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Subclinical hypothyroidism is associated with basal ganglia enlarged perivascular spaces and overall cerebral small vessel disease load.
Chu, Ming; Cai, Yinyuan; Zhong, Jie; Qian, Yun; Cen, Yan; Dou, Miaomiao; Chen, Guilin; Sun, Bo; Lu, Xiaowei.
Afiliação
  • Chu M; Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
  • Cai Y; Department of Geriatrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
  • Zhong J; School of Foreign Languages, Nanjing University of Finance & Economics, Nanjing, China.
  • Qian Y; Department of Geriatrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
  • Cen Y; Department of Geriatrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
  • Dou M; Department of Geriatrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
  • Chen G; Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
  • Sun B; Department of Neurology, The Affiliated Huaian No. 1 People's Hospital of Nanjing Medical University, Huai'an, China.
  • Lu X; Department of Geriatrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Quant Imaging Med Surg ; 12(2): 1475-1483, 2022 Feb.
Article em En | MEDLINE | ID: mdl-35111640
ABSTRACT

BACKGROUND:

The association between subclinical hypothyroidism (SCH) and cerebral small vessel disease (CSVD) in the stroke-free population is currently unclear.

METHODS:

A total of 354 individuals without a history of stroke were enrolled in this study. Demographic data, medical history, vascular risk factors, carotid arteriosclerosis, and the results of laboratory tests were collated. SCH is defined as an elevation in thyroid-stimulating hormone levels, but with normal free thyroxine levels. Magnetic resonance imaging (MRI) was used to assess 4 markers of CSVD, including white matter hyperintensities (WMHs), lacunes, deep microbleeds, and enlarged perivascular spaces (EPVSs). The overall CSVD load was then ranked using an ordinal scale ranging from 0 to 4. Brain atrophy was measured semi-quantitatively on MRI. A binary logistic regression model was used to explore the association of SCH with each CSVD marker after adjusting for confounding factors. The ordinal regression model was used to explore the association of SCH with CSVD burden and brain atrophy after adjusting for confounding factors.

RESULTS:

The mean age of the participants (66.9% males) was 69.4±12.8 years. SCH was observed in 44 (12.4%) participants. MRI findings revealed 13% of cases with lacunes, 6.2% with microbleeds, 50.3% with confluent WMH, and 49.2% with extensive basal ganglia EPVS. Assessment of total CSVD burden showed that 29.1% scored 1, 30.5% scored 2, 6.5% scored 3, and 2.3% scored ≥3. SCH was associated with extensive basal ganglia EPVS [odds ratio (OR) =2.175; 95% confidence interval (CI) 1.075 to 4.401] and total CSVD load (OR =1.879; 95% CI 1.028 to 3.438). SCH was not associated with advanced brain atrophy.

CONCLUSIONS:

SCH is associated with the advanced total burden of CSVD and basal ganglia EPVS in the stroke-free population.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Quant Imaging Med Surg Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Quant Imaging Med Surg Ano de publicação: 2022 Tipo de documento: Article