The Association Between Comorbidities and Medical Complications for Adult Spinal Deformity Surgery: What Factors Have the Greatest Impact on Adverse Events and Outcomes?
Bibliographic record
Abstract
Study designNarrative review.ObjectiveIt is known that adult spinal deformity surgery (ASD) is associated with a high medical complication rate. However, it remains unclear which comorbidities impact these adverse events. The purpose of this study was to review the current knowledge regarding the association between postoperative medical complications and comorbidities.MethodsThe literatures in English were searched using PubMed. The search method involved a combination of keywords including "adult spinal deformity," "complication," and each specific risk factor. The search was limited to items listed in PubMed by February 15, 2022. The odds ratio (OR) of medical complications and mortality were evaluated.ResultsA total of 94 publications were reviewed. The risk factors with the higher OR for medical complications were frailty (OR: 4.4, 95% CI: 2.0-9.9), ASA class 4 (OR: 3.58, 95% CI: 2.00-6.39), male sex (OR: 3.52, 95% CI: 1.78-6.96), malnutrition (OR: 2.89, 95% CI: 1.69-4.93), and pathologic weight loss (OR: 2.38, 95% CI: 2.01-2.81). Similarly, the risk factors with the higher OR for mortality were liver disease (OR: 36.09, 95% CI: 16.16-80.59), pathologic weight loss (OR: 7.28, 95% CI: 4.36-12.14), renal failure (OR: 5.51, 95% CI: 2.57-11.82), chronic heart failure (OR: 5.67, 95% CI: 3.3-9.73), and age over 65 (OR: 3.49, 95% CI: 2.31-5.29).ConclusionThis review demonstrates the impact of a patient's comorbidities on postoperative medical complications. Understanding the level of risk involved can help to provide surgeons and patients with the information required to determine the suitability for surgery.
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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 | 0.010 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".