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Background: Joint articular injection of mesenchymal stem cells (MSCs) has emerged as a novel treatment approach for osteoarthritis (OA). However, the effectiveness of MSCs derived from different sources in treating OA patients remains unclear. Therefore, this study aimed to explore the differences between the effectiveness and safety of different sources of MSCs. Materials and Methods: For inclusion consideration, we searched trial registries and published databases, including PubMed, Cochrane Library, Embase, and Web of Science databases. Revman (V5.3), STATA (V16.0), and R (V4.0) were utilized for conducting data analysis, while the Cochrane Risk of Bias Tool was employed for assessing the quality of the studies. We derived outcome measures at 6 and 12 months based on the duration of study follow-up, including visual analog scale (VAS) score, WOMAC score, WOMAC pain, WOMAC Functional Limitation, and WOMAC stiffness. The evaluation time for short-term effectiveness is set at 6 months, while 12 months is utilized as the longest follow-up time for most studies to assess long-term effectiveness. Results: The evaluation of literature quality showed that the included studies had excellent methodological quality. A meta-analysis revealed that different sources of MSCs improved knee function and pain more effectively among patients suffering from knee OA (KOA) than controls. The results of the network meta-analysis showed the following: short-term functional improvement (the indexes were evaluated after 6 months of follow-up) (WOMAC total score: bone marrow-derived MSC (BMMSC) vs. adipose-derived MSC (ADMSC) (mean difference (MD) = -20.12, 95% confidence interval (CI) -125.24 to 42.88), umbilical cord-derived MSC (UCMSC) (MD = -7.81, 95% CI -158.13 to 74.99); WOMAC stiffness: BMMSC vs. ADMSC (MD = -0.51, 95% CI -7.27 to 4.29), UCMSC (MD = -0.75, 95% CI -9.74 to 6.63); WOMAC functional limitation: BMMSC vs. ADMSC (MD = -12.22, 95% CI -35.05 to 18.86), UCMSC (MD = -9.31, 95% CI -44.26 to 35.27)). Long-term functional improvement (the indexes were evaluated after 12 months of follow-up) (WOMAC total: BMMSC vs. ADMSC (MD = -176.77, 95% CI -757.1 to 378.25), UCMSC (MD = -181.55, 95% CI -937.83 to 541.13); WOMAC stiffness: BMMSC vs. ADMSC (MD = -0.5, 95% CI -26.05 to 18.61), UCMSC (MD = -1.03, 95% CI -30.44 to 21.69); WOMAC functional limitation: BMMSC vs. ADMSC (MD = -5.18, 95% CI -316.72 to 177.1), UCMSC (MD = -8.33, 95% CI -358.78 to 218.76)). Short-term pain relief (the indexes were evaluated after 6 months of follow-up) (VAS score: UCMSC vs. BMMSC (MD = -10.92, 95% CI -31.79 to 12.03), ADMSC (MD = -14.02, 95% CI -36.01 to 9.81), PLMSC (MD = -17.09, 95% CI -46.31 to 13.17); WOMAC pain relief: BMMSC vs. ADMSC (MD = -11.42, 95% CI -39.52 to 11.77), UCMSC (MD = -6.73, 95% CI -47.36 to 29.15)). Long-term pain relief (the indexes were evaluated after 12 months of follow-up) (VAS score: BMMSC vs. UCMSC (MD = -4.33, 95% CI -36.81 to 27.08), ADMSC (MD = -11.43, 95% CI -37.5 to 13.42); WOMAC pain relief: UCMSC vs. ADMSC (MD = 0.23, 95% CI -37.87 to 38.11), BMMSC (MD = 5.89, 95% CI -25.39 to 51.41)). According to the GRADE scoring system, WOMAC, VAS, and AE scores were of low quality. Conclusion: Meta-analysis suggests MSCs can effectively treat KOA by improving pain and knee function compared to control groups. In terms of functional improvement in KOA patients, both short-term (6-month follow-up) and long-term (12-month follow-up) results indicated that while the differences between most treatments were not statistically significant, bone marrow-derived MSCs may have some advantages over other sources of MSCs. Additionally, BM-MSCs and UC-MSCs may offer certain benefits over ADMSCs in terms of pain relief for KOA patients, although the variances between most studies were not statistically significant. Therefore, this study suggests that BM-MSCs may present clinical advantages over other sources of MSCs.
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AIM: To develop a useful diabetic retinopathy (DR) screening tool for patients with type 2 diabetes mellitus (T2DM). METHODS: A DR prediction model based on the Logistic regression algorithm was established on the development dataset containing 778 samples (randomly assigned to the training dataset and the internal validation dataset at a ratio of 7:3). The generalization capability of the model was assessed using an external validation dataset containing 128 samples. The DR risk calculator was developed through WeChat Developer Tools using JavaScript, which was embedded in the WeChat Mini Program. RESULTS: The model revealed risk factors (duration of diabetes, diabetic nephropathy, and creatinine level) and protective factors (annual DR screening and hyperlipidemia) for DR. In the internal and external validation, the recall ratios of the model were 0.92 and 0.89, respectively, and the area under the curve values were 0.82 and 0.70, respectively. CONCLUSION: The DR screening tool integrates education, risk prediction, and medical advice function, which could help clinicians in conducting DR risk assessments and providing recommendations for ophthalmic referral to increase the DR screening rate among patients with T2DM.