Evidence map›Paper›PMID 34849084›Full record

ArticleYonago acta medica2021

A History of Recurrent Episodes of Prolonged Cough as a Predictive Value for Determining Cough Variant Asthma in a Primary Care Setting.

Masaaki Mikami, Katsuyuki Tomita, Akira Yamasaki

Open access · diamondAbstract read
In one paragraph

Article in Yonago acta medica, 2021. 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
0.4field-weighted citation impact, top 34% 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, 3 citations in OpenAlex.

  1. Article
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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

3 authors at 2 institutions in 1 country.

Masaaki MikamiHosshoji Internal Clinic, Nanbu 683-0351, Japan.
Katsuyuki TomitaDepartment of Respirology Medicine, National Hospital Organization Yonago Medical Center, Yonago 683-8518, Japan.
Akira YamasakiDivision of Medical Oncology and Molecular Respirology, School of Medicine, Faculty of Medicine, Tottori University, Yonago 683-8503, Japan.
National Hospital Organization · JPTottori University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMany patients visit primary care clinics with a complaint of cough. General practitioners (GPs) developed a list of the causative diseases of cough that can produce a patient's symptoms and signs. Then, the patients' medical histories were evaluated to determine whether the diagnosis of cough variant asthma (CVA) or post-infectious cough (PIC) could have been predicted.

methodsWe retrospectively investigated 195 outpatients with a complaint of cough. Medical histories of "recurrent episodes of prolonged cough" and "upper respiratory infection" were obtained during the initial visit. The accuracy of medical histories in predicting CVA and PIC was calculated on the area under the curve (AUC).

resultsAmong eligible patients with cough, PIC was diagnosed in 99 patients (50.8%), CVA in 40 patients (20.5%), upper airway cough syndrome in 28 patients (14.4%), and chronic obstructive pulmonary disease in 11 patients (5.6%). Among the patients with CVA and those with PIC, 93% and 12%, respectively, had a history of recurrent episodes of prolonged cough. For the diagnosis of CVA, having a history of recurrent episodes of prolonged cough showed a moderately accurate AUC (0.76, 95% CI: 0.71-0.82). On the other hand, for the diagnosis of PIC, having no history of recurrent episodes of prolonged cough also showed a moderately accurate AUC (0.87, 95% CI: 0.82-0.92).

conclusionThe medical history of recurrent episodes of prolonged cough is useful for the prediction of CVA as well as PIC.

Indexed as

cough variant asthmapost-infectious coughprolonged coughrecurrent episodes

Identifiers

PMID34849084
PMCPMC8612878
OpenAlexW3217593677

What OpenQuestion 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 OpenQuestion graph.