Evidence map›Paper›PMID 33735384›Full record

ArticlePain medicine (Malden, Mass.)2021

AAAPT: Assessment of the Acute Pain Trajectory.

Emine O Bayman, Jacob J Oleson, Jennifer A Rabbitts

Abstract read
In one paragraph

Article in Pain medicine (Malden, Mass.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Observational
  2. Review
  3. Article
  4. Observational
  5. Article
  6. Association between acute pain trajectory and patient-reported outcomes at 6-months following lumbar surgery for patients with lumbar degenerative disease.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2024
    Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
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.

Emine O BaymanDepartment of Biostatistics, University of Iowa College of Public Health, Iowa City, Iowa, USA.
Jacob J OlesonDepartment of Biostatistics, University of Iowa College of Public Health, Iowa City, Iowa, USA.
Jennifer A RabbittsDepartment of Anesthesiology & Pain Medicine, University of Washington, Seattle, Washington, USA.

Funding

Mechanisms of transition from acute to chronic pain in youth undergoing musculoskeletal surgeryR01AR073780 · NIAMS · SEATTLE CHILDREN'S HOSPITAL · PI PALERMO, TONYA M, RABBITTS, JENNIFER · 2018 to 2022
$3.1M
Predicting Chronic Pain after Thoracic Surgery: A Bayesian ApproachR03NS080110 · NINDS · UNIVERSITY OF IOWA · PI BAYMAN, EMINE OZGUR · 2013 to 2014
$150k
NIAMS NIH HHS R01 AR073780NINDS NIH HHS R03 NS080110
6 · The paper itself

Abstract

objectiveDefine and contrast acute pain trajectories vs. the aggregate pain measurements, summarize appropriate linear and nonlinear statistical analyses for pain trajectories at the patient level, and present methods to classify individual pain trajectories. Clinical applications of acute pain trajectories are also discussed.

settingIn 2016, an expert panel involving the Analgesic, Anesthetic, and Addiction Clinical Trial Translations, Innovations, Opportunities, and Networks (ACTTION), American Pain Society (APS), and American Academy of Pain Medicine (AAPM) established an initiative to create a pain taxonomy, named the ACTTION-APS-AAPM Pain Taxonomy (AAAPT), for the multidimensional classification of acute pain. The AAAPT panel commissioned the present report to provide further details on analysis of the individual acute pain trajectory as an important component of comprehensive pain assessment.

methodsLinear mixed models and nonlinear models (e.g., regression splines and polynomial models) can be applied to analyze the acute pain trajectory. Alternatively, methods for classifying individual pain trajectories (e.g., using the 50% confidence interval of the random slope approach or using latent class analyses) can be applied in the clinical context to identify different trajectories of resolving pain (e.g., rapid reduction or slow reduction) or persisting pain. Each approach has advantages and disadvantages that may guide selection. Assessment of the acute pain trajectory may guide treatment and tailoring to anticipated symptom recovery. The acute pain trajectory can also serve as a treatment outcome measure, informing further management.

conclusionsApplication of trajectory approaches to acute pain assessments enables more comprehensive measurement of acute pain, which forms the cornerstone of accurate classification and treatment of pain.

Indexed as

Acute PainHumansPain MeasurementAcute PainLatent Class Analyses (LCA)Random InterceptRandom SlopeTrajectory

Identifiers

PMID33735384
PMCPMC7971475

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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.