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Introduction: Due to the presence of ACE 2 receptors in the diaphragm, its involvement is likely among patients with Covid 19. This study aimed to describe the presence of diaphragm dysfunction among patients who have recovered from Covid 19. Method(s): The thickness fraction (TF) of the diaphragm was assessed via ultrasonography in supine or semirecumbent posture in the right hemidiaphragm in the zone of apposition. A TF of less than 20% was classified as diaphragm dysfunction. Result(s): A total of 50 (males 34) with a mean age of 49.36 years and recovered from acute Covid were enrolled in the study. Among these 50 participants, 11, 12, and 27 had recovered from mild, moderate, severe Covid, respectively. Overall, 37(74%) subjects were hospitalized, 13 (26%) cases were home quarantined;30 (60%) subjects required oxygen during the course of illness. The average weeks from the onset of symptoms to enrolment was 7.1 weeks. Among the study participants, 9 (18%) subjects (8 males and 1 female) had diaphragm dysfunction (thickness fraction less than 20%). Among subjects who were managed at the hospital (n=37), diaphragm dysfunction was observed in 8 (21.6%). Of patients who had diaphragm dysfunction, 3 out of 9 had mild disease, whereas 6 of 9 (66.6%) subjects had severe illness. sub7 out of 9 (77.7%) subjects were hospitalized and 6 required oxygen during the illness. Conclusion. A significant percentage of COVID-19 survivors had diaphragm dysfunction which may also attribute to the persistent shortness of breath. There is an urgent need for large-scale (nationwide) assessment of diaphragm function among the survivors.
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Introduction: The persistence of symptoms beyond 4 weeks of SARS-CoV-2 infection is referred to as long COVID. There is lack of data about the clinical determinants and natural history of this condition. Aims & objectives: We aimed to determine the risk factors, symptomatology, spirometric abnormalities and evolution of long COVID over a 1-year period. Method(s): We enrolled adult patients at 1-4 months after diagnosis of COVID-19. The demographics, COVID-19 history, clinical symptoms and spirometric results were recorded. Follow-up assessments were done in-person or telephonically at 4-8 months and 8-12 months, respectively. Result(s): We enrolled 128 patients (69% male) with median (IQR) age of 49 (37-56) years. Among these, 99 (77%) needed hospitalization, and 47 (37%) received oxygen for COVID-19. At the 1st assessment at median (IQR) of 64.5 (39.5-90) days after COVID-19 onset, 86 (67%) patients had symptoms, most commonly dyspnea (34%), fatigue (19%) and cough (19%). Reduced FVC (<80% of predicted) was found in 61% subjects. On multivariate analysis, the predictors of symptomatic long COVID were female gender (OR, 4.1;95% CI: 1.5-11;p=0.006) and dyspnea during acute COVID-19 (OR, 3.6;95% CI:1.1-11.3;p=0.03). The predictors of reduced FVC were dyspnea (OR, 4.4;95% CI: 1.6-12;p=0.004) and oxygen therapy (OR, 5.6;95% CI: 1.5-21;p=0.01) during acute COVID-19. The proportion of symptomatic patients reduced between 1st and 2nd assessment (67% vs 37%, p<0.001) and then plateaued at 3rd assessment (42%). Conclusion(s): Persistent symptoms are common over a 1-year follow-up among survivors of COVID-19. Female gender and dyspnea during acute COVID-19 may predict development of long COVID.
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Background: COVID-19 disease, a pandemic for more than two years, has major morbidity and mortality related to pulmonary involvement. Chest radiography is the main imaging tool for critically ill patients. As the availability of arterial blood gas analysis is limited in the Level I and II healthcare centres, which are major partners in providing healthcare in resource-limited times, we planned the present study. Objectives: To assess the role of chest radiography in predicting the need for oxygen/ventilator support in critically ill COVID-19 patients. Methods: This hospital-based, retrospective study included 135 patients who needed oxygen/ventilator support and had optimal-quality chest radiographs at admission. All the chest X-rays were evaluated and a severity score was calculated on a predesigned pro forma. Statistical evaluation of the data obtained was done using appropriate tools and methods. Results: Males outnumbered females, with a mean age of 54.35 ± 14.49 years. More than 72% of patients included in our study needed ventilator support while the rest needed oxygen support. There was a significant statistical correlation between the chest radiograph severity score and SPO2 /PaO2 levels in our study. Using a cut-off value >8 for the chest radiograph severity score in predicting the need for ventilator support in a Covid-19 patient, the sensitivity, specificity and accuracy was 85.7%, 92.5% and 89.5%, respectively. Conclusion: Chest radiography remains the mainstay of imaging in critically ill COVID-19 patients when they are on multiple life-support systems. Though arterial blood gas analysis is the gold standard tool for assessing the need for oxygen/ventilator support in these patients, the severity score obtained from the initial chest radiograph at the time of admission may also be used as a screening tool. Chest radiography may predict the need for oxygen/ventilator support, allowing time for patients to be moved to an appropriate-level healthcare centre, thus limiting morbidity and mortality.
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Background of the study: All over the globe anxiety was present among young adolescence. They are fear of infection and away from real education and fewer confidants to manage Covid pandemic situation.Objectives: Study investigated to assess the pre and posttest level of knowledge on social anxiety among First year nursing students in Covid-19 pandemic.Material and Methods: Experimental study done to assess the effectiveness of level of knowledge on reduction of social anxiety among first year nursing students in Covid-19 Pandemic among 100 Basic BSc 1st year nursing students. Self-prepared questionnaire selected as a tool for pre and post intervention which was validated by the expert .Ethical permission taken before conduction of study .samples chosen as per inclusion criteria of the study. Samples were explained well the purpose of the study .Pre taken with help of questionnaire and after seven days post taken and data analyzed as per objectives of the study.(Level of knowledge score was good8-29 ,average 4-7and poor 0-3 )Results: In this study pretest knowledge score was 16%, 72% and 12% as poor, average and good knowledge .post-test knowledge score was 0 %, 16% and 84% as poor, average and good knowledge. Pretest test SD1.565 and posttest SD 1.1.69 which was extremely significant.(p<0.ooo1)Conclusion: Finding of the study shows that self-instructional module was effective to increase the level of knowledge among the 1st year Basic B.Sc. student in covid-19 Pandemic.
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Objectives: Angiotensin-converting enzyme inhibitors (ACEIs)/angiotensin II receptor blockers (ARBs) are recommended for patients with comorbid diabetes mellitus and hypertension due to their favorable impact on microvascular and macrovascular events, cardiovascular outcomes, and mortality. Poor adherence to ACEI/ARB is a major public health concern. Motivational interviewing (MI) intervention is an effective patient-centered approach to improve adherence. The objective of this study was to evaluate the effectiveness of a telephonic MI intervention conducted by pharmacy students, tailored by the past ACEI/ARB adherence trajectories among nonadherent patients with comorbid diabetes mellitus and hypertension. Methods: Patients continuously enrolled in a Medicare Advantage Plan from July 2017-July 2021 with an ACEI/ARB prescription between July 2017-December 2017 were identified. Group-based trajectory modeling (GBTM) was used to identify 4 distinct patterns of ACEI/ARB adherence: adherent, gaps in adherence, gradual decline, and rapid decline in adherence. Patients from the 3 nonadherent trajectories were randomized either into MI intervention or control group. The intervention group received an initial call followed by 5 follow-up calls. The primary outcome was adherence measured as proportion of days covered (PDC) ≥ 0.80 for 1-year post-MI implementation. Multivariable logistic regression model evaluated the effect of the intervention on ACEI/ARB adherence. Results: This study included 240 patients who received intervention and 480 randomly selected controls. Patients who had received ≥ 4 calls were more likely to be adherent than those who received ≤ 3 follow-up calls (OR=2.01;P=0.01) despite the gaps in follow-up calls due to the COVID-19 outbreak. Other significant predictors of adherence were baseline adherence trajectories, number of other medications on the index date, prevalent users, regimen complexity, and CMS risk score. Conclusions: At 1 year, patients who received ≥ 4 calls had significantly better adherence than controls. MI intervention by pharmacy students has been demonstrated to improve adherence on a long-term basis.
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Background: Young people are presenting to services in greater numbers and with higher levels of psychological distress and acuity, greater clinical complexity and reduced capacity in their support networks in the context of the COVID-19 pandemic. Despite this there is often a delay in accessing timely youth-oriented care. Through COVID-19 enhancement funding, the youth Brief Intervention Service (yBIS) has been implemented in the Eastern Suburbs Mental Health Service (ESMHS), Sydney, Australia, adapted from the Brief Lifeworks Intervention Program (BLIP) (Project Air Strategy, 2019). Objectives: To report on the yBIS model of care and discuss effectiveness and implementation data for yBIS. Methods: yBIS is offered to young people aged 12-25 years who present to ESMHS in crisis with suicidal ideation and/or self-harm. Participants, together with a parent or guardian, are offered up to four sessions (face-to-face or virtual) with yBIS clinicians, comprising a psychiatrist, psychologists and a nurse specialist, over a 3- to 4-week period. A battery of measures is being collected at baseline, discharge and longer-term follow-up. Primary effectiveness outcomes are level of suicidal ideation and frequency of self-harm. A range of secondary effectiveness outcomes and implementation components will be explored. Findings: yBIS began servicing youth in crisis in June 2021. We anticipate analysing effectiveness-implementation data on 80 participants in March 2022. Conclusion: yBIS may be a feasible and effective service for youth in crisis. There is potential for yBIS to be scaled up pending the results of the service evaluation as one response to the current crisis in youth mental health presentations.
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The goal to promote human limits is for Artificial Intelligence (AI). It takes a posture on public administrations, represents the increasing availability of regaining clinical data and the rapid creation of intelligent strategies. The need to stress the need to use AI in the fight against the COVID-19 crisis. The paper outlines the main role played by Ai technologies in this unprecedented war and introduces a survey of AI methods used for multiple purposes in the fight against the outbreak of COVID-19. This paper also explains how the body temperature and coughing of the incoming person are assessed and whether the incoming person has not a protective facial mask. Should either of the above tests disqualify the participant, an alarming device invokes the local officials;the entrant may otherwise enter the premises after his/her hand has been sanitized. © 2022 Author(s).
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The Latest emergency issues are impacting the world as a result of the new 2019 corona virus rise and pandemic. It has spread to the worldwide and afflicted people to Covid-19. The virus transmitting has regarded as being transmitted by individuals who find it a convenient disease explosion. While coughing and sneezing the infection spreads from the infectious droplets. Although in the air, these droplets will still survive and transfer the virus on to humans. In worldwide, robots have been used to alleviate the proliferation of new corona virus infections, COVID-19 with food preservation, food supplies, sanitation tasks, spraying disinfectant, temperature monitoring, hand sanitizers distributing, work on sensitizing, etc. For fast strategizing, that are considered hazardous for human beings. This paper discuss the difficulties and opportunities associated with using humanoid robots to minimize the risk of spread of COVID-19 in.public healthcare. The primary application of humanoid robots is the minimization of individual interaction in public places, and the provision of containment to hygiene, disinfectants and helping. The following discussion aims to underline the value of humanoid robot's purposes in specific and to link their use as the COVID-19 perspectives. Throughout the testing, review and diagnosis of a vulnerability and for subset of events, artificial intelligence plays a crucial role. It may be used during potential for the forecast of events but also to record the number of alternative cases, restored instances and deaths. Technology based on artificial intelligence is being used to provide outstanding services such as the detection and substitution of drugs for the care of employees by robotics for the provision of prescriptions and nutrition in clinics. It also disinfects the substances in response to the spread of Covid-19. © 2022 Author(s).
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Structure-based drug discovery (SBDD) utilizes the three-dimensional (3D) structure of a target protein to identify the lead compounds. This medium is then considered a viable solution based on its availability and correlation with a particular disease. In the case of pandemics like COVID 19, shortening drug development time can save millions of people worldwide;for such a task, classical drug discovery methods will take a long time. Hence, researchers worldwide actively incorporated machine learning (ML) into the drug discovery process, particularly in SBDD, to minimize the lead optimization time. ML uses statistical methods to make a computer perform tasks, take a critical decision, and automate this entire process without being explicitly programmed. With this, the computer can discover new insights about data and unknown patterns crucial to decide the therapeutic use of lead compounds as drugs. The use of ML in the drug discovery field is not new, and it spans an ample research space. By integrating artificial intelligence with ML techniques, viable targets can be found using data clustering, regression, and classification from vast omics databases and sources. In this chapter, we will discuss the methods and applications of ML in SBDD. © 2022 Elsevier Inc. All rights reserved.
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Introduction: Medication adherence is important in ensuring the maximum effect of oral endocrine therapy (OET) in hormone receptor-positive breast cancer (HR+ BC) patients. Low medication adherence is more seen in racial and ethnic minority patients of lower socioeconomic status. COVID-19 pandemic has further introduced complexities that have impacted patients' medication-use behaviors. Our goal was to (1) assess the medication adherence to OET in racial and ethnic minority patients of lower socioeconomic status with HR+ BC and (2) assess the impact of the COVID-19 pandemic on their OET adherence. Patients and Methods: A retrospective, single-center study from September 2019 through September 2020 was conducted. The primary endpoint was adherence rate during the 6 months prior (September 2019-February 2020) and 6 months after (April 2020-September 2020) the COVID-19 pandemic started in the United States. The following three racial/ethnic groups were compared: Non-Hispanic White/Caucasian, Black/African American, and Hispanic/Latino. Chi-Square and Student's t-tests were used to compare the adherent and nonadherent groups. The secondary endpoint was to identify predictors of nonadherence to OET. Multivariable logistic regression model was used to assess predictors of S nonadherence. Results: Out of 270 patients, a total of 251 patients had a refill for an OET before COVID-19 with a mean proportion of days covered (PDC) of 0.72%. Of these, 140 (55.78%) were adherent and 111 (44.22%) were nonadherent. A total of 194 patients had a refill for an OET during COVID-19 with a mean PDC of 0.67%. Of these, 83 (42.78%) were adherent and 111 (57.22%) were nonadherent. A total of 187 patients had a refill for OET before and during the COVID-19 pandemic. There was a significant difference in the adherence before and during the pandemic when PDC was used as a continuous (p <0.0001, Student's paired t-test) or a categorical variable (p <0.0001, McNemar chi-square test). In a multivariate analysis of data before the pandemic, Black/African American and White/Caucasian were less likely to be adherent compared to Hispanic/Latino (Black/African American: odds ratio [OR], 0.36;95% confidence interval [CI], 0.18-0.723;White/Caucasian: OR, 0.25;95% CI, 0.074-0.853). Patients with diabetes mellitus (DM) were more likely to be adherent compared to patients without DM (OR, 2.364;95% CI, 1.199-4.662), and patients with hypertension (HTN) were less likely to be adherent compared to patients without HTN (OR, 0.481;95% CI, 0.236-0.981). Patients who were prescribed aromatase inhibitors were more likely to be adherent compared to patients that were prescribed tamoxifen (OR, 0.484;95% CI, 0.235-0.998). Patients diagnosed with invasive BC (stages 1-4) were more likely to be adherent compared to those diagnosed with non-invasive (in situ) tumors or ductal/lobular hyperplasia. During the pandemic, patients who used home delivery were more likely to be adherent compared to those who did not use home delivery (OR, 11.574;95% CI, 2.45-54.55). There was no significant difference in the proportion of patients using home delivery between different racial and ethnic groups. Conclusion: OET adherence was reduced during the COVID-19 pandemic in racial and ethnic minority patients with low socioeconomic status. Tamoxifen therapy, Black/African American, and White/Caucasian origin, not having DM, having HTN, and diagnosed with non-invasive BC were associated with OET nonadherence in patients before the COVID-19 pandemic. Whereas, not using home delivery for OET medications predicted nonadherence in patients during the COVID-19 pandemic.
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COVID-19 or coronavirus or novel coronavirus, whatever the name is, becomes a buzz in the year 2020, which made the whole world prison and cost several lives. It disturbed the countries' economies and made it fall like a house of cards, and several people lost their jobs, income sources, and it has been a penalty for several students. Several organizations got affected, and some organizations shut down entirely where some of the organizations gained huge profits. This chapter performed a rigorous study to know how salaried people and students' lives are affected during this pandemic. We will also discuss what kind of significant changes came into the entire world's education system, how did this pandemic affect the jobs around the world, and how did it create opportunities for new businesses at the same time to grow. © 2021 Nova Science Publishers, Inc.
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The elephant in the room and theme of the last two years;The pandemic has caused misery and harm to countless individuals. Its sheer scale of destruction and pain can and will never be fathomable. One of the many reasons why the pandemic is so unnerving is due to the fact that people cannot gather in public places and closed venues. Places like schools, offices, concerts, parks, malls etc. are major hotspots for the virus to spread easily and quickly. The best means to make sure that we can keep these venues opened while, at the same time, make sure everyone inside is safe and risk-free, is to test everyone entering. This paper deals with a highly accurate, low cost and effective health screening system. It is essentially a hyper-smart and convenient way to screen and monitor the health vitals of everyone entering a venue. It employs every means necessary to properly understand the state of health well-being of a potential entrant. The vitals that it measures ranges from blood oxygen saturation level (SpO2), Heart Rate and Body Temperature. It also has safety contingency measures like Mask detection and RFID verification. All this can be used for contact tracing as well as predictive diagnosis. © 2021 IEEE.
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Modeling infection spread during pandemics is not new, with models using past data to tune simulation parameters for predictions. These help in understanding of the healthcare burden posed by a pandemic and responding accordingly. However, the problem of how college/university campuses should function during a pandemic is new for the following reasons: (i) social contact in colleges are structured and can be engineered for chosen objectives;(ii) the last pandemic to cause such societal disruption was more than 100 years ago, when higher education was not a critical part of society;(iii) not much was known about causes of pandemics, and hence effective ways of safe operations were not known;and (iv) today with distance learning, remote operation of an academic institution is possible. As one of the first to address this problem, our approach is unique in presenting a flexible simulation system, containing a suite of model libraries, one for each major component. The system integrates agent-based modeling and the stochastic network approach, and models the interactions among individual entities (e.g., students, instructors, classrooms, residences) in great detail. For each decision to be made, the system can be used to predict the impact of various choices, and thus enables the administrator to make informed decisions. Although current approaches are good for infection modeling, they lack accuracy in social contact modeling. Our agent-based modeling approach, combinedwith ideas from Network Science, presents a novel approach to contact modeling. A detailed case study of the University of Minnesota's Sunrise Plan is presented. For each decision made, its impact was assessed, and results were used to get a measure of confidence. We believe that this flexible tool can be a valuable asset for various kinds of organizations to assess their infection risks in pandemic-time operations, including middle and high schools, factories, warehouses, and small/medium-sized businesses.
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Introduction: COVID-19 pandemic has placed the health systemworldwide in unprecedented stress, therefore, prompt identification and management of patients having severe disease is essential fortriaging of patients at the time of admission.Aims &Objectives: To identify hematological biomarkers ofCOVID-19 disease severity in patients admitted in a tertiary carehospital.Materials &Methods: A retrospective study was conducted over aperiod of 17 months (20th March 2020-19 August 2021) on 7416COVID-19 patients. Patients with cancers, pregnancy and chronichematological diseases were excluded from the study. Patients wereclassified clinically as per severity of disease as non-severe (asymptomatic, mild, moderate) or severe and their hematological parameterswere analyzed.Mann-Whitney test was used to compare between the groups. Optimal predictive cut off points for the variables were defined by receiveroperating characteristic (AUC) curve to dichotomize the variables.Univariate analysis was performed to screen out independent variables to be used in the binary logistic regression (BLR). A p valueof< = 0.05 was considered as statistically significant.Result: Age, duration of hospital stay, RBC count, WBC, Plateletcount, RDW, Neutrophils %, Absolute neutrophil count (ANC),Absolute monocyte count (AMC), NLR, PLR, NMR were statisticallyhigher whereas hemoglobin, hematocrit, MCHC, lymphocyte %,Absolute lymphocyte count (ALC), Eosinophils %, Absolute eosinophil count (AEC), Monocytes %, Basophils %, Absolute Basophilcount (ABC) and Lymphocyte Monocyte ratio (LMR) were lower insevere group. MCV and MCHC were not significant, so wereexcluded from the logistic regression model. All variables were significant in univariate analysis. Age (>42 yrs), duration of hospitalstay (>10 days), RBC count (B 4.33 106/lL),WBC count (> 7.73103/lL), RDW (>14.8%), Neutrophils (>71.7%), Eosinophils(B 0.3%), Monocytes (B 5%), ALC (B 1.01 103/lL), LMR(B 3.125) with adjusted odd ratio of 1.8, 1.5, 1.3,1.3, 1.4, 2.0, 2.1, 1.5,2.0 and 1.3 respectively were found to be significant predictors ofseverity.Conclusions: Age, duration of hospital stay, RBC count, WBC,RDW, Neutrophils %, Eosinophils %, Monocytes %, ALC, LMRshould be assessed and monitor at the earliest to halt unfavorableoutcome of mortality or morbidity.
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Introduction: The corona virus disease-2019 (COVID-19) pandemic has been associated with decrease in the rate of myocardial infarction (MI), and this is likely related to patients delaying seeking care due to COVID-19 concerns. Methods: In this retrospective observational study, we compared all patient encounters who presented with MI to Ascension Saint Agnes Hospital, Baltimore, MD from March to December 2020 with a cohort of patient encounters who presented with MI during an equivalent period in 2019. We analyzed the data using Statistical Package for Social Sciences (SPSS) and used two sample t-test and Chi-square x to compare the outcomes between the two cohorts as appropriate. Results: We had 275 MI admissions that met our inclusion criteria. When comparing MI encounters in 2020 with encounters in 2019, there were no significant differences in mortality (2.1% vs. 4.5%, p=0.274), acute renal failure(14.9% vs. 18.7%, p=0.403), or intensive care unit admission (7.1% vs. 7.5%, p=0.892). There were no significant differences in modalities of treatment including cardiac catheterization (94.3% vs. 95.5%, p=0.652), or medical treatment alone (13.5% vs. 18.7%, p=0.241) in 2020 vs. 2019. Referrals for coronary artery bypass graft surgery (CABG) were significantly higher in 2020 than in 2019 (8.5% vs. 3.0%, p=0.050). When comparing patients who presented during the first 5 months of the pandemic (March-July) with patients who presented in the last 5 months of the pandemic in 2020 (August-December);there were significant decrease in rate of cardiac catheterization (90.5% vs. 98.5%, p = 0.041), and significant increase in rate of medical treatment alone (18.9% vs. 7.5%, p = 0.047) in the first 5 months. Conclusions: The first five months of the pandemic were associated with a significant decrease in rates of pursuing cardiac catheterization along with an increase rates of medical treatment alone compared with the following five months.
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Background/Purpose: Teleconsultations have been an important means of communicating with the patients due to the travel restrictions during the COVID-19 pandemic. We assessed its usefulness and patients' views on their future use. Methods: Patients who received teleconsultations using telephone and WhatsApp during the COVID-19 pandemic were screened and asked to fill an online questionnaire seeking their views regarding teleconsultations in terms of their usefulness, cost-effectiveness, feasibility for future use. Only those patients were included who were of age ≥18 years and had had at least 2 physical visits in the past at our hospital. Information regarding their demographic features, disease characteristics like diagnosis, duration of disease was also collected. For the final analysis, 230 responses out of the 410 participants were included for who all the desired information was available. Results: Among the 230 patients, mean age was 38 years with a mean duration of disease of 4.25 years, 68 (29%) were male, 190 (83%) had rheumatoid arthritis, 100 (43%) patients assessed their disease condition as bad/severe and 90 (39%) depended on others to use a smartphone for teleconsultations. Among these patients, 131 (57%) patients missed their scheduled OPD appointment, 115 (50%) reported worsening of symptoms, 81 (35%) needed to consult a local physician for their problems. Regarding teleconsultations, 142 (62%) patients reported benefit with the teleconsultation service and 181 (79%) graded it ≥3 on a scale of 1-5 where 5 meant very useful (Figure 1). A total of 161 (70%) patients wanted to use it for future consultations. The commonest reasons for choosing teleconsultation were ease of appointment (52%), avoiding the need of travelling (22%) and cost-effectiveness (22%). Conclusions: Teleconsultation is a useful alternative to physical consultation with a high satisfaction rate. It could be a useful costeffective tool in a resource limited setting of developing countries like India.