Transition from acute to chronic postsurgical pain: risk factors and protective factors
Bibliographic record
Abstract
Most patients who undergo surgery recover uneventfully and resume their normal daily activities within weeks. Nevertheless, chronic postsurgical pain develops in an alarming proportion of patients. The prevailing approach of focusing on established chronic pain implicitly assumes that information generated during the acute injury phase is not important to the subsequent development of chronic pain. However, a rarely appreciated fact is that every chronic pain was once acute. Here, we argue that a focus on the transition from acute to chronic pain may reveal important cues that will help us to predict who will go on to develop chronic pain and who will not. Unlike other injuries, surgery presents a unique set of circumstances in which the precise timing of the physical insult and ensuing pain are known in advance. This provides an opportunity, before surgery, to identify the risk factors and protective factors that predict the course of recovery. In this paper, the epidemiology of chronic postsurgical pain is reviewed. The surgical, psychosocial, socio-environmental and patient-related factors that appear to confer a greater risk of developing chronic postsurgical pain are described. The genetics of chronic postsurgical pain are discussed with emphasis on known polymorphisms in human genes associated with chronic pain, genetic studies of rodent models of pain involving surgical approaches, the importance of developing accurate human chronic postsurgical pain phenotypes and the expected gains for chronic postsurgical pain medicine in the post-genomic era. Evidence is then reviewed for a preventive multimodal analgesic approach to surgery. While there is some evidence that chronic postsurgical pain can be minimized or prevented by an analgesic approach involving aggressive perioperative multimodal treatment, other studies fail to show this benefit. The transition of acute postoperative pain to chronic postsurgical pain is a complex and poorly understood developmental process, involving biological, psychological and social-environmental factors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".