Evidence map›Paper›PMID 27774427›Full record

ArticleJournal of traditional and complementary medicine2016

Influence of traditional Chinese medicine syndrome groups on quality of life in women with metabolic syndrome.

Li-Wen Huang, I-Ju Chen, Chung-Hua Hsu

Abstract read
In one paragraph

Article in Journal of traditional and complementary medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. 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

3 authors.

Li-Wen HuangInstitute of Traditional Medicine, National Yang-Ming University, Taipei, Taiwan, ROC; Taipei Tzuchi Hospital, The Buddhist Tzuchi Medical Foundation, New Taipei City, Taiwan, ROC.
I-Ju ChenInstitute of Traditional Medicine, National Yang-Ming University, Taipei, Taiwan, ROC; Branch of Linsen and Chinese Medicine, Taipei City Hospital, Taipei, Taiwan, ROC.
Chung-Hua HsuInstitute of Traditional Medicine, National Yang-Ming University, Taipei, Taiwan, ROC; Branch of Linsen and Chinese Medicine, Taipei City Hospital, Taipei, Taiwan, ROC.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Traditional Chinese medicine (TCM; zhōng yī) syndrome groups are based on the symptoms of human diseases and guide the use of Chinese herbs. The aim of this study was to examine the effects of TCM syndrome groups on biochemical characteristics and quality of life (QOL) in women with metabolic syndrome (MS). Among the 1080 registered female patients screened at our outpatient clinic, a total of 322 women aged between 18 and 65 years and meeting the requirements of MS were enrolled. All the patients were asked to fill out a questionnaire on metabolic TCM syndrome groups and a questionnaire on the QOL, the Medical Outcomes Study (MOS) Short Form-12 (SF-12). Data of biochemical characteristics were collected at the same time. The present study showed MS women in TCM syndrome groups had significantly lower physical and mental component scores in SF-12 compared with those not in TCM syndrome groups. We also found MS patients in TCM syndrome groups, except Kidney Deficiency syndrome, showed higher body mass indexes, waist circumference, and hip circumference. However, there was almost no difference in most biochemical characteristics between TCM syndrome groups. The MS patients diagnosed as belonging to TCM syndrome groups had poor QOL.

Indexed as

Kidney Deficiency syndromeMetabolic syndromeObese womenQuality of lifeTraditional Chinese medicine syndrome groups

Identifiers

PMID27774427
PMCPMC5067845

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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.