Comparative effectiveness of sotrovimab versus no treatment in non-hospitalised high-risk COVID-19 patients in north west London: a retrospective cohort study.

BACKGROUND: We assessed the effectiveness of sotrovimab vs no early COVID-19 treatment in highest-risk COVID-19 patients during Omicron predominance. METHODS: Retrospective cohort study using the Discover dataset in North West London. Included patients were non-hospitalised, aged ≥12 years and met ≥1 National Health Service highest-risk criterion for sotrovimab treatment. We used Cox proportional hazards models to compare HRs of 28-day COVID-19-related hospitalisation/death between highest-risk sotrovimab-treated and untreated patients. Age, renal disease and Omicron subvariant subgroup analyses were performed. RESULTS: We included 599 sotrovimab-treated patients and 5191 untreated patients. Compared with untreated patients, the risk of COVID-19 hospitalisation/death (HR 0.50, 95% CI 0.24, 1.06; p=0.07) and the risk of COVID-19 hospitalisation (HR 0.43, 95% CI 0.18, 1.00; p=0.051) were both lower in the sotrovimab-treated group; however, statistical significance was not reached. In the ≥65 years and renal disease subgroups, sotrovimab was associated with a significantly reduced risk of COVID-19 hospitalisation, by 89% (HR 0.11, 95% CI 0.02, 0.82; p=0.03) and 82% (HR 0.18, 95% CI 0.05, 0.62; p=0.007), respectively. CONCLUSIONS: Risk of COVID-19 hospitalisation in sotrovimab-treated patients aged ≥65 years and with renal disease was significantly lower compared with untreated patients. Overall, risk of hospitalisation was also lower for sotrovimab-treated patients, but statistical significance was not reached.

Qualitative study exploring the design of a patient-reported symptom-based risk stratification system for suspected head and neck cancer referrals: protocol for work packages 1 and 2 within the EVEREST-HN programme.

INTRODUCTION: Between 2009/2010 and 2019/2020, England witnessed an increase in suspected head and neck cancer (sHNC) referrals from 140 to 404 patients per 100 000 population. 1 in 10 patients are not seen within the 2-week target, contributing to patient anxiety. We will develop a pathway for sHNC referrals, based on the Head and Neck Cancer Risk Calculator. The evolution of a patient-reported symptom-based risk stratification system to redesign the sHNC referral pathway (EVEREST-HN) Programme comprises six work packages (WPs). This protocol describes WP1 and WP2. WP1 will obtain an understanding of language to optimise the SYmptom iNput Clinical (SYNC) system patient-reported symptom questionnaire for sHNC referrals and outline requirements for the SYNC system. WP2 will codesign key elements of the SYNC system, including the SYNC Questionnaire, and accompanying behaviour change materials. METHODS AND ANALYSIS: WP1 will be conducted at three acute National Health Service (NHS) trusts with variation in service delivery models and ensuring a broad mixture of social, economic and cultural backgrounds of participants. Up to 150 patients with sHNC (n=50 per site) and 15 clinicians (n=5 per site) will be recruited. WP1 will use qualitative methods including interviews, observation and recordings of consultations. Rapid qualitative analysis and inductive thematic analysis will be used to analyse the data. WP2 will recruit lay patient representatives to participate in online focus groups (n=8 per focus group), think-aloud technique and experience-based codesign and will be analysed using qualitative and quantitative approaches. ETHICS AND DISSEMINATION: The committee for clinical research at The Royal Marsden, a research ethics committee and the Health Research Authority approved this protocol. All participants will give informed consent. Ethical issues of working with patients on an urgent cancer diagnostic pathway have been considered. Findings will be disseminated via journal publications, conference presentations and public engagement activities.

Accuracy of automated computer-aided risk scoring systems to estimate the risk of COVID-19: a retrospective cohort study.

BACKGROUND: In the UK National Health Service (NHS), the patient's vital signs are monitored and summarised into a National Early Warning Score (NEWS) score. A set of computer-aided risk scoring systems (CARSS) was developed and validated for predicting in-hospital mortality and sepsis in unplanned admission to hospital using NEWS and routine blood tests results. We sought to assess the accuracy of these models to predict the risk of COVID-19 in unplanned admissions during the first phase of the pandemic. METHODS: Adult ( > = 18 years) non-elective admissions discharged (alive/deceased) between 11-March-2020 to 13-June-2020 from two acute hospitals with an index NEWS electronically recorded within ± 24 h of admission. We identified COVID-19 admission based on ICD-10 code 'U071' which was determined by COVID-19 swab test results (hospital or community). We assessed the performance of CARSS (CARS_N, CARS_NB, CARM_N, CARM_NB) for predicting the risk of COVID-19 in terms of discrimination (c-statistic) and calibration (graphically). RESULTS: The risk of in-hospital mortality following emergency medical admission was 8.4% (500/6444) and 9.6% (620/6444) had a diagnosis of COVID-19. For predicting COVID-19 admissions, the CARS_N model had the highest discrimination 0.73 (0.71 to 0.75) and calibration slope 0.81 (0.72 to 0.89) compared to other CARSS models: CARM_N (discrimination:0.68 (0.66 to 0.70) and calibration slope 0.47 (0.41 to 0.54)), CARM_NB (discrimination:0.68 (0.65 to 0.70) and calibration slope 0.37 (0.31 to 0.43)), and CARS_NB (discrimination:0.68 (0.66 to 0.70) and calibration slope 0.56 (0.47 to 0.64)). CONCLUSIONS: The CARS_N model is reasonably accurate for predicting the risk of COVID-19. It may be clinically useful as an early warning system at the time of admission especially to triage large numbers of unplanned admissions because it requires no additional data collection and is readily automated.

A palpable sense of frustration with NHS patient safety culture development.

John Tingle, Lecturer in Law, Birmingham Law School, University of Birmingham, discusses two recent reports on NHS patient safety.

An exploration of service use pattern changes and cost analysis following implementation of community perinatal mental health teams in pregnant women with a history of specialist mental healthcare in England: a national population-based cohort study.

BACKGROUND: The National Health Service in England pledged >£365 million to improve access to mental healthcare services via Community Perinatal Mental Health Teams (CPMHTs) and reduce the rate of perinatal relapse in women with severe mental illness. This study aimed to explore changes in service use patterns following the implementation of CPMHTs in pregnant women with a history of specialist mental healthcare in England, and conduct a cost-analysis on these changes. METHODS: This study used a longitudinal cohort design based on existing routine administrative data. The study population was all women residing in England with an onset of pregnancy on or after 1st April 2016 and who gave birth on or before 31st March 2018 with pre-existing mental illness (N = 70,323). Resource use and costs were compared before and after the implementation of CPMHTs. The economic perspective was limited to secondary mental health services, and the time horizon was the perinatal period (from the start of pregnancy to 1-year post-birth, ~ 21 months). RESULTS: The percentage of women using community mental healthcare services over the perinatal period was higher for areas with CPMHTs (30.96%, n=9,653) compared to areas without CPMHTs (24.72%, n=9,615). The overall percentage of women using acute care services (inpatient and crisis resolution teams) over the perinatal period was lower for areas with CPMHTs (4.94%, n=1,540 vs. 5.58%, n=2,171), comprising reduced crisis resolution team contacts (4.41%, n=1,375 vs. 5.23%, n=2,035) but increased psychiatric admissions (1.43%, n=445 vs. 1.13%, n=441). Total mental healthcare costs over the perinatal period were significantly higher for areas with CPMHTs (fully adjusted incremental cost £111, 95% CI £29 to £192, p-value 0.008). CONCLUSIONS: Following implementation of CPMHTs, the percentage of women using acute care decreased while the percentage of women using community care increased. However, the greater use of inpatient admissions alongside greater use of community care resulted in a significantly higher mean cost of secondary mental health service use for women in the CPMHT group compared with no CPMHT. Increased costs must be considered with caution as no data was available on relevant outcomes such as quality of life or satisfaction with services.

Comparing the effectiveness of computer-aided design/computer-aided manufacturing (CAD/CAM) of insoles manufactured from foam box cast versus direct scans on patient-reported outcome measures: a protocol for a double-blinded, randomised controlled trial.

INTRODUCTION: Custom insoles are a routine treatment for many foot pathologies, and the use of computer-aided design and computer-aided manufacturing (CAD/CAM) is well established within clinical practice in the UK. The method of foot shape capture used to produce insoles varies throughout orthotic services. This trial aims to investigate the effectiveness of two common shape-capture techniques on patient-reported outcomes in people who require insoles for a foot or ankle pathology. METHODS AND ANALYSIS: This double-blinded randomised controlled trial will involve two intervention groups recruited from a National Health Service orthotic service. Participants will be randomly assigned to receive a pair of custom CAD/CAM insoles, manufactured either from a direct digital scan or a foam box cast of their feet and asked to wear the insoles for 12 weeks. The primary outcome measure will be the Foot Health Status Questionnaire (FHSQ) pain subdomain, recorded at baseline (immediately after receiving the intervention), 4, 8 and 12 weeks post intervention. Secondary outcome measures will include FHSQ foot function and foot health subdomains recorded at baseline, 4, 8 and 12 weeks. The Orthotic and Prosthetic User Survey Satisfaction with Device will be recorded at 12 weeks. The transit times associated with each arm will be measured as the number of days for each insole to be delivered after foot shape capture. Tertiary outcome measures will include participant recruitment and dropout rates, and intervention adherence measured as the daily usage of the insoles over 12 weeks. The change in FHSQ scores for the subdomains and insole usage will be compared between the groups and time points, and between group differences in time in transit, cost-time analysis and environmental impact will be compared. ETHICS AND DISSEMINATION: Ethical approval was obtained from the Health Research Authority, London Stanmore Research Ethics Committee (22/LO/0579). Study findings will be submitted for publication in peer-reviewed journals, conference presentations and webinars. TRIAL REGISTRATION NUMBER: NCT05444192.

Effect of clinical engagement on value, standardisation, decision-making and savings in NHS product procurement.

BACKGROUND: UK healthcare expenditure is now £193.8 billion a year. The procurement function is seen as central to driving efficiencies within the NHS. This comes with an increasing onus on clinicians, including nurses and allied health professionals, to accept procurement outcomes to realise efficiency savings, with or without prior engagement. AIMS: This empirical study seeks to examine whether clinical engagement in the procurement of healthcare products in the NHS is necessary to achieve value, savings and standardisation; it will thereby address a gap in the research. METHODS: A multi-method qualitative case study design was used, which included a survey and eight semi-structured interviews. FINDINGS: Results identified three factors that influence the achievement of value, savings and standardisation around clinical engagement: micro-level processes for clinical engagement; clinical stakeholders and clinical procurement professionals as experts at the centre of procurement activity; and clinical value in standardisation. A shift away from standardisation to resilience was identified, resulting from current market supply pressures. CONCLUSION: This research brings empirically derived findings to address gaps in research, supports the benefit of clinical engagement through specific forums for collaboration at a trust level and provides a clinical/expert impact/preference matrix as a resource for procurement professionals to facilitate clinical engagement.

Solving poverty or tackling healthcare inequalities? Qualitative study exploring local interpretations of national policy on health inequalities under new NHS reforms in England.

OBJECTIVES: Major reforms to the organisation of the National Health Service (NHS) in England established 42 integrated care systems (ICSs) to plan and coordinate local services. The changes are based on the idea that cross-sector collaboration is needed to improve health and reduce health inequalities-and similar policy changes are happening elsewhere in the UK and internationally. We explored local interpretations of national policy objectives on reducing health inequalities among senior leaders working in three ICSs. DESIGN: We carried out qualitative research based on semistructured interviews with NHS, public health, social care and other leaders in three ICSs in England. SETTING AND PARTICIPANTS: We selected three ICSs with varied characteristics all experiencing high levels of socioeconomic deprivation. We conducted 32 in-depth interviews with senior leaders of NHS, local government and other organisations involved in the ICS's work on health inequalities. Our interviewees comprised 17 leaders from NHS organisations and 15 leaders from other sectors. RESULTS: Local interpretations of national policy objectives on health inequalities varied, and local leaders had contrasting-sometimes conflicting-perceptions of the boundaries of ICS action on reducing health inequalities. Translating national objectives into local priorities was often a challenge, and clarity from national policy-makers was frequently perceived as limited or lacking. Across the three ICSs, local leaders worried that objectives on tackling health inequalities were being crowded out by other short-term policy priorities, such as reducing pressures on NHS hospitals. The behaviour of national policy-makers appeared to undermine their stated priorities to reduce health inequalities. CONCLUSIONS: Varied and vague interpretations of NHS policy on health inequalities are not new, but lack of clarity among local health leaders brings major risks-including interventions being poorly targeted or inadvertently widening inequalities. Greater conceptual clarity is likely needed to guide ICS action in future.

Comorbidities and their association with COVID-19 mortality in Mexico between January 2020 and August 2021.

By August 17, 2021, 4.3 million people had died globally as a result of SARS-CoV-2 infection. While data collection is ongoing, it is abundantly obvious that this is one of the most significant public health crises in modern history. Consequently, global efforts are being made to attain a greater understanding of this disease and to identify risk factors associated with more severe outcomes. The goal of this study is to identify clinical characteristics and risk factors associated with COVID-19 mortality in Mexico. The dataset used in this study was released by Sistema Nacional de Vigilancia Epidemiologica de Enfermedades Respiratorias (SISVER) de la Secretaría de Salud and contains 2.9 million COVID-19 cases. The effects of risk factors on COVID-19 mortality were estimated using multivariable logistic regression models with generalized estimation equation and Kaplan-Meier curves. Case fatality rates, case hospitalization rates are also reported using the Centers for Disease Control and Prevention (CDC) USA death-to-case ratio method. In general, older males with pre-existing conditions had higher odds of death. Age greater than 40, male sex, hypertension, diabetes, and obesity are associated with higher COVID-19 mortality. End-stage renal disease, chronic obstructive pulmonary disease, and immunosuppression are all linked with COVID-19 patient fatalities. Smoking and Asthma are associated with lower COVID-19 mortality which is consistent with findings from the article published in Nature based on National Health Service (NHS) of UK dataset (17 million cases). Intensive care unit (ICU), patient intubation, and pneumonia diagnosis are shown to substantially increase mortality risk for COVID-19 patients.

Development of an enhanced scoring system to predict ICU readmission or in-hospital death within 24 hours using routine patient data from two NHS Foundation Trusts.

RATIONALE: Intensive care units (ICUs) admit the most severely ill patients. Once these patients are discharged from the ICU to a step-down ward, they continue to have their vital signs monitored by nursing staff, with Early Warning Score (EWS) systems being used to identify those at risk of deterioration. OBJECTIVES: We report the development and validation of an enhanced continuous scoring system for predicting adverse events, which combines vital signs measured routinely on acute care wards (as used by most EWS systems) with a risk score of a future adverse event calculated on discharge from the ICU. DESIGN: A modified Delphi process identified candidate variables commonly available in electronic records as the basis for a 'static' score of the patient's condition immediately after discharge from the ICU. L1-regularised logistic regression was used to estimate the in-hospital risk of future adverse event. We then constructed a model of physiological normality using vital sign data from the day of hospital discharge. This is combined with the static score and used continuously to quantify and update the patient's risk of deterioration throughout their hospital stay. SETTING: Data from two National Health Service Foundation Trusts (UK) were used to develop and (externally) validate the model. PARTICIPANTS: A total of 12 394 vital sign measurements were acquired from 273 patients after ICU discharge for the development set, and 4831 from 136 patients in the validation cohort. RESULTS: Outcome validation of our model yielded an area under the receiver operating characteristic curve of 0.724 for predicting ICU readmission or in-hospital death within 24 hours. It showed an improved performance with respect to other competitive risk scoring systems, including the National EWS (0.653). CONCLUSIONS: We showed that a scoring system incorporating data from a patient's stay in the ICU has better performance than commonly used EWS systems based on vital signs alone. TRIAL REGISTRATION NUMBER: ISRCTN32008295.