Evidence map›Paper›PMID 31725785›Full record

ArticlePloS one2019

Comparison of potential drug-drug interactions with metabolic syndrome medications detected by two databases.

Bovornpat Suriyapakorn, Pun Chairat, Suwanan Boonyoprakarn, Pimonwan Rojanarattanangkul, Wassana Pisetcheep, Natthaphon Hunsakunachai, Pornpun Vivithanaporn, Supakit Wongwiwatthananukit, Phisit Khemawoot

Abstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

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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

9 authors.

Bovornpat SuriyapakornDepartment of Pharmacy Practice, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, Thailand.ORCID 0000-0002-1081-8493
Pun ChairatOsotsala the Community Pharmacy, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, Thailand.
Suwanan BoonyoprakarnDepartment of Pharmacology and Physiology, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, Thailand.
Pimonwan RojanarattanangkulDepartment of Pharmacology and Physiology, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, Thailand.
Wassana PisetcheepDepartment of Pharmacology and Physiology, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, Thailand.
Natthaphon HunsakunachaiDepartment of Pharmacology and Physiology, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, Thailand.
Pornpun VivithanapornDepartment of Pharmacology, Faculty of Science, Mahidol University, Bangkok, Thailand.ORCID 0000-0002-2639-9545
Supakit WongwiwatthananukitDepartment of Pharmacy Practice, Daniel K. Inouye College of Pharmacy, University of Hawai'i, Hilo, Hawaii, United States of America.
Phisit KhemawootDepartment of Biochemistry and Microbiology, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, Thailand.ORCID 0000-0001-7994-4503

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDrug-drug interactions (DDIs) are one of the most common drug-related problems. Recently, electronic databases have drug interaction tools to search for potential DDIs, for example, Micromedex and Drugs.com. However, Micromedex and Drugs.com have different abilities in detecting potential DDIs, and this might cause misinformation to occur between patients and health care providers. METHODS AND

findingsThe aim of this study was to compare the ability of Micromedex and Drugs.com to detect potential DDIs with metabolic syndrome medications using the drug list from the U-central database, King Chulalongkorn Memorial Hospital in April 2019. There were 90 available drugs for the treatment of the metabolic syndrome and its associated complications, but six were not found in the Micromedex and Drugs.com databases; therefore, only 84 items were used in the present study. There were 1,285 potential DDI pairs found by the two databases. Micromedex reported DDIs of 724 pairs, while, Drugs.com reported 1,122 pairs. For the severity of the potential DDI reports, the same severity occurred between the two databases of 481 pairs (37.43%) and a different severity for 804 pairs (62.57%).

conclusionDrugs.com had a higher sensitivity to detect potential DDIs by approximately 1.5-fold, but Micromedex supplied more informative documentation for the severity classification. Therefore, pharmacists should use at least two databases to evaluate potential DDIs and determine the appropriate drug regimens for physician communications and patient consultations.

Indexed as

Drug InteractionsDatabases, PharmaceuticalDisease ManagementDrug-Related Side Effects and Adverse ReactionsFemaleHumansMaleMetabolic SyndromeSeverity of Illness Index

Identifiers

PMID31725785
PMCPMC6855424

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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.