Evidence map›Paper›PMID 28275620›Full record

ArticleAnnals of translational medicine2017

Hierarchical cluster analysis in clinical research with heterogeneous study population: highlighting its visualization with R.

Zhongheng Zhang, Fionn Murtagh, Sven Van Poucke, Su Lin, Peng Lan

Abstract readEditorial
In one paragraph

Article in Annals of translational medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed, 2 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

58 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  20. The Content of Volatile Organic Compounds inMolecules (Basel, Switzerland) · 2024
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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

5 authors.

Zhongheng ZhangDepartment of Emergency Medicine, Sir Run-Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China.
Fionn MurtaghBig Data Lab, University of Derby, Derby, UK;; Goldsmiths University of London, London, UK.
Sven Van PouckeDepartment of Anesthesia, Critical Care, Emergency Medicine and Pain Therapy, Ziekenhuis Oost-Limburg, Genk 3600, Belgium.
Su LinLiver Research Center, First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China.
Peng LanDepartment of Critical Care Medicine, Sir Run-Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Big data clinical research typically involves thousands of patients and there are numerous variables available. Conventionally, these variables can be handled by multivariable regression modeling. In this article, the hierarchical cluster analysis (HCA) is introduced. This method is used to explore similarity between observations and/or clusters. The result can be visualized using heat maps and dendrograms. Sometimes, it would be interesting to add scatter plot and smooth lines into the panels of the heat map. The inherent R

Indexed as

clinical researchdendrogramheat mapHierarchical cluster analysis (HCA)

Identifiers

PMID28275620
PMCPMC5337204

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.