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采用传统统计学和机器学习技术进行体积测量的成年颅骨成形术患者自体冷冻骨瓣吸收的危险因素分析

Risk Factor Analysis of Cryopreserved Autologous Bone Flap Resorption in Adult Patients Undergoing Cranioplasty with Volumetry Measurement Using Conventional Statistics and Machine-Learning Technique.

作者信息

Son Yohan, Chung Jaewoo

机构信息

Department of Neurosurgery, Dankook University Hospital, Cheonan, Korea.

Department of Neurosurgery, College of Medicine, Dankook University, Cheonan, Korea.

出版信息

J Korean Neurosurg Soc. 2024 Jan;67(1):103-114. doi: 10.3340/jkns.2023.0143. Epub 2023 Sep 15.

DOI:10.3340/jkns.2023.0143
PMID:37709548
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10788544/
Abstract

OBJECTIVE

Decompressive craniectomy (DC) with duroplasty is one of the common surgical treatments for life-threatening increased intracranial pressure (ICP). Once ICP is controlled, cranioplasty (CP) with reinsertion of the cryopreserved autologous bone flap or a synthetic implant is considered for protection and esthetics. Although with the risk of autologous bone flap resorption (BFR), cryopreserved autologous bone flap for CP is one of the important material due to its cost effectiveness. In this article, we performed conventional statistical analysis and the machine learning technique understand the risk factors for BFR.

METHODS

Patients aged >18 years who underwent autologous bone CP between January 2015 and December 2021 were reviewed. Demographic data, medical records, and volumetric measurements of the autologous bone flap volume from 94 patients were collected. BFR was defined with absolute quantitative method (BFR-A) and relative quantitative method (BFR%). Conventional statistical analysis and random forest with hyper-ensemble approach (RF with HEA) was performed. And overlapped partial dependence plots (PDP) were generated.

RESULTS

Conventional statistical analysis showed that only the initial autologous bone flap volume was statistically significant on BFR-A. RF with HEA showed that the initial autologous bone flap volume, interval between DC and CP, and bone quality were the factors with most contribution to BFR-A, while, trauma, bone quality, and initial autologous bone flap volume were the factors with most contribution to BFR%. Overlapped PDPs of the initial autologous bone flap volume on the BRF-A crossed at approximately 60 mL, and a relatively clear separation was found between the non-BFR and BFR groups. Therefore, the initial autologous bone flap of over 60 mL could be a possible risk factor for BFR.

CONCLUSION

From the present study, BFR in patients who underwent CP with autologous bone flap might be inevitable. However, the degree of BFR may differ from one to another. Therefore, considering artificial bone flaps as implants for patients with large DC could be reasonable. Still, the risk factors for BFR are not clearly understood. Therefore, chronological analysis and pathophysiologic studies are needed.

摘要

目的

带硬脑膜成形术的减压性颅骨切除术(DC)是治疗危及生命的颅内压(ICP)升高的常见手术方法之一。一旦ICP得到控制,为了保护和美观,会考虑采用重新植入冷冻保存的自体骨瓣或合成植入物的颅骨成形术(CP)。尽管存在自体骨瓣吸收(BFR)的风险,但由于其成本效益,冷冻保存的自体骨瓣仍是CP的重要材料之一。在本文中,我们进行了传统统计分析和机器学习技术,以了解BFR的危险因素。

方法

回顾了2015年1月至2021年12月期间接受自体骨CP的年龄>18岁的患者。收集了94例患者的人口统计学数据、病历以及自体骨瓣体积的容积测量数据。BFR采用绝对定量法(BFR-A)和相对定量法(BFR%)进行定义。进行了传统统计分析以及采用超集成方法的随机森林(RF与HEA)分析,并生成了重叠部分依赖性图(PDP)。

结果

传统统计分析表明,仅初始自体骨瓣体积对BFR-A具有统计学意义。RF与HEA显示,初始自体骨瓣体积、DC与CP之间的间隔以及骨质是对BFR-A贡献最大的因素,而创伤、骨质和初始自体骨瓣体积是对BFR%贡献最大的因素。BRF-A上初始自体骨瓣体积的重叠PDP在约60 mL处交叉,并且在非BFR组和BFR组之间发现了相对明显的数据分离。因此,初始自体骨瓣超过60 mL可能是BFR的一个潜在危险因素。

结论

从本研究来看,接受自体骨瓣CP的患者发生BFR可能不可避免。然而,BFR程度可能因人而异。因此,对于接受大型DC的患者,考虑使用人工骨瓣作为植入物可能是合理的。不过,BFR的危险因素仍未完全明确。因此,需要进行时间顺序分析和病理生理学研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a462/10788544/51ccc6f78326/jkns-2023-0143f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a462/10788544/a9a5eddaceb2/jkns-2023-0143f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a462/10788544/382059866351/jkns-2023-0143f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a462/10788544/51ccc6f78326/jkns-2023-0143f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a462/10788544/a9a5eddaceb2/jkns-2023-0143f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a462/10788544/382059866351/jkns-2023-0143f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a462/10788544/51ccc6f78326/jkns-2023-0143f3.jpg

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