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Record W7128734821 · doi:10.1097/brs.0000000000005505

Complications in Minimally Invasive Spine Surgery (2013–2024)

2025· article· en· W7128734821 on OpenAlexaboutno aff
Sean Inzerillo, Chibuikem A. Ikwuegbuenyi, Eesha Gurav, Noah Willett, Mousa Hamad, Ibrahim Hussain, Alan Hernández-Hernández, Galal Elsayed, Roger Härtl, Osama N. Kashlan

Bibliographic record

VenueSpine · 2025
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsnot available
Fundersnot available
KeywordsComplicationLumbar spineLumbarPalsyTearsMEDLINE

Abstract

fetched live from OpenAlex

STUDY DESIGN: Systematic review and proportional meta-analysis. OBJECTIVE: To evaluate overall and specific complication rates associated with lumbar uniportal endoscopic spine surgery (UESS) over the past decade. SUMMARY OF BACKGROUND DATA: UESS offers reduced tissue damage, faster recovery, and improved outcomes for lumbar spinal pathologies. However, its steep learning curve may contribute to variable complication rates, reported between 0% and 30%, highlighting the need for a pooled analysis. METHODS: We registered this review in the International Prospective Register of Systematic Reviews (CRD42024570377). We systematically searched PubMed, Medline, Embase, and Cochrane Library (January 2013-March 2024) following PRISMA guidelines. Studies with at least 10 adult patients that reported UESS complication rates were included. Conference abstracts, reviews, meta-analyses, non-English studies, and studies using micro-endoscopic, lateral, or oblique approaches were excluded. A random-effects model was used to pool complication rates. Study quality was assessed using the Cochrane Risk of Bias Tool and Newcastle-Ottawa Scale. Analyses were conducted with R Studio. RESULTS: Twenty-one studies with 1258 patients were included. Most studies were high quality and retrospective, with one randomized controlled trial. The patient's age ranged from 41.6 to 73.5 years, with 38.7% male, and follow-up periods between 6 and 26.5 months. The studies mainly focused on lumbar spinal stenosis treatment and were primarily conducted in China and Korea. The total pooled complication rate was 9.79% [95% CI (7.00%, 13.53%)]. Specific complication rates included dural tears (3.75%), nerve palsies (2.69%), postoperative hematomas (0.24%), surgical site infections (0.01%), and surgical revisions (2.39%). Total complication rates showed significant heterogeneity (I²=65.5%), whereas specific complications had low to moderate heterogeneity. CONCLUSIONS: Lumbar UESS demonstrated a 9.79% overall complication rate, with dural tears and nerve palsy being the most common. Despite UESS being generally safe, complication variability highlights the need for better patient selection and long-term outcome research.

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)0.019
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.037
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0180.045
Bibliometrics0.0100.009
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0020.002
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 head0.033
GPT teacher head0.320
Teacher spread0.287 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes1
Has abstractyes

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