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In this study, a computer-assisted kidney stone diagnosis system based on CT images has been proposed. The method is based on a combination of deep training and metaheuristics. The method aims to provide a customized Deep Believe Network (DBN) based on a fractional version of the coronavirus herd immunity enhancer to provide an efficient and reliable kidney stone diagnosis system. The designed method is then authenticated by running a standard benchmark called a "CT kidney dataset". Subsequently, a comparison is made between the results and some other state-of-the-art methods. Simulations show that the recommended DBN/FO-CHIO outperforms the other studied approaches in terms of efficiency with an accuracy of 97.98%. Moreover, the proposed DBN/FO-CHIO recall outperforms others with 92.99%, demonstrating its excellent accuracy compared to other comparison algorithms. Moreover, the higher specificity of the proposed method compared to the other evaluated approaches indicates its advanced event-independent value.Copyright © 2023 Elsevier Ltd
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Introduction: COVID-19 infection has been associated with right ventricular (RV) dysfunction and poor prognosis. This association is thought to be due to either a direct effect of COVID-19 infection on the myocardium or indirect damage to the lung parenchyma or vasculature. Limited echocardiography protocols for operator protection against COVID-19 has made the evaluation of the RV challenging. The purpose of this study is to evaluate if RV dysfunction by qualitative assessment can be used to predict all-cause mortality. Method(s): This is a single-center retrospective analysis from March 2020 to August 2021. Patients who were older than 18 years old, hospitalized with a positive RT-PCR for COVID-19, and had an echocardiogram while inpatient were included in the study. RV parameters, including RV dilation and dysfunction, were obtained by qualitative assessment. Data analysis was performed with STATA and SPSS. Result(s): A total of 223 patients were included in the analysis. 59.6% were male with a mean age of 64.3 years (SD +/- 16). 67.7% were Hispanic, 11.7% were non-Hispanic White, and 20.6% were Black. Severe COVID-19 infection requiring intensive care unit level of care made up 54.7% of cases (n=122) and the mortality rate was 27.8% (n=62). RV dysfunction and dilation was present in 13.5% (n=28) and 15.2% (n=33) of patients, respectively and occurred more often in patients with severe COVID-19 infection (p<0.01). Logistic binomial correlation showed an exponential increase in the probability of mortality related to RV dysfunction (OR 2.03, p=0.270;graph 1) and a mild decrease in mortality in patients with RV dilation (OR 0.88, p=0.794). However, both associations were not statistically significant. Conclusion(s): RV dysfunction by qualitative assessment could be a potential marker of mortality in patients with COVID-19 infection. The association may be stronger in studies with more power. Interestingly, RV dilation was associated with a mild decrease in mortality in this patient population;however, this may be a biased result due to the small sample size.Copyright © 2022
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The rage of the COVID-19 pandemic, coupled with the downward trend seen in the economy, has further aggravated the downturn of the job market and diminished people's sense of wellbeing in recent years. To mitigate the detrimental effects of the pandemic on college students' employment, the Chinese government has further expanded the enrollment of postgraduate and undergraduate students. This study leverages data from the 2019 and 2021 waves of the Chinese Social Survey and constructs a difference-in-differences (DID) model to examine the effect of the higher education expansion (HEE) policy, initiated in 1999, on individuals' subjective well-being during the COVID-19 pandemic. The results show that HEE policy could significantly improve individuals' subjective well-being (SWB) during the pandemic, and that social class mobility emerges as a vital mechanism through which HEE policy impacts individuals' SWB. Furthermore, there is a local-ladder effect due to reference dependence, with socio-metric status having a greater impact on SWB than socioeconomic status. This study reveals that the level of an individual's happiness depends largely on whom they are compared with. This implies that the key focus of the HEE policy is to stimulate individuals' potential and motivation for upward social mobility, ultimately enhancing their overall sense of well-being. © 2023 by the authors.
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Since the outbreak of Corona Virus Disease 2019 occurred in December 2019, the reduction of population mobility has curbed the spread of the epidemic to some extent but also prolonged the waiting time for the treatment of patients with gastric cancer. Based on fully understanding the different staging characteristics of gastric cancer, clinical departments should develop reasonable out-of-hospital management strategies. On one hand, reasonable communication channels should be established to allow patients to receive adequate guidance out of the hospital. On the other hand, shared decisions with patients should be made to adjust treatment strategies, and education on viral prevention should be implemented to minimize the impact of the epidemic on tumor treatment.Copyright © 2020 by the Chinese Medical Association.
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Background: Approximately 30% to 50% of breast cancer patients experienced mental distress prior to the advent of COVID.The delayed access to cancer treatment due to the outbreak of COVID -19 pandemic posed a unique challenge to breast cancer patients and caused a significant level of mental distress among them. In the current research, we examined the psychological impacts of COVID on breast cancer patients in China using Symptom Checklist-90-R (SCL-90-R). Method(s): Participants were breast cancer patients at the outpatient clinic of Xijing hospital. The study was conducted virtually, and the questionnaires were distributed via Wenjuanxing, the Chinese alternative of Qualtrics. The researchers were healthcare workers affiliated with Xijing hospital, and the survey was sent to a breast cancer patient support group which included 1399 cancer patients and 6 healthcare workers. The initial sample consisted of 199 participants who signed an informed consent form to participate in the study. The inclusion criteria were as follows: 1) diagnosed with breast cancer, 2) aged 18 years or above, and 3) had no history of cognitive impairment or previous diagnosis of psychiatric disorders. The validated Mandarin version of the SCL-90-R (Wang, 1984) was then given to the participants to evaluate their psychological status.Categorical variables were summarized as numbers and percentages;continuous variables were described as mean (M) +/- standard deviation (SD). Data were analyzed using IBM SPSS Statistics Version 26. Result(s): Participants (N = 195) filled out the SCL-90 questionnaire in February, 2020. All participants were female breast cancer patients treated at Xijing hospital, among which 16.41%, 36.41%, 19.49%, and 28.21% had respectively received treatment for less than a year, 1-3 years, 3-5 years, and 5 years or more. 64.62% of the patients were at stage I;0.77% were at stage II and III;4.62% were at stage IV according to TNM classification. The molecular type of participants is as follows: 47.2% of ER+ HER2-, 31.8% of HER2+, and 21.0% of Triple negative.Participants whose treatments continued to be delayed, on average, reported an elevated general psychopathology score (M = 1.48, SD = 0.47) compared to participants whose treatments were resumed (M = 1.30, SD = 0.34), and the difference was statistically significant, t(193) = 2.96, p = .003, d = 0.44, 95%Cl [0.06, 0.30]. The one-way ANOVA revealed a marginally significant effect of length of treatment delay on general psychopathology score, F(4, 190) = 2.09, p = .08, eta2 = .04. Follow-up multiple comparison analysis showed that participants who had their treatment delayed for 3 weeks to 1 month (M = 1.70, SD = 0.70) reported significantly higher general psychopathology scores than participants whose delay in treatment was less than 1 week (M = 1.34, SD = 0.40), p = .05. General health status (p < .001) and current treatment status (p = .02) are the only two variables that were statistically associated with general psychopathology score.Poorer perceived health status and current delay in treatment were associated with higher general psychopathology score, Additionally, younger age was associated with higher interpersonal sensitivity (p = .01) and hostility (p = .006). Conclusion(s): We found that breast cancer patients at an advanced stage were more likely to experience psychological symptoms with longer treatment delay, and whose treatments continued to be delayed reported elevated psychological symptoms than individuals whose treatment were resumed, regardless of treatment type. Additionally, a treatment delay of more than three weeks might have exacerbated breast cancer patients' psychological symptoms, whereas a short-term delay of less than three weeks was less likely to have a significant effect on one's mental wellbeing.
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The COVID-19 pandemic has been the world's greatest challenge since World War II. As an unprecedented global public health crisis, crisis management teams (CMTs) in the infected countries need to rethink to cope with the similar uncertainty and urgency of the ongoing COVID-19 pandemic. The shared context of COVID-19 allows us to explore a cross-nation study of different constructs and CMT to communicate information about crises with the public effectively. Since the pandemic affected all countries, the comparison is warranted. Can CMTs mitigate the effects of COVID-19? Based on the analysis of China and the US cases, our study explores how shared and common knowledge cognition among crisis responders plays a pivotal role in effective CMTs' communication while technological failures and inadequate information disrupt the system, worsening pandemics like COVID-19. Furthermore, organizational dysfunction, such as institutional fragmentation, regulatory hurdles and bureaucratic arrogance, impede effective communication between CMTs. However, effective coordination and decisive leadership could improve coordination effectiveness and reduce crisis costs. © 2023 John Wiley & Sons Ltd.
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The COVID pandemic has caused tremendous loss worldwide. Now vaccines are the primary weapon to combat the pandemic. Understanding how SARS-CoV-2, the virus that causes the COVID, may mutate in the presence of the vaccines is critical for designing drugs and vaccines for future variants of the virus. In this study, we investigated the numbers of mutations that SARS-CoV-2 accumulated on each protein over time. We found that different proteins of the virus accumulated different levels of mutations and their mutation rates changed over time following different patterns. We also presented evidence that the mutation of the Spike protein might have been suppressed by the vaccines. This is the first time that such a relation was reported based on real world data. Although the discovery was not meant to be conclusive, this study sheds light onto how the virus may response to the vaccines. If confirmed by further studies, the discovery will have significant impacts on many fields, including drug and vaccine designs. © 2022 IEEE.
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Sharing individual-level pandemic data is essential for accelerating the understanding of a disease. For example, COVID-19 data have been widely collected to support public health surveillance and research. In the United States, these data need to be de-identified before being released to the public due to privacy concerns. However, current data publishing approaches for individual-level pandemic data, such as those adopted by the U.S. Centers for Disease Control and Prevention (CDC), have not flexed over time to account for the dynamic nature of infection rates. Thus, the policies generated by these strategies may either raise privacy risks or impair the data utility (or usability). To optimize the tradeoff between privacy risk and data utility, we introduce a game theoretic model that adaptively generates policies to publish individual-level COVID-19 data according to infection dynamics. We model the data publishing process as a two-player Stackelberg game between a data publisher and a data recipient and then search for the best strategy for the publisher. In this game, we consider 1) the average accuracy of predicting future case counts for all demographic groups, and 2) the mutual information between the original data and the released data. We use COVID-19 case data from Vanderbilt University Medical Center from March 2020 to December 2021 to demonstrate our model and evaluate its effectiveness. The experimental results show that our game theoretic model outperforms all baseline approaches, including those adopted by CDC, while maintaining low privacy risk. © 2022 IEEE.
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The COVID pandemic has caused tremendous loss worldwide. Now vaccines are the primary weapon to combat the pandemic. Understanding how SARS-CoV-2, the virus that causes the COVID, may mutate in the presence of the vaccines is critical for designing drugs and vaccines for future variants of the virus. In this study, we investigated the numbers of mutations that SARS-CoV-2 accumulated on each protein over time. We found that different proteins of the virus accumulated different levels of mutations and their mutation rates changed over time following different patterns. We also presented evidence that the mutation of the Spike protein might have been suppressed by the vaccines. This is the first time that such a relation was reported based on real world data. Although the discovery was not meant to be conclusive, this study sheds light onto how the virus may response to the vaccines. If confirmed by further studies, the discovery will have significant impacts on many fields, including drug and vaccine designs. © 2022 IEEE.
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Overlap between the histopathologic changes of acute rejection and viral myocarditis presents a diagnostic dilemma. A 34 year-old female with a past medical history of postpartum cardiomyopathy and subsequent orthotopic heart transplant in December 2019, presented for routine surveillance heart biopsy seven months post-transplant. Her AlloMap was elevated and AlloSure was uptrending, concerning for rejection. Ten days prior to presentation, she tested positive for COVID-19 via polymerase chain reaction (PCR) testing. Her symptoms were fatigue and mild headache for two weeks prior to diagnosis. She did not seek medical attention for her symptoms and received no COVID-19 specific treatment. Endomyocardial biopsy showed grade 2R acute cellular rejection. Her echocardiogram was unchanged with normal left ventricular ejection fraction and right ventricular function. SARS-CoV-2 levels were measured by PCR of ribonucleic acid (RNA) isolated from the biopsy specimen and were undetectable. The patient was treated with two short courses of high dose prednisone which eventually abated her transplant rejection. The patient remained positive on PCR testing for COVID-19 for the next six months. Chest x-ray and computed tomography for follow up after COVID-19 infection showed no evidence of pulmonary fibrosis or superinfection considering ongoing immunosuppression for rejection. Our patient illustrates a case of concomitant COVID-19 infection and presumed transplant rejection, raising the question of whether the findings seen on immunohistochemistry were truly rejection or instead an elevated immune response due to COVID-19 infection. Given that our patient had a predominance of CD3+ T cells and less CD68+ macrophages (the former being more prominent in acute cellular rejection and the latter being more prominent in COVID-19 myocarditis), we are inclined to believe the former. (Figure Presented).
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INTRODUCTION: Dynamic monitoring of D-dimer levels is a prognostic tool used for patients with COVID-19 and higher levels are associated with increased mortality. However, optimal D-dimer cutoff models for ARDS have not been previously evaluated. We aimed to determine the optimal D-dimer level for the prediction of ARDS in patients admitted with COVID-19. METHOD(S): We conducted a two-center retrospective study of 502 adult patients hospitalized between 2020 and 2021 with confirmed COVID-19 infection. The D-dimer on admission and peak value during hospitalization were obtained. Differences between groups were determined by one-way ANOVA, Wilcoxon rank-sum, or Fisher exact test. The cutoff D-dimer level and the C-index were obtained using the receiver operating curve (ROC). Univariate and multivariate regression models were used. Statistical analyses were performed using SPSS 28. RESULT(S): The mean age was 65+/-15 and 58.4% (294/502) were males. ARDS developed in 51.3% (258/502) of the patients, and 30.5% (153/502) died. Elevated D-Dimer (>0.5 ug/mL) was present on admission in 84% (423/502) of all patients. Patients who developed ARDS had higher peak (median 3.54 ug/mL, p< 0.001) and admission (median 1.5 ug/mL, p=0.005) D-dimer levels. D-dimer level of >3.05 ug/ ml predicted ARDS with a sensitivity of 71%, specificity of 67% and C-index 0.723 (p=0.001, CI 0.68-0.77). The C-index for D-dimer on admission was 0.59 (p=0.001, CI 0.54-64). Using the peak D-dimer level of 3.05 ug/mL, unadjusted logistic regression models showed a statistically significant effect on ARDS (p< 0.001, OR 4.62, CI 3.12-6.83). This effect persisted after adjusting for other variables (p< 0.001, OR 3.81, CI 2.51-5.79). CONCLUSION(S): Peak D-dimer level during hospitalization with a cutoff of 3.05 ug/mL is a useful tool to predict ARDS in patients admitted with COVID-19. Dynamic monitoring of D-dimer is an adequate and objective measurement during hospitalization for assessment of deterioration. Further studies with better-controlled monitoring on the timeframe of obtaining D-dimer are needed to further evaluate this threshold.
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Introduction: Left ventricular hypertrophy (LVH) is a risk factor for adverse cardiovascular outcomes such as heart failure and arrhythmia. LVH is characterized by increased left ventricular mass with myocardial fibrosis and may contribute to COVID-19-induced cardiac injury. Hypothesis: LVH is a predictor of poor outcomes in patients with COVID-19. Method(s): We conducted a two-center retrospective study of 415 adult patients hospitalized with COVID-19 from March 2020 to September 2021 who had an echocardiogram performed while inpatient. Baseline characteristics, biomarkers, and hospitalization outcomes were described. LVH was diagnosed by linear measurements with echocardiography. Statistical analyses were performed using SAS 9.4 and SPSS 28. Differences between groups were determined by one-way ANOVA, Wilcoxon rank-sum, or Fisher exact test. Result(s): LVH was present in 34.2% (142/415) of patients. Compared to those without LVH, those with LVH were older (64 vs 68 years, p=0.02), heavier (84.4 vs 89.6 kg, p=0.03), and more likely to be diabetic (39.6% vs 50.0%, p=0.04), hypertensive (61.5% vs 71.8%, p=0.04), and smokers (5.1% vs 12.0%, p=0.02). NT-proBNP (1342 vs 721, p=0.02) and peak troponin I (0.03 vs 0.01, p=0.002) levels were higher in the LVH group. The LVH group had increased rates of myocardial infarction (7% vs 4%), new-onset heart failure (8.5% vs 7.3%), and mortality (35.9% vs 30%), although these findings were not statistically significant. Similarly, logistic regression models showed a sustained effect of age (OR 1.17 [CI 1.02-1.34], for every 10 years), diabetes (OR 1.53 [CI 1.02-2.29]), hypertension (OR 1.59 [CI 1.03-2.4]), and smoking (OR 2.52 [CI 1.2-5.3]) in patients with LVH;however, there was no difference between groups for all outcomes measured. Conclusion(s): LVH was significantly associated with other cardiovascular risk factors and increased cardiac biomarkers, suggesting a higher degree of cardiac injury in LVH patients with COVID-19. Although there was a higher rate of cardiovascular events and mortality in patients with LVH, these findings were not statistically significant. Studies with a larger sample size are needed to determine whether LVH is an independent predictor of COVID-19-induced cardiac injury.
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SESSION TITLE: Studies on COVID-19 Infections Posters SESSION TYPE: Original Investigation Posters PRESENTED ON: 10/18/2022 01:30 pm - 02:30 pm PURPOSE: COVID-19 associated morbidity and mortality are largely related to hypercoagulability events, including deep vein thrombosis (DVT) and pulmonary embolism (PE), with right ventricular (RV) dysfunction playing a likely role in the severity of outcomes. The purpose of this study is to correlate right ventricular parameters on echocardiography in patients who developed DVT and PE while admitted with COVID-19 infection, and to determine if PE and DVT were related to a higher incidence of adverse outcomes. METHODS: Single-center retrospective study from March 2020 to August 2021 including patients older than 18 years old hospitalized with confirmed COVID-19 by RT-PCR, who had an echocardiogram performed while inpatient. Right ventricular parameters were obtained mostly by linear measurements, with a limited COVID-19 protocol determined by the institution. The presence of PE and DVT were confirmed by chest CT angiography and venous ultrasound, respectively. RESULTS: A total of 223 patients were included in the study (mean age 64.3 +/- 16, 59.6% male, 67.4% Hispanic). Baseline characteristics did not differ when stratified for the outcomes of interest. DVT occurred in 9.4% (n=21) and PE in 19.6% (n=44) patients. PE and DVT were related to a higher rate of ARDS, ICU admission, non-fatal stroke and prolonged length of stay (38.9 vs 16.9 days, p<0.05). Although there was a higher rate of intubation in patients admitted with DVT (p<0.05), it was non-significant for patients with PE. Mortality was similar to patients without thromboembolic events. For PE and DVT, RV dilation was present on 25% (p<0.05) and 14%, and RV dysfunction on 21% and 11%, respectively. CONCLUSIONS: PE and DVT in patients with COVID-19 were related to higher morbidity, but not mortality in this patient population. Interestingly, these events were related to a higher rate of non-fatal stroke, suggesting that hypercoagulability plays a major role in the development of some adverse outcomes. Despite only finding RV dilation as a statistically significant marker present in patients who developed PE, the study was potentially underpowered to find significant differences between groups. CLINICAL IMPLICATIONS: Development of PE and DVT in patients admitted with COVID-19 infection are markers of increased morbidity and higher length of stay. RV dilation might be used as a marker of potential thromboembolic events in this patient population, but more studies with controlled variables are needed to determine it's utility. DISCLOSURES: No relevant relationships by Sharon Andrade-Bucknor No relevant relationships by Mikayla Bowen No relevant relationships by Alexis Jones No relevant relationships by Sukhpreet Kaur No relevant relationships by Neal Olarte No relevant relationships by Beatriz Rivera Rodriguez No relevant relationships by Crystal Yan
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SESSION TITLE: Pulmonary Manifestations of Infections SESSION TYPE: Case Reports PRESENTED ON: 10/17/2022 03:15 pm - 04:15 pm INTRODUCTION: Post-acute COVID-19 inflammatory syndrome is defined as persistent symptoms and/or delayed or long-term complications beyond 4 weeks from the onset of symptoms of original infection (1). These can manifest in various ways, but pulmonary, cardiac, and renal complications are the most common (1), with IL-6 thought to be an important mediator (2). We report what we believe to be the first case of Idiopathic Multicentric Castleman's Disease (iMCD) as a manifestation of post-acute COVID-19 inflammatory syndrome. CASE PRESENTATION: A 36-year old male with history of hypertension and childhood asthma (not on current therapy), and recently resolved COVID-19 from 4 weeks prior, is admitted to the hospital with progressive shortness of breath, cough, fevers and significant fatigue. Prior COVID-19 symptoms included fevers, cough, and shortness of breath, which improved after 2 weeks without treatment. Symptoms returned 2 weeks later and worsened. On admission, he was tachycardic to 108 with temp of 37.8C, and otherwise stable vitals. Pertinent labs included WBC 17 (neutrophil predominant), Hgb 11.6, Cr 2.52, Na 126 and albumin 2.7 (normal baselines). SARS-CoV2 PCR was negative. CT chest with PE protocol showed no PE but moderate bilateral pleural effusions and extensive mediastinal lymphadenopathy. 1.2L clear fluid (transudative with lymphocyte predominance) was removed via thoracentesis. Microbiology, flow cytometry and cytology were unremarkable. Renal and mediastinal lymph node biopsies were taken. Lymph node sampling was non-diagnostic x2, but renal biopsy showed acute microangiopathy without thrombi, concerning for acute glomerulonephritis. Serologic vasculitis and CTD workup were entirely negative. He was treated with a course of prednisone and improved, however as outpatient, had recurrence of all these issues. Repeat thoracentesis x3 was unrevealing. He was again admitted and had an excisional inguinal node biopsy, showing findings consistent with hyaline vascular Castleman Disease. Further heme/onc evaluation and discussion showed diagnosis meeting criteria for iMCD. DISCUSSION: Multicentric Castleman's Disease is most often associated with HHV-8 infection in the setting of HIV. If HHV-8 is negative, the disease is termed idiopathic (iMCD). In these cases, disease is mediated predominantly by IL-6, but the direct cause is unknown, though existing theories include non-specific viral infections, malignancy and autoimmune diseases (3). Our patient had no evidence of malignancy or autoimmune phenomena. Thus COVID-19 illness was the most plausible explanation, especially given known IL-6 activity in COVID-19 inflammatory syndromes. CONCLUSIONS: Post-acute COVID-19 inflammatory syndromes are extensive and can affect any organ system. iMCD is another possible manifestation, and must be diagnosed with excisional lymph node biopsy. High index of suspicion should be maintained to make this diagnosis. Reference #1: Nalbandian, Ani et al. "Post-acute COVID-19 syndrome." Nature medicine vol. 27,4 (2021): 601-615. Reference #2: Phetsouphanh, Chansavath et al. "Immunological dysfunction persists for 8 months following initial mild-to-moderate SARS-CoV-2 infection.” Nature immunology vol. 23,2 (2022): 210-216. Reference #3: Dispenzieri, Angela, and David C Fajgenbaum. "Overview of Castleman disease." Blood vol. 135,16 (2020): 1353-1364. DISCLOSURES: No relevant relationships by Kyle Halligan No relevant relationships by Chris Yan
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The COVID-19 pandemic highlights the need for broad dissemination of case surveillance data. Local and global public health agencies have initiated efforts to do so, but there remains limited data available, due in part to concerns over privacy. As a result, current COVID-19 case surveillance data sharing policies are based on strong adversarial assumptions, such as the expectation that an attacker can readily re-identify individuals based on their distinguishability in a dataset. There are various re-identification risk measures to account for adversarial capabilities;however, the current array insufficiently accounts for real world data challenges - particularly issues of missing records in resources of identifiable records that adversaries may rely upon to execute attacks (e.g., 10 50-year-old male in the de-identified dataset vs. 5 50-year-old male in the identified dataset). In this paper, we introduce several approaches to amend such risk measures and assess re-identification risk in light of how an attacker’s capabilities relate to missing records. We demonstrate the potential for these measures through a record linkage attack using COVID-19 case surveillance data and voter registration records in the state of Florida. Our findings demonstrate that adversarial assumptions, as realized in a risk measure, can dramatically affect re-identification risk estimation. Notably, we show that the re-identification risk is likely to be substantially smaller than the typical risk thresholds, which suggests that more detailed data could be shared publicly than is currently the case. © 2022, Springer Nature Switzerland AG.
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BACKGROUND: Olfactory dysfunction is a cardinal symptom of COVID-19 infection, however, studies assessing long-term olfactory dysfunction are limited and no randomised-controlled trials (RCTs) of early olfactory training have been conducted. METHODOLOGY: We conducted a prospective, multi-centre study consisting of baseline psychophysical measurements of smell and taste function. Eligible participants were further recruited into a 12-week RCT of olfactory training versus control (safety information). Patient-reported outcomes were measured using an electronic survey and BSIT at baseline and 12 weeks. An additional 1-year follow-up was open to all participants. RESULTS: 218 individuals with a sudden loss of sense of smell of at least 4-weeks were recruited. Psychophysical smell loss was observed in only 32.1%; 63 participants were recruited into the RCT. The absolute difference in BSIT improvement after 12 weeks was 0.45 higher in the intervention arm. 76 participants completed 1-year follow-up; 10/19 (52.6%) of participants with an abnormal baseline BSIT test scored below the normal threshold at 1-year, and 24/29 (82.8%) had persistent parosmia. CONCLUSIONS: Early olfactory training may be helpful, although our findings are inconclusive. Notably, a number of individuals who completed the 1-year assessment had persistent smell loss and parosmia at 1-year. As such, both should be considered important entities of long-Covid and further studies to improve management are highly warranted.
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The Movement Control Order (MCO) currently in effect in Malaysia was imposed in order to control the spread of the COVID-19 virus. This unfortunate circumstance has resulted in dramatic teaching and learning pedagogy shifts from traditional physical classes to online learning, including practical sessions. Therefore, this study aims to identify the Malaysian physiotherapy students' perceptions of e-practical education in achieving learning outcomes. In this cross-sectional study, 409 physiotherapy students from Malaysian universities participated voluntarily in the online Google Form survey, which was circulated through social media platforms from August 2021 to October 2021. Data were analyzed using IBM SPSS version 26.0 software. The results of the study demonstrate that students preferred traditional classes in comparison to online practical sessions in achieving the learning outcome of practical skills (p<.0.000) and social competencies (p<.0.000). Moreover, their activity level was also higher in physical classes (p<0.000). In a comparison of online and traditional practical (face-to-face) classes, the majority of students voted gaining theoretical knowledge as neutral or slightly effective but slightly ineffective in improving practical skills. Students felt that more hands-on practice through face-to-face classes would enhance the attainment of the learning outcome. In future, therefore, educational institutions can consider introducing other forms of interactive online mediums to simulate physical classes. © 2022 Society for Research and Knowledge Management. All rights reserved.
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Atmospheric aerosols have significant effects on the climate and on human health. New particle formation (NPF) is globally an important source of aerosols but its relevance especially towards aerosol mass loadings in highly polluted regions is still controversial. In addition, uncertainties remain regarding the processes leading to severe pollution episodes, concerning e.g. the role of atmospheric transport. In this study, we utilize air mass history analysis in combination with different fields related to the intensity of anthropogenic emissions in order to calculate air mass exposure to anthropogenic emissions (AME) prior to their arrival at Beijing, China. The AME is used as a semi-quantitative metric for describing the effect of air mass history on the potential for aerosol formation. We show that NPF events occur in clean air masses, described by low AME. However, increasing AME seems to be required for substantial growth of nucleation mode (diameter < 30 nm) particles, originating either from NPF or direct emissions, into larger mass-relevant sizes. This finding assists in establishing and understanding the connection between small nucleation mode particles, secondary aerosol formation and the development of pollution episodes. We further use the AME, in combination with basic meteorological variables, for developing a simple and easy-to-apply regression model to predict aerosol volume and mass concentrations. Since the model directly only accounts for changes in meteorological conditions, it can also be used to estimate the influence of emission changes on pollution levels. We apply the developed model to briefly investigate the effects of the COVID-19 lockdown on PM2.5 concentrations in Beijing. While no clear influence directly attributable to the lockdown measures is found, the results are in line with other studies utilizing more widely applied approaches.