Evidence map›Paper›PMID 29888071›Full record

ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2018

Identifying Supplement Use Within Clinical Notes: An Applicationof Natural Language Processing.

Vivekanand Sharma, Indra Neil Sarkar

Abstract read
In one paragraph

Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. iDISK: the integrated DIetary Supplements Knowledge base.Journal of the American Medical Informatics Association : JAMIA · 2020
    Article
  2. Normalizing Dietary Supplement Product Names Using the RxNorm Model.Studies in health technology and informatics · 2019
    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

2 authors.

Vivekanand SharmaCenter for Biomedical Informatics, Brown University, Providence, Rhode Island.
Indra Neil SarkarCenter for Biomedical Informatics, Brown University, Providence, Rhode Island.

Funding

Tracking and Evaluation CoreU54GM115677 · NIGMS · BROWN UNIVERSITY · PI KOGUT, STEPHEN J · 2016 to 2025
$45.0M
Leveraging the EHR to Collect and Analyze Social, Behavioral & Familial FactorsR01LM011364 · NLM · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI CHEN, ELIZABETH S., MELTON-MEAUX, GENEVIEVE B · 2012 to 2015
$1.4M
In silico identification of phyto-therapiesR01LM011963 · NLM · UNIVERSITY OF VERMONT & ST AGRIC COLLEGE · PI LAW, WAYNE, SARKAR, INDRA N · 2014 to 2016
$1.2M
NIGMS NIH HHS U54 GM115677NLM NIH HHS R01 LM011364NLM NIH HHS R01 LM011963
6 · The paper itself

Abstract

Recent statistics indicate that the use of dietary supplements has increased over the years. Although being popular among consumers who use them for a variety of reasons, there have been limited clinical data-driven studies of the impact of dietary supplements on health outcomes. Challenges that impede such analyses in a comprehensive manner include either the sequestered nature of such data or their embedding within biomedical and clinical text. This study explored the feasibility to uncover patterns in the use of supplements, focusing on vitamin use among patients diagnosed with mental illness within patient records from the MIMIC-III database. The relevance of vitamin(s) was calculated at different levels of granularity and compared with association identified from Dietary Supplement Subset of MEDLINE. The results reveal insights into vitamin use for specific mental health related diagnosis and highlight challenges with identifying supplement information from clinical sources.

Identifiers

PMID29888071
PMCPMC5961809

What OpenQuestion holds

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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.