Predictors of hospital-acquired pressure injuries in patients with complete spinal cord injury: a retrospective case–control study
Bibliographic record
Abstract
Abstract Background Despite current best practices, pressure injuries (PI) remain a devastating and prevalent hospital-acquired complication for patients with acute traumatic spinal cord injuries (SCIs). This study examined associations between risk factors for PI development in patients with complete SCI, such as norepinephrine dose and duration, and other demographic factors or lesion characteristics. Methods This case–control study included adults with acute complete SCIs ASIA-A, who were admitted to a level-one trauma center between 2014–18. A retrospective review was implement using data on patient and injury characteristics, including age, gender, level of SCI (cervical vs. thoracic), Injury Severity Score (ISS), length of stay (LOS) and mortality; presence/absence of PI during their acute hospital stay; and treatment factors such as spinal surgery, mean arterial pressure (MAP) targets, and vasopressor treatment. Multivariable logistic regression evaluated associations with PI. Results Eighty-two out of 103 eligible patients had complete data, and 30 (37%) developed PIs. Patient and injury characteristics, including age (Mean: 50.6; SD:21.3), location of SCI (48 cervical, 59%) and ISS (Mean 33.1; SD:11.8), did not differ between PI and non-PI groups. Logistic regression analysis revealed that male gender (OR:34.1; CI 95 :2.3–506.5, p = 0.010) and increased LOS (log-transformed; OR:20.5, CI 95 :2.8–149.9, p = 0.003) were associated with increased risk of PI. Having an order for a MAP > 80mmg (OR:0.05; CI 95 :0.01–0.30, p = 0.001) was associated with a reduced risk of PI. There were no significant associations between PI and duration of norepinephrine treatment. Conclusions Norepinephrine treatment parameters were not associated with development of PI, suggesting that MAP targets should be a focus for future investigations for SCI management. Increasing LOS should highlight the need for high-risk PI prevention and vigilance.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".