Administration and effects of beta blockers and oxandrolone in severely burned adults: a <i>post hoc</i> analysis of the RE-ENERGIZE trial
Bibliographic record
Abstract
Abstract Background Prospective randomized trials in severely burned children have shown the positive effects of oxandrolone (OX), beta blockers (BB) and a combination of the two (BBOX) on hypermetabolism, catabolism and hyperinflammation short- and long-term post-burn. Although data on severely burned adults are lacking in comparison, BB, OX and BBOX appear to be commonly employed in this patient population. In this study, we perform a secondary analysis of an international prospective randomized trial dataset to provide descriptive evidence regarding the current utilization patterns and potential treatment effects of OX, BB and BBOX. Methods The RE-ENERGIZE (RandomizEd Trial of ENtERal Glutamine to minimIZE Thermal Injury, NCT00985205) trial included 1200 adult patients with severe burns. We stratified patients according to their receipt of OX, BB, BBOX or none of these drugs (None) during acute hospitalization. Descriptive statistics describe the details of drug therapy and unadjusted analyses identify predisposing factors for drug use per group. Association between OX, BB and BBOX and clinical outcomes such as time to discharge alive and 6-month mortality were modeled using adjusted multivariable Cox regressions. Results More than half of all patients in the trial received either OX (n = 138), BB (n = 293) or BBOX (n = 282), as opposed to None (n = 487, 40.6%). Per study site and geographical region, use of OX, BB and BBOX was highly variable. Predisposing factors for the use of OX, BB and BBOX included larger total body surface area (TBSA) burned, higher acute physiology and chronic health evaluation (APACHE) II scores on admission and younger patient age. After adjustment for multiple covariates, the use of OX was associated with a longer time to discharge alive [hazard ratio (HR) 0.62, confidence interval (CI) (0.47–0.82) per 100% increase, p = 0.001]. A higher proportion of days on BB was associated with lower in-hospital-mortality (HR: 0.5, CI 0.28–0.87, p = 0.015) and 6-month mortality (HR: 0.44, CI 0.24–0.82, p = 0.01). Conclusions The use of OX, BB and BBOX is common within the adult burn patient population, with its use varying considerably across sites worldwide. Our findings found mixed associations between outcomes and the use of BB and OX in adult burn patients, with lower acute and 6-month-mortality with BB and longer times to discharge with OX. Further research into these pharmacological modulators of the pathophysiological response to severe burn injury is indicated.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".