American journal of ophthalmology · 2017
Keratoconus Screening Indices and Their Diagnostic Ability to Distinguish Normal From Ectatic Corneas.
Сравнительное исследованиеСтатьяНазвание и аннотация: Перевод пока не подготовлен
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Shetty Rohit, Rao Harsha, Khamar Pooja, Sainani Kanchan, Vunnava Krishnapoojita, Jayadev Chaitra, Kaweri Luci
Аннотация
PURPOSE: To compare the diagnostic ability of 3 Scheimpflug devices in differentiating normal from ectatic corneas.
DESIGN: Comparison of diagnostic instrument accuracy.
METHODS: This study included 42 normal, 37 subclinical keratoconic, and 51 keratoconic eyes seen in a tertiary eye care institute. Keratoconus screening indices were evaluated using the Pentacam (Oculus, Wetzlar, Germany), Galilei (Ziemer, Biel, Switzerland), and Sirius (Costruzione Strumenti Oftalmici, Florence, Italy). Sensitivity, specificity, and area under receiver operating characteristic curve (AUC) were calculated.
RESULTS: Highest sensitivity (100%) to diagnose keratoconus was seen for 6 parameters on Pentacam and 1 on Galilei. None of the indices in Sirius reached 100% sensitivity. For subclinical keratoconus, the highest sensitivity (100%) was seen for 2 parameters on Pentacam but for none of them on Galilei and Sirius. All parameters were strong enough to differentiate keratoconus (AUC > 0.9). On comparing the best parameters of all 3 machines, the AUC of the Belin/Ambrosio enhanced ectasia total derivation (BAD-D) and the inferior-superior value (ISV) of Pentacam were statistically similar to that of the keratoconus prediction index (KPI) and keratoconus probability (Kprob) of Galilei (P = .27) and 4.5 mm root mean square per unit area (RMS/A) back of Sirius (P = .55). When differentiating subclinical from normal corneas, BAD-D was similar to the surface regularity index (SRI) of Galilei (P = .78) but was significantly greater than the 8 mm RMS/A back of Sirius (P = .002).
CONCLUSION: Keratoconus indices measured by all 3 machines can effectively differentiate keratoconus from normal corneas. However, new cutoff values might be needed to differentiate subclinical from normal corneas.
DESIGN: Comparison of diagnostic instrument accuracy.
METHODS: This study included 42 normal, 37 subclinical keratoconic, and 51 keratoconic eyes seen in a tertiary eye care institute. Keratoconus screening indices were evaluated using the Pentacam (Oculus, Wetzlar, Germany), Galilei (Ziemer, Biel, Switzerland), and Sirius (Costruzione Strumenti Oftalmici, Florence, Italy). Sensitivity, specificity, and area under receiver operating characteristic curve (AUC) were calculated.
RESULTS: Highest sensitivity (100%) to diagnose keratoconus was seen for 6 parameters on Pentacam and 1 on Galilei. None of the indices in Sirius reached 100% sensitivity. For subclinical keratoconus, the highest sensitivity (100%) was seen for 2 parameters on Pentacam but for none of them on Galilei and Sirius. All parameters were strong enough to differentiate keratoconus (AUC > 0.9). On comparing the best parameters of all 3 machines, the AUC of the Belin/Ambrosio enhanced ectasia total derivation (BAD-D) and the inferior-superior value (ISV) of Pentacam were statistically similar to that of the keratoconus prediction index (KPI) and keratoconus probability (Kprob) of Galilei (P = .27) and 4.5 mm root mean square per unit area (RMS/A) back of Sirius (P = .55). When differentiating subclinical from normal corneas, BAD-D was similar to the surface regularity index (SRI) of Galilei (P = .78) but was significantly greater than the 8 mm RMS/A back of Sirius (P = .002).
CONCLUSION: Keratoconus indices measured by all 3 machines can effectively differentiate keratoconus from normal corneas. However, new cutoff values might be needed to differentiate subclinical from normal corneas.