Comparing natural language processing representations of coded disease sequences for prediction in electronic health records.

OBJECTIVE: Natural language processing (NLP) algorithms are increasingly being applied to obtain unsupervised representations of electronic health record (EHR) data, but their comparative performance at predicting clinical endpoints remains unclear. Our objective was to compare the performance of unsupervised representations of sequences of disease codes generated by bag-of-words versus sequence-based NLP algorithms at predicting clinically relevant outcomes. MATERIALS AND METHODS: This cohort study used primary care EHRs from 6 286 233 people with Multiple Long-Term Conditions in England. For each patient, an unsupervised vector representation of their time-ordered sequences of diseases was generated using 2 input strategies (212 disease categories versus 9462 diagnostic codes) and different NLP algorithms (Latent Dirichlet Allocation, doc2vec, and 2 transformer models designed for EHRs). We also developed a transformer architecture, named EHR-BERT, incorporating sociodemographic information. We compared the performance of each of these representations (without fine-tuning) as inputs into a logistic classifier to predict 1-year mortality, healthcare use, and new disease diagnosis. RESULTS: Patient representations generated by sequence-based algorithms performed consistently better than bag-of-words methods in predicting clinical endpoints, with the highest performance for EHR-BERT across all tasks, although the absolute improvement was small. Representations generated using disease categories perform similarly to those using diagnostic codes as inputs, suggesting models can equally manage smaller or larger vocabularies for prediction of these outcomes. DISCUSSION AND CONCLUSION: Patient representations produced by sequence-based NLP algorithms from sequences of disease codes demonstrate improved predictive content for patient outcomes compared with representations generated by co-occurrence-based algorithms. This suggests transformer models may be useful for generating multi-purpose representations, even without fine-tuning.

Assigning disease clusters to people: A cohort study of the implications for understanding health outcomes in people with multiple long-term conditions.

Background: Identifying clusters of co-occurring diseases may help characterise distinct phenotypes of Multiple Long-Term Conditions (MLTC). Understanding the associations of disease clusters with health-related outcomes requires a strategy to assign clusters to people, but it is unclear how the performance of strategies compare. Aims: First, to compare the performance of methods of assigning disease clusters to people at explaining mortality, emergency department attendances and hospital admissions over one year. Second, to identify the extent of variation in the associations with each outcome between and within clusters. Methods: We conducted a cohort study of primary care electronic health records in England, including adults with MLTC. Seven strategies were tested to assign patients to fifteen disease clusters representing 212 LTCs, identified from our previous work. We tested the performance of each strategy at explaining associations with the three outcomes over 1 year using logistic regression and compared to a strategy using the individual LTCs. Results: 6,286,233 patients with MLTC were included. Of the seven strategies tested, a strategy assigning the count of conditions within each cluster performed best at explaining all three outcomes but was inferior to using information on the individual LTCs. There was a larger range of effect sizes for the individual LTCs within the same cluster than there was between the clusters. Conclusion: Strategies of assigning clusters of co-occurring diseases to people were less effective at explaining health-related outcomes than a person's individual diseases. Furthermore, clusters did not represent consistent relationships of the LTCs within them, which might limit their application in clinical research.

Adoption of routine surgical video recording: a nationwide freedom of information act request across England and Wales.

Background: Surgical video contains data with significant potential to improve surgical outcome assessment, quality assurance, education, and research. Current utilisation of surgical video recording is unknown and related policies/governance structures are unclear. Methods: A nationwide Freedom of Information (FOI) request concerning surgical video recording, technology, consent, access, and governance was sent to all acute National Health Service (NHS) trusts/boards in England/Wales between 20th February and 20th March 2023. Findings: 140/144 (97.2%) trusts/boards in England/Wales responded to the FOI request. Surgical procedures were routinely recorded in 22 trusts/boards. The median estimate of consultant surgeons routinely recording their procedures was 20%. Surgical video was stored on internal systems (n = 27), third-party products (n = 29), and both (n = 9). 32/140 (22.9%) trusts/boards ask for consent to record procedures as part of routine care. Consent for recording included non-clinical purposes in 55/140 (39.3%) trusts/boards. Policies for surgeon/patient access to surgical video were available in 48/140 (34.3%) and 32/140 (22.9%) trusts/boards, respectively. Surgical video was used for non-clinical purposes in 64/140 (45.7%) trusts/boards. Governance policies covering surgical video recording, use, and/or storage were available from 59/140 (42.1%) trusts/boards. Interpretation: There is significant heterogeneity in surgical video recording practices in England and Wales. A minority of trusts/boards routinely record surgical procedures, with large variation in recording/storage practices indicating scope for NHS-wide coordination. Revision of surgical video consent, accessibility, and governance policies should be prioritised by trusts/boards to protect key stakeholders. Increased availability of surgical video is essential for patients and surgeons to maximally benefit from the ongoing digital transformation of surgery. Funding: KL is supported by an NIHR Academic Clinical Fellowship and acknowledges infrastructure support for this research from the National Institute for Health Research (NIHR) Imperial Biomedical Research Centre (BRC).

Telencephalic eversion in embryos and early larvae of four teleost species.

The telencephalon of ray-finned fishes undergoes eversion, which is very different to the evagination that occurs in most other vertebrates. Ventricle morphogenesis is key to build an everted telencephalon. Thus, here we use the apical marker zona occludens 1 to understand ventricle morphology, extension of the tela choroidea and the eversion process during early telencephalon development of four teleost species: giant danio (Devario aequipinnatus), blind cavefish (Astyanax mexicanus), medaka (Oryzias latipes), and paradise fish (Macroposus opercularis). In addition, by using immunohistochemistry against tubulin and calcium-binding proteins, we analyze the general morphology of the telencephalon, showing changes in the location and extension of the olfactory bulb and other telencephalic regions from 2 to 5 days of development. We also analyze the impact of abnormal eye and telencephalon morphogenesis on eversion, showing that cyclops mutants do undergo eversion despite very dramatic abnormal eye morphology. We discuss how the formation of the telencephalic ventricle in teleost fish, with its characteristic shape, is a crucial event during eversion.

Effect of timeframes to define long term conditions and sociodemographic factors on prevalence of multimorbidity using disease code frequency in primary care electronic health records: retrospective study.

Objective: To determine the extent to which the choice of timeframe used to define a long term condition affects the prevalence of multimorbidity and whether this varies with sociodemographic factors. Design: Retrospective study of disease code frequency in primary care electronic health records. Data sources: Routinely collected, general practice, electronic health record data from the Clinical Practice Research Datalink Aurum were used. Main outcome measures: Adults (≥18 years) in England who were registered in the database on 1 January 2020 were included. Multimorbidity was defined as the presence of two or more conditions from a set of 212 long term conditions. Multimorbidity prevalence was compared using five definitions. Any disease code recorded in the electronic health records for 212 conditions was used as the reference definition. Additionally, alternative definitions for 41 conditions requiring multiple codes (where a single disease code could indicate an acute condition) or a single code for the remaining 171 conditions were as follows: two codes at least three months apart; two codes at least 12 months apart; three codes within any 12 month period; and any code in the past 12 months. Mixed effects regression was used to calculate the expected change in multimorbidity status and number of long term conditions according to each definition and associations with patient age, gender, ethnic group, and socioeconomic deprivation. Results: 9 718 573 people were included in the study, of whom 7 183 662 (73.9%) met the definition of multimorbidity where a single code was sufficient to define a long term condition. Variation was substantial in the prevalence according to timeframe used, ranging from 41.4% (n=4 023 023) for three codes in any 12 month period, to 55.2% (n=5 366 285) for two codes at least three months apart. Younger people (eg, 50-75% probability for 18-29 years v 1-10% for ≥80 years), people of some minority ethnic groups (eg, people in the Other ethnic group had higher probability than the South Asian ethnic group), and people living in areas of lower socioeconomic deprivation were more likely to be re-classified as not multimorbid when using definitions requiring multiple codes. Conclusions: Choice of timeframe to define long term conditions has a substantial effect on the prevalence of multimorbidity in this nationally representative sample. Different timeframes affect prevalence for some people more than others, highlighting the need to consider the impact of bias in the choice of method when defining multimorbidity.

FAST® questionnaire for identifying glaucoma patients at risk for ocular surface disease.

OBJECTIVES: To evaluate the validity and reliability of the new Fast Assessment of the Ocular Surface Trouble (FAST®) questionnaire for identifying glaucoma or ocular hypertension (OHT) patients at risk of ocular surface disease (OSD). METHODS: A multicenter, international, cross-sectional, epidemiological survey evaluated the most accurate interview items and ocular signs on the initial 14-item version of FAST® to develop a shorter version for routine, quick clinical use. Rasch analysis and least absolute shrinkage and selection operator (LASSO) method was used to reduce the number of items on the questionnaire. Sensitivity and specificity of FAST® were assessed with receiver operating characteristic (ROC) curves for the detection of OSD with the questionnaire and ophthalmic assessment. RESULTS: A total of 2308 eyes (1154 patients) were analyzed in this study by 92 ophthalmologists. The initial version of the FAST® indicated 60% of the subjects had OSD. Rasch analysis allowed removal of some clinical signs. The LASSO method allowed elimination of some items from the original questionnaire for a 9-item and a 6-item version of FAST®. For the 6-item questionnaire, the sensitivity and specificity were 71.9% and 74.3% respectively and the area under the curve was 0.815. CONCLUSIONS: The FAST® questionnaire is a valid and reliable tool for use in routine clinical practice and in clinical trials. The short versions of the questionnaire allow quick detection of the majority of patients with OHT or glaucoma at risk of dry eye.

p-tau Ser356 is associated with Alzheimer's disease pathology and is lowered in brain slice cultures using the NUAK inhibitor WZ4003.

Tau hyperphosphorylation and aggregation is a common feature of many dementia-causing neurodegenerative diseases. Tau can be phosphorylated at up to 85 different sites, and there is increasing interest in whether tau phosphorylation at specific epitopes, by specific kinases, plays an important role in disease progression. The AMP-activated protein kinase (AMPK)-related enzyme NUAK1 has been identified as a potential mediator of tau pathology, whereby NUAK1-mediated phosphorylation of tau at Ser356 prevents the degradation of tau by the proteasome, further exacerbating tau hyperphosphorylation and accumulation. This study provides a detailed characterisation of the association of p-tau Ser356 with progression of Alzheimer's disease pathology, identifying a Braak stage-dependent increase in p-tau Ser356 protein levels and an almost ubiquitous presence in neurofibrillary tangles. We also demonstrate, using sub-diffraction-limit resolution array tomography imaging, that p-tau Ser356 co-localises with synapses in AD postmortem brain tissue, increasing evidence that this form of tau may play important roles in AD progression. To assess the potential impacts of pharmacological NUAK inhibition in an ex vivo system that retains multiple cell types and brain-relevant neuronal architecture, we treated postnatal mouse organotypic brain slice cultures from wildtype or APP/PS1 littermates with the commercially available NUAK1/2 inhibitor WZ4003. Whilst there were no genotype-specific effects, we found that WZ4003 results in a culture-phase-dependent loss of total tau and p-tau Ser356, which corresponds with a reduction in neuronal and synaptic proteins. By contrast, application of WZ4003 to live human brain slice cultures results in a specific lowering of p-tau Ser356, alongside increased neuronal tubulin protein. This work identifies differential responses of postnatal mouse organotypic brain slice cultures and adult human brain slice cultures to NUAK1 inhibition that will be important to consider in future work developing tau-targeting therapeutics for human disease.

Predictive value of the National Early Warning Score 2 for hospitalised patients with viral respiratory illness is improved by the addition of inspired oxygen fraction as a weighted variable.

OBJECTIVES: The National Early Warning Score 2 (NEWS2) is validated for predicting acute deterioration, however, the binary grading of inspired oxygen fraction (FiO2) may limit performance. We evaluated the incorporation of FiO2 as a weighted categorical variable on NEWS2 prediction of patient deterioration. SETTING: Two hospitals at a single medical centre, Guy's and St Thomas' NHS Foundation Trust. DESIGN: Retrospective cohort of all ward admissions, with a viral respiratory infection (SARS-CoV-2/influenza). PARTICIPANTS: 3704 adult ward admissions were analysed between 01 January 2017 and 31 December 2021. METHODS: The NEWS-FiO2 score transformed FiO2 into a weighted categorical variable, from 0 to 3 points, substituting the original 0/2 points. The primary outcome was a composite of cardiac arrest, unplanned critical care admission or death within 24 hours of the observation. Sensitivity, positive predictive value (PPV), number needed to evaluate (NNE) and area under the receiver operating characteristic curve (AUROC) were calculated. Failure analysis for the time from trigger to outcome was compared by log-rank test. RESULTS: The mean age was 60.4±19.4 years, 52.6% were men, with a median Charlson Comorbidity of 0 (IQR 3). The primary outcome occurred in 493 (13.3%) patients, and the weighted FiO2 score was strongly associated with the outcome (p=<0.001). In patients receiving supplemental oxygen, 78.5% of scores were reclassified correctly and the AUROC was 0.81 (95% CI 0.81 to 0.81) for NEWS-FiO2 versus 0.77 (95% CI 0.77 to 0.77) for NEWS2. This improvement persisted in the whole cohort with a significantly higher failure rate for NEWS-FiO2 (p=<0.001). At the 5-point threshold, the PPV increased by 22.0% (NNE 6.7) for only a 3.9% decrease in sensitivity. CONCLUSION: Transforming FiO2 into a weighted categorical variable improved NEWS2 prediction for patient deterioration, significantly improving the PPV. Prospective external validation is required before institutional implementation.

The use of clinical photography to aid in the triage of ENT patient referrals.

Waiting lists for Ear, Nose and Throat (ENT) outpatient appointments are currently the longest that they have ever been. The Aneurin Bevan University Health Board has adopted a unique Clinical Photography ENT triage service to tackle this. General Practitioner referrals are triaged by ENT consultants, to identify those patients in whom otoscopic imaging could be used to detect a serious otological condition or to enable virtual management. They are triaged to Clinical Photography, to undergo digital imaging which is reviewed in a virtual clinic alongside the initial referral. 72 patients have completed the pathway, with 51.3% discharged without requirement for face-to-face consultant appointment. 9.7% were upgraded to urgent or 2 week waits. This intervention is predicted to help identify patients on the waiting list with potentially serious disease so that they do not wait excessively, and to reduce waiting times for outpatient appointments in ENT.

Multiscale mobility patterns and the restriction of human movement.

From the perspective of human mobility, the COVID-19 pandemic constituted a natural experiment of enormous reach in space and time. Here, we analyse the inherent multiple scales of human mobility using Facebook Movement maps collected before and during the first UK lockdown. Firstly, we obtain the pre-lockdown UK mobility graph and employ multiscale community detection to extract, in an unsupervised manner, a set of robust partitions into flow communities at different levels of coarseness. The partitions so obtained capture intrinsic mobility scales with better coverage than nomenclature of territorial units for statistics (NUTS) regions, which suffer from mismatches between human mobility and administrative divisions. Furthermore, the flow communities in the fine-scale partition not only match well the UK travel to work areas but also capture mobility patterns beyond commuting to work. We also examine the evolution of mobility under lockdown and show that mobility first reverted towards fine-scale flow communities already found in the pre-lockdown data, and then expanded back towards coarser flow communities as restrictions were lifted. The improved coverage induced by lockdown is well captured by a linear decay shock model, which allows us to quantify regional differences in both the strength of the effect and the recovery time from the lockdown shock.

The rational design of ARUK2007145, a dual inhibitor of the α and γ isoforms of the lipid kinase phosphatidylinositol 5-phosphate 4-kinase (PI5P4K).

The phosphatidylinositol 5-phosphate 4-kinases (PI5P4Ks) are therapeutic targets for diseases such as cancer, neurodegeneration and immunological disorders as they are key components in regulating cell signalling pathways. In an effort to make probe molecules available for further exploring these targets, we have previously reported PI5P4Kα-selective and PI5P4Kγ-selective ligands. Herein we report the rational design of PI5P4Kα/γ dual inhibitors, using knowledge gained during the development of selective inhibitors for these proteins. ARUK2007145 (39) is disclosed as a potent, cell-active probe molecule with ADMET properties amenable to conducting experiments in cells.

Identifying potential biases in code sequences in primary care electronic healthcare records: a retrospective cohort study of the determinants of code frequency.

OBJECTIVES: To determine whether the frequency of diagnostic codes for long-term conditions (LTCs) in primary care electronic healthcare records (EHRs) is associated with (1) disease coding incentives, (2) General Practice (GP), (3) patient sociodemographic characteristics and (4) calendar year of diagnosis. DESIGN: Retrospective cohort study. SETTING: GPs in England from 2015 to 2022 contributing to the Clinical Practice Research Datalink Aurum dataset. PARTICIPANTS: All patients registered to a GP with at least one incident LTC diagnosed between 1 January 2015 and 31 December 2019. PRIMARY AND SECONDARY OUTCOME MEASURES: The number of diagnostic codes for an LTC in (1) the first and (2) the second year following diagnosis, stratified by inclusion in the Quality and Outcomes Framework (QOF) financial incentive programme. RESULTS: 3 113 724 patients were included, with 7 723 365 incident LTCs. Conditions included in QOF had higher rates of annual coding than conditions not included in QOF (1.03 vs 0.32 per year, p<0.0001). There was significant variation in code frequency by GP which was not explained by patient sociodemographics. We found significant associations with patient sociodemographics, with a trend towards higher coding rates in people living in areas of higher deprivation for both QOF and non-QOF conditions. Code frequency was lower for conditions with follow-up time in 2020, associated with the onset of the COVID-19 pandemic. CONCLUSIONS: The frequency of diagnostic codes for newly diagnosed LTCs is influenced by factors including patient sociodemographics, disease inclusion in QOF, GP practice and the impact of the COVID-19 pandemic. Natural language processing or other methods using temporally ordered code sequences should account for these factors to minimise potential bias.

Perceptions of chief clinical information officers on the state of electronic health records systems interoperability in NHS England: a qualitative interview study.

BACKGROUND: In the era of electronic health records (EHR), the ability to share clinical data is a key facilitator of healthcare delivery. Since the introduction of EHRs, this aspect has been extensively studied from the perspective of healthcare providers. Less often explored are the day-to-day challenges surrounding the procurement, deployment, maintenance, and use of interoperable EHR systems, from the perspective of healthcare administrators, such as chief clinical information officers (CCIOs). OBJECTIVE: Our study aims to capture the perceptions of CCIOs on the current state of EHR interoperability in the NHS, its impact on patient safety, the perceived facilitators and barriers to improving EHR interoperability, and what the future of EHR development in the NHS may entail. METHODS: Semi-structured interviews were conducted between November 2020 - October 2021. Convenience sampling was employed to recruit NHS England CCIOs. Interviews were digitally recorded and transcribed verbatim. A thematic analysis was performed by two independent researchers to identify emerging themes. RESULTS: Fifteen CCIOs participated in the study. Participants reported that limited EHR interoperability contributed to the inability to easily access and transfer data into a unified source, thus resulting in data fragmentation. The resulting lack of clarity on patients' health status negatively impacts patient safety through suboptimal care coordination, duplication of efforts, and more defensive practice. Facilitators to improving interoperability included the recognition of the need by clinicians, patient expectations, and the inherent centralised nature of the NHS. Barriers included systems usability difficulties, and institutional, data management, and financial-related challenges. Looking ahead, participants acknowledged that realising that vision across the NHS would require a renewed focus on mandating data standards, user-centred design, greater patient involvement, and encouraging inter-organisational collaboration. CONCLUSION: Tackling poor interoperability will require solutions both at the technical level and in the wider policy context. This will involve demanding interoperability functionalities from the outset in procurement contracts, fostering greater inter-organisation cooperation on implementation strategies, and encouraging systems vendors to prioritise interoperability in their products. Only by comprehensively addressing these challenges would the full potential promised by the use of fully interoperable EHRs be realised.

Back to basics: A mediation analysis approach to addressing the fundamental questions of integrated care evaluations.

Health systems around the world are aiming to improve the integration of health and social care services to deliver better care for patients. Existing evaluations have focused exclusively on the impact of care integration on health outcomes and found little effect. That suggests the need to take a step back and ask whether integrated care programmes actually lead to greater clinical integration of care and indeed whether greater integration is associated with improved health outcomes. We propose a mediation analysis approach to address these two fundamental questions when evaluating integrated care programmes. We illustrate our approach by re-examining the impact of an English integrated care program on clinical integration and assessing whether greater integration is causally associated with fewer admissions for ambulatory care sensitive conditions. We measure clinical integration using a concentration index of outpatient referrals at the general practice level. While we find that the scheme increased integration of primary and secondary care, clinical integration did not mediate a decrease in unplanned hospital admissions. Our analysis emphasizes the need to better understand the hypothesized causal impact of integration on health outcomes and demonstrates how mediation analysis can inform future evaluations and program design.

Identification of ARUK2002821 as an isoform-selective PI5P4Kα inhibitor.

The phosphatidylinositol 5-phosphate 4-kinases (PI5P4Ks) play a central role in regulating cell signalling pathways and, as such, have become therapeutic targets for diseases such as cancer, neurodegeneration and immunological disorders. Many of the PI5P4Kα inhibitors that have been reported to date have suffered from poor selectivity and/or potency and the availability of better tool molecules would facilitate biological exploration. Herein we report a novel PI5P4Kα inhibitor chemotype that was identified through virtual screening. The series was optimised to deliver ARUK2002821 (36), a potent PI5P4Kα inhibitor (pIC50 = 8.0) which is selective vs. other PI5P4K isoforms and has broad selectivity against lipid and protein kinases. ADMET and target engagement data are provided for this tool molecule and others in the series, as well as an X-ray structure of 36 solved in complex with its PI5P4Kα target.

Should Long-Term Survival in Elderly Patients Presenting with Diabetic Foot Complications Impact Treatment Decision Making?

Patients presenting with diabetic foot ulceration (DFU) and associated complications often require revascularisation. Although current evidence advocates for an open bypass first strategy if patients are expected to live more than two years, this may not be appropriate in octogenarians. We sought to investigate the survival of patients aged over 70 years presenting with complicated DFU and chronic limb threatening ischaemia (CLTI) to clarify its prognosis and guide subsequent management. A database of patients admitted into a large tertiary service over the age of 70 years with DFU and CLTI between 2014 and 2017 were included. Survival data was obtained from medical records and public obituaries through to 2020. Patients were divided into three age groups: seventies (70-79 years), eighties (80-89 years) and nineties (≥90 years). Survival was evaluated using a stratified log-rank test and Kaplan-Meier methods. A total of 323 patients were included for analysis. Survival information was available for 225 patients (69%). Mean duration of follow-up was 19 months. There were 113 deaths recorded (35%). Mean survival for patients in their seventies, eighties and nineties was 63 months (95% CI 48.8-65.5), 37 months (95% CI 27.4-44.9) and 6 months (95% CI 2.3-19.2), respectively. In patients over 70 years of age presenting with DFU and CLTI, long-term survival decreases rapidly with increasing age, especially in the octogenarians. With recent technological advances and reduced morbidity, an endovascular approach may sufficiently treat acute presentations in octogenarians while reserving an open first strategy for younger patients with better long-term survival and adequate autologous conduit.

Factors associated with enrolment into a national COVID-19 pulse oximetry remote monitoring programme in England: a retrospective observational study.

BACKGROUND: Hypoxaemia is an important predictor of severity in individuals with COVID-19 and can present without symptoms. The COVID Oximetry @home (CO@h) programme was implemented across England in November, 2020, providing pulse oximeters to higher-risk people with COVID-19 to enable early detection of deterioration and the need for escalation of care. We aimed to describe the clinical and demographic characteristics of individuals enrolled onto the programme and to assess whether there were any inequalities in enrolment. METHODS: This retrospective observational study was based on data from a cohort of people resident in England recorded as having a positive COVID-19 test between Oct 1, 2020, and May 3, 2021. The proportion of participants enrolled onto the CO@h programmes in the 7 days before and 28 days after a positive COVID-19 test was calculated for each clinical commissioning group (CCG) in England. Two-level hierarchical multivariable logistic regression with random intercepts for each CCG was run to identify factors predictive of being enrolled onto the CO@h programme. FINDINGS: CO@h programme sites were reported by NHS England as becoming operational between Nov 21 and Dec 31, 2020. 1 227 405 people resident in 72 CCGs had a positive COVID-19 test between the date of programme implementation and May 3, 2021, of whom 19 932 (1·6%) were enrolled onto the CO@h programme. Of those enrolled, 14 441 (72·5%) were aged 50 years or older or were identified as clinically extremely vulnerable (ie, having a high-risk medical condition). Higher odds of enrolment onto the CO@h programme were found in older individuals (adjusted odds ratio 2·21 [95% CI 2·19-2·23], p<0·001, for those aged 50-64 years; 3·48 [3·33-3·63], p<0·001, for those aged 65-79 years; and 2·50 [2·34-2·68], p<0·001, for those aged ≥80 years), in individuals of non-White ethnicity (1·35 [1·28-1·43], p<0·001, for Asian individuals; 1·13 [1·04-1·22], p=0·005, for Black individuals; and 1·17 [1·03-1·32], p=0·015, for those of mixed ethnicity), in those who were overweight (1·31 [1·26-1·37], p<0·001) or obese (1·69 [1·63-1·77], p<0·001), or in those identified as clinically extremely vulnerable (1·58 [1·51-1·65], p<0·001), and lower odds were reported in those from the least socioeconomically deprived areas compared with those from the most socioeconomically deprived areas (0·75 [0·69-0·81]; p<0·001). INTERPRETATION: Nationally, uptake of the CO@h programme was low, with clinical judgment used to determine eligibility. Preferential enrolment onto the pulse oximetry monitoring programme was observed in people known to be at the highest risk of developing severe COVID-19. FUNDING: NHS England, National Institute for Health Research, and The Wellcome Trust.