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基于不同的脑震荡后症状表现模式识别和预测轻度创伤性脑损伤退伍军人亚群:一项潜在类别分析。

Identifying and Predicting Subgroups of Veterans With Mild Traumatic Brain Injury Based on Distinct Configurations of Postconcussive Symptom Endorsement: A Latent Class Analysis.

机构信息

Veteran Affairs Rocky Mountain Mental Illness Research, Education, and Clinical Center (MIRECC) for Suicide Prevention, Aurora, Colorado (Drs Kinney, Forster, Bahraini, and Brenner, Ms Schneider, and Messrs King and Yan); and Departments of Physical Medicine and Rehabilitation (Drs Kinney, Forster, Bahraini, and Brenner), Psychiatry (Drs Bahraini and Brenner), and Neurology (Dr Brenner), Anschutz Medical Campus, University of Colorado, Aurora.

出版信息

J Head Trauma Rehabil. 2024;39(4):247-257. doi: 10.1097/HTR.0000000000000890. Epub 2024 Jan 23.

Abstract

OBJECTIVE

To identify distinct subgroups of veterans with mild traumatic brain injury (mTBI) based on configurations of postconcussive symptom (PCS) endorsement, and to examine predictors of subgroup membership.

SETTING

Outpatient Veterans Health Administration (VHA).

PARTICIPANTS

Veterans with clinician-confirmed mTBI who completed the Neurobehavioral Symptom Inventory (NSI), determined using the Comprehensive Traumatic Brain Injury Evaluation database. Individuals who tended to overreport symptoms were excluded via an embedded symptom validity scale.

DESIGN

Retrospective cohort study leveraging national VHA clinical data from 2012 to 2020. Latent class analysis (LCA) with a split-sample cross-validation procedure was used to identify subgroups of veterans. Multinomial logistic regression was used to examine predictors of subgroup membership.

MAIN MEASURES

Latent classes identified using NSI items.

RESULTS

The study included 72 252 eligible veterans, who were primarily White (73%) and male (94%). The LCA supported 7 distinct subgroups of veterans with mTBI, characterized by diverging patterns of risk for specific PCS across vestibular (eg, dizziness), somatosensory (eg, headache), cognitive (eg, forgetfulness), and mood domains (eg, anxiety). The most prevalent subgroup was Global (20.7%), followed by Cognitive-Mood (16.3%), Headache-Cognitive-Mood (H-C-M; 16.3%), Headache-Mood (14.2%), Anxiety (13.8%), Headache-Sleep (10.3%), and Minimal (8.5%). The Global class was used as the reference class for multinomial logistic regression because it was distinguished from others based on elevated risk for PCS across all domains. Female (vs male), Black (vs White), and Hispanic veterans (vs non-Hispanic) were less likely to be members of most subgroups characterized by lesser PCS endorsement relative to the Global class (excluding Headache-Mood).

CONCLUSION

The 7 distinct groups identified in this study distill heterogenous patterns of PCS endorsement into clinically actionable phenotypes that can be used to tailor clinical management of veterans with mTBI. Findings reveal empirical support for potential racial, ethnic, and sex-based disparities in PCS among veterans, informing efforts aimed at promoting equitable recovery from mTBI in this population.

摘要

目的

根据脑震荡后症状(PCS)的表现模式,确定轻度创伤性脑损伤(mTBI)退伍军人的不同亚组,并研究亚组归属的预测因素。

背景

退伍军人健康管理局(VA)门诊。

参与者

使用综合性创伤性脑损伤评估数据库,完成神经行为症状量表(NSI),并经临床医生确认患有 mTBI 的退伍军人。通过嵌入式症状有效性量表排除了倾向于过度报告症状的个体。

设计

利用 2012 年至 2020 年全国退伍军人健康管理局临床数据进行回顾性队列研究。使用潜在类别分析(LCA)和样本分割交叉验证程序来确定退伍军人亚组。使用多项逻辑回归检验亚组归属的预测因素。

主要测量

使用 NSI 项目确定的潜在类别。

结果

研究纳入了 72252 名符合条件的退伍军人,其中主要为白人(73%)和男性(94%)。LCA 支持 mTBI 退伍军人有 7 个不同的亚组,这些亚组的特征是特定 PCS 的风险模式各不相同,分布于前庭(如头晕)、躯体感觉(如头痛)、认知(如健忘)和情绪领域(如焦虑)。最常见的亚组是总体组(20.7%),其次是认知情绪组(16.3%)、头痛认知情绪组(H-C-M;16.3%)、头痛情绪组(14.2%)、焦虑组(13.8%)、头痛睡眠组(10.3%)和最小组(8.5%)。由于总体组在所有领域的 PCS 风险均高于其他组,因此将其用作多项逻辑回归的参考组。女性(与男性相比)、黑人(与白人相比)和西班牙裔退伍军人(与非西班牙裔相比),与总体组相比,不太可能属于大多数以 PCS 发生率较低为特征的亚组(不包括头痛情绪组)。

结论

本研究确定的 7 个不同组将 PCS 的不同表现模式提炼为可用于定制 mTBI 退伍军人临床管理的临床可行表型。研究结果为退伍军人中 PCS 的潜在种族、民族和性别差异提供了实证支持,为促进该人群从 mTBI 中公平恢复的努力提供了信息。

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