Association of bradykinin receptor 2 (BDKRB2) variants with physical performance and muscle mass: Findings from the LACE sarcopenia trial.

INTRODUCTION: Understanding genetic contributors to sarcopenia (age-related loss of muscle strength and mass) is key to finding effective therapies. Variants of the bradykinin receptor 2 (BDKRB2) have been linked to athletic and muscle performance. The rs1799722-9 and rs5810761 T alleles have been shown to be overrepresented in endurance athletes, possibly due to increased transcriptional rates of the receptor. These variants have been rarely studied in older people or people with sarcopenia. METHODS: We performed a post hoc sub-study of the Leucine and ACE (LACE) inhibitor trial, which enrolled 145 participants aged ≥70 years with low grip strength and low gait speed. Participants' blood samples were genotyped for rs179972 using TaqMan and rs5810761 by amplification through Hotstar Taq. Genotypes were compared with outcomes of physical performance and body composition measures. RESULTS: Data from 136 individuals were included in the analysis. For rs1799722 the genotype frequency (TT: 17, CC: 48, CT: 71) remained in Hardy-Weinberg Equilibrium (HWE p = 0.248). There was no difference between the genotypes for six-Minute Walk Distance (6MWD) or Short Physical Performance Battery (SPPB). Men with the TT genotype had a significantly greater 6MWD than other genotypes (TT 400m vs CT 310m vs CC 314m, p = 0.027), and greater leg muscle mass (TT 17.59kg vs CT 15.04kg vs CC 15.65kg, p = 0.007). For rs5810761, the genotype frequency (-9-9: 31, +9+9: 43, -9+9: 60) remained in HWE (p = 0.269). The +9+9 genotype was associated with a significant change in SPPB score at 12 months (-9-9 0 vs -9+9 0 vs +9+9-1, p<0.001), suggesting an improvement. In men, the -9-9 genotype was associated with lower arm fat (-9-9 2.39kg vs -9+9 2.72kg vs +9+9 2.76kg, p = 0.019). CONCLUSION: In men, the rs1799722 TT genotype was associated with longer 6MWD and greater leg muscle mass, while the rs5810761 -9-9 genotype was associated with lower arm fat mass.

Patients' and Clinicians' Perceptions of the Clinical Utility of Predictive Risk Models for Chemotherapy-Related Symptom Management: Qualitative Exploration Using Focus Groups and Interviews.

BACKGROUND: Interest in the application of predictive risk models (PRMs) in health care to identify people most likely to experience disease and treatment-related complications is increasing. In cancer care, these techniques are focused primarily on the prediction of survival or life-threatening toxicities (eg, febrile neutropenia). Fewer studies focus on the use of PRMs for symptoms or supportive care needs. The application of PRMs to chemotherapy-related symptoms (CRS) would enable earlier identification and initiation of prompt, personalized, and tailored interventions. While some PRMs exist for CRS, few were translated into clinical practice, and human factors associated with their use were not reported. OBJECTIVE: We aim to explore patients' and clinicians' perspectives of the utility and real-world application of PRMs to improve the management of CRS. METHODS: Focus groups (N=10) and interviews (N=5) were conducted with patients (N=28) and clinicians (N=26) across 5 European countries. Interactions were audio-recorded, transcribed verbatim, and analyzed thematically. RESULTS: Both clinicians and patients recognized the value of having individualized risk predictions for CRS and appreciated how this type of information would facilitate the provision of tailored preventative treatments or supportive care interactions. However, cautious and skeptical attitudes toward the use of PRMs in clinical care were noted by both groups, particularly in relationship to the uncertainty regarding how the information would be generated. Visualization and presentation of PRM information in a usable and useful format for both patients and clinicians was identified as a challenge to their successful implementation in clinical care. CONCLUSIONS: Findings from this study provide information on clinicians' and patients' perspectives on the clinical use of PRMs for the management of CRS. These international perspectives are important because they provide insight into the risks and benefits of using PRMs to evaluate CRS. In addition, they highlight the need to find ways to more effectively present and use this information in clinical practice. Further research that explores the best ways to incorporate this type of information while maintaining the human side of care is warranted. TRIAL REGISTRATION: ClinicalTrials.gov NCT02356081; https://clinicaltrials.gov/study/NCT02356081.

Community antibiotic prescribing in patients with COVID-19 across three pandemic waves: a population-based study in Scotland, UK.

OBJECTIVES: This study aims to examine community antibiotic prescribing across a complete geographical area for people with a positive COVID-19 test across three pandemic waves, and to examine health and demographic factors associated with antibiotic prescribing. DESIGN: A population-based study using administrative data. SETTING: A complete geographical region within Scotland, UK. PARTICIPANTS: Residents of two National Health Service Scotland health boards with SARS-CoV-2 virus test results from 1 February 2020 to 31 March 2022 (n=184 954). Individuals with a positive test result (n=16 025) had data linked to prescription and hospital admission data ±28 days of the test, general practice data for high-risk comorbidities and demographic data. OUTCOME MEASURES: The associations between patient factors and the odds of antibiotic prescription in COVID-19 episodes across three pandemic waves from multivariate binary logistic regression. RESULTS: Data included 768 206 tests for 184 954 individuals, identifying 16 240 COVID-19 episodes involving 16 025 individuals. There were 3263 antibiotic prescriptions ±28 days for 2395 episodes. 35.6% of episodes had a prescription only before the test date, 52.3% of episodes after and 12.1% before and after. Antibiotic prescribing reduced over time: 20.4% of episodes in wave 1, 17.7% in wave 2 and 12.0% in wave 3. In multivariate logistic regression, being female (OR 1.31, 95% CI 1.19 to 1.45), older (OR 3.02, 95% CI 2.50 to 3.68 75+ vs <25 years), having a high-risk comorbidity (OR 1.45, 95% CI 1.31 to 1.61), a hospital admission ±28 days of an episode (OR 1.58, 95% CI 1.42 to 1.77) and health board region (OR 1.14, 95% CI 1.03 to 1.25, board B vs A) increased the odds of receiving an antibiotic. CONCLUSION: Community antibiotic prescriptions in COVID-19 episodes were uncommon in this population and likelihood was associated with patient factors. The reduction over pandemic waves may represent increased knowledge regarding COVID-19 treatment and/or evolving symptomatology.