Evidence map›Paper›PMID 41323451›Full record

ArticleDementia and geriatric cognitive disorders extra

The Utility of CSF Biomarkers in Diagnosing Alzheimer's Disease: A Thai Cohort Study.

Witsarut Nanthasi, Chatchawan Rattanabannakit, Natthamon Wongkom, Pathitta Dujada, Atthapon Raksthaput, Sunisa Chaichanettee, Paphawadee Phoyoo, Leatchai Wachirutmanggur, Seong Soo A An, Vorapun Senanarong

Abstract read
In one paragraph

Article in Dementia and geriatric cognitive disorders extra. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Witsarut NanthasiDivision of Neurology, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Chatchawan RattanabannakitDivision of Neurology, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Natthamon WongkomDivision of Neurology, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Pathitta DujadaDivision of Neurology, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Atthapon RaksthaputDivision of Neurology, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Sunisa ChaichanetteeDivision of Neurology, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Paphawadee PhoyooNeurological Laboratory, Division of Neurology, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Leatchai WachirutmanggurNeurological Laboratory, Division of Neurology, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Seong Soo A AnDepartment of Bionano Technology, Gachon University, Seongnam, Republic of Korea.
Vorapun SenanarongDivision of Neurology, Department of Medicine, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Cutoff values for cerebrospinal fluid biomarkers vary by analytic technique and population, which complicates the differentiation of Alzheimer's disease (AD) from non-AD dementias. We aimed to establish local cerebrospinal fluid biomarker cutoffs within a Thai cohort. Materials and Methods: We recruited 68 patients with various forms of dementia from the Memory Clinic at Siriraj Hospital, Thailand. Each patient underwent clinical subtyping for dementia, and their cerebrospinal fluid levels of Aβ42, p-tau181, and t-tau were quantified using the Fujirebio INNOTEST ELISA. We then employed a data-driven approach, specifically a Z-score-based Gaussian Mixture Model, to define intersection cutoffs for Aβ42, p-tau181, t-tau, and the p-tau181/Aβ42 ratio. These established biomarker cutoffs were subsequently incorporated with clinical manifestations to refine the clinicobiological diagnoses. Results: Our study included 67 patients (mean age 65.5 ± 7.4 years, 61.2% female). Using a data-driven approach, we established the following CSF biomarker cutoffs for identifying AD in this Thai cohort: Aβ42 at 492.67 pg/mL, p-tau181 at 44.00 pg/mL, t-tau at 545.97 pg/mL, and the p-tau181/Aβ42 ratio at 0.057. After incorporating these CSF biomarker results with clinical profiles, the diagnoses changed in 17.9% of the patients. Conclusions: In this study, CSF cutoffs for differentiating AD from non-AD dementia were established through a data-driven approach, which has been demonstrated as a valid alternative methodology. The integration of clinical and biological profiles is paramount in achieving accurate dementia diagnoses.

Indexed as

Alzheimer’s diseaseCerebrospinal fluid biomarkersDementiaThai cohort

Identifiers

PMID41323451
PMCPMC12659453

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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.