Evidence map›Paper›PMID 22965697›Full record

ReviewChinese journal of integrative medicine2012

Which research is needed to support clinical decision-making on integrative medicine?- Can comparative effectiveness research close the gap?

Claudia M Witt, Wen-jing Huang, Lixing Lao, Berman Bm

Abstract readReview
PubMed Publisher
In one paragraph

Review in Chinese journal of integrative medicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. The status of acupuncture and oriental medicine in the United States.Chinese journal of integrative medicine · 2014
    Article
  8. Conference report - samyukti 2013.Journal of Ayurveda and integrative medicine · 2013
    Article
  9. Article
  10. Article
  11. Evidence-based chinese medicine for hypertension.Evidence-based complementary and alternative medicine : eCAM · 2013
    Article
  12. 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

4 authors.

Claudia M WittCharité University Medical Center, Institute for Social Medicine, Epidemiology and Health Economics, Berlin 10117, Germany. claudia.witt@charite.de
Wen-jing Huang
Lixing Lao
Berman Bm

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In clinical research on complementary and integrative medicine, experts and scientists have often pursued a research agenda in spite of an incomplete understanding of the needs of end users. Consequently, the majority of previous clinical trials have mainly assessed the efficacy of interventions. Scant data is available on their effectiveness. Comparative effectiveness research (CER) promises to support decision makers by generating evidence that compares the benefits and harms of the best care options. This evidence, more generalizable than the evidence generated by traditional randomized controlled trials (RCTs), is better suited to inform real-world care decisions. An emphasis on CER supports the development of the evidence base for clinical and policy decision-making. Whereas in most areas of complementary and integrative medicine data on comparative effectiveness is scarce, available acupuncture research already contributes to CER evidence. This paper will introduce CER and make suggestions for future research.

Indexed as

Comparative Effectiveness ResearchDecision Support Systems, ClinicalIntegrative MedicineHumansMedicine, Chinese TraditionalPractice Guidelines as TopicRandomized Controlled Trials as Topic

Identifiers

What OpenQuestion holds

Textmetadata
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.