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R-cVR,一种用于急性头晕和眩晕鉴别诊断的两步床旁算法。

R-cVR, a two-step bedside algorithm for the differential diagnosis of acute dizziness and vertigo.

作者信息

Li Mingxia, Tan Bichun, Wu Qingnan, Liu Shuangxi, Zhou Jun, Xiao Liqian, Nie Meng, Ming Fengyu, Zhou Jing, Luo Xing, Yin Junjie

机构信息

Department of Neurology, Hunan University of Medicine General Hospital, 418000, Hunan, PR China.

Department of Neurology, People's Hospital of Mayang Miao Autonomous County, Hunan, 419400, PR China.

出版信息

Heliyon. 2024 Sep 26;10(19):e38532. doi: 10.1016/j.heliyon.2024.e38532. eCollection 2024 Oct 15.

Abstract

BACKGROUND

The ability to quickly and accurately differentiate between peripheral and central dizziness or vertigo is vital. We developed the R-cVR algorithm for the early identification of central-type dizziness or vertigo.

METHODS

In this single-center, retrospective cohort study, we assessed patients with isolated dizziness or vertigo between December 10, 2023, and February 28, 2024. Classification into central or peripheral types was based on magnetic resonance imaging (MRI)-diffusion-weighted imaging (DWI) results. We reevaluated the diagnostic value of the Romberg test for acute dizziness or vertigo by quantifying the duration of standing and created the R-cVR algorithm. The algorithm's accuracy was subsequently validated against the MRI-DWI results.

RESULTS

After screening, 109 patients were recruited and divided into central (n = 25) and peripheral (n = 84) groups. The central group had a high incidence of cerebral infarction (88.0 %), whereas the peripheral group included patients with vestibular neuronitis, benign paroxysmal positional vertigo, and Meniere's disease (96.4 %). Significant disparities in the incidence of balance disorders were noted between the groups (92.0 % vs. 15.5 %, p < 0.001). Multivariate logistic regression revealed an odds ratio of 61.82 for balance disorders (p < 0.001). The R-cVR algorithm, which integrates the Romberg test and the V-shaped stance with closed-eyes protocol, was tested against MRI-DWI and yielded high diagnostic agreement (kappa = 0.80), with a sensitivity and specificity of 88.0 % and 94.0 %, respectively. There was no significant difference in the diagnostic efficacy of this algorithm for acute dizziness or vertigo with or without nystagmus.

CONCLUSION

The R-cVR algorithm effectively identifies central-type dizziness or vertigo and is simple for general practitioners to use without specialized equipment, which may be valuable in various clinical settings.

摘要

背景

快速准确地区分周围性和中枢性头晕或眩晕的能力至关重要。我们开发了R-cVR算法用于早期识别中枢型头晕或眩晕。

方法

在这项单中心回顾性队列研究中,我们评估了2023年12月10日至2024年2月28日期间患有孤立性头晕或眩晕的患者。根据磁共振成像(MRI)-弥散加权成像(DWI)结果将其分为中枢型或周围型。我们通过量化站立时间重新评估了Romberg试验对急性头晕或眩晕的诊断价值,并创建了R-cVR算法。随后根据MRI-DWI结果验证了该算法的准确性。

结果

筛选后,招募了109例患者并分为中枢型组(n = 25)和周围型组(n = 84)。中枢型组脑梗死发生率较高(88.0%),而周围型组包括前庭神经炎、良性阵发性位置性眩晕和梅尼埃病患者(96.4%)。两组之间平衡障碍发生率存在显著差异(92.0%对15.5%,p < 0.001)。多因素逻辑回归显示平衡障碍的比值比为61.82(p < 0.001)。将Romberg试验和闭眼V形站姿相结合的R-cVR算法与MRI-DWI进行对比测试,结果显示诊断一致性较高(kappa = 0.80),敏感性和特异性分别为88.0%和94.0%。该算法对伴有或不伴有眼球震颤的急性头晕或眩晕的诊断效能无显著差异。

结论

R-cVR算法能有效识别中枢型头晕或眩晕,全科医生无需专业设备即可简便使用,在各种临床环境中可能具有重要价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a1f8/11470403/b8e2151c81a3/gr1.jpg

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