Evidence map›Paper›PMID 32664670›Full record

ArticleJournal of clinical medicine2020

Accuracy of a Symptom-Based Approach to Identify Hypertensive Emergencies in the Emergency Department.

Fabrizio Vallelonga, Federica Carbone, Francesco Benedetto, Lorenzo Airale, Silvia Totaro, Dario Leone, Anna Astarita, Eleonora Avenatti, Simona Maule, Franco Veglio and 2 more

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 17% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Guideline
  2. Hypertensive emergencies and urgencies: a preliminary report of the ongoing Italian multicentric study ERIDANO.Hypertension research : official journal of the Japanese Society of Hypertension · 2023
    Article
  3. Review
  4. Article
  5. Article
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

12 authors at 1 institution in 1 country.

Fabrizio VallelongaDivision of Internal Medicine and Hypertension, Department of Medical Sciences, University of Turin, Via Genova 3, 10126 Turin, Italy.ORCID 0000-0002-4628-6767
Federica CarboneDivision of Emergency Medicine, AOU Città Salute e Scienza, Torino, Department of Medical Sciences, University of Turin, 10126 Turin, Italy.
Francesco BenedettoDivision of Emergency Medicine, AOU Città Salute e Scienza, Torino, Department of Medical Sciences, University of Turin, 10126 Turin, Italy.
Lorenzo AiraleDivision of Internal Medicine and Hypertension, Department of Medical Sciences, University of Turin, Via Genova 3, 10126 Turin, Italy.
Silvia TotaroDivision of Emergency Medicine, AOU Città Salute e Scienza, Torino, Department of Medical Sciences, University of Turin, 10126 Turin, Italy.
Dario LeoneDivision of Emergency Medicine, AOU Città Salute e Scienza, Torino, Department of Medical Sciences, University of Turin, 10126 Turin, Italy.
Anna AstaritaDivision of Internal Medicine and Hypertension, Department of Medical Sciences, University of Turin, Via Genova 3, 10126 Turin, Italy.
Eleonora AvenattiDivision of Internal Medicine and Hypertension, Department of Medical Sciences, University of Turin, Via Genova 3, 10126 Turin, Italy.
Simona MauleDivision of Internal Medicine and Hypertension, Department of Medical Sciences, University of Turin, Via Genova 3, 10126 Turin, Italy.
Franco VeglioDivision of Internal Medicine and Hypertension, Department of Medical Sciences, University of Turin, Via Genova 3, 10126 Turin, Italy.
Enrico LupiaDivision of Emergency Medicine, AOU Città Salute e Scienza, Torino, Department of Medical Sciences, University of Turin, 10126 Turin, Italy.
Alberto MilanDivision of Internal Medicine and Hypertension, Department of Medical Sciences, University of Turin, Via Genova 3, 10126 Turin, Italy.ORCID 0000-0002-8863-8572
University of Turin · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA hierarchical symptoms-based diagnostic strategy relying on the presence of five main symptoms (chest pain, acute dyspnea, neurological symptoms, headache, visual impairment) was recently proposed to diagnose patients with hypertensive emergency. However, poor scientific evidence is available about the role of symptoms in both diagnosis and management of acute hypertensive disorders.

methodsData from 718 patients presenting to the emergency department of the "Città della Salute e della Scienza" Hospital of Turin with systolic blood pressure > 180 and/or diastolic blood pressure > 110 mm/Hg were retrospectively analyzed. The accuracy of the typical symptoms for identification of hypertensive emergencies was assessed.

resultsA total of 79 (11%) out of 718 patients were diagnosed with hypertensive emergencies (51% had cardiovascular and 49% neurovascular acute organ damage). Patients with hypertensive emergencies were older and with higher prevalence of coronary artery disease and chronic heart failure than patients with uncontrolled hypertension. Typical symptoms could discriminate true hypertensive emergency from uncontrolled hypertension with 64% accuracy, 94% sensitivity, and 60% specificity.

conclusionTypical symptoms might be used as a simple screening test (99% negative predictive value) in the emergency department to select for further evaluations of patients with suspected hypertensive emergencies among those with acute hypertensive disorders.

Indexed as

diagnostic approachhypertensive emergenciessymptoms accuracy

Identifiers

PMID32664670
PMCPMC7408741
OpenAlexW3041915178

What OpenQuestion holds

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LicenceCC BY
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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.