Evidence map›Paper›PMID 35795736›Full record

ArticleComputational intelligence and neuroscience2022

Reliability Analysis of a Functional Diagnostic Test for Primary Hyperaldosteronism Based on Data Analysis.

Yan Wang, Jun Cai

Open access · hybridAbstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.1field-weighted citation impact, top 50% 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, 2 citations in OpenAlex.

  1. Article
  2. Observational
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

2 authors at 1 institution in 1 country.

Yan WangFuwai Hospital, Chinese Academy of Medical Sciences, Beijing 100037, China.
Jun CaiFuwai Hospital, Chinese Academy of Medical Sciences, Beijing 100037, China.ORCID https://orcid.org/0000-0001-5524-9047
Chinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Primary aldosteronism (PA) is one of the most common causes of secondary hypertension, with a prevalence of 12-20% in the hypertensive population. To determine the characteristic function of a fuzzy concept based on the epidemiological data, clinical manifestations, and auxiliary examinations of PA, the essence is to select a suitable domain and determine the affiliation of each element in the domain. The aldosterone/renin ratio was proposed to increase the detection rate of PA, which has the shortcoming of a high underdiagnosis rate when relying only on clinical manifestations. However, there is no unified standard for the diagnostic cut point, and there are differences in testing methods and diagnostic cut point values for different populations, which require different laboratories to establish appropriate cut points according to different regional populations to improve the diagnostic accuracy. In this article, we analyzed the reliability of functional diagnostic tests for PA based on data analysis and compared the sensitivity and specificity of different plasma aldosterone cut points for the diagnosis of PA in the 40 mg kibbutz test. The results showed that when post-saline PAC and post-cato PAC were used to confirm the diagnosis of proaldosterone, respectively, there was a similar subject working area under the curve between SSST and CCT, 0.89 and 0.78, respectively, with no significant difference in the area under the curve between the two (

Indexed as

HyperaldosteronismHypertensionAldosteroneData AnalysisDiagnostic Tests, RoutineHumansReninReproducibility of ResultsAldosteroneRenin

Identifiers

PMID35795736
PMCPMC9252634
OpenAlexW4285743974

What OpenQuestion holds

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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.