Evidence map›Paper›PMID 37693748›Full record

ArticleFrontiers in neurology2023

Predictive factors for Alzheimer's disease progression: a comprehensive retrospective analysis of 3,553 cases with 211 months follow-up.

Aynur Özge, Reza Ghouri, Nevra Öksüz, Bahar Taşdelen

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.6field-weighted citation impact, top 18% of its field
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

10 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
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  4. Primary age-related tauopathy.Acta neuropathologica · 2025
    Review
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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

4 authors at 1 institution in 1 country.

Aynur ÖzgeDepartment of Neurology, School of Medicine, Mersin University, Mersin, Türkiye.
Reza GhouriDepartment of Neurology, School of Medicine, Mersin University, Mersin, Türkiye.
Nevra ÖksüzDepartment of Neurology, School of Medicine, Mersin University, Mersin, Türkiye.
Bahar TaşdelenDepartment of Biostatistics, School of Medicine, Mersin University, Mersin, Türkiye.
Mersin Üniversitesi · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: There is conflicting data regarding the predictors of Alzheimer's Disease (AD), the most common form of dementia. The main objective of the study is to evaluate potential predictors of AD progression using a comprehensive follow-up dataset that includes functional/cognitive assessments, clinical and neuropsychiatric evaluations, and neuroimaging biomarkers such as hippocampal atrophy or white matter intensities (WMIs). Method: A total of 161 AD cases were recruited from a dementia database consisting of individuals who consulted the Dementia Outpatient Clinic of the Neurology Department at Mersin University Medical Faculty between 2000 and 2022, under the supervision of the same senior author have at least 3 full evaluation follow-up visit including functional, clinical, biochemical, neuropsychological, and radiological screening. Data were exported and analyzed by experts accordingly. Results: Mean follow-up duration of study sample was 71.66 ± 41.98, min 15 to max 211 months. The results showed a fast and slow progressive subgroup of our AD cases with a high sensitivity (Entropy = 0.836), with a close relationship with several cofactors and the level of disability upon admittance. Hippocampal atrophy and WMIs grading via Fazekas were found to be underestimated predictors of AD progression, and functional capacity upon admittance was also among the main stakeholders. Conclusion: The study highlights the importance of evaluating multiple potential predictors for AD progression, including functional capacity upon admittance, hippocampal atrophy, and WMIs grading via Fazekas. Our findings provide insight into the complexity of AD progression and may contribute to the development of effective strategies for managing and treating AD.

Indexed as

Alzheimer’s diseasedementiaFazekas gradingfunctional capacityhippocampal atrophyneuroimagingpredictorswhite matter intensities

Identifiers

PMID37693748
PMCPMC10484751
OpenAlexW4386163719

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.