OPERATIVE TREATMENT OF ACUTE UNSTABLE CHEST WALL INJURIES DOES NOT REDUCE PAIN OR IN-HOSPITAL OPIOID REQUIREMENTS: A MULTICENTRED RANDOMIZED CONTROLLED TRIAL
Bibliographic record
Abstract
A previous randomized clinical trial evaluating operative versus nonoperative treatment of acute unstable chest wall injuries revealed more ventilator free days in operatively treated patients who were ventilated at the time of randomization. Our goal was to perform a secondary analysis to evaluate pain, and post-injury opioid requirements of operatively and non-operatively treated unstable chest wall injuries. Data from a previous multicenter prospective randomized clinical trial conducted from 2011-2019 were analyzed. Patients sustaining acute, unstable chest wall injuries were randomized to operative or non-operative treatment. In hospital pain medication logs were evaluated and daily morphine milligram equivalents (MME) were calculated. MME were compared between the two treatment groups. A linear mixed model analyzed the MME over time between the two groups for hospital days 1 through 14. A multiple linear regression analysis was then performed to determine variables associated with patient's average MME/day while in hospital. Variables analyzed included treatment group, injury severity scores (ISS), GCS at randomization, ventilation status at randomization, epidural, ICU length of stay and number of surgeries in the first 28 days. Two-hundred and seven patients were randomized in the original trial - 99 patients to non-operative treatment and 108 to operative treatment. MME data was available for 200 patients. There was no evidence of a difference in pain medication usage between the two groups at any of the time points examined (p=0.477). There was no clinical difference between generalized pain, chest wall pain, chest wall tightness or shortness of breath at any time post-operatively in patients treated surgically or non-operatively. This secondary analysis of a randomized clinical trial suggests that operative treatment of patients with unstable chest wall injuries does not decrease in-hospital daily opioid requirements. There was also no improvement of generalized pain, chest wall pain, chest wall tightness or shortness of breath symptoms. Surgical treatment of these injuries for pain management does not appear to be supported by the results of this study. Further work is needed to identify factors that are associated with increase in pain and opioid requirements.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".