MétaCan
Menu
Back to cohort
Record W2040208716 · doi:10.1097/ajp.0b013e3181850dce

Hypervigilance as Predictor of Postoperative Acute Pain: Its Predictive Potency Compared With Experimental Pain Sensitivity, Cortisol Reactivity, and Affective State

2009· article· en· W2040208716 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClinical Journal of Pain · 2009
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHypervigilanceMedicinePotencyReactivity (psychology)AnesthesiaSensitivity (control systems)Acute painPostoperative painInternal medicinePsychiatryAnxietyPathology

Abstract

fetched live from OpenAlex

OBJECTIVES: Pain hypervigilance--a strong attentional bias toward pain--is thought to accompany chronic pain and modulate pain management. Its usefulness as predisposing factor for the development and maintenance of pain has been discussed. The aim of our study was to demonstrate the predictive power of hypervigilance for the development of acute postoperative pain. METHODS: Fifty-four young male patients were assessed 1 day before surgery (correction of chest malformation) on a range of psychologic predictors. These predictors included the assessment of hypervigilance (questionnaires as the Pain Catastrophizing Scale, Pain Anxiety Symptom Scale, the Pain Vigilance and Awareness Questionnaire, and the dot-probe task) and affective state, experimental pain sensitivity, and cortisol reactivity. Acute postoperative pain was assessed by ratings of pain intensity 1 week postsurgery and through the amount of analgesics [patient-controlled epidural analgesia (PCEA)] requested during the first days after surgery. RESULTS: Pain intensity was significantly explained (17% explained variance) by hypervigilance, whereas PCEA performance was not (10%). Adding all other predictors led to a significant increase of explained variance (35%) for pain ratings and a nonsignificant increase (19%) for PCEA. A more parsimonious solution with only heat pain threshold added led to a significant increase in explained variance (30%) for pain intensity. Hypervigilance was only moderately correlated with the other predictors. DISCUSSION: Hypervigilance proved to be a powerful predictor of subjective acute postoperative pain, but was less useful with regard to the amount of requested analgesics. The overlap with other psychologic predictors (affective state, experimental pain sensitivity, and cortisol reactivity) is sufficiently small to consider hypervigilance a promising supplement in psychologic predictor research.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.340
Teacher spread0.317 · 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