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COVID-19 is an outbreak of disease which is created by China. COVID-19 is originated by coronavirus (CoV), generally created mutation pattern with 'SARS-CoV2' or '2019 novel coronavirus'. It is declared by the World Health Organization of 2019 in December. COVID-19 is a contagious virus and contiguous disease that will create the morality of life. Even though it is detected in an early stage it can be incurable if the severity is more. The throat and nose samples are collected to identify COVID-19 disease. We collected the X-Ray images to identify the virus. We propose a system to diagnose the images using Convolutional Neural Network (CNN) models. Dataset used consists of both Covid and Normal X-ray images. Among Convolutional Neural Network (CNN) models, the proposed models are ResNet50 and VGG16. RESNET50 consists of 48 convolutional, 1 MaxPool, and Average Pool layers, and VGG16 is another convolutional neural network that consists of 16 deep layers. By using these two models, the detection of COVID-19 is done. This research is designed to help physicians for successful detection of COVID-19 disease at an early stage in the medical field. © 2022 IEEE.
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Objectives: Bariatric surgery has evolved over the past two decades yet assessing trends of bariatric surgery utilization in the growing eligible population is lacking.This study aimed to update the trends in bariatric surgery utilization, changes in types of procedures performed, and the characteristics of patients who underwent bariatric surgery in the US, using real-world data. Method(s): This cross-sectional study was conducted using the TriNetX, a federated electronic medical records network from 2012 to 2021, for adult patients 18 years old or older who had bariatric surgery. Descriptive statistical analysis was conducted to assess patients' demographics and characteristics. Annual secular trend analyses were conducted for the annual rate of bariatric surgery, and the specific procedural types and proportions of laparoscopic surgeries. Result(s): A steady increase in the number of procedures performed in the US over the first six years of the study, a plateau for the following two years, and then a decline in 2020 and 2021 (during the coronavirus-19 pandemic). The annual rate of bariatric surgery was lowest in 2012 at 59.2 and highest in 2018 at 79.6 surgeries per 100,000 adults. During the study period, 96.2% to 98.8% of procedures performed annually were conducted laparoscopically as opposed to the open technique. Beginning in 2012, the Roux-en-Y (RYGB) procedure fell to represent only 17.1% of cases in 2018, along with a sharp decline in the adjustable gastric band (AGB) procedure, replaced by a sharp increase in the sleeve gastrectomy (SG) procedure to represent over 74% of cases in 2018. Conclusion(s): Bariatric surgery utilization in the US showed a moderate decline in the number of RYGB procedures, which was offset by a substantial increase in the number of SG procedures and a precipitous drop in the annual number of AGB procedures.Copyright © 2023
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Introduction: Individual and community characteristics predictive of knowledge, perception, and attitude on COVID-19, specifically on gender, have not been adequately explored. Objective: To examine the gender differences in COVID-19 knowledge, self-risk perception and public stigma among the general community and to understand other socio-demographic factors which were predictive of them. Method: A nationally representative cross-sectional multi-centric survey was conducted among adult individuals(≥18 yrs) from the community member (N = 1978) from six states and one union territory of India between August 2020 to February 2021. The participants were selected using systematic random sampling. The data were collected telephonically using pilot-tested structured questionnaires and were analyzed using STATA. Gender-segregated multivariable analysis was conducted to identify statistically significant predictors (p < 0.05) of COVID-19-related knowledge, risk perception, and public stigma in the community. Results: Study identified significant differences between males and females in their self-risk perception (22.0% & 18.2% respectively) and stigmatizing attitude (55.3% & 47.1% respectively). Highly educated males and females had higher odds of having COVID-19 knowledge (aOR: 16.83: p < 0.05) than illiterates. Highly educated women had higher odds of having self-risk perception (aOR: 2.6; p < 0.05) but lower public stigma [aOR: 0.57; p < 0.05]. Male rural residents had lower odds of having self-risk perception and knowledge [aOR: 0.55; p < 0.05 & aOR: 0.72; p < 0.05] and female rural residents had higher odds of having public stigma [aOR: 1.36; p < 0.05]. Conclusion: Our study findings suggest the importance of considering thegender differentials and their background, education status and residential status in designing effective interventions to improve knowledge and reduce risk perception and stigma in the community about COVID-19.
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Background: Atrial fibrillation and/or flutter is a common comorbidity in hospitalized patients with COVID-19. Objective(s): We aimed to assess the effect of atrial fibrillation and/or flutter on the outcomes of COVID-19 patients in a nationally representative sample. Method(s): We conducted a population-based analysis utilizing data from the national inpatient sample database. Hospitalized adults >= 18 years who were hospitalized with COVID-19 during the year 2020 were included. We used multivariate logistic regression models to investigate the outcomes in patients who had atrial fibrillation or flutter. Result(s): Among 1,018,115 (Nationally weighted sample) admissions with COVID-19, 154795 cases (15.2%) had atrial fibrillation and/or flutter. Patients with atrial fibrillation and/or flutter had significantly higher adjusted odds of all-cause in-hospital mortality (Odds Ratio [OR], 1.78 [confidence interval (CI), 1.75-1.80]), acute stroke (OR, 1.96 [CI, 1.85-2.07]), acute coronary syndrome (OR, 1.43 [CI, 1.37-1.48]), acute heart failure (OR, 4.24 [CI, 4.15-4.34]), cardiogenic shock (OR, 3.07 [CI, 2.85-3.30]), need for vasopressors (OR, 2.14 [CI, 2.06-2.22]), cardiac arrest (OR, 1.95 [CI, 1.89-2.02]), need for mechanical ventilation (OR, 1.79 [CI, 1.77-1.82]), acute kidney injury (OR, 1.25 [CI, 1.23-1.27]), major bleeding (OR, 1.82 [CI, 1.73-1.92]) compared to those patients without atrial fibrillation or flutter. On subgroup analysis, the risk for mortality was highest among atrial flutter (OR, 2.91), followed by atrial flutter and fibrillation group (OR, 2.38), followed by only atrial fibrillation group (OR, 1.71) (P value <0.001 for all) when compared to non-atrial fibrillation, non-atrial flutter in patients with COVID-19. Conclusion(s): Atrial fibrillation and flutter are associated with higher inpatient mortality and worse outcomes in COVID-19 patients. [Formula presented]Copyright © 2023
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Background: The ongoing COVID-19 pandemic has grave implications worldwide. Workers in small scale industries like fisheries forms a vulnerable group without social security/recognised labour rights Objectives: To assess the physical, mental and socio- economic impact of COVID-19 among fishermen community from coastal area of Karnataka 2. To understand the challenges faced and coping mechanism adopted to mitigate the impact Methodology: This community based mixed methods study was conducted among 138 participants from a fishermen community in coastal Karnataka. Quantitative data included sociodemographics, COVID-19 diagnosis, treatment, related expenses and DASS -21 questionnaire. Qualitative data was collected through 3 Focus Group Discussions and 7 Key informant Interviews till data saturation. Result(s): A total of 138 participants (quantitative 107 and qualitative 31) were included. Majority of the participants were males (70.1%), belonged to age category of 46-60 years (37.4%), nuclear family (71%) and were from low socioeconomic status (79.4%). COVID-19 appropriate behaviour was found to be poor among participants with only 36% using masks, 24.3% washing hands and 10.3% maintaining social distancing. Among 107, 51 (47.7%) participants had probable COVID-19 symptoms. However only 7 (10.9%) had tested for COVID-19 with test positivity rate of 57.1%. Two participants were admitted in hospital with mean hospital stay of 7 days. According to DASS-21, 20.6%, 15.9% and 9.3% screened positive for depression, anxiety and stress respectively. Nealy 90% lost jobs and more than 75% reported to have financial difficulties. Major challenges included loss of livelihood, inaccessibility to health care, repayment of loans, stigma related to Covid-19 and meeting educational expenses of children with one drop out from college. Strategies to cope up with financial difficulty included borrowings, pawning and selling assets at individual level. Activities of local self-help groups in the community and grass root level marketing strategies were highly successful in mitigating the impact as a community. Conclusion(s): COVID-19 has affected fishermen community to a large extent. This understanding will enable to implement need-based intervention strategies and help in disaster preparedness among this population.
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With cyberspace's continuous evolution, online reviews play a crucial role in determining business success in various sectors, ranging from restaurants and hotels to e-commerce applications. Typically, a favorable review for a specific product draws in more consumers and results in a significant boost in sales. Unfortunately, a few businesses are using deceptive methods to improve their online reputation by using fake reviews of competitors. As a result, detecting fake reviews has become a difficult and ever-changing research field. Verbal characteristics extracted from review text, as well as nonverbal features such as the reviewer's engagement metrics, the IP address of the device, and so on, play an important role in detecting fake reviews. This article examines and compares various machine learning techniques for detecting deceptive reviews on various online platforms such as e-commerce websites such as Amazon and online review websites such as Yelp, among others. © 2023 IEEE.
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Using data on Chinese GEM-listed companies from the first quarter of 2018 to the second quarter of 2022, we examine the impact of COVID-19 on SMEs' financing constraints and the moderating effect of fiscal and tax incentives using the difference-in-differences method (DID). The results indicate that the COVID-19 shock severely affected SMEs' financing constraints, and this effect is more pronounced among firms in industries particularly sensitive to COVID-19, such as transportation, catering, accommodation, culture, and entertainment. A further analysis shows that tax incentives and fiscal subsidies have differing moderating effects, with the former alleviating SMEs' financing constraints and the latter having only a relatively limited effect. This finding provides direct micro-level evidence for understanding the impact of COVID-19 on financing constraints and provides insights for promoting the optimization of fiscal support policies for SMEs. © 2023 Informa UK Limited, trading as Taylor & Francis Group.
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Introduction: The progression of pathophysiological pulmonary changes in patients following acute COVID-19 is not well established. Method(s): Patients hospitalised with COVID-19 pneumonia without signs of ILD, had MRI exams at a median of 6 (n=9), 12 (n=9), 25 (n=7), and 52 (n=3) weeks. MRI sequences included: dynamic contrast enhanced (DCE) lung perfusion,129 Xe diffusion weighted (DW-MRI), 129Xe ventilation and 129Xe 3D dissolved phase imaging. Result(s): 9 patients (age 56+/-9 years;7 male;1 required treatment in an ICU) were recruited. Median RBC:TP was abnormally low at all visits compared to reference age and sex matched data. An individual's RBC:TP was significantly and positively associated with an increase in their pulmonary blood volume (p=0.026). For patients with 52 week data available, one showed a continued increase in RBC:TP, 2 patients maintained a low RBC:TP (Figure 1). Ventilation defect percentage, and ventilation heterogeneity significantly decreased at 25 weeks compared to 6 129 129 129 weeks (p=0.010 and p=0.048). DW-MRI was normal at all visits. Dissolved phase xenon imaging showed RBC:TP significantly increased at 12 and 25 weeks compared to 6 weeks (p=0.048). Conclusion(s): In patients recovering after COVID-19, poor gas transfer is reflected by impaired xenon transfer, which improves alongside pulmonary blood volume.
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Remote working is increasingly seen as an effective model in several countries in the last decade, mainly thanks to the development of information and communication technologies in support of common daily working tasks. The emergence of the COVID-19 pandemic has represented a pivotal moment for the adoption of remote working in multiple sectors, with positive effects on the environmental impacts caused by the daily commuting of workers. However, due to the fact that pandemic-induced remote working has represented a major forced experiment on a global scale, and that it has often been imposed rather than chosen by employees, workers' well-being has not always been ensured. This research work presents an analysis of a wide survey of remote workers in public administrations in four different provinces in Italy, with the aim of assessing the main characteristics of the users and the related environmental benefits. Survey data refer to remote workers before COVID-19, thus representing workers who have freely chosen to work from home for different reasons. The results of this work represent a useful tool with which to support the definition of new remote work strategies that could help policy makers reduce a part of the systematic mobility demand. We have also calculated average energy and emission savings to provide useful indicators for a preliminary estimation of the potential environmental benefits of remote working. Considering the entire sample of respondents, workers who would have commuted at least partially by car have saved on average 6 kg of CO2 per day thanks to remote working (with an average round-trip commuting distance of approximately 35 km). The current results will be supplemented by the results of a new survey underway, aimed at evaluating the differences of remote working experiences during the emergency response to COVID-19. © 2023 by the authors.
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Mathematical modeling is one of the most used techniques for analyzing and preventing the transmission of COVID-19. To control this pandemic, it is essential to classify the infected population. So in this article, a new SEAIQHRDP model was formulated to investigate the transmittal dynamics of COVID-19. This model contains nine compartments Susceptible(S) class, Exposed(E) class, Asymptomatic(A) class, Infected(I) class, Quarantined(Q) class, Hospitalized(H) class, Recovered(R) class, Death(D) class, and Insusceptible (P) class. This model was fitted to the daily and cumulative confirmed COVID-19 cases in the period between 30th January 2020 and 13th January 2021 in India. Sensitivity analysis concerning R0 was performed to classify the significance of parameters. Contour plots for R0 were executed and the effect of various parameters on the infected classes had shown graphically. The necessity of stringent face mask usage and social seclusion is highlighted by optimal control analysis as a key factor in the dramatic reduction of infection rates. So the optimal control technique was adopted to lessen the disease mortality by taking both nonpharmaceutical and pharmaceutical intervention strategies as control functions and comparing infectives and recoveries with and without controls. © 2023, Eudoxus Press, LLC. All rights reserved.
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BACKGROUND/OBJECTIVES: Globally, the COVID-19 pandemic and its prevention and control policies have impacted maternal and child health (MCH) services. This study documents the challenges faced by patients in accessing MCH services, and the experiences of health care providers in delivering those services during the COVID-19 outbreak, explicitly focusing on the lockdown period in India. METHODS: A cross-sectional study (rapid survey) was conducted in 18 districts from 6 states of India during March to June, 2020. The sample size included 540 MCH patients, 18 gynaecologists, 18 paediatricians, 18 district immunisation officers and 108 frontline health workers. Bivariate analysis and multivariable analysis were used to assess the association between sociodemographic characteristics, and challenges faced by the patients. RESULTS: More than one-third of patients (n = 212; 39%) reported that accessing MCH services was a challenge during the lockdown period, with major challenges being transportation-related difficulties (n = 99; 46%) unavailability of hospital-based services (n = 54; 23%) and interrupted outreach health services (n = 39; 18.4%). The supply-side challenges mainly included lack of infrastructural preparedness for outbreak situations, and a shortage of human resources. CONCLUSIONS/RECOMMENDATIONS: A holistic approach is required that focuses on both preparedness and response to the outbreak, as well reassignment and reinforcement of health care professionals to continue catering to and maintaining essential MCH services during the pandemic.
Subject(s)
COVID-19 , Child Health Services , Maternal Health Services , Child , Humans , Female , Pregnancy , COVID-19/epidemiology , Cross-Sectional Studies , Pandemics , Communicable Disease Control , India/epidemiologyABSTRACT
The long-term effects of coronavirus disease 2019 (COVID- 19) pneumonia on the lungs and pulmonary circulation require further characterization. We assessed progression of pathophysiological pulmonary changes during 1 year of follow-up of patients who had been hospitalized because of COVID-19. After discharge, recruited patients had up to four MRI examinations at a median of 6 (n=9), 12 (n=9), 25 (n=7) and 52 (n=3) weeks. Lung MRI examinations included: ultra-short echo time (UTE), dynamic contrastenhanced (DCE) lung perfusion, 129Xe diffusion weighted (DW-MRI), 129Xe ventilation and 129Xe 3D dissolved phase imaging. Nine patients (age 56 +/-9 years;six male) were recruited. Ventilation defect percentage and whole lung coefficient of variation of lung ventilation decreased significantly at 25 weeks (visit 3) compared with visit 1 at 6 weeks (p=0.010 and p=0.048). The UTE imaging indicated no evidence of lung scarring, and DW-MRI indicated normal lung microstructure across all visits. Dissolved phase xenon imaging showed that RBC:TP increased significantly at visits 2 and 3 compared with visit 1 (p=0.048). Median RBC:TP was abnormally low at all visits compared with reference age- and sex-matched data. An individual's RBC:TP was associated significantly and positively with an increase in their pulmonary blood volume (p=0.026). For patients with 52-week data available, one showed a continued improvement in RBC:TP;however, two of the patients maintained a low RBC:TP. In patients recovering from COVID-19, xenon gas transfer improves alongside pulmonary blood volume. Further work is needed to establish the proportion of post-COVID-19 patients who have longer-term impairment in xenon transfer and to correlate changes in lung MRI parameters with symptoms, lung function tests and other imaging modalities. Persistent impairment of xenon transfer might represent a physiological mechanism underlying ongoing symptoms in some patients and might indicate damage to the pulmonary microcirculation.
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The in silico evaluation of 11H-pyrido[2,1-b]quinazolin-11-one derivatives against SARS-CoV-2 RdRp was undertaken based on the reports on antiviral activities of this class of compounds in addition to the promising interactions of the antiviral drug penciclovir as well as quinazoline derivatives with SARS-CoV-2 RdRp in silico. The target compounds were prepared via an Ullmann-Goldberg type coupling followed by the subsequent cyclization (involving amidation) in a single pot. The methodology involved a CuI-catalyzed reaction of 2-iodobenzoate ester with 2-aminopyridine or quinolin-2-amine or thiazol-2-amine under ultrasound to give the expected products in acceptable (51-93%) yields. The molecular interactions of the synthesized 11H-pyrido[2,1-b]quinazolin-11-one derivatives with the SARS-CoV-2 RdRp (PDB: 7AAP) were evaluated in silico. The study suggested that though none of these compounds showed interactions better than penciclovir but the compound 3a and 3n appeared to be comparable along with 3b seemed to be nearly comparable to favipiravir and remdesivir. The compound 3n with the best binding energy (-79.85 Kcal/mol) participated in the H-bond interactions through its OMe group with THR556 as well as ARG624 and via the N-5 atom with the residue SER682. The in silico studies further suggested that majority of the compounds interacted with the main cavity of active site pocket whereas 3h and 3o that showed relatively lower binding energies (-66.06 and -66.28 Kcal/mol) interacted with the shallow cavity underneath the active site of SARS CoV-2 RdRp. The study also revealed that a OMe group was favourable for interaction with respect to its position in the order C-8 > C-1 > C-2. Further, the presence of a fused quinoline ring was tolerated whereas a fused thiazole ring decreased the interaction significantly. The in silico predictions of pharmacokinetic properties of 3a, 3b and 3n indicated that besides the BBB (Blood Brain Barrier) penetration potential these molecules may show a good overall ADME. Overall, the regioisomers 3a, 3b and 3n have emerged as molecules of possible interest in the context of targeting COVID-19.
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Aim: In 2019, the British Society of Gastroenterology (BSG) published the first United Kingdom national guidelines for acute lower gastrointestinal bleeding (LGIB),(1) following inadequacies in LGIB emergency service provision.(1,2) Method: We performed a retrospective cohort study (January 2019 to September 2020), using paper and electronic notes through coded data, for all LGIB emergency surgical admissions for LGIB. Paper and electronic notes were used, in retrieving data. Primary outcome end-points: evaluate our standards as per BSG guidelines. Result(s): 48 patients were identified as matching the inclusion criteria, with a median age of 64.75 and diverticular diseases accounting for the majority of cases. None of the patients were categorised in the group of being stable/unstable or had their Oakland scores calculated. 62.5% of patients were offered outpatient investigations versus 6.25% for inpatient investigations. 0% of unstable patients were offered a CT angiogram (as no patients were stratified as unstable). 75% of patients achieved haemoglobin target levels post-transfusion. 100% of patients taking warfarin and dual antiplatelets followed guidelines versus 50% on clopidogrel, 80% on dual antiplatelet therapy and 63.6% on aspirin alone. Conclusion(s): This study found that our department did not adhere to the BSG guidelines. This can be improved through the routine calculation of the Oakland score and shock index, which will stratify clinical risk. Additionally creating an agreed trust management pathway and assigning a gastrointestinal bleed lead will allow for earlier detection and encourage better clinical practice. Whilst there were limitations due to restricted data collection, as a result of the coronavirus, further research will identify how these implementations can be amended and if the changes are effective in local practice.
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Mathematical modeling is one of the most used techniques for analyzing and preventing the transmission of COVID-19. To control this pandemic, it is essential to classify the infected population. So in this article, a new SEAIQHRDP model was formulated to investigate the transmittal dynamics of COVID-19. This model contains nine compartments Susceptible(S) class, Exposed(E) class, Asymptomatic(A) class, Infected(I) class, Quarantined(Q) class, Hospitalized(H) class, Recovered(R) class, Death(D) class, and Insusceptible (P) class. This model was fitted to the daily and cumulative confirmed COVID-19 cases in the period between 30th January 2020 and 13th January 2021 in India. Sensitivity analysis concerning R0 was performed to classify the significance of parameters. Contour plots for R0 were executed and the effect of various parameters on the infected classes had shown graphically. The necessity of stringent face mask usage and social seclusion is highlighted by optimal control analysis as a key factor in the dramatic reduction of infection rates. So the optimal control technique was adopted to lessen the disease mortality by taking both nonpharmaceutical and pharmaceutical intervention strategies as control functions and comparing infectives and recoveries with and without controls. [ FROM AUTHOR]
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Background & objectives: COVID-19 pandemic has triggered social stigma towards individuals affected and their families. This study describes the process undertaken for the development and validation of scales to assess stigmatizing attitudes and experiences among COVID-19 and non-COVID-19 participants from the community. Methods: COVID-19 Stigma Scale and Community COVID-19 Stigma Scale constituting 13 and six items, respectively, were developed based on review of literature and news reports, expert committee evaluation and participants' interviews through telephone for a multicentric study in India. For content validity, 61 (30 COVID-19-recovered and 31 non-COVID-19 participants from the community) were recruited. Test-retest reliability of the scales was assessed among 99 participants (41 COVID-19 recovered and 58 non-COVID-19). Participants were administered the scale at two-time points after a gap of 7-12 days. Cronbach's alpha, overall percentage agreement and kappa statistics were used to assess internal consistency and test-retest reliability. Results: Items in the scales were relevant and comprehensible. Both the scales had Cronbach's α above 0.6 indicating moderate-to-good internal consistency. Test-retest reliability assessed using kappa statistics indicated that for the COVID-19 Stigma Scale, seven items had a moderate agreement (0.4-0.6). For the Community COVID-19 Stigma Scale, four items had a moderate agreement. Interpretation & conclusions: Validity and reliability of the two stigma scales indicated that the scales were comprehensible and had moderate internal consistency. These scales could be used to assess COVID-19 stigma and help in the development of appropriate stigma reduction interventions for COVID-19 infected, and mitigation of stigmatizing attitudes in the community.
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COVID-19 , Social Stigma , Humans , India/epidemiology , Pandemics , Psychometrics , Reproducibility of Results , Surveys and QuestionnairesABSTRACT
In the time of the pandemic like CORONA, Covid-19, everyone is ftghting against this deadly virus. Besides, governments are looking for a barrier that stops spread of virus until the vaccine is made. In modern era, technology plays an important role. This paper brings the way by using a powerful technology called Big data. Big data know for handling a large amount of data and provide powerful insights into the data. Big data integrated with Artificial Intelligence is a powerful tool to ftght against this pandemic. Many countries like Taiwan, China with the use of Big Data stop this pandemic up to some extent. But the collection of data itself comes up with the big challenge of PRIVACY AND SECURITY. In the recent times, the world has seen the effect of data leaking whether by Facebook or by Google. Many European countries due to this big challenge will not be able to use this technology. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Aims: 67 000 cholecystectomies performed every year in The UK and 92% are laparoscopic. 75% of operations should be done as day cases. National rates vary between 6-50% with The most successful centres at 70%. Our aim was to audit The day case rate at our Trust pre-COVID and compare it to during COVID. Method(s): A retrospective audit of patients identified via clinical coding who had an elective cholecystectomy at one hospital in The Trust between 1 December 2018 to 31 November 2019. During COVID we did a prospective audit of patients identified via Theatreman who had an elective cholecystectomy at The Trust's designated "Green Hospital" between 21 September 2020 to 21 December 2020. Data for all patients was collected from electronic discharge summaries, clinic letters and patient notes. Result(s): Pre-COVID our day case cholecystectomy rate was 73% compared to 54.7% during COVID. Pre-COVID conversion rate from planned day case to inpatient stay was 16.3% and during COVID The conversion rate increased to 44%. The waiting time for a cholecystectomy doubled during COVID to 26.3 weeks from 13.6 weeks pre-COVID. Average re-admission rate with symptomatic gallstones was 0.79 pre-COVID and 0.95 during COVID, with 64% of patients having at lEast one admission prior to surgery. The average length of stay pre-COVID was 0.75 days compared to 0.57 days during COVID. Summary: COVID adversely affected our day case cholecystectomy rates with resultant increased waiting times for Surgery and readmissions with symptomatic gallstones however The average length of hospital stay was reduced.