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A multi-regression framework to improve diagnostic ability of optical coherence tomography retinal biomarkers to discriminate mild cognitive impairment and Alzheimer's disease.
Chua, Jacqueline; Li, Chi; Ho, Lucius Kang Hua; Wong, Damon; Tan, Bingyao; Yao, Xinwen; Gan, Alfred; Schwarzhans, Florian; Garhöfer, Gerhard; Sng, Chelvin C A; Hilal, Saima; Venketasubramanian, Narayanaswamy; Cheung, Carol Y; Fischer, Georg; Vass, Clemens; Wong, Tien Yin; Chen, Christopher Li-Hsian; Schmetterer, Leopold.
Afiliación
  • Chua J; Singapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, The Academia, Level 6, Discovery Tower, Singapore, 169856, Singapore.
  • Li C; Ophthalmology and Visual Sciences Academic Clinical Program, Duke-NUS Medical School, National University of Singapore, Singapore, Singapore.
  • Ho LKH; SERI-NTU Advanced Ocular Engineering (STANCE), Singapore, Singapore.
  • Wong D; Singapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, The Academia, Level 6, Discovery Tower, Singapore, 169856, Singapore.
  • Tan B; SERI-NTU Advanced Ocular Engineering (STANCE), Singapore, Singapore.
  • Yao X; Singapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, The Academia, Level 6, Discovery Tower, Singapore, 169856, Singapore.
  • Gan A; Singapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, The Academia, Level 6, Discovery Tower, Singapore, 169856, Singapore.
  • Schwarzhans F; SERI-NTU Advanced Ocular Engineering (STANCE), Singapore, Singapore.
  • Garhöfer G; School of Chemical and Biological Engineering, Nanyang Technological University, Singapore, Singapore.
  • Sng CCA; Singapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, The Academia, Level 6, Discovery Tower, Singapore, 169856, Singapore.
  • Hilal S; SERI-NTU Advanced Ocular Engineering (STANCE), Singapore, Singapore.
  • Venketasubramanian N; School of Chemical and Biological Engineering, Nanyang Technological University, Singapore, Singapore.
  • Cheung CY; Singapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, The Academia, Level 6, Discovery Tower, Singapore, 169856, Singapore.
  • Fischer G; SERI-NTU Advanced Ocular Engineering (STANCE), Singapore, Singapore.
  • Vass C; School of Chemical and Biological Engineering, Nanyang Technological University, Singapore, Singapore.
  • Wong TY; Singapore Eye Research Institute, Singapore National Eye Centre, 20 College Road, The Academia, Level 6, Discovery Tower, Singapore, 169856, Singapore.
  • Chen CL; Center for Medical Statistics Informatics and Intelligent Systems, Section for Medical Information Management, Medical University Vienna, Vienna, Austria.
  • Schmetterer L; Department of Clinical Pharmacology, Medical University Vienna, Vienna, Austria.
Alzheimers Res Ther ; 14(1): 41, 2022 03 10.
Article en En | MEDLINE | ID: mdl-35272711
BACKGROUND: Diagnostic performance of optical coherence tomography (OCT) to detect Alzheimer's disease (AD) and mild cognitive impairment (MCI) remains limited. We assessed whether compensating the circumpapillary retinal nerve fiber layer (cpRNFL) thickness for multiple demographic and anatomical factors as well as the combination of macular layers improves the detection of MCI and AD. METHODS: This cross-sectional study of 62 AD (n = 92 eyes), 108 MCI (n = 158 eyes), and 55 cognitively normal control (n = 86 eyes) participants. Macular ganglion cell complex (mGCC) thickness was extracted. Circumpapillary retinal nerve fiber layer (cpRNFL) measurement was compensated for several ocular factors. Thickness measurements and their corresponding areas under the receiver operating characteristic curves (AUCs) were compared between the groups. The main outcome measure was OCT thickness measurements. RESULTS: Participants with MCI/AD showed significantly thinner measured and compensated cpRNFL, mGCC, and altered retinal vessel density (p < 0.05). Compensated RNFL outperformed measured RNFL for discrimination of MCI/AD (AUC = 0.74 vs 0.69; p = 0.026). Combining macular and compensated cpRNFL parameters provided the best detection of MCI/AD (AUC = 0.80 vs 0.69; p < 0.001). CONCLUSIONS AND RELEVANCE: Accounting for interindividual variations of ocular anatomical features in cpRNFL measurements and incorporating macular information may improve the identification of high-risk individuals with early cognitive impairment.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfermedad de Alzheimer / Disfunción Cognitiva Tipo de estudio: Diagnostic_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Alzheimers Res Ther Año: 2022 Tipo del documento: Article País de afiliación: Singapur

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfermedad de Alzheimer / Disfunción Cognitiva Tipo de estudio: Diagnostic_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Alzheimers Res Ther Año: 2022 Tipo del documento: Article País de afiliación: Singapur