Evidence map›Paper›PMID 39364422›Full record

ArticleFrontiers in neurology2024

Logistic regression model for predicting risk factors and contribution of cerebral microbleeds using renal function indicators.

Xuhui Liu, Zheng Pan, Yilan Li, Xiaoyong Huang, Xiner Zhang, Feng Xiong

Abstract read
In one paragraph

Article in Frontiers in neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Xuhui LiuDepartment of Neurology of the Second Hospital Affiliated to Lanzhou University, Lanzhou, China.
Zheng PanJinshan Branch of Shanghai Sixth People's Hospital, Shanghai, China.
Yilan LiTianjin 4th Center Hospital, Tianjin, China.
Xiaoyong HuangDepartment of Cardiology, Lishui People's Hospital, The Sixth Affiliated Hospital of Wenzhou Medical University, Lishui, China.
Xiner ZhangDepartment of Medical Oncology, Affiliated Tumor Hospital of Xinjiang Medical University, Ürümqi, China.
Feng XiongJinshan Branch of Shanghai Sixth People's Hospital, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The brain and kidneys share similar low-resistance microvascular structures, receiving blood at consistently high flow rates and thus, are vulnerable to blood pressure fluctuations. This study investigates the causative factors of cerebral microbleeds (CMBs), aiming to quantify the contribution of each risk factor by constructing a multivariate model via stepwise regression. Methods: A total of 164 hospitalized patients were enrolled from January 2022 to March 2023 in this study, employing magnetic susceptibility-weighted imaging (SWI) to assess the presence of CMBs. The presence of CMBs in patients was determined by SWI, and history, renal function related to CMBs were analyzed. Results: Out of 164 participants in the safety analysis, 36 (21.96%) exhibited CMBs and 128 (78.04%) did not exhibit CMBs, and the median age of the patients was 66 years (range: 49-86 years). Multivariate logistic regression identified hypertension (OR = 13.95%, 95% CI: 4.52, 50.07%), blood urea nitrogen (BUN) (OR = 1.57, 95% CI: 1.06-2.40), cystatin C (CyC) (OR = 4.90, 95% CI: 1.20-22.16), and urinary β-2 microglobulin, (OR = 2.11, 95% CI: 1.45-3.49) as significant risk factors for CMBs. The marginal Conclusion: Hypertension, BUN, urinary β-2 microglobulin, CyC were risk factors for CMBs morbidity, and controlling the above indicators within a reasonable range will help to reduce the incidence of CMBs.

Indexed as

cerebral microbleedscontributionhypertensionrenal function indicatorsrisk factors

Identifiers

PMID39364422
PMCPMC11447291

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