Evidence map›Paper›PMID 39338218›Full record

ArticleJournal of personalized medicine2024

The Absence of Typical Stroke Symptoms and Risk Factors Represents the Greatest Risk of an Incorrect Diagnosis in Stroke Patients.

Rakesh Jalali, Aleksandra Bieniecka, Marek Jankowski, Patryk Stanisław Michel, Marta Popielarczyk, Mariusz Krzysztof Majewski, Jacek Zwiernik, Joanna Maria Harazny

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of personalized medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Rakesh JalaliDepartment of Emergency Medicine, School of Medicine, University of Warmia and Mazury, 10-719 Olsztyn, Poland.ORCID 0000-0002-2898-9434
Aleksandra BienieckaStudents' Research Group, Department of Human Physiology and Pathophysiology, School of Medicine, University of Warmia and Mazury, 10-719 Olsztyn, Poland.
Marek JankowskiStudents' Research Group, Department of Human Physiology and Pathophysiology, School of Medicine, University of Warmia and Mazury, 10-719 Olsztyn, Poland.
Patryk Stanisław MichelStudents' Research Group, Department of Human Physiology and Pathophysiology, School of Medicine, University of Warmia and Mazury, 10-719 Olsztyn, Poland.
Marta PopielarczykSchool of Public Health, University of Warmia and Mazury, 10-719 Olsztyn, Poland.
Mariusz Krzysztof MajewskiDepartment of Human Physiology and Pathophysiology, School of Medicine, University of Warmia and Mazury, 10-719 Olsztyn, Poland.ORCID 0000-0001-5818-7689
Jacek ZwiernikDepartment of Neurology and Neurosurgery, School of Medicine, University of Warmia and Mazury, 10-719 Olsztyn, Poland.
Joanna Maria HaraznyDepartment of Human Physiology and Pathophysiology, School of Medicine, University of Warmia and Mazury, 10-719 Olsztyn, Poland.ORCID 0000-0003-0124-0543

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundStroke is one of the most misdiagnosed conditions that causes serious medical disabilities. Its early and accurate diagnosis by the emergency team is crucial for the patient's survival. This study aimed to determine the percentage of brain strokes incorrectly diagnosed by paramedic teams and to analyze the factors influencing incorrect diagnoses.

methodsThe data of 103 patients, mean age of 68.4 ± 14.96 years, admitted in 2019 to hospital emergency departments of the two hospitals in Olsztyn, Poland, were analyzed retrospectively. All patient data were obtained from their information cards. The parameters of the patients misdiagnosed and accurately diagnosed by paramedics were analyzed with Odds Ratio (OR) calculations using IBM SPSS version 23 software.

resultsStroke and transient ischemic attack were recognized in 77 cases (74.8%). In 26 patients (25.2%), the diagnosis made in the ambulance differed from that made in the hospital ward. The analysis of the Odds Ratio (OR) has shown that typical stroke risk factors, if present in a patient, facilitate the correct diagnosis. The greatest source of misdiagnosis of stroke by the paramedic team was the lack of hemiplegia (OR = 6.0).

conclusionsThe absence of typical stroke risk factors and neurological stroke symptoms, such as smoking, hemiplegia, aphasia, hypercholesterolemia, arrhythmia, diabetes or a drooping corner of the mouth, constitutes a high risk of misdiagnosing stroke by the paramedic team.

Indexed as

emergency medicineincorrect diagnosisneurological stroke symptomsstrokestroke risk factors

Identifiers

PMID39338218
PMCPMC11433094

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.