Abstract
Purpose:
We constructed a clinical clue-based algorithm to identify the microbiology-positive post-cataract surgery endophthalmitis.
Methods:
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.
Results:
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).
Conclusions:
EIMA identified microbiology-positive endophthalmitis three-quarters of the time.
Translational Relevance:
EIMA suggested infectivity and the class of microbial infection could help targeted management of endophthalmitis after cataract surgery.
The retrospective data were entered into a Microsoft Excel (2007) sheet and analyzed using SPSS version 27 (IBM Corporation, Armonk, New York, USA). Categorical variables were expressed in frequency and percentages; the continuous variables were expressed in mean and standard deviation. The normality of the continuous variables was checked using the Shapiro-Wilks test. Univariate analysis was performed using the χ2 test and Mann-Whitney U test for association between two categorical variables and comparison of means between two groups, respectively. A P value < 0.05 was considered statistically significant. Sensitivity, specificity, positive and negative likelihood ratio, positive and negative predictive value, disease (infectious endophthalmitis prevalence), and accuracy of EIMA vis-à-vis culture-positive, sequencing-positive, and microbiology-positive endophthalmitis were calculated. Sensitivity and specificity were calculated at IS 12.5 (moderate endophthalmitis) and LS 7.5 (Snellen 20/800-20/640).
After evaluating several decision-making models, we used the CHAID (Chi-squared Automatic Interaction Detection) model. It is a classification method for building decision trees using χ
2 statistics to identify optimal splits.
12 We divided the datasets randomly into training and testing datasets. The algorithm was designed with 70% (n = 1011) of the dataset, and the results of the algorithms were tested on the remaining 30% (n = 433) of the dataset. The performance of the model was evaluated using accuracy and area under the curve using the receiver operating characteristic curve. We chose the model that had the highest discriminant ability. We used the IS of the ocular tissues significantly associated with culture-positive endophthalmitis and the presenting LS to determine the EIMA predictability. We added two categories of symptom duration (≤2 and 3–6 days) to the EIMA-positive endophthalmitis to identify the infecting micro-organisms.
Using the presenting IS and LS, there were six possible situations, three each for microbiology-positive and microbiology-negative endophthalmitis (
Fig.).
Three situations for microbiology-positive end-ophthalmitis:
- 1. Corneal edema IS ≤ 2 (iris visible) + hypopyon IS > 1 (>25% of anterior chamber) + presenting vision < 20/400
- 2. Corneal edema IS > 2 (iris barely visible) + corneal abscess IS ≤ 1 (measuring < 1 mm) + hypopyon IS > 1 (>25% of anterior chamber)
- 3. Corneal edema IS > 2 (iris barely visible) + Corneal abscess IS > 1 (measuring 1–2 mm)
Three situations for microbiology-negative end-ophthalmitis:
- 1. Corneal edema IS ≤ 2 (iris visible) + hypopyon IS ≤ 1 (trace)
- 2. Corneal edema IS ≤ 2 (iris visible) + hypopyon IS > 1 (<25% of anterior chamber) + presenting vision > 20/400
- 3. Corneal edema IS > 2 (iris barely visible) + Corneal abscess ≤ 1 (measuring < 1 m) + hypopyon IS ≤ 1 (trace)
Two situations in either case above were independent of presenting vision.
In building the clinical algorithm, only the anterior segment findings seen in the slit lamp were included because these findings were imaged in all the eyes; the vitreous conditions (opacities and flare) were excluded because these were not imaged in all the eyes.
The EIMA was validated with prospectively collected data from 175 consecutive post-cataract endophthalmitis. The microbiology-positive group consisted of 35 (34%) gram-positive cocci, 48 (46.6%) gram-negative bacilli, 19 (18.4%) fungi, and one (1%) gram-positive bacillus. There was a difference between the culture and Sanger sequencing results. The proportion of culture and Sanger-positive micro-organisms were 33.3% and 35%, respectively, for gram-positive cocci, 55.6% and 32.8% for gram-negative bacilli, and 9.5% and 32.5% for fungi.
The sensitivity, specificity, positive- and negative likelihood ratio, and positive and negative predictive value of EIMA against culture-positive, PCR-positive, and microbiology-positive endophthalmitis are shown in
Table 3. The accuracy of EIMA was 82.2% (95% CI, 74.71–88.26), 74.1 (95% CI, 64.97–81.23), and 77.1 (95% CI, 70.20–83.14), respectively (
Table 3).
Culture-positive (also PCR positive): The EIMA accuracy was 82.5% (52 of 63). EIMA failed to predict in 11 instances. The presenting vision was >20/400 in two of 11 eyes; the cornea was clear in three of 11 eyes; none of these eyes had a corneal abscess, trace hypopyon (grade <1) was present in nine of 11 eyes, and the IS was ≥10 (11–16) in nine of 11 eyes. Vitreous grew gram-positive cocci (
Staphylococcus species), gram-negative bacilli (chiefly,
Pseudomonas species), and gram-positive bacilli (
Kocuria species) in six (54.5%), four (36.4%), and one eye, respectively (
Table 4).
Culture-negative + PCR positive: The EIMA accuracy was 60.0% (24 of 40). EIMA failed to predict in 16 instances. The presenting vision was >20/400 in four of 16 eyes; the cornea was clear in 12 of 16 eyes; none of these eyes had a corneal abscess, 14 of 16 eyes had trace hypopyon (grade <1), and IS was ≥10 (10–16) in 11 of 16 eyes (
Table 4).
Culture-negative + PCR negative: The EIMA false positivity was 18% (13 of 72). EIMA failed to predict in 13 instances. The presenting vision was <20/400 in 100 % (13 of 13) of eyes, 92.3% (12 of 13) eyes had corneal edema, 69.2% (nine of 13) of eyes had a corneal abscess, and 100% (13 of 13) eyes had hypopyon (
Table 4).
Thus EIMA predicted microbiology-positive results 73.8% (76 of 103) of the time, the false-positive was 18%, and it was undecided 8.2% of the time. It invariably failed when the presenting vision was >20/400 or there was trace or no hypopyon.
Supported by the Hyderabad Eye Research Foundation, Hyderabad, India. (LEC-BHR-R-07-22-911).
Disclosure: T. Das, None; J. Sahoo, None; A. Belenje, None; J. Joseph, None; S. Pandey, None; A. Kapoor, None; R. Pandya, None; U.C. Behera, None; V.P. Dave, None