Complications of cerebrospinal fluid drainage in thoracoabdominal aortic procedures
Bibliographic record
Abstract
BACKGROUND: Cerebrospinal fluid (CSF) drainage is used to reduce spinal cord ischemia (SCI) in patients undergoing thoracoabdominal aortic procedures. Recent literature has found high rates of complication associated with CSF drainage, which has led to changes in practice. The aim of this study was to investigate rates of CSF drain-related complications in patients undergoing a thoracoabdominal aortic procedure with perioperative placement of a CSF drain. METHODS: We conducted a single-centre retrospective cohort study. We defined major complications as intracranial hemorrhage, epidural hematoma or abscess, meningitis, and catheter retention requiring a reoperation. Minor complications assessed included drain-induced neurologic deficits, CSF leak, postdural puncture headache, asymptomatic blood in the CSF, drain failure, and catheter retention not requiring a reoperation. We recorded postoperative neurologic deficits as secondary outcomes. RESULTS: There were 129 patients who met the inclusion criteria. We found 5 cases of permanent paraplegia in the overall cohort (3.9%), with only 2 occurring in the patients with prophylactic CSF drains (1.6%). There were no major CSF drain-related complications. The rate of minor complications was 17.8%. We found no association between complication rates and indication for procedure or type of operation. CONCLUSION: The lack of major complications in this series adds to existing variability in recent literature and provides support for continued use of this adjunct for SCI prevention. Further research is required to identify the etiology of significant differences in CSF drain complication rates seen at other centres.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".