Exploring Risk Factors and Neurophysiological Mechanisms Underlying the Development of Chronic Postsurgical Pain After Thoracic Surgery: Protocol for an Observational Feasibility Study
Bibliographic record
Abstract
BACKGROUND: Chronic postsurgical pain (CPSP) is a debilitating chronic pain condition that particularly impacts patients undergoing thoracic surgery, with incidence rates of up to 50%. The current understanding of risk factors is limited, and preoperative neurophysiological risk factors that may predict the development of CPSP have not yet been explored. Additionally, the specific neural mechanisms underlying the transition to CPSP are not well characterized. As a novel approach, we propose the use of transcranial magnetic stimulation and electroencephalography, along with other patient and surgical factors, to understand the neurophysiological mechanisms underlying the onset of CPSP after thoracic surgery. OBJECTIVE: The primary objective of this study is to evaluate the feasibility of our study design to inform a larger observational cohort study. Secondary objectives include exploring preoperative neurophysiological markers along with clinical characteristics associated with a higher risk of developing CPSP, as well as exploring postoperative differences in cortical function between patients who undergo thoracic surgery and develop CPSP compared with those who do not develop CPSP. METHODS: A total of 30 participants undergoing video-assisted thoracic surgery or a robotic-assisted thoracic lobectomy, wedge resection, segmental section, or minimally invasive esophagectomy, will be recruited to take part in 2 assessment sessions. The first assessment will take place 2 to 3 weeks before surgery, and the second assessment will take place 3 months after surgery, during which the CPSP diagnosis of each participant will be assessed by the experimenter using a validated definition. Feasibility outcomes include recruitment and retention rates of study participants. The secondary objectives include exploring factors associated with the development of CPSP, as well as examining postoperative differences in neurophysiological measures between patients with and without CPSP. We will consider the following neurophysiological measures for these objectives: transcranial magnetic stimulation measures of short-latency intracortical inhibition, cortical silent period, and motor evoked potentials; electroencephalography measures of resting band activity, event-related desynchronization, and corticomuscular coherence; and quantitative sensory testing of mechanical detection threshold and pressure pain threshold. RESULTS: This is an ethics-approved, ongoing study. Initial funding for this study was provided in March 2023. Recruitment for the study began in January 2025. A total of 22 participants have been recruited for the study. We anticipate completing data collection for this study by April 2026, with data analysis to follow. CONCLUSIONS: This protocol details our study design for a feasibility study exploring the neurophysiological markers and patient characteristics associated with the development of CPSP. Demonstration of feasibility is expected to lead to a larger study. Improved understanding of the risk factors and mechanisms underlying CPSP may inform the delivery of targeted therapies and preventive measures to reduce the incidence of CPSP after thoracic surgery. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/81042.
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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 | 0.027 | 0.017 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.028 | 0.007 |
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".