Complications in Minimally Invasive Cervical Spine Surgery–Tubular, Uniportal, and Biportal Endoscopic Surgery (2013–2024)
Bibliographic record
Abstract
STUDY DESIGN: Systematic review and proportional meta-analysis. OBJECTIVE: To assess and compare overall and specific complication rates across tubular, uniportal, and biportal minimally invasive techniques for cervical spine surgery. SUMMARY OF BACKGROUND DATA: The three primary minimally invasive spine surgery (MISS) approaches are tubular retractor-based surgery, uniportal endoscopic spine surgery, and biportal endoscopic spine surgery. Each has distinct benefits: tubular approaches rely on familiar instruments and surgical corridors, uniportal techniques reduce skin incision size and tissue disruption, and biportal methods preserve tissue while providing dual working channels that improve surgical access compared with uniportal approaches. However, the relative complication rates of tubular, uniportal, and biportal techniques remain unclear. METHODS: This review was registered in PROSPERO (CRD42024594335). Following PRISMA guidelines, we conducted a systematic review and meta-analysis. PubMed, Medline, Embase, and Cochrane Library were searched (January 2013-March 2024) for cervical MISS studies. Studies with ≥10 adult patients reporting UESS complication rates were included. Conference abstracts, reviews, meta-analyses, and non-English articles were excluded. Study quality was assessed using the Cochrane Risk of Bias tool and Newcastle-Ottawa Scale. A random-effects model was applied. RESULTS: Twenty-one studies (1299 patients) were included, with average patient ages ranging from 47 to 74.5 years and 64% male. All studies had low bias risk. Follow-up periods ranged from 3 to 33 months. The pooled complication rate for cervical MISS was 5% (95% CI: 3%-7%), with heterogeneity ( I ²=59%). Subgroup analysis showed complication rates of 4% (95% CI: 1%-10%, I ²=70%) for tubular, 6% (95% CI: 2%-12%, I2 =46%) for uniportal, and 5% (95% CI: 2%-8%, I2 =39%) for biportal. No statistically significant differences were found ( P =0.85). Nerve injury rates were higher with the uniportal approach (6%, 95% CI: 2%-16%, P =0.02). Dural tears (1%, 95% CI: 0%-2%, I ²=0%) and postoperative hematomas (0%, 95% CI: 0%-3%, I ²=0%) had low incidence, with no significant differences between approaches ( P = 0.61 and 0.78, respectively). CONCLUSIONS: Cervical MISS demonstrates a low overall complication rate, with tubular approaches showing a numerically lower risk, though differences were not statistically significant. Larger comparative studies are needed to provide more definitive results for better clinical application.
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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 | 0.015 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.040 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".