The effect of mobile application-based technology on post-stroke aphasia: a systematic review.

Background: Enhancing speech-language therapy remains the most effective strategy for improving post-stroke aphasia, However, conventional face-to-face interventions often lack the necessary therapeutic intensity. In recent years, mobile application-based speech-language therapy has emerged progressively, offering new opportunities for independent rehabilitation among aphasic patients. This review aims to evaluate the impact of mobile application-based interventions on post-stroke aphasic. Methods: By conducting a systematic search across five databases (PubMed, Web of Science, EMBASE, CINAHL, and Scopus), we identified and included studies that investigated the utilization of mobile application-based technologies (such as computers, iPads, etc.) for treating post-stroke aphasia. Results: This study included 15 research investigations, including 10 randomized controlled trials (RCTs), four self-controlled studies and one cross-over experimental design study. Among these, eight studies demonstrated the efficacy of mobile application-based therapy in enhancing overall language functionality for post-stroke aphasia patients, three studies highlighted its potential for improving communication skills, three studies observed its positive impact on spontaneous speech expression. Moreover, four studies indicated its effectiveness in enhancing naming abilities, two studies underscored the positive influence of mobile application-based interventions on the quality of life for individuals with aphasia. Six studies noted that speech improvement effects were maintained during the follow-up period. Conclusion: The results of this review demonstrate the potential of mobile application-based interventions for improving speech-language function in individuals with aphasia. However, further high-quality research is needed to establish their effects across different domains and to delve into the comparative advantages of various treatment approaches. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=405248.

A Comparison of Dynamic SPECT Coronary Flow Reserve with TIMI Frame Count in the Treatment of Non-Obstructive Epicardial Coronary Patients.

Background: Microvascular dysfunction in patients with non-obstructive epicardial coronary may aggravate patient's symptoms or lead to various clinical events. Objective: To investigate the correlation between dynamic single photon emission computed tomography (D-SPECT) derived coronary flow reserve (CFR) and TIMI frame count (TFC) in patients with non-obstructive epicardial coronary patients. Methods: Patients with suspected or known stable CAD who were recommended to undergo invasive coronary angiography were prospectively enrolled in this study. Those who had non-obstructive coronary received TIMI frame count (TFC) and D-SPECT. A cut-off value of >40 was defined as slow flow referred to TFC. Results: A total of 47 patients diagnosed with non-obstructive coronary were enrolled. The mean age of patients was 66.09 ± 8.36 years, and 46.8% were male. Dynamic SPECT derived coronary flow reserve (CFR) was significantly correlated with TIMI frame count in 3 epicardial coronary (LAD: r=-0.506, P = 0.0003; LCX: r= -0.532, P = 0.0001; RCA: r= -0.657, P < 0.0001). The sensitivity and specificity of CFR in identifying abnormal TIMI frame count < 40 was 100.0% and 57.6% in LAD, 62.5% and 87.0% in LCX, 83.9% and 75.0% in RCA, respectively. The optimal CFR cut-off values were 2.02, 2.47, and 1.96 among the three vessels. Conclusion: In patients with non-obstructive coronary, CFR derived from D-SPECT was strongly correlated with TFC. This study demonstrates that that CFR may be an alternative non-invasive method for identifying slow flow in non-obstructive coronary.

[Factors related to the poor coronary collateral circulation in patients with coronary artery disease].

OBJECTIVE: To explore the factors related to poor coronary collateral circulation (CCC) and the synergy effects among various factors in patients with coronary artery disease (CAD). METHODS: A total of 180 patients with coronary angiography confirmed CAD (at least one major coronary artery stenosis equal to or greater than 95%) were included in this study. Coronary collateral circulation was graded according to the Rentrop scoring system. There were in 54 patients with Rentrop 0 and 1 (poor CCC) and 126 patients with Rentrop 2 and 3 (good CCC). Clinical data including age, weight, gender, history of smoking, and factors that were known to influence the development of collateral s, such as hypertension, diabetes mellitus, fasting blood glucose (FBG), hemoglobin A1c (HbA1c), serum total cholesterol (TC), triglyceride (TG), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C) and estimate glomerular filtration rate(eGFR) levels were also documented. Multivariate logistic regression was performed to detect possible factors related to CCC. RESULTS: (1) FBG levels and the incidence of eGFR < 60 ml·min(-1)·1.73 m(-2) were significant higher in Rentrop 0 and 1 group than in Rentrop 2 and 3 group (P = 0.001, P = 0.034, respectively). (2) After adjusting for age, gender, smoking habits, hypertension, diabetes and dyslipidemia, FBG levels (OR = 1.374, P = 0.005) and eGFR levels (OR = 2.412, P = 0.013) remained as independent risk factors for CCC. (3) The ROC curve showed that the optimal cut-off point for FBG to predict poor CCC was 5.8 mmol/L. The area under the ROC curve was 0.656 (P = 0.001). (4) According to FBG and eGFR, patients were further divided into FBG ≥ 5.8 mmol/L and eGFR < 60 ml·min(-1)·1.73 m(-2) group (group A), FBG ≥ 5.8 mmol/L and eGFR ≥ 60 ml·min(-1)·1.73 m(-2) group (group B), FBG < 5.8 mmol/L and eGFR < 60 ml·min(-1)·1.73 m(-2) group (group C), and FBG<5.8mmol/L and eGFR ≥ 60 ml·min(-1)·1.73 m(-2) group (group D). The frequencies of poor CCC of the four groups were 51.7% (15/29) , 36.7% (18/49), 35.5% (11/31) and 12.7% (8/63) respectively (P < 0.001). After adjusting for age, gender, smoking habits, hypertension and dyslipidemia, the risk of poor CCC in group A, B and C patients were 7.494 (95%CI = 1.410-7.551, P = 0.001), 3.921 (95%CI = 1.061-6.910, P = 0.005) and 3.474 (95%CI = 0.160-4.477, P = 0.047) times higher than patients in group D. CONCLUSIONS: Our results show that higher FBG levels and lower eGFR are independent predictors of poor CCC in CAD patients. Higher FBG levels and lower eGFR evoke a synergistic effect on poor CCC in CAD patients.