30,180 Alzheimer's and dementia studies in plain English, each scored out of 100.
Longitudinal fMRI provides a reliable indicator of brain activation over time, and may prove useful in identifying functional brain changes associated with cognitive decline on the trajectory toward clinical Alzheimer disease. 3 key findings →
Design: cross-sectional Participants: 21 Evidence: moderate
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More research is needed to elucidate the neural mechanisms underlying these regional associations, which may involve motor and sensorimotor circuits hitherto largely neglected in the pathophysiology of AD. 1 key finding →
Design: cross-sectional Evidence: low
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Higher baseline body mass index (BMI) and slower declining BMI in late life are associated with a reduced risk of dementia, suggesting that low BMI or a faster decline in BMI in late life may be preclinical indicators of an underlying dementing illness, especially for those who were initially overweight or obese. 3 key findings →
Design: cohort study Evidence: moderate
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Among 1,969 subjects without dementia, 329 subjects had MCI, with a prevalence of 16.0% (95% confidence interval [CI] 14.4-17.5) for any MCI, 11.1% (95% CI 9.8-12.3) for amnestic MCI, and 4.9% (95% CI 4.0-5.8) for nonamnestic MCI. 3 key findings →
Participants: 1,969 Evidence: low
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Brain atrophy with aging was observed in supratentorial and infratentorial areas, as well in primary motor, sensory, and heteromodal association regions. 1 key finding →
Design: longitudinal study Participants: 33 Evidence: moderate
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Increased amygdalar diffusivity in the absence of tissue loss in dementia with Lewy bodies (DLB) may be related to microvacuolation, a common pathology associated with Lewy body disease in the amygdala. 3 key findings →
Design: case-control study Participants: 30 Evidence: moderate
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Acceleration in WMH burden, a common indicator of cerebrovascular disease in the elderly, is a pathologic change that emerges early in the presymptomatic phase leading to MCI. 2 key findings →
Design: longitudinal study Participants: 134 Evidence: moderate
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At baseline measurements, amyloid burden does not distinguish between cognitively impaired and unimpaired subjects with PD without dementia, but our data suggest that amyloid contributes to cognitive, but not motor, decline over time. 3 key findings →
Design: cohort study Participants: 46 Evidence: moderate
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We examined the neuropsychological test performance of a randomly selected community sample of English-speaking non-Hispanic African American and white elders in northern Manhattan. 3 key findings →
Evidence: low
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Older age is associated with increased HAD in this HIV-1 cohort. 2 key findings →
Design: cross-sectional Participants: 106 Evidence: moderate
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We evaluated 22 persons with nfvPPA (mean age: 67.3 years; 13 female patients) and confirmed underlying 4-repeat tauopathy, 15 persons with semantic variant primary progressive aphasia (svPPA; mean age: 66.5 years; 8 female patients), and 10 healthy controls (HCs; 70 years; 5 female patients). 3 key findings →
Design: cross-sectional Participants: 12 Evidence: moderate
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Higher concentrations may reflect the intensity of the disease in FTD and are associated with more rapid atrophy of the frontal lobes. 3 key findings →
Participants: 74 Evidence: low
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Cognitive decline associated with Parkinson disease (PD) is common and highly disabling. 4 key findings →
Design: cohort study Participants: 45 Evidence: moderate
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ATN (β-amyloid [Aβ], tau, neurodegeneration) system categorizes individuals based on their core Alzheimer disease (AD) biomarkers. 4 key findings →
Design: cross-sectional Participants: 410 Evidence: low
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The association between vascular risk factors and dementia varies with age, making generalizability of dementia risk prediction rules to individuals of different ages challenging. 4 key findings →
Participants: 4,899 Evidence: moderate
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A total of 807 K-ROAD participants (median age 72.0 years, 58.7% female) and 230 ADNI participants (median age 70.9 years, 49.1% female) were analyzed. 5 key findings →
Design: cohort study Participants: 807 Evidence: moderate
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Plasma Aβ42/Aβ40, especially when combined with age and APOE ε4 status, accurately diagnoses brain amyloidosis and can be used to screen cognitively normal individuals for brain amyloidosis. 2 key findings →
Evidence: low
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During the 17-year follow-up period, 164 participants developed dementia; 136 of these cases were AD. 5 key findings →
Participants: 164 Evidence: moderate
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This should be considered when designing protocols for amyloid-modifying clinical trials. 1 key finding →
Design: longitudinal study Evidence: moderate
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CLU and MS4A4A eSNPs may at least partly explain the LOAD risk association at these loci. 3 key findings →
Evidence: low
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These findings from healthy high-risk older individuals suggest that OI reflects degree of preclinical AD pathology, while its relationships with age and cognition result from the association of these latter variables with such pathology. 3 key findings →
Design: cross-sectional Participants: 101 Evidence: moderate
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There was a significant interaction between cholesterol, APOE-epsilon4, and the risk of Alzheimer disease (AD) in the Yoruba, a population that has lower cholesterol levels and lower incidence rates of AD compared to African Americans. 4 key findings →
Design: longitudinal study Participants: 1,075 Evidence: moderate
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Our results provide evidence supporting 25OHD as a causal risk factor for AD. 5 key findings →
Participants: 33,996 Evidence: high
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The findings support the cross-cultural use of a relatively inexpensive odor identification test as an early biomarker of cognitive decline and AD dementia. 1 key finding →
Participants: 1,037 Evidence: moderate
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Although we have found a slightly lower risk than other reports, the risk of developing neurodegenerative disease in idiopathic REM sleep behavior disorder is substantial, with the majority of patients developing Parkinson disease and Lewy body dementia. 2 key findings →
Participants: 113 Evidence: low
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Free full text links and the Full text may need a subscription label come from Unpaywall, Europe PMC and OpenAlex records of free copies, checked 10 Oct 2026. A study with neither is unknown, not paywalled.
This is alzhub's own score. It is not an official metric, not an impact factor, and no journal, publisher or ranking body endorses it. We built it so that a reader who is not a scientist can tell a landmark trial from a conference abstract without having to already know the difference. Every point comes from one of 20 components, all of them printed on the study itself, so you can disagree with our arithmetic rather than having to trust the total.
Journals are placed in ordered tiers, never given a numeric impact factor — we could not verify current impact factors from a source we control, and an invented one would be worse than none. Tier 1 is the top-tier general journals (NEJM, The Lancet, JAMA, Nature, Science, Nature Medicine); tier 2 is the leading specialty journals; tier 3 is every other peer-reviewed journal. A separate part scores how much the journal's own papers are cited, which tells the tier-3 journals apart.
Two rules we don't bend. First, we never fill in a missing value: if a record does not state a sample size or a design, that component scores zero, and if we simply have no data for a part, such as a citation count, that part is left out and the study is scored on the parts we could check. The study card says which. Second, anything that is not a peer-reviewed article is capped at 16/100 and carries a warning chip — so a conference abstract or a company press release can never outrank a peer-reviewed paper, no matter how good it looks.
We rank a rigorous null result — a good trial showing that something does not work — above an early positive finding. Someone deciding whether to buy a supplement is served by that, and the rigour is already counted by the design and journal components.
The score is computed from the published data alone and is reproducible: the same file always yields the same numbers.
See the whole rubric drawn out → — four charts covering all 30,180 studies: how the scores are spread and where the cap bites, which of the 20 components the library is strong and weak on, which subjects rest on stronger evidence, and what kinds of study each subject is actually built from.
This is a large sample of the Alzheimer's literature, not an exhaustive index of it. It holds 30,180 records, built mostly from automated pulls of Europe PMC (64.2% of the library) and OpenAlex (16.9%), plus smaller pulls from PubMed, Crossref and medRxiv. If a study, a drug, or a finding isn't here, that is not evidence it doesn't exist in the literature — it may simply not have been pulled in yet.
1,037 records (3.4% of the library) are not peer-reviewed — 964 of those are preprints posted before any journal review, and the rest are conference abstracts, regulatory notices and reports. Every study card on this page states its status plainly, and the score above is capped for anything that isn't a peer-reviewed article.
See the full, machine-readable breakdown of this library's coverage →