Hemodynamic Perturbations in Deep Brain Stimulation Surgery: First Detailed Description
Bibliographic record
Abstract
Background Hemodynamic perturbations can be anticipated in deep brain stimulation (DBS) surgery and may be attributed to multiple factors. Acute changes in hemodynamics may produce rare but severe complications such as intracranial bleeding, transient ischemic stroke and myocardium infarction. Therefore, this retrospective study attempts to determine the incidence of hemodynamic perturbances (rate) and related risk factors in patients undergoing deep brain stimulation surgery. Material and Methods After institutional approval, all patients undergoing DBS surgery for the past ten years were recruited for this study. Demographic characteristics, procedural characteristics and intraoperative hemodynamic changes were noted. Event rate was calculated and the effect of all the variables on hemodynamic perturbations was analyzed by regression model. Results Total hemodynamic adverse events during DBS surgery was 10.8 (0-42) and treated in 57 % of cases. Conclusion Among all the perioperative variables, the baseline blood pressure including systolic, diastolic and mean arterial pressure was found to have highly significant effect on these intraoperative hemodynamic perturbations.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".