Study protocol for a randomised controlled trial to investigate the effectiveness of thoracic epidural and paravertebral blockade in reducing chronic post-thoracotomy pain: 2 (TOPIC 2)
Bibliographic record
Abstract
BACKGROUND: Thoracotomy is considered one of the most painful surgical procedures and can cause debilitating chronic post-surgical pain lasting months or years postoperatively. Aggressive management of acute pain resulting from thoracotomy may reduce the likelihood of developing chronic pain. This trial compares the two most commonly used modes of acute analgesia provision at the time of thoracotomy (thoracic epidural blockade (TEB) and paravertebral blockade (PVB)) in terms of their clinical and cost-effectiveness in preventing chronic post-thoracotomy pain. METHODS: TOPIC 2 is a multi-centre, open-label, parallel group, superiority, randomised controlled trial, with an internal pilot investigating the use of TEB and PVB in 1026 adult (≥ 18 years old) patients undergoing thoracotomy in up to 20 thoracic centres throughout the UK. Patients (N = 1026) will be randomised in a 1:1 ratio to receive either TEB or PVB. During the first year, the trial will include an integrated QuinteT (Qualitative Research Integrated into Trials) Recruitment Intervention (QRI) with the aim of optimising recruitment and informed consent. The primary outcome is the incidence of chronic post-surgical pain at 6 months post-randomisation defined as 'worst chest pain over the last week' equating to a visual analogue score greater than or equal to 40 mm indicating at least a moderate level of pain. Secondary outcomes include acute pain, complications of regional analgesia and surgery, health-related quality of life, mortality and a health economic analysis. DISCUSSION: Both TEB and PVB have been demonstrated to be effective in the prevention of acute pain following thoracotomy and nationally practice is divided. Identification of which mode of analgesia is both clinically and cost-effective in preventing chronic post-thoracotomy pain could ameliorate the debilitating effects of chronic pain, improving health-related quality of life, facilitating return to work and caring responsibilities and resulting in a cost saving to the NHS. TRIAL REGISTRATION: NCT03677856 [ClinicalTrials.gov] registered September 19, 2018. https://clinicaltrials.gov/ct2/show/NCT03677856 . First patient recruited 8 January 2019.
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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 | 0.041 | 0.059 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.011 | 0.007 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.010 | 0.011 |
| Insufficient payload (model declined to judge) | 0.198 | 0.033 |
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".