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Background: Hand dysfunction is one of the main symptoms of stroke patients, but there is still a lack of accurate hand function assessment systems. This study focused on the application of the multi-dimensional intelligent visual quantitative assessment system (MDIVQAS) in the rehabilitation assessment of hand function in stroke patients and evaluate hand function rehabilitation in stroke patients. Methods: Eighty-two patients with stroke and unilateral hand dysfunction were evaluated by MDIVQAS. Cronbach’s Alpha coefficient was used to assess the internal consistency of MDIVQAS; the F-test is used to assess the differences in MDIVQAS for multiple repeated measures. Spearman’s analysis was used to identify correlations of MDIVQAS with other assessment systems. T-tests were used to identify differences in outcomes assessed with MDIVQAS in patients before and after treatment. p< 0.05 were considered significant. Results: (1) Cronbach’s Alpha coefficient of MDIVQAS in evaluating hand’s function >0.9. (2) There was no significant difference between the other repeated measurements, except for thumb rotation in MDIVQAS. (3) MDIVQAS had a significant correlation with other assessment systems (r > 0.5, p < 0.01). (4) There were significant differences in the evaluation of hand function in patients before and after treatment using MDIVQAS. Conclusion: The MDIVQAS system has good reliability and validity in the evaluation of stroke hand function, and it can also better evaluate the treatment effect.

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Aberrant protein glycosylation is an active pathological alteration related to the progression of cancers. The speed of progression varies among individuals, increasing the difficulties of prognosis assessment. Hence, evaluating variation in glycosylation using patients themselves as their own controls is a potential way to reduce the impact of individual differences on progression monitoring. Here, following a longitudinal follow-up study involving 125 lung cancer (LC) patients with progressive disease, we isolated disease-specific IgG from serum using polyacrylamide gel electrophoresis, obtained IgG glycoform ratios using mass spectrometry, and then set a fold-change cutoff of 1.5 to utilize the intra-individual variation in IgG glycosylation to monitor PD. We found that the serial monitoring of 15 types of glycoform ratios provided an effective way for monitoring LC progression. Over 1.5-fold changes in glycoform ratios relative to the first observed value were detected in 117 of 125 LC patients (93.6%). Our established method predicted LC progression 55.8 (IQR 31.1–90.1) weeks earlier than imaging examination did. In summary, intra-individual variation in IgG glycoform ratios is useful to monitor LC progression, expanding our knowledge about the relationship between IgG glycosylation and cancer prognosis. The raw data files are available via the ProteomeXchange Consortium with the identifier PXD037541.