75.7-94.8%. No consistent cross-reactivity was observed. CONCLUSION: Our evaluation showed heterogeneous assay performance. Reader training is key to reliable LFA performance, and can be tailored for survey goals. Informed use of serology will require evaluations covering the full spectrum of SARS-CoV-2 infections, from asymptomatic and mild infection to severe disease, and later convalescence. Well-designed studies to elucidate the mechanisms and serological correlates of protective immunity will be crucial to guide rational clinical and public health policies.

12.
The Journal of heart and lung transplantation : the official publication of the International Society for Heart Transplantation ; 41(4):S131-S131, 2022.
Article in English | EuropePMC | ID: covidwho-1782282

ABSTRACT

Purpose Racial disparities in severe acute respiratory syndrome coronavirus 2 (COVID) incidence and mortality have been demonstrated in the United States (U.S.). Transplant recipients represent a particularly vulnerable population given their comorbidities and immunosuppression. With this in mind, we aimed to evaluate the relationship between race and mortality due to COVID in lung transplant recipients. Methods Adult lung transplant recipients in the U.S. were identified using the Organ Procurement and Transplantation (OPTN) database. Multiorgan transplants and patients transplanted after December 31, 2020 were excluded. Recipients who were deceased or lost to follow-up prior to January 2020 were excluded as they were not at risk for death due to COVID. Lung transplant recipients were stratified by race (Black, Hispanic, White, and other race). Death due to COVID was the primary outcome while all-cause mortality and non-COVID mortality were secondary outcomes. Student's t-test, Chi-square test, and Cox proportional hazards models were used for comparisons. Results 17,198 recipients met inclusion criteria (1,598 Black, 1,353 Hispanic, 13,755 White, and 492 other race). 231 (1.34%) deaths due to COVID were reported. COVID mortality rate was significantly different (p=0.001) by race, being lowest in White recipients (n=162 [1.18%]) and highest in Hispanic recipients (n=30 [2.22%]). Non-COVID mortality was lowest in Hispanic recipients (n=129 [9.53%]) and highest in Black recipients (n=236 [14.77%];p=0.008). There was no significant difference in all-cause mortality (p=0.054). After adjustment, Hispanic (HR=2.18;p=0.005) recipients experienced higher rates of mortality due to COVID compared to whites, but no significant difference in Black recipients (HR=1.73;p=0.066). See table 1 for additional predictors of death due to COVID. Conclusion Racial disparities in death due to COVID persist in U.S. lung transplant recipients, despite adjusting for social determinants of health.

13.
Chinese Journal of Clinical Pharmacology and Therapeutics ; 27(2):190-197, 2022.
Article in Chinese | EMBASE | ID: covidwho-1780273

ABSTRACT

COVID-19 pandemic has put a huge burden on public health and global economy. Vaccines play an important role in controlling virus transmission and reducing mortality. While monoclonal virus neutralizing antibodies can reduce the viral load, improve symptoms, and prevent the aggravation of the disease from hospitalization. Now hundreds of clinical trials of COVID-19 vaccine and monoclonal neutralizing antibody are in progress. The vaccine focuses on disease prevention, while the neutralizing antibody focuses on disease treatment. There are quite many differences between the two kinds of clinical trials by following different technical guidelines, research purpose, trial design, implementation and outcome assessment. Therefore, it is necessary to summarize the similarities and differences between the clinical trials for the reference of new drug research and development as well as clinical researchers.

14.
Blood ; 138(SUPPL 1):3525, 2021.
Article in English | EMBASE | ID: covidwho-1770434

ABSTRACT

Background - The WINDOW-1 regimen introduced first-line ibrutinib with rituximab (IR) followed by 4 cycles of R-HCVAD for younger mantle cell lymphoma (MCL) patients (pts) demonstrating 90% CR on IR alone and we aimed to improve the CR rate with the addition of venetoclax. We therefore investigated the efficacy and safety of IR and venetoclax (IRV) followed by risk-stratified observation or short course R-HCVAD/MTX-ARA-C as consolidation in previously untreated young patients with mantle cell lymphoma (MCL). Our aim was to use a triplet chemotherapy-free induction to reduce the toxicity, complications and minimize chemotherapy exposure in MCL pts. Methods - We enrolled 50 previously untreated pts in this single institution, single arm, phase II clinical trial - NCT03710772. Pts received IR induction (Part-1) for initial 4 cycles. Pts were restaged at cycle 4 and received IRV for up to eight cycles (Cycle 5 to Cycle 12) starting with ramp up venetoclax dosing in Cycle 5. All pts who achieved CR prior to cycle 12 continued to receive IRV for 4 cycles (maximum 12 cycles) and then moved to part 2. Pts were stratified into three disease risk groups: high, moderate and low risk categories from the baseline data for assignment to R-HCVAD/MTX-ARA-C as consolidation in part 2 (4 cycles, 2 cycles, or no chemotherapy for high, medium and low risk pts respectively). Briefly, low risk pts were those with Ki-67 ≤30%, largest tumor mass <3 cm, low MIPI score and no features of high risk disease (Ki-67 ≥50%, mutations in the TP53, NSD2 or in NOTCH genes, complex karyotype or del17p, MYC positive, or largest tumor diameter >5 cm or blastoid/pleomorphic histology or if they remain in PR after 12 cycles of part 1. Medium risk are pts which did not belong to low or high-risk category. Those who experienced progression on part 1 went to part 2 and get 4 cycles of part 2. Patient were taken off protocol but not off study, if they remained in PR after 4 cycles of chemotherapy, these patients were followed up for time to next treatment and progression free survival on subsequent therapies. After part 2 consolidation, all pts received 2 years of IRV maintenance. The primary objective was to assess CR rates after IRV induction. Adverse events were coded as per CTCAE version 4. Molecular studies are being performed. Results - Among the 50 pts, the median age was 57 years (range - 35-65). There were 20 pts in high-risk group, 20 pts in intermediate-risk group and 10 pts in low-risk group. High Ki-67 (≥30%) in 18/50 (36%) pts. Eighteen (36%) had high and intermediate risk simplified MIPI scores. Six (12%) pts had aggressive MCL (blastoid/pleomorphic). Among the 24 TP53 evaluable pts, eight pts (33%) had TP53 aberrations (mutated and/or TP53 deletion by FISH). Forty-eight pts received IRV. Best response to IRV was 96% and CR of 92%. After part 2, the best ORR remained unaltered, 96% (92% CR and 4% PR). The median number of cycles of triplet IRV to reach best response was 8 cycles (range 2-12). Fifteen pts (30%) did not receive part 2 chemotherapy, two pts (4%) received 1 cycle, 16 pts (32%) 2 cycles and 13 pts (26%) got 4 cycles of chemotherapy. With a median follow up of 24 months, the median PFS and OS were not reached (2 year 92% and 90% respectively). The median PFS and OS was not reached and not significantly different in pts with high and low Ki-67% or with/without TP53 aberrations or among pts with low, medium or high-risk categories. The median PFS and OS was inferior in blastoid/pleomorphic MCL pts compared to classic MCL pts (p=0.01 and 0.03 respectively). Thirteen pts (26%) came off study - 5 for adverse events, 3 for on study deaths, and 2 for patient choice, 2 patients lost to follow up and one for disease progression. Overall, 5 pts died (3 on trial and 2 pts died off study, one due to progressive disease and another due to COVID pneumonia). Grade 3-4 toxicities on part 1 were 10% myelosuppression and 10% each with fatigue, myalgia and rashes and 3% mucositis. One pt developed grade 3 atrial flutter on part 1. None had grade 3-4 bleeding/bruising. Conclusions - Chemotherapy-free induction with IRV induced durable and deep responses in young MCL pts in the frontline setting. WINDOW-2 approach suggests that pts with low risk MCL do not need chemotherapy but further follow up is warranted. This combined modality treatment approach significantly improves outcomes of young MCL pts across all risk groups. Detailed molecular analyses will be reported. (Figure Presented).

15.
Acta Crystallographica a-Foundation and Advances ; 77:C705-C705, 2021.
Article in English | Web of Science | ID: covidwho-1762645
16.
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

17.
Journal of Health and Safety at Work ; 12(1):123-140, 2022.
Article in English, Persian | Scopus | ID: covidwho-1756010

ABSTRACT

Introduction: Covid-19 pandemic has imposed a significant effect on mental health of the health care workers. The present systematic review and meta-analysis aimed at determining the pooled prevalence of anxiety and depression among Iranian health care workers during the Covid-19 pandemic. Material and Methods: To conduct this systematic review and meta-analysis, Web of Science, Scopus, Medline (PubMed), Embase, SID, Magiran databases and Google Scholar search engine were investigated to find studies over the prevalence of anxiety and depression among health care workers during the Covid-19 pandemic from December 2019 to June 10, 2021. Quality of the primary studies was assessed using the Newcastle-Ottawa tool and the random effects model was applied to estimate the pooled prevalence. Furthermore, χ2 test and I2 index were used to evaluate the degree of heterogeneity among the studies. The pooled prevalence of anxiety and depression in different subgroups was reported based on the severity of anxiety and depression, assessment tools, and staff jobs. Results: Of 488 articles obtained as a result of the initial search, 10 related studies were identified and entered into the systematic review and meta-analysis. The pooled prevalence of anxiety was 42% (95% CI: 25-75) and the pooled prevalence of depression was 35% (95% CI: 19-55). The pooled prevalence of anxiety was 54% (95% CI: 39-70) in the occupational group of nurses and 29% (95% CI: 17-44) among all health care workers. The pooled prevalence of depression was 46% (95% CI: 30 to 63) and 17% (95% CI: 10 to 26) among nurses and all health workers, respectively. Conclusion: According to the findings, a high prevalence of anxiety and depression was observed among the health care workers of Iran during the Covid-19 epidemic. The authorities are required to plan for preventive and therapeutic interventions to reduce the psychological burden of the epidemic. © 2022 The Authors.

18.
Open Forum Infectious Diseases ; 8(SUPPL 1):S401-S402, 2021.
Article in English | EMBASE | ID: covidwho-1746407

ABSTRACT

Background. Telemedicine (TM) can provide specialty ID care for remote and underserved areas;however, the need for dedicated audio-visual equipment, secure and stable internet connectivity, and local staff to assist with the consultation has limited wider implementation of synchronous TM. ID e-consults (ID electronic consultations or asynchronous™) are an alternative but data are limited on their effectiveness, especially patient outcomes. Methods. In the setting of the COVID-19 pandemic and ID physician outage, we were asked to perform ID e-consults at a 380-bed tertiary care hospital located in Blair County, PA. We performed retrospective chart reviews of 121 patients initially evaluated by ID e-consults between April 2020 and July 2020. Follow-up visits were also conducted via e-consults with or without direct phone calls with the patient. Key patient outcomes assessed were length of stay (LOS), disposition after hospitalization, 30-day mortality from initial ID e-consult and 30-day readmission post-discharge. Results. The majority of patients were white males and non-ICU (Table 1). The most common ID diagnosis was bacteremia (27.3%, 33/121), followed by skin and soft tissue infections (15.7%, 19/121) and bone/joint infections (14.9%, 18/121) (Figure 1). Table 2 shows patient outcomes. Average total LOS was 11 days and 7 days post-initial ID e-consult. 48.7% (59/121) of patients were discharged home and 37.2% (45/121) to a post-acute rehabilitation facility. 2.5% (3/121) of patients required transfer to a higher level of care facility;none of which were to obtain in-person ID care. The index mortality rate was 3.3% (4/121), which appears to be lower than published data for in-person ID care. The 30-day mortality rate was 4.1% (5/121), which is also comparable to previously reported for ID e-consults. 25.6% (31/121) of patients required readmission within 30 days but only 14.0% (17/121) were related to the initial infection. Conclusion. We believe that this is the first report of the implementation of ID e-consults at a tertiary care hospital. Mortality rates appear to be comparable to in-person ID care. In the absence of in-person ID physicians, ID e-consults can be a reasonable substitute. Further study is required to compare performance of ID e-consults to in-person ID consults.

19.
Frontiers in Education ; 6:11, 2022.
Article in English | Web of Science | ID: covidwho-1745146

ABSTRACT

The lockdown control measures implemented against the pandemic of COVID-19 have had a global effect on various aspects of our lives as a society. Considering the impact of the lockdown caused by COVID-19 on adolescents, we conducted practical longitudinal research on the changes in adolescent satisfaction before and after lockdown. A total of 221 students aged 13-19 years from a professional adolescent football school in China participated in a self-report satisfaction questionnaire before and after the lockdown. The results showed that the satisfaction of adolescents improved significantly after the lockdown. There were significant differences based on age in the improvement rate, but the correlation between the students' home regions (and how they were affected by COVID-19) and satisfaction improvement was not significant. To examine the possible reasons behind the improvement in adolescent satisfaction, we then analyzed in detail the online teaching and training methods implemented by the school during the lockdown. Based on this investigation, we outlined recommendations to guide future practice. This research is expected to deepen the theory and practice associated with the development of Chinese adolescent teaching, which may be applied to other training institutions.

20.
Journal of the Hong Kong College of Cardiology ; 28(2):91, 2020.
Article in English | EMBASE | ID: covidwho-1743732

ABSTRACT

Objectives: Cardiac rehabilitation is the key component in optimizing physical function, reducing the cardiovascular risk and mortality for cardiac patients. However, as the coronavirus disease 2019 (COVID- 19) pandemic has begun since the end of 2019, usual service is affected. Patients' compliance and attendance to exercise training is worth concern and the general recommendation of 150-minute per week of moderate intensity exercise is almost unachievable. The limitation of routine health care delivery is explored. In order to increase patients' physical activity and prevent secondary complication, the Cardiac Society of Australia and New Zealand (CSANZ) recommended health care profession continued to deliver evidencedbased strategies with the use of electronic health platforms as it was more accessible during the pandemic. This study sought to examine the value of home virtual exercise in cardiac rehabilitation during COVID-19. Methods: Twenty-eight patients were recruited from the Cardiac Rehabilitation program (CRP) in Tseung Kwan O Hospital between December 2019 and August 2020. Patients who attended the CRP were under usual care receiving 1.5-hour center-based training 1-2 times per week. The home virtual exercise which was circuit training was given via QR code. All patients completed 12-sessions of CRP. Patients' safety, body weight and body mass index (BMI), 6 Minutes Walk Test (6MWT) distance, Five Times Sit To Stand (FTSTS) and Cardiac Exercise Self-Efficacy Instrument (CESEI) were measured at baseline and at end of 12th session. Results: No adverse events were reported in relation to home virtual exercise. Although there were no statistically changes in body weight and BMI (p>0.109), there were significant improvement in 6MWT distance (p=0.000), FTSTS (p=0.000) and CESEI (p=0.007). Conclusion: Home virtual exercise appears to be safe and effective for patients to exercise at home during COVID-19. Improvement in functional capacity and self-efficacy were observed, therefore, suggesting that home virtual exercise could be used in addition to center-based training to improve cardiovascular risk. Cardiac rehabilitation specialists should consider using electronic platforms during the pandemic to deliver exercise regimes. Future study is needed to explore the long-term effects of virtual exercise after program completion.

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