31,380 Alzheimer's and dementia studies in plain English, each scored out of 100.
Levels of autolysosomal proteins in neurally derived blood exosomes distinguish patients with AD from case controls and appear to reflect the pathology of AD up to 10 years before clinical onset. 4 key findings →
Design: cross-sectional Participants: 26 Evidence: low
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Over a median follow-up of 5.1 years, 153 of 534 participants (28.7%) with prevalent or incident MCI progressed to dementia (71.3 per 1,000 person-years). 2 key findings →
Participants: 534 Evidence: moderate
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Even in a cohort of patients seen at dementia research centers, reversion from MCI was fairly common. 5 key findings →
Participants: 3,020 Evidence: moderate
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Hippocampal MRglc reductions using FDG-PET during normal aging predict cognitive decline years in advance of the clinical diagnosis. 2 key findings →
Design: longitudinal study Participants: 55 Evidence: moderate
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The following 2 regions for tau burden were identified: the entorhinal cortex, which exhibits early signs of tauopathy, and the inferior temporal region, which is more closely associated with AD-related pathologic mechanisms. 4 key findings →
Design: cross-sectional Participants: 133 Evidence: low
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Subjective cognitive decline (SCD) is regarded as the first clinical manifestation in the Alzheimer's disease (AD) continuum. 3 key findings →
Design: longitudinal study Evidence: moderate
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Previous neuroimaging studies reveal that MCI is associated with aberrant sensory-perceptual processing in cortical brain regions subserving auditory and language function. 5 key findings →
Evidence: low
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Both interventions were highly feasible and acceptable and allowed improvement in different aspects of cognitive and psychosocial functioning in MCI subjects. 4 key findings →
Evidence: high
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Levels of P-S396-tau, P-T181-tau, and Aβ1-42 in extracts of neurally derived blood exosomes predict the development of AD up to 10 years before clinical onset. 2 key findings →
Participants: 57 Evidence: low
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Cognitive complaints are common in the elderly, and nearly one in three meet criteria for MCI. 1 key finding →
Design: longitudinal study Participants: 1,037 Evidence: moderate
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A challenge in developing informative neuroimaging biomarkers for early diagnosis of Alzheimer's disease is the need to identify biomarkers that are evident before the onset of clinical symptoms, and which have sufficient sensitivity and specificity on an individual patient basis. 4 key findings →
Design: longitudinal study Evidence: moderate
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The most novel characteristics of our machine learning model compared to previous ones are the following: 1) our deep learning model is multi-tasking, in the sense that it jointly learns to simultaneously predict both MCI to AD conversion as well as AD vs. healthy controls classification, which facilitates relevant feature extraction for AD prognostication; 2) the neural network classifier employs fewer parameters than other deep learning architectures which significantly limits data-overfitting (we use ∼550,000 network parameters, which is orders of magnitude lower than other network designs); 3) both structural MRI images and their warp field characteristics, which quantify local volumetric changes in relation to the MRI template, were used as separate input streams to extract as much information as possible from the MRI data. 1 key finding →
Participants: 785 Evidence: low
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In Alzheimer's disease, post-mortem studies have shown that the first cortical site where neurofibrillary tangles appear is the transentorhinal region, a subregion within the medial temporal lobe that largely overlaps with Brodmann area 35, and the entorhinal cortex. 5 key findings →
Participants: 215 Evidence: low
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Transition probabilities from normal cognition through AD severity states are important for understanding patient progression across the AD spectrum. 1 key finding →
Design: longitudinal study Participants: 18,103 Evidence: moderate
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Compared to age matched controls, in the AD group, we found increases in both spectral power and coherence at the slower frequencies (Delta, Theta). 5 key findings →
Participants: 26 Evidence: low
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Current classifications of MCI have variable outcomes in population-based samples. 2 key findings →
Design: cohort study Participants: 2,640 Evidence: moderate
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Qualitatively, our review of 57 MCI versus HC comparisons suggests substantial inconsistency; 9 showed no group difference, 8 showed MCI > HC and 22 showed HC > MCI across the brain, and 18 showed regionally-mixed directions of effect. 3 key findings →
Design: meta-analysis Evidence: high
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We have developed MCI risk scores using variables easily assessable in the clinical setting and that may be useful in routine patient care. 2 key findings →
Design: cohort study Evidence: moderate
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With the aging US population and increasing incidence of Alzheimer disease (AD), understanding factors contributing to driving cessation among older adults is crucial for clinicians. 4 key findings →
Design: longitudinal study Participants: 283 Evidence: moderate
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Age-related cognitive impairment and dementia are an increasing societal burden. 4 key findings →
Evidence: low
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Mild cognitive impairment (MCI) is a syndrome thought to be a prodrome of dementia for some patients. 4 key findings →
Design: longitudinal study Participants: 1,379 Evidence: moderate
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Sensitive detection of cognitive decline over the course of preclinical Alzheimer's disease is critical as the field moves toward secondary prevention trials. 4 key findings →
Design: longitudinal study Evidence: moderate
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Of 9,361 randomized participants, 7,221 (77%) were eligible to be re-contacted. 5 key findings →
Participants: 248 Evidence: high
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This text discusses the characterisation of subjective cognitive decline (SCD), a term conceived in 2014 to describe cognitively unimpaired individuals who are concerned about reduced cognitive function and seek medical help. 3 key findings →
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Insomnia in cognitively unimpaired adults at increased risk for AD is associated to poorer performance in some executive functions and volume changes in cortical and subcortical gray matter, including key areas involved in Alzheimer's disease, as well as decreased white matter diffusivity. 4 key findings →
Design: cross-sectional Participants: 366 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 31,380 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 31,380 records, built mostly from automated pulls of Europe PMC (65.6% of the library) and OpenAlex (16.2%), 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.
1,048 records (3.3% of the library) are not peer-reviewed — 973 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