30,580 Alzheimer's and dementia studies in plain English, each scored out of 100.
An international working group from the Centres of Excellence in Neurodegeneration completed a structured process to develop definitions and imaging standards for markers and consequences of cerebral small vessel disease (SVD). 3 key findings →
Evidence: low
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White matter hyperintensities (WMHs) are neuroimaging markers widely interpreted as caused by cerebral small vessel disease, yet emerging evidence suggests that a subset may have a neurodegenerative etiology. 1 key finding →
Participants: 32,526 Evidence: moderate
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Participants' median age was 70.7 years (Q1-Q3 = 67.8-74.0), with 52.4% being women. 5 key findings →
Design: cross-sectional Participants: 678 Evidence: moderate
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This article examines mechanisms of blood-brain barrier dysfunction in neurodegenerative disorders, notably Alzheimer's disease, and highlights therapeutic opportunities relating to these neurovascular deficits.
Evidence: low
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Cerebral small vessel disease (SVD) is recognized as a major vascular contributor to cognitive decline, ultimately leading to dementia and stroke. 1 key finding →
Design: longitudinal study Evidence: moderate
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Sensitivity analyses were performed to validate the robustness of the linear regression results. 4 key findings →
Design: longitudinal study Participants: 832 Evidence: moderate
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White matter hyperintensities predict an increased risk of stroke, dementia, and death.
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Of 104 metabolites studied, glycodeoxycholic acid (GDCA) surpassed the false discovery rate and was associated the Alzheimer's Disease Assessment Scale-Cognitive Subscale version 13 (ADAS-Cog13) score (β = 0.12, 95 % CI = 0.05-0.20, p = 0.001) and cognitive impairment determined by mini-mental status exam (MMSE) (OR = 2.11, 95 % CI = 1.41-3.15, p < 0.001). 4 key findings →
Design: cross-sectional Participants: 578 Evidence: moderate
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SES and LA were associated with better cognitive performance at baseline, but were not associated with cognitive decline over time. 5 key findings →
Design: longitudinal study Participants: 181 Evidence: moderate
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The final model, which included age, systolic blood pressure >140, atrial fibrillation, and tobacco use, achieved an AUC of 0.83 (95% CI 0.75-0.90) in the development cohort (N=143, 62.4±12.6 years, 44% female, 36% non-white race) and 0.85 (95% CI 0.77-0.92) in the validation cohort (N=127, 65.2±16.8 years, 51% female, 34% non-white race), with similar results using WMH measurements derived from cMRI (N=120, p=0.98, AUC=0.86, 95% CI 0.77-0.93). 5 key findings →
Participants: 143 Evidence: moderate
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This study included 3540 participants with RVC data and 489 with WMH data (median [IQR] age: 73.2 [71.4-76.3] and 72.5 [71.2-75.4] years; female: 52.9% and 47.6%) over a median follow-up of 7.4 [IQR 5.5-8.5] and 3.8 [IQR 2.9-5.3] years, respectively. 5 key findings →
Design: cross-sectional Participants: 3,540 Evidence: moderate
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White matter hyperintensity (WMH), indicative of cerebral small vessel disease, has emerged as a potential biomarker for cognitive decline in Alzheimer's disease (AD). 2 key findings →
Design: cross-sectional Participants: 158 Evidence: low
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Five WMH clusters emerged. Compared to those with low WMH burden, participants in the mild occipital and high parieto-occipital clusters had faster memory decline; mild fronto-parietal and high parieto-occipital clusters showed faster executive decline; and mild and high fronto-parietal and high parieto-occipital clusters had faster language decline. 5 key findings →
Design: longitudinal study Participants: 1,047 Evidence: moderate
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Type 2 diabetes mellitus (T2DM) and major depressive disorder (MDD) are reciprocal risk factors, and both elevate dementia risk. 4 key findings →
Participants: 15,765 Evidence: low
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MAFLD was associated with an increased risk of WMH over 4.1 years in middle‐aged adults. 5 key findings →
Participants: 2,155 Evidence: moderate
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Our results pertaining to menopause-related characteristics, such as age at menopause or menopause hormonal therapy, did not replicate the literature reporting an association with WMH volumes. 5 key findings →
Design: cross-sectional Participants: 9,560 Evidence: low
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Cerebral small vessel disease (cSVD) is characterised by white matter hyperintensities (WMH) and contributes to stroke and dementia. 5 key findings →
Design: cross-sectional Participants: 60 Evidence: low
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White matter hyperintensities (WMH) are neuroimaging markers linked to an elevated risk of cognitive decline. 2 key findings →
Participants: 60 Evidence: low
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Among 225 patients (mean age 65.4 years, 54.2% male), MCR prevalence was 16.4%. 5 key findings →
Design: cross-sectional Participants: 225 Evidence: low
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This raises the suggestion that a decreased neurovascular coupling in the disease process of AD is related to comorbid small vessel disease. 2 key findings →
Participants: 119 Evidence: moderate
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Cerebral small vessel disease (cSVD) is associated with vascular cognitive impairment, dementia, and stroke. 3 key findings →
Design: cross-sectional Participants: 59 Evidence: low
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Hyperhomocysteinemia (HHcy) is an established risk factor for cognitive impairment. 2 key findings →
Design: cross-sectional Participants: 507 Evidence: moderate
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Alzheimer's disease (AD) and vascular dementia (VaD) exhibit distinct neuropathological hallmarks, with AD defined by cortical amyloid plaques and neurofibrillary tangles, while VaD arises primarily from cerebrovascular disease (CeVD). 4 key findings →
Participants: 531 Evidence: moderate
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Pulse pressure, but not mean arterial pressure, significantly mediated the relationship between age and white matter hyperintensity load. 5 key findings →
Design: cohort study Evidence: moderate
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The plasma PlGF level was significantly elevated in patients with SIVD compared with CUCs, and showed a high accuracy with an area under the curve of 0.893. 5 key findings →
Participants: 102 Evidence: moderate
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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 30,580 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 30,580 records, built mostly from automated pulls of Europe PMC (64.7% of the library) and OpenAlex (16.6%), 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 →
Newest studies, as a dated timeline → Atom feed Where this research is being discussed: events