Evidence map›Paper›PMID 23626642›Full record

ArticleJournal of research in medical sciences : the official journal of Isfahan University of Medical Sciences2012

Human experimental pain models: A review of standardized methods in drug development.

K Sunil Kumar Reddy, M U R Naidu, P Usha Rani, T Ramesh Kumar Rao

Abstract read
In one paragraph

Article in Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 5 pooled it
–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

45 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
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  6. Effect ofNutrients · 2026
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  18. Nociplastic pain: controversy of the concept.The Korean journal of pain · 2025
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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

4 authors.

K Sunil Kumar ReddyDepartment of Clinical Pharmacology and Therapeutics, ICMR Advance Centre for Clinical Pharmacodynamic, Nizam's Institute of Medical Sciences, Hyderabad, India.
M U R Naidu
P Usha Rani
T Ramesh Kumar Rao

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human experimental pain models are essential in understanding the pain mechanisms and appear to be ideally suited to test analgesic compounds. The challenge that confronts both the clinician and the scientist is to match specific treatments to different pain-generating mechanisms and hence reach a pain treatment tailored to each individual patient. Experimental pain models offer the possibility to explore the pain system under controlled settings. Standardized stimuli of different modalities (i.e., mechanical, thermal, electrical, or chemical) can be applied to the skin, muscles, and viscera for a differentiated and comprehensive assessment of various pain pathways and mechanisms. Using a multimodel-multistructure testing, the nociception arising from different body structures can be explored and modulation of specific biomarkers by new and existing analgesic drugs can be profiled. The value of human experimental pain models is to link animal and clinical pain studies, providing new possibilities for designing successful clinical trials. Spontaneous pain, the main compliant of the neuropathic patients, but currently there is no human model available that would mimic chronic pain. Therefore, current human pain models cannot replace patient studies for studying efficacy of analgesic compounds, although being helpful for proof-of-concept studies and dose finding.

Indexed as

Analgesicsmultimodel-multitissuepain modelsproof-of-conceptspontaneous pain

Identifiers

PMID23626642
PMCPMC3634303

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.