Satisfactory management of acute pain remains a major medical challenge despite the availability of multiple therapeutic options including the fixed-dose combination (FDC) drugs. Tramadol and dexketoprofen trometamol (TRAM/DKP) 75/25 mg FDC was launched in 2018 in Asia and is widely used in the management of moderate to severe acute pain. There are limited data on its effectiveness and safety in Asian patients, and therefore, a need to better understand its usage patterns in clinical practice. We aim to understand the usage pattern of TRAM/DKP FDC, its effectiveness and tolerability in patients with moderate to severe acute pain in Asia.

REKOVER is a phase-IV, multicountry, multicentre, prospective, real-world observational study. A total of 750 postsurgical and non-surgical patients (male and female, aged 18–80 years) will be recruited from 13 tertiary-care hospitals (15 sites) in Singapore, Thailand, the Philippines and Malaysia. All patients prescribed with TRAM/DKP FDC and willing to participate in the study will be enrolled. The recruitment duration for each site will be 6 months. The severity of pain will be collected using Numeric Pain Rating Scale through the treatment period from day 1 to day 5, while satisfaction with the treatment will be evaluated using Patient Global Evaluation Scale at the end of treatment. Any adverse event reported during the study duration will be recorded for safety analysis (up to day 6). The study data will be entered into the ClaimIt portal and mobile application (app) (ObvioHealth, USA). All the inpatient data will be entered into the portal by the study site and for outpatient it will be done by patients through an app.

The study has been approved by the local ethics committee from each study sites in Singapore, Thailand, the Philippines and Malaysia. Findings will be disseminated through local and global conference presentations, publications in peer-reviewed scientific journals and continuing medical education.

Despite international efforts, the number of individuals struggling with obesity is still increasing. An important aspect of obesity prevention relates to identifying individuals at risk at early stage, allowing for timely risk stratification and initiation of countermeasures. However, obesity is complex and multifactorial by nature, and one isolated (bio)marker is unlikely to enable an optimal risk stratification and prognosis for the individual; rather, a combined set is required. Such a multicomponent interpretation would integrate biomarkers from various domains, such as classical markers (eg, anthropometrics, blood lipids), multiomics (eg, genetics, proteomics, metabolomics), lifestyle and behavioural attributes (eg, diet, physical activity, sleep patterns), psychological traits (mental health status such as depression) and additional host factors (eg, gut microbiota diversity), also by means of advanced interpretation tools such as machine learning. In this paper, we will present a protocol that will be employed for a scoping review that attempts to summarise and map the state-of-the-art in the area of multicomponent (bio)markers related to obesity, focusing on the usability and effectiveness of such biomarkers.

PubMed, Scopus, CINAHL and Embase databases will be searched using predefined key terms to identify peer-reviewed articles published in English until January 2024. Once downloaded into EndNote for deduplication, CADIMA will be employed to review and select abstracts and full-text articles in a two-step procedure, by two independent reviewers. Data extraction will then be carried out by several independent reviewers. Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews and Peer Review of Electronic Search Strategies guidelines will be followed. Combinations employing at least two biomarkers from different domains will be mapped and discussed.

Ethical approval is not required; data will rely on published articles. Findings will be published open access in an international peer-reviewed journal. This review will allow guiding future directions for research and public health strategies on obesity prevention, paving the way towards multicomponent interventions.