Classification of older adults who underwent lumbar-related surgery using pre-operative biopsychosocial predictors and relationships with surgical recovery: An observational study conducted in the United States.
Alessandra Narciso GarciaCorey B SimonZidanyue Lexie YangDonna NiedzwieckiChad E CookOren GottfriedPublished in: Health & social care in the community (2021)
Lumbar surgery is a commonly prescribed intervention for low back pain but poses higher risks and worse outcomes for older adults. Identifying clinical phenotypes based on biopsychosocial factors may help identify older adults who are at greatest risk for poor postoperative recovery. This study aimed to (a) classify older adults who underwent lumbar surgery based on preoperative biopsychosocial factors, and (b) quantify the association between preoperative biopsychosocial classifications and 3 and 12 months postoperative improvement outcomes. Latent class analysis was used to identify biopsychosocial classifications in 10,283 individuals aged ≥60 from the Quality Outcomes Database (the United States, 2021-2018). Logistic regression models measured the association between biopsychosocial classifications and 3 and 12 months postoperative outcomes (back/leg pain intensity, disability and quality of life), adjusting for covariates. Three classes were identified based on 19 a priori biopsychosocial factors and were characterised as 'high-risk' (15%), 'physical-/social health-risk' (44%) and 'low-risk' (41%). The high-risk class demonstrated increased odds of failing to recover post-operatively compared to the other classes. Similarly, the physical-/social-risk class demonstrated increased odds of failing to recover in all outcomes and time points compared to the low-risk class. Biopsychosocial factors with higher prevalence in the high versus low-risk class were depression (92.5% vs. 10.6%), multiple morbidities (55.3% vs. 25.7%) and obesity (59.5% vs. 37.2%). This study introduces novel non-recovery phenotypes for older adults undergoing lumbar surgery and may lead to the development of tailored interventions to improve clinical care and outcomes for this population.
Keyphrases
- minimally invasive
- physical activity
- patients undergoing
- coronary artery bypass
- healthcare
- mental health
- health risk
- randomized controlled trial
- metabolic syndrome
- machine learning
- palliative care
- adipose tissue
- spinal cord injury
- emergency department
- depressive symptoms
- risk assessment
- coronary artery disease
- surgical site infection
- insulin resistance
- pain management
- risk factors
- climate change
- neuropathic pain
- electronic health record
- skeletal muscle
- high fat diet induced