Incidence, timing and risk factors of type 1 retinopathy of prematurity in a North American cohort

Flicker electroretinogram in preterm infants

BACKGROUND

Infants born prematurely are at risk of developing retinopathy of prematurity, which is associated with abnormalities in retinal function as measured using electroretinography. The aim of this study was to record non-invasive flicker electroretinograms (ERGs) in preterm infants and compare function of moderate and very or extremely preterm infants.

METHODS

In this non-randomized, cross-sectional study, 40 moderate preterm (gestational age (GA) 34 0/7 to 36 6/7 weeks, Group A) and 40 very or extremely preterm infants (GA ≤ 31 weeks, Group B) were recruited for flicker ERG recording through closed eyelids using the RETeval® device and skin electrodes. Group A was tested within the first week of life and Group B between 34th and 37th week postmenstrual age. Flicker stimuli were presented at 28.3 Hz with stimulus levels of 3, 6, 12, 30 and 50 cd•s/m2. Primary endpoints were peak time (ms) and amplitude (µV).

RESULTS

Flicker ERGs were recordable in most infants with the highest proportion of reproducible ERGs at 30 cd•s/m2. Amplitudes increased with stronger flicker stimulation, while peak times did not differ significantly between stimulus levels nor groups. Amplitudes were significantly greater in Group B at the strongest stimulus level (Mann-Whitney-U-Test=198.00, Z = 4.097, p = <0.001).

CONCLUSIONS

Feasibility of collecting flicker ERG data in most preterm infants was confirmed. We found no evidence of reduced retinal responses to flicker stimuli associated with extreme prematurity. Higher amplitudes in very and extremely preterm infants could indicate acceleration of retinal development following birth, triggered by visual stimulation.

A Study of the Demographic Profile, Screening, and Management of Patients Visiting a Retinopathy of Prematurity Clinic

Background and objective Retinopathy of prematurity (ROP) is a retinal vasoproliferative disease affecting premature infants. Despite improvements in neonatal care and management, ROP still remains a major cause of childhood blindness worldwide. Studying the demographic profile and screening is essential to develop predictive models, to gain insights into the cause of retinal vascular diseases and diseases of prematurity, and to determine the future management and research in ROP. The objective of the present study was to estimate the incidence of ROP, to identify the risk factors that predispose to ROP, and to assess the outcome of these cases. Hence, this study was conducted in a tertiary care hospital in Maharashtra. Method A prospective, observational study was conducted from 10 August 2022 to 10 October 2022. Infants with gestational ages < 34 weeks, birth weights < 2000 g, infants who received supplemental oxygen therapy, or patients who required NICU stay were screened for ROP. Demographic details were recorded to assess the risk factors and treatment was given according to the severity of ROP grade. Result A total of 160 eyes of 80 infants were screened and analysed. The overall incidence of "any ROP" was 19 patients (38 eyes), i.e., 24%. Out of 80 patients, six were of 28 weeks gestational age, of whom four (67%) were positive for ROP. The mean birth weight of infants with ROP was 1331.58 ± 238.532 g (p < 0.0001). ROP stage 1 was seen in five patients (26.32%), stage 2 in 10 patients (52.63%), and stage 3 in four patients (21.0%), with no subjects in stages 4 & 5. Out of 19 patients, six (32%) had type 1 ROP, and 13 (68%) had type 2 ROP. Out of 19 cases, 13 (68%) received follow-up care based on the severity of their disease, and six (32%) were treated with panretinal photocoagulation (PRP) laser. Conclusion Incidence of any ROP was 24%. Prematurity, low birth weight, and oxygen therapy remain the most significant risk factors associated with the development of ROP. Early referral, diagnosis, and timely intervention will play a monumental role in improving the prognosis of this potentially blinding disease.

Image-free recognition of moderate ROP from mild with machine learning algorithm on plasma Raman spectrum

The retinopathy of prematurity (ROP) can cause serious clinical consequences and, fortunately, it is remediable while the time window for treatment is relatively narrow. Therefore, it is urgent to screen all premature infants and diagnose ROP degree timely, which has become a large workload for pediatric ophthalmologists. We developed a retinal image-free procedure using small amount of blood samples based on the plasma Raman spectrum with the machine learning model to automatically classify ROP cases before medical intervention was performed. Statistical differences in infrared Raman spectra of plasma samples were found among the control, mild (ZIIIS1), moderate (ZIIIS2 & ZIIS1), and advanced (ZIIS2) ROP groups. With the different wave points of Raman spectra as the inputs, the outputs of our support vector machine showed that the area under the curves in the receiver operating characteristic (AUC) were 0.763 for the pair comparisons of the control with the mild groups, 0.821 between moderate and advanced groups (ZIIS2), while more than 90% in comparisons of the other four pairs: control vs. moderate (0.981), control vs. advanced (0.963), mild vs. moderate (0.936), and mild vs. advanced (0.953), respectively. Our study could advance principally the ROP diagnosis in two dimensions: the moderate ROPs have been classified remarkably from the mild ones, which leaves more time for the medical treatments, and the procedure of Raman spectrum with a machine learning model based on blood samples can be conveniently promoted to those hospitals lacking of the pediatric ophthalmologists with experience in reading retinal images.

Comparison of Weight-Gain-Based Prediction Models for Retinopathy of Prematurity in an Australian Population

Purpose

Four weight-gain-based algorithms are compared for the prediction of type 1 ROP in an Australian cohort: the weight, insulin-like growth factor, neonatal retinopathy of prematurity (WINROP) algorithm, the Children's Hospital of Philadelphia Retinopathy of Prematurity (CHOPROP), the Colorado Retinopathy of Prematurity (CO-ROP) algorithm, and the postnatal growth, retinopathy of prematurity (G-ROP) algorithm.

Methods

A four-year retrospective cohort analysis of infants screened for ROP in a tertiary neonatal intensive care unit in Brisbane, Australia. The main outcome measures were sensitivities, specificities, and positive and negative predictive values.

Results

531 infants were included (mean gestational age 28 + 3). 24 infants (4.5%) developed type 1 ROP. The sensitivities, specificities, and negative predictive values, respectively, for type 1 ROP (95% confidence intervals) were for WINROP 83.3% (61.1-93.3%), 52.3% (47.8-56.7%), and 98.4% (96.1-99.4%); for CHOPROP 100% (86.2-100%), 46.0% (41.7-50,3%), and 100% (98.4-100%); for CO-ROP 100% (86.2-100%), 32.0% (28.0%-36.1%), and 100% (98.3-100%); and for G-ROP 100% (86.2-100%), 28.2% (24.5-32.3%), and 100% (97.4-100%). Of the five infants with persistent nontype 1 ROP that underwent treatment, only CO-ROP was able to successfully identify all.

Conclusions

CHOPROP, CO-ROP, and G-ROP performed well in this Australian population. CHOPROP, CO-ROP, and G-ROP would reduce the number of infants requiring examinations by 43.9%, 30.5%, and 26.9%, respectively, compared to current ROP screening guidelines. Weight-gain-based algorithms would be a useful adjunct to the current ROP screening.

Premature infants with gestational age less than 25 weeks require increased ophthalmology resources for retinopathy of prematurity

BACKGROUND

It is unclear how increasing survival of low gestational age (GA) infants affects ophthalmologic screening and treatment rates for retinopathy of prematurity (ROP). This study compared the examination and treatment rates of infants born at GA of <25 weeks and those born at GA of at least 25 weeks.

METHODS

This was a retrospective study of patients who met institutional ROP screening criteria and were admitted to two neonatal intensive care units (NICUs) from January 2017 to June 2020. Variables analyzed were GA, birth weight, number of ophthalmology examinations, worst stage of ROP, presence of type 1 ROP, and comorbidities associated with ROP. The χ², Fisher exact, and two-tailed t tests, as well as univariate and multivariable logistic regression, were used for statistical analysis.

RESULTS

Compared to the GA≥25 group, the GA<25 group had a higher number of total exams (10 vs 4.3 [P < 0.001]), higher average worst stage of ROP (1.4 vs 0.3 [P < 0.001]) and higher rate of type 1 ROP (21% vs 1.4% [P < 0.001]), as well as higher mortality (37% vs 8.11% [P < 0. 001]). Multivariable logistic regression analysis controlling for GA, sepsis, and number of transfusions revealed that only GA was significantly associated with developing type 1 ROP.

CONCLUSIONS

Infants with GA <25 weeks had more severe ROP and required significantly more ophthalmologic examinations than GA ≥25. It is important for ROP services to plan for this increased screening load, especially if the number of such lower-weight infants in their NICUs increases.

Incidence and Risk Factors for Retinopathy of Prematurity in a Portuguese Cohort

PURPOSE

To evaluate the incidence and risk factors for retinopathy of prematurity (ROP) in two Portuguese neonatal units with a sub-analysis of infants with a gestational age (GA) of 28 weeks or older.

METHODS

This was a retrospective case series of all infants who underwent ROP screening from 2012 to 2020. Demographic, clinical, and laboratory data were collected. Univariate logistic regression was used to examine the risk factors for ROP followed by multivariate regression.

RESULTS

A total of 475 infants were included with a median GA of 30 weeks (range: 23 to 36 weeks) and a median birth weight of 1,229 grams (range: 408 to 2,620 grams). ROP was diagnosed in 113 infants (23.8%) and 29 (6.1%) were treated. In the multivariate analysis, GA and hyperglycemia were significantly associated with severe ROP (P < .001). In the subgroup analysis of infants with a GA of 28 weeks or older, bronchopulmonary dysplasia, late-onset sepsis, and hyperglycemia were linked to severe ROP.

CONCLUSIONS

The incidence of ROP in the cohort falls within the range of other high-income countries. Hyperglycemia overpowered all of the other risk factors. Although rare, more mature infants are also at risk for severe ROP. Infants with older GA share the same group of risk factors, but bronchopulmonary dysplasia seems to play a greater role. [J Pediatr Ophthalmol Strabismus. 2022;59(4):254-260.].

Cost-effectiveness of Artificial Intelligence-Based Retinopathy of Prematurity Screening

Importance

Artificial intelligence (AI)-based retinopathy of prematurity (ROP) screening may improve ROP care, but its cost-effectiveness is unknown.

Objective

To evaluate the relative cost-effectiveness of autonomous and assistive AI-based ROP screening compared with telemedicine and ophthalmoscopic screening over a range of estimated probabilities, costs, and outcomes.

Design, Setting, and Participants

A cost-effectiveness analysis of AI ROP screening compared with ophthalmoscopy and telemedicine via economic modeling was conducted. Decision trees created and analyzed modeled outcomes and costs of 4 possible ROP screening strategies: ophthalmoscopy, telemedicine, assistive AI with telemedicine review, and autonomous AI with only positive screen results reviewed. A theoretical cohort of infants requiring ROP screening in the United States each year was analyzed.

Main Outcomes and Measures

Screening and treatment costs were based on Current Procedural Terminology codes and included estimated opportunity costs for physicians. Outcomes were based on the Early Treatment of ROP study, defined as timely treatment, late treatment, or correctly untreated. Incremental cost-effectiveness ratios were calculated at a willingness-to-pay threshold of $100 000. One-way and probabilistic sensitivity analyses were performed comparing AI strategies to telemedicine and ophthalmoscopy to evaluate the cost-effectiveness across a range of assumptions. In a secondary analysis, the modeling was repeated and assumed a higher sensitivity for detection of severe ROP using AI compared with ophthalmoscopy.

Results

This theoretical cohort included 52 000 infants born 30 weeks' gestation or earlier or weighed 1500 g or less at birth. Autonomous AI was as effective and less costly than any other screening strategy. AI-based ROP screening was cost-effective up to $7 for assistive and $34 for autonomous screening compared with telemedicine and $64 and $91 compared with ophthalmoscopy in the primary analysis. In the probabilistic sensitivity analysis, autonomous AI screening was more than 60% likely to be cost-effective at all willingness-to-pay levels vs other modalities. In a second simulated cohort with 99% sensitivity for AI, the number of late treatments for ROP decreased from 265 when ROP screening was performed with ophthalmoscopy to 40 using autonomous AI.

Conclusions and Relevance

AI-based screening for ROP may be more cost-effective than telemedicine and ophthalmoscopy, depending on the added cost of AI and the relative performance of AI vs human examiners detecting severe ROP. As AI-based screening for ROP is commercialized, care must be given to appropriately price the technology to ensure its benefits are fully realized.