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Record W4391380793 · doi:10.1213/ane.0000000000006848

A Prospective Cohort Study of Acute Pain and In-Hospital Opioid Consumption After Cardiac Surgery: Associations With Psychological and Medical Factors and Chronic Postsurgical Pain

2024· article· en· W4391380793 on OpenAlexaff
M. Gabrielle Pagé, Praveen Ganty, Dorothy Wong, Vivek Rao, James S. Khan, Karim S. Ladha, John G. Hanlon, Sarah Miles, Rita Katznelson, Duminda N. Wijeysundera, Joel Katz, Hance Clarke

Bibliographic record

VenueAnesthesia & Analgesia · 2024
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsYork UniversitySt. Michael's HospitalMount Sinai HospitalUniversity of TorontoUniversity Health NetworkToronto General HospitalUniversité de MontréalCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineProspective cohort studyOpioidChronic painAcute painAnesthesiaCohortCohort studyEmergency medicinePhysical therapySurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Understanding the association of acute pain intensity and opioid consumption after cardiac surgery with chronic postsurgical pain (CPSP) can facilitate implementation of personalized prevention measures to improve outcomes. The objectives were to (1) examine acute pain intensity and daily mg morphine equivalent dose (MME/day) trajectories after cardiac surgery, (2) identify factors associated with pain intensity and opioid consumption trajectories, and (3) assess whether pain intensity and opioid consumption trajectories are risk factors for CPSP. METHODS: Prospective observational cohort study design conducted between August 2012 and June 2020 with 1-year follow-up. A total of 1115 adults undergoing cardiac surgery were recruited from the preoperative clinic. Of the 959 participants included in the analyses, 573 completed the 1-year follow-up. Main outcomes were pain intensity scores and MME/day consumption over the first 6 postoperative days (PODs) analyzed using latent growth mixture modeling (GMM). Secondary outcome was 12-month CPSP status. RESULTS: Participants were mostly male (76%), with a mean age of 61 ± 13 years. Three distinct linear acute postoperative pain intensity trajectories were identified: "initially moderate pain intensity remaining moderate" (n = 62), "initially mild pain intensity remaining mild" (n = 221), and "initially moderate pain intensity decreasing to mild" (n = 251). Age, sex, emotional distress in response to bodily sensations, and sensitivity to pain traumatization were significantly associated with pain intensity trajectories. Three distinct opioid consumption trajectories were identified on the log MME/day: "initially high level of MME/day gradually decreasing" (n = 89), "initially low level of MME/day remaining low" (n = 108), and "initially moderate level of MME/day decreasing to low" (n = 329). Age and emotional distress in response to bodily sensations were associated with trajectory membership. Individuals in the "initially mild pain intensity remaining mild" trajectory were less likely than those in the "initially moderate pain intensity remaining moderate" trajectory to report CPSP (odds ratio [95% confidence interval, CI], 0.23 [0.06-0.88]). No significant associations were observed between opioid consumption trajectory membership and CPSP status (odds ratio [95% CI], 0.84 [0.28-2.54] and 0.95 [0.22-4.13]). CONCLUSIONS: Those with moderate pain intensity right after surgery are more likely to develop CPSP suggesting that those patients should be flagged early on in their postoperative recovery to attempt to alter their trajectory and prevent CPSP. Emotional distress in response to bodily sensations is the only consistent modifiable factor associated with both pain and opioid trajectories.

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)0.002
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 score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.007
GPT teacher head0.267
Teacher spread0.261 · 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

Citations12
Published2024
Admission routes1
Has abstractyes

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