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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.
This study aimed to develop atorvastatin-loaded emulgel and nano-emulgel dosage forms and investigate their efficiency on surgical wound healing and reducing post-operative pain. This double-blind randomized clinical trial was conducted in a surgical ward of a tertiary care hospital affiliated with university of medical sciences. The eligible patients were adults aged 18 years or older who were undergoing laparotomy. The participants were randomized in a 1:1:1 ratio to one of three following groups of atorvastatin-loaded emulgel 1% (n = 20), atorvastatin-loaded nano-emulgel 1% (n = 20), and placebo emulgel (n = 20) twice a day for 14 days. The primary outcome was the Redness, Edema, Ecchymosis, Discharge, and Approximation (REEDA) scores to determine the rate of wound healing. The Visual Analogue Scale (VAS) and quality of life were the secondary outcomes of this study. A total of 241 patients assessed for eligibility; of them, 60 patients completed the study and considered for final evaluation. A significant decrease in REEDA score was observed on Days 7 (63%) and 14 (93%) of treatment with atorvastatin nano-emulgel (p-value < 0.001). A significant decrease of 57% and 89% in REEDA score was reported at Days 7 and 14, respectively, in atorvastatin the emulgel group (p-value < 0.001). Reduction in pain VAS in the atorvastatin nano-emulgel was also recorded at Days 7 and 14 of the intervention. The results of the present study suggested that both topical atorvastatin-loaded emulgel and nano-emulgel 1% were effective in acceleration of wound healing and alleviation of pain of laparotomy surgical wounds, without causing intolerable side effects.
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