scholarly journals Erratum to: An overview of the National COVID-19 Chest Imaging Database: data quality and cohort analysis

GigaScience ◽  
2021 ◽  
Vol 10 (12) ◽  
Author(s):  
Dominic Cushnan ◽  
Oscar Bennett ◽  
Rosalind Berka ◽  
Ottavia Bertolli ◽  
Ashwin Chopra ◽  
...  
GigaScience ◽  
2021 ◽  
Vol 10 (11) ◽  
Author(s):  
Dominic Cushnan ◽  
Oscar Bennett ◽  
Rosalind Berka ◽  
Ottavia Bertolli ◽  
Ashwin Chopra ◽  
...  

Abstract Background The National COVID-19 Chest Imaging Database (NCCID) is a centralized database containing mainly chest X-rays and computed tomography scans from patients across the UK. The objective of the initiative is to support a better understanding of the coronavirus SARS-CoV-2 disease (COVID-19) and the development of machine learning technologies that will improve care for patients hospitalized with a severe COVID-19 infection. This article introduces the training dataset, including a snapshot analysis covering the completeness of clinical data, and availability of image data for the various use-cases (diagnosis, prognosis, longitudinal risk). An additional cohort analysis measures how well the NCCID represents the wider COVID-19–affected UK population in terms of geographic, demographic, and temporal coverage. Findings The NCCID offers high-quality DICOM images acquired across a variety of imaging machinery; multiple time points including historical images are available for a subset of patients. This volume and variety make the database well suited to development of diagnostic/prognostic models for COVID-associated respiratory conditions. Historical images and clinical data may aid long-term risk stratification, particularly as availability of comorbidity data increases through linkage to other resources. The cohort analysis revealed good alignment to general UK COVID-19 statistics for some categories, e.g., sex, whilst identifying areas for improvements to data collection methods, particularly geographic coverage. Conclusion The NCCID is a growing resource that provides researchers with a large, high-quality database that can be leveraged both to support the response to the COVID-19 pandemic and as a test bed for building clinically viable medical imaging models.


2021 ◽  
Author(s):  
Dominic Cushnan ◽  
Oscar Bennett ◽  
Rosalind Berka ◽  
Ottavia Bertolli ◽  
Ashwin Chopra ◽  
...  

AbstractThe National COVID-19 Chest Imaging Database (NCCID) is a centralised database containing chest X-rays, chest Computed Tomography (CT) scans and cardiac Magnetic Resonance Images (MRI) from patients across the UK, jointly established by NHSX, the British Society of Thoracic Imaging (BSTI), Royal Surrey NHS Foundation Trust (RSNFT) and Faculty. The objective of the initiative is to support a better understanding of the coronavirus SARS-CoV-2 disease (COVID-19) and development of machine learning (ML) technologies that will improve care for patients hospitalised with a severe COVID-19 infection. The NCCID is now accumulating data from 20 NHS Trusts and Health Boards across England and Wales, with a total contribution of approximately 25,000 imaging studies in the training set (at time of writing) and is actively being used as a research tool by several organisations. This paper introduces the training dataset, including a snapshot analysis performed by NHSX covering: the completeness of clinical data, the availability of image data for the various use-cases (diagnosis, prognosis and longitudinal risk) and potential model confounders within the imaging data. The aim is to inform both existing and potential data users of the NCCID’s suitability for developing diagnostic/prognostic models. In addition, a cohort analysis was performed to measure the representativeness of the NCCID to the wider COVID-19 affected population. Three major aspects were included: geographic, demographic and temporal coverage, revealing good alignment in some categories, e.g., sex and identifying areas for improvements to data collection methods, particularly with respect to geographic coverage. All analyses and discussions are focused on the implications for building ML tools that will generalise well to the clinical use cases.


Author(s):  
Melen McBride

Ethnogeriatrics is an evolving specialty in geriatric care that focuses on the health and aging issues in the context of culture for older adults from diverse ethnic backgrounds. This article is an introduction to ethnogeriatrics for healthcare professionals including speech-language pathologists (SLPs). This article focuses on significant factors that contributed to the development of ethnogeriatrics, definitions of some key concepts in ethnogeriatrics, introduces cohort analysis as a teaching and clinical tool, and presents applications for speech-language pathology with recommendations for use of cohort analysis in practice, teaching, and research activities.


2012 ◽  
Author(s):  
Nurul A. Emran ◽  
Noraswaliza Abdullah ◽  
Nuzaimah Mustafa

2019 ◽  
pp. 5-28
Author(s):  
Vadim V. Radaev

A sociological approach towards the generational cohort analysis is developed. A special emphasis is made upon the youngest adult generation of millennials coming out of their adolescence in the 2000s. A broad range of social indicators is used for empirical exploration of intra-generational differences between urban and rural millennials. Data were collected from the annual Russian Longitudinal Monitoring Survey (RLMS-HSE) in 2003—2016. Numerous significant differences have been revealed with regard to the educational level, family planning, use of modern gadgets and digital technologies, commitment to healthy lifestyles, and some values. Some practices are more widely spread among rural millennials, whereas other practices are more characteristic of urban millennials. Most of revealed differences are explained by the lower level of material well-being of rural millennials and lower quality of rural infrastructure.


2013 ◽  
pp. 97-116 ◽  
Author(s):  
A. Apokin

The author compares several quantitative and qualitative approaches to forecasting to find appropriate methods to incorporate technological change in long-range forecasts of the world economy. A?number of long-run forecasts (with horizons over 10 years) for the world economy and national economies is reviewed to outline advantages and drawbacks for different ways to account for technological change. Various approaches based on their sensitivity to data quality and robustness to model misspecifications are compared and recommendations are offered on the choice of appropriate technique in long-run forecasts of the world economy in the presence of technological change.


2020 ◽  
Vol 3 (3) ◽  
pp. 297-310 ◽  
Author(s):  
Rafael Ricafranca Castillo ◽  
Gino Rei A. Quizon ◽  
Mario Joselito M. Juco ◽  
Arthur Dessi E. Roman ◽  
Donnah G De Leon ◽  
...  

 Treatment for coronavirus disease 2019 (COVID19) pneumonia remains empirical and the search for therapies that can improve outcomes continues. Melatonin has been shown to have anti-inflammatory, antioxidant, and immune-modulating effects that may address key pathophysiologic mechanisms in the development and progression of acute respiratory distress syndrome (ARDS), which has been implicated as the likely cause of death in COVID19. We aimed to describe the observable clinical outcomes and tolerability of high-dose melatonin (hdM) given as adjuvant therapy in patients admitted with COVID19 pneumonia. We conducted a retrospective descriptive case series of patients who: 1) were admitted to the Manila Doctors Hospital in Manila, Philippines, between March 5, 2020 and April 4, 2020; 2) presented with history of typical symptoms (fever, cough, sore throat, loss of smell and/or taste, myalgia, fatigue); 3) had admitting impression of atypical pneumonia; 4) had history and chest imaging findings highly suggestive of COVID19 pneumonia, and, 5) were given hdM as adjuvant therapy, in addition to standard and/or empirical therapy. One patient admitted to another hospital, who one of the authors helped co-manage, was included. He was the lone patient given hdM in that hospital during the treatment period. Main outcomes described were: time to clinical improvement, duration of hospital stay from hdM initiation, need for mechanical ventilation (MV) prior to cardiopulmonary resuscitation, and final outcome (death or recovery/discharge). Of 10 patients given hdM at doses of 36-72mg/day per os (p.o.) in 4 divided doses as adjuvant therapy, 7 were confirmed COVID19 positive (+) by reverse transcription polymerase chain reaction (RT-PCR) and 3 tested negative  (-), which was deemed to be false (-) considering the patients’ typical history, symptomatology, chest imaging findings and elevated bio-inflammatory parameters.  In all 10 patients given hdM, clinical stabilization and/or improvement was noted within 4-5 days after initiation of hdM. All hdM patients, including 3 with moderately severe ARDS and 1 with mild ARDS, survived; none required MV. The 7 COVID19(+) patients were discharged at an average of 8.6 days after initiation of hdM. The 3 highly probable COVID19 patients on hdM were discharged at an average of 7.3 days after hdM initiation. Average hospital stay of those not given hdM (non-hdM) COVID19(+) patients who were admitted during the same period and recovered was 13 days. To provide perspective, although the groups are not comparable, 12 of the 34 (35.3%) COVID19(+) non-hdM patients admitted during the same period died, 7/34 (20.6%) required MV; while 6 of 15 (40%) non-hdM (-) by RT-PCR but highly probable COVID19 pneumonia patients also died, 4/15  (26.7%) required MV. No significant side-effects were noted with hdM except for sleepiness, which was deemed favorable by all patients, most of whom had anxiety- and symptom-related sleeping problems previously. HdM may have a beneficial role in patients treated for COVID19 pneumonia, in terms of shorter time to clinical improvement, less need for MV, shorter hospital stay, and possibly lower mortality. HdM was well tolerated. This is the first report describing the benefits of hdM in patients being treated for COVID19 pneumonia.  Being a commonly available and inexpensive sleep-aid supplement worldwide, melatonin may play a role as adjuvant therapy in the global war against COVID19. 


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