Evidence map›Paper›PMID 37096200›Full record

ArticleInternational journal of general medicine2023

A Simplified Risk Score to Predict In-Hospital Newly-Diagnosed Atrial Fibrillation in Acute Ischemic Stroke Patients.

Thanachporn Saengmanee, Kitti Thiankhaw, Surat Tanprawate, Atiwat Soontornpun, Chayasak Wantaneeyawong, Chutithep Teekaput, Nopdanai Sirimaharaj, Angkana Nudsasarn

Open access · goldAbstract read
In one paragraph

Article in International journal of general medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 29% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

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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

8 authors at 1 institution in 1 country.

Thanachporn Saengmanee *Division of Neurology, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Kitti Thiankhaw *Division of Neurology, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.ORCID 0000-0002-0556-541X
Surat TanprawateDivision of Neurology, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Atiwat SoontornpunDivision of Neurology, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Chayasak WantaneeyawongDivision of Neurology, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Chutithep TeekaputDivision of Neurology, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Nopdanai SirimaharajDivision of Neurology, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Angkana NudsasarnThe Northern Neuroscience Centre, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Chiang Mai University · TH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Atrial fibrillation (AF) is a significant cause of stroke, and newly diagnosed AF (NDAF) is typically detected in the early period of stroke onset. We aimed to identify the factors associated with in-hospital NDAF in acute ischemic stroke patients and developed a simplified clinical prediction model. Methods: Patients with cryptogenic stroke aged 18 years or older who were admitted between January 2017 and December 2021 were recruited. NDAF was determined by inpatient cardiac telemetry. Univariable and multivariable regression analyses were used to evaluate the factors associated with in-hospital NDAF. The predictive model was developed using regression coefficients. Results: The study enrolled 244 eligible participants, of which 52 NDAFs were documented (21.31%), and the median time to detection was two days (1-3.5). After multivariable regression analysis, parameters significantly associated with in-hospital NDAF were elderly (>75 years) (adjusted Odds ratio, 2.99; 95% confident interval, 1.51-5.91; P = 0.002), female sex (2.08; 1.04-4.14; P = 0.04), higher admission national institute of health stroke scale (1.04; 1.00-1.09; P = 0.05), and presence of hyperdense middle cerebral artery sign (2.33; 1.13-4.79; P = 0.02). The area under the receiver operating characteristic curve resulted in 0.74 (95% CI 0.65-0.80), and the cut-point of 2 showed 87% sensitivity and 42% specificity. Conclusion: The validated and simplified risk scores for predicting in-hospital NDAF primarily rely on simplified parameters and high sensitivity. It might be used as a screening tool for in-hospital NDAF in stroke patients who initially presumed cryptogenic stroke.

Indexed as

acute ischemic strokeclinical prediction modelnewly diagnosed atrial fibrillationrisk scoring

Identifiers

PMID37096200
PMCPMC10122483
OpenAlexW4366347172

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.