Publications by authors named "V Sounderajah"

31 Publications

YouTube as a source of public health information regarding COVID-19 vaccination: an assessment of reliability and quality of video content.

JMIR Public Health Surveill 2021 May 21. Epub 2021 May 21.

Department of Surgery & Cancer, Imperial College London, Department of Surgery and Cancer10th floor, Queen Elizabeth Queen Mother Building, St. Mary's Hospital, South Wharf Road, Paddington, GB.

Background: Recent emergency authorisation and rollout of COVID-19 vaccines by regulatory bodies has generated global attention. As the most popular video-sharing platform globally, YouTube is a potent medium for dissemination of key public health information. Understanding the nature of available content regarding COVID-19 vaccination on this widely used platform is of substantial public health interest.

Objective: To evaluate the reliability and quality of information of YouTube videos regarding COVID-19 vaccination.

Methods: For this cross-sectional study, the phrases 'coronavirus vaccine' and 'COVID-19 vaccine' were searched on the UK version of YouTube on December 10, 2020. The 200 most-viewed videos of each search were extracted and screened for relevance and English language. Video content and characteristics were extracted and independently rated against Health on the Net Foundation Code of Conduct (HONcode) and DISCERN quality criteria for consumer health information by two authors.

Results: Forty-eight videos, with a combined total view count of 30,100,561, were included in the analysis. Topics addressed comprised: vaccine science (58%), vaccine trials (58%), side effects (48%), efficacy (35%) and manufacturing (17%). Twenty-one percent of videos encouraged continued public health measures. Only 4.2% of videos made non-factual claims. Ninety-eight percent of video content was scored to have low (56%) or moderate (42%) adherence to HONcode principles. Median overall DISCERN score per channel type ranged from 40.3 (34.8-47) to 64.3 (58.5-66.3). Educational channels produced by both medical and non-medical professionals achieved significantly higher DISCERN scores than other categories. The highest DISCERN scores were achieved by educational videos produced by medical professionals (64.3 (58.5-66.3)) and the lowest scores by independent users (18 (18-20)).

Conclusions: Overall quality and reliability of information on YouTube regarding COVID-19 vaccines remains poor. Videos produced by educational channels, especially by medical professionals, were higher in quality and reliability than those produced by other sources, including health-related organisations. Collaboration between health-related organisations and established medical and educational YouTube content producers provides an opportunity for dissemination of high-quality information regarding COVID-19 vaccination. Such collaboration holds potential as a rapidly implementable public health intervention aiming to engage a wide audience and increase public vaccination awareness and knowledge.

Clinicaltrial:
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2196/29942DOI Listing
May 2021

Characteristics and predictors of acute and chronic post-COVID syndrome: A systematic review and meta-analysis.

EClinicalMedicine 2021 Jun 24;36:100899. Epub 2021 May 24.

Department of Surgery and Cancer, Imperial College London, St Mary's Hospital, London W2 1NY, UK.

Background: A significant proportion of individuals experience lingering and debilitating symptoms following acute COVID-19 infection. The National Institute for Health and Care Excellence (NICE) have coined the persistent cluster of symptoms as post-COVID syndrome. This has been further sub-categorised into acute post-COVID syndrome for symptoms persisting three weeks beyond initial infection and chronic post-COVID syndrome for symptoms persisting beyond twelve weeks. The aim of this review was to detail the prevalence of clinical features and identify potential predictors for acute and chronic post-COVID syndrome.

Methods: A systematic literature search, with no language restrictions, was performed to identify studies detailing characteristics and outcomes related to survivorship of post-COVID syndrome. The last search was performed on 6 March 2021 and all pre-dating published articles included. A means of proportion meta-analysis was performed to quantify characteristics of acute and chronic post-COVID syndrome. Study quality was assessed with a specific risk of bias tool. PROSPERO Registration: CRD42020222855.

Findings: A total of 43 studies met the eligibility criteria; of which, 38 allowed for meta-analysis. Fatigue and dyspnoea were the most prevalent symptoms in acute post-COVID (0·37 and 0·35) and fatigue and sleep disturbance in chronic post-COVID syndrome (0·48 and 0·44), respectively. The available evidence is generally of poor quality, with considerable risk of bias, and are of observational design.

Interpretation: In conclusion, this review highlights that flaws in data capture and interpretation, noted in the uncertainty within our meta-analysis, affect the applicability of current knowledge. Policy makers and researchers must focus on understanding the impact of this condition on individuals and society with appropriate funding initiatives and global collaborative research.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.eclinm.2021.100899DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8141371PMC
June 2021

Patient-reported outcomes after oesophagectomy in the multicentre LASER study.

Br J Surg 2021 May 11. Epub 2021 May 11.

Oesophago-gastric Centre, Churchill Hospital, University of Oxford, Oxford, UK.

Background: Data on the long-term symptom burden in patients surviving oesophageal cancer surgery are scarce. The aim of this study was to identify the most prevalent symptoms and their interactions with health-related quality of life.

Methods: This was a cross-sectional cohort study of patients who underwent oesophageal cancer surgery in 20 European centres between 2010 and 2016. Patients had to be disease-free for at least 1 year. They were asked to complete a 28-symptom questionnaire at a single time point, at least 1 year after surgery. Principal component analysis was used to assess for clustering and association of symptoms. Risk factors associated with the development of severe symptoms were identified by multivariable logistic regression models.

Results: Of 1081 invited patients, 876 (81.0 per cent) responded. Symptoms in the preceding 6 months associated with previous surgery were experienced by 586 patients (66.9 per cent). The most common severe symptoms included reduced energy or activity tolerance (30.7 per cent), feeling of early fullness after eating (30.0 per cent), tiredness (28.7 per cent), and heartburn/acid or bile regurgitation (19.6 per cent). Clustering analysis showed that symptoms clustered into six domains: lethargy, musculoskeletal pain, dumping, lower gastrointestinal symptoms, regurgitation/reflux, and swallowing/conduit problems; the latter two were the most closely associated. Surgical approach, neoadjuvant therapy, patient age, and sex were factors associated with severe symptoms.

Conclusion: A long-term symptom burden is common after oesophageal cancer surgery.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/bjs/znab124DOI Listing
May 2021

Determinants of burnout and other aspects of psychological well-being in healthcare workers during the Covid-19 pandemic: A multinational cross-sectional study.

PLoS One 2021 16;16(4):e0238666. Epub 2021 Apr 16.

Department of Surgery and Cancer, Imperial College London, London, United Kingdom.

The Covid-19 pandemic has placed unprecedented pressure on healthcare systems and workers around the world. Such pressures may impact on working conditions, psychological wellbeing and perception of safety. In spite of this, no study has assessed the relationship between safety attitudes and psychological outcomes. Moreover, only limited studies have examined the relationship between personal characteristics and psychological outcomes during Covid-19. From 22nd March 2020 to 18th June 2020, healthcare workers from the United Kingdom, Poland, and Singapore were invited to participate using a self-administered questionnaire comprising the Safety Attitudes Questionnaire (SAQ), Oldenburg Burnout Inventory (OLBI) and Hospital Anxiety and Depression Scale (HADS) to evaluate safety culture, burnout and anxiety/depression. Multivariate logistic regression was used to determine predictors of burnout, anxiety and depression. Of 3,537 healthcare workers who participated in the study, 2,364 (67%) screened positive for burnout, 701 (20%) for anxiety, and 389 (11%) for depression. Significant predictors of burnout included patient-facing roles: doctor (OR 2.10; 95% CI 1.49-2.95), nurse (OR 1.38; 95% CI 1.04-1.84), and 'other clinical' (OR 2.02; 95% CI 1.45-2.82); being redeployed (OR 1.27; 95% CI 1.02-1.58), bottom quartile SAQ score (OR 2.43; 95% CI 1.98-2.99), anxiety (OR 4.87; 95% CI 3.92-6.06) and depression (OR 4.06; 95% CI 3.04-5.42). Significant factors inversely correlated with burnout included being tested for SARS-CoV-2 (OR 0.64; 95% CI 0.51-0.82) and top quartile SAQ score (OR 0.30; 95% CI 0.22-0.40). Significant factors associated with anxiety and depression, included burnout, gender, safety attitudes and job role. Our findings demonstrate a significant burden of burnout, anxiety, and depression amongst healthcare workers. A strong association was seen between SARS-CoV-2 testing, safety attitudes, gender, job role, redeployment and psychological state. These findings highlight the importance of targeted support services for at risk groups and proactive SARS-CoV-2 testing of healthcare workers.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0238666PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8051812PMC
May 2021

Diagnostic accuracy of deep learning in medical imaging: a systematic review and meta-analysis.

NPJ Digit Med 2021 Apr 7;4(1):65. Epub 2021 Apr 7.

Institute of Global Health Innovation, Imperial College London, London, UK.

Deep learning (DL) has the potential to transform medical diagnostics. However, the diagnostic accuracy of DL is uncertain. Our aim was to evaluate the diagnostic accuracy of DL algorithms to identify pathology in medical imaging. Searches were conducted in Medline and EMBASE up to January 2020. We identified 11,921 studies, of which 503 were included in the systematic review. Eighty-two studies in ophthalmology, 82 in breast disease and 115 in respiratory disease were included for meta-analysis. Two hundred twenty-four studies in other specialities were included for qualitative review. Peer-reviewed studies that reported on the diagnostic accuracy of DL algorithms to identify pathology using medical imaging were included. Primary outcomes were measures of diagnostic accuracy, study design and reporting standards in the literature. Estimates were pooled using random-effects meta-analysis. In ophthalmology, AUC's ranged between 0.933 and 1 for diagnosing diabetic retinopathy, age-related macular degeneration and glaucoma on retinal fundus photographs and optical coherence tomography. In respiratory imaging, AUC's ranged between 0.864 and 0.937 for diagnosing lung nodules or lung cancer on chest X-ray or CT scan. For breast imaging, AUC's ranged between 0.868 and 0.909 for diagnosing breast cancer on mammogram, ultrasound, MRI and digital breast tomosynthesis. Heterogeneity was high between studies and extensive variation in methodology, terminology and outcome measures was noted. This can lead to an overestimation of the diagnostic accuracy of DL algorithms on medical imaging. There is an immediate need for the development of artificial intelligence-specific EQUATOR guidelines, particularly STARD, in order to provide guidance around key issues in this field.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41746-021-00438-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8027892PMC
April 2021