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Record W2951261316 · doi:10.1038/s41467-018-05859-1

Brain and psychological determinants of placebo pill response in chronic pain patients

2018· article· en· W2951261316 on OpenAlexfundno aff
Étienne Vachon‐Presseau, Sara Berger, Taha Abdullah, L. Q. Huang, Guillermo Cecchi, James W. Griffith, Thomas J. Schnitzer, A. Vania Apkarian

Bibliographic record

VenueNature Communications · 2018
Typearticle
Languageen
FieldNeuroscience
TopicPain Management and Placebo Effect
Canadian institutionsnot available
FundersNational Center for Complementary and Integrative HealthFonds de Recherche du Québec - SantéCanadian Institutes of Health Research
KeywordsPillPlaceboChronic painPlacebo responseMedicinePsychiatryPhysical therapyInternal medicineClinical psychologyAlternative medicinePharmacology

Abstract

fetched live from OpenAlex

The placebo response is universally observed in clinical trials of pain treatments, yet the individual characteristics rendering a patient a 'placebo responder' remain unclear. Here, in chronic back pain patients, we demonstrate using MRI and fMRI that the response to placebo 'analgesic' pills depends on brain structure and function. Subcortical limbic volume asymmetry, sensorimotor cortical thickness, and functional coupling of prefrontal regions, anterior cingulate, and periaqueductal gray were predictive of response. These neural traits were present before exposure to the pill and most remained stable across treatment and washout periods. Further, psychological traits, including interoceptive awareness and openness, were also predictive of the magnitude of response. These results shed light on psychological, neuroanatomical, and neurophysiological principles determining placebo response in RCTs in chronic pain patients, and they suggest that the long-term beneficial effects of placebo, as observed in clinical settings, are partially predictable.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.049
GPT teacher head0.368
Teacher spread0.318 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations129
Published2018
Admission routes1
Has abstractyes

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