Corneal biomechanical parameters as novel predictors of refractive stability after small incision lenticule extraction.

purposeTo evaluate the predictive value of preoperative corneal biomechanical parameters for refractive stability after small-incision lenticule extraction (SMILE) and to develop a multivariate model integrating biomechanical and anatomical factors for clinical application.

methodsThis prospective study analyzed 200 eyes from 100 patients undergoing SMILE. Preoperative and 6-month postoperative parameters were recorded, including diopter (D) of spherical and cylindrical refraction, intraocular pressure, slit-lamp examination, scanning laser ophthalmoscope, corneal topographic map, optical coherence tomography, corneal biomechanics and Pentacam imaging. Refractive stability was defined as spherical equivalent (SE) within ± 0.50 D at 6 months. Multivariate logistic regression with generalized estimating equations (GEE) was used to identify predictors of instability, accounting for inter-eye correlation. Model performance was assessed using receiver operating characteristic (ROC) curves and validated with bootstrapping. Statistical comparisons of area under the curve (AUC) were performed using the DeLong test.

resultsMean preoperative SE was − 4.83 ± 1.84 D. At 6 months postoperatively, 75.5% of eyes achieved SE within ± 0.50 D, 24.5% were unstable. In ROC analysis, preoperative SE exhibited the highest predictive value among the parameters assessed (AUC = 0.78, P < 0.01), with an optimal cutoff value of − 5.25 D (sensitivity 72.3%, specificity 75.6%). Multivariate GEE logistic regression identified SE (OR = 1.52 per diopter, P < 0.01), axial length (OR = 1.36 per mm, P < 0.01), corneal biomechanical index (CBI) > 0.05 (OR = 2.39, P < 0.01), younger age (OR = 1.28 per decade decrease, P = 0.042), and lenticule thickness > 110 μm (OR = 1.97, P < 0.01) as independent risk factors. The full multivariate model achieved an AUC of 0.88 (accuracy 83.5%, sensitivity 84.7%, specificity 82.8%), significantly outperforming the SE-only model (DeLong test, P = 0.02). Bootstrap validation yielded an optimism-corrected AUC of 0.85. Incorporating biomechanical profiling could refine preoperative risk stratification and guide surgical planning, such as adjusting lenticule thickness or considering alternative procedures in high-risk patients.

conclusionCorneal biomechanical properties, particularly CBI, are significant adjunctive predictors of post-SMILE refractive stability. Integrating these parameters with traditional clinical factors enhances predictive accuracy. CLINICAL TRIAL NUMBER: Not applicable.