The quality of research with real-world evidence.

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.

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

4 citing papers in PubMed.

1. Auriculotherapy in primary care: profile of graduates from a large-scale course.Revista de saude publica · 2025
   Article
2. Personalized venlafaxine dose prediction using artificial intelligence technology: a retrospective analysis based on real-world data.International journal of clinical pharmacy · 2024
   Article
3. Developing a machine learning model for predicting venlafaxine active moiety concentration: a retrospective study using real-world evidence.International journal of clinical pharmacy · 2024
   Article
4. Predicting Lapatinib Dose Regimen Using Machine Learning and Deep Learning Techniques Based on a Real-World Study.Frontiers in oncology · 2022
   Article

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

PubMed holds no abstract for this paper.

Indexed as