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A Single Baseline Amyloid Positron Emission Tomography Could Be Sufficient for Predicting Alzheimer's Disease Conversion in Mild Cognitive Impairment.
Choo, Il Han; Chong, Ari; Chung, Ji Yeon; Ha, Jung-Min; Choi, Yu Yong; Kim, Hoowon.
Afiliação
  • Choo IH; Department of Neuropsychiatry, School of Medicine, Chosun University, Chosun University Hospital, Gwangju, Republic of Korea.
  • Chong A; Biomedical Technology Center, Chosun University Hospital, Gwangju, Republic of Korea.
  • Chung JY; Department of Nuclear Medicine, School of Medicine, Chosun University, Chosun University Hospital, Gwangju, Republic of Korea.
  • Ha JM; Biomedical Technology Center, Chosun University Hospital, Gwangju, Republic of Korea.
  • Choi YY; Department of Neurology, School of Medicine, Chosun University, Chosun University Hospital, Gwangju, Republic of Korea.
  • Kim H; Biomedical Technology Center, Chosun University Hospital, Gwangju, Republic of Korea.
Psychiatry Investig ; 19(5): 394-400, 2022 May.
Article em En | MEDLINE | ID: mdl-35620825
ABSTRACT

OBJECTIVE:

Baseline amyloid burden in mild cognitive impairment (MCI) has been linked to conversion to Alzheimer's disease (AD), but the comparison of baseline and longitudinal changes in amyloid burden for predicting AD remains unresolved. The objectives of this study aimed to compare the prognostic ability of baseline and longitudinal changes in amyloid burden in MCI patients.

METHODS:

Seventy-five individuals with MCI were recruited and examined annually by clinical interviews for a mean follow-up of 24 months (range, 11.6-42.0). [18F]Florbetaben positron emission tomography (PET) scans were performed. T1-weighted 3D volumes were acquired for co-registration, and to define regions of interest. We examined whether baseline and longitudinal amyloid burden changes can improve AD conversion by Cox proportional hazard model analysis and receiver operating characteristic (ROC) curve analysis.

RESULTS:

Cox proportional hazards model analysis showed that baseline amyloid burden was significantly associated with increased risk of conversion to AD (hazard ratio [HR]=10.0; 95% confidence interval [CI], 1.15-85.39; p=0.04), but longitudinal amyloid burden changes was not (HR=0.2; 95% CI, 0.02-1.18; p=0.07). When predicting AD, longitudinal amyloid burden changes had better ROC accuracy of 65.2% (95% CI, 48.4-82.0) than baseline amyloid burden of 59.6% (95% CI, 40.3-79.0), without statistical significance in pairwise comparison.

CONCLUSION:

A single baseline amyloid PET could be sufficient in the prediction of AD conversion in MCI.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article