Baker Nawfal Jawad

Background: Poor appetite, a major contributor to malnutrition, is highly prevalent among older adults and associated with adverse clinical outcomes. Nevertheless, there are currently no widely accepted or consistently effective pharmacological treatments targeting appetite that are routinely recommended alongside nutritional interventions. Medical cannabis has been proposed as a potential appetite stimulant in older adults with poor appetite through modulation of appetite-regulating hormones such as glucagon-like peptide-1 (GLP-1) and total ghrelin, but the evidence remains limited. Aims: To investigate the effects of Sativex^® versus placebo on postprandial GLP-1 and total ghrelin concentrations following a single dose (8.1 mg Δ9-tetrahydrocannabinol (THC) and 7.5 mg cannabidiol (CBD)), and on subjective appetite following two separated doses, in older adults with poor appetite, and to investigate the associations between plasma concentrations of THC and its metabolites on these outcomes. Methods: This protocolized secondary analysis included 17 participants (≥65 years) with poor appetite from a double-blind, randomized, placebo-controlled crossover trial. Participants received Sativex^® or placebo on two separate study days. GLP-1 and total ghrelin were measured following one dose of Sativex^®/placebo and a standardized breakfast, and subjective appetite was assessed repeatedly using visual analog scales throughout the administration of two separate doses of Sativex^®/placebo, the consumption of a standardized breakfast, and an ad libitum lunch meal. Effects/associations were analyzed using linear mixed-effects models. Results: Compared with placebo, Sativex^® produced an estimated 2.38 pmol/L (95% confidence intervals (CI): −0.71 to 5.46; Bonferroni-corrected p = 0.274) reduction in mean GLP-1 and time-dependent changes in mean total ghrelin (Bonferroni-corrected p = 0.054). Compared with placebo, Sativex^® produced minimal changes in separate subjective appetite sensations (all Bonferroni-corrected p = 1.00) and a slightly lower combined appetite score (−5.2 mm; 95% CI: −24.4 to 4.0; Bonferroni-corrected p = 1.00). Increased plasma concentrations of THC and metabolites were associated with reduced estimates of mean GLP-1 concentrations and subjective appetite, as well as increased mean total ghrelin concentrations. However, no statistically significant differences were detected for any analyses, and estimates had wide CIs, warranting cautious interpretation. Conclusions: In conclusion, no statistically significant differences were detected between Sativex^® and placebo in postprandial GLP-1, total ghrelin, or subjective appetite over time in older adults with poor appetite. Similarly, no statistically significant associations were observed between plasma concentrations of THC and its metabolites and GLP-1, total ghrelin, or subjective appetite. Trial registration: ClinicalTrials.gov ID: NCT05503147; EudraCT nr.: 2021-002318-15.

Background: Poor appetite, a major contributor to malnutrition, is highly prevalent among older adults and associated with adverse clinical outcomes. Nevertheless, no effective appetite targeted treatments are currently part of clinical practice alongside nutritional interventions. Medical cannabis has been proposed as a potential appetite stimulant in older adults with poor appetite through modulation of appetite regulating hormones such as glucagon like peptide 1 (GLP 1) and ghrelin, but the evidence remains limited. Aims: To investigate the associations between a fixed dose of Sativex® (8.1 mg Δ9-tetrahydrocannabinol (THC) and 7.5 mg cannabidiol (CBD)) versus placebo and postprandial GLP 1, total ghrelin concentrations as well as subjective appetite in older adults with poor appetite, and the associations between THC and its metabolites on these outcomes. Methods: This protocolized secondary analysis included 17 participants (≥65 years) with poor appetite from a double blinded, randomized, placebo controlled crossover trial. Participants received Sativex® or placebo on two separate study days. GLP 1 and total ghrelin were measured following a standardized breakfast, and subjective appetite was assessed repeatedly using visual analogue scales. Associations were analyzed using linear mixed effects models. Results: Sativex® administration compared with placebo was associated with an estimated 2.38 pmol/L (95% confidence intervals (CI) -0.71−5.46; p = 0.137) reduction in mean GLP 1 concentration, time dependent changes in mean total ghrelin (p = 0.054), and overall estimates of reduced subjective appetite. Increased THC and metabolite concentrations were associated with reduced estimates of mean GLP-1 concentrations and subjective appetite, and an increased mean total ghrelin. However, no clinically relevant or statistically significant associations were observed, and estimates had wide CIs, warranting cautious interpretation. Conclusions: In conclusion, the administration of medical cannabis, formulated as Sativex®, did not differ from placebo with respect to postprandial GLP-1, total ghrelin as well as subjective appetite over time in older adults with poor appetite. The same was found for associations between THC and its metabolites, and GLP-1, total-ghrelin, and subjective appetite.

Background: Accurate health assessments in the Emergency Department are critical for guiding treatment decisions. However, these assessments are often heavily influenced by chronological age, which does not reflect the variability in physiological health among patients, particularly older adults. Biological age estimation based on biomarkers may better indicate a patient’s true health status. However, its use in acute care Emergency Department settings is not established. This study introduces the concepts and corresponding estimates of Acute Biological Age and Acute Difference in Age in the Emergency Department setting and assesses their association with in-hospital care needs following acute conditions. Methods: Using data from a prospective study of 6071 Emergency Department patients aged over 18, Acute Biological Age was calculated by converting 30-day mortality risk estimates from a machine-learning model incorporating fifteen biomarkers into biological age expressed in years. Acute Difference in Age was derived from the difference between Acute Biological Age and chronological age. Logistic regressions were used to analyze associations between these estimates and twenty predefined events requiring in-hospital care, with a detailed analysis conducted on nine specific events. Results: Here, we show that Acute Biological Age and Acute Difference in Age are significantly associated with hospitalization risk. Each additional year of Acute Biological Age increases the odds of requiring intravenous treatments, in-hospital care, extended stays, and admission to intensive care, with odds ratios ranging from 1.03 to 1.05. Conclusions: Acute Biological Age and Acute Difference in Age are promising metrics to identify high-risk Emergency Department patients and may improve resource allocation in acute care settings.

Purpose: To investigate the association between glucagon-like peptide-1 receptor agonist (GLP-1RA) use and nonarteritic anterior ischaemic optic neuropathy (NAION) in type 2 diabetes, examining treatment recency and cumulative duration. Methods: This nationwide registry-based nested case-control study utilised Danish health registries (1996–2023). Among 201,776 metformin-treated adults initiating second-line antihyperglycaemic therapy, 123 incident NAION cases were matched to 4,920 controls by birth year and sex (incidence-density sampling). Conditional logistic regression estimated adjusted hazard rate ratios (HRs) for GLP-1RA exposure by recency (current 0–90 days; recent 91–365 days) and cumulative duration, adjusting for socioeconomic factors, hypertension, hypercholesterolaemia, sleep apnoea, and diabetes duration. Results: GLP-1RA use occurred in 63/123 cases (51.2%) and 1,688/4,920 controls (34.3%). Ever use was associated with a higher NAION rate than other second-line therapies (HR 2.13, 95% CI 1.43–3.18). Current use was associated with elevated rates (HR 2.28, 95% CI 1.49–3.48), whereas the estimate for recent use was imprecise (HR 1.69, 95% CI 0.88–3.25). By cumulative duration, no clear evidence of an increase was seen within 0–½ years (HR 0.80, 95% CI 0.32–2.05), and rates were highest at ½–1 year (HR 3.63, 95% CI 2.06–6.40) and 1–1½ years (HR 3.52, 95% CI 1.73–7.17). Findings were consistent after HbA1c adjustment and in a new-user analysis. Conclusion: GLP-1RA use is associated with a higher NAION rate in type 2 diabetes. This association appears time-dependent, being most pronounced during current treatment and peaking after 6–18 months of cumulative exposure.

Background: Predicting mortality in emergency departments (EDs) using machine learning models presents challenges, particularly in balancing simplicity with performance. This study aims to develop models that are both simple and effective for predicting short- and long-term mortality in ED patients. Our approach uses a minimal set of variables derived from one single blood sample obtained at admission. Methods: Data from three cohorts at two large Danish university hospitals were analyzed, including one retrospective and two prospective cohorts where prognostic models were applied to predict individual mortality risk, spanning the years 2013–2022. Routine biochemistry analyzed in blood samples collected at admission was the primary data source for the prediction models. The outcomes were mortality at 10, 30, 90, and 365 days after admission to the ED. The models were developed using Light Gradient Boosting Machines. The evaluation of mortality predictions involved metrics such as Area Under the Receiver Operating Characteristic Curve (AUC), sensitivity, specificity, negative predictive values, positive predictive values, and Matthews correlation coefficient (MCC). Results: A total of 43,648 unique patients with 65,484 admissions were analyzed. The models showed high accuracy, with very good to excellent AUC values between 0.87 and 0.93 across different time intervals. Conclusions: This study demonstrates that a single assessment of routine clinical biochemistry upon admission can serve as a powerful predictor for both short-term and long-term mortality in ED admissions.