In-Hospital Mortality for the Elderly with Acute Traumatic Spinal Cord Injury
Bibliographic record
Abstract
As the incidence of traumatic spinal cord injury (tSCI) in the elderly rises, clinicians are increasingly faced with difficult discussions regarding aggressiveness of management, likelihood of recovery, and survival. Our objective was to outline risk factors associated with in-hospital mortality in elderly surgical and non-surgical patients following tSCI and to determine those unlikely to have a favorable outcome. Data from elderly patients (≥ 65 years of age) in the Canadian Rick Hansen SCI Registry from 2004 to 2017 were analyzed using descriptive analysis. Survival and mortality groups in each of the surgical and non-surgical group were compared to explore factors associated with in-hospital mortality and their impact, using logistical regression. Of 1340 elderly patients, 1018 had surgical data with 826 having had surgery. In the surgical group, the median time to death post-injury was 30 days with 75% dying within 50 days compared with 7 days and 20 days, respectively, in the non-surgical group. Significant predictors for in-hospital mortality following surgery are age, comorbidities, neurological injury severity (American Spinal Injury Association [ASIA] Impairment Scale [AIS]), and ventilation status. The odds of dying 50 days post-surgery are six times higher for patients ≥77 years of age versus those 65-76 years of age, five times higher for those with AIS A versus those with AIS B/C/D, and seven times higher for those who are ventilator dependent. An expected probability of dying within 50 days post-surgery was determined using these results. In-hospital mortality in the elderly after tSCI is high. The trend with age and time to death and the significant predictors of mortality identified in this study can be used to inform clinical decision making and discussions with patients and their families.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".