Extent of Fatty Infiltration of Lumbar Paraspinal Muscles as a Proxy for Frailty and Its Relationship with Perioperative Outcomes in Patients Undergoing Elective Spinal Surgery
Bibliographic record
Abstract
Study DesignRetrospective Cohort Study.ObjectivesThe purpose of this study was to identify the role of lumbar paraspinal muscle fatty infiltration using the Goutallier classification in predicting perioperative outcomes following elective lumbar surgery.MethodsA retrospective review was conducted on patients who underwent elective one- or two-level lumbar decompressions or instrumented fusions for degenerative pathology at a single institution over a 3 year period. Patients were stratified by procedure type. Data included demographics, perioperative outcomes, and the 5-item Modified Frailty Index (MFI-5). Fatty infiltration was graded at L4-5 using the Goutallier classification (intraclass correlation coefficient = 0.908). Opportunistic osteoporosis screening used computed tomography-based Hounsfield units (HU) at L1-2. The relationships between Goutallier grade, demographics, MFI-5 score, and postoperative outcomes were analyzed using Chi-squared analyses, Fisher's exact test, Analysis of Variance, and multivariable logistic and linear regression.ResultsIn total, 314 patients met the inclusion criteria. Mean age was 68.9 ± 8.6 years; mean Goutallier score was 2.2 ± 1.1 and MFI-5 was 1.3 ± 1.0. Goutallier score significantly correlated with age, American Society of Anesthesiologists grade, steroid use, MFI-5, discharge disposition, and 180 day complications and reoperation. Subgroup analyses revealed differing associations between Goutallier score and comorbidities/outcomes across procedure types. Multivariable regression confirmed Goutallier score as predictive of 180 day complications, reoperation, non-home discharge, and frailty.ConclusionGoutallier score is a predictive marker of frailty and postoperative outcomes in lumbar spine surgery. Goutallier classification is an effective tool that can aid in risk stratification for patients undergoing lumbar spinal surgery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".