This page is alzhub.org's plain-English summary of a published study, not the paper itself. It is generated from the record we hold for this study, sourced and linked below — check the original for the full text and methods.

40/100

✓ Peer-reviewed alzhub usefulness score 40 out of 100. Cognitive tests and assessment

Topic: Amyloid, tau and blood-test diagnosis

Plain-language summary

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia in adults. AF increases the risk of heart failure, cardiac ischemic disease, dementia and Alzheimer's disease. Either clinical and subclinical AF increase the risk of stroke and worsen the patients' clinical outcome. The early diagnosis of AF episodes, even if asymptomatic or clinically silent, is of pivotal importance to ensure prompt and adequate thromboembolic risk prevention therapies. The development of technology is allowing new systematic mass screening possibilities, especially in patients with higher stroke risk. The mobile health devices available for AF detection are: smartphones, wrist-worn, earlobe sensors and handheld ECG. These devices showed a high accuracy in AF detection especially when a combined approach with single-lead ECG and photoplethysmography algorithms is used. The use of wearable devices for AF screening is a feasible method but more head-to-head comparisons between mHealth and medical devices are needed to establish their comparative effectiveness across different study populations.

Cite this study APA, Vancouver, BibTeX · download .bib or .ris

APA 7th

Papaccioli, G., Bassi, G., Lugi, C., Parente, E., D'Andrea, A., Proietti, R., et al. (2022). Smartphone and new tools for atrial fibrillation diagnosis: evidence for clinical applicability. Minerva cardiology and angiology. https://doi.org/10.23736/s2724-5683.22.05841-0

Vancouver

Papaccioli G, Bassi G, Lugi C, Parente E, D'Andrea A, Proietti R, et al. Smartphone and new tools for atrial fibrillation diagnosis: evidence for clinical applicability. Minerva cardiology and angiology. 2022. doi:10.23736/s2724-5683.22.05841-0. PMID: 35212504.

BibTeX

@article{papaccioli2022-35212504,
  author  = {Papaccioli, G. and Bassi, G. and Lugi, C. and Parente, E. and D'Andrea, A. and Proietti, R. and Imbalzano, E. and Al Turki, A. and others},
  title   = {{Smartphone and new tools for atrial fibrillation diagnosis: evidence for clinical applicability}},
  journal = {Minerva cardiology and angiology},
  year    = {2022},
  doi     = {10.23736/s2724-5683.22.05841-0},
  pmid    = {35212504},
  url     = {https://doi.org/10.23736/s2724-5683.22.05841-0}
}

Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.

How to read this study

Design: our record does not state a study design, so check the methods section of the original before weighing the result.
Size: the record gives no participant count. Look for one in the original before trusting a pattern.
Effect: the record gives no effect size, so the summary above cannot say how large any difference was.

What the evidence grade means here

This page is graded low. alzhub.org assigns the grade automatically from keywords in the abstract, not from reading the paper. Low means the abstract matched neither pattern. It is the default label, and it does not mean the work is poor; many sound lab and imaging papers land here. It can add at most 5 of the 100 points in the study score, and it is a label about design, not a verdict on whether the findings are true.

New to reading papers? Six questions to ask of any Alzheimer’s study · how we score.

Key findings

The early diagnosis of AF episodes, even if asymptomatic or clinically silent, is of pivotal importance to ensure prompt and adequate thromboembolic risk prevention therapies.
The development of technology is allowing new systematic mass screening possibilities, especially in patients with higher stroke risk.
The mobile health devices available for AF detection are: smartphones, wrist-worn, earlobe sensors and handheld ECG.
These devices showed a high accuracy in AF detection especially when a combined approach with single-lead ECG and photoplethysmography algorithms is used.
The use of wearable devices for AF screening is a feasible method but more head-to-head comparisons between mHealth and medical devices are needed to establish their comparative effectiveness across different study populations.

Study details

Evidence strengthLow

How this study scored 40/100

Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomized / blinded because the record does not state it. We have no data on journal's citation record, times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record and multicenter collaboration, so those were left out: it earned 23 of the 58 points we could judge it on, which is 40 out of 100.

Component	Points	Why
Journal tier	7 / 10	Tier 3 — peer-reviewed journal (Minerva cardiology and angiology)
Journal's citation record	— / 4	No journal record from OpenAlex — left out of this score
Study design	0 / 12	No study design recorded — scores zero, not guessed (not stated in the record — scored 0)
Strength of evidence	1 / 5	Rated “low” in our summary
Peer-review validation	10 / 10	Peer-reviewed. Published as an article in a named peer-reviewed journal.
How recent	3 / 5	2022 — within 6 year(s) of the newest study here
Sample size	0 / 4	Participant count not stated — scores zero (not stated in the record — scored 0)
Effect reported	0 / 3	No effect size reported — scores zero (not stated in the record — scored 0)
Studied in people	0 / 3	Not stated whether this was studied in people — scores zero (not stated in the record — scored 0)
Randomized / blinded	0 / 2	No randomization or blinding stated — scores zero (not stated in the record — scored 0)
Times cited	— / 7	No citation count (not found in OpenAlex) — left out of this score
Citations per year	— / 5	No citation count or no year — left out of this score
Impact for its field and year	— / 6	No field-weighted citation impact (OpenAlex has none yet) — left out of this score
Cited by studies here	— / 6	Not yet checked against this library's citation graph — left out of this score
Still being cited	— / 4	No yearly citation counts — left out of this score
Senior author's track record	— / 4	Senior author's record not available — left out of this score
Institution's track record	— / 3	No institution listed in OpenAlex — left out of this score
Multicenter collaboration	— / 3	Institutions not listed — left out of this score
Indexed in PubMed	2 / 2	Indexed in PubMed (PMID 35212504)
Free to read	0 / 2	Behind a paywall — scores zero
Points	23 / 58	Scored on 11 of 20 parts. We have no data for the rest, so they are left out: 23 of the 58 points we could judge it on is 40 out of 100.
Total	40 / 100	—

What each of these 20 components measures, and what this score is not →

Read the original

Free copy unknown: no free-copy check has an answer for this record yet. That does not mean it is paywalled.

Studies in the library that share something with this one. The line above each title says what.

Related studies in Cognitive tests and assessment from nearby years

Also tagged “applicability”

2 studies in the library carry the topic tag “applicability”; these are this study's neighbours in a fixed, alphabetical-by-hash tour of them, not the closest in content. All 2 tagged studies.

Studies sharing this one's topic tags

Similar studies

More on Cognitive tests and assessment

See all studies in Cognitive tests and assessment →