Imperial College London

Professor the Lord Darzi of Denham PC KBE FRS FMedSci HonFREng

Faculty of MedicineDepartment of Surgery & Cancer

Co-Director of the IGHI, Professor of Surgery
 
 
 
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Contact

 

+44 (0)20 3312 1310a.darzi

 
 
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Location

 

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

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Summary

 

Publications

Publication Type
Year
to

2129 results found

Chadeau-Hyam M, Tang D, Eales O, Bodinier B, Wang H, Jonnerby J, Whitaker M, Elliott J, Haw D, Walters CE, Atchison C, Diggle PJ, Page AJ, Ashby D, Barclay W, Taylor G, Cooke G, Ward H, Darzi A, Donnelly CA, Elliott Pet al., 2022, Omicron SARS-CoV-2 epidemic in England during February 2022: A series of cross-sectional community surveys, LANCET REGIONAL HEALTH-EUROPE, Vol: 21, ISSN: 2666-7762

Journal article

Nazarian S, Gkouzionis I, Kawka M, Jamroziak M, Lloyd J, Darzi A, Patel N, Elson DS, Peters CJet al., 2022, Real-time tracking and classification of tumour and non-tumour tissue in upper gastrointestinal cancers using diffuse reflectance spectroscopy for resection margin assessment, JAMA Surgery, ISSN: 2168-6254

Importance:Cancers of the upper gastrointestinal tract remain a major contributor to the global cancer burden. The accurate mapping of tumour margins is of particular importance for curative cancer resection and improvement in overall survival. Current mapping techniques preclude a full resection margin assessment in real-time.Objective:We aimed to use diffuse reflectance spectroscopy on gastric and oesophageal cancer specimens to differentiate tissue types and provide real-time feedback to the operator.Design:This was a prospective ex vivo validation study. Patients undergoing oesophageal or gastric cancer resection were prospectively recruited into the study between July 2020 and July 2021 at Hammersmith Hospital in London, United Kingdom.Setting:This was a single-centre study based at a tertiary hospital.Participants:Tissue specimens were included for patients undergoing elective surgery for either oesophageal carcinoma (adenocarcinoma or squamous cell carcinoma) or gastric adenocarcinoma.Exposure:A hand-held diffuse reflectance spectroscopy probe and tracking system was used on freshly resected ex vivo tissue to obtain spectral data. Binary classification, following histopathological validation, was performed using four supervised machine learning classifiers. Main Outcomes and Measures:Data were divided into training and testing sets using a stratified 5-fold cross-validation method. Machine learning classifiers were evaluated in terms of sensitivity, specificity, overall accuracy, and the area under the curve.Results:A total of 14,097 mean spectra for normal and cancerous tissue were collected from 37 patients. The machine learning classifier achieved an overall normal versus cancer diagnostic accuracy of 93.86±0.66 for stomach tissue and 96.22±0.50 for oesophageal tissue, and sensitivity and specificity of 91.31% and 95.13% for stomach and 94.60% and 97.28% for oesophagus, respectively. Real-time tissue tracking and classification was achieved a

Journal article

Eales O, Ainslie KEC, Walters CE, Wang H, Atchison C, Ashby D, Donnelly CA, Cooke G, Barclay W, Ward H, Darzi A, Elliott P, Riley Set al., 2022, Appropriately smoothing prevalence data to inform estimates of growth rate and reproduction number, Epidemics: the journal of infectious disease dynamics, Vol: 40, ISSN: 1755-4365

The time-varying reproduction number () can change rapidly over the course of a pandemic due to changing restrictions, behaviours, and levels of population immunity. Many methods exist that allow the estimation of from case data. However, these are not easily adapted to point prevalence data nor can they infer across periods of missing data. We developed a Bayesian P-spline model suitable for fitting to a wide range of epidemic time-series, including point-prevalence data. We demonstrate the utility of the model by fitting to periodic daily SARS-CoV-2 swab-positivity data in England from the first 7 rounds (May 2020–December 2020) of the REal-time Assessment of Community Transmission-1 (REACT-1) study. Estimates of over the period of two subsequent rounds (6–8 weeks) and single rounds (2–3 weeks) inferred using the Bayesian P-spline model were broadly consistent with estimates from a simple exponential model, with overlapping credible intervals. However, there were sometimes substantial differences in point estimates. The Bayesian P-spline model was further able to infer changes in over shorter periods tracking a temporary increase above one during late-May 2020, a gradual increase in over the summer of 2020 as restrictions were eased, and a reduction in during England’s second national lockdown followed by an increase as the Alpha variant surged. The model is robust against both under-fitting and over-fitting and is able to interpolate between periods of available data; it is a particularly versatile model when growth rate can change over small timescales, as in the current SARS-CoV-2 pandemic. This work highlights the importance of pairing robust methods with representative samples to track pandemics.

Journal article

Wallace W, Chan C, Chidambaram S, Hanna L, Iqbal FM, Acharya A, Normahani P, Ashrafian H, Markar SR, Sounderajah V, Darzi Aet al., 2022, The diagnostic and triage accuracy of digital and online symptom checker tools: a systematic review, npj Digital Medicine, Vol: 5, ISSN: 2398-6352

Digital and online symptom checkers are an increasingly adopted class of health technologies that enable patients to input their symptoms and biodata to produce a set of likely diagnoses and associated triage advice. However, concerns regarding the accuracy and safety of these symptom checkers have been raised. This systematic review evaluates the accuracy of symptom checkers in providing diagnoses and appropriate triage advice. MEDLINE and Web of Science were searched for studies that used either real or simulated patients to evaluate online or digital symptom checkers. The primary outcomes were the diagnostic and triage accuracy of the symptom checkers. The QUADAS-2 tool was used to assess study quality. Of the 177 studies retrieved, 10 studies met the inclusion criteria. Researchers evaluated the accuracy of symptom checkers using a variety of medical conditions, including ophthalmological conditions, inflammatory arthritides and HIV. 50% of the studies recruited real patients, while the remainder used simulated cases. The diagnostic accuracy of the primary diagnosis was low across included studies (range: 19% to 37.9%) and varied between individual symptom checkers, despite consistent symptom data input. Triage accuracy (range: 48.8% to 90.1%) was typically higher than diagnostic accuracy. Overall, the diagnostic and triage accuracy of symptom checkers are variable and of low accuracy. Given the increasing push towards adopting this class of technologies across numerous health systems, this study demonstrates that reliance upon symptom checkers could pose significant patient safety hazards. Large scale primary studies, based upon real world data, are warranted to demonstrate adequate performance of these technologies in a manner that is and non-inferior to current best practice. Moreover, an urgent assessment of how these systems are regulated and implemented is required.

Journal article

Elliott P, Eales O, Bodinier B, Tang D, Wang H, Jonnerby LJA, Haw D, Elliott J, Whitaker M, Walters C, Atchison C, Diggle P, Page A, Trotter A, Ashby D, Barclay W, Taylor G, Ward H, Darzi A, Cooke G, Chadeau M, Donnelly Cet al., 2022, Dynamics of a national Omicron SARS-CoV-2 epidemic during January 2022 in England, Nature Communications, Vol: 13, ISSN: 2041-1723

Rapid transmission of the SARS-CoV-2 Omicron variant has led to record-breaking case incidence rates around the world. Since May 2020, the REal-time Assessment of Community Transmission-1 (REACT-1) study tracked the spread of SARS-CoV-2 infection in England through RT-PCR of self-administered throat and nose swabs from randomly-selected participants aged 5 years and over. In January 2022, we found an overall weighted prevalence of 4.41% (n=102,174), three-fold higher than in November to December 2021; we sequenced 2,374 (99.2%) Omicron infections (19 BA.2), and only 19 (0.79%) Delta, with a growth rate advantage for BA.2 compared to BA.1 or BA.1.1. Prevalence was decreasing overall (reproduction number R=0.95, 95% credible interval [CrI], 0.93, 0.97), but increasing in children aged 5 to 17 years (R=1.13, 95% CrI, 1.09, 1.18). In England during January 2022, we observed unprecedented levels of SARS-CoV-2 infection, especially among children, driven by almost complete replacement of Delta by Omicron.

Journal article

Omar I, Miller K, Madhok B, Amr B, Singhal R, Graham Y, Pouwels S, Abu Hilal M, Aggarwal S, Ahmed I, Aminian A, Ammori BJ, Arulampalam T, Awan A, Balibrea JM, Bhangu A, Brady RR, Brown W, Chand M, Darzi A, Gill TS, Goel R, Gopinath BR, Henegouwen MVB, Himpens JM, Kerrigan DD, Luyer M, Macutkiewicz C, Mayol J, Purkayastha S, Rosenthal RJ, Shikora SA, Small PK, Smart NJ, Taylor MA, Udwadia TE, Underwood T, Viswanath YKS, Welch NT, Wexner SD, Wilson MSJ, Winter DC, Mahawar KKet al., 2022, The first international Delphi consensus statement on Laparoscopic Gastrointestinal surgery, INTERNATIONAL JOURNAL OF SURGERY, Vol: 104, ISSN: 1743-9191

Journal article

Eales O, Martins LDO, Page AJ, Wang H, Bodinier B, Tang D, Haw D, Jonnerby J, Atchison C, Ashby D, Barclay W, Taylor G, Cooke G, Ward H, Darzi A, Riley S, Elliott P, Donnelly CA, Chadeau-Hyam Met al., 2022, Dynamics of competing SARS-CoV-2 variants during the Omicron epidemic in England, Nature Communications, Vol: 13, ISSN: 2041-1723

The SARS-CoV-2 pandemic has been characterised by the regular emergence of genomic variants. With natural and vaccine-induced population immunity at high levels, evolutionary pressure favours variants better able to evade SARS-CoV-2 neutralising antibodies. The Omicron variant (first detected in November 2021) exhibited a high degree of immune evasion, leading to increased infection rates worldwide. However, estimates of the magnitude of this Omicron wave have often relied on routine testing data, which are prone to several biases. Using data from the REal-time Assessment of Community Transmission-1 (REACT-1) study, a series of cross-sectional surveys assessing prevalence of SARS-CoV-2 infection in England, we estimated the dynamics of England’s Omicron wave (from 9 September 2021 to 1 March 2022). We estimate an initial peak in national Omicron prevalence of 6.89% (5.34%, 10.61%) during January 2022, followed by a resurgence in SARS-CoV-2 infections as the more transmissible Omicron sub-lineage, BA.2 replaced BA.1 and BA.1.1. Assuming the emergence of further distinct variants, intermittent epidemics of similar magnitudes may become the ‘new normal’.

Journal article

Eales O, Wang H, Bodinier B, Haw D, Jonnerby J, Atchison C, Ashby D, Barclay W, Taylor G, Cooke G, Ward H, Darzi A, Riley S, Chadeau M, Donnelly C, Elliott Pet al., 2022, SARS-CoV-2 lineage dynamics in England from September to November 2021: high diversity of Delta sub-lineages and increased transmissibility of AY.4.2, BMC Infectious Diseases, Vol: 22, ISSN: 1471-2334

Background: Since the emergence of SARS-CoV-2, evolutionary pressure has driven large increases in the transmissibility of the virus. However, with increasing levels of immunity through vaccination and natural infection the evolutionary pressure will switch towards immune escape. Genomic surveillance in regions of high immunity is crucial in detecting emerging variants that can more successfully navigate the immune landscape. Methods: We present phylogenetic relationships and lineage dynamics within England (a country with high levels of immunity), as inferred from a random community sample of individuals who provided a self-administered throat and nose swab for rt-PCR testing as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. During round 14 (9 September - 27 September 2021) and 15 (19 October - 5 November 2021) lineages were determined for 1322 positive individuals, with 27.1% of those which reported their symptom status reporting no symptoms in the previous month.Results: We identified 44 unique lineages, all of which were Delta or Delta sub-lineages, and found a reduction in their mutation rate over the study period. The proportion of the Delta sub-lineage AY.4.2 was increasing, with a reproduction number 15% (95% CI, 8%-23%) greater than the most prevalent lineage, AY.4. Further, AY.4.2 was less associated with the most predictive COVID-19 symptoms (p = 0.029) and had a reduced mutation rate (p = 0.050). Both AY.4.2 and AY.4 were found to be geographically clustered in September but this was no longer the case by late October/early November, with only the lineage AY.6 exhibiting clustering towards the South of England.Conclusions: As SARS-CoV-2 moves towards endemicity and new variants emerge, genomic data obtained from random community samples can augment routine surveillance data without the potential biases introduced due to higher sampling rates of symptomatic individuals.

Journal article

Acharya A, Ashrafian H, Cunnignham D, Ruwende J, Darzi A, Judah Get al., 2022, Evaluating the impact of a novel behavioural science informed animation upon breast cancer screening uptake: protocol for a randomised controlled trial, BMC Public Health, Vol: 22, ISSN: 1471-2458

BackgroundBreast cancer screening is estimated to save 1300 lives annually in the United Kingdom. Despite this, uptake of invitations has fallen over the past decade. Behavioural science-informed interventions addressing the determinants of attendance behaviour have shown variable effectiveness. This may be due to the narrow repertoire of techniques trialled, and the difficulties of implementation at a population-scale. The aim of this study is to evaluate the impact on breast screening uptake of a novel behavioural video intervention which can contain more complex combinations of behavioural change techniques. MethodsA 3-armed randomised controlled trial will be undertaken in London comparing the impact of (1) the usual care SMS reminder, to (2) a behavioural plain text SMS reminder and (3) a novel video sent as a link within the behavioural plain text SMS reminder. A total of 8391 participants (2797 per group) will be allocated to one of the three trial arms using a computer randomisation process, based upon individuals’ healthcare identification numbers. The novel video has been co-designed with a diverse range of women to overcome the barriers faced by underserved communities and the wider population. The behavioural SMS content has also been co-designed through the same process as the video. Messages will be sent through the current reminder system used by the London screening programmes, with reminders 7 days and 2 days prior to a timed appointment. The primary outcome is attendance at breast cancer screening within 3 months of the initial invitation. Secondary outcomes will include evaluating the impact of each message amongst socio-demographic groups and according to the appointment type e.g. first invitation or recall. DiscussionIn addition to general declining trends in attendance, there is also concern of increasing healthcare inequalities with breast cancer screening in London. The current novel intervention, designed with underserved groups and t

Journal article

Lam K, Abramoff M, Balibrea J, Bishop S, Brady R, Callcut R, Chand M, Collins J, Diener M, Eisenmann M, Fermont K, Galvao Neto M, Hager G, Hinchliffe R, Horgan A, Jannin P, Langerman A, Logishetty K, Mahadik A, Maier-Hein L, Martin Antona E, Mascagni P, Mathew R, Mueller-Stich B, Neumuth T, Nickel F, Park A, Pellino G, Rudzicz F, Shah S, Slack M, Smith M, Soomro N, Speidel S, Stoyanov D, Tilney H, Wagner M, Darzi A, Kinross J, Purkayastha Set al., 2022, A Delphi consensus statement for digital surgery, npj Digital Medicine, Vol: 5, Pages: 1-9, ISSN: 2398-6352

The use of digital technology is increasing rapidly across surgical specialities, yet there is noconsensus for the term ‘digital surgery’. This is critical as digital health technologies present technical, governance, and legal challenges which are unique to the surgeon and surgical patient. We aim to define the term digital surgery and the ethical issues surrounding its clinical application, and to identify barriers and research goals for future practice. 38 international experts, across the fields of surgery, AI, industry, law, ethics and policy, participated in a four-round Delphi exercise. Issues were generated by an expert panel and public panel through a scoping questionnaire around key themes identified from the literature and voted upon in two subsequent questionnaire rounds. Consensus was defined if >70% of the panel deemed the statement important and <30% unimportant. A final online meeting was held to discuss consensus statements. The definition of digital surgery as the use of technology for the enhancement of preoperative planning, surgical performance, therapeutic support, or training, to improve outcomes and reduce harm achieved 100% consensus agreement. We highlight key ethical issues concerning data, privacy, confidentiality and public trust, consent, law; litigation and liability, and commercial partnerships within digital surgery and identify barriers and research goals for future practice. Developers and users of digital surgery must not only have an awareness of the ethical issues surrounding digital applications in healthcare, but also the ethical considerations unique to digital surgery. Future research into these issues must involve all digital surgery stakeholders including patients.

Journal article

Eales O, de Oliveira Martins L, Page A, Wang H, Bodinier B, Tang D, Haw D, Jonnerby LJA, Atchison C, Ashby D, Barclay W, Taylor G, Cooke G, Ward H, Darzi A, Riley S, Elliott P, Donnelly C, Chadeau Met al., 2022, Dynamics and scale of the SARS-CoV-2 variant Omicron epidemic in England, Nature Communications, ISSN: 2041-1723

Journal article

Che Bakri NA, Kwasnicki R, Khan N, Ghandour O, Lee A, Grant Y, Dawidziuk A, Darzi A, Ashrafian H, Leff Det al., 2022, Impact of axillary lymph node dissection and sentinel lymph node biopsy on upper limb morbidity in breast cancer patients: a systematic review and meta-analysis, Annals of Surgery, ISSN: 0003-4932

Objective: To evaluate the impact of ALND and SLNB on upper limb (UL) morbidity in breastcancer patients.Summary Background: Axillary de-escalation is motivated by a desire to reduce harm ofALND. Understanding the impact of axillary surgery and disparities in operative procedureson post-operative arm morbidity would better direct resources to the point of need and cementthe need for de-escalation strategies.Methods: Embase, Medline, CINAHL and PsychINFO were searched from 1990 until March2020. Included studies were randomized-controlled and observational studies focusing on ULmorbidities, in breast surgery patients. The study followed the Preferred Reporting Items forSystematic Reviews and Meta-Analyses (PRISMA) guidelines. The prevalence of upper limbmorbidity comparing SLNB and ALND at less than 12 months, 12-24 months and beyond 24months were analyzed.Results: Sixty-seven studies were included. All studies reported a higher rate of lymphedemaand pain after ALND compared to SLNB. The difference in lymphedema and pain prevalencebetween SLNB and ALND was 13.7% (95% CI 10.5-16.8, p<0.005) and 24.2% (95% CI 12.1-36.3, p<0.005) respectively. Pooled estimates for prevalence of reduced strength and rangeof motion after SLNB and ALND were 15.2% vs 30.9% and 17.1% vs 29.8% respectively.Type of axillary surgery, greater BMI, and radiotherapy were some of the predictors for ULmorbidities.Conclusions: Prevalence of lymphedema after ALND was higher than previously estimated.ALND patients experienced greater rates of lymphedema, pain, reduced strength, and ROMcompared to SLNB. The findings support the continued drive to de-escalate axillary surgery.

Journal article

Fernandez Crespo R, Leis M, Alford J, Patel M, Jones S, Fontana G, Howitt P, Darzi A, Nabarro Det al., 2022, COVID-19 Global Behaviours and Attitudes: A review of the survey results of over 450,000 people in 9 countries

Report

Lear R, Freise L, Kybert M, Darzi A, Neves AL, Mayer Eet al., 2022, Patients’ willingness and ability to identify and respond to errors in their personal health records: a mixed methods analysis of cross-sectional survey data, Journal of Medical Internet Research, Vol: 24, ISSN: 1438-8871

Background:Errors in electronic health records are known to contribute to patient safety incidents, yet systems for checking the accuracy of patient records are almost non-existent. Personal health records, enabling patient access to, and interaction, with the clinical record, offer a valuable opportunity for patients to actively participate in error surveillance.Objective:The aim of this study was to evaluate patients’ willingness and ability to identify and respond to errors in their personal health records.Methods:A cross-sectional survey study was conducted using an online questionnaire. Patient sociodemographic data were collected, including age, gender, ethnicity, educational level, health status, geographical location, motivation to self-manage, and digital health literacy (measured by the eHEALS tool). Patients with experience of using the Care Information Exchange (CIE) portal, who specified both age and gender, were included in these analyses. Patients’ responses to four relevant survey items (closed-ended questions, some with space for free-text comments) were examined to understand their willingness and ability to identify and respond to errors in their personal health records. Multinomial logistic regression was used to identify patient characteristics that predict i) ability to understand information in CIE, and ii) willingness to respond to errors in their records. The Framework Method was used to derive themes from patients’ free-text responses.Results:Of 445 patients, 40.7% (n=181) “definitely” understood CIE information and around half (49.4%, n=220) understood CIE information “to some extent”. Patients with high digital health literacy (eHEALS score ≥30) were more confident in their ability to understand their records compared to patients with low digital health literacy (odds ratio (OR) 7.85, 95% confidence interval (CI) 3.04-20.29, P<.001). Information-related barriers (medical terminology; lack of

Journal article

Wong N, Meshkinfamfard S, Turbé V, Whitaker M, Moshe M, Bardanzellu A, Dai T, Pignatelli E, Barclay W, Darzi A, Elliott P, Ward H, Tanaka R, Cooke G, McKendry R, Atchison C, Bharath Aet al., 2022, Machine learning to support visual auditing of home-based lateral flow immunoassay self-test results for SARS-CoV-2 antibodies, Communications Medicine, Vol: 2, ISSN: 2730-664X

Lateral flow immunoassays (LFIAs) are being used worldwide for COVID-19 mass testing and antibody prevalence studies. Relatively simple to use and low cost, these tests can be self-administered at home but rely on subjective interpretation of a test line by eye, risking false positives and negatives. Here we report the development of ALFA (Automated Lateral Flow Analysis) to improve reported sensitivity and specificity. Our computational pipeline uses machine learning, computer vision techniques and signal processing algorithms to analyse images of the Fortress LFIA SARS-CoV-2 antibody self-test, and subsequently classify results as invalid, IgG negative and IgG positive. A large image library of 595,339 participant-submitted test photographs was created as part of the REACT-2 community SARS-CoV-2 antibody prevalence study in England, UK. Automated analysis showed substantial agreement with human experts (Kappa 0.90-0.97) and performed consistently better than study participants, particularly for weak positive IgG results. Specificity (98.7-99.4%) and sensitivity (90.1-97.1%) were high compared with visual interpretation by human experts (ranges due to the varying prevalence of weak positive IgG tests in datasets). Alongside ALFA, we developed an analysis toolkit which could also detect device blood leakage issues. Given the potential for LFIAs to be used at scale in the COVID-19 response (for both antibody and antigen testing), even a small improvement in the accuracy of the algorithms could impact the lives of millions of people by reducing the risk of false positive and false negative result read-outs by members of the public. Our findings support the use of machine learning-enabled automated reading of at-home antibody lateral flow tests, to be a tool for improved accuracy for population-level community surveillance.

Journal article

Joshi M, Ashrafian H, Arora S, Sharabiani M, Kenny M, Sadia K, Cooke G, Ara Det al., 2022, A pilot study to investigate real time digital alerting from wearable sensors in surgical patients, Pilot and Feasibility Studies, Vol: 8, ISSN: 2055-5784

Background Continuous vital sign monitoring may identify changes sooner than current standard monitoring. Objective To investigate if the use of real time digital alerts sent to healthcare staff can improve the time taken to identify unwell patients and those with sepsis. DesignA prospective cohort study design. Setting West Middlesex University Hospital, UK. Participants 50 acutely unwell surgical patients admitted to hospital. Intervention Patients wore a lightweight wearable sensor measuring heart rate (HR), respiratory rate (RR) and temperature every 2 minutes whilst standard intermittent ward monitoring of vital signs was performed by nurses. Digital alerts were sent to healthcare staff from the sensor to a smartphone device. All alerts were reviewed for recruited patients to identify the exact time on the sensor in which deterioration occurred. The time to acknowledgement was then reviewed for each action and an average time to acknowledgement calculated.Results There were 50 patients recruited in the pilot study, of which there were vital sign alerts in 18 patients (36%). The total number of vital sign alerts generated in these 18 patients was 51. Of these 51 alerts there 7 alerts for high HR (13.7%), 33 for RR (64.7%) and 11 for temperature (21.6%). Out of the 27 acknowledged alerts there were 2 alerts for HR, 17 for RR and 8 for temperature. The average time to staff acknowledgement of the notification for all alerts was 154 minutes (2.6 hours). There were some patients which had shown signs of deterioration in the cohort. The frequency of routine observation monitoring was increased in 2 cases, 3 patients were referred to a senior clinician and 2 patients were initiated on the sepsis pathway. Conclusion This study demonstrates the evaluation of digital alerts to nurses in real-time. Although not all alerts were acknowledged, deterioration on the ward observations was detected and actions were taken accordingly. Patients were started on the sepsis pathw

Journal article

Patel R, Suwa Y, Kinross J, von Roon A, Woods AJ, Darzi A, Singh H, Leff DRet al., 2022, Neuroenhancement of surgeons during robotic suturing, Surgical Endoscopy: surgical and interventional techniques, Vol: 36, Pages: 4803-4814, ISSN: 0930-2794

BackgroundThe initial phases of robotic surgical skills acquisition are associated with poor technical performance, such as low knot-tensile strength (KTS). Transcranial direct-current stimulation (tDCS) can improve force and accuracy in motor tasks but research in surgery is limited to open and laparoscopic tasks in students. More recently, robotic surgery has gained traction and is now the most common approach for certain procedures (e.g. prostatectomy). Early-phase robotic suturing performance is dependent on prefrontal cortex (PFC) activation, and this study aimed to determine whether performance can be improved with prefrontal tDCS.MethodsFifteen surgical residents were randomized to either active then sham tDCS or sham then active tDCS, in two counterbalanced sessions in a double-blind crossover study. Within each session, participants performed a robotic suturing task repeated in three blocks: pre-, intra- and post-tDCS. During the intra-tDCS block, participants were randomized to either active tDCS (2 mA for 15 min) to the PFC or sham tDCS. Primary outcome measures of technical quality included KTS and error scores.ResultsSignificantly faster completion times were observed longitudinally, regardless of active (p < 0.001) or sham stimulation (p < 0.001). KTS was greater following active compared to sham stimulation (median: active = 44.35 N vs. sham = 27.12 N, p < 0.001). A significant reduction in error scores from “pre-” to “post-” (p = 0.029) were only observed in the active group.ConclusiontDCS could reduce error and enhance KTS during robotic suturing and warrants further exploration as an adjunct to robotic surgical training.

Journal article

Iqbal FM, Joshi M, Khan S, Wright M, Ashrafian H, Darzi Aet al., 2022, Key Stakeholder Barriers and Facilitators to Implementing Remote Monitoring Technologies: Protocol for a Mixed Methods Analysis, JMIR RESEARCH PROTOCOLS, Vol: 11, ISSN: 1929-0748

Journal article

Iqbal F, Joshi M, Fox R, Tonia K, Sharma A, Wright M, Khan S, Ashrafian H, Darzi Aet al., 2022, Outcomes of vital sign monitoring of an acute surgical cohort with wearable sensors and digital alerting systems: a pragmatically designed cohort study and propensity-matched analysis, Frontiers in Bioengineering and Biotechnology, Vol: 10, ISSN: 2296-4185

Background: The implementation and efficacy of wearable sensors and alerting systems in acute secondary care have been poorly described. Objectives: to pragmatically test one such system and its influence on clinical outcomes in an acute surgical cohort.Methods: In this pragmatically designed, pre-post implementation trial, participants admitted to the acute surgical unit at our institution were recruited. In the pre-implementation phase (September 2017 to May 2019), the SensiumVitals™ monitoring system, which continuously measures temperature, heart, and respiratory rates, was used for monitoring alongside usual care (intermittent monitoring in accordance with the National Early Warning Score 2 [NEWS 2] protocol) without alerts being generated. In the post-implementation phase (May 2019 to March 2020), alerts were generated when pre-established thresholds for vital parameters were breached, requiring acknowledgement from healthcare staff on provided mobile devices. Hospital length of stay, intensive care use, and 28-day mortality were measured. Balanced cohorts were created with 1:1 ‘optimal’ propensity score logistic regression models.Results: The 1:1 matching method matched the post-implementation group (n = 141) with the same number of subjects from the pre-implementation group (n = 141). The median age of the entire cohort was 52 (range: 18-95) years and the median duration of wearing the sensor was 1.3 (interquartile range: 0.7-2.0) days. The median alert acknowledgement time was 111 (range: 1-2146) minutes. There were no significant differences in critical care admission (planned or unplanned), hospital length of stay, or mortality.Conclusion: This study offered insight into the implementation of digital health technologies within our institution. Further work is required for optimisation of digital workflows, particularly given their more favourable acceptability in the post pandemic era.Clinical trials registration information: Cli

Journal article

Iqbal F, Joshi M, Khan S, Wright M, Ashrafian H, Darzi Aet al., 2022, Barriers and facilitators of key stakeholders to implement remote monitoring technologies: a protocol for a mixed-methods analysis, JMIR Research Protocols, ISSN: 1929-0748

Background: Implementation of novel digital solutions within the National Health Service (NHS) has historically been challenging. Since the COVID-19 pandemic, there has been a greater push for digitisation and for operating remote monitoring solutions. However, the implementation and widespread adoption of this type of innovation has been poorly studied.Objective: to investigate key stakeholder barriers and facilitators of implementing remote monitoring solutions, identifying factors that could affect successful adoption.Methods: A mixed methods approach will be implemented: semi-structured interviews will be conducted with high level stakeholders from industry, academia, and healthcare providers who have played an instrumental role with prior experience of implementing digital solutions alongside the use of an adapted version of the Technology Acceptance Model (TAM) questionnaire.Results: Enrolment is currently underway, having started in February 2022; it is anticipated to end in July 2022 with data analysis to commence in August 2022.Conclusions: the results of this study may highlight key barriers and facilitators in implementing digital remote monitoring solutions, allowing for improved future widespread adoption with the NHS.Clinical trials registration information: ClinicalTrials.gov Identifier: NCT05321004

Journal article

Chadeau M, Tang D, Eales O, Bodinier B, Wang H, Jonnerby LJA, Whitaker M, Elliott J, Haw D, Walters C, Atchison C, Diggle P, Page A, Ashby D, Barclay W, Taylor G, Cooke G, Ward H, Darzi A, Donnelly C, Elliott Pet al., 2022, Cross-sectional community surveys to monitor the Omicron SARS-CoV-2 epidemic in England during February 2022, The Lancet Regional Health Europe, ISSN: 2666-7762

Background: The Omicron wave of COVID-19 in England peaked in January 2022 resulting from the rapid transmission of the Omicron BA.1 variant. We investigate the spread and dynamics of the SARS-CoV-2 epidemic in the population of England during February 2022, by region, age and main SARS-CoV-2 sub-lineage.Methods: In the REal-time Assessment of Community Transmission-1 (REACT-1) study we obtained data from a random sample of 94,950 participants with valid throat and nose swab results by RT-PCR during round 18 (8 February to 1 March 2022).Findings: We estimated a weighted mean SARS-CoV-2 prevalence of 2.88% (95% credible interval [CrI] 2.76–3.00), with a within-round effective reproduction number (R) overall of 0.94 (0·91–0.96). While within-round weighted prevalence fell among children (aged 5 to 17 years) and adults aged 18 to 54 years, we observed a level or increasing weighted prevalence among those aged 55 years and older with an R of 1.04 (1.00–1.09). Among 1,616 positive samples with sublineages determined, one (0.1% [0.0–0.3]) corresponded to XE BA.1/BA.2 recombinant and the remainder were Omicron: N=1,047, 64.8% (62.4–67.2) were BA.1; N=568, 35.2% (32.8–37.6) were BA.2. We estimated an R additive advantage for BA.2 (vs BA.1) of 0.38 (0.34–0.41). The highest proportion of BA.2 among positives was found in London. Interpretation: In February 2022, infection prevalence in England remained high with level or increasing rates of infection in older people and an uptick in hospitalisations. Ongoing surveillance of both survey and hospitalisations data is required.Funding Department of Health and Social Care, England.

Journal article

Lounsbury O, Roberts L, Kurek N, Shaw A, Flott K, Ghafur S, Labrique A, Leatherman S, Darzi A, Neves ALet al., 2022, The role of digital innovation in improving healthcare quality in extreme adversity: an interpretative phenomenological analysis study, Journal of Global Health Reports, ISSN: 2399-1623

Background: High quality is a necessary feature of healthcare delivery. These healthcare quality challenges are particularly present in areas of extreme adversity, such as in conflict settings or sustained humanitarian crises. Digital health technologies have recently emerged as an innovation to deliver care around the world in a variety of settings. However, there is little insight into how digital health technologies can be used to improve the quality of care where extreme adversity introduces unique challenges. Objective: This study aimed to identify where digital health technologies may be most impactful in improving the quality of care and evaluate opportunities for accelerated and meaningful digital innovation in adverse settings. Methods: A phenomenological approach (Interpretative Phenomenological Approach [IPA]), using semi-structured interviews, was adopted. Six individuals were interviewed in-person based on their expertise in global health, international care delivery, and application of digital health technologies to improve the quality of care in extreme adversity settings. The interviews were informed by a semi-structured topic guide with open-ended questions. The transcripts were compiled verbatim and were systematically examined by 2 reviewers, using the framework analysis method to extract themes and subthemes. Results: The participants identified several areas in which digital health technologies could be most impactful, which include engagement in care, continuity of care, workforce operations, and data collection. Opportunities for accelerated digital innovation include improving terminology, identity, ownership, and interoperability, identifying priority areas for digital innovation, developing tailored solutions, co-ordination and standardisation, and sustainability and resilience.Conclusions: These results suggest that there are conditions that favour or challenge the application of digital health technologies, even in specific areas in which

Journal article

Eales O, Wang H, Haw D, Ainslie KEC, Walters CE, Atchison C, Cooke G, Barclay W, Ward H, Darzi A, Ashby D, Donnelly CA, Elliott P, Riley Set al., 2022, Trends in SARS-CoV-2 infection prevalence during England’s roadmap out of lockdown, January to July 2021

<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Following rapidly rising COVID-19 case numbers, England entered a national lockdown on 6 January 2021, with staged relaxations of restrictions from 8 March 2021 onwards.</jats:p></jats:sec><jats:sec><jats:title>Aim</jats:title><jats:p>We characterise how the lockdown and subsequent easing of restrictions affected trends in SARS-CoV-2 infection prevalence.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>On average, risk of infection is proportional to infection prevalence. The REal-time Assessment of Community Transmission-1 (REACT-1) study is a repeat cross-sectional study of over 98,000 people every round (rounds approximately monthly) that estimates infection prevalence in England. We used Bayesian P-splines to estimate prevalence and the time-varying reproduction number (<jats:italic>R</jats:italic><jats:sub><jats:italic>t</jats:italic></jats:sub>) nationally, regionally and by age group from round 8 (beginning 6 January 2021) to round 13 (ending 12 July 2021) of REACT-1. As a comparator, a separate segmented-exponential model was used to quantify the impact on <jats:italic>R</jats:italic><jats:sub><jats:italic>t</jats:italic></jats:sub> of each relaxation of restrictions.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Following an initial plateau of 1.54% until mid-January, infection prevalence decreased until 13 May when it reached a minimum of 0.09%, before increasing until the end of the study to 0.76%. Following the first easing of restrictions, which included schools reopening, the reproduction number <jats:italic>R</jats:italic><jats:sub><jats:italic>t</jats:italic></jats:sub> incre

Journal article

Chadeau M, Eales O, Bodinier B, Wang H, Haw D, Whitaker M, Elliott J, Walters C, Jonnerby LJA, Atchison C, Diggle P, Page A, Ashby D, Barclay W, Taylor G, Cooke G, Ward H, Darzi A, Donnelly C, Elliott Pet al., 2022, Breakthrough SARS-CoV-2 infections in double and triple vaccinated adults and single dose vaccine effectiveness among children in Autumn 2021 in England: REACT-1 study, EClinicalMedicine, Vol: 48, Pages: 1-14, ISSN: 2589-5370

Background: Prevalence of SARS-CoV-2 infection with Delta variant was increasing in England in late summer 2021 among children aged 5 to 17 years, and adults who had received two vaccine doses. In September 2021, a third (booster) dose was offered to vaccinated adults aged 50 years and over, vulnerable adults and healthcare/care-home workers, and a single vaccine dose already offered to 16 and 17 year-olds was extended to children aged 12 to 15 years. Methods: SARS-CoV-2 community prevalence in England was available from self-administered throat and nose swabs using reverse transcriptase polymerase chain reaction (RT-PCR) in round 13 (24 June to 12 July 2021, N= 98,233), round 14 (9 to 27 September 2021, N = 100,527) and round 15 (19 October to 5 November 2021, N = 100,112) from the REACT-1 study randomised community surveys. Linking to National Health Service (NHS) vaccination data for consenting participants, we estimated vaccine effectiveness in children aged 12 to 17 years and compared swab-positivity rates in adults who received a third dose with those who received two doses. Findings: Weighted SARS-CoV-2 prevalence was 1.57% (1.48%, 1.66%) in round 15 compared with 0.83% (0.76%, 0.89%) in round 14, and the previously observed link between infections and hospitalisations and deaths had weakened. Vaccine effectiveness against infection in children aged 12 to 17 years was estimated (round 15) at 64.0% (50.9%, 70.6%) and 67.7% (53.8%, 77.5%) for symptomatic infections. Adults who received a third vaccine dose were less likely to test positive compared to those who received two doses, with adjusted odds ratio of 0.36 (0.25, 0.53). Interpretation: Vaccination of children aged 12 to 17 years and third (booster) doses in adults were effective at reducing infection risk. High rates of vaccination, including booster doses, are a key part of the strategy to reduce infection rates in the community.

Journal article

van Dael J, Reader TW, Gillespie AT, Freise L, Darzi A, Mayer EKet al., 2022, Do national policies for complaint handling in English hospitals support quality improvement? Lessons from a case study, Journal of the Royal Society of Medicine, Pages: 1-9, ISSN: 0141-0768

ObjectivesA range of public inquiries in the English National Health Service have indicated repeating failings in complaint handling, and patients are often left dissatisfied. The complex, bureaucratic nature of complaints systems is often cited as an obstacle to meaningful investigation and learning, but a detailed examination of how such bureaucratic rules, regulations, and infrastructure shape complaint handling, and where change is most needed, remains relatively unexplored. We sought to examine how national policies structure local practices of complaint handling, how they are understood by those responsible for enacting them, and if there are any discrepancies between policies-as-intended and their reality in local practice.DesignCase study involving staff interviews and documentary analysis.SettingA large acute and multi-site NHS Trust in England.ParticipantsClinical, managerial, complaints, and patient advocacy staff involved in complaint handling at the participating NHS Trust (n=20).Main outcome measuresNot applicable.ResultsFindings illustrate four areas of practice where national policies and regulations can have adverse consequences within local practices, and partly function to undermine an improvement-focused approach to complaints. These include muddled routes for raising formal complaints, investigative procedures structured to scrutinize the ‘validity’ of complaints, futile data collection systems, and adverse incentives and workarounds resulting from bureaucratic performance targets.ConclusionThis study demonstrates how national policies and regulations for complaint handling can impede, rather than promote, quality improvement in local settings. Accordingly, we propose a number of necessary reforms, including patient involvement in complaints investigations, the establishment of independent investigation bodies, and more meaningful data analysis strategies to uncover and address systemic causes behind recurring complaints.

Journal article

Cann A, Clarke C, Brown J, Thomson T, Prendecki M, Moshe M, Badhan A, Simmons B, Klaber B, Elliott P, Darzi A, Riley S, Ashby D, Martin P, Gleeson S, Willicombe M, Kelleher P, Ward H, Barclay WS, Cooke GSet al., 2022, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody lateral flow assay for antibody prevalence studies following vaccination: a diagnostic accuracy study [version 2; peer review: 2 approved], Wellcome Open Research, Vol: 6, ISSN: 2398-502X

Background: Lateral flow immunoassays (LFIAs) are able to achieve affordable, large scale antibody testing and provide rapid results without the support of central laboratories. As part of the development of the REACT programme extensive evaluation of LFIA performance was undertaken with individuals following natural infection. Here we assess the performance of the selected LFIA to detect antibody responses in individuals who have received at least one dose of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine. Methods: This was a prospective diagnostic accuracy study. Sampling was carried out at renal outpatient clinic and healthcare worker testing sites at Imperial College London NHS Trust. Two cohorts of patients were recruited; the first was a cohort of 108 renal transplant patients attending clinic following two doses of SARS-CoV-2 vaccine, the second cohort comprised 40 healthcare workers attending for first SARS-CoV-2 vaccination and subsequent follow up. During the participants visit, finger-prick blood samples were analysed on LFIA device, while paired venous sampling was sent for serological assessment of antibodies to the spike protein (anti-S) antibodies. Anti-S IgG was detected using the Abbott Architect SARS-CoV-2 IgG Quant II CMIA. A total of 186 paired samples were collected. The accuracy of Fortress LFIA in detecting IgG antibodies to SARS-CoV-2 compared to anti-spike protein detection on Abbott Assay Results: The LFIA had an estimated sensitivity of 92.0% (114/124; 95% confidence interval [CI] 85.7% to 96.1%) and specificity of 93.6% (58/62; 95% CI 84.3% to 98.2%) using the Abbott assay as reference standard (using the threshold for positivity of 7.10 BAU/ml) Conclusions: Fortress LFIA performs well in the detection of antibody responses for intended purpose of population level surveillance but does not meet criteria for individual testing.

Journal article

Leiloglou M, Kedrzycki M, Chalau V, Chiarini N, Thiruchelvam P, Hadjiminas D, Hogben K, Rashid F, Ramakrishnan R, Darzi A, Leff D, Elson Det al., 2022, Indocyanine green fluorescence image processing techniques for breast cancer macroscopic demarcation, Scientific Reports, Vol: 12, ISSN: 2045-2322

Re-operation due to disease being inadvertently close to the resection margin is a major challenge in breast conserving surgery (BCS). Indocyanine green (ICG) fluorescence imaging could be used to visualize the tumor boundaries and help surgeons resect disease more efficiently. In this work, ICG fluorescence and color images were acquired with a custom-built camera system from 40 patients treated with BCS. Images were acquired from the tumor in-situ, surgical cavity post-excision, freshly excised tumor and histopathology tumour grossing. Fluorescence image intensity and texture were used as individual or combined predictors in both logistic regression (LR) and support vector machine models to predict the tumor extent. ICG fluorescence spectra in formalin-fixed histopathology grossing tumor were acquired and analyzed. Our results showed that ICG remains in the tissue after formalin fixation. Therefore, tissue imaging could be validated in freshly excised and in formalin-fixed grossing tumor. The trained LR model with combined fluorescence intensity (pixel values) and texture (slope of power spectral density curve) identified the tumor’s extent in the grossing images with pixel-level resolution and sensitivity, specificity of 0.75 ± 0.3, 0.89 ± 0.2.This model was applied on tumor in-situ and surgical cavity (post-excision) images to predict tumor presence.

Journal article

Bielinska A, Archer S, Darzi A, Urch Cet al., 2022, Co-designing an intervention to increase uptake of Advance Care Planning in later life following emergency hospitalisation: a research protocol using Accelerated Experience-Based Co-design (AEBCD) and The Behaviour Change Wheel (BCW)., BMJ Open, Vol: 12, Pages: 1-7, ISSN: 2044-6055

Introduction: Despite the potential benefits of advance care planning, uptake in older adults is low. In general, there is a lack of guidance as to how to initiate advance care planning conversations and encourage individuals to take action in planning their future care, including after emergency hospitalisation. Participatory action research methods are harnessed in health services research to design interventions that are relevant to end-users and stakeholders. This study aims to involve older persons, carers and healthcare professionals in co-designing an intervention to increase uptake of advance care planning in later life, which can be used by social contacts and healthcare professionals, particularly in the context of a recent emergency hospitalisation.Methods and analysis: The theory-driven participatory design research method integrates and adapts Accelerated Experience-Based Co-Design with the Behaviour Change Wheel, in the form of a collaborative multi-stakeholder co-design workshop. In total, 12 participants, comprising 4 lay persons aged 70+, 4 carers and 4 healthcare professionals with experience in elder care, will be recruited to participate in two online half-day sessions, together comprising one online workshop. There will be a maximum of 2 workshops. Firstly, in the discovery phase, participants will reflect on findings from earlier qualitative research on views and experiences of advance care planning from three workstreams: patients, carers, and healthcare professionals. Secondly, in the co-design phase, participants will explore practical mechanisms in which older persons aged 70+ can be encouraged to adopt advance care planning behaviours based on the Behaviour Change Wheel, in order to co-design a behavioural intervention to increase uptake of advance care planning in older adults after an emergency hospitalisation.Ethics and dissemination: Ethical approval has been obtained from the Science Engineering Technology Research Ethics Committee at

Journal article

Sivananthan A, Gueroult A, Zijlstra G, Martin G, Baheerathan A, Pratt P, Darzi A, Patel N, Kinross Jet al., 2022, A feasibility trial of HoloLens 2™; Using mixed reality headsets to deliver remote bedside teaching during COVID-19, JMIR Formative Research, Vol: 6, Pages: 1-7, ISSN: 2561-326X

BackgroundCOVID-19 has had a catastrophic impact measured in human lives. Medical education has also been impacted: appropriately stringent infection control policies have precluded medical trainees from attending clinical teaching. Lecture-based education has been easily transferred to a digital platform, but bedside teaching has not. This study aims to assess the feasibility of using a mixed reality (MR) headset to deliver remote bedside teaching.MethodsTwo MR sessions were led by senior doctors wearing the HoloLens™ headset. The trainers selected patients requiring their specialist input. The headset allowed bi-directional audio-visual communication between the trainer and trainee doctors. Trainee doctor conceptions of bedside teaching, impact of COVID-19 on bedside teaching and the MR sessions were evaluated using pre- and post-round questionnaires, using Likert scales. Data related to clinician exposure to at risk patients and use of PPE were collected.ResultsPre-questionnaire respondents (n=24) strongly agreed that bedside teaching is key to educating clinicians (7, IQR 6-7). Post-session questionnaires showed that overall users subjectively agreed the MR session was helpful to their learning (6, IQR 5.25 – 7) and that it was worthwhile (6, IQR 5.25 – 7). Mixed-reality versus in-person teaching led to a 79.5% reduction in cumulative clinician exposure time and 83.3% reduction in PPE use. ConclusionsThis study is proof of principle that HoloLens™ can be used effectively to deliver clinical bedside teaching This novel format confers significant advantages in terms of: minimising exposure of trainees to COVID-19; saving PPE; enabling larger attendance; and convenient accessible real-time clinical training.

Journal article

Chidambaram S, Maheswaran Y, Chan C, Hanna L, Ashrafian H, Markar SR, Sounderajah V, Alverdy JC, Darzi Aet al., 2022, Misinformation about the human gut microbiome in YouTube videos: cross-sectional study, JMIR Formative Research, Vol: 6, ISSN: 2561-326X

Background: Social media platforms such as YouTube are integral tools for disseminating information about health and wellness to the public. However, anecdotal reports have cited that the human gut microbiome has been a particular focus of dubious, misleading, and, on occasion, harmful media content. Despite these claims, there have been no published studies investigating this phenomenon within popular social media platforms.Objective: The aim of this study is to (1) evaluate the accuracy and reliability of the content in YouTube videos related to the human gut microbiome and (2) investigate the correlation between content engagement metrics and video quality, as defined by validated criteria.Methods: In this cross-sectional study, videos about the human gut microbiome were searched for on the United Kingdom version of YouTube on September 20, 2021. The 600 most-viewed videos were extracted and screened for relevance. The contents and characteristics of the videos were extracted and independently rated using the DISCERN quality criteria by 2 researchers.Results: Overall, 319 videos accounting for 62,354,628 views were included. Of the 319 videos, 73.4% (n=234) were produced in North America and 78.7% (n=251) were uploaded between 2019 and 2021. A total of 41.1% (131/319) of videos were produced by nonprofit organizations. Of the videos, 16.3% (52/319) included an advertisement for a product or promoted a health-related intervention for financial purposes. Videos by nonmedical education creators had the highest total and preferred viewership. Daily viewership was the highest for videos by internet media sources. The average DISCERN and Health on the Net Foundation Code of Conduct scores were 49.5 (SE 0.68) out of 80 and 5.05 (SE 2.52) out of 8, respectively. DISCERN scores for videos by medical professionals (mean 53.2, SE 0.17) were significantly higher than for videos by independent content creators (mean 39.1, SE 5.58; P<.001). Videos including promotional mate

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