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Record W4393358963 · doi:10.3171/2024.1.jns232385

Comprehensive characterization of intracranial hemorrhage in deep brain stimulation: a systematic review of literature from 1987 to 2023

2024· review· en· W4393358963 on OpenAlexaff
Cletus Cheyuo, Artur Vetkas, Can Sarica, Suneil K. Kalia, Mojgan Hodaie, Andrés M. Lozano

Bibliographic record

VenueJournal of neurosurgery · 2024
Typereview
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsToronto Western HospitalKrembil FoundationUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineDeep brain stimulationPsychological interventionMEDLINEPediatricsInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.028
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0100.011
Bibliometrics0.0210.020
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.035
GPT teacher head0.326
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations25
Published2024
Admission routes1
Has abstractyes

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