AIMS: This study aims to assess the efficacy of resistance training in preventing sarcopenia among breast cancer patients undergoing chemotherapy.
METHODS: A systematic search was conducted across PubMed, EMBASE, Medline, the Cochrane Library, and CINAHL until May 5, 2023. Selected literature focused on the effects of resistance training on body fat, muscle mass, muscle strength, and physical performance in breast cancer patients undergoing chemotherapy. Cochrane Risk of Bias tool version 2.0 was employed for quality assessment, and data were analyzed using Comprehensive Meta-Analysis version 2.0.
RESULTS: Eleven randomized controlled trials (RCTs) showed that resistance training had a significant positive impact on reducing body fat (SMD = -0.250, 95% CI [-0.450, -0.050]), increasing lean body mass (SMD = 0.374, 95% CI [0.178, 0.571]), and enhancing handgrip strength at both the affected site (SMD = 0.326, 95% CI [0.108, 0.543]) and the nonaffected site (SMD = 0.276, 95% CI [0.059, 0.492]). Additionally, significant improvements were observed in leg press strength (SMD = 0.598, 95% CI [0.401, 0.796]) and overall physical performance (SMD = 0.671, 95% CI [0.419, 0.923]).
LINKING EVIDENCE TO ACTION: Resistance training is a recommended intervention for reducing body fat, increasing muscle mass, muscle strength, and enhancing physical performance in breast cancer patients undergoing chemotherapy. Ideal low-intensity resistance training programs span 8-24 weeks, with 20-to-90-min sessions 2-4 times weekly. Regimens generally entail 8-12 repetitions at 40%-90% of one-repetition maximum test, with free-weight resistance training targeting major muscle groups yielding substantial benefits. Further research should explore outcomes across different chemotherapy phases and investigate long-term resistance training effects for a comprehensive view.
METHODS: Twenty-two MED-EL CI recipients (aged 13-93 months) participated in this study. The acoustic CAEP (aCAEP) waveforms were elicited using four speech stimuli (/ba/, /m/, /g/, and /t/) presented at 65 dB SPL in a free-field condition. The electrical CAEP (eCAEP) responses were obtained by presenting electrical pulses through apical, medial, and basal electrodes. The aCAEP and eCAEP data (n = 28 ears) were analyzed using coefficient of variation (CV) and other appropriate statistics.
RESULTS: P1, N1, and P2 peaks were observed in most of the children (92.9% response rate). The CV values were smaller for the latency metric (13.6-34.2%) relative to the amplitude metric (51.3-92.4%), and the differences were statistically significant (p
MATERIALS AND METHODS: A total of 521 cranial MSCT datasets of Malaysian sub-adults (0-20 years old) consisting of Malay, Chinese, and Indian populations were analysed and constructed into three-dimensional (3D) cranial models using Mimics software version 21. Fourteen selected craniometric parameters were measured on the 3D models, adhering to the plane-to-plane protocol. All measurements were statistically analysed using discriminant function analysis.
RESULTS: Cranial measurements such as maximum cranial width, biasteronic width, and occipital chord showed significant differences among Malays, Chinese, and Indians. In addition, a high similarity of the measurements between Chinese and Malays compared to Indians and Malays and Chinese and Indians was demonstrated. The highest classification accuracy was obtained by the age group of 10-12 years old, with Indians achieving the highest accuracy (72.2%), followed by Chinese (71.8%) and Malays (58.3%). The accuracy percentages between the pooled-sex and male/female formulas were relatively similar.
CONCLUSIONS: This study demonstrated the presence of morphometric variations among the three different sub-adult populations in Malaysia using MSCT datasets.
METHODS: A sequential mixed method research design was used in this study. A validated questionnaire was distributed to undergraduate students of Medicine, Dentistry and Pharmacy programmes to collect their general views on LA. Focus group interviews with a total of 18 students were conducted to explore their perceptions in depth, followed by thematic analysis of the transcribed data.
RESULTS: Generally, the students were aware of their demographic data, utilisation of learning management system and academic performance data being collected by the university. They were agreeable for collection of those data which had direct association with their learning to be used for LA. However, they expressed concerns about the privacy, confidentiality, and security of the collected data. Three themes emerged from the interviews, i.e., self-regulated learning, evidence-based decision making and data management. The students perceived that LA could help them to monitor achievement of learning outcomes and provide support for individualised learning paths through recommendations of learning resources and learning motivation. They also opined that LA could help educators and institutions by providing feedback on teaching and learning methods, resource allocation and interventions to create conducive learning environment.
CONCLUSIONS: LA is a useful tool to support self-regulated learning, however, precautions should be exercised during implementation to ensure data privacy and security.