Twitter communication of the UK public on dental health and care during a COVID lockdown : "My kingdom for a dentist"

Peer reviewedPublisher PD

A core outcome set for symptomatic uncomplicated gallstone disease

Funding This work was supported by a National Institute for Health Research Health Technology Assessment Programme Grant (14/192/71). The work was also supported by an NHS Grampian Endowment grant (16/11/006). K.G. held a Medical Research Council UK Methodology Fellowship during the delivery of this project (MR/L01193X/1). The HSRU, Institute of Applied Health Sciences (University of Aberdeen) is core funded by the Chief Scientist Office of the Scottish Government Health and Social Care Directorates. Acknowledgements The study team thank the DelphiManager team for support and guidance on use of the Delphi platform; and all participants in the study and organizations that disseminated the survey.Peer reviewedPublisher PD

Diagnostic accuracy of optical coherence tomography for diagnosing glaucoma: secondary analyses of the GATE study

Background/Aims: To assess the diagnostic performance of retinal nerve fibre layer (RNFL) data of optical coherence tomography (OCT) for detecting glaucoma. Methods: Secondary analyses of a prospective, multicentre diagnostic study (Glaucoma Automated Tests Evaluation (GATE)) referred to hospital eye services in the UK were conducted. We included data from 899 of 966 participants referred to hospital eye services with suspected glaucoma or ocular hypertension. We used both eyes’ data and logistic regression-based receiver operator characteristics analysis to build a set of models to measure the sensitivity and specificity of the average and inferior quadrant RNFL thickness data of OCT. The reference standard was expert clinician examination including automated perimetry. The main outcome measures were sensitivity at 0.95 specificity and specificity at 0.95 sensitivity and the corresponding RNFL thickness thresholds. We explored the possibility of accuracy improvement by adding measures of within-eye and between-eye variation, scan quality, intraocular pressure (IOP) and age. Results: Glaucoma was diagnosed in at least one eye in 17% of participants. Areas under the curve were between 0.83 and 0.88. When specificity was fixed at 0.95, the sensitivity was between 0.38 and 0.55, and the highest values were reached with models including the inferior quadrant rather than the average RNFL thickness. Fixing specificity at 0.95, the sensitivity was between 0.36 and 0.58. The addition of age, refractive error, IOP or within-subject variation did not improve the accuracy. Conclusion: RNFL thickness data of OCT can be used as a diagnostic test, but accuracy estimates remain moderate even in exploratory multivariable modelling of aiming to improve accuracy

Non-invasive testing for early detection of neovascular macular degeneration in unaffected second eyes of older adults : EDNA diagnostic accuracy study

Funding This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 26, No. 8. See the NIHR Journals Library website for further project information.Peer reviewedPublisher PD

Diagnostic Accuracy of Monitoring Tests of Fellow Eyes in Patients with Unilateral Neovascular Age-Related Macular Degeneration : Early Detection of Neovascular Age-Related Macular Degeneration Study

Funding Information: The author(s) have made the following disclosure(s): R.G.: Personal fees ? Heidelberg Engineering.S.S.: Grants and personal fees ? Bayer, during the conduct of the study; Grants and personal fees ? Novartis, Boehringer Ingleheim; Grants ? Allergan, Roche; Personal fees ? Apellis, Oxurion, Heidelberg Engineering, Optos, outside the submitted work; Funded by the Moorfields Biomedical Research Centre and Clinical Research Facility.The project was funded by the National Institute for Health Research Health Technology Assessment Programme (Project Number: 12/142/07) and will be published in full in Health Technology Assessment. The Health Services Research Unit and the Health Economics Research Unit are core funded by the Chief Scientist Office of the Scottish Government Health and Social Care Directorate. F.G.: Grants ? NIHR, during the conduct of the study; Grants and personal fees ? Novartis, Roche, Bayer; Personal fees ? Allergan, Alimera; Grants ? Chengdu Pharma; Grants and nonfinancial support ? NIHR, outside the submitted work. J.A.C.: Study grant ? NIHR. K.B.: Grants ? NIHR HTA Programme, during the conduct of the study. Obtained funding: Chakravarthy, Ramsay, Sivaprasad, Scotland, Azuara-Blanco, Heiman and Cook Publisher Copyright: © 2021Peer reviewedPublisher PD

Trial Forge Guidance 3: randomised trials and how to recruit and retain individuals from ethnic minority groups- practical guidance to support better practice

Randomised trials, especially those intended to directly inform clinical practice and policy, should be designed to reflect all those who could benefit from the intervention under test should it prove effective. This does not always happen. The UK National Institute for Health and Care Research (NIHR) INCLUDE project identified many groups in the UK that are under-served by trials, including ethnic minorities. This guidance document presents four key recommendations for designing and running trials that include the ethnic groups needed by the trial. These are (1) ensure eligibility criteria and recruitment pathway do not limit participation in ways you do not intend, (2) ensure your trial materials are developed with inclusion in mind, (3) ensure staff are culturally competent and (4) build trusting partnerships with community organisations that work with ethnic minority groups. Each recommendation comes with best practice advice, public contributor testimonials, examples of the inclusion problem tackled by the recommendation, or strategies to mitigate the problem, as well as a collection of resources to support implementation of the recommendations. We encourage trial teams to follow the recommendations and, where possible, evaluate the strategies they use to implement them. Finally, while our primary audience is those designing, running and reporting trials, we hope funders, grant reviewers and approvals agencies may also find our guidance useful

Can Automated Imaging for Optic Disc and Retinal Nerve Fiber Layer Analysis Aid Glaucoma Detection?

Purpose- To compare the diagnostic performance of automated imaging for glaucoma. Design- Prospective, direct comparison study. Participants- Adults with suspected glaucoma or ocular hypertension referred to hospital eye services in the United Kingdom. Methods- We evaluated 4 automated imaging test algorithms: the Heidelberg Retinal Tomography (HRT; Heidelberg Engineering, Heidelberg, Germany) glaucoma probability score (GPS), the HRT Moorfields regression analysis (MRA), scanning laser polarimetry (GDx enhanced corneal compensation; Glaucoma Diagnostics (GDx), Carl Zeiss Meditec, Dublin, CA) nerve fiber indicator (NFI), and Spectralis optical coherence tomography (OCT; Heidelberg Engineering) retinal nerve fiber layer (RNFL) classification. We defined abnormal tests as an automated classification of outside normal limits for HRT and OCT or NFI ≥ 56 (GDx). We conducted a sensitivity analysis, using borderline abnormal image classifications. The reference standard was clinical diagnosis by a masked glaucoma expert including standardized clinical assessment and automated perimetry. We analyzed 1 eye per patient (the one with more advanced disease). We also evaluated the performance according to severity and using a combination of 2 technologies. Main Outcome Measures- Sensitivity and specificity, likelihood ratios, diagnostic, odds ratio, and proportion of indeterminate tests. Results- We recruited 955 participants, and 943 were included in the analysis. The average age was 60.5 years (standard deviation, 13.8 years); 51.1% were women. Glaucoma was diagnosed in at least 1 eye in 16.8%; 32% of participants had no glaucoma-related findings. The HRT MRA had the highest sensitivity (87.0%; 95% confidence interval [CI], 80.2%–92.1%), but lowest specificity (63.9%; 95% CI, 60.2%–67.4%); GDx had the lowest sensitivity (35.1%; 95% CI, 27.0%–43.8%), but the highest specificity (97.2%; 95% CI, 95.6%–98.3%). The HRT GPS sensitivity was 81.5% (95% CI, 73.9%–87.6%), and specificity was 67.7% (95% CI, 64.2%–71.2%); OCT sensitivity was 76.9% (95% CI, 69.2%–83.4%), and specificity was 78.5% (95% CI, 75.4%–81.4%). Including only eyes with severe glaucoma, sensitivity increased: HRT MRA, HRT GPS, and OCT would miss 5% of eyes, and GDx would miss 21% of eyes. A combination of 2 different tests did not improve the accuracy substantially. Conclusions- Automated imaging technologies can aid clinicians in diagnosing glaucoma, but may not replace current strategies because they can miss some cases of severe glaucoma

Developing the INCLUDE Ethnicity Framework—a tool to help trialists design trials that better reflect the communities they serve

Background Ensuring that a trial is designed so that its participants reflect those who might benefit from the results, or be spared harms, is key to the potential benefits of the trial reaching all they should. This paper describes the process, facilitated by Trial Forge, that was used between July 2019 and October 2020 to develop the INCLUDE Ethnicity Framework, part of the wider INCLUDE initiative from the National Institute for Health Research to improve inclusion of under-served groups in clinical research studies. Methods Development of the Framework was done in seven phases: (1) outline, (2) initial draft, (3) stakeholder meeting, (4) modify draft, (5) Stakeholder feedback, (6) applying the Framework and (7) packaging. Phases 2 and 3 were face-to-face meetings. Consultation with stakeholders was iterative, especially phases 4 to 6. Movement to the next phase was done once all or most stakeholders were comfortable with the results of the current phase. When there was a version of the Framework that could be considered final, the Framework was applied to six trials to create a set of examples (phase 6). Finally, the Framework, guidance and examples were packaged ready for dissemination (phase 7). Results A total of 40 people from stakeholder groups including patient and public partners, clinicians, funders, academics working with various ethnic groups, trial managers and methodologists contributed to the seven phases of development. The Framework comprises two parts. The first part is a list of four key questions: 1.Who should my trial apply to? 2.Are the groups identified likely to respond in different ways? 3.Will my study intervention make it harder for some groups to engage? 4.Will the way I have designed the study make it harder for some groups to engage? The second part is a set of worksheets to help trial teams address these questions. The Framework can be used for any stage of trial, for a healthcare intervention in any disease area. The Framework was launched on 1st October 2020 and is available open access at the Trial Forge website: https://www.trialforge.org/trial-forge-centre/include/. Conclusion Thinking about the number of people in our trials is not enough: we need to start thinking more carefully about who our participants are