[Analysis on status quo of outcomes and measurement instruments of randomized controlled trials of acupuncture for post-stroke dysphagia].

OBJECTIVE: To analyze the report status of outcomes and measurement instruments of randomized controlled trials (RCTs) of acupuncture for post-stroke dysphagia, so as to provide a basis for designing clinical trials and developing the core outcome set in acupuncture for post-stroke dysphagia. METHODS: RCTs of acupuncture for post-stroke dysphagia were searched in databases i.e. CNKI, SinoMed, Wanfang, PubMed, EMbase, Web of Science and clinical trial registries i.e. ClinicalTrials.gov and Chinese Clinical Trial Registry (ChiCTR), from January 1st, 2012 to October 30th, 2021. By literature screening and data extraction, outcomes and measurement instruments were summarized and analyzed. RESULTS: A total of 172 trials (including 165 RCTs and 7 ongoing trials registrations) were included, involving 91 outcomes. The outcomes could be classified into 7 domains according to functional attributes, namely clinical manifestation, physical and chemical examination, quality of life, TCM symptoms/syndromes, long-term prognosis, safety assessment and economic evaluation. It was found that there were various measurements instruments with large differences, inconsistent measurement time point and without discriminatively reporting primary or secondary outcomes. CONCLUSION: The status quo of outcomes and measurement instruments of RCTs of acupuncture for post-stroke dysphagia is not conducive to the summary and comparison of each trial's results. Thus, it is suggested to develop a core outcome set for acupuncture for post-stroke dysphagia to improve the normative and research quality of their clinical trial design.

Towards Enabling Binary Decomposition for Partial Multi-Label Learning.

Partial multi-label learning (PML) is an emerging weakly supervised learning framework, where each training example is associated with multiple candidate labels which are only partially valid. To learn the multi-label predictive model from PML training examples, most existing approaches work by identifying valid labels within candidate label set via label confidence estimation. In this paper, a novel strategy towards partial multi-label learning is proposed by enabling binary decomposition for handling PML training examples. Specifically, the widely used error-correcting output codes (ECOC) techniques are adapted to transform the PML learning problem into a number of binary learning problems, which refrains from using the error-prone procedure of estimating labeling confidence of individual candidate label. In the encoding phase, a ternary encoding scheme is utilized to balance the definiteness and adequacy of the derived binary training set. In the decoding phase, a loss weighted scheme is applied to consider the empirical performance and predictive margin of derived binary classifiers. Extensive comparative studies against state-of-the-art PML learning approaches clearly show the performance advantage of the proposed binary decomposition strategy for partial multi-label learning.

[Changes in health-related quality of life in incipient stroke survivors].

OBJECTIVE: To assess the long-term changes in quality of life of stroke patients. METHODS: A total of 467 stroke survivors were recruited for this study. The participants completed the 12-Item Short Form Health Survey (SF-12) at a three-month interval over two years. Multi-level modelling was performed to identify the trend of changes and associated demographic characteristics. RESULTS: The participants had (31.50 +/- 10.49) PCS and (51.92 +/- 10.03) MCS at the baseline survey. Overall, PCS and MCS scores increased over time, but MCS scores declined slightly 15 months later. Men had higher PCS scores than women. The multi-level model revealed similar trends of PCS changes in those with different gender and education. Older patients had slower changes in quality of life over time (beta9 = -0.013, P = 0.03) compared with their younger counterparts. The trends of MCS changes were similar among those with different age, gender and education. CONCLUSION: Support should be strengthened for female stroke survivors and those with older age and lower levels of education.

[Assessing quality of life of patients with stroke using EQ-5D and SF-12].

OBJECTIVE: To compare.the results of EQ-SD and SF-12 for assessing health-related quality of life in stroke patients. METHODS: EQ-5D and SF-12 were administered to 598 ischemic stroke patients through face-to-face interviews. Differences in PCS-12 and MCS-12 scores across different levels of EQ-5D dimensions were tested using analysis of variance (ANOVA). The EQ-5D index and visual analogue scale/score (VAS) scores of respondents were compared between those with higher than and lower than median SF-12 scores using student t-test. Pearson correlations between PCS-12 and EQ-5D scores were tested. RESULTS: PCS-12 and MCA-12 scores varied across different levels of EQ-5D dimensional scores, except for pain/discomfort. EQ-5D and VAS scores varied between those with high and low SF-12 scores. No significant differences in EQ-5D index and VAS scores were found in the EQ-5D indicated healthy respondents between those with high and low SF-12 scores (P>0.05). PCS-12 was positively correlated with EQ-5D index and VAS scores, with r=0.15 (P<0.001) and r=0.33 (P< 0.001), respectively. MCS-12 was also positively correlated with EQ-5D index and VAS score, with r=0.17 (P<0.001) and r = 0.13 (P<0.001), respectively. CONCLUSION: Both instruments are valid measurements for assessing quality of life. The SF-12 appeared to be more sensitive to differences in health status. EQ-5D is preferable if both quality of life assessment and health economics study are to be conducted.