Evidence map›Paper›PMID 29700763›Full record

ArticleChinese journal of integrative medicine2019

Reliability, Accuracy, and Use Frequency of Evaluation Methods for Amount of Tongue Coating.

Su-Ryun Kim, Dong-Hyun Nam

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Article in Chinese journal of integrative medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Observational
  4. 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.

Su-Ryun KimDepartment of Biofunctional Medicine and Diagnosis, College of Korean Medicine, Sangji University, Wonju, 26339, Republic of Korea.
Dong-Hyun NamDepartment of Biofunctional Medicine and Diagnosis, College of Korean Medicine, Sangji University, Wonju, 26339, Republic of Korea. omdnam@sangji.ac.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo classify the evaluation methods for amount of tongue coating (TC) and investigate their reliability, accuracy, and frequency of use.

methodsArticles published from 1985 to 2015 were searched for evaluation methods for the amount of TC in PubMed and the Cochrane Library. Only clinical researches were included except protocol articles. The methods were classified according to their characteristics.

resultsFinally, 113 articles were selected. The evaluation method for the amount of TC from the articles was classified into 4 types: intuitive, specificative, computerized, and weighing TC. The reliability in the intuitive and specificative methods (κ =0.33-0.92) showed varying levels among the studies. In general, the amount of TC calculated by the specificative method (Spearman's r=0.68-0.80) was more strongly related to the directly measured value than to the value estimated by the computerized method (Pearson's r=0.442). The number of articles published on this topic has increased consistently, and the specificative method was the most frequently used. Despite the higher reliability of the computerized method, it has not been widely used.

conclusionsThe high prevalence of the specificative method would continue in clinical practice because of its convenience and accuracy. However, to establish higher reliability, the limitation of the subjectivity of the assessors should be overcome through calibration training. In the computerized method, novel algorithms are needed to obtain a higher accuracy so that it can help the practitioners confidently estimate the amount of TC.

Indexed as

HumansMedicine, Chinese TraditionalReproducibility of ResultsTongueaccuracyevaluation methodsfrequencyreliabilitytongue coating

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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.