The Effect of Older Age on the Perioperative Outcomes of Spinal Fusion Surgery in Patients With Lumbar Degenerative Disc Disease With Spondylolisthesis: A Propensity Score-Matched Analysis
Bibliographic record
Abstract
BACKGROUND: Degenerative spondylolisthesis (DS) is often treated with lumbar spinal fusion (LSF). However, there is concern that the morbidity of LSF may be prohibitively high in older adults. OBJECTIVE: To evaluate the impact of advanced age on the safety of LSF for DS. METHODS: Patients who underwent LSF for DS were retrospectively identified from National Surgical Quality Improvement Program datasets for 2011 to 2015 using Current Procedural Terminology codes. Data on demographic characteristics, comorbidities, surgical factors, and 30-d morbidity and mortality were collected. Propensity score matching (nearest neighbor) was performed with age (<70 vs ≥70 yr) as the dependent variable and sex, type of fusion procedure, number of levels fused, diabetes, smoking, hypertension, and chronic steroid use as covariates. Outcomes were compared between age <70 and ≥70 groups. RESULTS: The study cohort consisted of 2238 patients (n = 1119, age <70; n = 1119, age ≥70). The 2 age groups were balanced for key covariates including sex, race, diabetes, hypertension, CHF, smoking, chronic steroid use, type of fusion, and number of levels. Rates of all complications were similar between younger and older age groups, except urinary tract infection, which was more frequent among the ≥70 age group (OR 2.32, P = .009). Further, patients in the older age group were more likely to be discharged to a rehabilitation (OR 2.94, P < .001) or skilled care (OR 3.66, P < .001) facility, rather than directly home (OR 0.25, P < .001). CONCLUSION: LSF may be performed safely in older adults with DS. Our results suggest older age alone should not exclude a patient from undergoing lumbar fusion for DS.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".