Evidence map›Paper›PMID 40951388›Full record

ArticleFrontiers in public health2025

Peruvian validation and standardization of the TabCAT-brain health assessment.

Andrés Muñoz-Najar, Manuel Montemurro, María Del Carmen Tejada, Claudia Rivera-Fernández, Miguel Sánchez-Fernández, Nilton Custodio, Katherine L Possin, Elena Tsoy, Serggio Lanata, Marcio Soto-Añari

Abstract readValidation Study
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Andrés Muñoz-NajarLaboratorio de Neurociencia Cognitiva, Universidad Católica San Pablo, Arequipa, Peru.
Manuel MontemurroEscuela de Psicología, Universidad del Alba, Santiago, Chile.
María Del Carmen TejadaEscuela de Psicología, Universidad del Alba, Santiago, Chile.
Claudia Rivera-FernándezUniversidad Tecnológica del Perú, Arequipa, Peru.
Miguel Sánchez-FernándezClinica del Sur, Arequipa, Peru.
Nilton CustodioInstituto Peruano de Neurociencia, Lima, Peru.
Katherine L PossinMemory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States.
Elena TsoyMemory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States.
Serggio LanataMemory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States.
Marcio Soto-AñariLaboratorio de Neurociencia Cognitiva, Universidad Católica San Pablo, Arequipa, Peru.

Funding

Augmenting Nurse Support and EHR Integration for the Pragmatic Trial of the UCSF-BHAU01NS128913 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Katherine Laurel Possin · 2022 to 2026
$8.2M
NINDS NIH HHS U01 NS128913
6 · The paper itself

Abstract

Introduction: Detecting cognitive impairment in low-educated and marginalized populations may result in under- or over-estimation of diagnoses due to reliance on non-validated approaches and normative data. This study validates and standardizes TabCAT-BHA for older adults living in the Andean region of Peru using regression-based normalization. Methods: Two hundred fifty-eight participants were assessed with the MMSE, RUDAS, and TabCAT-BHA. Classified as either cognitively healthy or impaired based on Clinical Dementia Rating criteria. Results: By incorporating sex, place of residence, age, and years of education as covariates, the TabCAT-BHA demonstrated greater accuracy in detecting cognitive impairment (AUC = 75.3%) compared to the MMSE (AUC = 66.4%) and RUDAS (AUC = 71.4%). After incorporating only significant sociodemographic predictors, TabCAT-BHA obtained better AUC (77.4%) compared to MMSE (66.6%) and RUDAS (71.9%). Discussion: The TabCAT-BHA proves to be a valid tool for detecting cognitive impairment, and incorporating sociodemographic factors improves its accuracy in marginalized settings of Peru.

Indexed as

Cognitive DysfunctionNeuropsychological TestsAgedAged, 80 and overDementiaFemaleHumansMaleMiddle AgedPeruReproducibility of ResultsAlzheimer’s diseasebrief cognitive testscognitive assessmentdiagnostic accuracydigital cognitive toolslow educational attainmentmild cognitive impairmentregression-based norming

Identifiers

PMID40951388
PMCPMC12425762

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.