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24 小时眼压与青光眼进展的双眼相关性分析。

Inter-eye correlation analysis of 24-h IOPs and glaucoma progression.

机构信息

Department of Ophthalmology, University of Würzburg, Josef-Schneider-Straße 11, 97080, Würzburg, Germany.

Institute for Artificial Intelligence and Knowledge Systems, Department of Informatics, University of Würzburg, Würzburg, Germany.

出版信息

Graefes Arch Clin Exp Ophthalmol. 2022 Oct;260(10):3349-3356. doi: 10.1007/s00417-022-05651-4. Epub 2022 May 2.

Abstract

PURPOSE

To determine whether 24-h IOP monitoring can be a predictor for glaucoma progression and to analyze the inter-eye relationship of IOP, perfusion, and progression parameters.

METHODS

We extracted data from manually drawn IOP curves with HIOP-Reader, a software suite we developed. The relationship between measured IOPs and mean ocular perfusion pressures (MOPP) to retinal nerve fiber layer (RNFL) thickness was analyzed. We determined the ROC curves for peak IOP (T), average IOP(T), IOP variation (IOP), and historical IOP cut-off levels to detect glaucoma progression (rate of RNFL loss). Bivariate analysis was also conducted to check for various inter-eye relationships.

RESULTS

Two hundred seventeen eyes were included. The average IOP was 14.8 ± 3.5 mmHg, with a 24-h variation of 5.2 ± 2.9 mmHg. A total of 52% of eyes with RNFL progression data showed disease progression. There was no significant difference in T, T, and IOP between progressors and non-progressors (all p > 0.05). Except for T and the temporal RNFL, there was no correlation between disease progression in any quadrant and T, T, and IOP. Twenty-four-hour and outpatient IOP variables had poor sensitivities and specificities in detecting disease progression. The correlation of inter-eye parameters was moderate; correlation with disease progression was weak.

CONCLUSION

In line with our previous study, IOP data obtained during a single visit (outpatient or inpatient monitoring) make for a poor diagnostic tool, no matter the method deployed. Glaucoma progression and perfusion pressure in left and right eyes correlated weakly to moderately with each other.

摘要

目的

确定 24 小时眼压监测是否可以预测青光眼进展,并分析眼压、灌注和进展参数的双眼间关系。

方法

我们从 HIOP-Reader 提取手动绘制的眼压曲线数据,这是我们开发的一款软件套件。分析测量眼压与平均眼内灌注压(MOPP)和视网膜神经纤维层(RNFL)厚度之间的关系。我们确定了峰值眼压(T)、平均眼压(T)、眼压变化(IOP)和历史眼压截断值的 ROC 曲线,以检测青光眼进展(RNFL 损失率)。还进行了双变量分析,以检查各种双眼间关系。

结果

共纳入 217 只眼。平均眼压为 14.8 ± 3.5mmHg,24 小时眼压变化为 5.2 ± 2.9mmHg。有 RNFL 进展数据的眼睛中,有 52%显示疾病进展。进展组和非进展组的 T、T 和平均眼压均无显著差异(均 P>0.05)。除 T 和颞侧 RNFL 外,任何象限的疾病进展与 T、T 和眼压均无相关性。24 小时和门诊眼压变量在检测疾病进展方面的敏感性和特异性均较差。双眼间参数的相关性为中度;与疾病进展的相关性较弱。

结论

与我们之前的研究一致,单次就诊(门诊或住院监测)获得的眼压数据无论采用何种方法,都不能作为良好的诊断工具。左右眼的青光眼进展和灌注压之间的相关性为弱到中度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/82c8/9477895/7345d5f04b99/417_2022_5651_Fig1_HTML.jpg

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