METHODS AND RESULTS: A literature search was conducted on PubMed, EMBASE, Ovid, and Cochrane library databases for randomized controlled trials, published in English language between January 1980 and November 2020. Multicomponent integrated care defined as two or more quality improvement strategies targeting different domains (the healthcare system, healthcare providers, and patients) for one month or more. The study outcomes were all-cause and cardiovascular-related mortality, hospitalization, and emergency department visits. We pooled the risk ratio (RR) with 95% confidence interval (CI) for the association between multicomponent integrated care and study outcomes using the Mantel-Haenszel test. 74 trials (n = 93 278 patients with ACS) were eligible. The most common quality improvement strategies were team change (83.8%), patient education (62.2%), and facilitated patient-provider relay (54.1%). Compared with usual care, multicomponent integrated care was associated with reduced risks for all-cause mortality (RR 0.83, 95% CI 0.77-0.90; P
METHODS: Data from 133 participants from the Rapid Intervention with Glyceryl Trinitrate in Hypertensive Stroke-2 Trial trial were analysed. Measures included ICHV (using ABC/2) and ICV (XYZ/2) (by independent observers); ICHV, ICV and CPV (semiautomated segmentation, SAS); atrophy (intercaudate distance, ICD, Sylvian fissure ratio, SFR); midline shift; leukoaraiosis and cistern effacement (visual assessment). The effects of these measures on death at day 4 and poor functional outcome at day 90 (modified Rankin scale, mRS of >3) was assessed.
RESULTS: ICV was significantly different between XYZ and SAS: mean (SD) of 1357 (219) vs 1420 (196), mean difference (MD) 62 mL (p<0.001). There was no significant difference in ICHV between ABC/2 and SAS. There was very good agreement for ICV measured by SAS, CPV, ICD, SFR, leukoaraiosis and cistern score (all interclass correlations, n=10: interobserver 0.72-0.99, intraobserver 0.73-1.00). ICHV/ICV and ICHV/CPV were significantly associated with mRS at day 90, death at day 4 and acute neurological deterioration (all p<0.05), similar to ICHV. Midline shift and cistern effacement at baseline were associated with poor functional outcome but old infarcts, leukoaraiosis and brain atrophy were not.
CONCLUSIONS: Intracranial compartment measures and visual estimates are reproducible. ICHV adjusted for ICH and CPV could be useful to prognosticate in acute stroke. The presence of midline shift and cistern effacement may predict outcome but the mechanisms need validation in larger studies.
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.
METHODS: We used individual participant data (N = 39271, Mage = 70.67 (40-102), 58.86% female, Meducation = 8.43 years, Mfollow-up = 3.22 years) from 13 longitudinal ageing studies. A two-stage meta-analysis of Cox regression models examined the association between social connection markers with our primary outcomes.
RESULTS: We found associations between good social connections structure and quality and lower risk of incident mild cognitive impairment (MCI); between social structure and function and lower risk of incident dementia and mortality. Only in Asian cohorts, being married/in a relationship was associated with reduced risk of dementia, and having a confidante was associated with reduced risk of dementia and mortality.
DISCUSSION: Different aspects of social connections - structure, function, and quality - are associated with benefits for healthy aging internationally.
HIGHLIGHTS: Social connection structure (being married/in a relationship, weekly community group engagement, weekly family/friend interactions) and quality (never lonely) were associated with lower risk of incident MCI. Social connection structure (monthly/weekly friend/family interactions) and function (having a confidante) were associated with lower risk of incident dementia. Social connection structure (living with others, yearly/monthly/weekly community group engagement) and function (having a confidante) were associated with lower risk of mortality. Evidence from 13 longitudinal cohort studies of ageing indicates that social connections are important targets for reducing risk of incident MCI, incident dementia, and mortality. Only in Asian cohorts, being married/in a relationship was associated with reduced risk of dementia, and having a confidante was associated with reduced risk of dementia and mortality.
MATERIALS AND METHOD: This work uses two (private and public) datasets. The private dataset consists of 3807 magnetic resonance imaging (MRI) and computer tomography (CT) images belonging to two (normal and AD) classes. The second public (Kaggle AD) dataset contains 6400 MR images. The presented classification model comprises three fundamental phases: feature extraction using an exemplar hybrid feature extractor, neighborhood component analysis-based feature selection, and classification utilizing eight different classifiers. The novelty of this model is feature extraction. Vision transformers inspire this phase, and hence 16 exemplars are generated. Histogram-oriented gradients (HOG), local binary pattern (LBP) and local phase quantization (LPQ) feature extraction functions have been applied to each exemplar/patch and raw brain image. Finally, the created features are merged, and the best features are selected using neighborhood component analysis (NCA). These features are fed to eight classifiers to obtain highest classification performance using our proposed method. The presented image classification model uses exemplar histogram-based features; hence, it is called ExHiF.
RESULTS: We have developed the ExHiF model with a ten-fold cross-validation strategy using two (private and public) datasets with shallow classifiers. We have obtained 100% classification accuracy using cubic support vector machine (CSVM) and fine k nearest neighbor (FkNN) classifiers for both datasets.
CONCLUSIONS: Our developed model is ready to be validated with more datasets and has the potential to be employed in mental hospitals to assist neurologists in confirming their manual screening of AD using MRI/CT images.
METHODS: This study was carried out through a desk review of the secondary source of information covering the impact of COVID-19 in Malaysia particularly in the agri-food aspect, and a wide range of strategies and initiatives as the effective measures to overcome the crisis of this pandemic. Online desk research of the government published data and customer desk research were utilized to complete this study. Search engines such as Google Scholar and the statistical data from the official websites including the Department of Statistics Malaysia (DOSM) and the Food and Fertilizer Technology Center for the Asian and Pacific Region (FFTC-AP), were utilized. Keywords such as impact of COVID-19, pandemic, and agri-food supply chain were used to conduct the searches. The articles identified to be related to the study's objective were then downloaded and included in the study. Descriptive methods were used as the primary analysis technique following the descriptive analysis and visual data analysis in performing the sources obtained.
RESULTS: This devastating impact damages the lives by causing 4.3 million confirmed infections and more than 290,000 deaths. This disease presents an unprecedented challenge to the public health. The lockdown restriction under the movement control order (MCO), for more than of the world's population in the year 2020 to control the virus from spreading, has disrupted most of the economic sectors. The agriculture industry was seen as one of the essential industries and allowed to operate under strict standard operating procedures (SOP). Working under strict regulations came with a huge price paid for almost all industries.
CONCLUSION: This pandemic has affected the national agri-food availability and accessibility in Malaysia. This outbreak created a reflection of opportunity for sharing a more flexible approaches in handling emergencies on agricultural food production and supply chains. Therefore, the government should be ready with the roadmap and enforce the measures to control the pandemic without disrupting the agri-food supply chain in the near future.
METHODS: This cross-sectional study was conducted from June 2021 until April 2022, and SLE patients were recruited to complete the SLEQoL, LupusQoL and Short Form Health Survey (SF-36) in Malay language. Disease activity were recorded using the modified SLE Disease Activity Index (M- SLEDAI) and British Isles Lupus Assessment Group 2004 (BILAG-2004) index. Presence of organ damage was determined using the SLICC Damage index. Cronbach's alpha was calculated to determine internal consistency while exploratory factor analysis was done to determine the construct validity. Concurrent validity was evaluated using correlation with SF-36. Multiple linear regression analysis was deployed to determine the factors affecting each domain of SLEQoL and LupusQoL.
RESULTS: A total of 125 subjects were recruited. The Cronbach's α value for the Malay-SLEQoL (M-SLEQoL) and Malay-LupusQOL (M-LupusQoL) was 0.890 and 0.944 respectively. Exploratory factor analysis found formation of similar number of components with the original version of questionnaires and all items have good factor loading of >0.4. Both instruments also had good concurrent validity with SF-36. M-SLEQoL had good correlations with BILAG-2004 and M-SLEDAI scores. Musculoskeletal (MSK) involvement was independently associated with lower M-SLEQoL in physical function, activity and symptom domains. Meanwhile, MSK and NPSLE were associated with fatigue in M-LupusQoL.
CONCLUSION: Both M-SLEQoL and M-LupusQoL are reliable and valid as disease -specific QoL instruments for Malaysian patients. The M-Lupus QoL has better discriminative validity compared to the M-SLEQoL. SLE patients with MSK involvement are at risk of poor QoL in multiple domains including physical function, activity, symptoms and fatigue.