To determine the diagnostic precision of combined Scheimpflug tomography and biomechanical analysis with optical coherence tomography (OCT) for detection of subclinical keratoconus (SCKC).

All subjects in this prospective, cross-sectional study underwent Scheimpflug tomography (Pentacam HR), air-puff tonometry (Corvis ST), and spectral-domain optical coherence tomography (Cirrus HD SD-OCT). The diagnosis of SCKC and keratoconus (KCN) were based on the Oculus Pentacam classification. Combined diagnostic models were developed using stepwise logistic regression (SLR). The Kruskal-Walli’s test evaluated group differences. Diagnostic accuracy was assessed by calculating the area under the curve (AUC).

A total of 137 participants comprising 73 females and 64 males, including 48 with KCN, 36 with SCKC, and 53 with normal corneas. The mean age for each group was 31.39±10.82y, 29.25±7.33y, and 30.45±8.03y, respectively. Most examined tomography, biomechanical, and pachymetry indices showed significant differences between KCN, SCKC, and normal eyes (P<0.05). Single tomographic biomechanical index (TBI) data was the most effective in identifying SCKC, achieving an AUC of 0.978 (P<0.001) with 100% sensitivity and 84.91% specificity. Combining SD-OCT and Pentacam HR data, the SLR model yielded superior accuracy for SCKC detection, with an AUC of 0.966 (86.11% sensitivity and 96.13% specificity). The highest accuracy for SCKC identification was attained by integrating data from all three devices, resulting in 0.990 accuracy (91.67% sensitivity; 100% specificity).

While current parameters accurately identify KCN, they are less effective for SCKC. Integrating Scheimpflug-based biomechanical and tomographic analysis with SD-OCT improves SCKC detection, supporting more accurate screening and earlier identification in patients with otherwise normal findings.