Mechanical Ventilation after Traumatic Spinal Cord Injury—A Multicentric Cohort Study-based Prediction Model for Weaning Success: The BICYCLE Score
Bibliographic record
Abstract
Abstract Rationale Limited information exists about the epidemiology, outcomes, and predictors of weaning from mechanical ventilation in patients with spinal cord injury. Objectives Our aim was to investigate predictors of weaning outcomes for patients with traumatic spinal cord injury (tSCI) and develop and validate a prognostic model and score for weaning success. Methods This was a registry-based, multicentric cohort study including all adult patients with tSCI requiring mechanical ventilation (MV) and admitted to one of the intensive care units (ICUs) of the Trauma Registry at St. Michael’s Hospital (Toronto, ON, Canada) and the Canadian Rick Hansen Spinal Cord Injury Registry between 2005 and 2019. The primary outcome was weaning success from MV at ICU discharge. Secondary outcomes included weaning success at Days 14 and 28, time to liberation from MV accounting for competing risk of death, and ventilator-free days at 28 and 60 days. Associations between baseline characteristics and weaning success or time to liberation from MV were measured using multivariable logistic and competing risk regressions. A parsimonious model to predict weaning success and ICU discharge was developed and validated via bootstrap. A prediction score for weaning success at ICU discharge was derived, and its discriminative ability was assessed using receiver operating characteristic curve analysis and compared with the Injury Severity Score (ISS). Results Of 459 patients analyzed, 246 (53.6%), 302 (65.8%), and 331 (72.1%) were alive and free of MV at Day 14, Day 28, and ICU discharge, respectively; 54 (11.8%) died in the ICU. Median time to liberation from MV was 12 days. Factors associated with weaning success were Blunt injury (odds ratio [OR], 2.96; P = 0.010), ISS (OR, 0.98; P = 0.025), Complete syndrome (OR, 0.53; P = 0.009), age in Years (OR, 0.98; P = 0.003), and Cervical LEsion (OR, 0.60; P = 0.045). The BICYCLE score showed a greater area under the curve than the ISS (0.689 [95% confidence interval (CI), 0.631–0.743] vs. 0.537 [95% CI, 0.479–0.595]; P < 0.0001). Factors predicting weaning success also predicted time to liberation. Conclusions In a large multicentric cohort, 72% of patients with tSCI were weaned and discharged alive from the ICU. Readily available admission characteristics can reasonably predict weaning success and help prognostication.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".