Imperial College London

MrHutanAshrafian

Faculty of MedicineDepartment of Surgery & Cancer

 
 
 
//

Contact

 

+44 (0)20 3312 7651h.ashrafian

 
 
//

Location

 

1089Queen Elizabeth the Queen Mother Wing (QEQM)St Mary's Campus

//

Summary

 

Publications

Publication Type
Year
to

424 results found

Clarke J, Flott K, Crespo R, Ashrafian H, Fontana G, Benger J, Darzi A, Elkin Set al., 2021, Assessing the Safety of Home Oximetry for Covid-19: A multi-site retrospective observational study, BMJ Open, ISSN: 2044-6055

Objectives To determine the safety and effectiveness of home oximetry monitoring pathways safe for Covid-19 patients in the English NHS.Design Retrospective, multi-site, observational study of home oximetry monitoring for patients with suspected or proven Covid-19 Setting This study analysed patient data from four Covid-19 home oximetry pilot sites in England across primary and secondary care settings.Participants A total of 1338 participants were enrolled in a home oximetry programme across four pilot sites. Participants were excluded if primary care data and oxygen saturations are rest at enrolment were not available. Data from 908 participants was included in the analysis. Interventions Home oximetry monitoring was provided to participants with a known or suspected diagnosis of Covid-19. Participants were enrolled following attendance to emergency departments, hospital admission or referral through primary care services. Results Of 908 patients enrolled into four different Covid-19 home oximetry programmes in England, 771 (84.9%) had oxygen saturations at rest of 95% or more, and 320 (35.2%) were under 65 years of age and without comorbidities. 52 (5.7%) presented to hospital and 28 (3.1%) died following enrolment, of which 14 (50%) had Covid-19 as a named cause of death. All-cause mortality was significantly higher in patients enrolled after admission to hospital (OR 8.70 [2.53-29.89]), compared to those enrolled in primary care. Patients enrolled after hospital discharge (OR 0.31 [0.15-0.68]) or emergency department presentation (OR 0.42 [0.20-0.89]) were significantly less likely to present to hospital than those enrolled in primary care. ConclusionsThis study find that home oximetry monitoring can be a safe pathway for Covid-19 patients; and indicates increases in risk to vulnerable groups and patients with oxygen saturations < 95% at enrolment, and in those enrolled on discharge from hospital. Findings from this evaluation have contributed to the national

Journal article

Acharya A, Lam K, Danielli S, Ashrafian H, Darzi Aet al., 2021, COVID-19 vaccinations among Black Asian and Minority Ethnic (BAME) groups: Learning the lessons from influenza, INTERNATIONAL JOURNAL OF CLINICAL PRACTICE, ISSN: 1368-5031

Journal article

Che Bakri NA, Kwasnicki R, Dhillon K, Ghandour O, Khan N, Cairns A, Darzi A, Leff Det al., 2021, Objective assessment of post-operative morbidity following breast cancer treatments with wearable activity monitors, Annals of Surgical Oncology, Vol: 28, Pages: 5597-5606, ISSN: 1068-9265

BackgroundCurrent validated tools to measure upper limb dysfunction after breast cancer treatment, such as questionnaires, are prone to recall bias and do not enable comparisons between patients. This study aimed to test the feasibility of wearable activity monitors (WAMs) for achieving a continuous, objective assessment of functional recovery by measuring peri-operative physical activity (PA).MethodsA prospective, single-center, non-randomized, observational study was conducted. Patients undergoing breast and axillary surgery were invited to wear WAMs on both wrists in the peri-operative period and then complete upper limb function (DASH) and quality-of-life (EQ-5D-5L) questionnaires. Statistical analyses were performed to determine the construct validity and concurrent validity of WAMs.ResultsThe analysis included 39 patients with a mean age of 55 ± 13.2 years. Regain of function on the surgically treated side was observed to be an increase of arm activity as a percentage of preoperative levels, with the greatest increase observed between the postoperative days 1 and 2. The PA was significantly greater on the side not treated by surgery than on the surgically treated side after week 1 (mean PA, 75.8% vs. 62.3%; p < 0.0005) and week 2 (mean PA, 91.6% vs. 77.4%; p < 0.005). Subgroup analyses showed differences in recovery trends between different surgical procedures. Concurrent validity was demonstrated by a significant negative moderate correlation between the PA and DASH questionnaires (R = −0.506; p < 0.05).ConclusionThis study demonstrated the feasibility and validity of WAMs to objectively measure postoperative recovery of upper limb function after breast surgery, providing a starting point for personalized rehabilitation through early detection of upper limb physical morbidity.

Journal article

Li E, Clarke J, Neves AL, Ashrafian H, Darzi Aet al., 2021, Electronic health records, interoperability, and patient safety in health systems of high-income countries: a systematic review protocol, BMJ Open, Vol: 11, ISSN: 2044-6055

Introduction The availability and routine use of electronic health records (EHRs) have become commonplace in healthcare systems of many high-income countries. While there is an ever-growing body ofliterature pertaining to EHR use, evidence surrounding the importance of EHR interoperability and its impact on patient safety remains less clear. There is therefore a need and opportunity to evaluate the evidence available regarding this relationship so as to better inform health informatics development and policies in the years to come. This systematic review aims to evaluate the impact of EHR interoperability on patient safety in health systems of high-income countries. Methods and analysis A systematic literature review will be conducted via a computerised search through four databases: PubMed, Embase, HMIC, and PsycInfo for relevant articles published between 2010 and 2020. Outcomes of interest will include: impact on patient safety, and the broader effects on health systems. Quality of the randomised quantitative studies will be assessed using Cochrane Risk of Bias Tool. Non-randomised papers will be evaluated with the Risk of Bias In Non Randomised Studies - of Interventions (ROBINS-I) tool. Drummond’s Checklist will be utilised for publications pertaining to economic evaluation. The National Institute for Health and Care Excellence (NICE) quality appraisal checklist will be used to assess qualitative studies. A narrative synthesis will be conducted for included studies, and the body of evidence will be summarised in a summary of findings table. Ethics and dissemination This review will summarise published studies with non-identifiable data and thus does not require ethical approval. Findings will be disseminated through preprints, open access peer reviewed publication, and conference presentations

Journal article

Nazarian S, Glover B, Ashrafian H, Darzi A, Teare Jet al., 2021, Diagnostic Accuracy of Artificial Intelligence and Computer-Aided Diagnosis for the Detection and Characterization of Colorectal Polyps: Systematic Review and Meta-analysis, JOURNAL OF MEDICAL INTERNET RESEARCH, Vol: 23, ISSN: 1438-8871

Journal article

Aggarwal R, Farag S, Martin G, Ashrafian H, Darzi Aet al., 2021, Patient perceptions on data sharing and applying artificial intelligence to healthcare data: a cross sectional survey, Journal of Medical Internet Research, Vol: 23, Pages: 1-12, ISSN: 1438-8871

Background:Considerable research is being conducted as to how artificial intelligence (AI) can be effectively applied to healthcare. However, for it to be successful, large amounts of health data are required for the training and testing of algorithms. Data sharing for this purpose is controversial, therefore it is imperative to understand patient perceptions on this.Objective:To understand the perspectives and viewpoints of patients regarding the use of their health data in AI research.Methods:A cross-sectional survey with patients was conducted at a large multi-site teaching hospital in the United Kingdom. Data were collected on patient and public views about sharing health data for research and the use of AI on health data.Results:A total of 408 participants completed the survey. Respondents had low levels of prior knowledge of AI in general. Most were comfortable with sharing health data with the NHS (77·9%) or universities (65·7%), but far fewer with commercial organisations such as technology companies (26·4%). The majority endorsed AI research on healthcare data (76·8%) and healthcare imaging (76·4%) in a university setting, providing that concerns about privacy, re-identification of anonymised health care data and consent processes were addressed.Conclusions:There is significant variance in patient perceptions, levels of support, and understanding of health data research and AI. There is a need for greater public engagement and debate to ensure the acceptability of AI research and its successful integration into clinical practice in the future.

Journal article

Chan C, Sounderajah V, Daniels E, Acharya A, Clarke J, Yalamanchili S, Normahani P, Markar S, Ashrafian H, Darzi Aet al., 2021, The reliability and quality of YouTube videos as a source of public health information regarding COVID-19 vaccination: cross-sectional study, JMIR Public Health and Surveillance, Vol: 7, ISSN: 2369-2960

Background: Recent emergency authorization 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 the 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: This study aimed to evaluate the reliability and quality of information on COVID-19 vaccination in YouTube videos.Methods: In 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 and DISCERN quality criteria for consumer health information by 2 authors.Results: Forty-eight videos, with a combined total view count of 30,100,561, were included in the analysis. Topics addressed comprised the following: vaccine science (n=18, 58%), vaccine trials (n=28, 58%), side effects (n=23, 48%), efficacy (n=17, 35%), and manufacturing (n=8, 17%). Ten (21%) videos encouraged continued public health measures. Only 2 (4.2%) videos made nonfactual claims. The content of 47 (98%) videos was scored to have low (n=27, 56%) or moderate (n=20, 42%) adherence to Health on the Net Foundation Code of Conduct principles. Median overall DISCERN score per channel type ranged from 40.3 (IQR 34.8-47.0) to 64.3 (IQR 58.5-66.3). Educational channels produced by both medical and nonmedical professionals achieved significantly higher DISCERN scores than those of other categories. The highest median DISCERN scores were achieved by educational videos produced by medical professionals (64.3, IQR 58.5-66.3) and the lowest median scores by indep

Journal article

Kedrzycki MS, Leiloglou M, Ashrafian H, Jiwa N, Thiruchelvam PTR, Elson DS, Leff DRet al., 2021, Meta-analysis comparing fluorescence imaging with radioisotope and blue dye-guided sentinel node identification for breast cancer surgery., Annals of Surgical Oncology, Vol: 28, Pages: 3738-3748, ISSN: 1068-9265

INTRODUCTION: Conventional methods for axillary sentinel lymph node biopsy (SLNB) are fraught with complications such as allergic reactions, skin tattooing, radiation, and limitations on infrastructure. A novel technique has been developed for lymphatic mapping utilizing fluorescence imaging. This meta-analysis aims to compare the gold standard blue dye and radioisotope (BD-RI) technique with fluorescence-guided SLNB using indocyanine green (ICG). METHODS: This study was registered with PROSPERO (CRD42019129224). The MEDLINE, EMBASE, Scopus, and Web of Science databases were searched using the Medical Subject Heading (MESH) terms 'Surgery' AND 'Lymph node' AND 'Near infrared fluorescence' AND 'Indocyanine green'. Studies containing raw data on the sentinel node identification rate in breast cancer surgery were included. A heterogeneity test (using Cochran's Q) determined the use of fixed- or random-effects models for pooled odds ratios (OR). RESULTS: Overall, 1748 studies were screened, of which 10 met the inclusion criteria for meta-analysis. ICG was equivalent to radioisotope (RI) at sentinel node identification (OR 2.58, 95% confidence interval [CI] 0.35-19.08, p < 0.05) but superior to blue dye (BD) (OR 9.07, 95% CI 6.73-12.23, p < 0.05). Furthermore, ICG was superior to the gold standard BD-RI technique (OR 4.22, 95% CI 2.17-8.20, p < 0.001). CONCLUSION: Fluorescence imaging for axillary sentinel node identification with ICG is equivalent to the single technique using RI, and superior to the dual technique (RI-BD) and single technique with BD. Hospitals using RI and/or BD could consider changing their practice to ICG given the comparable efficacy and improved safety profile, as well as the lesser burden on hospital infrastructure.

Journal article

Sounderajah V, Ashrafian H, Golub RM, Shetty S, De Fauw J, Hooft L, Moons K, Collins G, Moher D, Bossuyt PM, Darzi A, Karthikesalingam A, Denniston AK, Mateen BA, Ting D, Treanor D, King D, Greaves F, Godwin J, Pearson-Stuttard J, Harling L, McInnes M, Rifai N, Tomasev N, Normahani P, Whiting P, Aggarwal R, Vollmer S, Markar SR, Panch T, Liu X, STARD-AI Steering Committeeet al., 2021, Developing a reporting guideline for artificial intelligence-centred diagnostic test accuracy studies: the STARD-AI protocol, BMJ Open, Vol: 11, ISSN: 2044-6055

Introduction Standards for Reporting of Diagnostic Accuracy Study (STARD) was developed to improve the completeness and transparency of reporting in studies investigating diagnostic test accuracy. However, its current form, STARD 2015 does not address the issues and challenges raised by artificial intelligence (AI)-centred interventions. As such, we propose an AI-specific version of the STARD checklist (STARD-AI), which focuses on the reporting of AI diagnostic test accuracy studies. This paper describes the methods that will be used to develop STARD-AI.Methods and analysis The development of the STARD-AI checklist can be distilled into six stages. (1) A project organisation phase has been undertaken, during which a Project Team and a Steering Committee were established; (2) An item generation process has been completed following a literature review, a patient and public involvement and engagement exercise and an online scoping survey of international experts; (3) A three-round modified Delphi consensus methodology is underway, which will culminate in a teleconference consensus meeting of experts; (4) Thereafter, the Project Team will draft the initial STARD-AI checklist and the accompanying documents; (5) A piloting phase among expert users will be undertaken to identify items which are either unclear or missing. This process, consisting of surveys and semistructured interviews, will contribute towards the explanation and elaboration document and (6) On finalisation of the manuscripts, the group’s efforts turn towards an organised dissemination and implementation strategy to maximise end-user adoption.Ethics and dissemination Ethical approval has been granted by the Joint Research Compliance Office at Imperial College London (reference number: 19IC5679). A dissemination strategy will be aimed towards five groups of stakeholders: (1) academia, (2) policy, (3) guidelines and regulation, (4) industry and (5) public and non-specific stakeholders. We anticipate th

Journal article

Li J, 2021, Roux-en-Y Gastric bypass-induced bacterial perturbation contributes to altered host-bacterial co-metabolic phenotype, Microbiome, Vol: 9, ISSN: 2049-2618

BACKGROUND: Bariatric surgery, used to achieve effective weight loss in individuals with severe obesity, modifies the gut microbiota and systemic metabolism in both humans and animal models. The aim of the current study was to understand better the metabolic functions of the altered gut microbiome by conducting deep phenotyping of bariatric surgery patients and bacterial culturing to investigate causality of the metabolic observations. METHODS: Three bariatric cohorts (n = 84, n = 14 and n = 9) with patients who had undergone Roux-en-Y gastric bypass (RYGB), sleeve gastrectomy (SG) or laparoscopic gastric banding (LGB), respectively, were enrolled. Metabolic and 16S rRNA bacterial profiles were compared between pre- and post-surgery. Faeces from RYGB patients and bacterial isolates were cultured to experimentally associate the observed metabolic changes in biofluids with the altered gut microbiome. RESULTS: Compared to SG and LGB, RYGB induced the greatest weight loss and most profound metabolic and bacterial changes. RYGB patients showed increased aromatic amino acids-based host-bacterial co-metabolism, resulting in increased urinary excretion of 4-hydroxyphenylacetate, phenylacetylglutamine, 4-cresyl sulphate and indoxyl sulphate, and increased faecal excretion of tyramine and phenylacetate. Bacterial degradation of choline was increased as evidenced by altered urinary trimethylamine-N-oxide and dimethylamine excretion and faecal concentrations of dimethylamine. RYGB patients' bacteria had a greater capacity to produce tyramine from tyrosine, phenylalanine to phenylacetate and tryptophan to indole and tryptamine, compared to the microbiota from non-surgery, normal weight individuals. 3-Hydroxydicarboxylic acid metabolism and urinary excretion of primary bile acids, serum BCAAs and dimethyl sulfone were also perturbed following bariatric surgery. CONCLUSION: Altered bacterial composition and metabolism contribute to metabolic observations in biofluid

Journal article

Sivananthan A, Nazarian S, Ayaru L, Patel K, Ashrafian H, Darzi A, Patel Net al., 2021, PERFORMANCE OF COMPUTER AIDED DETECTION SYSTEMS IN FLAT, SESSILE AND DIMINUITIVE ADENOMAS: A META-ANALYSIS, Publisher: MOSBY-ELSEVIER, Pages: AB197-AB197, ISSN: 0016-5107

Conference paper

Iqbal F, Lam K, Sounderajah V, Clarke J, Ashrafian H, Darzi Aet al., 2021, Characteristics and predictors of acute and chronic post-COVID syndrome: a systematic review and meta-analysis, EClinicalMedicine, Vol: 36, ISSN: 2589-5370

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: CRD42020222855Findings: 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) post-COVID syndrome, 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.

Journal article

Nazarian S, Glover B, Ashrafian H, Darzi A, Teare Jet al., 2021, The diagnostic accuracy of artificial intelligence and computer-aided diagnosis for the detection and characterisation of colorectal polyps: A systematic review and meta-analysis., Journal of Medical Internet Research, ISSN: 1438-8871

AimsColonoscopy reduces the incidence of colorectal cancer by allowing detection and resection of neoplastic polyps. Evidence shows that many small polyps are missed on a single colonoscopy. There has been a successful adoption of AI technologies to tackle the issues around missed polyps and as a tool to increase adenoma detection rate (ADR). The aim of this review was to examine the diagnostic accuracy of AI-based technologies in assessing colorectal polyps.MethodA comprehensive literature search was undertaken using the databases of EMBASE, Medline and the Cochrane Library. PRISMA guidelines were followed. Studies reporting use of computer-aided diagnosis for polyp detection or characterisation during colonoscopy were included. Independent proportion and their differences were calculated and pooled through DerSimonian and Laird random-effects modelling. ResultsA total of 48 studies were included. The meta-analysis showed a significant increase in pooled PDR in patients with the use of AI for polyp detection during colonoscopy compared with patients who had standard colonoscopy (OR 1.75; 95% CI 1.56-1.96; p= 0.0005). When comparing patients undergoing colonoscopy with the use of AI to those without, there was also a significant increase in ADR (OR 1.53; 95% CI 1.32-1.77; p= 0005). ConclusionWith the aid of machine learning, there is potential to improve ADR and consequently reduce the incidence of CRC. The current generation of AI-based systems demonstrate impressive accuracy for the detection and characterisation of colorectal polyps. However, this is an evolving field and before its adoption into a clinical setting, AI systems must prove worthy to patients and clinicians.

Journal article

Nabeel A, Al-Sabah SK, Ashrafian H, 2021, Effective cleaning of endoscopic lenses to achieve visual clarity for minimally invasive abdominopelvic surgery: a systematic review, SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES, ISSN: 0930-2794

Journal article

Jiwa N, Kedrzycki M, Kumar S, Gandhewar R, Chauhan H, Wright C, Takats Z, Ashrafian H, Leff DRet al., 2021, Diagnostic Accuracy of Nipple Discharge Fluid Cytology: A Meta-Analysis and Systematic Review of the Literature, Publisher: SPRINGER, Pages: S346-S347, ISSN: 1068-9265

Conference paper

Iqbal F, Joshi M, Khan S, Ashrafian H, Darzi Aet al., 2021, Implementation of wearable sensors and digital alerting systems in secondary care: protocol for a real-world prospective study evaluating clinical outcomes, JMIR Research Protocols, Vol: 10, ISSN: 1929-0748

ackground: Advancements in wearable sensors have caused a resurgence in their use, particularly because their miniaturization offers ambulatory advantages while performing continuous vital sign monitoring. Digital alerts can be generated following early recognition of clinical deterioration through breaches of set parameter thresholds, permitting earlier intervention. However, a systematic real-world evaluation of these alerting systems has yet to be conducted, and their efficacy remains unknown.Objective: The aim of this study is to implement wearable sensors and digital alerting systems in acute general wards to evaluate the resultant clinical outcomes.Methods: Participants on acute general wards will be screened and recruited into a trial with a pre-post implementation design. In the preimplementation phase, the SensiumVitals monitoring system, which continuously measures temperature, heart, and respiratory rates, will be used for monitoring alongside usual care. In the postimplementation phase, alerts will be generated from the SensiumVitals system when pre-established thresholds for vital parameters have been crossed, requiring acknowledgement from health care staff; subsequent clinical outcomes will be analyzed.Results: Enrolment is currently underway, having started in September 2017, and is anticipated to end shortly. Data analysis is expected to be completed in 2021.Conclusions: This study will offer insight into the implementation of digital health technologies within a health care trust and aims to describe the effectiveness of wearable sensors for ambulatory continuous monitoring and digital alerts on clinical outcomes in acute general ward settings.Trial Registration: ClinicalTrials.gov NCT04638738; https://clinicaltrials.gov/ct2/show/NCT04638738.International Registered Report Identifier (IRRID): DERR1-10.2196/26240

Journal article

Davids J, Makariou S-G, Ashrafian H, Darzi A, Marcus HJ, Giannarou Set al., 2021, Automated Vision-Based Microsurgical Skill Analysis in Neurosurgery Using Deep Learning: Development and Preclinical Validation, WORLD NEUROSURGERY, Vol: 149, Pages: E669-E686, ISSN: 1878-8750

Journal article

Glymenaki M, Curio S, Cabrera PM, Ashrafian H, Guerra N, Li JVet al., 2021, TYRAMINE IS A POTENTIAL CONTRIBUTOR TO INCREASED COLON CANCER RISK FOLLOWING BARIATRIC SURGERY, Publisher: W B SAUNDERS CO-ELSEVIER INC, Pages: S738-S738, ISSN: 0016-5085

Conference paper

Joshi M, Archer S, Morbi A, Arora S, Kwasnicki R, Ashrafian H, Khan S, Cooke G, Darzi Aet al., 2021, Short-Term Wearable Sensors for In-Hospital Medical and Surgical Patients: Mixed Methods Analysis of Patient Perspectives, JMIR Perioperative Medicine, Vol: 4, Pages: e18836-e18836

<jats:sec> <jats:title>Background</jats:title> <jats:p>Continuous vital sign monitoring using wearable sensors may enable early detection of patient deterioration and sepsis.</jats:p> </jats:sec> <jats:sec> <jats:title>Objective</jats:title> <jats:p>This study aimed to explore patient experiences with wearable sensor technology and carry out continuous monitoring through questionnaire and interview studies in an acute hospital setting.</jats:p> </jats:sec> <jats:sec> <jats:title>Methods</jats:title> <jats:p>Patients were recruited for a wearable sensor study and were asked to complete a 9-item questionnaire. Patients responses were evaluated using a Likert scale and with continuous variables. A subgroup of surgical patients wearing a Sensium Vital Sign Sensor was invited to participate in semistructured interviews. The Sensium wearable sensor measures the vital signs: heart rate, respiratory rate, and temperature. All interview data were subjected to thematic analysis.</jats:p> </jats:sec> <jats:sec> <jats:title>Results</jats:title> <jats:p>Out of a total of 500 patients, 453 (90.6%) completed the questionnaire. Furthermore, 427 (85.4%) patients agreed that the wearable sensor was comfortable, 429 (85.8%) patients agreed to wear the patch again when in hospital, and 398 (79.6%) patients agreed to wear the patch at home. Overall, 12 surgical patients consented to the interviews. Five main themes of interest to patients emerged from the interviews: (1) centralized monitoring, (2) enhanced feelings of patient safety, (3) impact on nursing staff, (4) comfort and usability, and (5) future use and views on technology.</jats:p> </jats:sec> <jats:sec> <jat

Journal article

Aggarwal R, Sounderajah V, Martin G, Ting D, Karthikesalingam A, King D, Ashrafian H, Darzi Aet al., 2021, Diagnostic accuracy of deep learning in medical imaging: a systematic review and meta-analysis, npj Digital Medicine, Vol: 4, ISSN: 2398-6352

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.

Journal article

Iqbal F, Joshi M, Davies G, Khan S, Ashrafian H, Darzi Aet al., 2021, The pilot, proof of concept REMOTE-COVID trial: remote monitoring use in suspected cases of COVID-19 (SARS-CoV 2), BMC Public Health, Vol: 21, Pages: 1-8, ISSN: 1471-2458

Background: SARS-CoV-2has ever-increasing attributed deaths. Vital sign trends are routinely used to monitor patients with changes in these parameters preceding an adverse event. Wearable sensors can measure vital signs continuously and remotely, outside of hospital facilities, recognising early clinical deterioration. We aim to determine the feasibility& acceptability of remote monitoring systems for quarantined individuals in a hotel suspected of COVID-19.Methods: A pilot, proof-of-concept, feasibility trial was conducted in engineered hotels near London airports(May-June 2020). Individuals arriving to London with mild suspected COVID-19 symptoms requiring quarantine, as recommended by Public Health England, or healthcare professionals with COVID-19 symptoms unable to isolate at home were eligible. The Sensium Vitals™ patch, measuring temperature, heart & respiratory rates, was applied on arrival for the duration of their stay. Alerts were generated when pre-established thresholds were breeched; trained nursing staff could consequently intervene. Results: Fourteen individuals (M=7, F=7) were recruited; the mean age was 34.9 (SD 11) years. Mean length of stay was 3 (SD 1.8) days. In total, 10 vital alerts were generated across 4 participants, resulting in telephone contact, reassurance, or adjustment of the sensor. No individuals required hospitalisation or virtual general practitioner review. Discussion: This proof-of-concept trial demonstrated the feasibility of a rapidly implemented model of healthcare delivery through remote monitoring during a pandemic at a hotel, acting as an extension to a healthcare trust. Benefits included reduced viral exposure to healthcare staff, with recognition of clinical deterioration through ambulatory, continuous, remote monitoring using a discrete wearable sensor. Conclusion: Remote monitoring systems can be applied to hotels to deliver healthcare safely in individuals suspected of COVID-19. Further w

Journal article

Nazarian S, Lam K, Darzi A, Ashrafian Het al., 2021, The diagnostic accuracy of smartwatches for the detection of cardiac arrhythmia: A systematic review and meta-analysis, Journal of Medical Internet Research, ISSN: 1438-8871

Background:A significant morbidity, mortality and financial burden is associated with cardiac rhythm abnormalities. Atrial fibrillation (AF) is the most common type of cardiac arrhythmia. Conventional screening tools are often unsuccessful at detecting AF due to its episodic nature. Smartwatches have gained popularity in recent years as a health screening tool.Objective:The aim of our study was to systematically review and meta-analyse the diagnostic accuracy of smartwatches in the detection of cardiac arrhythmias.Methods:A comprehensive literature search was undertaken using the databases of EMBASE, Medline and the Cochrane Library. PRISMA guidance was followed. Studies reporting use of a smartwatch for detection of cardiac arrythmia were included. Independent proportion and their differences were calculated and pooled through DerSimonian and Laird random-effects modelling. Quality was assessed using the QUADAS-2 tool.Results:A total of 18 studies were analysed, measuring diagnostic accuracy in 424, 371 subjects in total. The overall sensitivity, specificity and accuracy of smartwatches to detect cardiac arrhythmias was 100% (95% CI 0.99-1.00), 95% (95% CI 0.93-0.97) and 97% (95% CI 0.96-0.99), respectively. The pooled PPV and NPV for detecting cardiac arrythmias was 85% 85% (95% CI 0.79-0.90) and 100% (95% CI 1.0-1.0), respectively.Conclusions:This review demonstrates the evolving field of digital disease screening and the increased role of machine learning in healthcare. The current diagnostic accuracy of smartwatch technology for detection of cardiac arrhythmias is high. Whilst the innovative drive of digital devices in healthcare screening will continue to gain momentum, the process of accurate evidence accrual and regulatory standards ready to accept their introduction is strongly needed. Clinical Trial: PROSPERO registration number: CRD42020213237

Journal article

Sounderajah V, Clarke J, Yalamanchili S, Acharya A, Markar SR, Ashrafian H, Darzi Aet al., 2021, A national survey assessing public readiness for digital health strategies against COVID-19 within the United Kingdom, Scientific Reports, Vol: 11, Pages: 1-24, ISSN: 2045-2322

There is concern that digital public health initiatives used in the management of COVID-19 may marginalise certain population groups. There is an overlap between the demographics of groups at risk of digital exclusion (older, lower social grade, low educational attainment and ethnic minorities) and those who are vulnerable to poorer health outcomes from SARS-CoV-2. In this national survey study (n=2040), we assessed how the UK population; particularly these overlapping groups, reported their preparedness for digital health strategies. We report, with respect to using digital information to make health decisions, that those over 60 are less comfortable (net comfort: 57%) than those between 18-39 (net comfort: 78%) and lower social grades are less comfortable (net comfort: 63%) than higher social grades (net comfort: 75%). With respect to a preference for digital over non-digital sources in seeking COVID-19 health information, those over 60 (net preference: 21%) are less inclined than those between 18-39 (net preference: 60%) and those of low educational attainment (net preference: 30%) are less inclined than those of high educational attainment (net preference: 52%). Lastly, with respect to distinguishing reliable digital COVID-19 information, lower social grades (net confidence: 55%) are less confident than higher social grades (net confidence: 68%) and those of low educational attainment (net confidence: 51%) are less confident than those of high educational attainment (net confidence: 71%). All reported differences are statistically significant (p<0.01) following multivariate regression modelling. This study suggests that digital public health approaches to COVID-19 have the potential to marginalise groups who are concurrently at risk of digital exclusion and poor health outcomes from SARS-CoV-2.

Journal article

Iqbal F, Joshi M, Davies G, Hussain S, Ashrafian H, Darzi Aet al., 2021, Design of the pilot, proof of concept REMOTE-COVID trial: remote monitoring use in suspected cases of COVID-19 (SARS-CoV-2), Pilot and Feasibility Studies, Vol: 7, Pages: 1-7, ISSN: 2055-5784

Background: The outbreak of SARS-CoV-2 (coronavirus, COVID-19), declared a pandemic by the World Health Organisation (WHO) is global health problem with ever-increasing attributed deaths. Vital sign trends are routinely used to monitor patients with changes in these parameters often preceding an adverse event. Wearable sensors can measure vital signs continuously (e.g. heart rate, respiratory rate, temperature) remotely and can be utilised to recognise early clinical deterioration. Methods: We describe the protocol for a pilot, proof-of-concept, observational study to be conducted in an engineered hotel near London airports, United Kingdom. The study is set to continue for the duration of the pandemic. Individuals arriving to London with mild symptoms suggestive of COVID-19 or returning from high risk areas requiring quarantine, as recommended by Public Health England, or healthcare professionals with symptoms suggestive of COVID-19 unable to isolate at home will be eligible for a wearable patch to be applied for the duration of their stay. Notifications will be generated should deterioration be detected through the sensor and displayed on a central monitoring hub viewed by nursing staff, allowing for trend deterioration to be noted. The primary objective is to determine the feasibility of remote monitoring systems in detecting clinical deterioration for quarantined individuals in a hotel. Discussion: This trial should prove the feasibility of a rapidly implemented model of healthcare delivery through remote monitoring during a global pandemic at a hotel, acting as an extension to a healthcare trust. Potential benefits would include reducing infection risk of COVID-19 to healthcare staff, with earlier recognition of clinical deterioration through ambulatory, continuous, remote monitoring using a discrete wearable sensor. We hope our results can power future, robust future randomised trials.

Journal article

Moshe M, Daunt A, Flower B, Simmons B, Brown JC, Frise R, Penn R, Kugathasan R, Petersen C, Stockmann H, Ashby D, Riley S, Atchison C, Taylor GP, Satkunarajah S, Naar L, Klaber R, Badhan A, Rosadas C, Marchesin F, Fernandez N, Sureda-Vives M, Cheeseman H, O'Hara J, Shattock R, Fontana G, Pallett SJC, Rayment M, Jones R, Moore LSP, Ashrafian H, Cherapanov P, Tedder R, McClure M, Ward H, Darzi A, Cooke GS, Barclay WS, On behalf of the REACT Study teamet al., 2021, SARS-CoV-2 lateral flow assays for possible use in national covid-19 seroprevalence surveys (REACT2): diagnostic accuracy study, BMJ: British Medical Journal, Vol: 372, Pages: 1-8, ISSN: 0959-535X

Objective: To evaluate the performance of new lateral flow immunoassays (LFIAs) suitable for use in a national COVID-19 seroprevalence programme (REACT2).Design: Laboratory sensitivity and specificity analyses were performed for seven LFIAs on a minimum of 200 sera from individuals with confirmed SARS-CoV-2 infection, and 500 pre-pandemic sera respectively. Three LFIAs were found to have a laboratory sensitivity superior to the finger-prick sensitivity of the LFIA currently used in REACT2 seroprevalence studies (84%). These LFIAs were then further evaluated through finger-prick testing on participants with confirmed previous SARS-CoV-2 infection. Two LFIAs (Surescreen, Panbio) were evaluated in clinics in June-July, 2020, and a third LFIA (AbC-19) in September, 2020. A Spike protein enzyme-linked immunoassay (S-ELISA) and hybrid double antigen binding assay (DABA) were used as laboratory reference standards.Setting: Laboratory analyses were performed at Imperial College, London and University facilities in London, UK. Research clinics for finger-prick sampling were run in two affiliated NHS trusts.Participants: Sensitivity analysis on sera were performed on 320 stored samples from previous participants in the REACT2 programme with confirmed previous SARS-CoV-2 infection. Specificity analysis was performed using 1000 pre-pandemic sera. 100 new participants with confirmed previous SARS-CoV-2 infection attended study clinics for finger-prick testing.Main outcome measures: The accuracy of LFIAs in detecting IgG antibodies to SARS-CoV-2 in comparison to two in-house ELISAs.Results: The sensitivity of seven new LFIAs using sera varied between 69% and 100% (vs S-ELISA/hybrid DABA). Specificity using sera varied between 99.6% and 100%. Sensitivity on finger-prick testing for Panbio, Surescreen and AbC-19 was 77% (CI 61.4 to 88.2), 86% (CI 72.7 to 94.8) and 69% (CI 53.8 to 81.3) respectively vs S-ELISA/hybrid DABA. Sensitivity for sera from matched clinical samples performe

Journal article

Iqbal FM, Lam K, Sounderajah V, Elkin S, Ashrafian H, Darzi Aet al., 2021, Understanding the survivorship burden of long COVID, ECLINICALMEDICINE, Vol: 33

Journal article

Danielli S, Patria R, Donnelly P, Ashrafian H, Darzi Aet al., 2021, Economic interventions to ameliorate the impact of COVID-19 on the economy and health: an international comparison, Journal of Public Health, Vol: 43, Pages: 42-46, ISSN: 1741-3842

BackgroundThe COVID-19 pandemic continues to challenge governments and policymakers worldwide. They have rightfully prioritised reducing the spread of the virus through social distancing interventions. However, shuttered business and widespread restrictions on travel and mobility have led to an economic collapse with increasing uncertainty of how quickly recovery will be achieved.MethodsThe authors carried out a review of publicly available information on the economic intervention’s countries have put in place to ameliorate the impact of COVID-19.ResultsThe strategies and scale of economic interventions have been broad, ranging from 2.5% to a reported 50% of Gross Domestic Product.ConclusionsNumerous countries are beginning to ease lockdown restrictions and restart economies in different ways. There is therefore evolving, real-world data that should be used dynamically by governments and policymakers. The strategies on restarting the economy must be balanced against the uncertainty of a possible second wave of COVID-19. A nuanced approach to easing restrictions needs to take into account not only immediate risk to life but longer-term risks of widening inequalities and falling life expectancy.

Journal article

Egan M, Acharya A, Sounderajah V, Xu Y, Mottershaw A, Phillips R, Ashrafian H, Darzi Aet al., 2021, Evaluating the effect of infographics on public recall, sentiment and willingness to use face masks during the COVID-19 pandemic: a randomised internet-based questionnaire study, BMC Public Health, Vol: 21, ISSN: 1471-2458

BackgroundThe use of face masks remains contentious, with international variation in practice. Their prevalence in the UK, is likely to increase due to new legislation. Clear information regarding the appropriate use of masks is needed, to ensure compliance with policies to reduce transmission of COVID-19. We aimed to assess the impact of visual representations of guidance, or infographics, upon the knowledge of appropriate face mask usage in a representative UK cohort.MethodsAdult patients were recruited to this randomised internet-based questionnaire study during the 12–14 May 2020 from across the UK. Respondents viewed one of five public health stimuli regarding the use of face masks, or no stimulus. The groups accessed aids by the European Centre for Disease Control (EUCDC), World Health Organisation (WHO), Singaporean Ministry of Health (SMOH), text from the UK government (UK Gov), or an infographic designed by the Behavioural Insights Team (BIT). The primary outcome was to evaluate the effect of each infographic upon participants’ recall of face mask technique, sentiments and willingness to wear a face covering. Secondary outcomes included the effect of symptomology and socio-demographic factors.Results4099 respondents were randomised (1009 control, 628 EUCDC, 526 WHO, 639 SMOH, 661 UKGOV and 606 BIT). Stimuli from the WHO, SMOH and BIT demonstrated significantly higher average recall scores compared to the controls (7.40 v. 7.38 v. 7.34 v. 6.97, P < 0.001). BIT’s stimulus led to the highest confidence about mask-wearing (87%). Only 48.2% of the cohort felt stimuli reduced anxiety about COVID-19. However, willingness to use a mask was high, (range 84 to 88%).ConclusionsTo ensure the appropriate use of masks, as mandated by UK law, guidance must provide sufficient information, yet remain understandable. Infographics can aid the recall of correct mask techniques by highlighting salient steps and reducing cognitive burden. They have al

Journal article

Danielli S, Coffey T, Ashrafian H, Darzi Aet al., 2021, Systematic review into city interventions to address obesity, EClinicalMedicine, Vol: 32, ISSN: 2589-5370

BackgroundObesity threatens to undo the improvements that have been made in life expectancy over the last two centuries. It disproportionately affects lower socioeconomic and ethnic minority groups and has become one of the most important global health challenges of the 21stcentury. Whilst obesity is not confined to city populations, cities are home to more than half of the world's population with concentrated groups at high risk of obesity. Cities have also long been the forefront of social and technological change that has led to our current obesogenic environment. The aim of this study was to systematically identify city-wide interventions to address obesity, from which recommendations for policy makers, health system leaders and political leaders in cities could be made.MethodsSystematic review, conducted according to PRISMA guidelines, examining Embase, Ovid Medline, Central, Scopus, Campbell Library, CINALH, Health Business Elite; Health Management Information Consortium (HMIC), PyschINFO and Prospero. No restrictions on article type, date range or geographic location were applied. Along with classic academic sources, books and policy white papers were sought and reviewed. Studies that described a city-wide intervention to reduce obesity were included, irrespective of study design or perceived methodological quality. Only studies in English language were included. The primary outcome indicators that were sought and extracted were: reduction in obesity, reduction in weight and/or reduction in BMI. Where a primary outcome indicator was not stated, any other secondary impact measure was identified and recorded. This manuscript represents thematic analysis of a sub-set of data from the Prospero study, registration number: CRD42020166210FindingsOur search yielded 42,137 original citations of which 1614 met the inclusion criteria and 96 were coded as relating to obesity. The 96 citations, ranging in year of publication 1997 to 2019, were conducted in 36 cities, with

Journal article

This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.

Request URL: http://wlsprd.imperial.ac.uk:80/respub/WEB-INF/jsp/search-html.jsp Request URI: /respub/WEB-INF/jsp/search-html.jsp Query String: respub-action=search.html&id=00531308&limit=30&person=true