Anant Bajaj Retina Institute-Srimati Kanuri Santhamma Centre for Vitreoretinal Diseases, LV Prasad Eye Institute, Hyderabad, India.
https://orcid.org/0000-0002-1295-4528.
Transl Vis Sci Technol. 2024 Aug 1;13(8):10. doi: 10.1167/tvst.13.8.10.
We constructed a clinical clue-based algorithm to identify the microbiology-positive post-cataract surgery endophthalmitis.
The Endophthalmitis Infectivity Measurement Algorithm (EIMA) was constructed using presenting Snellen vision (Letter score [LS]) and Inflammation Score (IS, from the cornea, anterior chamber, iris, and vitreous). Retrospective data (70% for training; 30% for testing) was fitted into CHAID (Chi-squared Automatic Interaction Detection). EIMA was validated with prospective data. EIMA-categorized disease severity was weighed against the symptom duration to detect infecting micro-organisms.
EIMA was constructed from 1444 retrospective data. The average LS was 6.03 ± 12.11, median IS was 14 (8-24), and culture positivity was 38%. The accuracy and area under the curve of CHAID were 66.36% and 0.642, respectively. EIMA was validated with 175 prospectively collected data. Microbiology positivity (culture + sequencing) was 58.9%. EIMA sensitivity, specificity, and accuracy against microbiology-positive endophthalmitis were 73.7 (95% confidence interval [CI], 64.19-81.96), 81.9 (95% CI, 71.1-90.02), 77.1 (95% CI, 70.20-83.14), respectively. The positive and negative likelihood ratios were 4.08 (95% CI, 2.46-6.67) and 0.32 (95% CI, 0.22-0.45), respectively. There was higher microbial growth in two days or less than in three- to six-day symptom duration (69.9% vs. 28.2%; P = 0.018) endophthalmitis. Gram-negative infection was higher in two days or less (55.6% vs. 20.2%; P = 0.014), and gram-positive infection was higher in three- to six-day endophthalmitis (62.1% vs. 27.7%; P = 0.027).
EIMA identified microbiology-positive endophthalmitis three-quarters of the time.
EIMA suggested infectivity and the class of microbial infection could help targeted management of endophthalmitis after cataract surgery.
我们构建了一种基于临床线索的算法来识别白内障手术后眼内炎的微生物阳性。
使用眼前视力（字母评分[LS]）和炎症评分（IS，来自角膜、前房、虹膜和玻璃体）构建眼内炎感染性测量算法（EIMA）。回顾性数据（70%用于训练；30%用于测试）被拟合到 CHAID（卡方自动交互检测）中。使用前瞻性数据验证 EIMA。EIMA 分类的疾病严重程度与症状持续时间进行权衡，以检测感染微生物。
EIMA 由 1444 份回顾性数据构建而成。平均 LS 为 6.03±12.11，中位数 IS 为 14（8-24），培养阳性率为 38%。CHAID 的准确性和曲线下面积分别为 66.36%和 0.642。EIMA 用 175 份前瞻性收集的数据进行验证。微生物阳性（培养+测序）率为 58.9%。EIMA 对微生物阳性眼内炎的敏感性、特异性和准确性分别为 73.7%（95%CI，64.19-81.96）、81.9%（95%CI，71.1-90.02）和 77.1%（95%CI，70.20-83.14）。阳性和阴性似然比分别为 4.08（95%CI，2.46-6.67）和 0.32（95%CI，0.22-0.45）。在两天或更短的时间内有更高的微生物生长，而在三到六天的症状持续时间内则较低（69.9%比 28.2%；P=0.018）。在两天或更短的时间内革兰氏阴性感染更高（55.6%比 20.2%；P=0.014），而在三到六天的眼内炎中革兰氏阳性感染更高（62.1%比 27.7%；P=0.027）。
EIMA 有四分之三的时间能识别出微生物阳性的眼内炎。
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