Wang Chengjing, Li Changqing
Heilongjiang University of Chinese Medicine, Harbin, China.
J Orthop Surg Res. 2025 Mar 12;20(1):265. doi: 10.1186/s13018-025-05644-z.
Proximal interphalangeal joint (PIPJ) fractures present significant therapeutic challenges in hand surgery. This systematic review evaluated the comparative efficacy of dynamic external fixation against traditional treatment modalities, integrating machine learning analysis to enhance outcome prediction and treatment selection.
We systematically reviewed 43 clinical studies published between January 2014 and January 2024, including 26 dynamic external fixations, 6 traditional internal fixations, and 11 static external fixations. Studies were included if they reported quantitative outcomes of PIPJ fracture treatment, had a minimum follow-up of 4 weeks, and included at least 20 patients. Case series with fewer than 5 patients and non-English publications without available translations were excluded. The analysis focused on four key outcomes: range of motion (ROM), recovery time, complication rates, and functional results. We developed a neural network model to predict treatment outcomes, achieving 89.7% accuracy (95% CI 87.3-92.1%). Methodological quality was assessed using the Newcastle-Ottawa Scale and Cochrane Risk of Bias tool.
Dynamic external fixation demonstrated superior outcomes across multiple domains. ROM analysis revealed a median of 86.12° (range: 70°-95°) for dynamic fixation compared to 72.30° (range: 56°-88°) for traditional approaches (mean difference: 13.82°, 95% CI 10.24-17.40°). Dynamic fixation significantly reduced recovery duration (9.68 weeks vs. 20.47 weeks, p < 0.001). Complication profiles favored dynamic fixation, with pin tract infection rates of 2.4% versus 3.8% for traditional fixation. Functional assessment using the Ishida scoring system showed favorable outcomes in the dynamic fixation group, with a mean score of 85.3 points and 78% of cases achieving scores above 80 points.
This comprehensive systematic review provides evidence supporting the efficacy of dynamic external fixation for PIPJ fracture treatment. The findings demonstrate improved functional outcomes, accelerated rehabilitation, and reduced complication rates. The integration of machine learning analysis shows promise for optimizing patient-specific treatment selection. Further validation through large-scale, multicenter randomized controlled trials with extended follow-up periods is warranted.
近端指间关节(PIPJ)骨折在手外科治疗中面临重大挑战。本系统评价评估了动力外固定与传统治疗方式相比的疗效,并结合机器学习分析以改善预后预测和治疗选择。
我们系统回顾了2014年1月至2024年1月发表的43项临床研究,包括26项动力外固定、6项传统内固定和11项静力外固定。如果研究报告了PIPJ骨折治疗的定量结果、至少随访4周且纳入至少20例患者,则纳入研究。排除患者少于5例的病例系列以及没有可用译文的非英文出版物。分析聚焦于四个关键结果:活动范围(ROM)、恢复时间、并发症发生率和功能结果。我们开发了一个神经网络模型来预测治疗结果,准确率达到89.7%(95%CI 87.3-92.1%)。使用纽卡斯尔-渥太华量表和Cochrane偏倚风险工具评估方法学质量。
动力外固定在多个领域显示出更好的结果。ROM分析显示,动力固定的中位数为86.12°(范围:70°-95°),而传统方法为72.30°(范围:56°-88°)(平均差异:13.82°,95%CI 10.24-17.40°)。动力固定显著缩短了恢复时间(9.68周对20.47周,p<0.001)。并发症情况有利于动力固定,针道感染率分别为2.4%和3.8%。使用石田评分系统进行的功能评估显示,动力固定组结果良好,平均得分为85.3分,78%的病例得分高于80分。
本全面的系统评价提供了支持动力外固定治疗PIPJ骨折疗效的证据。研究结果表明功能结果得到改善、康复加速且并发症发生率降低。机器学习分析的整合显示出优化个体化治疗选择的前景。有必要通过大规模、多中心随机对照试验并延长随访期进行进一步验证。