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1.
Indian J Surg ; : 1-2, 2020 May 31.
Article in English | MEDLINE | ID: covidwho-1920084
3.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-325023

ABSTRACT

We present Covidex, a search engine that exploits the latest neural ranking models to provide information access to the COVID-19 Open Research Dataset curated by the Allen Institute for AI. Our system has been online and serving users since late March 2020. The Covidex is the user application component of our three-pronged strategy to develop technologies for helping domain experts tackle the ongoing global pandemic. In addition, we provide robust and easy-to-use keyword search infrastructure that exploits mature fusion-based methods as well as standalone neural ranking models that can be incorporated into other applications. These techniques have been evaluated in the ongoing TREC-COVID challenge: Our infrastructure and baselines have been adopted by many participants, including some of the highest-scoring runs in rounds 1, 2, and 3. In round 3, we report the highest-scoring run that takes advantage of previous training data and the second-highest fully automatic run.

4.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-325022

ABSTRACT

We present the Neural Covidex, a search engine that exploits the latest neural ranking architectures to provide information access to the COVID-19 Open Research Dataset curated by the Allen Institute for AI. This web application exists as part of a suite of tools that we have developed over the past few weeks to help domain experts tackle the ongoing global pandemic. We hope that improved information access capabilities to the scientific literature can inform evidence-based decision making and insight generation. This paper describes our initial efforts and offers a few thoughts about lessons we have learned along the way.

5.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-322519

ABSTRACT

We present CovidQA, the beginnings of a question answering dataset specifically designed for COVID-19, built by hand from knowledge gathered from Kaggle's COVID-19 Open Research Dataset Challenge. To our knowledge, this is the first publicly available resource of its type, and intended as a stopgap measure for guiding research until more substantial evaluation resources become available. While this dataset, comprising 124 question-article pairs as of the present version 0.1 release, does not have sufficient examples for supervised machine learning, we believe that it can be helpful for evaluating the zero-shot or transfer capabilities of existing models on topics specifically related to COVID-19. This paper describes our methodology for constructing the dataset and presents the effectiveness of a number of baselines, including term-based techniques and various transformer-based models. The dataset is available at http://covidqa.ai/

6.
J Family Med Prim Care ; 10(1): 427-431, 2021 Jan.
Article in English | MEDLINE | ID: covidwho-1167910

ABSTRACT

BACKGROUND AND AIMS: In the COVID-19 times, Indian sub-continent is struggling to contain the epidemic and trying to strengthen the existing health infrastructure, the national level lockdown has raised concerns about the pattern of injuries whether it has remained the same or has changed over this period. This is the first study to compare injury pattern during the two months lockdown period with the data of corresponding months from years 2016-2020. Also we compared the age- and sex-wise distribution patterns of these injuries for the above mentioned period. METHODS: This retrospective cross sectional study was conducted by the Department of Orthopaedics in Guru Gobind Singh Medical College and Hospital (GGSMCH) in Faridkot, Punjab. Secondary data for patient's age and sex, mode of injury, and site of injury was collected through record review for the period of two months (24th March to 24th May) for five consecutive years of 2016-2020. Descriptive analysis and Chi-square test was used to see the association between age and sex with mode and type of injury. RESULTS: The five year injury trends reflected that the proportion of injuries in 2016 was 16.5% (n = 48) of the total musculoskeletal injuries (n = 291) which rose to 23.4% (n = 68) in 2020. Majority of the patients were males (80%), and belonged to adult age group (69.4%) followed by elderly (17.2%), adolescents (8.6%) and children (4.8%). The proportion of road traffic accidents out of all injuries significantly reduced during the lock down period of two months in 2020 (p = 0.001). On the contrary, the proportion of injuries due to falls as well as unspecified assault increased significantly in 2020 as compared to previous years. CONCLUSIONS: The proportion of musculoskeletal injuries have increased from 2016-2020. Unspecified assault and all types of falls pushed the road traffic accidents to third position during the lockdown period in 2020 as compared to previous four years. Injury surveillance needs to be integrated in routine hospital system for precise information and for more efficient functioning.

8.
Monaldi Arch Chest Dis ; 90(3)2020 Jul 22.
Article in English | MEDLINE | ID: covidwho-665524

ABSTRACT

Disease associated with SARS-CoV-2 also termed as Coronavirus disease 2019 or COVID-19, has become a potential threat to public health by spreading across more than 200 countries worldwide within a short span of time. Tuberculosis (TB) is already existing as unprecedented pandemic worldwide over several years. Both diseases have many overlapping features but there are striking differences too. There is usually chronicity of symptoms in TB as compared to acute or rapid progression in COVID-19. Little evidence exists regarding TB and COVID-19 coinfection. It is anticipated that person with TB either in active, previously treated or latent forms are more at risk of poor outcomes with COVID-19. The relationship between the two diseases is still unclear at present, and more studies are needed to enable analyses of interactions and determinants of outcomes in patients affected by both the diseases. Most of the countries across the world imposed nationwide lockdown to promote social distancing, which is one important preventive measure to mitigate the spread of COVID-19 pandemic. However, it becomes quite challenging to ensure smooth functioning of programmatic services, leading to disruption of routine TB care, leading to transmission of infection. Health authorities should frame polices that can support TB patients by providing diagnostic, management and prevention services without any interruption during this era of ongoing COVID-19 pandemic. Effort should be made to control both the diseases simultaneously and avoid unfavourable outcome in near future.


Subject(s)
Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Tuberculosis, Pulmonary/epidemiology , COVID-19 , Coinfection , Coronavirus Infections/prevention & control , Humans , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Tuberculosis, Pulmonary/prevention & control , Tuberculosis, Pulmonary/therapy
10.
Lung India ; 37(4): 292-294, 2020.
Article in English | MEDLINE | ID: covidwho-640488
11.
Indian J Surg ; 82(3): 295-296, 2020 Jun.
Article in English | MEDLINE | ID: covidwho-591833
12.
Indian J Surg ; 82(3): 293-294, 2020 Jun.
Article in English | MEDLINE | ID: covidwho-574650
13.
Int J Surg ; 79: 215-216, 2020 07.
Article in English | MEDLINE | ID: covidwho-548934
14.
Indian J Surg ; 82(3): 288, 2020 Jun.
Article in English | MEDLINE | ID: covidwho-505734
15.
Indian J Surg ; 82(3): 286-287, 2020 Jun.
Article in English | MEDLINE | ID: covidwho-459234
16.
Int J Surg ; 79: 165-167, 2020 Jul.
Article in English | MEDLINE | ID: covidwho-437477

ABSTRACT

Coronavirus Disease 2019(COVID 19) had emerged as a global pandemic in recent times. The healthcare sector is at the epicentre of this unprecedented global pandemic challenge. Hospitals all over the world have reduced the number of non-emergency surgeries in order to utilise the staff and resources in a more efficient way. Severe acute respiratory syndrome coronavirus (SARS-CoV-2) is most transmitted via respiratory droplets, but risk of transmission is hugely increased while doing aerosol generating procedures (AGPs). Laparoscopy remains the preferred surgical approach for most surgical indications. There is theoretical possibility of generation of aerosols contaminated with COVID-19 from leaked CO2 and smoke generation after energy device use. The aim of this paper is to review available evidence evaluating the risk of spread of COVID-19 during necessary laparoscopic procedures and to compile guidelines from relevant professional organizations to minimize this risk.


Subject(s)
Coronavirus Infections/transmission , Infectious Disease Transmission, Patient-to-Professional/prevention & control , Laparoscopy , Pandemics , Pneumonia, Viral/transmission , Aerosols , Betacoronavirus , COVID-19 , Coronavirus Infections/epidemiology , Humans , India/epidemiology , Infection Control , Laparoscopy/methods , Pneumonia, Viral/epidemiology , Practice Guidelines as Topic , SARS-CoV-2 , Surgeons
17.
Indian J Surg ; : 1, 2020 May 26.
Article in English | MEDLINE | ID: covidwho-361340
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