27,380 Alzheimer's and dementia studies in plain English, each scored out of 100.
The double-cutoff approach revealed high confidence for interpreting scans as negative when Centiloid values were lower than 11 (95% CI, 9-13; I2 = 95%) and interpreting scans as positive if Centiloid values were higher than 26 (95% CI, 24-28; I2 = 95%). 3 key findings →
Design: meta-analysis Participants: 49,227 Evidence: high
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We found a sequence to pathological changes, with rates of Aβ deposition in mutation carriers being significantly different from those in non-carriers first (across regions that showed a significant difference, at a mean of 18·9 years [SD 3·3] before expected onset), followed by hypometabolism (14·1 years [5·1] before expected onset), and lastly structural decline (4·7 years [4·2] before expected onset). 2 key findings →
Design: longitudinal study Participants: 346 Evidence: moderate
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Compared with participants who learned that they had a not elevated amyloid result, individuals who learned of an elevated amyloid result were no more likely to experience short-term increases in depression (mean [SD] change in the Geriatric Depression Scale score, 0.02 [1.3] vs 0.04 [1.3]; P = .90), anxiety (mean [SD] change in State-Trait Anxiety Inventory score, -0.02 [3.2] vs -0.15 [3.0]; P = .65), or suicidality (mean [SD] change in the Columbia Suicide Severity Rating Scale score, 0.0 [0.4] vs -0.01 [0.5]; P = .67). 5 key findings →
Design: cohort study Participants: 1,167 Evidence: high
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Among the 445 participants (243 with normal amyloid, 202 with elevated amyloid), mean (SD) age was 74.0 (5.9) years, mean education was 16.4 (2.7) years, and 52% were women. 2 key findings →
Design: longitudinal study Participants: 243 Evidence: moderate
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The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a longitudinal multisite observational study of healthy elders, mild cognitive impairment (MCI), and Alzheimer's disease. 5 key findings →
Design: longitudinal study Evidence: moderate
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The literature has several methodological limitations including lack of sufficient algorithm development descriptions and standard definitions. 1 key finding →
Participants: 255 Evidence: moderate
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The highly consistent regional hierarchy of PET-evidenced amyloid deposition across participants resembles neuropathologic observations and suggests a predictable regional sequence that may be used to stage an individual's progress of amyloid pathology in vivo. 2 key findings →
Design: cross-sectional Participants: 667 Evidence: moderate
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Therefore, we conducted a longitudinal study to examine whether PM2.5 affects the episodic memory decline, and also explored the potential mediating role of increased neuroanatomic risk of Alzheimer's disease associated with exposure. 5 key findings →
Design: longitudinal study Participants: 998 Evidence: moderate
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Thinning in specific cortical areas known to be affected by Alzheimer disease (AD) is detectable in individuals with questionable AD dementia (QAD) and predicts conversion to mild AD dementia. 3 key findings →
Design: longitudinal study Participants: 49 Evidence: moderate
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Florbetapir F 18 PET can image amyloid-β (Aβ) aggregates in the brains of living subjects. 4 key findings →
Design: longitudinal study Participants: 51 Evidence: moderate
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In DIAD, solanezumab was not associated with ARIA. 5 key findings →
Design: cross-sectional Participants: 52 Evidence: moderate
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In ADNI, Aβ-positive participants showed more decline than did Aβ-negative participants with regard to the ADCS-PACC score at 24 months (mean [SE] difference, -1.239 [0.522] [95% CI, -2.263 to -0.215]; P = .02). 4 key findings →
Evidence: low
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Early identification of individuals at risk of developing Alzheimer's disease (AD) dementia is important for developing disease-modifying therapies. 4 key findings →
Design: cross-sectional Participants: 1,677 Evidence: moderate
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Encoding-task fMRI was successfully implemented in a single-site, 24-week, AD randomized controlled trial. 2 key findings →
Design: randomized controlled trial Participants: 24 Evidence: high
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AD-signature cortical thinning in CN-AD converters in both samples was remarkably similar, about 0.2 mm (p 1). 3 key findings →
Design: longitudinal study Evidence: moderate
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44 participants were included: 20 PSEN1 E280A mutation carriers and 24 non-carriers. 2 key findings →
Participants: 44 Evidence: moderate
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Autosomal-dominant AD is associated with increased WMH well before expected symptom onset. 4 key findings →
Participants: 299 Evidence: low
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In this study, clinically normal adults with SNAP did not exhibit evidence of elevated tau levels, which suggests that this biomarker construct does not represent amyloid-independent tauopathy. 5 key findings →
Design: longitudinal study Participants: 247 Evidence: moderate
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We used Kaplan-Meier survival analysis to examine the distribution of incident ARIA-E from the start of bapineuzumab treatment and proportional hazards regression models to assess risk factors associated with ARIA. 3 key findings →
Design: clinical trial Participants: 262 Evidence: low
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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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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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In this study, researchers assessed the validity and reliability of an automated labeling system developed to subdivide the human cerebral cortex on magnetic resonance images into gyral based regions of interest. 3 key findings →
Evidence: low
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Resting-state functional connectivity magnetic resonance imaging changes with progressing AD severity are similar between ADAD and LOAD. 2 key findings →
Design: cross-sectional Participants: 79 Evidence: moderate
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To assess the relationship between dementia, neuronal loss, and neuropathological findings in Alzheimer's disease (AD), we counted the number of neurons, senile plaques, and neurofibrillary tangles in a high-order association cortex. 1 key finding →
Participants: 34 Evidence: low
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These optimized thresholds can help to inform future research and clinical trials targeting early Aβ. 2 key findings →
Participants: 342 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. Show only studies that are free to read
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 27,380 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 27,380 records, built mostly from automated pulls of Europe PMC (60.6% of the library) and OpenAlex (18.6%), 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.
1,032 records (3.8% of the library) are not peer-reviewed — 962 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 →