MétaCan
Menu
Back to cohort
Record W2911738452 · doi:10.3171/2018.6.jns172690

Endoscopic versus open microvascular decompression for trigeminal neuralgia: a systematic review and comparative meta-analysis

2019· review· en· W2911738452 on OpenAlexaff
Nirmeen Zagzoog, Ahmed Attar, Radwan Takroni, Mazen Alotaibi, Kesh Reddy

Bibliographic record

VenueJournal of neurosurgery · 2019
Typereview
Languageen
FieldMedicine
TopicTrigeminal Neuralgia and Treatments
Canadian institutionsHamilton General Hospital
Fundersnot available
KeywordsMedicineMicrovascular decompressionTrigeminal neuralgiaSurgeryDecompressionCraniotomyRhizotomyParesisAnesthesia

Abstract

fetched live from OpenAlex

OBJECTIVE: Microvascular decompression (MVD) is commonly used in the treatment of trigeminal neuralgia (TN) with positive clinical outcomes. Fully endoscopic MVD (E-MVD) has been proposed as an effective minimally invasive alternative, but a comparative review of the two approaches has not been conducted. The authors performed a meta-analysis of studies, comparing patient outcome rates and complications for the open versus the endoscopic technique. METHODS: The PubMed/MEDLINE and Ovid databases were searched for studies published from database inception to 2017. The search terms used included, but were not limited to, "open microvascular decompression," "microvascular decompression for trigeminal neuralgia," and "endoscopic decompression for trigeminal neuralgia." Criteria for inclusion of studies in the meta-analysis were established as follows: adult patients, clinical studies with ≥ 10 patients (excluding case studies to obtain a higher volume of outcome rates), utilization of open MVD or E-MVD to treat TN, craniotomy and retrosigmoid incision, English-language studies, and articles that listed pain relief outcomes (complete, very good, partial, or absent), recurrence rate (number of patients), and complications (paresis, hearing loss, CSF leakage, cerebellar damage, infection, death). Relevant references from the chosen articles were also included. RESULTS: From a larger pool of 1039 studies, 23 articles were selected for review: 13 on traditional MVD and 10 on E-MVD. The total number of patients was 6749, of which 5783 patients (and 5802 procedures) had undergone MVD and 993 patients (and procedures) had undergone E-MVD. Analyzed data included postoperative pain relief outcome (complete or good pain relief vs partial or no pain relief), and rates of recurrence and complications including facial paralysis, weakness, or paresis; hearing loss; auditory and facial nerve damage; cerebrospinal fluid leakage; infection; cerebellar damage; and death.Good pain relief was achieved in 81% of MVD patients and 88% of E-MVD patients, with a mean recurrence rate of 14% and 9%, respectively. Average rates of reported complications were statistically lower in E-MVD than in MVD approaches, including facial paresis or weakness, hearing loss, cerebellar damage, infection, and death, whereas cerebrospinal fluid leakage was similar. The overall incidence of complications was 19% for MVD and 8% for E-MVD. CONCLUSIONS: The reviewed literature revealed similar clinical outcomes with respect to pain relief for MVD and E-MVD. The recurrence rate was lower in E-MVD studies, though not significantly so, and the incidence of complications, notably facial paresis and hearing loss, were statistically higher for MVD than for E-MVD. Based on these results, the use of endoscopy to perform MVD for TN appears to offer at least as good a surgical outcome as the more commonly used open MVD, with the possible added advantages of having a shorter operative time, smaller craniotomy, and lower recurrence rates. The authors advise caution in interpreting these data given the asymmetry in the sample size between the two groups and the relative novelty of the E-MVD approach.

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)0.010
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.022
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0170.029
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.449
GPT teacher head0.473
Teacher spread0.024 · 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 designMeta-analysis
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

Citations57
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of neurosurgerySame topicTrigeminal Neuralgia and TreatmentsFrench-language works237,207