Postthoracotomy Pain Syndrome Following Surgery for Lung Cancer: Symptoms and Impact on Quality of Life
Bibliographic record
Abstract
Postthoracotomy pain syndrome (PTPS) is a common complication following thoracic surgery. Most studies examining the influence of PTPS on patient-reported symptoms include few patients managed using a minimally invasive approach. Associated sensory changes, potentially neuropathic in origin, are not well described. We therefore examined the symptoms and quality of life (QOL) of patients with and without PTPS who underwent a standard thoracotomy (n = 43) or minimally invasive surgery (n = 54). Patients in this prospective, cross-sectional study completed questionnaires to assess pain (McGill Pain Questionnaire), neuropathic symptoms (Neuropathic Symptom Questionnaire), symptom distress (Symptom Distress Scale), anxiety and depression (Hospital Anxiety and Depression Scale), and QOL (Functional Assessment Cancer Therapy-Lung). Excepting younger age (p = .009), no demographic or surgical characteristic differentiated patients with and without PTPS. Patients with PTPS described discomfort as pain only (15.1%), neuropathic symptoms only (30.2%) or pain and neuropathic symptoms (54.7%). Scores differed between patients with and without PTPS for symptom distress (p < .001), anxiety and depression (p < .001), and QOL (p = .009), with higher distress associated with PTPS. Despite new surgical techniques, PTPS remains common and results in considerable distress. A focused assessment is needed to identify all experiencing this condition, with referral to pain management specialists if symptoms persist.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".