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1.
JMIR Hum Factors ; 9(4): e41499, 2022 Nov 04.
Article in English | MEDLINE | ID: covidwho-2109574

ABSTRACT

BACKGROUND: Due to the upsurge of COVID-19, nations are increasingly adopting telemedicine programs in anticipation of similar crises. Similar to all nations worldwide, Jordan is implementing efforts to adopt such technologies, yet it is far from complete. OBJECTIVE: This study aims to assess the knowledge, attitudes, and perceptions of Jordanians toward telemedicine, to identify key factors predisposing individuals to its use or acting as barriers to its implementation. METHODS: We implemented a cross-sectional design using an online, self-administered questionnaire executed in Google Forms and distributed through social media. Differences in knowledge and attitude scores were examined using independent sample t tests and ANOVA. A multivariate linear regression model was computed to assess predictors of awareness toward telemedicine. RESULTS: A total of 1201 participants fully completed the questionnaire. Participants were characterized by a mean age of 36.3 (SD 14.4) years and a male-to-female ratio of nearly 1:1. About 50% (619/1201, 51.5%) of our studied population were aware of telemedicine, while nearly 25% (299/1201, 24.9%) declared they had observed it in action. Approximatively 68% (814/1201, 67.8%) of respondents were willing to use telemedicine. The majority of the sample portrayed favorable and positive views toward telemedicine. Higher educational degrees, living in urban districts, and having a higher perception of electronic usage ability were associated with higher knowledge and better attitudes toward telemedicine (all P<.05). The multivariate linear regression analysis demonstrated that perceived ability to use electronics was associated with positive attitudes (ß=0.394; 95% CI 0.224 to 0.563), while living in Southern Jordan predicted poor attitudes toward telemedicine (ß=-2.896; 95% CI -4.873 to -0.919). CONCLUSIONS: Jordanians portray favorable perceptions of telemedicine. Nonetheless, concerns with regards to privacy, medical errors, and capacity for accurate diagnoses are prevalent. Furthermore, Jordanians believe that integrating telemedicine within the health care system is not applicable due to limited resources.

2.
Pharmaceuticals (Basel) ; 15(11)2022 Oct 28.
Article in English | MEDLINE | ID: covidwho-2090304

ABSTRACT

SARS-CoV-2 is a positive single-strand RNA-based macromolecule that has caused the death of more than 6.3 million people since June 2022. Moreover, by disturbing global supply chains through lockdowns, the virus has indirectly caused devastating damage to the global economy. It is vital to design and develop drugs for this virus and its various variants. In this paper, we developed an in silico study-based hybrid framework to repurpose existing therapeutic agents in finding drug-like bioactive molecules that would cure COVID-19. In the first step, a total of 133 drug-likeness bioactive molecules are retrieved from the ChEMBL database against SARS coronavirus 3CL Protease. Based on the standard IC50, the dataset is divided into three classes: active, inactive, and intermediate. Our comparative analysis demonstrated that the proposed Extra Tree Regressor (ETR)-based QSAR model has improved prediction results related to the bioactivity of chemical compounds as compared to Gradient Boosting-, XGBoost-, Support Vector-, Decision Tree-, and Random Forest-based regressor models. ADMET analysis is carried out to identify thirteen bioactive molecules with the ChEMBL IDs 187460, 190743, 222234, 222628, 222735, 222769, 222840, 222893, 225515, 358279, 363535, 365134, and 426898. These molecules are highly suitable drug candidates for SARS-CoV-2 3CL Protease. In the next step, the efficacy of the bioactive molecules is computed in terms of binding affinity using molecular docking, and then six bioactive molecules are shortlisted, with the ChEMBL IDs 187460, 222769, 225515, 358279, 363535, and 365134. These molecules can be suitable drug candidates for SARS-CoV-2. It is anticipated that the pharmacologist and/or drug manufacturer would further investigate these six molecules to find suitable drug candidates for SARS-CoV-2. They can adopt these promising compounds for their downstream drug development stages.

3.
Environmental and Sustainability Indicators ; : 100209, 2022.
Article in English | ScienceDirect | ID: covidwho-2083186

ABSTRACT

In recent years, it became clear that the human unsustainable behaviours’ impact on the environment. Environment protected behavior is especially relevant in the context of the current epidemiological situation ushered by the COVID-19. Environmental awareness is becoming a part of everyday life. The time has come when it is necessary to sacrifice the comfort for the future of the planet. This study primarily focuses on the attitudes of residents of a typical Russian industrial city towards environmental issues and the use of the Energy-Saving Behavior Index (ESBI) as an environmental indicator of sustainable behavior. Our work investigates ESBI and the factors which are associated with domestic energy-saving behavior. We surveyed 599 people in Chelyabinsk, Russia. We studied (1) the socio-demographic factors of residents and their households, (2) mental health and subjective well-being (SWB), and (3) physical health. The study showed that the overwhelming majority of residents of a typical Russian city are extremely dissatisfied with the state of the environment (more than 80% of respondents) and 70% of them believe that they can contribute to improving the situation. However, Russians are still wasteful in household energy consumption. It has been shown that unstable behavior is due to psychological factors and has a compensatory mechanism that is connected with the “feelings-emotions-behavior” sequence.

4.
3rd International Conference on Information Science, Parallel and Distributed Systems, ISPDS 2022 ; : 116-121, 2022.
Article in English | Scopus | ID: covidwho-2063273

ABSTRACT

Omicron BA.2, a new variant of severe acute respiratory syndrome coronavirus (SARS-CoV-2), has attracted worldwide attention due to its high infectivity and vaccine escape mutation. Based on the SEIR model being susceptible to changes in external factors and having specific errors, the ARIMA model is data-dependent and can only capture linear relationships. In this paper, based on the traditional infectious disease dynamic model SEIR and the differential integrated mean autoregressive model ARIMA, an SEIR-ARIMA mixed model is proposed to predict and evaluate the virus outbreak in March in Jilin Province, China. The data from SEIR and ARIMA models were processed using SPSS to obtain the predicted values f and e, respectively. Linear regression modeling was performed on the predicted values f and e to establish the SEIR-ARIMA model. MATLAB is used to complete the best linear fitting line. Furthermore, The results show that the model's predicted value is in good agreement with the actual value. It shows that the SEIR-ARIMA mixed model based on the SEIR-ARIMA model has a good prediction effect, which is beneficial for the country to make the right decision when facing the epidemic. It is of great value for preventing other types of infectious diseases in China in the future. © 2022 IEEE.

5.
Journal of Pediatric Gastroenterology and Nutrition ; 75(Supplement 1):S155-S156, 2022.
Article in English | EMBASE | ID: covidwho-2057941

ABSTRACT

BACKGROUND: Electronic health record systems (EHRs) represent one of the most widely adopted digital healthcare technologies in the past decade. Among the potential benefits of EHRs has been the quantification of individual physician time spent performing key components of clinical workload. Epic EHR is a global system with the majority market share in North American acute care and ambulatory arenas and may offer a means to quantify the clinical workload of pediatric gastroenterology, as a subspecialty field of medicine. OBJECTIVE(S): To quantify clinical workload of pediatric gastroenterology across Epic EHR systems. METHOD(S): From January 2020 through April 2022, we evaluated Signal EHR data captured in Epic for all pediatric gastroenterologists (PGI), defined as physicians (MDs) with an Epic specified PGI profile. Signal data provides detailed data on clinician time spent daily (defined by days where a MD was clinically active or logged into the EHR) interfacing with the EHR, including clinical work process data in 4 key areas: In-Basket (including communications with patients and other healthcare providers), Orders, Notes and Letters, and Clinical Review. For our study purposes, clinical workload was characterized by 4 monthly metrics: days with appointments;appointments per scheduled day (data from April-July 2020 during COVID-19 lockdown were not included to accurately reflect current practice);pajama EHR time (5:30 PM to 7 AM);and EHR time outside templated clinic hours. Proportional time spent in different clinical arenas was reported for April 2022 only. Monthly process metrics captured in each of the 4 key areas focused on work volume and time spent. Outcome metrics were reported as average+/-standard deviation (SD) and median (interquartile range (IQR)). All metrics were evaluated for change over time using regression modeling. Statistical significance was set at p<0.05. RESULT(S): Signal data from 993 PGI at 213 institutions were analyzed. 95.8% (n=204) institutions were located in the US. Clinical workload Over the reporting period, PGI had clinical appointments an average of 43+/-3% [median (IQR) = 46% (35%, 57%)] days per month or about 3 days per week. PGI had 7.6+/-0.3 [7.0 (5.8, 8.9)] clinical appointments per scheduled day. On average, PGI spent an additional 23.7+/-1.6 [14.4 (4.6, 30.2)] pajama time minutes and 36.1+/-1.9 [30.3 (15.8, 43.3)] minutes outside scheduled hours interacting with the EHR each day. Clinical workload metrics remained stable over the study period. On average, PGI spent 60% time in the ambulatory arena, 9.7% in inpatient, 0.3% in the emergency department and 30% in other. In-Basket The average time spent in In-Basket by PGI was 23.0+/-1.3 [20.4 (13.2, 26.5)] minutes per day. Average time in In-Basket increased significantly over the study period (p<0.0001). Primary drivers for this change included increases in certain types of In-Basket messages, including results (p=0.01), patient medical advice (p<0.0001), hospital chart completion requests (p<0.0001), prescription authorization requests (p=0.003), and staff messages (p<0.0001). Orders On average, PGI prescribed 1 medication every other appointment, or 0.5+/-0.02 [0.4 (0.3, 0.6)] medications per visit. PGI ordered 2.2+/-0.3 [2 (1.4, 2.8)] tests/evaluations per appointment. Notes and Letters The average note length was 6392+/-193 [6072 (4344, 7696)] characters, equivalent to over 3.5 pages of text. Time spent in notes was 10.2+/-0.4 [9.7 (6.7, 13.1)] minutes per appointment and 46.9+/-2.4 [43.6 (29.9, 56.2)] minutes per day. Length of notes increased significantly over the study period (r=0.51, p=0.01) but time spent in notes did not. Clinical Review PGI spent an average of 17.7+/-1.5 [17 (12.7, 20.3)] minutes per scheduled day in chart review, equivalent to 4+/-0.2 [3.9 (2.7, 5.3)] minutes per appointment. CONCLUSION(S): Quantification of some key components of clinical workload inherent to PGI is possible using EHRs. PGIs routinely spend time outside of work hours performing EHR work. Over the past 2 years, In-Basket time has contributed substantially to PGI workload and has trended towards increasing messages from both external (patients and pharmacies) and internal sources (staff and hospital compliance). Considerable PGI time has also been spent constructing clinical notes of lengths that appear to have increased during the same 2-year period. Limitations to the study include non-standardized, opaque metric definitions and unclear fidelity of provider categorization. We would also note that our results document increasing EHR-related workload burdens on PGIs that can contribute to physician burnout. Through identification of best outcome metrics, quantification of PGI clinical workload using EPIC Signal data may allow quality improvement activities that reduce provider burden while enabling our subspecialty field to benefit from widespread implementation of EHRs.

6.
Investigative Ophthalmology and Visual Science ; 63(7):331-F0162, 2022.
Article in English | EMBASE | ID: covidwho-2057745

ABSTRACT

Purpose : The COVID-19 Pandemic has disrupted the care of patients receiving intravitreal injections for neovascular age-related macular degeneration (nAMD). This study looks at the factors that affected visit adherence for this population of patients during the height of the first pandemic surge. Methods : In this retrospective, observational, case-control study, we included nAMD patients receiving anti-VEGF injections with an appointment scheduled during the target periods of March 11, 2020-May 26, 2020 at either an urban hospital-based or suburban eye clinic. Patients who did not present for their appointment (cases) were compared to patients who did present to their appointment (controls). Medical records were reviewed to collect age, sex, race, presence of appointment attendance, language, marital status, distance from clinic, and area of deprivation index (ADI), which is a measure of socioeconomic health. Multivariate regression models were created with Stata (College Station, Texas) to determine the differences of these factors between no-show and show groups. Results : 115 no-show patients (21% male, mean age 81 years) and 129 controls (26 % male, mean age 80.9 years) were enrolled. The odds of no-show were higher in non-White patients compared to White [(odds ratio (OR) = 2.7, 95% Confidence Interval (CI) = 1.22- 6.17, P = 0.01)], the urban site compared to suburban site (OR = 3.1, 95% CI = 1.70-5.76, P = 0.0001) and single patients compared to married (OR = 2.3, 95% CI = 1.09-4.89, P = 0.02) in univariate analysis. The associations remained significant in multivariate analysis for non-White patients (OR = 3.1, 95% CI = 1.30-6.88, P = 0.01) and urban site (OR = 4.3, 95% CI = 1.78-10.3, P = 0.001) after adjusting for age, gender, language, distance from clinic and ADI. Age, distance from clinic, gender, ADI, and language were not statistically different between the two groups. Conclusions : Visit adherence was lower for non-White patients during the first surge of the COVID-19 pandemic underlying the disparities which can be seen during the pandemic. Patients treated at an urban hospital were less likely to present for their anti-VEGF treatments than those receiving care in a suburban clinic. Further research is needed to determine whether differences in visit adherence effected long-term vision outcomes.

7.
International Journal of Statistics in Medical Research ; 11:51-58, 2022.
Article in English | Scopus | ID: covidwho-2056197

ABSTRACT

The new wave of COVID-19 in Hong Kong, China was overwhelming again by “dynamic zero” strategy and non-pharmaceutical interventions (DZ-NPIs), which makes a time challenge to control the variant of this epidemic. We describe the variant of Covid-19 in Kong Hong to the infected proportion of the population, cumulative confirmed cases, cumulative deaths and current hospitalizations by age group via statistical measure firstly, then establish time series model for fitting the accumulative confirmed cases, further to predict the trend for searching out possible turning time-points. Non-linear regression model is created to feature the deaths series, then we figure out the parameters and educe the controlling condition for this epidemic. We expect our data-driven modeling process providing some insights to the controlling strategy for the new wave of the Covid-19 variant in Hong Kong, even in the mainland of China © 2022 Ding and Xiang;Licensee Lifescience Global. This is an open access article licensed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution and reproduction in any medium, provided the work is properly cited

8.
Intelligent Systems Conference, IntelliSys 2022 ; 543 LNNS:328-338, 2023.
Article in English | Scopus | ID: covidwho-2048142

ABSTRACT

The COVID-19 outbreak and the resulting mobility controls have led to profound changes in consumers’ grocery purchase preferences. This study explores the consumer demand response to the spread of the coronavirus and its variants. We establish a regression model, apply it to sales history data from a major North American retailer, and study the consumer preference in what food they buy and through which channel. While our empirical results provide data-driven support to several academic and industry viewpoints, and some counterexamples, a systematic implementation of the model can automatically provide managerial insights on future trends across vendors, brands and specific products. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

9.
Russian Journal of Infection & Immunity ; 12(4):783-789, 2022.
Article in Russian | Academic Search Complete | ID: covidwho-2040484

ABSTRACT

The objects of the study were the daily data on the population morbidity and mortality due to coronavirus disease 2019 (COVID-19) in Russian regions, as well as regional medical, demographic and environmental data recorded in recent years. COVID-19 is a contagious disease caused by the novel coronavirus (SARS-CoV-2). The mathematical methods consist of correlation and regression analysis, methods of testing statistical hypotheses. First, a multiple Variable Structure Regression should be specified. The intercept in the model differs from region to region, depending on the combination of values for dummy variables. The role of the dependent variable Yt was chosen as the cumulative mortality published by the operational headquarters for the regions that has been linked to day t, so that COVID-19 was considered the main cause of death. The complex of explanatory variables included two factorial variables that changed daily, and had a lag relative to t value. Also, this complex included a number of variables that did not change with the growth of t: the explanatory variable with the region’s availability with doctors of certain specialties;and four dummy variables. One of them coded the region’s belonging to the two southern Russian Federal Districts. Three other variables characterized the increased air pollution in settlements recorded in recent years, as well as the level of radiation pollution of the region’s territory and the population health estimated for 10 classes of diseases (for the circulatory system, endocrine system, etc.). The values of such dummy variables were obtained from open data from the Federal State Statistics Service (Rosstat) etc. The model parameters were estimated by the least squares method using the training table, which included 40 Russia’s regions, the t parameter for variable Yt was assessed starting from November, 1, 2021. As a result, a statistical model was built with an approximation error equal to 3%. For ¾ regions of the regions examined this error was 1.94 (±1.5)% for the value Yt that has been fixed on the 1st Nov. The plots show daily prediction for mortality rate due to COVID-19 in the first half of November for seven Russian regions compared with actual data. The model can be useful in development of medical and demographic policy in geographic regions, as well as generating adjusted compartment models that based on systems of differential equations (SEIRF, SIRD, etc.). (English) [ FROM AUTHOR] Объектами исследования были официальные данные по заболеваемости и смертности от COVID-19 в российских регионах, а также региональные медико-демографические и экологические данные за последние годы. Математическими методами работы являются корреляционный и регрессионный анализ, методы проверки статистических гипотез. Сначала специфицируется модель регрессии, имеющая переменную структуру;свободный член в ней отличается от региона к региону в зависимости от сочетания значений ряда фиктивных переменных (dummy). На роль зависимой переменной Y t выбиралась смертность, привязанная в сводной таблице оперативного штаба к суткам с отсчетом t, причем основной причиной смерти считалась COVID-19. Комплекс объясняющих переменных включал две факторные переменные, которые изменяются ежесуточно, причем с лагами относительно t. Также в этот комплекс входил еще ряд переменных, которые не изменялись во времени: показатель обеспеченности региона врачами ряда специальностей и четыре dummy-переменные. Одна из них кодировала южную принадлежность региона: ЮФО или СКФО. Три прочие характеризовали повышенное загрязнение атмосферного воздуха в населенных пунктах за последние годы, а также радиационное загрязнение территории и здоровье жителей регионов по 10 классам болезней (для системы кровообращения, эндокринной системы и проч.). Значения этих dummy-переменных были получены по открытым данным Росстата и др. Параметры модели оценивались методом наименьших квадратов по обучающей таблице, которая включала 40 регионов, где отсчет t переменной Y t входил за дату 1.xi.2021. В итоге построена статистическая модель с ошибкой аппроксимации 3%;для ¾ регионов из этой таблицы она оказалась 1,94 (±1,5)%. Приводятся графики с ежесуточными прогнозами смертности от COVID-19 в первой половине ноября 2021 г. для семи регионов в сравнении с фактическими значениями. Модель может быть полезной при разработке медико-демографической политики в регионах, а также при построении уточненных моделей секторного типа, состоящих из систем дифференциальных уравнений (SEIRF, SIRD и др.) (Russian) [ FROM AUTHOR] Copyright of Russian Journal of Infection & Immunity is the property of National Electronic-Information Consortium 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 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 . (Copyright applies to all s.)

10.
BMC Public Health ; 22(1): 1757, 2022 09 16.
Article in English | MEDLINE | ID: covidwho-2038715

ABSTRACT

OBJECTIVE: The COVID-19 pandemic has changed peoples' routine of daily living and posed major risks to global health and economy. Few studies have examined differential impacts of economic factors on health during pandemic compared to pre-pandemic. We aimed to compare the strength of associations between perceived health and socioeconomic position (household income, educational attainment, and employment) estimated before and during the pandemic. METHODS: Two waves of nationwide survey [on 2018(T1;n = 1200) and 2021(T2;n = 1000)] were done for 2200 community adults. A balanced distribution of confounders (demographics and socioeconomic position) were achieved across the T2 and T1 by use of the inverse probability of treatment weighting. Distributions of perceived health [= (excellent or very good)/(bad, fair, or good)] for physical-mental-social-spiritual subdomains were compared between T1 and T2. Odds of bad/fair/good health for demographics and socioeconomic position were obtained by univariate logistic regression. Adjusted odds (aOR) of bad/fair/good health in lower household income(< 3000 U.S. dollars/month) were retrieved using the multiple hierarchical logistic regression models of T1 and T2. RESULTS: Perceived health of excellent/very good at T2 was higher than T1 for physical(T1 = 36.05%, T2 = 39.13%; P = 0.04), but were lower for mental(T1 = 38.71%, T2 = 35.17%; P = 0.01) and social(T1 = 42.48%, T2 = 35.17%; P < 0.001) subdomains. Odds of bad/fair/good health were significantly increased at T2 than T1 for household income (physical-mental-social; all Ps < 0.001) and educational attainment (social; P = 0.04) but not for employment (all Ps > 0.05). AORs of bad/fair/good health in lower household income were stronger in T2 than T1, for mental [aOR (95% CI) = 2.15(1.68-2.77) in T2, 1.33(1.06-1.68) in T1; aOR difference = 0.82(P < 0.001)], physical [aOR (95% CI) = 2.64(2.05-3.41) in T2, 1.50(1.18-1.90) in T1; aOR difference = 1.14(P < 0.001)] and social [aOR (95% CI) = 2.15(1.68-2.77) in T2, 1.33(1.06-1.68) in T1; aOR difference = 0.35(P = 0.049)] subdomains. CONCLUSIONS: Risks of perceived health worsening for mental and social subdomains in people with lower monthly household income or lower educational attainment became stronger during the COVID-19 pandemic compared to pre-pandemic era. In consideration of the prolonged pandemic as of mid-2022, policies aiming not only to sustain the monthly household income and compulsory education but also to actively enhance the perceived mental-social health status have to be executed and maintained.


Subject(s)
COVID-19 , Pandemics , Adult , COVID-19/epidemiology , Educational Status , Health Status , Humans , Surveys and Questionnaires
11.
Indian Journal of Biochemistry and Biophysics ; 59(9):879-891, 2022.
Article in English | Scopus | ID: covidwho-2030669

ABSTRACT

Drug repurposing is a major approach used by researchers to tackle the COVID-19 pandemic which has been worsened by the current surge of delta variant in many countries. Though drugs like Remdesivir and Hydroxychloroquine have been repurposed, studies prove these drugs have insignificant effect in treatment. So, in this study, we use the already FDA approved database of 1615 drugs to apply semi-flexible and flexible molecular docking methods to calculate the docking scores and identify the best 20 potential inhibitors for our modelled delta variant spike protein RBD. Then, we calculate 2325 1-D and 2-D molecular descriptors and use machine-learning algorithms like K-Nearest Neighbor, Random Forest, Support Vector Machine and ensemble stacking method to build regression-based prediction models. We identify 15 best descriptors for the dataset all of which were found to be inversely correlated with ligand binding. With only these few descriptors, the models performed excellently with an area under curve (AUC) value of 0.952 in Regression Error Characteristic curve for ensemble stacking. Therefore, we comment that these 15 descriptors are the most important features for the binding of inhibitors to the spike protein and hence these should be studied properly in terms of drug repurposing and drug discovery. © 2022, National Institute of Science Communication and Policy Research. All rights reserved.

12.
Front Public Health ; 10: 920103, 2022.
Article in English | MEDLINE | ID: covidwho-2022948

ABSTRACT

Rumors regarding COVID-19 have been prevalent on the Internet and affect the control of the COVID-19 pandemic. Using 1,296 COVID-19 rumors collected from an online platform (piyao.org.cn) in China, we found measurable differences in the content characteristics between true and false rumors. We revealed that the length of a rumor's headline is negatively related to the probability of a rumor being true [odds ratio (OR) = 0.37, 95% CI (0.30, 0.44)]. In contrast, the length of a rumor's statement is positively related to this probability [OR = 1.11, 95% CI (1.09, 1.13)]. In addition, we found that a rumor is more likely to be true if it contains concrete places [OR = 20.83, 95% CI (9.60, 48.98)] and it specifies the date or time of events [OR = 22.31, 95% CI (9.63, 57.92)]. The rumor is also likely to be true when it does not evoke positive or negative emotions [OR = 0.15, 95% CI (0.08, 0.29)] and does not include a call for action [OR = 0.06, 95% CI (0.02, 0.12)]. By contrast, the presence of source cues [OR = 0.64, 95% CI (0.31, 1.28)] and visuals [OR = 1.41, 95% CI (0.53, 3.73)] is related to this probability with limited significance. Our findings provide some clues for identifying COVID-19 rumors using their content characteristics.


Subject(s)
COVID-19 , China , Humans , Internet , Pandemics , Probability
13.
Journal of Clinical Oncology ; 40(16), 2022.
Article in English | EMBASE | ID: covidwho-2009518

ABSTRACT

Background: Screening mammography programs often require patients undergo multiple visits (screening exam, diagnostic exam, and biopsy) before tissue diagnoisis of screen-detected abnormalities. During the COVID-19 pandemic, same-day breast imaging services were leveraged to decrease the number of visits following abnormal screening exams. Specifically, in May 2020, we implemented an immediate-read screening mammography program to synergize with our pre-existing same-day breast biopsy program, such that every effort was made to perform diagnostic imaging during the same visit after an abnormal screening mammogram. This study aims to evaluate the impact of these same-day breast imaging services on time and number of patient visits to undergo breast biopsy after an abnormal screening mammogram. Methods: Consecutive screening mammograms performed during normal business hours pre- (6/1/16 to 5/30/17) and post-implementation (6/1/20 to 5/30/21) of same-day services were identified. Patient demographics, imaging and biopsy results, and visit dates were extracted from the medical record. Multivariable logistic, linear, and ordinal regression models estimated with generalized estimating equations were fit to assess the association of period (pre- versus post-implementation), patient age, and race and ethnicity (White versus races other than White) with having a same-day biopsy (biopsy on the same day as the abnormal screening exam), number of days to biopsy, and number of visits. Adjusted odds ratios (aOR) and beta estimates (aBeta) of each covariate and corresponding 95% confidence intervals (CI) were estimated. Results: A total of 409/25,922 (1.6%) of patients (median age 61, IQR 50-70) pre-implementation and 221/20,452 (1.1%) patients (median age 62, IQR 49-71) post-implementation had screen-detected abnormalities leading to diagnostic breast imaging and biopsy. Median number of days from screening to biopsy decreased from 16 days pre-implementation to 5 days post-implementation (p < 0.001). Pre-implementation, 86.8% of patients required 3 visits between screening and biopsy, while post-implementation only 23.1% required 3 visits (p < 0.001). Compared to pre-implementation, the post-implementation period was associated with increased odds of undergoing same-day biopsy (aOR 20.7, 95% CI 8.3-51.7), p < 0.001), fewer days from abnormal screening mammogram to biopsy (aBeta -13.3, 95% CI -15.7 to -10.9, p < 0.001), and fewer visits (aOR 0.05, 95% CI 0.02-0.09), p < 0.001), controlling for age and race and ethnicity. Conclusions: Same-day breast imaging services decreased time and patient visits between abnormal screening mammogram and breast biopsy. Same-day services implemented out of necessity during the COVID-19 pandemic should be continued after the pandemic has subsided to improve timeliness of care.

14.
Annals of the Rheumatic Diseases ; 81:953-954, 2022.
Article in English | EMBASE | ID: covidwho-2009005

ABSTRACT

Background: Multisystem Infammatory Syndrome in Children (MIS-C) associated with COVID-19, presents as a cytokine storm with features of Kawasaki disease. Many cases present with shock and require intensive care admission. Objectives: We aimed to identify predictors for severe clinical course of MIS-C as defned by the need for ionotropic support during admission Methods: A retrospective multinational cohort study was conducted. Patients with a diagnosis of MIS-C from 9 Israeli medical centers and one US medical center (Chicago, IL) were included. Demographic, clinical, laboratory and imaging variables during admission and hospitalization were retrieved. Univariate and multivariate regression models were used to assess odds ratio (OR) of ionotropic support need during hospitalization. Results: Overall 100 MIS-C patients were included in the study. Sixty-five patients (65%) were hypotensive, 44% required ionotropic support, and 37% had fnding of Left ventricular dysfunction. Univariate model showed that LVD was associated with the need for ionotropic support (OR 4.178 [95%CI 1.760-9.917], while conjunctivitis (OR 0.403 [95%CI 0.173-0.938]) and mucosal changes (OR 0.333 [95%CI 0.119-0.931]) were protective. Laboratory markers for severe disease course were low hemoglobin levels, leukocyte count, thrombocyte count, lymphocyte count, neutrophils count, albumin and potassium, as well as high troponin and BNP. Conclusion: Patients with MIS-c that present with a Kawasaki-like phenotype are less likely to require ionotropic support, while other clinical and laboratory parameters were found as risk factors and should be monitored during MIS-C hospitalization.

15.
Annals of the Rheumatic Diseases ; 81:328-329, 2022.
Article in English | EMBASE | ID: covidwho-2008991

ABSTRACT

Background: During the frst months of the Sars-CoV-2 pandemic, antimalarial drugs were the central axis of the treatment of patients with acute respiratory infection. After that, several studies reported a risk of prolongation of corrected QT interval (QTc) at the electrocardiogram (ECG). Historically, these drugs, have been the common denominator in the treatment of patients with Systemic Lupus Erythematosus (SLE). Objectives: To analyze the possible relationship between the use of antima-larial drugs ant the electrocardiographic alterations in patients diagnosed with SLE. Methods: Cross-sectional study in patients diagnosed with SLE (SLICC 2012). In all of them, we performed a 12-lead ECG at rest. We measured the QT interval: manually and automatically, ant its correction was made according to the Hodge formule (QTc). Results: 91 patients diagnosed with SLE were included in the study. Of the total of patients included in the study, 64 were in current treatment with an antimalar-ial drug, with a mean of 9.09 (5.73) years of treatment, and a mean cumulative dosage of 813.16 (436.12) gr. Of the patients on current treatment with antimalarial drugs, 4.69% had a prolonged QTc, compared to 3.7% of the patients without current treatment with these drugs. We analyzed the possible relationship between the QTc interval, the current treatment with antimalarial drugs, and the cumulated dosage of this medication. We corrected the lineal regression models by the years of disease evolution, the presence or absence of known heart disease, the women gender, and other treatments such as antiarrhythmics or beta-blockers. We found a statistically signifcant association between taking antimalarial drugs and the elongated QTc interval (p= 0,001). Nevertheless, in the multivariate analysis, we did not found a signifcant relationship between the ECG alterations and the treatment with antimalarial drugs. Conclusion: In our study, we did not observe a direct relationship between the intake of antimalarial drugs and the alteration of the corrected QT interval.

16.
Annals of the Rheumatic Diseases ; 81:330, 2022.
Article in English | EMBASE | ID: covidwho-2008937

ABSTRACT

Background: Among immunocompromised patients with immune mediated infammatory diseases (IMIDs), those undergoing therapy with B cell depleting agents are among the most vulnerable to both severe COVID-19 disease and sub-optimal response to COVID-19 vaccines(1). Numerous studies have documented suppressed humoral, but relatively maintained cell mediated, responses to COVID-19 vaccines in these patients. However, the clinical signifcance of such immunity in terms of protection from infection and its sequelae are poorly understood. We have analyzed a large cohort of vaccinated IMIDs patients undergoing B cell depleting therapy for the presence of breakthrough infection and assessed their outcomes. Objectives: To defne the frequency and outcomes of COVID-19 breakthrough infection in fully or partially vaccinated IMIDs patients receiving B cell depleting therapies. To assess the characteristics and risk factors for severe outcomes and death. Methods: All pharmacy records from within a large health care system were electronically searched for patients undergoing B cell depleting therapies with approved monoclonal antibodies in 2020. Records with ICD codes for IMIDs but not malignancies were included;patients must also have had at least one documented COVID-19 vaccine. From this cohort all patients with breakthrough COVID-19 disease from time of 1st vaccination through December 15, 2021 were identifed;each record was hand-reviewed to extract clinical data including vaccine history, demographics, comorbidities, use of monoclonal antibodies, dose and timing of B cell depleting therapy, and outcomes as assessed by an 8 point NIH ordinal scale. Univariate and multivariable logistic/proportional-odds regression models were used to examine the risk factors for severe outcomes. Results: A total of 1677 IMIDs patients were identifed who received any B cell depleting monoclonal antibody and at least one COVID-19 vaccine in 2021. From this cohort 74 patients (4.4%) experienced a breakthrough COVID-19 infection. Among the breakthrough patients 34 (46%) had a rheumatic disease (RA 11, AAV 15, SLE 2), 34 (46%) had CNS infammatory disease (MS 32, 2 other), and 6 (8%) had immune hematologic/miscellaneous diseases. Four patients had a previous history of COVID-19 infection. Overall 24 (35%) were hospitalized with 11 patients requiring critical level care (15%) and 6 deaths (8 %). All fatal cases had rheumatic diseases. Monoclonal antibodies were given as outpatient therapy to 21 patients and among these only 1 patient was hospitalized without requiring O2 and none died. In univariate analysis only number of comorbidi-ties had a signifcant positive effect (p=.001) on severe outcomes (i.e. groups 1-4 vs. groups 5-8: Table 1) while monoclonal antibody therapy was associated with more favorable outcomes (p=.005 group 1-2 vs.3-8, Table 1). There were no associations between the dose, duration or timing of the B cell therapy, concomitant therapies including glucocorticoids, vaccine status (incomplete, complete, boosted) or date of vaccination with severe outcomes. Conclusion: In IMIDs patients treated with B cell depleting therapies breakthrough infections are common with many experiencing severe outcomes. Concomitant comorbidities were associated with risk of severe disease. Monoclonal antibody therapy was used in only 28% but was associated with enhanced clinical outcomes with only 1 in 21 requiring hospitalization and zero mortality. This population of immunocompromised patients remains vulnerable to COVID-19 disease despite vaccination. More aggressive use of outpatient management with monoclonal antibody therapy and other preventive and therapeutic measures are urgently needed.

17.
Annals of the Rheumatic Diseases ; 81:116-117, 2022.
Article in English | EMBASE | ID: covidwho-2008931

ABSTRACT

Background: Limited data is available regarding long-term effectiveness of SARS-CoV-2 vaccines in patients with immune-mediated infammatory diseases (IMIDs) on immunosuppressive therapy. Whether the persistence of vaccine-induced humoral immunity against SARS-CoV-2 differs between this patient population and the general public is currently unknown. Objectives: To compare the persistence of anti-Spike antibodies following two SARS-CoV-2 vaccine doses between IMID patients using immunosuppressive medication and healthy controls and identify predictors of antibody decline. Methods: We included patients with infammatory joint-and bowel diseases on immunosuppressive medication and healthy controls enrolled in the prospective observational Nor-vaC study. Serum samples were collected at two time points following two dose SARS-CoV-2 vaccination (frst assessment within 6-48 days and second within 49-123 days). Sera were analysed for antibodies binding the receptor-binding domain (RBD) of the SARS-CoV-2 Spike protein. Anti-RBD <200 BAU/ml were defned as low levels. The estimated percent reduction in anti-RBD standardised to 30 days was calculated and factors associated with reduction were identifed in multivariable regression models. Results: A total of 1097 patients (400 rheumatoid arthritis, 189 psoriatic arthritis, 189 spondyloarthritis, 129 ulcerative colitis, 190 Crohńs disease) (median age 54 years [IQR 43-64];56% women) and 133 controls (median age 45 years [IQR 35-56];83% women) provided blood samples within the defined intervals (median 19 days [IQR 15-24] and 97 days [86-105] after second vaccine dose). Antibody levels were significantly lower in patients compared to controls at both assessments, with median anti-RBD 1468 BAU/ml [IQR 500-5062] in patients and 5514 BAU/ml [2528-9580] in controls (p<0.0001) and 298 BAU/ml [IQR 79-500] in patients and 715 BAU/ml [28-2870] in controls (p<0.0001), at first and second assessment respectively. Figure 1 show antibody levels at both assessments after medication group. At the second assessment, anti-RBD antibody levels decreased below 200 BAU/ml in 452 (41%) patients and in 1 (0.8%) control (p<0.0001) (Table 1). The percentage change in anti-RBD levels were-86 % in patients and-77 % in controls (p<0.0001). The majority of patients using rituximab had low antibody levels at both assessments, Figure 1. In the multivariable regression analyses, patients had a greater decline in anti-RBD levels compared to controls β-3.7 (95% CI-6.0,-1.4) (p<0.001). Use of tumor necrosis factor inhibitors in mono-or combination therapy was associated with the greatest decline compared to controls, β-6.1 (95% CI-8.1,-4.1) and β-6.4 (-8.4,-4.2) respectively (p<0.001). Conclusion: Within four months after the second vaccine dose, anti-Spike antibody levels declined considerably in both IMID patients and controls. Patients had lower antibody levels at the frst assessment and a more pronounced decline compared to controls, and were consequently more likely to have low antibody levels four months after the second vaccine dose. Our results support that IMID patients lose humoral protection and need additional vaccine doses sooner than healthy individuals.

18.
Annals of the Rheumatic Diseases ; 81:1212, 2022.
Article in English | EMBASE | ID: covidwho-2008890

ABSTRACT

Background: Worries have been expressed, concerning the care of chronic diseases during the Covid times (1). Objectives: To study the current status of patients with RA in the Finnish quality register database. Methods: Patients who receive care for RA were identifed in the database. Clinical and demographic data from the last visits during 2020-21 were collected, including swollen (SJC46) and tender joint counts (TJC46), doctor assessment of disease activity (Dr global), laboratory tests for infammatory and serology markers, patient reported outcomes (PROs), and DAS28. Regression models were applied to compare measures of clinical status between the health care regions, adjusted for gender, age, ACPA status, and disease duration. Results: A total of 14163 patients (72% female, mean (SD) age 62 (14) years, median (IQR) disease duration 8.5 (2.6, 20) years, 84% ACPA positive) were identifed. For the entire population, the median (IQR) SJC46 was 0 (0, 1), TJC46 0 (0, 2), ESR 8 (5, 18), CRP 3 (1, 6), and dr global 8 (0, 19). Among PROs, median (IQR) HAQ was 0.5 (0, 1), pain 26 (10, 51), fatigue 28 (8, 54) and patient global 29 (11, 51). Between health care regions, statistically signifcant differences were found for all variables due to a large sample size. The mean (SD) DAS28 was 2.3 (0.9) for the entire group and 69 % of all patients had DAS28<2.6. The median DAS28 ranged from 2 to 2.7 among health care regions (Figure 1) (p<0.001). Majority of patients were taking csDMARDs only. Conclusion: The quality register provides comprehensive real-world data on the current status of patients with RA. A majority of patients can be considered being in remission even during the Covid times.

19.
Annals of the Rheumatic Diseases ; 81:720-722, 2022.
Article in English | EMBASE | ID: covidwho-2008862

ABSTRACT

Background: Evaluation of physical function is fundamental in the management of idiopathic infammatory myopathies (IIMs). Patient-Reported Outcome Measurement Information System (PROMIS) is a National Institute of Health initiative established in 2004 to develop patient-reported outcome measures (PROMs) with improved validity and efficacy. PROMIS Physical Function (PF) short forms have been validated for use in IIMs [1]. Objectives: To investigate the physical function status of IIM patients compared to those with non-IIM autoimmune diseases (AIDs) and healthy controls (HCs) utilizing PROMIS PF data obtained in the coronavirus disease-2019 (COVID-19) Vaccination in Autoimmune Diseases (COVAD) study, a large-scale, international self-reported e-survey assessing the safety of COVID-19 vaccines in AID patients [2]. Methods: The survey data regarding demographics, IIM and AID diagnosis, disease activity, and PROMIS PF short form-10a scores were extracted from the COVAD study database. The disease activity (active vs inactive) of each patient was assessed in 3 different ways: (1) physician's assessment (active if there was an increased immunosuppression), (2) patient's assessment (active vs inactive as per patient), and (3) current steroid use. These 3 defnitions of disease activity were applied independently to each patient. PROMIS PF-10a scores were compared between each disease category (IIMs vs non-IIM AIDs vs HCs), stratifed by disease activity based on the 3 defnitions stated above, employing negative binominal regression model. Multivariable regression analysis adjusted for age, gender, and ethnicity was performed clustering countries, and the predicted PROMIS PF-10a score was calculated based on the regression result. Factors affecting PROMIS PF-10a scores other than disease activity were identifed by another multivariable regression analysis in the patients with inactive disease (IIMs or non-IIM AIDs). Results: 1057 IIM patients, 3635 non-IIM AID patients, and 3981 HCs responded to the COVAD survey until August 2021. The median age of the respondents was 43 [IQR 30-56] years old, and 74.8% were female. Among IIM patients, dermatomyositis was the most prevalent diagnosis (34.8%), followed by inclusion body myositis (IBM) (23.6%), polymyositis (PM) (16.2%), anti-syn-thetase syndrome (11.8%), overlap myositis (7.9%), and immune-mediated necrotizing myopathy (IMNM) (4.6%). The predicted mean of PROMIS PF-10a scores was signifcantly lower in IIMs compared to non-IIM AIDs or HCs (36.3 [95% (CI) 35.5-37.1] vs 41.3 [95% CI 40.2-42.5] vs 46.2 [95% CI 45.8-46.6], P < 0.001), irrespective of disease activity or the defnitions of disease activity used (physician's assessment, patient's assessment, or steroid use) (Figure 1). The largest difference between active IIMs and non-IIM AIDs was observed when the disease activity was defned by patient's assessment (35.0 [95% CI 34.1-35.9] vs 40.1 [95% CI 38.7-41.5]). Considering the subgroups of IIMs, the scores were signifcantly lower in IBM in comparison with non-IBM IIMs (P < 0.001). The independent factors associated with low PROMIS PF-10a scores in the patients with inactive disease were older age, female gender, and the disease category being IBM, PM, or IMNM. Conclusion: Physical function is signifcantly impaired in IIMs compared to non-IIM AIDs or HCs, even in patients with inactive disease. The elderly, women, and IBM groups are the worst affected, suggesting that developing targeted strategies to minimize functional disability in certain groups may improve patient reported physical function and disease outcomes.

20.
Journal of Public Health in Africa ; 13:52-53, 2022.
Article in English | EMBASE | ID: covidwho-2006812

ABSTRACT

Introduction/ Background: Non-pharmaceutical interventions are important public health measures targeted at behavioral changes to interrupt the transmission of coronavirus in humans. This study evaluated the challenges of implementing non-pharmaceuticalinterventions, assessed adherence, and identified requirements to the successful control of the spread of COVID-19 among individuals living in an urban-slum setting in Lagos-Nigeria. Methods: A cross-sectional study conducted among resident of an urban-slum in Makoko, Lagos-Nigeria. Adult members of households aged 18 years and above were selected via convenient sampling. An interviewer administered semi-structured questionnaire was used to obtain information on sociodemographic characteristics, living conditions and adherence to non-pharmaceutical interventions over a period of five-months from May to September 2020. Adherence to nonpharmaceutical intervention was determined by calculating an adherence index from 10 evidence based protective behaviors and a self-report of adhering to the measures. Descriptive-statistics and multiple-logistics regression model were used to determine challenges and factors associated with adherence to COVID-19 preventive measures. Results: A total of 357 participants with a mean-age of 45.8 ± 12.9 years were included in the analysis. Majority were males (62.2%) and married (83.8%). Most participants (93.8%) had no space for selfisolation as majority lived in a one-roomapartment (72.8%), shared toilets/kitchen-space (63.6%) with other families and had no constant source of water-supply (61.9%). About 98.8% are aware of the pandemic but only 33.9% adhered to the preventive-measures. The ability to afford facemasks/hand-sanitizers (aOR:6.7;95% CI:3.8-11.6), living-alone (aOR:3.7;95%CI:1.3-10.6), and ability to buy-water (aOR:0.3;95% CI:0.1-0.5) were found to be associated with adherence to the preventivemeasures after adjusting for covariates in a multilogistic- regression-model. Impact: This study gives insight on the realities/challenges of implementing non-pharmaceutical-intervention against COVID-19 disease in a setting of economically disadvantaged individuals who are at a great risk of being a hub for circulating the virus. This will aid the government in addressing cogent factors that might fuel re-occurrence of the pandemic waves. Conclusion: Implementation of non-pharmaceutical interventions for COVID-19 prevention was a challenge as only a quarter of residents adhered to national guidelines. Government should prioritize vaccinating these cohort of individuals and address factors like poor housing, overcrowding and lack of public water supply that affects adherence to public health measures in this setting.

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