Comprehensive characterization of intracranial hemorrhage in deep brain stimulation: a systematic review of literature from 1987 to 2023
Bibliographic record
Abstract
OBJECTIVE: Deep brain stimulation (DBS) is an effective treatment for medically refractory movement disorders and other neurological conditions. To comprehensively characterize the prevalence, locations, timing of detection, clinical effects, and risk factors of DBS-related intracranial hemorrhage (ICH), the authors performed a systematic review of the published literature. METHODS: PubMed, EMBASE, and Web of Science were searched using 2 concepts: cerebral hemorrhage and brain stimulation, with filters for English, human studies, and publication dates 1980-2023. The inclusion criteria were the use of DBS intervention for any human neurological condition, with documentation of hemorrhagic complications by location and clinical effect. Studies with non-DBS interventions, no documentation of hemorrhage outcome, patient cohorts of ≤ 10, and pediatric patients were excluded. The risk of bias was assessed using Centre for Evidence-Based Medicine Levels of Evidence. The authors performed proportional meta-analysis for ICH prevalence. RESULTS: A total of 63 studies, with 13,056 patients, met the inclusion criteria. The prevalence of ICH was 2.9% (fixed-effects model, 95% CI 2.62%-3.2%) per patient and 1.6% (random-effects model, 95% CI 1.34%-1.87%) per DBS lead, with 49.6% being symptomatic. The ICH rates did not change with time. ICH most commonly occurred around the DBS lead, with 16% at the entry point, 31% along the track, and 7% at the target. Microelectrode recording (MER) during DBS was associated with increased ICH rate compared to DBS without MER (3.5 ± 2.2 vs 2.1 ± 1.4; p[T ≤ t] 1-tail = 0.038). Other reported ICH risk factors include intraoperative systolic blood pressure > 140 mm Hg, sulcal DBS trajectories, and multiple microelectrode insertions. Sixty percent of ICH was detected at 24 hours postoperatively and 27% intraoperatively. The all-cause mortality rate of DBS was 0.4%, with ICH accounting for 22% of deaths. Single-surgeon DBS experience showed a weak inverse correlation (r = -0.27, p = 0.2189) between the rate of ICH per lead and the number of leads implanted per year. CONCLUSIONS: This study provides level III evidence that MER during DBS is a risk factor for ICH. Other risk factors include intraoperative systolic blood pressure > 140 mm Hg, sulcal trajectories, and multiple microelectrode insertions. Avoidance of these risk factors may decrease the rate of ICH.
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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 | 0.009 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.021 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".