Heterogeneous trajectories of oral frailty and their determinants in older patients receiving dental implants: a longitudinal study.

IF 4.1 3区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Frontiers in Public Health Pub Date : 2026-10-05 eCollection Date: 2026-01-01 DOI:10.3389/fpubh.2026.1891290
Ying Zhang, Nan Lu, Mengyao Liang, Qiufeng Zhu
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引用次数: 0

Abstract

Objective: To describe distinct trajectory patterns of oral frailty after implant-supported prosthesis delivery in older patients and to identify associated factors.

Methods: This prospective longitudinal cohort study consecutively enrolled 211 older patients who completed implant-supported prosthesis delivery at Nantong Stomatological Hospital and Haoting Dental Clinic between January 1 and April 30, 2025. Oral frailty was assessed using the adapted seven-item version of the Oral Frailty Index-8 (OFI-8, 7-item version; score range 0-9) at baseline (T0, prosthesis delivery) and at 3, 6, 9, and 12 months post-delivery (T1-T4). Distinct trajectories were identified using latent class growth modeling (LCGM). Multivariable multinomial logistic regression was used to analyze factors associated with trajectory membership.

Results: Three distinct oral frailty trajectories were identified: (1) Rapid Improvement-Stable Pattern (Class 1, n = 90, 42.7%), characterized by a sharp decline in OFI-8 scores immediately after prosthesis delivery followed by sustained low levels; (2) Gradual Improvement-Plateau Pattern (Class 2, n = 74, 35.1%), showing a gradual decline followed by a plateau; and (3) Persistent High-Risk Pattern (Class 3, n = 47, 22.2%), with scores remaining elevated throughout the 12-month observation period. Multivariable multinomial logistic regression analysis revealed that age (aOR = 1.12, 95% CI: 1.04-1.21), number of medications (aOR = 1.25, 95% CI: 1.05-1.49), and number of missing teeth (aOR = 1.09, 95% CI: 1.02-1.16) were independently associated with membership in Class 3. Bootstrap validation supported the robustness of the model. None of these variables showed statistical significance in distinguishing Class 2 from Class 1.

Conclusion: Oral frailty trajectories in older patients with dental implants are heterogeneous. Older age, polypharmacy, and a greater number of missing teeth were independently associated with membership in the persistent high-risk trajectory, suggesting that these factors may help identify patients requiring prioritized follow-up.

接受种植牙的老年患者口腔脆弱及其决定因素的异质性轨迹:一项纵向研究。
目的:描述老年患者种植体移植后口腔虚弱的不同轨迹模式,并确定相关因素。方法:本前瞻性纵向队列研究连续纳入南通市口腔医院和浩亭牙科诊所于2025年1月1日至4月30日完成种植体支持的老年患者211例。在基线(T0,假体分娩)和分娩后3、6、9和12 个月(T1-T4)时,使用口腔虚弱指数-8 (OFI-8, 7项版本,评分范围0-9)的七项版本评估口腔虚弱。使用潜在类别增长模型(LCGM)确定了不同的轨迹。采用多变量多项逻辑回归分析轨迹隶属度的相关因素。结果:确定了三种不同的口腔虚弱轨迹:(1)快速改善-稳定模式(1类,n = 90,42.7%),其特征是在假体交付后立即出现OFI-8评分急剧下降,随后持续低水平;(2)渐进式改善-平台型(第2类,n = 74,35.1%),表现为先逐渐下降后进入平台期;(3)持续高危模式(Class 3, n = 47,22.2%),在12个月的观察期内评分一直处于升高状态。多变量多项式logistic回归分析显示,年龄(aOR = 1.12,95% CI: 1.04-1.21)、用药数量(aOR = 1.25,95% CI: 1.05-1.49)和缺牙数量(aOR = 1.09,95% CI: 1.02-1.16)与隶属于第3类独立相关。Bootstrap验证支持了模型的鲁棒性。这些变量在区分第2类和第1类方面均无统计学意义。结论:老年种植牙患者的口腔脆弱轨迹是不均匀的。年龄较大、服用多种药物和大量缺牙与持续高风险轨迹的成员独立相关,表明这些因素可能有助于确定需要优先随访的患者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Frontiers in Public Health
Frontiers in Public Health Medicine-Public Health, Environmental and Occupational Health
CiteScore
4.80
自引率
7.70%
发文量
4469
审稿时长
14 weeks
期刊介绍: Frontiers in Public Health is a multidisciplinary open-access journal which publishes rigorously peer-reviewed research and is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, clinicians, policy makers and the public worldwide. The journal aims at overcoming current fragmentation in research and publication, promoting consistency in pursuing relevant scientific themes, and supporting finding dissemination and translation into practice. Frontiers in Public Health is organized into Specialty Sections that cover different areas of research in the field. Please refer to the author guidelines for details on article types and the submission process.
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