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1.
Rheumatology (Oxford) ; 2022 Feb 01.
Article in English | MEDLINE | ID: covidwho-1662131

ABSTRACT

OBJECTIVES: Infections including Tuberculosis (TB) are a leading cause of morbidity and mortality in Idiopathic Inflammatory Myopathies (IIM). We systematically reviewed the prevalence of Mycobacterial infections in patients with IIM. METHODS: We screened PUBMED, EMBASE and SCOPUS databases and conference abstracts (2015-20) for original articles using Covidence. Pooled estimates of prevalence were calculated. RESULTS: Of 83 studies (28 cohort-studies, 2 case-control and 53 case reports), 19 were analysed. Of 14043 IIM patients, Dermatomyositis (54.41%) was the most common subset among TB. Most studies were from Asia with high prevalence [5.86%,2.33%-10.60%].Pooled prevalence of Mycobacterial infections among IIM was 3.58% (95% CI = 2.17% - 5.85%, p< 0.01). Disseminated and extrapulmonary forms (46.58%; 95% CI 39.02%-54.31%, p= 1.00) were as common as pulmonary TB (49.07%; 95% CI = 41.43%-56.75%, p= 0.99) both for I2=0. Muscle involvement, an otherwise rare site, was frequently seen in case reports (24.14%). M. Tuberculosis (28.84%) was the most common pathogen followed by Mycobacterium Avium Complex (3.25%). Non-tuberculous Mycobacteria were less common overall (6.25; 95% CI = 3.49%-10.93%) I2=0, p= 0.94.Subgroup analysis & meta-regression based on high vs low TB regions found prevalence 6.61% (2.96%-11.33%) in high TB regions vs 2.05% (0.90%-3.56%) in low TB regions. While death due to TB was occasionally reported [p= 0.82], successful anti-tubercular treatment was common (13.95%). CONCLUSION: TB is common in IIM, particularly in endemic regions though current data is largely heterogeneous. Extra-pulmonary forms &atypical sites including the muscle are frequent. Limited data suggests fair outcomes, although larger prospective studies may offer better understanding.

2.
J Korean Med Sci ; 36(50): e338, 2021 Dec 27.
Article in English | MEDLINE | ID: covidwho-1596045

ABSTRACT

Generating a testable working hypothesis is the first step towards conducting original research. Such research may prove or disprove the proposed hypothesis. Case reports, case series, online surveys and other observational studies, clinical trials, and narrative reviews help to generate hypotheses. Observational and interventional studies help to test hypotheses. A good hypothesis is usually based on previous evidence-based reports. Hypotheses without evidence-based justification and a priori ideas are not received favourably by the scientific community. Original research to test a hypothesis should be carefully planned to ensure appropriate methodology and adequate statistical power. While hypotheses can challenge conventional thinking and may be controversial, they should not be destructive. A hypothesis should be tested by ethically sound experiments with meaningful ethical and clinical implications. The coronavirus disease 2019 pandemic has brought into sharp focus numerous hypotheses, some of which were proven (e.g. effectiveness of corticosteroids in those with hypoxia) while others were disproven (e.g. ineffectiveness of hydroxychloroquine and ivermectin).


Subject(s)
COVID-19/drug therapy , Research Design , SARS-CoV-2 , COVID-19/epidemiology , Ethics, Research , Humans , Peer Review , Pilot Projects , Publishing
3.
JK Science ; 23(1):1-2, 2021.
Article in English | ProQuest Central | ID: covidwho-1573255

ABSTRACT

At times, unusual presentations may lead to an erroneous diagnosis of an idiopathic vasculitis, connective tissue disorders, or hyperinflammatory syndromes of unclear origin in the event of false-negative COVID-19 PCR. [...]it is imperative to maintain a high degree of clinical suspicion during the pandemic period and actively look out for relatively specific signs of COVID-19 like anosmia for timely diagnosis. On occasion, classic dermatomyositis-like presentations, replete with classic rashes have been reported, raising the case for de novo virus-triggered autoimmune disease. [...]similarities are seen between anti MDA5 antibody-associated muscle-lung syndromes and COVID-19 since both involve a 'cytokine storm' (a maladaptive overproduction of inflammatory cytokines including IL-1, IL6, and TNF-alpha) and ultimately diffuse alveolar damage (the clinical presentation being acute respiratory distress syndrome) with similar radiological and histological findings (5). While immunosuppressive therapy has had mixed results in the management of COVID-19, corticosteroids have come to the forefront of this battle with a decrease in mortality in hospitalized patients with severe COVID19 Even though COVID-19 is an acute disease, some effects last greater than 3 months or even longer in nearly three-quarters of those afflicted with the virus.

4.
Diagnostics (Basel) ; 11(12)2021 Dec 15.
Article in English | MEDLINE | ID: covidwho-1572404

ABSTRACT

(1) Background: COVID-19 computed tomography (CT) lung segmentation is critical for COVID lung severity diagnosis. Earlier proposed approaches during 2020-2021 were semiautomated or automated but not accurate, user-friendly, and industry-standard benchmarked. The proposed study compared the COVID Lung Image Analysis System, COVLIAS 1.0 (GBTI, Inc., and AtheroPointTM, Roseville, CA, USA, referred to as COVLIAS), against MedSeg, a web-based Artificial Intelligence (AI) segmentation tool, where COVLIAS uses hybrid deep learning (HDL) models for CT lung segmentation. (2) Materials and Methods: The proposed study used 5000 ITALIAN COVID-19 positive CT lung images collected from 72 patients (experimental data) that confirmed the reverse transcription-polymerase chain reaction (RT-PCR) test. Two hybrid AI models from the COVLIAS system, namely, VGG-SegNet (HDL 1) and ResNet-SegNet (HDL 2), were used to segment the CT lungs. As part of the results, we compared both COVLIAS and MedSeg against two manual delineations (MD 1 and MD 2) using (i) Bland-Altman plots, (ii) Correlation coefficient (CC) plots, (iii) Receiver operating characteristic curve, and (iv) Figure of Merit and (v) visual overlays. A cohort of 500 CROATIA COVID-19 positive CT lung images (validation data) was used. A previously trained COVLIAS model was directly applied to the validation data (as part of Unseen-AI) to segment the CT lungs and compare them against MedSeg. (3) Result: For the experimental data, the four CCs between COVLIAS (HDL 1) vs. MD 1, COVLIAS (HDL 1) vs. MD 2, COVLIAS (HDL 2) vs. MD 1, and COVLIAS (HDL 2) vs. MD 2 were 0.96, 0.96, 0.96, and 0.96, respectively. The mean value of the COVLIAS system for the above four readings was 0.96. CC between MedSeg vs. MD 1 and MedSeg vs. MD 2 was 0.98 and 0.98, respectively. Both had a mean value of 0.98. On the validation data, the CC between COVLIAS (HDL 1) vs. MedSeg and COVLIAS (HDL 2) vs. MedSeg was 0.98 and 0.99, respectively. For the experimental data, the difference between the mean values for COVLIAS and MedSeg showed a difference of <2.5%, meeting the standard of equivalence. The average running times for COVLIAS and MedSeg on a single lung CT slice were ~4 s and ~10 s, respectively. (4) Conclusions: The performances of COVLIAS and MedSeg were similar. However, COVLIAS showed improved computing time over MedSeg.

5.
Front Biosci (Landmark Ed) ; 26(11): 1312-1339, 2021 11 30.
Article in English | MEDLINE | ID: covidwho-1552205

ABSTRACT

Background: Atherosclerosis is the primary cause of the cardiovascular disease (CVD). Several risk factors lead to atherosclerosis, and altered nutrition is one among those. Nutrition has been ignored quite often in the process of CVD risk assessment. Altered nutrition along with carotid ultrasound imaging-driven atherosclerotic plaque features can help in understanding and banishing the problems associated with the late diagnosis of CVD. Artificial intelligence (AI) is another promisingly adopted technology for CVD risk assessment and management. Therefore, we hypothesize that the risk of atherosclerotic CVD can be accurately monitored using carotid ultrasound imaging, predicted using AI-based algorithms, and reduced with the help of proper nutrition. Layout: The review presents a pathophysiological link between nutrition and atherosclerosis by gaining a deep insight into the processes involved at each stage of plaque development. After targeting the causes and finding out results by low-cost, user-friendly, ultrasound-based arterial imaging, it is important to (i) stratify the risks and (ii) monitor them by measuring plaque burden and computing risk score as part of the preventive framework. Artificial intelligence (AI)-based strategies are used to provide efficient CVD risk assessments. Finally, the review presents the role of AI for CVD risk assessment during COVID-19. Conclusions: By studying the mechanism of low-density lipoprotein formation, saturated and trans fat, and other dietary components that lead to plaque formation, we demonstrate the use of CVD risk assessment due to nutrition and atherosclerosis disease formation during normal and COVID times. Further, nutrition if included, as a part of the associated risk factors can benefit from atherosclerotic disease progression and its management using AI-based CVD risk assessment.


Subject(s)
Arteries/diagnostic imaging , Atherosclerosis/diagnostic imaging , COVID-19/physiopathology , Cardiovascular Diseases/diagnostic imaging , Nutritional Status , Algorithms , COVID-19/diagnostic imaging , COVID-19/virology , Humans , Risk Factors , SARS-CoV-2/isolation & purification
6.
Lancet Respir Med ; 9(5): 511-521, 2021 05.
Article in English | MEDLINE | ID: covidwho-1537197

ABSTRACT

BACKGROUND: Global randomised controlled trials of the anti-IL-6 receptor antibody tocilizumab in patients admitted to hospital with COVID-19 have shown conflicting results but potential decreases in time to discharge and burden on intensive care. Tocilizumab reduced progression to mechanical ventilation and death in a trial population enriched for racial and ethnic minorities. We aimed to investigate whether tocilizumab treatment could prevent COVID-19 progression in the first multicentre randomised controlled trial of tocilizumab done entirely in a lower-middle-income country. METHODS: COVINTOC is an open-label, multicentre, randomised, controlled, phase 3 trial done at 12 public and private hospitals across India. Adults (aged ≥18 years) admitted to hospital with moderate to severe COVID-19 (Indian Ministry of Health grading) confirmed by positive SARS-CoV-2 PCR result were randomly assigned (1:1 block randomisation) to receive tocilizumab 6 mg/kg plus standard care (the tocilizumab group) or standard care alone (the standard care group). The primary endpoint was progression of COVID-19 (from moderate to severe or from severe to death) up to day 14 in the modified intention-to-treat population of all participants who had at least one post-baseline assessment for the primary endpoint. Safety was assessed in all randomly assigned patients. The trial is completed and registered with the Clinical Trials Registry India (CTRI/2020/05/025369). FINDINGS: 180 patients were recruited between May 30, 2020, and Aug 31, 2020, and randomly assigned to the tocilizumab group (n=90) or the standard care group (n=90). One patient randomly assigned to the standard care group inadvertently received tocilizumab at baseline and was included in the tocilizumab group for all analyses. One patient randomly assigned to the standard care group withdrew consent after the baseline visit and did not receive any study medication and was not included in the modified intention-to-treat population but was still included in safety analyses. 75 (82%) of 91 in the tocilizumab group and 68 (76%) of 89 in the standard care group completed 28 days of follow-up. Progression of COVID-19 up to day 14 occurred in eight (9%) of 91 patients in the tocilizumab group and 11 (13%) of 88 in the standard care group (difference -3·71 [95% CI -18·23 to 11·19]; p=0·42). 33 (36%) of 91 patients in the tocilizumab group and 22 (25%) of 89 patients in the standard care group had adverse events; 18 (20%) and 15 (17%) had serious adverse events. The most common adverse event was acute respiratory distress syndrome, reported in seven (8%) patients in each group. Grade 3 adverse events were reported in two (2%) patients in the tocilizumab group and five (6%) patients in the standard care group. There were no grade 4 adverse events. Serious adverse events were reported in 18 (20%) patients in the tocilizumab group and 15 (17%) in the standard care group; 13 (14%) and 15 (17%) patients died during the study. INTERPRETATION: Routine use of tocilizumab in patients admitted to hospital with moderate to severe COVID-19 is not supported. However, post-hoc evidence from this study suggests tocilizumab might still be effective in patients with severe COVID-19 and so should be investigated further in future studies. FUNDING: Medanta Institute of Education and Research, Roche India, Cipla India, and Action COVID-19 India.


Subject(s)
Antibodies, Monoclonal, Humanized , COVID-19 , Cytokine Release Syndrome , Receptors, Interleukin-6/antagonists & inhibitors , Respiratory Distress Syndrome , SARS-CoV-2/isolation & purification , Antibodies, Monoclonal, Humanized/administration & dosage , Antibodies, Monoclonal, Humanized/adverse effects , COVID-19/complications , COVID-19/immunology , COVID-19/mortality , COVID-19/therapy , Critical Care/methods , Cytokine Release Syndrome/drug therapy , Cytokine Release Syndrome/etiology , Cytokine Release Syndrome/immunology , Drug Monitoring/methods , Female , Humans , Immunologic Factors/administration & dosage , Immunologic Factors/adverse effects , India , Male , Middle Aged , Mortality , Respiration, Artificial/methods , Respiratory Distress Syndrome/diagnosis , Respiratory Distress Syndrome/etiology , Severity of Illness Index , Treatment Outcome
7.
Non-conventional in English | [Unspecified Source], Grey literature | ID: grc-750484

ABSTRACT

The global impact of COVID-19 pandemic has increased the need to rapidly develop and improve utilization of mobile applications across the healthcare continuum to address rising barriers of access to care due to social distancing challenges and allow continuity in sharing of health information, assist with COVID-19 activities including contact tracing, and providing useful information as needed. Here we provide an overview of mobile applications being currently utilized for COVID-19 related activities. We performed a systematic review of the literature and mobile platforms to assess mobile applications been currently utilized for COVID-19, and quality assessment of these applications using the Mobile Application Rating Scale (MARS) for overall quality, Engagement, Functionality, Aesthetics, and Information. Finally, we provide an overview of the key salient features that should be included in mobile applications being developed for future use. Our search identified 63 apps that are currently being used for COVID-19. Of these, 25 were selected from the Google play store and Apple App store in India, and 19 each from the UK and US. 18 apps were developed for sharing up to date information on COVID-19, and 8 were used for contact tracing while 9 apps showed features of both. On MARS Scale, overall scores ranged from 2.4 to 4.8 with apps scoring high in areas of functionality and lower in Engagement. Future steps should involve developing and testing of mobile applications using assessment tools like the MARS scale and the study of their impact on health behaviors and outcomes.

8.
Diagnostics (Basel) ; 11(11)2021 Nov 01.
Article in English | MEDLINE | ID: covidwho-1488513

ABSTRACT

Background: For COVID-19 lung severity, segmentation of lungs on computed tomography (CT) is the first crucial step. Current deep learning (DL)-based Artificial Intelligence (AI) models have a bias in the training stage of segmentation because only one set of ground truth (GT) annotations are evaluated. We propose a robust and stable inter-variability analysis of CT lung segmentation in COVID-19 to avoid the effect of bias. Methodology: The proposed inter-variability study consists of two GT tracers for lung segmentation on chest CT. Three AI models, PSP Net, VGG-SegNet, and ResNet-SegNet, were trained using GT annotations. We hypothesized that if AI models are trained on the GT tracings from multiple experience levels, and if the AI performance on the test data between these AI models is within the 5% range, one can consider such an AI model robust and unbiased. The K5 protocol (training to testing: 80%:20%) was adapted. Ten kinds of metrics were used for performance evaluation. Results: The database consisted of 5000 CT chest images from 72 COVID-19-infected patients. By computing the coefficient of correlations (CC) between the output of the two AI models trained corresponding to the two GT tracers, computing their differences in their CC, and repeating the process for all three AI-models, we show the differences as 0%, 0.51%, and 2.04% (all < 5%), thereby validating the hypothesis. The performance was comparable; however, it had the following order: ResNet-SegNet > PSP Net > VGG-SegNet. Conclusions: The AI models were clinically robust and stable during the inter-variability analysis on the CT lung segmentation on COVID-19 patients.

9.
Rheumatol Int ; 41(11): 1941-1947, 2021 Nov.
Article in English | MEDLINE | ID: covidwho-1370384

ABSTRACT

Management of ANCA-associated vasculitis (AAV) during the COVID-19 pandemic poses unique therapeutic challenges. An online survey was conducted to understand physician's choices for treating AAV during the COVID-19 pandemic. Web-based survey featuring nineteen questions was circulated amongst physicians across various specialties. The responses regarding immunosuppressive therapy for remission induction and maintenance, COVID-19 testing, and preventive measures were recorded. A total of 304 responses were recorded. Most of the respondents were from India (83.9%) and comprised rheumatologists (66%) in practice for ≥ 5 years (71%). Though a majority preferred Rituximab or intravenous cyclophosphamide (CYC) as a remission induction agent, a significant proportion opted for oral CYC and mycophenolate mofetil (MMF) also. Only one-third wanted to test for COVID-19 before initiating immunosuppressive therapy in patients with organ/life-threatening manifestations. Rituximab was the most favored maintenance therapy (47%), followed by azathioprine, MMF, and methotrexate. The results of this focused survey of managing AAV patients depict the real-world dilemmas and physicians' choices in this setting.


Subject(s)
Anti-Neutrophil Cytoplasmic Antibody-Associated Vasculitis/drug therapy , Practice Patterns, Physicians' , Rheumatology/methods , Adult , COVID-19/epidemiology , COVID-19 Testing , Female , Humans , Immunosuppressive Agents/therapeutic use , Male , Middle Aged , Pandemics , Remission Induction/methods , SARS-CoV-2 , Surveys and Questionnaires
10.
Diagnostics (Basel) ; 11(8)2021 Aug 04.
Article in English | MEDLINE | ID: covidwho-1341653

ABSTRACT

BACKGROUND: COVID-19 lung segmentation using Computed Tomography (CT) scans is important for the diagnosis of lung severity. The process of automated lung segmentation is challenging due to (a) CT radiation dosage and (b) ground-glass opacities caused by COVID-19. The lung segmentation methodologies proposed in 2020 were semi- or automated but not reliable, accurate, and user-friendly. The proposed study presents a COVID Lung Image Analysis System (COVLIAS 1.0, AtheroPoint™, Roseville, CA, USA) consisting of hybrid deep learning (HDL) models for lung segmentation. METHODOLOGY: The COVLIAS 1.0 consists of three methods based on solo deep learning (SDL) or hybrid deep learning (HDL). SegNet is proposed in the SDL category while VGG-SegNet and ResNet-SegNet are designed under the HDL paradigm. The three proposed AI approaches were benchmarked against the National Institute of Health (NIH)-based conventional segmentation model using fuzzy-connectedness. A cross-validation protocol with a 40:60 ratio between training and testing was designed, with 10% validation data. The ground truth (GT) was manually traced by a radiologist trained personnel. For performance evaluation, nine different criteria were selected to perform the evaluation of SDL or HDL lung segmentation regions and lungs long axis against GT. RESULTS: Using the database of 5000 chest CT images (from 72 patients), COVLIAS 1.0 yielded AUC of ~0.96, ~0.97, ~0.98, and ~0.96 (p-value < 0.001), respectively within 5% range of GT area, for SegNet, VGG-SegNet, ResNet-SegNet, and NIH. The mean Figure of Merit using four models (left and right lung) was above 94%. On benchmarking against the National Institute of Health (NIH) segmentation method, the proposed model demonstrated a 58% and 44% improvement in ResNet-SegNet, 52% and 36% improvement in VGG-SegNet for lung area, and lung long axis, respectively. The PE statistics performance was in the following order: ResNet-SegNet > VGG-SegNet > NIH > SegNet. The HDL runs in <1 s on test data per image. CONCLUSIONS: The COVLIAS 1.0 system can be applied in real-time for radiology-based clinical settings.

12.
World J Diabetes ; 12(3): 215-237, 2021 Mar 15.
Article in English | MEDLINE | ID: covidwho-1148329

ABSTRACT

Coronavirus disease 2019 (COVID-19) is a global pandemic where several comorbidities have been shown to have a significant effect on mortality. Patients with diabetes mellitus (DM) have a higher mortality rate than non-DM patients if they get COVID-19. Recent studies have indicated that patients with a history of diabetes can increase the risk of severe acute respiratory syndrome coronavirus 2 infection. Additionally, patients without any history of diabetes can acquire new-onset DM when infected with COVID-19. Thus, there is a need to explore the bidirectional link between these two conditions, confirming the vicious loop between "DM/COVID-19". This narrative review presents (1) the bidirectional association between the DM and COVID-19, (2) the manifestations of the DM/COVID-19 loop leading to cardiovascular disease, (3) an understanding of primary and secondary factors that influence mortality due to the DM/COVID-19 loop, (4) the role of vitamin-D in DM patients during COVID-19, and finally, (5) the monitoring tools for tracking atherosclerosis burden in DM patients during COVID-19 and "COVID-triggered DM" patients. We conclude that the bidirectional nature of DM/COVID-19 causes acceleration towards cardiovascular events. Due to this alarming condition, early monitoring of atherosclerotic burden is required in "Diabetes patients during COVID-19" or "new-onset Diabetes triggered by COVID-19 in Non-Diabetes patients".

13.
Comput Biol Med ; 130: 104210, 2021 03.
Article in English | MEDLINE | ID: covidwho-1064978

ABSTRACT

COVID-19 has infected 77.4 million people worldwide and has caused 1.7 million fatalities as of December 21, 2020. The primary cause of death due to COVID-19 is Acute Respiratory Distress Syndrome (ARDS). According to the World Health Organization (WHO), people who are at least 60 years old or have comorbidities that have primarily been targeted are at the highest risk from SARS-CoV-2. Medical imaging provides a non-invasive, touch-free, and relatively safer alternative tool for diagnosis during the current ongoing pandemic. Artificial intelligence (AI) scientists are developing several intelligent computer-aided diagnosis (CAD) tools in multiple imaging modalities, i.e., lung computed tomography (CT), chest X-rays, and lung ultrasounds. These AI tools assist the pulmonary and critical care clinicians through (a) faster detection of the presence of a virus, (b) classifying pneumonia types, and (c) measuring the severity of viral damage in COVID-19-infected patients. Thus, it is of the utmost importance to fully understand the requirements of for a fast and successful, and timely lung scans analysis. This narrative review first presents the pathological layout of the lungs in the COVID-19 scenario, followed by understanding and then explains the comorbid statistical distributions in the ARDS framework. The novelty of this review is the approach to classifying the AI models as per the by school of thought (SoTs), exhibiting based on segregation of techniques and their characteristics. The study also discusses the identification of AI models and its extension from non-ARDS lungs (pre-COVID-19) to ARDS lungs (post-COVID-19). Furthermore, it also presents AI workflow considerations of for medical imaging modalities in the COVID-19 framework. Finally, clinical AI design considerations will be discussed. We conclude that the design of the current existing AI models can be improved by considering comorbidity as an independent factor. Furthermore, ARDS post-processing clinical systems must involve include (i) the clinical validation and verification of AI-models, (ii) reliability and stability criteria, and (iii) easily adaptable, and (iv) generalization assessments of AI systems for their use in pulmonary, critical care, and radiological settings.


Subject(s)
Artificial Intelligence , COVID-19/diagnostic imaging , Lung/diagnostic imaging , SARS-CoV-2 , Severity of Illness Index , Tomography, X-Ray Computed , Humans
14.
Rev Cardiovasc Med ; 21(4): 541-560, 2020 12 30.
Article in English | MEDLINE | ID: covidwho-1059479

ABSTRACT

Artificial Intelligence (AI), in general, refers to the machines (or computers) that mimic "cognitive" functions that we associate with our mind, such as "learning" and "solving problem". New biomarkers derived from medical imaging are being discovered and are then fused with non-imaging biomarkers (such as office, laboratory, physiological, genetic, epidemiological, and clinical-based biomarkers) in a big data framework, to develop AI systems. These systems can support risk prediction and monitoring. This perspective narrative shows the powerful methods of AI for tracking cardiovascular risks. We conclude that AI could potentially become an integral part of the COVID-19 disease management system. Countries, large and small, should join hands with the WHO in building biobanks for scientists around the world to build AI-based platforms for tracking the cardiovascular risk assessment during COVID-19 times and long-term follow-up of the survivors.


Subject(s)
Artificial Intelligence , COVID-19/epidemiology , Cardiovascular Diseases/epidemiology , Delivery of Health Care/methods , Pandemics , Risk Assessment , SARS-CoV-2 , Cardiovascular Diseases/therapy , Comorbidity , Humans , Risk Factors
15.
Rheumatol Int ; 41(1): 67-76, 2021 01.
Article in English | MEDLINE | ID: covidwho-1029537

ABSTRACT

Teleconsultation has assumed a central role in the management of chronic and disabling rheumatic diseases, such as the idiopathic inflammatory myopathies (IIM), during COVID-19. However, the feasibility, challenges encountered, and outcomes remain largely unexplored. Here, we describe our teleconsultation experience in a prospectively followed cohort of adult and juvenile IIM. 250 IIM enrolled into the MyoCite cohort (2017-ongoing) were offered the option of audio/visual teleconsultation using WhatsApp during the nationwide lockdown. Clinical outcomes (major/minor relapse) and prescription changes were compared between IIM subsets. Socio-demographic and clinico-serological characteristics of those who sought teleconsultation were compared with those who did not. 151 teleconsultations were sought over a 93 day period by 71 (52.2%) of 136 IIM (median age 38 years, F:M 4.5:1). Nearly one-third (38%) consulted on an emergency basis, with voice consultations being the primary medium of communication. Over a quarter (26.8%) reported relapse (15.5% minor, 11.3% major), these being more common in JDM [71.4%, OR 8.9 (1.5-51)] as compared with adult IIM, but similar across various antibody-based IIM subtypes. Patients who relapsed required more consultations [2(2-3) vs 1(1-2), p 0.009]. The demographic and socioeconomic profile of the patients seeking consultation (n = 71) was not different from those who did not (n = 65). Voice-based teleconsultations may be useful to diagnose and manage relapses in IIM during the pandemic. Patient education for meticulous and timely reporting may be improve care, and larger multicentre studies may identify subsets of IIM that require greater care and early tele-triage for effective management of the condition.


Subject(s)
COVID-19 , Myositis/therapy , Telemedicine/methods , Adult , Case-Control Studies , Child , Disease Progression , Female , Humans , India , Male , Middle Aged , Myositis/classification , Pandemics , Prospective Studies , SARS-CoV-2 , Telemedicine/statistics & numerical data , Text Messaging
16.
Disaster Med Public Health Prep ; 14(3): 387-390, 2020 Jun.
Article in English | MEDLINE | ID: covidwho-1030339

ABSTRACT

OBJECTIVE: The coronavirus disease (COVID-19) pandemic is a disaster of unprecedented proportions with global repercussions. Psychological preparedness, the primed cognitive awareness and anticipation of dealing with emotional responses in an adverse situation, has assumed a compelling relevance during a health disaster of this magnitude. METHODS: An anonymized eSurvey was conducted in India to assess psychological preparedness toward the ongoing pandemic with a focus on knowledge, management of own and others' emotional response, and anticipatory coping mechanisms among the survey population. An adapted version of the qualitative Psychological Preparedness for Natural Disaster Scale validated by the World Health Organization was widely circulated over the Internet and various social media platforms for assessment. Results are expressed as median ± standard deviation. Descriptive statistics were used and figures downloaded from surveymonkey.com. RESULTS: Of the 1120 respondents (M:F 1.7:1, age 35 years ±14.1), most expressed a high level of perceived knowledge and confidence of managing COVID-19, such as awareness of the symptoms of the illness (95.1%), actions needed (94.4%), hospital to report to (88.9%), and emergency contact number (89.1%). A majority (95%) monitored regularly the news bulletins and scientific journals regarding COVID-19. However, nearly one-third (29.2%) could not assess their likelihood of developing COVID-19, and 17.5% were unaware of the difference between a mild and severe infection. Twenty-three percent (23.3%) were unfamiliar with the materials needed in an acute illness situation. CONCLUSION: Psychological disaster preparedness is reasonable, although lacking in specific domains. Timely but focused interventions can be a cost-efficient administrative exercise, which federal agencies may prioritize working on.


Subject(s)
Adaptation, Psychological , Coronavirus Infections/complications , Health Literacy/standards , Pneumonia, Viral/complications , Stress, Psychological/psychology , Adult , Aged , Aged, 80 and over , COVID-19 , Coronavirus Infections/epidemiology , Coronavirus Infections/psychology , Female , Health Literacy/statistics & numerical data , Humans , India/epidemiology , Male , Middle Aged , Pandemics/statistics & numerical data , Pneumonia, Viral/epidemiology , Pneumonia, Viral/psychology , Surveys and Questionnaires
17.
Rheumatol Int ; 41(2): 257-273, 2021 02.
Article in English | MEDLINE | ID: covidwho-1002076

ABSTRACT

Sudden cardiac death is commonly seen due to arrhythmias, which is a common cardiac manifestation seen in COVID-19 patients, especially those with underlying cardiovascular disease (CVD). Administration of hydroxychloroquine (HCQ) as a potential treatment option during SARS-CoV-2, initially gained popularity, but later, its safe usage became questionable due to its cardiovascular safety, largely stemming from instances of cardiac arrhythmias in COVID-19. Moreover, in the setting of rheumatic diseases, in which patients are usually on HCQ for their primary disease, there is a need to scale the merits and demerits of HCQ usage for the treatment of COVID-19. In this narrative review, we aim to address the association between usage of HCQ and sudden cardiac death in COVID-19 patients. MEDLINE, EMBASE, ClinicalTrials.gov and SCOPUS databases were used to review articles in English ranging from case reports, case series, letter to editors, systematic reviews, narrative reviews, observational studies and randomized control trials. HCQ is a potential cause of sudden cardiac death in COVID-19 patients. As opposed to the reduction in CVD with HCQ in treatment of systemic lupus erythematous, rheumatoid arthritis, and other rheumatic diseases, safe usage of HCQ in COVID-19 patients is unclear; whereby, it is observed to result in QTc prolongation and Torsades de pointes even in patients with no underlying cardiovascular comorbidity. This is occasionally associated with sudden cardiac death or cardiac arrest; hence, its clinical efficacy needs further investigation by large-scale clinical trials.


Subject(s)
Antirheumatic Agents/adverse effects , COVID-19/drug therapy , Death, Sudden, Cardiac/etiology , Hydroxychloroquine/adverse effects , Antirheumatic Agents/administration & dosage , COVID-19/complications , Humans , Hydroxychloroquine/administration & dosage , Pandemics , Rheumatic Diseases/drug therapy , Risk Assessment , SARS-CoV-2
18.
J Clin Rheumatol ; 27(1): 31-33, 2021 Jan 01.
Article in English | MEDLINE | ID: covidwho-990968

ABSTRACT

BACKGROUND: The coronavirus disease (COVID-19) pandemic and its subsequent effects on health care systems have significantly impacted the management of chronic rheumatic diseases, including systemic sclerosis (SSc). METHODS: In this context, a 25-item anonymized e-survey was posted on the Twitter and Facebook e-groups and pages of various scleroderma organizations and patient communities to assess the problems faced by patients with SSc during the pandemic, with a focus on effects on the disease, drug procurance, continuity of medical care, and prevalent fears among patients. RESULTS: Of the 291 participants (median age of 55 [43.5-63] years, 93.8% females), limited systemic sclerosis was the most common diagnosis (42.3%). Many patients experienced problems attributable to the COVID-19 pandemic (119, 40.9%), of which 46 (38.7%) required an increase in medicines, and 12 (10.1%) of these needed hospitalizations for disease-related complications. More than one-third (36.4%) were on glucocorticoids or had underlying cardiovascular risks (39%) that would predispose them to severe COVID-19.A significant proportion (38.1%) faced hurdles in procuring medicines or experienced disruption in physiotherapy sessions (24.7%). One-quarter (24.1%) felt it was difficult to contact their specialist, whereas another 7.2% were unable to do so. Contracting COVID-19 was the most prevalent fear (71.5%), followed by infection in the family (61.9%), and a flare of the disease (45.4%). Most respondents preferred teleconsultations (55.7%) over hospital visits in the pandemic period. CONCLUSION: The results of the patient survey suggest that the COVID-19 pandemic has affected many patients with SSc and may translate to poorer outcomes in this population in the postpandemic period.


Subject(s)
COVID-19/epidemiology , Health Services Accessibility , Scleroderma, Systemic/complications , Scleroderma, Systemic/therapy , Adult , Female , Humans , Male , Middle Aged , Pandemics , SARS-CoV-2 , Surveys and Questionnaires
19.
J Korean Med Sci ; 35(45): e398, 2020 Nov 23.
Article in English | MEDLINE | ID: covidwho-976184

ABSTRACT

The coronavirus disease 2019 (COVID-19) pandemic has led to a massive rise in survey-based research. The paucity of perspicuous guidelines for conducting surveys may pose a challenge to the conduct of ethical, valid and meticulous research. The aim of this paper is to guide authors aiming to publish in scholarly journals regarding the methods and means to carry out surveys for valid outcomes. The paper outlines the various aspects, from planning, execution and dissemination of surveys followed by the data analysis and choosing target journals. While providing a comprehensive understanding of the scenarios most conducive to carrying out a survey, the role of ethical approval, survey validation and pilot testing, this brief delves deeper into the survey designs, methods of dissemination, the ways to secure and maintain data anonymity, the various analytical approaches, the reporting techniques and the process of choosing the appropriate journal. Further, the authors analyze retracted survey-based studies and the reasons for the same. This review article intends to guide authors to improve the quality of survey-based research by describing the essential tools and means to do the same with the hope to improve the utility of such studies.


Subject(s)
Publishing , Research , Authorship , COVID-19/pathology , COVID-19/virology , Humans , Periodicals as Topic , Publishing/standards , SARS-CoV-2/isolation & purification , Surveys and Questionnaires
20.
Front Public Health ; 8: 571419, 2020.
Article in English | MEDLINE | ID: covidwho-921174

ABSTRACT

Background: The private medical sector is a resource that must be estimated for efficient inclusion into public healthcare during pandemics. Methods: A survey was conducted among private healthcare workers to ascertain their views on the potential resources that can be accessed from the private sector and methods to do the same. Results: There were 213 respondents, 80% of them being doctors. Nearly half (47.4%) felt that the contribution from the private medical sector has been suboptimal. Areas suggested for improved contributions by the private sector related to patient care (71.8%) and provision of equipment (62.4%), with fewer expectations (39.9%) on the research front. Another area of deemed support was maintaining continuity of care for non-COVID patients using virtual consultation services (77.4%), tele-consultation being the preferred option (60%). 58.2% felt that the Government had not involved the private sector adequately; and 45.1% felt they should be part of policy-making. Conclusion: A streamlined pathway to facilitate the private sector to join hands with the public sector for a national cause is the need of the hour. Through our study, we have identified gaps in the current contribution by the private sector and identified areas in which they could contribute, by their own admission.


Subject(s)
COVID-19 , Pandemics , Cross-Sectional Studies , Humans , India/epidemiology , Pandemics/prevention & control , Private Sector , SARS-CoV-2
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