Minimally Invasive Spine Lumbar Surgery in Obese Patients: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background Transforaminal lumbar interbody fusion (TLIF) is the treatment of choice for lumbar spinal stenosis and spondylolisthesis. The procedure can be performed through a traditional open approach (O-TLIF) or through minimally invasive techniques (MI-TLIF). Spinal surgeries in obese patients can pose risks, including increased rates of infection and thromboembolic events. Questions/Purposes We sought to systematically review the literature on the differences between MI-TLIF and O-TLIF in the obese patient in terms of complication rate, functional outcomes, blood loss, and length of hospital stay. Methods We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to systematically search PubMed, Embase, Web of Science, and the Cochrane Library for studies published through February 2019 and identified those comparing the outcomes of O-TLIF and MI-TLIF in obese patients. The primary outcome was complication rate (total, infections, dural tears); secondary outcomes were blood loss, length of hospital stay, and functional scores. Two authors independently reviewed the studies using the Newcastle-Ottawa Scale, and data were pooled using the Mantel-Haenszel random-effects model. Results In the sample of 430 patients, the average age was 53.5 years, there were 153 men and 203 women, and the average body mass index was 33.6. Complications were significantly higher in O-TLIF than in MI-TLIF (OR = 0.420 [95% CI: 0.199, 0.887]; I 2 = 45.20%). No difference was detected between the two groups for visual analog scale back pain scores and Oswestry Disability Index scores between the pre-operative and last follow-up visits (SMD = –0.034 [95% CI –0.695, 0.627]; I 2 = 62.14% and SMD = 0.617 [95% CI: –1.082, 2.316]; I 2 = 25%, respectively). Blood loss was significantly lower in MI-TLIF compared to O-TLIF (SMD = –426.736 [95% CI: –490.720, –362.752]; I 2 = 70.53%), as was the duration of hospital stay (SMD = –1.079 [95% CI: –1.591, –0.208]; I 2 = 84.3%). Conclusion MI-TLIF has equivalent efficacy to O-TLIF in obese patients at long-term follow-up. In addition, complication rate, blood loss, and length of hospital stay were lower in MI-TLIF than in O-TLIF.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.027 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".