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Fractures, Bone

Fractures, Bone: explore 3 source-linked works published from 2025 to 2026, with original documents and citations.

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Effect of photobiomodulation on pain relief and functional improvement in fractures: a systematic review and meta-analysis.

INTRODUCTION: Fractures, the most common type of trauma, can cause considerable distress to patients. Pain can not only affect the comfort of fracture patients but also delay their participation in rehabilitation training. Photobiomodulation (PBM) has been associated with pain reduction and the promotion of tissue healing. This systematic review and meta-analysis aimed to evaluate the efficacy of PBM in reducing pain and promoting rehabilitation in patients with fractures. METHODS: This study was registered on PROSPERO (CRD42024591373). We systematically searched PubMed, EMBASE, the Cochrane Library and Web of Science for RCTs that investigated PBM in fractures as of August 2025. The primary outcome was the pain score. The secondary outcomes included functional and healing. RESULT: Finally, 12 and 9 studies were ultimately included in the systematic review and meta-analysis, respectively. The pooled analysis showed that the one-week pain score was lower in the PBM group than in the placebo group (MD -0.74, 95% CI -1.00, -0.47, p&#x2009;<&#x2009;0.0001, I2 = 0%). Subgroup analysis showed that the difference between the two groups was statistically significant regardless of fracture site or acupoint irradiation. Changes in pain scores were statistically significant in both groups at different wavelength combinations. The improvement in grip strength at 4&#x2009;weeks was significantly greater in PBM than in placebo (MD 5.03, 95% CI 4.29, 5.78; p&#x2009;<&#x2009;0.0001; I2 = 0%). There were no significant differences in pain and functional scores at 4-26&#x2009;weeks. Bone healing did not show differences between the two groups. No side effects reported. CONCLUSION: PBM appears to relieve short-term pain in fractures and improve grip strength in patients with upper limb fractures, but does not show significant long-term benefits. Evidence for mandibular functional recovery and bone healing remains inconsistent. Future studies should determine therapeutic parameters and their impact on bone healing and long-term functional outcomes across fracture types.

Humans

Atopic dermatitis and the risk of osteoporosis and fractures: a meta-analysis of cohort studies.

BACKGROUND: This meta-analysis aims to evaluate the risk of osteoporosis and fractures in patients with atopic dermatitis (AD) by synthesizing data from cohort studies. We also provide a comprehensive analysis of fracture risks across different severities of AD and anatomical sites. METHODS: Following the PRISMA 2020 guidelines, a systematic search was conducted in PubMed, Embase, and the Cochrane Library up to May 30, 2025. Studies that investigated the relationship between AD and osteoporosis or fractures were included in the analysis. Data extraction and screening were performed independently by two reviewers. Study quality was assessed using the Newcastle-Ottawa Scale (NOS). A random-effects meta-analysis was applied, alongside sensitivity and subgroup analyses. Publication bias was evaluated using funnel plots and Egger's test. RESULTS: Ten cohort studies, involving 368 to over 2 million AD patients, were included. NOS scores ranged from 7 to 8, indicating generally high study quality. The pooled analysis revealed a 56% increased risk of osteoporosis (OR = 1.56, 95% CI: 1.14-2.13; I2&#xa0;=&#xa0;99.9%, p&#x2009;<&#x2009;0.0001) and an 8% increased risk of all-cause fractures (OR = 1.08, 95% CI: 1.05-1.10; I2&#xa0;=&#xa0;82.1%, p&#x2009;<&#x2009;0.0001) in AD patients. Subgroup analyses demonstrated a progressive increase in fracture risk with the severity of AD. Specific risks were significantly higher for vertebral fractures (OR = 1.14, 95% CI: 1.08-1.20; I2&#xa0;=&#xa0;67.3%, p&#x2009;=&#x2009;0.009) and lower limb fractures (OR = 1.11, 95% CI: 1.08-1.13; I2&#xa0;=&#xa0;65.0%, p&#x2009;=&#x2009;0.014). Sensitivity analyses confirmed the robustness of these findings, and no significant publication bias was detected (p&#x2009;=&#x2009;0.316). CONCLUSION: AD is associated with an increased risk of osteoporosis and fractures, particularly among patients with severe AD and those experiencing vertebral or lower limb fractures. These findings highlight the importance of targeted bone health monitoring in the clinical management of AD patients.Registration: (PROSPERO: CRD420251066550).

Humans

Enhanced fracture detection on radiographs with AI assistance for clinicians: a systematic review and meta-analysis.

BACKGROUND: Emergency radiographic interpretation for fractures is prone to missed or misdiagnoses. Artificial intelligence (AI) is expected to become a powerful tool to assist clinicians in fracture detection. PURPOSE: A systematic review and meta-analysis was performed to assess whether AI improves clinicians' ability to detect fractures on radiographs. MATERIALS AND METHODS: A literature search was conducted in PubMed, Web of Science, and Cochrane Library for studies published between January 1, 2010, and October 10, 2025. A meta-analysis of diagnostic accuracy studies was performed using a Summary Receiver Operating Characteristic (SROC) curve. The quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Subgroup analysis and meta-regression were conducted to explore potential sources of heterogeneity. RESULTS: A total of 26 studies were included . The pooled sensitivity of clinicians increased from 77% (95% CI: 72-81) to 87% (95% CI: 83-90) with AI assistance, while the pooled specificity improved from 88% (95% CI: 85-90) to 92% (95% CI: 89-94). The corresponding AUC values were 0.90 (95% CI: 0.87-0.92) before and 0.95 (95% CI: 0.93-0.97) after AI assistance. Eight studies were rated as high risk of bias. Subgroup analysis and meta-regression identified potential sources of heterogeneity, including fracture location, AI model type, high risk of bias, and reference standards. CONCLUSION: AI assistance significantly improves clinicians' diagnostic performance in detecting fractures on radiographs for extremity and trunk fractures.

Humans
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