Evidence map›Paper›PMID 42588460›Full record

ReviewMolecules (Basel, Switzerland)2026

Classic Psychedelics for Treating Chronic Pain: Mechanism and Clinical Translation.

Hongyu Chen, Bowen Ke, Ruotian Jiang

Abstract readReview
In one paragraph

Review in Molecules (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Hongyu ChenDepartment of Anesthesiology, West China Hospital, Sichuan University, Chengdu 610000, China.
Bowen KeDepartment of Anesthesiology, West China Hospital, Sichuan University, Chengdu 610000, China.
Ruotian JiangDepartment of Anesthesiology, West China Hospital, Sichuan University, Chengdu 610000, China.ORCID 0000-0001-5322-6802

Funding

Brain Science and Brain-like Intelligence Technology-National Science and Technology Major Project 2025ZD0214904National Natural Science Foundation of China 82571390 and 82271249
6 · The paper itself

Abstract

Chronic pain is a complex disorder of central nervous system maladaptation, perpetuated not only by ascending nociceptive transmission but also by entrenched prior expectations. Conventional analgesics typically fail to reverse this cognitive rigidity and the ensuing pathological cycles. Classic psychedelics, however, are emerging as a promising avenue to help address this therapeutic impasse. This narrative review provides a comprehensive overview of the emerging science of psychedelics, encompassing their biological binding targets, potential neural mechanisms and clinical applications, in the context of chronic pain. We synthesize the therapeutic potential of classic psychedelics and critically examine the discrepancies between clinical outcomes and foundational mechanistic research. Furthermore, we evaluate key translational barriers, particularly compromised blinding and expectancy bias, and highlight the necessity for developing novel validation strategies. Ultimately, these new insights compel a fundamental rethinking of how biological neuroplasticity and subjective psychological experiences independently or synergistically drive analgesia, thereby offering a paradigm-shifting perspective for the translation of psychedelics into evidence-based analgesic therapeutics.

Indexed as

Chronic PainHallucinogensAnalgesicsAnimalsHumansNeuronal PlasticityTranslational Research, BiomedicalAnalgesicsHallucinogens5-HT receptoranalgesiachronic painclassic psychedelicsdefault mode networkneuroplasticity

Identifiers

PMID42588460
PMCPMC13467641

What OpenQuestion holds

Textmetadata
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.