Decision analysis and personalized clinical tool for cerebrospinal fluid drains in thoracoabdominal aortic aneurysms repair
Bibliographic record
Abstract
BACKGROUND AND AIM: The routine use of cerebrospinal fluid (CSF) drainage in patients undergoing operative repair of thoracoabdominal aneurysms (TAAA) has been associated with decreased rates of spinal cord ischemia. The use of CSF drains is not without consequence, however with complications including subarachnoid hemorrhage, epidural hematoma, meningitis, and, in 1% of cases, death. To date, a decision analysis tool to help clinicians decide when to use and not to use a CSF drain does not exist. In this analysis, we set out to develop a decision analysis tool for CSF drain placement in patients undergoing operative repair of TAAA. METHODS: A Markov state-transition cohort model that compared TAAA repair with adjunctive CSF drain insertion to TAAA repair without drain insertion for the outcome of life expectancy was developed in TreeAge 2020. The cycle length was 1 month and the time horizon was 60 months. RESULTS: The use of a CSF drain was associated with improved 5-year life expectancy (3.21 ± 0.10 vs. 3.09 ± 0.11 life-years gained). In the sensitivity analysis that varied the effectiveness of a CSF drain (odds ratio closer to 1 = less effective), the use of a CSF drain resulted in higher life expectancy in almost all scenarios. CONCLUSIONS: The routine use of a CSF drain in patients undergoing TAAA repair is safe and effective, with few exceptions. This decision analysis tool can be used by clinicians to develop a personalized approach.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| 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".