Evidence map›Paper›PMID 34982723›Full record

Observational studyJMIR public health and surveillance2022

Comparison of Online Patient Reviews and National Pharmacovigilance Data for Tramadol-Related Adverse Events: Comparative Observational Study.

Susan Park, So Hyun Choi, Yun-Kyoung Song, Jin-Won Kwon

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in JMIR public health and surveillance, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 27% of its field
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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Pharmacovigilance in the digital age: gaining insight from social media data.Experimental biology and medicine (Maywood, N.J.) · 2025
    Review
  3. Article
  4. Article
  5. 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 at 2 institutions in 1 country.

Susan ParkBK21 FOUR Community-Based Intelligent Novel Drug Discovery Education Unit, College of Pharmacy, Research Institute of Pharmaceutical Sciences, Kyungpook National University, Daegu, Republic of Korea.ORCID 0000-0002-7082-8554
So Hyun ChoiDepartment of Statistics, Kyungpook National University, Daegu, Republic of Korea.ORCID 0000-0002-1703-9580
Yun-Kyoung SongCollege of Pharmacy, Daegu Catholic University, Gyeongsan-si, Gyeongbuk, Republic of Korea.ORCID 0000-0003-3687-4052
Jin-Won KwonBK21 FOUR Community-Based Intelligent Novel Drug Discovery Education Unit, College of Pharmacy, Research Institute of Pharmaceutical Sciences, Kyungpook National University, Daegu, Republic of Korea.ORCID 0000-0003-3467-7805
Kyungpook National University · KRDaegu Catholic University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTramadol is known to cause fewer adverse events (AEs) than other opioids. However, recent research has raised concerns about various safety issues.

objectiveWe aimed to explore these new AEs related to tramadol using social media and conventional pharmacovigilance data.

methodsThis study used 2 data sets, 1 from patients' drug reviews on WebMD (January 2007 to January 2021) and 1 from the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS; January 2016 to December 2020). We analyzed 2062 and 29,350 patient reports from WebMD and FAERS, respectively. Patient posts on WebMD were manually assigned the preferred terms of the Medical Dictionary for Regulatory Activities. To analyze AEs from FAERS, a disproportionality analysis was performed with 3 measures: proportional reporting ratio, reporting odds ratio, and information component.

resultsFrom the 869 AEs reported, we identified 125 new signals related to tramadol use not listed on the drug label that satisfied all 3 signal detection criteria. In addition, 20 serious AEs were selected from new signals. Among new serious AEs, vascular disorders had the largest signal detection criteria value. Based on the disproportionality analysis and patients' symptom descriptions, tramadol-induced pain might also be an unexpected AE.

conclusionsThis study detected several novel signals related to tramadol use, suggesting newly identified possible AEs. Additionally, this study indicates that unexpected AEs can be detected using social media analysis alongside traditional pharmacovigilance data.

Indexed as

Drug-Related Side Effects and Adverse ReactionsTramadolAdverse Drug Reaction Reporting SystemsHumansPharmacovigilanceUnited StatesUnited States Food and Drug AdministrationTramadoladverse effectdrug safetypharmacovigilancesocial mediatramadol

Identifiers

PMID34982723
PMCPMC8767477
OpenAlexW3216917910

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.