Influence of unilateral eyelid spasms and botulinum toxin treatment on intraocular pressure measured by transpalpebral tonometer.

PURPOSE: Eyelid spasms might be associated with elevated intraocular pressure (IOP) in hemifacial spasm (HFS) patients. IOP assessment using a Goldmann applanation tonometer (GAT) is often compromised by eyelid spasms. This study aimed to assess the effect of HFS on IOP measurements using the transpalpebral tonometer Diaton® before and after treatment with botulinum toxin type A (BTX-A) and compared Diaton® and GAT measurements after treatment with BTX-A. METHODS: IOP measurements were obtained with Diaton® in 27 patients with moderate-to-severe HFS before and after treatment with BTX-A. After treatment, the IOP was also measured using GAT and the results were compared with the ones measured with a Diaton®. The patients underwent automated perimetry, OCT, and pachymetry for screening to glaucoma. RESULTS: Mean IOP with Diaton® was 11 ± 3.42 mmHg before treatment in the affected eye and 9 ± 2.98 mmHg in the contralateral eye. This difference was statistically significant (P = 0.012). However, after treatment with BTX-A, no interocular difference was found in IOP obtained with Diaton® (P = 0.204) or GAT (P = 0.971). Comparison between GAT and Diaton® measurements showed no significant differences after BTX-A treatment between the affected (P = 0.212) and contralateral eye (P = 0.971). CONCLUSIONS: A significant reduction in IOP measurements on the affected side of HFS patients was observed after treatment with BTX-A, demonstrating that eyelid spasms may increase the IOP. No significant difference was observed between Diaton® and GAT measurements after the application of BTX-A. No differences were found in automated perimetry, OCT, and CCT when comparing affected eyes with contralateral eyes.

Traboulsi syndrome without features of Marfan syndrome caused by a novel homozygous ASPH variant associated with a heterozygous FBN1 variant.

BACKGROUND: Traboulsi syndrome is a rare disease clinically characterized by facial dysmorphism, abnormal spontaneous filtering blebs, ectopia lentis (EL) and multiple anterior segment abnormalities. MATERIAL AND METHODS: An 18-year-old female was referred to the Emergency Service of Hospital São Geraldo (HSG) claiming decreased right eye (RE) visual acuity associated with ocular pain that was noticed approximately 2 months earlier. She underwent a complete ophthalmic and physical examination including hands, ankle, wrist and chest X-ray, abdominal ultrasound, echocardiogram and genetic analysis (whole-exome sequencing). RESULTS: The ophthalmic examination revealed a high myopia with spherical equivalent of - 9.50 D and best corrected visual acuity (BCVA) of 20/60 in RE and - 9.25 D with BCVA of 20/30 in the left eye (LE). Slit-lamp examination showed normal conjunctiva in both eyes (BE) and a superior-temporal cystic lesion in RE and nasal in LE; the flat anterior chamber in BE with the transparent crystalline lens touches the central corneal endothelium in the RE. Fundoscopy suggested glaucoma as the cup/disc ratio was 0.7, although the intraocular pressure (IOP) was 10 mmHg in BE without medication. Validation of data from whole exome demonstrated a novel splicing homozygous pathogenic variant (PV) (c.1765-1G>A) of the ASPH gene as well as a heterozygous variant of unknown significance (VUS) of the FBN1 gene (c.6832C>T). CONCLUSION: We here report a novel splice-affecting homozygous pathogenic variant in the ASPH gene that was detected in a Brazilian patient with clinical features of Traboulsi syndrome.

Outcomes of early versus delayed trabeculotomy for primary congenital glaucoma.

PURPOSE: In patients with primary congenital glaucoma (PCG), elevated intraocular pressure (IOP) causes abnormal eye growth. This study compared the outcomes of children with PCG who underwent ab externo trabeculotomy (TROC) at age ≤ 6 months (early TROC) and of those who underwent TROC at age > 6 months (delayed TROC). METHODS: Intraocular pressure, horizontal corneal diameter (HCD), central corneal thickness (CCT) and axial length (AL) were compared before TROC and at 1-, 3-, 6- and 12-month follow-up visits between the groups of children who underwent TROC until or after 6 months of age. The ALs of these groups were also compared with the ALs of healthy age-matched eyes examined under the same conditions. RESULTS: Trabeculotomy was performed in 43 children: 18 (33 eyes) aged 6 months (group 1) and 25 (37 eyes) aged >6 months (group 2); the mean ages were 86.56 ± 53.64 and 504.48 ± 448.14 days, respectively. The mean pre- and 12-month postoperative IOP values were 15.97 ± 4.78/16.62 ± 4.85 and 9.77 ± 2.88/10.93 ± 4.83 mmHg, respectively. Delayed TROC was associated with abnormal AL in 31 (88.6%) out of 37 eyes, while after early TROC, only 13 (41.9%) out of 33 eyes had abnormal AL (chi-square, 8.00; p = 0.03). In multivariable analysis, each 1-mmHg increase in preoperative IOP was associated with a 0.25-mmHg increase at 12 months (p = 0.04). On average, the mean IOP of the delayed TROC group was higher than that of the early TROC group by 3.72 mmHg at postoperative month 12 (95% CI = 0.44-6.99; p = 0.02). CONCLUSION: Compared with delayed TROC, early TROC is associated with reduced IOP and substantially reduced incidence of abnormal AL at postoperative month 12.

Use of machine learning to predict the risk of early morning intraocular pressure peaks in glaucoma patients and suspects / Uso de aprendizado de máquina para predizer o risco de picos de pressão intraocular no início da manhã em pacientes com glaucoma e suspeitos

ABSTRACT Purpose: To use machine learning to predict the risk of intraocular pressure peaks at 6 a.m. in primary open-angle glaucoma patients and suspects. Methods: This cross-sectional observational study included 98 eyes of 98 patients who underwent a 24-hour intraocular pressure curve (including the intraocular pressure measurements at 6 a.m.). The diurnal intraocular pressure curve was defined as a series of three measurements at 8 a.m., 9 a.m., and 11 a.m. from the 24-hour intraocular pressure curve. Two new variables were introduced: slope and concavity. The slope of the curve was calculated as the difference between intraocular pressure measurements at 9 a.m. and 8 a.m. and reflected the intraocular pressure change in the first hour. The concavity of the curve was calculated as the difference between the slopes at 9 a.m. and 8 a.m. and indicated if the curve was bent upward or downward. A classification tree was used to determine a multivariate algorithm from the measurements of the diurnal intraocular pressure curve to predict the risk of elevated intraocular pressure at 6 a.m. Results: Forty-nine (50%) eyes had intraocular pressure measurements at 6 a.m. >21 mmHg, and the median intraocular pressure peak in these eyes at 6 a.m. was 26 mmHg. The best predictors of intraocular pressure measurements >21 mmHg at 6 a.m. were the intraocular pressure measurements at 8 a.m. and concavity. The proposed model achieved a sensitivity of 100% and a specificity of 86%, resulting in an accuracy of 93%. Conclusions: The machine learning approach was able to predict the risk of intraocular pressure peaks at 6 a.m. with good accuracy. This new approach to the diurnal intraocular pressure curve may become a widely used tool in daily practice and the indication of a 24-hour intraocular pressure curve could be rationalized according to risk stratification.

RESUMO Objetivo: Utilizar aprendizado de máquina para predizer o risco de picos de pressão intraocular às 6 AM em pacientes com glaucoma primário de ângulo aberto e suspeitos. Métodos: Esse estudo observacional transversal incluiu 98 olhos de 98 pacientes submetidos à curva de 24 horas de pressão intraocular (incluindo as medidas às 6 AM). A curva diurna de pressão intraocular foi definida como uma série de três medidas da curva de 24 horas de pressão intraocular às 8 AM, às 9 AM e às 11 AM. Duas novas variáveis foram apresentadas: inclinação e concavidade. A inclinação da curva às 8 AM foi calculada como a diferença entre pressão intraocular às 9 AM e 8 AM e reflete a variação da pressão intraocular na primeira hora. A concavidade da curva foi calculada como a diferença entre as inclinações às 9 AM e às 8 AM e pode ser para cima ou para baixo. Uma árvore de classificação foi usada para determinar um algoritmo multivariado a partir das medidas da curva diurna para prever o risco de pressão intraocular elevada às 6 AM. Resultados: Quarenta e nove (50%) olhos apresentaram pressão intraocular às 6 AM >21 mmHg e a mediana do pico de pressão intraocularPIO foi 26 mmHg. Os melhores preditores de pressão intraocular às 6 AM >21 mmHg foram a pressão intraocular às 8 AM e a concavidade. O modelo proposto apresentou uma sensibilidade de 100% e uma especificidade de 86%, com uma acurácia de 93%. Conclusões: A abordagem de aprendizado de máquina foi capaz de prever o risco de picos de pressão intraocular às 6 AM com uma boa acurácia. Essa nova abordagem para a curva diurna de pressão intraocular pode se tornar uma ferramenta amplamente utilizada na prática clínica e a indicação da curva de 24 horas de pressão intraocular pode ser racionalizada de acordo com a estratificação de risco.

Use of machine learning to predict the risk of early morning intraocular pressure peaks in glaucoma patients and suspects.

PURPOSE: To use machine learning to predict the risk of intraocular pressure peaks at 6 a.m. in primary open-angle glaucoma patients and suspects. METHODS: This cross-sectional observational study included 98 eyes of 98 patients who underwent a 24-hour intraocular pressure curve (including the intraocular pressure measurements at 6 a.m.). The diurnal intraocular pressure curve was defined as a series of three measurements at 8 a.m., 9 a.m., and 11 a.m. from the 24-hour intraocular pressure curve. Two new variables were introduced: slope and concavity. The slope of the curve was calculated as the difference between intraocular pressure measurements at 9 a.m. and 8 a.m. and reflected the intraocular pressure change in the first hour. The concavity of the curve was calculated as the difference between the slopes at 9 a.m. and 8 a.m. and indicated if the curve was bent upward or downward. A classification tree was used to determine a multivariate algorithm from the measurements of the diurnal intraocular pressure curve to predict the risk of elevated intraocular pressure at 6 a.m. RESULTS: Forty-nine (50%) eyes had intraocular pressure measurements at 6 a.m. >21 mmHg, and the median intraocular pressure peak in these eyes at 6 a.m. was 26 mmHg. The best predictors of intraocular pressure measurements >21 mmHg at 6 a.m. were the intraocular pressure measurements at 8 a.m. and concavity. The proposed model achieved a sensitivity of 100% and a specificity of 86%, resulting in an accuracy of 93%. CONCLUSIONS: The machine learning approach was able to predict the risk of intraocular pressure peaks at 6 a.m. with good accuracy. This new approach to the diurnal intraocular pressure curve may become a widely used tool in daily practice and the indication of a 24-hour intraocular pressure curve could be rationalized according to risk stratification.

Comparison of Tono-Pen Avia and Handheld Applanation Tonometry in Primary Congenital Glaucoma.

PRCIS: Tono-Pen AVIA (TPA) intraocular pressure (IOP) values are different from those taken with handheld Goldmann applanation tonometer (GAT) in primary congenital glaucoma (PCG). These differences indicate both tonometers cannot be used interchangeably for measuring IOP in PCG. PURPOSE: The aim was to compare IOP measurements obtained using TPA and a handheld version of GAT in children with PCG. MATERIALS AND METHODS: Forty-two eyes from 23 patients were evaluated for central corneal thickness (CCT), axial length, biomicroscopy and IOP measurement with TPA and a handheld GAT under inhalation anesthesia. After 1 eye from each patient was randomized, paired the Student t-test and the Pearson correlation were used for analysis. Generalized linear mixed model was used to estimate the difference between tonometers. RESULTS: Mean age of children was 28.3±20.5 months. Mean axial length was 24.89±3.33 mm and mean CCT was 605.9±81.0 µm. Mean IOP was 22.1±9.6 for TPA and 14.0±4.5 mm Hg for GAT. There was a significant difference of 8.1±6.9 mm Hg between TPA IOP and GAT IOP (P<0.001). Each 6 months increase in age was associated with 1.32 mm Hg reduction in the difference between tonometers (P=0.002) and each 1 mm Hg higher of mean GAT IOP was associated with -0.73 mm Hg in the difference between TPA and GAT (P=0.002). Also, for every 20 µm increase in CCT an increase of 1.16 mm Hg in the difference between both devices was expected (P=0.003), after adjustment for potentially confounding variables. CONCLUSION: There is a significant difference between TPA IOP and GAT IOP in PCG. The difference between TPA and GAT in PCG is influenced by CCT, age and GAT IOP value.

Correlation between retinal nerve fiber layer thickness and IOP variation in glaucoma suspects and patients with primary open-angle glaucoma.

PURPOSE: To analyze the relationship between retinal nerve fiber layer thickness (RNFLT) and intraocular pressure (IOP) variation in glaucoma suspects (GS) and patients with primary open-angle glaucoma (POAG). METHODS: Thirty-one GS and 34 POAG patients underwent ophthalmologic examination and 24-h IOP measurements. GS had IOPs ranging from 19 to 24 mmHg and/or suspicious appearance of the optic nerve. POAG patients had reproducible abnormal visual fields. We only included patients who presented with short-term IOP fluctuation >6 mm Hg (∆IOP). Only one eye per patient was included through a randomized process. Peripapillary RNFLT was assessed by spectral-domain optical coherence tomography. We correlated RNFLT with IOP parameters. RESULTS: Mean IOP was similar between GS and POAG groups (15.6 ± 3.47 vs 15.6 ± 2.83 mmHg, p = 0.90) as was IOP peak at 6 AM (21.7 ± 3.85 vs 21.3 ± 3.80 mmHg, p = 0.68). Statistically significant negative correlations were found in POAG group between IOP at 6 AM and RNFLT in global (rs = -0.543; p < 0.001), inferior (rs = -0.540; p < 0.001), superior (rs = -0.405; p = 0.009), and nasal quadrants (rs = -0.561; p < 0.001). Negative correlations were also found between ∆IOP and RNFLT in global (rs = -0.591; p < 0.001), and all other sectors (p < 0.05). In GS IOP at 6 AM correlated only with inferior quadrant (rs = -0.307; p = 0.047). CONCLUSION: IOP at 6 AM and ∆IOP had negative correlations with RNFLT quadrants in POAG. In GS this correlation occurred between IOP at 6 AM and inferior quadrant. These findings may indicate potential risk factors for glaucoma progression.