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Association of the Area Deprivation Index With Dementia Basic Workup and Diagnosis in Central and Western Virginia: A Cross-Sectional Study.
D'Abreu, Anelyssa; Bankole, Azziza; Kapur, Jaideep; Manning, Carol A; Chernyavskiy, Pavel.
Afiliação
  • D'Abreu A; Departments of Neurology (ADA, CAM, JK), Neuroscience (JK), and Public Health Sciences (PC), University of Virginia, Charlottesville; Department of Psychiatry and Behavioral Health (AB), Virginia Tech Carilion School of Medicine, Roanoke.
  • Bankole A; Departments of Neurology (ADA, CAM, JK), Neuroscience (JK), and Public Health Sciences (PC), University of Virginia, Charlottesville; Department of Psychiatry and Behavioral Health (AB), Virginia Tech Carilion School of Medicine, Roanoke.
  • Kapur J; Departments of Neurology (ADA, CAM, JK), Neuroscience (JK), and Public Health Sciences (PC), University of Virginia, Charlottesville; Department of Psychiatry and Behavioral Health (AB), Virginia Tech Carilion School of Medicine, Roanoke.
  • Manning CA; Departments of Neurology (ADA, CAM, JK), Neuroscience (JK), and Public Health Sciences (PC), University of Virginia, Charlottesville; Department of Psychiatry and Behavioral Health (AB), Virginia Tech Carilion School of Medicine, Roanoke.
  • Chernyavskiy P; Departments of Neurology (ADA, CAM, JK), Neuroscience (JK), and Public Health Sciences (PC), University of Virginia, Charlottesville; Department of Psychiatry and Behavioral Health (AB), Virginia Tech Carilion School of Medicine, Roanoke.
Neurol Clin Pract ; 14(5): e200323, 2024 Oct.
Article em En | MEDLINE | ID: mdl-38919929
ABSTRACT
Background and

Objectives:

The Area Deprivation Index (ADI) provides a validated and multidimensional metric of areal disadvantage. Our goals were to determine if the ADI influences the likelihood of receiving workup based on published guidelines and an etiologic diagnosis of dementia in Central and Western Virginia.

Methods:

We collected deidentified data from the electronic health record of individuals aged 50-105 years diagnosed with dementia at the University of Virginia (UVA) Medical Center (2016-2021) and at Carillion Clinic (2018-2021). Visit-specific ICD-10 codes were used to classify each dementia diagnosis as "disease-specific" (e.g., Alzheimer disease) or "general" (e.g., unspecified dementia). Following the American Academy of Neurology guidelines, we considered the evaluation performed as "adequate" if patients had vitamin B12, thyroid-stimulating hormone, and brain CT or magnetic resonance imaging within 6 months of the initial diagnosis. Census tract ADI was linked to study participants using the unique census tract identifier derived from the participants' home addresses at the time of diagnosis. Statistical modeling occurred under a Bayesian paradigm implemented using a standard code in R.

Results:

The study included 13,431 individuals diagnosed with dementia at UVA (n = 7,152) and Carillion Clinic (n = 6,279). Of those, 32.5% and 20.4% received "disease-specific" diagnoses at UVA and Carillion Clinic and 8.2% and 20.4% underwent "adequate" workup, respectively. The adjusted relationship between census tract ADI and the likelihood of a disease-specific diagnosis was U-shaped Residence in moderately disadvantaged areas was associated with the lowest likelihood of disease-specific diagnosis.

Discussion:

Most patients diagnosed with dementia did not receive an adequate evaluation or an etiologic diagnosis. Those living in locations just above the national median ADI levels had the lowest likelihood of receiving an etiologic diagnosis, lower than those in the least and most deprived areas. Renewed awareness efforts among providers are needed to increase compliance with diagnostic guidelines.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Neurol Clin Pract Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Neurol Clin Pract Ano de publicação: 2024 Tipo de documento: Article