METHODS: One hundred and seven older adults with mild to moderate depressive symptoms were recruited from Ya'an city. Fifty-five participants were cluster randomized to combined music and Tai Chi group for three months, while the other fifty-two individuals were randomized to the control group that entailed routine health education delivered monthly by community nurses. The primary outcome of depressive symptoms was measured with the Geriatric Depression Scale (GDS) at baseline and monthly for three months.
RESULTS: At three-month follow-up, a statistically significant improvement in depressive symptoms was found in the intervention group compared with control group (F(3,315) = 69.661, P < 0.001). Following adjustments for socio-demographic data, the true effect of intervention on depressive symptoms was significant (F = 41.725, P < 0.01, ηp2 = 0.574).
CONCLUSIONS: Combined music and Tai Chi reduced depressive symptoms among community-dwelling older persons. This represents an economically viable solution to the management of depression in highly populous developing nations.
PURPOSE: To demonstrate automatic detection of BM on three MRI datasets using a deep learning-based approach. To improve the performance of the network is iteratively co-trained with datasets from different domains. A systematic approach is proposed to prevent catastrophic forgetting during co-training.
STUDY TYPE: Retrospective.
POPULATION: A total of 156 patients (105 ground truth and 51 pseudo labels) with 1502 BM (BrainMetShare); 121 patients with 722 BM (local); 400 patients with 447 primary gliomas (BrATS). Training/pseudo labels/validation data were distributed 84/51/21 (BrainMetShare). Training/validation data were split: 121/23 (local) and 375/25 (BrATS).
FIELD STRENGTH/SEQUENCE: A 5 T and 3 T/T1 spin-echo postcontrast (T1-gradient echo) (BrainMetShare), 3 T/T1 magnetization prepared rapid acquisition gradient echo postcontrast (T1-MPRAGE) (local), 0.5 T, 1 T, and 1.16 T/T1-weighted-fluid-attenuated inversion recovery (T1-FLAIR) (BrATS).
ASSESSMENT: The ground truth was manually segmented by two (BrainMetShare) and four (BrATS) radiologists and manually annotated by one (local) radiologist. Confidence and volume based domain adaptation (CAVEAT) method of co-training the three datasets on a 3D nonlocal convolutional neural network (CNN) architecture was implemented to detect BM.
STATISTICAL TESTS: The performance was evaluated using sensitivity and false positive rates per patient (FP/patient) and free receiver operating characteristic (FROC) analysis at seven predefined (1/8, 1/4, 1/2, 1, 2, 4, and 8) FPs per scan.
RESULTS: The sensitivity and FP/patient from a held-out set registered 0.811 at 2.952 FP/patient (BrainMetShare), 0.74 at 3.130 (local), and 0.723 at 2.240 (BrATS) using the CAVEAT approach with lesions as small as 1 mm being detected.
DATA CONCLUSION: Improved sensitivities at lower FP can be achieved by co-training datasets via the CAVEAT paradigm to address the problem of data sparsity.
LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 2.
STUDY DESIGN: A scoping review design was used.
METHODS: A systematic literature search was conducted using the Medline, CINAHL, AMED, Ageline, PsycINFO, Web of Sciences, Scopus, Thai-Journal Citation Index, MyCite and trial registries databases.
RESULTS: Thirty-seven studies and six study protocols were included, from Thailand, Malaysia, Singapore, Vietnam, Indonesia and the Philippines. One-sixth of the studies involved interventions, while the remainder were observational studies. The observational studies mainly determined the falls risk factors. The intervention studies comprised multifactorial interventions and single interventions such as exercises, educational materials and visual correction. Many of the studies replicated international studies and may not have taken into account features unique to Southeast Asia.
CONCLUSION: Our review has revealed studies evaluating falls and management of falls in the Southeast Asian context. More research is required from all Southeast Asian countries to prepare for the future challenges of managing falls as the population ages.
METHODS: MEDLINE, EMBASE, PubMed, Web of Science, and ProQuest were searched. Studies were included if participants were more than 60 years, were set within the community or within long-term care and diagnosis was based on a postural drop in systolic blood pressure (BP) ≥20 mmHg or diastolic BP ≥10 mmHg. Data were extracted independently by two reviewers. Random and quality effects models were used for pooled analysis.
RESULTS: Of 23,090 identified records, 20 studies were included for community-dwelling older people (n = 24,967) and six were included for older people in long-term settings (n = 2,694). There was substantial variation in methods used to identify OH with differing supine rest duration, frequency and timing of standing BP, measurement device, use of standing and tilt-tables and interpretation of the diagnostic drop in BP. The pooled prevalence of OH in community-dwelling older people was 22.2% (95% CI = 17, 28) and 23.9% (95% CI = 18.2, 30.1) in long-term settings. There was significant heterogeneity in both pooled results (I2 > 90%).
CONCLUSIONS: OH is very common, affecting one in five community-dwelling older people and almost one in four older people in long-term care. There is great variability in methods used to identify OH.