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Find studies

Showing 1–22 of 22 studies in Digital health tools · 28,180 in the whole library · How the 0–100 score works

Download bibliography of these 22 studies, in this order: BibTeX (.bib) · RIS (.ris)

Showing 22 studies tagged leading-causes — clear

Browse by subject, author or institution

Each number is how many studies that link shows, with your other filters kept.

What “Digital health tools” covers

Digital health tools — Apps, wearables, online tests and other technology used to detect, monitor or support people with dementia.

A note on reading research. One study is rarely the final word.

We try to note the size of a study, whether it was in humans or animals, and how early-stage the finding is. If a summary here doesn't make that clear, treat it with extra caution and check the original source.

Study objective To examine the risks and compare the occurrences of major long-term side effects (sexual dysfunction, bone fractures, diabetes, cardiovascular morbidity, acute myocardial infarction [MI], and dementia) in patients with prostate cancer who received androgen-deprivation therapy (ADT) with those who did not. 5 key findings →

Design: cohort study Participants: 201,797 Evidence: moderate

Increasing comorbidity and health services utilization in older adults with prior stroke

✓ Peer-reviewed alzhub usefulness score 71 out of 100. Neurology 2016-10-19

Our findings demonstrate the importance of community-based patient-centered care strategies for stroke survivors that address their range of health needs and prevent more costly acute care use. 2 key findings →

Design: cohort study Participants: 29,673 Evidence: moderate

Among older Medicare beneficiaries with heart failure, there is a higher overall burden of comorbidity and greater prevalence of discordant comorbidity among the oldest old. 5 key findings →

Design: cohort study Participants: 201,130 Evidence: moderate

Low-Value Care at the Actionable Level of Individual Health Systems

✓ Peer-reviewed alzhub usefulness score 66 out of 100. JAMA internal medicine 2021-11-01

The findings of this large cohort study suggest that system-level measurement and reporting of specific low-value services is feasible, enables cross-system comparisons, and reveals a broad range of low-value care use. 3 key findings →

Design: cohort study Evidence: moderate

Men, racial and ethnic minority individuals, older adults, and those with language barriers are at increased risk for undertreatment of depression. 5 key findings →

Design: cohort study Evidence: moderate

Illness duration and symptom prevalence, duration, and burden were analysed for children testing positive for SARS-CoV-2 for whom illness duration could be determined, and were assessed overall and for younger (age 5-11 years) and older (age 12-17 years) groups. 4 key findings →

Design: cohort study Evidence: moderate

GIM services care for a markedly heterogeneous population but the most common conditions were similar across 7 hospitals. 3 key findings →

Design: cross-sectional Participants: 223 Evidence: low

The use of methods that focus on determining a single underlying cause may lead to underestimation of the extent of the contribution of some diseases such as dementia and respiratory disease to death in older adults and overestimation of the contribution of other diseases. 1 key finding →

Design: longitudinal study Evidence: moderate

Claims data studies that include indicators of potentially diminished patient functional status better capture heterogeneity of patients with multiple chronic conditions. 1 key finding →

Participants: 72,056 Evidence: moderate

Men with prostate cancer treated with androgen deprivation therapy had a higher likelihood of developing new comorbidities than men who did not receive androgen deprivation therapy. 3 key findings →

Design: cohort study Evidence: moderate

Predictors of long-term mortality after severe sepsis in the elderly

✓ Peer-reviewed alzhub usefulness score 47 out of 100. The American journal of the medical sciences 2014-04-01

The authors identified several factors, including receipt of mechanical ventilation, which were significantly associated with increased long-term mortality for survivors of severe sepsis. 5 key findings →

Participants: 2,727 Evidence: low

The CPCSSN diagnostic algorithms showed excellent sensitivity and specificity for hypertension, diabetes, epilepsy, and parkinsonism and acceptable values for the other conditions. 1 key finding →

Design: cross-sectional Evidence: low

Multiple EHR components provide a more consistent and higher performance than a single one for the selected phenotypes. 5 key findings →

Participants: 175 Evidence: low

The objective of this study was to determine the accuracy of administrative data (by use of hospital discharge codes) for measuring comorbidity in patients with heart disease. 1 key finding →

Evidence: low

A prognostic model for 1-year mortality in older adults after hospital discharge

✓ Peer-reviewed alzhub usefulness score 40 out of 100. The American journal of medicine 2007-05-01

Reasonable prognostic information for 1-year mortality in older patients discharged from general medicine services can be derived from administrative data to identify high-risk groups of persons. 2 key findings →

Evidence: moderate

Patients with peripheral artery disease (PAD), chronic limb-threatening ischemia (CLTI), and/or diabetic foot ulcer (DFU) are at increased risk for limb loss and death. 3 key findings →

Participants: 178,995 Evidence: moderate

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Where “Free full text” comes from

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

How the 0–100 score works — and why some entries are capped

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.

  • Journal tier up to 10 pts
  • Journal's citation record up to 4 pts
  • Study design up to 12 pts
  • Strength of evidence up to 5 pts
  • Peer-review validation up to 10 pts
  • How recent up to 5 pts
  • Sample size up to 4 pts
  • Effect reported up to 3 pts
  • Studied in people up to 3 pts
  • Randomised / blinded up to 2 pts
  • Times cited up to 7 pts
  • Citations per year up to 5 pts
  • Impact for its field and year up to 6 pts
  • Cited by studies here up to 6 pts
  • Still being cited up to 4 pts
  • Senior author's track record up to 4 pts
  • Institution's track record up to 3 pts
  • Multi-centre collaboration up to 3 pts
  • Indexed in PubMed up to 2 pts
  • Free to read up to 2 pts

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 28,180 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.

What this library is — and isn't

This is a large sample of the Alzheimer's literature, not an exhaustive index of it. It holds 28,180 records, built mostly from automated pulls of Europe PMC (61.7% of the library) and OpenAlex (18.1%), 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.

1,034 records (3.7% 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 →

Newest studies, as a dated timeline →    Atom feed