Work stress, office clutter and employees' performance during COVID-19 waves

PurposeThe aim of the study is to test the integrated model involving work stress, office clutter and employee performance with the moderating roles of training and self-discipline (SD) after the re-opening of the banks after the COVID-19 wave.Design/methodology/approach The study used 333 respondents from banking industry, whose responses were recorded using a closed ended questionnaire. The authors used partial least square path anaysis to analyze the data.Findings Work stress significantly increases office clutter, which harms the employees' performance. Moreover, SD and training significantly improve employees' performance by reducing work stress and thereby office clutter. There are various mechanisms through which both these factors reduced stress and office clutter.Practical implications The employee's performance can be enhanced with lower levels of office clutter. The office clutter can be managed through having lower levels of stress and providing people with training and inculcating SD among them. A greater understanding of the factors that count toward office clutter might help bank managers and employees to address the issues related to their performance.Originality/value The authors have proposed a new framework involving conservation of resources theory for the employees' performance. They posit employees' performance is an organizational resource, which can be conserved as well as enriched both by employers and employees through their own contribution.

Ensemble Deep Learning Framework for Situational Aspects-Based Annotation and Classification of International Student's Tweets during COVID-19

As the COVID-19 pandemic swept the globe, social media plat-forms became an essential source of information and communication for many. International students, particularly, turned to Twitter to express their struggles and hardships during this difficult time. To better understand the sentiments and experiences of these international students, we developed the Situational Aspect-Based Annotation and Classification (SABAC) text mining framework. This framework uses a three-layer approach, combining baseline Deep Learning (DL) models with Machine Learning (ML) models as meta-classifiers to accurately predict the sentiments and aspects expressed in tweets from our collected Student-COVID-19 dataset. Using the pro-posed aspect2class annotation algorithm, we labeled bulk unlabeled tweets according to their contained aspect terms. However, we also recognized the challenges of reducing data's high dimensionality and sparsity to improve performance and annotation on unlabeled datasets. To address this issue, we proposed the Volatile Stopwords Filtering (VSF) technique to reduce sparsity and enhance classifier performance. The resulting Student-COVID Twitter dataset achieved a sophisticated accuracy of 93.21% when using the random forest as a meta-classifier. Through testing on three benchmark datasets, we found that the SABAC ensemble framework performed exceptionally well. Our findings showed that international students during the pandemic faced various issues, including stress, uncertainty, health concerns, financial stress, and difficulties with online classes and returning to school. By analyzing and summarizing these annotated tweets, decision-makers can better understand and address the real-time problems international students face during the ongoing pandemic.

Perspectives of a Predominantly Marginalized Population on Telemedicine

Purpose of Study: Telemedicine has become a common option for healthcare delivery in the post-COVID-19 era. There are advantages, but the barriers to care for children with medical complexity (CMC) and marginalized populations have not been well-described. This study assessed parental perception of telemedicine in the care of their children. Methods Used: A REDcap survey was distributed to parents of hospitalized patients close to discharge to examine their attitudes regarding outpatient telemedicine with a focus on the post-discharge follow-up visit. Summary of Results: A total of 78 parents responded to our survey. A majority (58%) identified themselves as an ethnic minority. About 47% of parents completed college or postgraduate education;the rest had a high school diploma or some college education. Half (50%) of the parents reported a family income of <$100,000. Of the 78, 50% had used telemedicine previously, and a majority (76%) preferred in-person visits. Of those who belonged to a minority population, 80% preferred in-person visits after hospital discharge. Fifty-seven of the parents answered further questions about telemedicine and their child's medical complexity. Of these 57, 53% had a CMC, requiring specialized care and only 20% agreed or strongly agreed that it was difficult to take their child to in-person visits. Fifty-three out of the 78 parents provided a free text response about their thoughts on telemedicine visits. Common themes about advantages of in-person visits were a) preference for a physician's physical exam b) in-person visits were more personal and facilitated clearer communication and c) in-person visits provided more accurate? care compared to telemedicine (See Figure). Internet or computer access as a barrier was only mentioned by 3 parents. The main advantage of telemedicine mentioned was convenience. Conclusion(s): Our study shows that most parents prefer in-person visits, especially after hospital discharge. Our results may not apply to other populations as most of our patients were medically complex and belonged to a minority population. To increase parental support of telemedicine, techniques to improve family confidence in visual assessment and communication are required. Larger studies are needed to identify the needs of patients and families with a focus on the child's medical needs.

Prescribing of oral antibacterial drugs in primary care out-of-hours services: a scoping review

Introduction: The rapid spread of antimicrobial resistance (AMR), which causes a serious threat to both human health and the global economy, is primarily linked to the overuse and misuse of antibacterial drugs. The AMR crisis is significantly impacted by the use of antibacterial drugs in primary care (1). Within these settings, oral antibacterial drugs are considered one of the most frequently prescribed group of medicines. It has been claimed that within primary care, the proportion of antibacterial drug prescribing is higher outside the regular working hours (out-of-hours (OOH) services) compared to in-hours (IH) services (2). Aim(s): To identify the existing body of literature around oral antibacterial drug prescribing within primary care OOH services. Method(s): The scoping review was guided by the Joanna Briggs Institute manual and reported in accordance with the PRISMA-ScR. Seven electronic databases (Medline, Embase, Emcare, CINAHL, Scopus, Web of Science, and Cochrane Library) were systematically searched, and the results were screened against pre-defined eligibility criteria. Original and secondary analysis studies that addressed oral antibacterial prescribing in OOH primary care and were published in English were included. Titles and s were independently screened by three reviewers. A pre-piloted extraction form was used to extract relevant data. A narrative synthesis approach was used to summarise the results. Result(s): The initial search yielded 834 records. Upon screening, 28 publications fulfilled the eligibility criteria. Included studies originated from nine high-income countries, with the most frequent being the United Kingdom (six studies, 21.4%) followed by Belgium (five studies, 17.9%). Literature on antibacterial prescribing in OOH services was mostly from quantitative studies (23 studies, 82.14%), with only a few employing a qualitative design (five studies, 17.86%). Different themes and sub-themes were identified across these studies. The majority discussed antibacterial prescribing data in terms of the commonly prescribed medications and/or associated conditions. Eleven studies provided a comparison between IH and OOH settings. Seven studies reported the trends of prescribing over time;of these, three explored prescribing trends before and during COVID-19. The impact of intervention implementation on prescribing was investigated in two studies, an educational intervention in one study and the use of an interactive booklet in the other study. Four studies assessed the quality/appropriateness of prescribing either by adherence to guidelines or antibiotic prescribing quality indicators. Limited studies explored prescribing predictors and patients' expectations and satisfaction with OOH services. In contrast, qualitative studies focussed more on exploring prescribers' experiences, perspectives, behaviours, and the challenges they face during consultations within OOH settings which may influence their decision-making process. Of these, one study explored why patients consult OOH services and how they communicate their problems. Conclusion(s): This review shows the key areas around oral antibacterial prescribing in primary care OOH services. While there is a satisfactory number of published articles covering various areas within OOH, the use of different approaches to OOH across countries may confound the comparison of practice. A strength of this work is using three reviewers to screen identified records independently. Further research is needed to provide a better understanding of current practice in these settings and how it may be contributing to AMR.

Insilico Screening for Identification of Hits against SARS-Cov-2 Variant of Concern B.1.617 and NSP12 Mutants by Molecular Docking and Simulation Studies

Human coronaviruses (HCoVs), including severe acute respiratory syndrome coronavirus (SARS-CoV) and 2019 novel coronavirus (2019-nCoV), also known as SARS-CoV-2, have caused global epidemics with high morbidity and mortality. Active research on finding effective drugs against 2019-nCoV/SARS-CoV-2 is going on. In silico screening represents the best approach for hits identification and could shorten the time and reduce cost compared to de novo drug discovery. Recently, CoV2 mutations have been a big concern in India, particularly on non-structural proteins (NSPs) and Spike Protein (B.1.617) which are the key targets that play a pivotal role in mediating viral replication and transcription. Herein, this study analyzed the NSPs and spike's structural aspects of mutant strains of SARS-CoV-2. The three-dimensional structures of NSPs and S Spike proteins were retrieved from the protein data bank or modeled. And a dataset of an antiviral compound library containing 490,000 drug-like ligands and structurally diverse biologically active scaffolds was used for our studies. Initially, the molecular alignment was performed for library compounds with the reference drug molecule to find targets that match the field points. Antiviral compounds having a similarity score >0.6;were selected for further docking studies with wild and mutant NSPs and S Spike protein of SARS-CoV-2 variant B.1.617. The docking studies identified a potent analog MA-11, which exhibited the highest binding affinity towards wild and mutant proteins. Further, molecular dynamics simulation studies of selected compounds confirmed their perfect fitting into NSP12 and spike active sites and offer direction for further lead optimization and rational drug design.

Steroids use in Severe/Life Threatening COVID-19 Pneumonia: Does the Type or Dose Matter?

Objective: To compare the effect of different doses of methylprednisolone and dexamethasone on in-hospital mortality in severe COVID-19 pneumoniaMethods: This retrospective chart review was done by reviewing old medical reports of patients with severe disease admitted to COVID-19 Intensive Care and High Dependency Unit from October 2020 to September 2021. Those with suspected COVID-19 infection (suggestive radiological findings but negative PCR for SARS- CoV-2 on at least two occasions) were excluded. Patients requiring high flow oxygen (> 6 liters per minute) or higher levels of respiratory support were classified as having severe disease. We recorded the type of steroids used and the doses. Methylprednisolone in doses up to 40mg per day, or other steroids in equivalent doses, were considered low dose. Primary outcome of interest was in-hospital mortality.Results: There were 279 patients aged 52.53 +/- 11.31 years, including 216 (77.42%) males. Mean hospital stay was 10.18 +/- 3.13 days. During hospital stay, 96 (34.41%) patients died. Amongst patients receiving dexamethasone, 70 (44.87%) expired, whereas 26 (21.14%) out of 123 patients who received methylprednisolone expired (p < 0.001;hazard ratio 3.037). With high dose steroids, 52 (41.27%) out of 126 patients expired, whereas 44 (28.76%) out of 153 patients treated with low dose steroids expired (p=0.029;hazard ratio 1.741). In multivariate binary logistic regression, in-hospital mortality was related to the type of steroid but not the steroid dose.Conclusion: Methylprednisolone is superior to dexamethasone for treatment of severe COVID-19 pneumonia.

Identification of a Plausible Inhibitor of SARS-Cov 2 Protease (6LU7) and the Spike Envelope Glycoprotein (6MOJ) from Active Compounds of Nigella sativa: An In-silico Approach

SARS-CoV-2, the recent disease outbreak causing respiratory tract illness, raised as the global health burden that has caused significant morbidity and mortality worldwide. In the ongoing transmission of this pandemic virus, its control is very challenging due to the lack of specific treatment. The compelling situation feels the necessity for the use of all assets to cure this disease. SARS-CoV-2, main protease, and spike envelope glycoprotein are important determinants in the infectious virus process, and targeting these proteins is gaining importance in anti-CoV drug design. In these conceptual circumstances, an attempt has been made to suggest an in silico molecular docking approach to identify new probable leads from the active constituents from Nigella sativa L against protein target main protease(6LU7) and spike envelope glycoprotein(6MOJ). Our results indicate that Nigellicine and Nigellicimine N-Oxide towards main protease and Nigellamine A5 and Nigellamine A1 towards spike glycoprotein has potential antiviral protein binding affinity among others forming good interactions. Thus, these compounds may be considered to be potential inhibitors against SARS-CoV-2 but need to be explored for further evaluations are recommended. © 2022, AMG Transcend Association. All rights reserved.

The perspective of energy poverty and 1st energy crisis of green transition

The role of energy transition amidst the energy crisis and how policymakers can drive down emissions while focusing on energy security are critical. Given the geo-political situation, energy crisis volatility, energy shortage and climate change all affect the green transition and the short-term priorities for energy companies and policymakers. Energy security is not an isolated issue but has widespread implications as various sectors depend on energy supply to function properly. Governments around the world are faced with this trilemma, how to balance energy security with energy sustainability while also considering energy affordability. Sustainability has been in focus for about a decade. However, energy security is suddenly becoming one of the most important priorities that policymakers need to consider. Unfortunately, the renewable energy infrastructure is not yet ready to replace the growing volume of energy demand from hydrocarbon, which the world has been dependent on. This means, for now, a surge in energy generation through hydrocarbon to meet the existing energy demand deficit. However, it is important not to lose focus on the challenge of energy sustainability and climate change adaption and mitigation. Where trends like carbon capture and storage;solar, wind, hydro, green hydrogen, etc.;renewable energy infrastructure and integrations, with supply chain and engineering services consideration [in aspect for the growing market in this space] need better attention with regards to investment and full-scale implementation. This paper aims to analyze this 1st energy crisis of green transition with a priori on energy poverty with consideration of major influences and associated impacts. Furthermore, it proposes a specific framework for inclusive investigations, which considers the entire energy ecosystem with consideration of major influences, to enable the policymakers to better drive the green transition. This involves formulating energy policies that are not entirely conservative towards renewable energy sources but instead promote investments in both green and relatively more environmentally benign energy sources compared to high emission hydrocarbons. In this regard, this paper renders exhaustive prospects and recommendations. © 2023 Elsevier Ltd

An exploratory study of organisational and industry drivers for the implementation of emerging technologies in logistics

Purpose: Emerging technologies have the capacity to transform industries offering substantial benefits to users. Given the increasing demand for advanced logistics services, third-party logistic service providers (LSPs) face greater pressure to deploy and realise these technologies, especially given the demands and operational challenges created during the COVID-19 crisis. Drawing upon the diffusion of innovation (DOI) theory and technology–organisation–environment (TOE) framework, this paper goes beyond just identifying drivers and barriers to technology adoption to understanding how LSPs and industry experts perceive these drivers and barriers and simultaneously confront and undertake actions to implement them. Design/methodology/approach: An exploratory study was conducted in three phases: (1) in-depth interviews with twelve stakeholders in the Australian logistics industry;(2) five in-depth interviews conducted with stakeholders during the COVID-19 crisis and (3) a focus group discussion session. All interviews were analysed using content analysis and revealed several drivers for the deployment of emerging technologies, including internal organisational factors that drive supply chain (SC) network optimisation. Findings: The analysis of the three phases identified several drivers for the deployment of emerging technologies in logistics, including internal organisational factors that drive SC network optimisation. Also identified were external drivers including the impact of the COVID-19 crisis, along with barriers and specific actions that were considered and implemented by LSPs for sustainable operations, particularly in a post-COVID-19 environment. Originality/value: This study explores organisational and industry drivers for the implementation of emerging technologies. Explicitly, it extends the extant research by highlighting organisational and industry drivers and enablers that influence adoption and deployment of emerging technologies. Second, it advances the existing perspectives on LSPs in the Australian context on the development and implementation of technology strategies. The paper offers insights around implementation of technologies, directly obtained from industrial application for managers and practitioners. © 2023, Emerald Publishing Limited.

Identification of Clinical Features Associated with Mortality in COVID-19 Patients

Understanding clinical features and risk factors associated with COVID-19 mortality is needed to early identify critically ill patients, initiate treatments and prevent mortality. A retrospective study on COVID-19 patients referred to a tertiary hospital in Iran between March and November 2020 was conducted. COVID-19-related mortality and its association with clinical features including headache, chest pain, symptoms on computerized tomography (CT), hospitalization, time to infection, history of neurological disorders, having a single or multiple risk factors, fever, myalgia, dizziness, seizure, abdominal pain, nausea, vomiting, diarrhoea and anorexia were investigated. Based on the investigation outcome, decision tree and dimension reduction algorithms were used to identify the aforementioned risk factors. Of the 3008 patients (mean age 59.3 ± 18.7 years, 44% women) with COVID-19, 373 died. There was a significant association between COVID-19 mortality and old age, headache, chest pain, low respiratory rate, oxygen saturation < 93%, need for a mechanical ventilator, having symptoms on CT, hospitalization, time to infection, neurological disorders, cardiovascular diseases and having a risk factor or multiple risk factors. In contrast, there was no significant association between mortality and gender, fever, myalgia, dizziness, seizure, abdominal pain, nausea, vomiting, diarrhoea and anorexia. Our results might help identify early symptoms related to COVID-19 and better manage patients according to the extracted decision tree. The proposed ML models identified a number of clinical features and risk factors associated with mortality in COVID-19 patients. These models if implemented in a clinical setting might help to early identify patients needing medical attention and care. However, more studies are needed to confirm these findings. © 2023, The Author(s).

Current pandemic COVID-19 vaccine strategies and development: a comprehensive review

The coronavirus disease-19 pandemic with the characteristics of asymptomatic condition, long incubation period and poor treatment has influenced the entire globe. Coronaviruses are important emergent pathogens, specifically, the recently emerged sever acute respiratory syndrome coronavirus 2, the causative virus of the current COVID-19 pandemic. To mitigate the virus and curtail the infection risk, vaccines are the most hopeful solution. The protein structure and genome sequence of SARS-CoV-2 were processed and provided in record time;providing feasibility to the development of COVID-19 vaccines. In an unprecedented scientific and technological effort, vaccines against SARS-CoV-2 have been developed in less than one year. This review addresses the approaches adopted for SARS-CoV-2 vaccine development and the effectiveness of the currently approved vaccines.Copyright © 2023, Finlay Ediciones. All rights reserved.

Determinants of COVID-19 safety behaviors: Implications for preventive policy

Objective: To identify the predictors of COVID-19 safety behaviors (hand washing, physical distancing, & wearing masks), in Pakistan. Methodology: This correlational study was conducted at Karakoram International University, Gilgit and Combined Military Hospital, Kharian from November 2020 to April 2021. We used newly developed COVID-19 Safety Behaviors Scale-Urdu, COVID-19 Anxiety Scale-Urdu, COVID-19 Knowledge Scale-Urdu, and a brief version of the Big Five Personality Inventory, on 911 participants (395 women). Result(s): COVID-19 related anxiety (beta = 0.02, p < 0.05) and the personality trait 'conscientiousness' (beta = 0.02, p < 0.01) significantly moderated the positive relationship between COVID-19 knowledge and COVID-19 safety behaviors. This implies that people with a dominant personality trait of 'conscientiousness' were actively seeking COVID-19 related knowledge that led to higher levels of preventive behaviors. Conclusion(s): To control the current pandemic and associated negative consequences through 'safety behaviors' it is important to educate people while keeping the demographic variables in view.Copyright © 2023, Pakistan Medical Association. All rights reserved.

US public investment in development of mRNA covid-19 vaccines: retrospective cohort study.

OBJECTIVE: To estimate US public investment in the development of mRNA covid-19 vaccines. DESIGN: Retrospective cohort study. SETTING: Publicly funded science from January 1985 to March 2022. DATA SOURCES: National Institutes of Health (NIH) Report Portfolio Online Reporting Tool Expenditures and Results (RePORTER) and other public databases. Government funded grants were scored as directly, indirectly, or not likely related to four key innovations underlying mRNA covid-19 vaccines-lipid nanoparticle, mRNA synthesis or modification, prefusion spike protein structure, and mRNA vaccine biotechnology-on the basis of principal investigator, project title, and abstract. MAIN OUTCOME MEASURE: Direct public investment in research and vaccine development, stratified by the rationale, government funding agency, and pre-pandemic (1985-2019) versus pandemic (1 January 2020 to 31 March 2022). RESULTS: 34 NIH funded research grants that were directly related to mRNA covid-19 vaccines were identified. These grants combined with other identified US government grants and contracts totaled $31.9bn (£26.3bn; €29.7bn), of which $337m was invested pre-pandemic. Pre-pandemic, the NIH invested $116m (35%) in basic and translational science related to mRNA vaccine technology, and the Biomedical Advanced Research and Development Authority (BARDA) ($148m; 44%) and the Department of Defense ($72m; 21%) invested in vaccine development. After the pandemic started, $29.2bn (92%) of US public funds purchased vaccines, $2.2bn (7%) supported clinical trials, and $108m (<1%) supported manufacturing plus basic and translational science. CONCLUSIONS: The US government invested at least $31.9bn to develop, produce, and purchase mRNA covid-19 vaccines, including sizeable investments in the three decades before the pandemic through March 2022. These public investments translated into millions of lives saved and were crucial in developing the mRNA vaccine technology that also has the potential to tackle future pandemics and to treat diseases beyond covid-19. To maximize overall health impact, policy makers should ensure equitable global access to publicly funded health technologies.

Predicting factors affecting business operations during pandemic COVID-19

Purpose: The global COVID-19 pandemic has rapidly overwhelmed our societies, shocked the global economy and disturbed normal business operations. While such impacts of COVID-19 are becoming clearer, the effects of the disease on business operations are more common. This study mainly focuses on identifying the factors that affect the smooth operation of businesses during a pandemic situation. Design/methodology/approach: Analytical hierarchy process (AHP) method was used to rate the result index. A total of 40 professionals and experts of different businesses were listed on stock exchanges, and asked to rank the key variables with relative indices and weighting methods. Findings: The results of the AHP successfully assigned weighting scores to all key important factors during the COVID-19 pandemic situation that businesses should focus on, with economic factors receiving the highest score of 60%. Likewise, the other factors that impact values for business operations are reported as social (22%), legal (12.2%), technological (5.16%) and political (0.57%). The results of this study also match with the current policies adopted by different government and nongovernment agencies like the guidelines of the World Health Organization and some most recent research results. Originality/value: In the hectic and growing environment under COVID-19 pandemic, more contributions are not enough, and it is helpful for the whole business industry and society by stipulating more views. This study aims to overview the global impacts and challenges of COVID-19 pandemic on business operations. © 2023, Emerald Publishing Limited.

Predicting COVID-19 vaccinators based on machine learning and sentiment analysis

In the past two years, the world witnessed the spread of the coronavirus (COVID-19) pandemic that disrupted the entire world, the only solution to this epidemic was health isolation, and with it everything stopped. When announcing the availability of a vaccine, the world was divided over the effectiveness and harms of this vaccine. This article provides an analysis of vaccinators and analysis of people's opinions of the vaccine's efficacy and whether negative or positive. Then a model is built to predict the future numbers of vaccinators and a model that predicts the number of negative opinions or tweets. The model consists of three stages: first, converting data sets into a synchronized time series, that is, the same place and time for vaccination and tweets. The second stage is building a prediction model and the third stage was descripting analysis of the prediction results. The autoregressive integrated moving averages (ARIMA) method was used after decomposing the components of ARIMA and choosing the optimal model, the best results obtained from seasonal ARIMA (SARIMA) for both predictions, the last stage is the descriptive analysis of the results and linking them together to obtain an analysis describing the change in the number of vaccinators and the number of negative tweets. © 2023, Institute of Advanced Engineering and Science. All rights reserved.

Did all Emerging Equity Markets get Equally Affected by Covid-19? Role of Market Characteristics, Economic Conditions, and Government Policies

The Covid-19 pandemic wreaked havoc on global economies. Emerging markets were hit particularly harder during the Covid19 pandemic due to their reliance on exports, tourism, and weaker fiscal policies. This paper aims to analyze the performance of the equity markets of 22 developing countries based on their average firm-related characteristics, macroeconomic conditions, and freedom variables during the early outbreak of Covid-19. Our results show that leverage, the fiscal health of the country, and financial freedom were the most important variables for emerging market countries as they provided resilience during the Pandemic. These findings have clear policy implications and are important for the sustainability of emerging stock markets. © 2022, AfricaGrowth Institute. All rights reserved.

Frequency of Respiratory Complications in Post COVID-19 Patients After Coronary Artery Bypass Grafting

Objective: To determine the frequency of post-operative pulmonary complications after (coronary artery bypass grafting) CABG surgery and to compare the respiratory complications of post COVID and comparison group Study Design: Analytical Cross-sectional study Study Place and Duration: Study was conducted in Adult Intensive Care Unit, Armed Forces Institute of Cardiology, Rawalpindi Pakistan, from Sep 2021 to Mar 2022. Methodology: 40 patients were selected, and divided into two groups using non-Probability consecutive sampling. Group-A had history of COVID-19 infection and Group-B was a comparison group and had no history of COVID-19 infection. Patients presenting for elective On-Pump (coronary artery bypass grafting) CABG surgery and known history of COVID-19 were included in our study. Patients of age ranging 30 to 70 years irrespective of gender were included in the study. Any patient who had cardiopulmonary bypass time of more than 120 min, respiratory illness like asthma or Chronic Obstructive Pulmonary Disease (COPD), history of smoking, or requiring post-operative re-ventilation due to cardiac or neurological complication, were excluded from the study. After patients were received from Operation theatre, they were monitored for the respiratory complications and both groups were compared. Results: A total of 40 patients were included in this study having mean age 57.9±7.62 years. Most of the patient population was male 31(77.5%) and only 09(22.5%) were female patients. Study population was equally divided into two groups i.e., 20(50%) in comparison group and 20(50%) in post COVID-19 group. There was no significant difference in age (p=0.714), ventilation time (p=0.068), gender (p=1.000), and re-ventilation (p=0.451) of both groups. While Intensive Care Unit stay (p=<0.0001) and non-invasive ventilation (NIV) were found to be significant (p=0.007). © 2022, Army Medical College. All rights reserved.