Target Product Profile for a Machine Learning-Automated Retinal Imaging Analysis Software for Use in English Diabetic Eye Screening: Protocol for a Mixed Methods Study.

BACKGROUND: Diabetic eye screening (DES) represents a significant opportunity for the application of machine learning (ML) technologies, which may improve clinical and service outcomes. However, successful integration of ML into DES requires careful product development, evaluation, and implementation. Target product profiles (TPPs) summarize the requirements necessary for successful implementation so these can guide product development and evaluation. OBJECTIVE: This study aims to produce a TPP for an ML-automated retinal imaging analysis software (ML-ARIAS) system for use in DES in England. METHODS: This work will consist of 3 phases. Phase 1 will establish the characteristics to be addressed in the TPP. A list of candidate characteristics will be generated from the following sources: an overview of systematic reviews of diagnostic test TPPs; a systematic review of digital health TPPs; and the National Institute for Health and Care Excellence's Evidence Standards Framework for Digital Health Technologies. The list of characteristics will be refined and validated by a study advisory group (SAG) made up of representatives from key stakeholders in DES. This includes people with diabetes; health care professionals; health care managers and leaders; and regulators and policy makers. In phase 2, specifications for these characteristics will be drafted following a series of semistructured interviews with participants from these stakeholder groups. Data collected from these interviews will be analyzed using the shortlist of characteristics as a framework, after which specifications will be drafted to create a draft TPP. Following approval by the SAG, in phase 3, the draft will enter an internet-based Delphi consensus study with participants sought from the groups previously identified, as well as ML-ARIAS developers, to ensure feasibility. Participants will be invited to score characteristic and specification pairs on a scale from "definitely exclude" to "definitely include," and suggest edits. The document will be iterated between rounds based on participants' feedback. Feedback on the draft document will be sought from a group of ML-ARIAS developers before its final contents are agreed upon in an in-person consensus meeting. At this meeting, representatives from the stakeholder groups previously identified (minus ML-ARIAS developers, to avoid bias) will be presented with the Delphi results and feedback of the user group and asked to agree on the final contents by vote. RESULTS: Phase 1 was completed in November 2023. Phase 2 is underway and expected to finish in March 2024. Phase 3 is expected to be complete in July 2024. CONCLUSIONS: The multistakeholder development of a TPP for an ML-ARIAS for use in DES in England will help developers produce tools that serve the needs of patients, health care providers, and their staff. The TPP development process will also provide methods and a template to produce similar documents in other disease areas. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/50568.

Cross-sectional survey of child weight management service provision by acute NHS trusts across England in 2020/2021.

OBJECTIVE: With one in five children in England living with obesity, we mapped the geographical distribution and format of child weight management services provided by acute National Health Service (NHS) trusts across England, to identify breadth of service provision. DESIGN: A cross-sectional survey. SETTING: The survey was sent to acute NHS trusts (n=148) in England in 2020, via a freedom of information request. PARTICIPANTS: Responses were received from 139 of 148 (94%) acute NHS trusts, between March 2020 to March 2021. OUTCOME MEASURES: The survey asked each acute NHS trust whether they provide a weight management service for children living with obesity. For those trusts providing a service, data were collected on eligibility criteria, funding source, personnel involved, number of new patients seen per year, intervention duration, follow-up length and outcome measures. Service characteristics were reported using descriptive statistics. Service provision was analysed in the context of ethnicity and Index of Multiple Deprivation score of the trust catchment area. RESULTS: From the 139 survey respondents, 23% stated that they provided a weight management service for children living with obesity. There were inequalities in the proportion of acute NHS trusts providing a service across the different regions of England, ranging from 4% (Midlands) to 36% (London). For trusts providing a service, there was variability in the number of new cases seen per year, eligibility criteria, funding source, intervention format and outcome measures collected. A multidisciplinary approach was not routinely provided, with only 41% of services reporting ≥3 different staff disciplines. CONCLUSION: In 2020/2021, there were geographical inequalities in weight management service provision by acute NHS trusts for children living with obesity. Services provided lacked standardisation, did not routinely offer children multidisciplinary care and were insufficient in size to meet need.

Choosing an Effective PCR-Based Approach for Diet Analysis of Insect Herbivores: A Systematic Review.

Identification of ingested plant species using polymerase chain reaction (PCR)-based methods is an increasingly useful yet challenging approach to accurately determine the diet composition of insect herbivores and thus their trophic interactions. A typical process of detection of DNA of ingested plants involves the choice of a DNA extraction method, a genomic target region, and/or the best approach for an accurate plant species identification. The wide range of available techniques makes the choice of the most appropriate method for an accurately and timely identification of ingested plants from insect guts difficult. In our study, we reviewed the commonly used PCR-based approaches in studies published from 1977 to 2019, to provide researchers with the information on the tools which have been shown to be effective for obtaining and identifying ingested plants. Our results showed that among five insect orders used in the retrieved studies Coleoptera and Hemiptera were prevalent (33 and 28% of all the records, respectively). In 79% of the studies a DNA barcoding approach was employed. In a substantial number of studies Qiagen DNA extraction kits and CTAB protocol were used (43 and 23%, respectively). Of all records, 65% used a single locus as a targeted plant DNA fragment; trnL, rbcL, and ITS regions were the most frequently used loci. Sequencing was the dominant type of among DNA verification approaches (70% of all records). This review provides important information on the availability of successfully used PCR-based approaches to identify ingested plant DNA in insect guts, and suggests potential directions for future studies on plant-insect trophic interactions.