Total diet replacements (TDRs) and weight loss medications (WLMs) have proven effective in producing substantial weight loss for individuals with obesity. Evidence is lacking on whether combining these treatments is effective and cost-effective in primary care for adults with obesity class I (body mass index (BMI) 30–34.9) or uncomplicated obesity class II or higher (BMI≥35 without obesity-related disease).

LightCARE is a 2-year 1:1 randomised, parallel-group, clinical superiority trial with blinded outcome assessment evaluating the benefits and harms of an intensive weight loss (IWL) intervention compared with usual care for adults with obesity in Denmark and the UK. The trial will include 400 participants aged 18–60 years with obesity class I or uncomplicated obesity class II or higher. The IWL programme aims to achieve and maintain a weight loss of ≥20% through a flexible and individualised combination of TDR, behavioural support, including physical activity and sleep guidance, and WLM if needed and will continue for 2 years. The control group will receive usual care offered in each country, typically consisting of brief behavioural support for weight loss. The primary outcome is body weight 2 years after randomisation. Secondary outcomes will include the proportion of participants achieving ≥20% weight loss, Short-Form-36 Mental Component Score, 4-m gait speed and Metabolic Syndrome Severity-Z score. Serious adverse events, the incidence of eating disorders and bone mineral density will be evaluated as safety outcomes. We will also examine the cost-effectiveness of the intervention, within the trial and in the longer term through modelling. We will conduct a process evaluation to inform any future implementation.

Ethical approval was granted in Denmark (December 2023, H-23051332) and the UK (August 2024, 24/SC/0210). Findings from the trial will be disseminated through peer-reviewed journals and scientific conferences.

NCT06321432.

To integrate the quantitative and qualitative data collected as part of the PEACH (Procalcitonin: Evaluation of Antibiotic use in COVID-19 Hospitalised patients) study, which evaluated whether procalcitonin (PCT) testing should be used to guide antibiotic prescribing and safely reduce antibiotic use among patients admitted to acute UK National Health Service (NHS) hospitals.

Triangulation to integrate quantitative and qualitative data.

Four data sources in 148 NHS hospitals in England and Wales including data from 6089 patients.

A triangulation protocol was used to integrate three quantitative data sources (survey, organisation-level data and patient-level data: data sources 1, 2 and 3) and one qualitative data source (clinician interviews: data source 4) collected as part of the PEACH study. Analysis of data sources initially took place independently, and then, key findings for each data source were added to a matrix. A series of interactive discussion meetings took place with quantitative, qualitative and clinical researchers, together with patient and public involvement (PPI) representatives, to group the key findings and produce seven statements relating to the study objectives. Each statement and the key findings related to that statement were considered alongside an assessment of whether there was agreement, partial agreement, dissonance or silence across all four data sources (convergence coding). The matrix was then interpreted to produce a narrative for each statement.

To explore whether PCT testing safely reduced antibiotic use during the first wave of the COVID-19 pandemic.

Seven statements were produced relating to the PEACH study objective. There was agreement across all four data sources for our first key statement, ‘During the first wave of the pandemic (01/02/2020-30/06/2020), PCT testing reduced antibiotic prescribing’. The second statement was related to this key statement, ‘During the first wave of the pandemic (01/02/2020-30/06/2020), PCT testing safely reduced antibiotic prescribing’. Partial agreement was found between data sources 3 (quantitative patient-level data) and 4 (qualitative clinician interviews). There were no data regarding safety from data sources 1 or 2 (quantitative survey and organisational-level data) to contribute to this statement. For statements three and four, ‘PCT was not used as a central factor influencing antibiotic prescribing’, and ‘PCT testing reduced antibiotic prescribing in the emergency department (ED)/acute medical unit (AMU),’ there was agreement between data source 2 (organisational-level data) and data source 4 (interviews with clinicians). The remaining two data sources (survey and patient-level data) contributed no data on this statement. For statement five, ‘PCT testing reduced antibiotic prescribing in the intensive care unit (ICU)’, there was disagreement between data sources 2 and 3 (organisational-level data and patient-level data) and data source 4 (clinician interviews). Data source 1 (survey) did not provide data on this statement. We therefore assigned dissonance to this statement. For statement six, ‘There were many barriers to implementing PCT testing during the first wave of COVID-19’, there was partial agreement between data source 1 (survey) and data source 4 (clinician interviews) and no data provided by the two remaining data sources (organisational-level data and patient-level data). For statement seven, ‘Local PCT guidelines/protocols were perceived to be valuable’, only data source 4 (clinician interviews) provided data. The clinicians expressed that guidelines were valuable, but as there was no data from the other three data sources, we assigned silence to this statement.

There was agreement between all four data sources on our key finding ‘during the first wave of the pandemic (01/02/2020-30/06/2020), PCT testing reduced antibiotic prescribing’. Data, methodological and investigator triangulation, and a transparent triangulation protocol give validity to this finding.

ISRCTN66682918.