Can We Predict Imbalance in Patients? Analysis of the CDC National Health and Nutrition Examination Survey.
Bassel G DieboSarah G StroudNeil V ShahJames MessinaJames M HongDaniel AlsoofKashif AnsariRenaud LafagePeter G PassiasVirginie LafageFrank J SchwabCarl B PaulinoRoy K AaronAlan H DanielsPublished in: Journal of clinical medicine (2023)
Understanding global body balance can optimize the postoperative course for patients undergoing spinal or lower limb surgical realignment. This observational cohort study aimed to characterize patients with reported imbalance and identify predictors. The CDC establishes a representative sample annually via the NHANES. All participants who said "yes" (Imbalanced) or "no" (Balanced) to the following question were identified from 1999-2004: "During the past 12 months, have you had dizziness, difficulty with balance or difficulty with falling?" Univariate analyses compared Imbalanced versus Balanced subjects and binary logistic regression modeling predicted for Imbalance. Of 9964 patients, imbalanced (26.5%) were older (65.4 vs. 60.6 years), with more females (60% vs. 48%). Imbalanced subjects reported higher rates of comorbidities, including osteoporosis (14.4% vs. 6.6%), arthritis (51.6% vs. 31.9%), and low back pain (54.4% vs 32.7%). Imbalanced patients had more difficulty with activities, including climbing 10 steps (43.8% vs. 21%) and stooping/crouching/kneeling (74.3% vs. 44.7%), and they needed greater time to walk 20 feet (9.5 vs. 7.1 s). Imbalanced subjects had significantly lower caloric and dietary intake. Regression revealed that difficulties using fingers to grasp small objects (OR: 1.73), female gender (OR: 1.43), difficulties with prolonged standing (OR: 1.29), difficulties stooping/crouching/kneeling (OR: 1.28), and increased time to walk 20 feet (OR: 1.06) were independent predictors of Imbalance (all p < 0.05). Imbalanced patients were found to have identifiable comorbidities and were detectable using simple functional assessments. Structured tests that assess dynamic functional status may be useful for preoperative optimization and risk-stratification for patients undergoing spinal or lower limb surgical realignment.