Evidence map›Paper›PMID 41377917›Full record

ArticleFrontiers in cardiovascular medicine2025

Patient-needs-enhanced emergency nursing assessment framework accelerates time-critical care for non-traumatic chest pain.

Yan Sun, Xiaoxia Liu, Lili Shen, Fangfang Zhao, Kaiyun Xu

Abstract read
In one paragraph

Article in Frontiers in cardiovascular medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

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No citing paper in PubMed yet.

4 · The record

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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

5 authors.

Yan Sun *Department of Emergency Medicine, Third Affiliated Hospital of Naval Medical University, Shanghai, China.
Xiaoxia Liu *Department of Emergency Medicine, Third Affiliated Hospital of Naval Medical University, Shanghai, China.
Lili ShenDepartment of Emergency Medicine, Marine Corps Hospital of the People's Liberation Army, Chaozhou, Guangdong, China.
Fangfang ZhaoDepartment of Emergency Medicine, Third Affiliated Hospital of Naval Medical University, Shanghai, China.
Kaiyun XuDepartment of Emergency Medicine, Third Affiliated Hospital of Naval Medical University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Non-traumatic chest pain requires rapid Emergency Department (ED) triage, yet adherence to ECG ≤10 min and early troponin targets is inconsistent, standard nursing frameworks seldom prompt patient-needs that affect timeliness and documentation. The aim of this study is to determine whether implementing a patient-needs-enhanced Emergency Nursing Assessment Framework (ENAF), compared with usual care, increases the proportion of ED patients with non-traumatic chest pain receiving a 12-lead ECG within 10 min. Methods: This prospective single-center quasi-experimental before-after study was conducted in the T Third Affiliated Hospital of Naval Medical University from January 2023 to January 2025 and assigned to a control group and ENAF group. The ENAF group comprised (1) eight hours of nurse training, (2) an ENAF electronic template incorporating mandatory pain, anxiety, information-need and social-support items, and (3) a triage "rapid chest-pain kit". The primary endpoint was completion of a 12-lead ECG within 10 min of triage; secondary endpoints were door-to-troponin time, ≥2-point pain reduction at 30 min, documentation completeness, ED length of stay (LOS) and 30-day major adverse cardiac events (MACE). Multivariable logistic regression adjusted for age, sex, HEART score, arrival mode and peak ED census. Results: Of 372 screened patients, 340 met eligibility and were analyzed (170 control, 170 ENAF). Timely ECG completion increased from 60.0% to 78.2% (adjusted odds ratio 2.31, 95% CI: 1.47-3.63; Conclusions: Augmenting ENAF with a structured clinical-needs module significantly accelerates ECG acquisition, improves other process metrics and enhances nursing documentation while maintaining patient safety. Adoption of this nurse-led approach could strengthen ED chest-pain pathways in comparable resource-constrained settings, and multicenter validation are warranted to establish generalizability.

Indexed as

chest painelectrocardiogram timingemergency nursingpatient-centred checklistquality improvement

Identifiers

PMID41377917
PMCPMC12685830

What Socratic 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 Socratic graph.