ArticleAnnals of translational medicine2015
Data management by using R: big data clinical research series.
Article in Annals of translational medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Diagnostic accuracy of contrast enhanced ultrasound in patients with blunt abdominal trauma presenting to the emergency department: a systematic review and meta-analysis.Scientific reports · 2017Pooled it
- TSR: A User-Friendly R Shiny Application for Assessment of Optimal Blood Product Selection in ABO-Incompatible Hematopoietic Stem Cell Transplantation.Current medical science · 2023Article
- What role do patients prefer in medical decision-making?: a population-based nationwide cross-sectional study.BMJ open · 2021Article
- Use of ulinastatin was associated with reduced mortality in critically ill patients with sepsis.Journal of thoracic disease · 2019Article
- Enteral nutrition feeding in Chinese intensive care units: a cross-sectional study involving 116 hospitals.Critical care (London, England) · 2018Article
- Effect of team training on efficiency of trauma care in a Chinese hospital.The Journal of international medical research · 2018Article
- Univariate description and bivariate statistical inference: the first step delving into data.Annals of translational medicine · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Electronic medical record (EMR) system has been widely used in clinical practice. Instead of traditional record system by hand writing and recording, the EMR makes big data clinical research feasible. The most important feature of big data research is its real-world setting. Furthermore, big data research can provide all aspects of information related to healthcare. However, big data research requires some skills on data management, which however, is always lacking in the curriculum of medical education. This greatly hinders doctors from testing their clinical hypothesis by using EMR. To make ends meet, a series of articles introducing data management techniques are put forward to guide clinicians to big data clinical research. The present educational article firstly introduces some basic knowledge on R language, followed by some data management skills on creating new variables, recoding variables and renaming variables. These are very basic skills and may be used in every project of big data research.
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Registered trials
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.