ArticleCureus2021
Novel Software for Pain Drawing Analysis.
Article in Cureus, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
- Perceiving pain alters body perception: the effects of acute pain on body image and sensory testing.Pain · 2026Trial
- Sex and Sleep Quality Effects on the Relationship Between Sleep Disruption and Pain Sensitivity.European journal of pain (London, England) · 2025Article
- Spatial Distribution Dynamics of Sensory Disturbances in the Treatment of Obesity-Related Meralgia Paresthetica Using Transcutaneous Electrical Nerve Stimulation.Journal of clinical medicine · 2025Article
- Automated Pain Spots Recognition Algorithm Provided by a Web Service-Based Platform: Instrument Validation Study.JMIR mHealth and uHealth · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction Pain drawings (PDs) are an important component of the assessment of a patient with pain. Although analog pain drawings (APDs), such as pen-on-paper drawings, have been extensively used in clinical assessment and clinical research, there is a lack of digital pain drawing (DPD) software that would be able to quantify and analyze the digital pain distribution obtained by the patients. The aim of this work is to describe a method that can quantify the extent and location of pain through novel custom-built software able to analyze data from the digital pain drawings obtained from the patients. Methods The application analysis and software specifications were based on the information gathered from the literature, and the programmers created the custom-built software according to the published needs of the pain scientific community. Results We developed a custom-built software named "Pain Distribution," which, among others, automatically calculates the number of the pixels the patient has chosen and therefore quantifies the pain extent, provides the frequency distribution from a group of images, and has the option to select the threshold over which the patient is considered with central sensitization (CS). Additionally, it delivers results and statistics for both every image and the frequency distribution, providing mean values, standard deviations, and CS indicators, as well as the ability to export them in *.txt file format for further analysis. Conclusion A novel Pain Distribution application was developed, freely available for use in any setting, clinical, research, or academic.
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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.