Evidence map›Paper›PMID 35446875›Full record

ArticlePloS one2022

Optimal opportunistic screening of atrial fibrillation using pulse palpation in cardiology outpatient clinics: Who and how.

Jordi Bañeras, Ivana Pariggiano, Eduard Ródenas-Alesina, Gerard Oristrell, Roxana Escalona, Berta Miranda, Pau Rello, Toni Soriano, Blanca Gordon, Yassin Belahnech and 4 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 27% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 4 institutions in 5 countries.

Jordi BañerasDepartment of Cardiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain.ORCID 0000-0002-7395-0862
Ivana PariggianoDivision of Clinical Cardiology, A.O.R.N. "Sant'Anna e San Sebastiano", Caserta, Italy.
Eduard Ródenas-AlesinaDepartment of Cardiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain.
Gerard OristrellDepartment of Cardiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain.
Roxana EscalonaDepartment of Cardiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain.
Berta MirandaDepartment of Cardiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain.
Pau RelloDepartment of Cardiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain.
Toni SorianoDepartment of Cardiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain.
Blanca GordonDepartment of Cardiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain.
Yassin BelahnechDepartment of Cardiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain.
Paolo CalabròDivision of Clinical Cardiology, A.O.R.N. "Sant'Anna e San Sebastiano", Caserta, Italy.ORCID 0000-0002-5018-830X
David García-DoradoDepartment of Cardiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain.
Ignacio Ferreira-GonzálezDepartment of Cardiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain.
Joaquim RaduaInstitut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.
Vall d'Hebron Hospital Universitari · ESUniversitat Autònoma de Barcelona · ESUniversity of Campania "Luigi Vanvitelli" · ITKing's College London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAtrial fibrillation (AF) remain a prevalent undiagnosed condition frequently encountered in primary care.

objectiveWe aimed to find the parameters that optimize the diagnostic accuracy of pulse palpation to detect AF. We also aimed to create a simple algorithm for selecting which individuals would benefit from pulse palpation and, if positive, receive an ECG to detect AF.

methodsNurses from four Cardiology outpatient clinics palpated 7,844 pulses according to a randomized list of arterial territories and durations of measure and immediately followed by a 12-lead ECG, which we used as the reference standard. We calculated the sensitivity and specificity of the palpation parameters. We also assessed whether diagnostic accuracy depended on the nurse's experience or on a list of clinical factors of the patients. With this information, we estimated the positive predictive values and false omission rates according to very few clinical factors readily available in primary care (age, sex, and diagnosis of heart failure) and used them to create the algorithm.

resultsThe parameters associated with the highest diagnostic accuracy were palpation of the radial artery and classifying as irregular those palpations in which the nurse was uncertain about pulse regularity or unable to palpate pulse (sensitivity = 79%; specificity = 86%). Specificity decreased with age. Neither the nurse's experience nor any investigated clinical factor influenced diagnostic accuracy. We provide the algorithm to select the ≥40 years old individuals that would benefit from a pulse palpation screening: a) do nothing in <60 years old individuals without heart failure; b) do ECG in ≥70 years old individuals with heart failure; c) do radial pulse palpation in the remaining individuals and do ECG if the pulse is irregular or you are uncertain about its regularity or unable to palpate it.

conclusionsOpportunistic screening for AF using optimal pulse palpation in candidate individuals according to a simple algorithm may have high effectiveness in detecting AF in primary care.

Indexed as

Atrial FibrillationCardiologyHeart FailureAdultAgedAmbulatory Care FacilitiesElectrocardiographyHumansMass ScreeningMiddle AgedPalpationPulse

Identifiers

PMID35446875
PMCPMC9022883
OpenAlexW4224225900

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.