IMPACT OF BODY HABITUS ON PERIOPERATIVE MORBIDITY ASSOCIATED WITH FUSION OF THE THORACOLUMBAR AND LUMBAR SPINE
Bibliographic record
Abstract
OBJECTIVE: Spinal fusion is performed in patients ranging from young and healthy to aged and frail. Although recent population trends in the United States are toward obesity, no large-scale study has evaluated how body habitus affects mortality, complications, and resource utilization for lumbar spine fusion. Such information is important for patient selection and to confirm the safety of such procedures in this population. METHODS: Data for 244 170 patients who underwent thoracolumbar or lumbar spine fusion for degenerative disease between 1988 and 2004 were collected from the Nationwide Inpatient Sample database, and subjects were grouped by surgical approach and body habitus. Multivariate logistic regression evaluated group effects on selected postoperative complications, length of stay, resource utilization, and discharge disposition. RESULTS: This study confirms that body habitus affects perioperative morbidity sustained by patients undergoing thoracolumbar or lumbar spine fusion. Demographic heterogeneity exists for race, geography, and number of diseased levels among body habitus groups, prompting application of multivariate logistic regression for outcomes. For all approaches, higher body mass index associated with increased transfusion requirements and likelihood of discharge to assisted living. Furthermore, morbidly obese patients undergoing posterior fusion sustained more wound complications and postoperative infections. CONCLUSION: This nationwide study describes inpatient complications encountered during fusion surgery in patients who are obese. For a given surgical approach, patients with higher body mass index sustain increased transfusion requirements and utilize more resources during thoracolumbar and lumbar spine fusion. Nevertheless, the findings of equivalent mortality, length of stay, and other complication rates suggest that patients who are obese remain safe surgical candidates.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".