Sight-threatening Retinopathy Of Prematurity Research Articles

Vision on wheels: Technician-assisted retinopathy of prematurity screening in rural Tamil Nadu and Andhra Pradesh: 2018-2021 Project Report.

To analyze the incidence of sight-threatening retinopathy of prematurity (ROP) in premature infants in rural Tamil Nadu and Andhra Pradesh from 2018 to 2021, and to analyze its association with birthweight (BW), gestational age (GA), and postconceptional age (PCA). Project Vision on Wheels is a free ROP screening and treatment program initiated by a tertiary eye care center in South India in June 2018 to screen preterm infants in rural areas in 11 centers in Tamil Nadu and Andhra Pradesh by trained technicians. Infants with sight-threatening ROP were immediately shifted for vision-preserving laser. Of the 18,117 infants screened from 2018 to 2021, 1046 infants underwent laser, with the majority being bigger and more mature when compared to Western data. There was a yearly increase in the number of infants with sight-threatening ROP in the lower BW, GA, and PCA categories. The timely detection of the condition by committed screening led to salvage of vision by timely laser in 100% of the treated babies in all the years. The incidence of sight-threatening ROP had a yearly decrease in higher BW, GA, and PCA categories. These trends were statistically significant ( P = 0.001 for ROP and BW, P = 0.037 for ROP and GA, and P = 0.001 for ROP and PCA). The statistically significant trend of decreasing sight-threatening ROP in babies with higher BW, GA, and PCA and increasing treatable ROP in younger and smaller babies (with lower BWs, GAs, and PCAs) in rural India, over time, is a hitherto unreported finding. This is the first such study in rural Tamil Nadu and Andhra Pradesh combined, with the largest data to date (as per MEDLINE search) to document this healthier trend.

A Multicenter Cross-Sectional Study of the Awareness and Screening for Retinopathy of Prematurity Among NICU Pediatricians in Makkah and Jeddah, Saudi Arabia.

Purpose This study aims to evaluate neonatal intensive care unit (NICU) pediatricians' knowledge about retinopathy of prematurity (ROP) in the major tertiary centers in Makkah and Jeddah, Saudi Arabia. Methods This cross-sectional study uses a self-administered electronic questionnaire completed by NICU pediatricians at the main hospitals of Makkah and Jeddah cities. Based on the participants' correctly selected responses to the validated questionnaire, a scoring system was used in the data analysis to show their level of ROP knowledge. Results Seventy-seven responses were analyzed. The male gender was 49.4%. The majority were recruited from the ministry of health hospitals (63.6%). A small proportion (28.6%) correctly identified who performs the examination. Around three-quarters of the participants have correctly stated that ROP therapy is a very good option to prevent blindness (72.7%). The treatment should generally begin within 72 hours after diagnosis of sight-threatening ROP (79.2%). The requirements for ROP screening were unknown to more than half of our participants (53.2%). With the lowest score of 4.0 and a maximum score of 17.0, the median knowledge score was 13.0 (IQR = 11.0 to 14.0). Based on pediatricians' clinical qualifications, knowledge scores varied significantly. Residents had a significantly lower knowledge score than specialists and consultants (median = 7.0, IQR = 6.0 to 9.0, p = 0.001). Additionally, pediatricians with less experience (<5 years) performed significantly lower on the knowledge score (median = 10.0, IQR = 6.2 to 12.8) than those with more experience (median = 13.0, IQR = 11.0 to 15.0) for participants with 5-10 years of experience, and (median = 13.0, IQR = 11.0 to 14.0) for participants with >10 years of experience). Conclusion Our study showed that NICU pediatricians understood ROP risk factors and treatment options. Nevertheless, they needed to understand the ROP screening inclusion criteria and when the screening could be stopped. Residents scored substantially lower in knowledge overall. Accordingly, we emphasized the need for NICU pediatricians to increase their level of awareness by having regular educational sessions and standardizing one guideline to be strictly followed.

Impact of COVID-19 Pandemic on Retinopathy of Prematurity Services in the Indian Public Healthcare System.

To analyze the impact of the COVID-19 pandemic on the retinopathy of prematurity (ROP) services at Special Newborn Care Units (SNCUs), which provide care for sick neonates in the Indian public healthcare system. A retrospective chart analysis of 508 babies screened for ROP at two SNCUs in West Bengal (India). We compared the data from the lockdown period (April, 2020-June, 2020; study arm) with the same period of the preceding year, 2019 (control arm). Out of the 508 babies, 187 were screened during the lockdown and 328 during 2019. The odds of developing ROP were 2.08 times (95% CI:1.25-3.48; P=0.002) higher during the lockdown period (35/187 babies; 18.72%) as compared to the previous year (34/328 babies; 10.37%). Also, the risk of sight-threatening ROP (ST-ROP) increased significantly during the lockdown (12/35 ROP babies; 34.29%) compared to the previous year (4/34 ROP babies; 11.76%) (odds ratio: 3.9; 95% CI:1.1-13.7; P=0.015). Notably, all babies with ROP during the lockdown presented more than 30 days after birth, compared to none in the previous year. All babies requiring laser therapy recovered completely in both groups. An increased odds of developing ROP, including ST-ROP, was observed during the COVID-19 pandemic. Delayed ROP screening, which was noted in all study eyes, can have a detrimental effect on long-term visual prognosis. The findings of our research call for modifying the present healthy policy framework to make it more adaptable to disruptions in healthcare services, given the cyclical nature of the worldwide COVID-19 pandemic.

Predicting ROP Severity by Artificial Intelligence: Pragmatic Versus Knowledge-Based Approach.

Retinopathy of prematurity (ROP) blindness is largely preventable, with many countries having already established programs for its timely identification. However, ∼93% of infants screened do not develop ROP severe enough to require treatment.1 As reported in this issue of Pediatrics by Coyner et al.2 artificial intelligence (AI) is innovative methodology to optimize the timing of ROP examinations. For example, it can predict whether an eye will not require treatment, reducing the number of examinations needed while also predicting which eyes need closer surveillance. This is an important development because it would make ROP programs more effective and efficient, thus reducing the burden on infants, families, and the health care team.From the earliest descriptions, congestion and tortuosity of the posterior retinal vessels were recognized as prominent features of serious ROP.3 In the first international classification of ROP in 1984,4 the term “plus disease” was included to describe progressive vascular incompetence. Two decades later, after the recommendations of the Early Treatment for Retinopathy of Prematurity trial,5 plus disease became the major driver for treatment. With focus now directed to the timely identification of plus disease, the historical dichotomous categorization of normal versus plus disease was deemed inadequate and led to the introduction of an intermediate level, “preplus disease,” in 20056 and the subsequent critical acknowledgment in the 2021 classification7 that the vascular changes associated with ROP do not progress stepwise but are a continuous spectrum.However, categorizing the plus spectrum is subjective and subject to significant variation.8–10 In the late 1990s, the introduction of digital imaging into the NICU provided the opportunity to objectively measure what had long been seen, and this development spawned several methods of retinal vessel measurement.11,12 Despite revealing great early promise, these methods have yet to be incorporated into routine ROP screening worldwide.AI has recently been used to help interpret the complex images captured to monitor for ROP and other patient-specific risk factors. Coyner et al1 report the use of this technology to explore the spectrum of ROP-related vascular changes, and using deep learning (a type of machine learning that can be used to develop predictive rules), the Oregon team developed i-ROP (an algorithm to detect plus disease),13 from which a vascular severity score (VSS) was derived from zone I (the area closest to the optic disc).13,14 Coyner et al1 have devised a risk model to predict ROP requiring treatment using 2 components: gestational age and VSS. Based on images obtained at 32 to 33 weeks’ postmenstrual age, the model had 100% sensitivity and 80.8% negative predictive value to predict (on average, >1 month in advance of the diagnosis) an eye which would later require treatment. This is an exciting and important development. As a result, instead of a stepwise progression through normal, preplus, and plus disease, VSS permits a sliding scale and detailed analysis of the entire plus spectrum, which hopefully will permit fine tuning of the model in the future.To paraphrase Lord Kelvin (1883), when you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot measure it, your knowledge is of a meager and unsatisfactory kind. Herein lies a dilemma: Terms such as AI and deep learning are now in common parlance, so much so that few of us are brave enough to express ignorance. By expressing it (VSS) in numbers, it is not clear that, currently, we fully understand what is being measured or if it has advanced our scientific understanding. Hopefully, this will become apparent in the future. Pragmatically, however, there is no doubt that AI-related techniques, including deep learning–derived VSS, are effective and will likely be important in ROP screening. For this to be incorporated into routine clinical practice, some challenges need to be overcome: a short processing time will be essential preferably within the time span of the NICU ward rounds. In addition, this research is North America based and needs to be validated in other countries in which neonatal care may well be more variable and larger infants develop sight-threatening ROP over a shorter time period. Coyner et al1 have introduced us to a new and exciting era of efficient ROP identification.

Artificial Intelligence for ROP Screening and to Assess Quality of Care: Progress and Challenges.

The goal of retinopathy of prematurity (ROP) screening is to detect the constellation of clinical signs that suggest a high risk of progression to retinal detachment so that urgent treatment can be given. At each screening episode, there are 3 considerations: whether urgent treatment is needed, whether follow-up screening is needed, and whether there is no risk of sight-threatening ROP so that the screening can stop. The decisions are based on a detailed examination of the retina focused on the severity (ie, stage), location (ie, zone), and degree of dilation and tortuosity of retinal blood vessels (ie, plus disease). If ROP is not present, the peripheral retina needs to be assessed to determine the degree of maturity of the retinal vessels; if they are mature or ROP detected earlier is definitely regressing, the screening can stop.Telemedicine with artificial intelligence (AI) image analysis could transform ROP screening, especially in settings with an insufficient supply of ophthalmologists, which can happen either because of absolute workforce shortages or when ophthalmologists choose not to offer ROP screening because of the time burden or fear of litigation. Telemedicine with AI image analysis is particularly appealing for low-resource settings in which greater exposure to risk factors, such as hyperoxia, can lead to a high frequency of treatment-requiring ROP in infants born at a gestational age (GA) of <32 weeks, and severe disease can also develop in more mature infants.1 In these settings, wider screening criteria are required, which increases the screening workload.2In this issue of Pediatrics, Campbell et al3 describe a multicenter screening program in India, the Retinopathy of Prematurity Eradication Save Our Sight program, which was done in collaboration with a United States–based international group, Imaging and Informatics in Retinopathy of Prematurity (iROP). This report describes not only the diagnostic-test accuracy of the deep learning (DL) system developed by this group (iROP DL) but, also, whether the findings can be used as an indicator to assess the quality of neonatal care.iROP DL, which quantifies plus disease, performed well, with 100% sensitivity and a high specificity compared to image grading by 3 ROP experts as the gold standard. Because missing ROP that requires treatment can have serious vision consequences, a high sensitivity is essential. The low positive predictive value is not surprising because of the low prevalence of treatment-requiring ROP.The study findings related to quality of care are particularly interesting. There were highly significant associations between the mean iROP DL score and lower birth weight and whether the unit had adequate equipment to mix and monitor oxygen. A striking finding was that only 3 of the 14 study units had enough of this equipment, which is a frequent and regrettable occurrence in a large number of units in many low- and middle-income countries.There are some important limitations of this study. iROP cannot be used to assess stage or zone, only plus disease. Whether DL and AI image analysis can achieve equally high diagnostic-test accuracy for these other prognostic signs, compared to clinical examination by indirect ophthalmoscopy or image analysis by an ROP expert, remains to be seen. In India and other low-resource settings, data on GA can be unreliable because of low attendance at antenatal care, high rates of intrauterine-growth restriction, and lack of routine prenatal ultrasound. Because GA is an important risk factor for ROP, in this study, more accurate data may have attenuated the association between iROP DL scores and quality of care. The study findings might not be generalizable to other regions. For example, the degree of retinal pigmentation, which can be greater for children born in Africa, could impact the interpretation of images.Several other groups are also working on AI for ROP screening,4–7 and once systems can provide reliable information on all of the signs needed to make a management decision at each screening episode, together with the availability of lower-cost imaging devices, the door is open for a dramatic change in how ROP screening is delivered and by whom.8In 2019, the World Health Organization and United Nations Children’s Fund recommended ROP screening and treatment as standard of care in their “Survive and Thrive” policy.9 The authors correctly indicate that integrated systems will be essential before the benefits of telemedicine and AI image analysis can be fully realized. Studies of the feasibility, acceptability, and cost-effectiveness of this approach would also be required for decision-makers and policy change within countries, with allocation of resources for implementation.

Fluorescein angiographic features post-intravitreal bevacizumab for retinopathy of prematurity: can they support rescue laser photocoagulation to the avascular retina

ObjectiveTo study the fluorescein angiography (FA) features post-intravitreal bevacizumab (post-IVB) monotherapy for retinopathy of prematurity (ROP) that may pose risk for late sight-threatening ROP and support rescue laser to the avascular retina. MethodsA retrospective review of 26 infants (47 eyes) with type 1 ROP treated with IVB monotherapy. ResultsAll infants had RetCam and FA performed at an average of 68 weeks postmenstrual age (PMA), 19 at an average 98 weeks PMA, and 10 at an average of 120 weeks PMA. Average gestational age at birth and birth weight were 24.8 weeks (standard deviation [SD] 1.91 weeks) and 683 g (SD 158.85 g), respectively. Average PMA at first IVB was 37 weeks. Eight eyes of 6 infants received repeat IVB for recurrent stage 3 at an average of 46.6 weeks PMA. All infants had inhibited retinal vasculature in zone 2, and 25 of 26 had conventional FA features, which included peripheral leakage, shunts, abnormal branching, and tangles with no late reactivation of ROP until age 3 years. Only 1 infant showed diffuse hyperfluorescence along the regressed proliferation site with a late proliferation necessitating laser to preserve vision. ConclusionsConventional FA features seen in 98% post-IVB monotherapy showed no late complications without rescue laser photocoagulation to the avascular retina.

Retinopathy of prematurity: Overview and highlights of an initiative to integrate prevention, screening, and management into the public health system in India.

Purpose:In India, more than 800 special newborn care units (SNCUs) have been established since 2008 in government facilities. More preterm infants are now surviving and blindness from retinopathy of prematurity (ROP) is increasing. The aim of the Queen Elizabeth Diamond Jubilee Trust's initiative (2012–1019) was to improve the quality of neonatal care and integrate ROP services into the government health system using expertise in the government and nongovernment sector in four states in a sustainable and scalable manner.Methods:State Ministries of Health were engaged and collaboration was established between three government programs (Ministry of Health and Family Welfare, Rashtriya Bal Swasthya Karyakram, and blindness prevention) and relevant professionals. Extensive training took place and equipment was provided. Implementation was guided by a multidisciplinary National Task Force and was monitored by state coordination committees. The Task Force appointed technical expert groups to support implementation through advocacy, information, education and communication materials, operational guidelines, a competency-based training curriculum, and an online database and website.Results:Twenty-two ophthalmologists in government facilities were trained to screen for ROP and nine to treat ROP. Almost 13,500 preterm infants were screened in 17 SNCUs and 86% of the 456 infants with sight-threatening ROP were treated. An educational resource using latest pedagogy based on key domain areas for best practices for small and preterm neonates including ROP has been developed and pilot tested and is being evaluated and scaled up.Conclusion:All four states are scaling up services or have plans to scale up, and several other states have started the initiatives.

Development of a quality improvement package for reducing sight-threatening retinopathy of prematurity

Purpose:With improving survival of preterm neonates, retinopathy of prematurity (ROP) is emerging as a major cause of childhood blindness. Incidence of sight-threatening ROP can be reduced by improving the quality of care provided to preterm neonates.Methods:This before-and-after study was designed to develop a need-based intervention package to improve knowledge, skills, and practices of those providing care for preterm neonates, and to evaluate the effectiveness of this package when combined with point-of-care quality improvement (POCQI) in improving survival of preterm neonates without sight-threatening ROP. The study had a formative component to assess baseline knowledge, skills, practices and attitudes, and to assess the needs of the healthcare staff to improve the care of preterm neonates. It was conducted in four special care neonatal units (SCNU) in the state of Madhya Pradesh in India.Results:A theory of change was developed to guide the development of study tools including needs assessment and educational package development. The educational package thus developed has been tested at the study sites in combination with POCQI projects driven by local teams of healthcare providers. The effectiveness of the interventions has been evaluated by collection of individual-level data on neonates admitted at the study sites.Conclusion:A multidimensional educational package integrated with system changes in the form of quality improvement (QI) endeavours driven by local context and needs were developed and evaluated in the project.

Knowledge, attitude, and practice study on awareness of retinopathy of prematurity among pediatricians in Goa

Context: The improvement in neonatal care has led to more number of premature infants surviving. This has led to more number of babies requiring screening for retinopathy of prematurity (ROP). Thus, there is a need to bridge the knowledge gap between pediatricians and ophthalmologists for ROP management. Limited studies done among pediatricians across India had shown that there is a need for greater awareness and timely screening of pre-terms for ROP. No such study was carried out in Goa and adjoining Western India. Hence, the present study was undertaken. Aims: The aim of the study is to assess the knowledge, attitude, and practices about ROP among practicing pediatricians in Goa. Settings and Design: This is a cross-sectional study. Materials and Methods: A pretested pro forma was given to 58 pediatricians, which contained 19 questions related to their educational and practice profile, about the risk factors for ROP, screening protocol, referral criteria, facilities for referral, treatment options, and problems faced by them for referral of babies requiring treatment for sight-threatening ROP. Statistical Analysis Used: Percentages and proportions are used for analysis. Results: Among the 58 pediatricians, 75.86% were practicing in government hospitals including Goa Medical College and Hospital, whereas 14 (24.13%) were private practitioners. 50% had been practicing for 5–10 years. All participants had heard about ROP and were aware of the most common risk factors for ROP. 87.93% were aware of the timing of first screening of preterm infants for ROP; 84.48%were aware of referral to an ophthalmologist for screening and management of ROP. 77.58% had knowledge about the treatment modalities. 56.89% reported that they faced barriers to referral. Conclusions: There is a very high level of awareness among pediatricians in Goa about the risk factors and screening of ROP.

Assessment of WINROP algorithm as screening tool for preterm infants in Manitoba to detect retinopathy of prematurity.

Developing less invasive methods for early detection of retinopathy of prematurity (ROP) is vital to minimizing blindness in premature infants. Lofqvist and colleagues developed a computer-based ROP risk algorithm (WINROP) (https://winrop.com), which detects downtrends in postnatal weight gain that correlate with the development of sight-threatening ROP. The aim of this study is to investigate the sensitivity and specificity of the WINROP algorithm to detect vision-threatening ROP. This is a retrospective chart review study between January 2008 and December 2013. This study was conducted in the neonatal intensive care unit in Children's Hospital at Health Sciences Centre, Winnipeg, Manitoba, Canada. The study included preterm infants, less than 32 weeks' gestation, who were admitted to the hospital during the study period. The included 215 infants were eligible for ROP screening and had sufficient data to be entered into the WINROP algorithm. Infants were screened by a paediatric ophthalmologist for retinopathy of prematurity. The body weight of infants was measured weekly and entered into the WINROP algorithm; the sensitivity and the specificity of the WINROP algorithm were assessed. The mean gestational age was 28.6 ± 1.8 weeks. The mean body weight was 1244 ± 294 g. The sensitivity of the WINROP algorithm to detect vision-threatening retinopathy of prematurity in our cohort was 90% (P=0.021) with a specificity of 60% (P=0.002). The WINROP algorithm lacks sufficient sensitivity to be used clinically in our population. The algorithm needs to be reassessed in contemporary populations.

Predictive algorithms for early detection of retinopathy of prematurity.

To evaluate sensitivity, specificity and the safest cut-offs of three predictive algorithms (WINROP, ROPScore and CHOP ROP) for retinopathy of prematurity (ROP). A retrospective study was conducted in three centres from 2012 to 2014; 445 preterms with gestational age (GA)≤30weeks and/or birthweight (BW)≤1500g, and additional unstable cases, were included. No-ROP, mild and type 1 ROP were categorized. The algorithms were analysed for infants with all parameters (GA, BW, weight gain, oxygen therapy, blood transfusion) needed for calculation (399 babies). Retinopathy of prematurity (ROP) was identified in both eyes in 116 patients (26.1%), and 44 (9.9%) had type 1 ROP. Gestational age and BW were significantly lower in ROP group compared with no-ROP subjects (GA: 26.7±2.2 and 30.2±1.9, respectively, p<0.0001; BW: 839.8±287.0 and 1288.1±321.5g, respectively, p=0.0016). Customized alarms of ROPScore and CHOP ROP correctly identified all infants having any ROP or type 1 ROP. WINROP missed 19 cases of ROP, including three type 1 ROP. ROPScore and CHOP ROP provided the best performances with an area under the receiver operating characteristic curve for the detection of severe ROP of 0.93 (95% CI, 0.90-0.96, and 95% CI, 0.89-0.96, respectively), and WINROP obtained 0.83 (95% CI, 0.77-0.87). Median time from alarm to treatment was 11.1, 5.1 and 9.1weeks, for WINROP, ROPScore and CHOP ROP, respectively. ROPScore and CHOP ROP showed 100% sensitivity to identify sight-threatening ROP. Predictive algorithms are a reliable tool for early identification of infants requiring referral to an ophthalmologist, for reorganizing resources and reducing stressful procedures to preterm babies.

Sight-Threatening Retinopathy of Prematurity: Changing Trends in Treatment.

To study the incidence and treatment of severe retinopathy of prematurity (ROP) in infants younger than 30 weeks' gestational age (GA) in New South Wales and the Australian Capital Territory, Australia, from 2003 to 2008. These data were then compared to data from previously reported epochs (1986 to 1987, 1992 to 1997, and 1998 to 2002). Data were divided into two sub-epochs (2003 to 2005 and 2006 to 2008) to study trends and combined to compare over 22 years. From 2003 to 2008, 2,550 of 3,004 (84.9%) infants survived, 200 (7.8%) were diagnosed as having severe ROP, and 119 (59.5%) required laser therapy. No significant difference in the incidence of severe ROP or treatment rate in infants younger than 27 and 30 weeks' GA from 2003 to 2005 and 2006 to 2008 occurred. Similarly, between 1986 and 2008 there was no difference in the incidence of severe ROP. However, the treatment rate significantly increased during this time. The incidence of severe ROP has been stable since 1986. However, laser treatment significantly increased to include 8 infants with stage 2 ROP from 2003 to 2008.

Impact of retinopathy of prematurity on ocular structures and visual functions

The preterm baby may develop ophthalmic sequelae which can be due to prematurity per se, due to retinopathy of prematurity (ROP) or due to neurological damage. Focusing on the former...

The Use of the WINROP Screening Algorithm for the Prediction of Retinopathy of Prematurity in a Chinese Population

Background: Retinopathy of prematurity (ROP) is a gestational age (GA)-related illness that can lead to blindness in premature infants. Timely screening of premature infants could improve visual prognosis. Objective: To evaluate the WINROP algorithm as a method of predicting severe ROP in a Chinese population. Methods: 590 infants with a GA <32 weeks were entered into an online surveillance system (www.winrop.com) that included ROP evaluations and weekly weight measurements from birth to a corrected GA of 40 weeks. If the rate of weight gain decreased to a certain degree, the algorithm signaled an alarm that the infant was at risk for developing sight-threatening ROP. Each infant was categorized as having no, mild, or severe ROP. Results: Among the 590 infants with a GA <32 weeks, an alarm was triggered in 85 infants (14.4%), 50 of which developed severe ROP and were identified in this alarm group. Twenty-seven infants triggered the alarm signal in the first week after birth and 7 infants triggered the alarm at birth. Seven of the infants developed proliferative ROP and the median GA at birth for these infants was 31 weeks. Conclusions: The WINROP system had a sensitivity of 87.5% in a Chinese population for the early identification of infants that developed severe ROP. Postnatal weight gain may help predict ROP in lower birth weight infants.

Low Incidence of Sight-Threatening Retinopathy of Prematurity in Infants Born Before 28 Weeks Gestation at a Neonatal Intensive Care Unit in Japan

Improvement in neonatal care has led to increased survival rates of very premature infants. Accordingly, there are now more extremely preterm infants who are at risk of developing retinopathy of prematurity (ROP). ROP is a disorder of low birth-weight preterm infants and may lead to blindness. However, the prevalence of ROP varies globally, depending on different neonatal and ophthalmic care. Therefore, we studied the incidence and progression of ROP in extremely preterm infants in Japan. In addition, we investigated the characteristics and the clinical courses of the infants who progressed to sight-threatening ROP. A total of 3,154 infants were born at the Japanese Red Cross Sendai Hospital between 2009 and 2011, including 53 live-born infants born before 28 weeks' gestation. Two extremely preterm infants died before the first ROP examination. Among the survived 51 infants (the birth-weight ranged from 309 to 1,354 g, mean 779 g), 36 infants (70.6%) developed ROP: 18 infants with mild ROP and 18 infants with severe ROP. Eight out of the 51 infants (15.7%) underwent laser treatment. None of the infants born at older than 27 weeks 0 day of gestation required any treatment for ROP. In conclusion, most of extremely preterm infants develop some degree of ROP. However, in the majority of these infants the ROP never progressed beyond mild disease and resolved spontaneously without treatment. Sight-threatening ROP was rare. The present study clarifies the natural history of ROP in extremely preterm infants with active perinatal care.

Retinopathy of Prematurity: An Optimum Screening Strategy

We sought to find out whether birth weight of less than 1251 g or gestational age less than 30 weeks could provide a safe and efficient screening criteria of detecting treatable retinopathy of prematurity (ROP). Infants either with a birth weight less than 1500 g or gestational age less than 32 weeks were screened for ROP during an 8-year period. In our study, the incidence of ROP was 36 of 187 (19.3%) infants. Although there was a slight increase in the number of infants screened over the years, the incidence of ROP of any stage remained stable. The maximum stage of ROP reached was stage 1 in 10 of 187 (5.3%), stage 2 in 8 of 187 (4.3%), and stage 3 in 18 of 187 (9.6%) infants. Among those with stage 3 disease, threshold ROP was present in 16 of 18 (88.9%). All infants with threshold ROP had a BW less than 1100 g and gestational age less than or equal to 28 weeks. Significantly fewer babies (105/187, or 56%) would have been examined had inclusion criteria of a birth weight of less than 1251 g and gestational age less than 30 weeks been applied. In addition, 31% (134/437) of screening examinations could have been avoided. Our study suggests that a birth weight of less than 1251 g and gestational age less than 30 weeks can be safely and efficiently used to screen infants without missing a diagnosis of sight-threatening ROP in our catchment population.