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Article

Retinopathy of Prematurity in Eight Portuguese Neonatal Intensive Care Units: Incidence, Risk Factors, and Progression—A Prospective Multicenter Study

by
Mariza Fevereiro-Martins
1,2,3,*,
Ana Carolina Santos
1,
Carlos Marques-Neves
1,4,
Manuel Bicho
1,2,
Hercília Guimarães
5 and
on behalf of the GenE-ROP Study Group
†
1
Ecogenetics and Human Health Unit, Environmental Health Institute-ISAMB, Associate Laboratory TERRA, Faculty of Medicine, University of Lisbon, Av. Professor Egas Moniz, 1649-028 Lisboa, Portugal
2
Institute for Scientific Research Bento da Rocha Cabral, Calçada Bento da Rocha Cabral 14, 1250-012 Lisboa, Portugal
3
Department of Ophthalmology, Cuf Descobertas Hospital, Rua Mário Botas, 1998-018 Lisboa, Portugal
4
Center for the Study of Vision Sciences, University Ophthalmology Clinic, Faculty of Medicine, University of Lisbon, Av. Professor Egas Moniz, Piso 1C, 1649-028 Lisboa, Portugal
5
Department of Gynecology—Obstetrics and Pediatrics, Faculty of Medicine, University of Porto, Alameda Prof. Hernâni Monteiro, 4200-319 Porto, Portugal
*
Author to whom correspondence should be addressed.
†
Collaborators of the study group are provided in the Acknowledgments.
Children 2024, 11(10), 1154; https://doi.org/10.3390/children11101154
Submission received: 16 August 2024 / Revised: 21 September 2024 / Accepted: 23 September 2024 / Published: 24 September 2024
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Abstract

:
Background/Objectives: Retinopathy of prematurity (ROP) is a retinal neovascular disease affecting preterm infants. Identifying risk factors for its development and progression is critical for effective screening and prevention. This study aimed to analyze the incidence of ROP and identify key risk factors for its development and progression. Methods: We conducted a prospective, observational cohort study on 455 neonates (gestational age [GA] < 32 weeks or birth weight < 1500 g) across eight Portuguese NICUs. Results: ROP incidence was 37.8%, with 4.6% requiring treatment. Multivariate analysis identified low GA and the number of red blood cell (RBC) transfusions as significant factors for ROP development and progression. After adjusting for these variables, platelet transfusions, high maximum fraction of inspired oxygen (FiO2) in the second week, and surfactant use remained significantly associated with ROP development, while early and late sepsis, maternal chronic hypertension, and delayed enteral nutrition were associated with progression to ROP requiring treatment. Conclusions: These findings underscore the importance of addressing low GAs and adult RBC transfusions in ROP risk management and suggest that maximum FiO2, platelet transfusions, and sepsis also play crucial roles. Larger studies are needed to validate these results and explore preventive interventions, particularly regarding the impact of multiple adult RBC transfusions on fetal hemoglobin percentages.

Graphical Abstract

1. Introduction

Retinopathy of prematurity (ROP) is a retinal neovascular disorder primarily affecting preterm infants due to the immaturity of their retinal vasculature [1]. While advances in neonatal care, fueled by scientific and technological innovations, have markedly increased the survival rates of infants born at lower gestational ages (GAs), they have also contributed to a higher incidence of ROP [2]. Notably, ROP is recognized as the second leading cause of childhood blindness, surpassed only by cortical visual impairment, as documented in studies [3].
ROP progresses through two phases: Initially, retinal vessel growth is arrested due to postnatal hyperoxia [4]. Subsequently, the incompletely vascularized retina becomes hypoxic, leading to neovascularization driven by angiogenic growth factors [5].
The etiology of ROP is multifactorial, with a low GA and hyperoxia identified as primary contributors [6]. Additionally, genetic factors have been implicated in the development of the disease, as evidenced by studies estimating the heritability of ROP in twins and identifying polymorphisms in genes such as the brain-derived neurotrophic factor (BDNF) associated with severe ROP [7,8]. Our previous research further suggests that genetic factors may influence susceptibility to ROP by regulating erythropoiesis and fetal hemoglobin (HbF) expression, potentially through polymorphisms in genes involved in epigenetic regulation, including lysine-specific histone demethylase 1A (KDM1A) [9].
ROP is categorized based on the International Classification of Retinopathy of Prematurity (ICROP), most recently updated in 2021 with the ICROP3 revision [10,11,12]. The ICROP provides a comprehensive system for describing the acute changes in ROP based on four key parameters: the location of retinal involvement (zones), the presence of plus disease (indicating vascular dilation and tortuosity), severity (stages), and the extent of disease (measured in clock hours). The retinal area is organized into three concentric zones centered around the optic nerve: Zone I, the innermost and most crucial region, extends to a radius that is double the distance between the optic nerve and the macula; Zone II extends from the edge of Zone I to the ora serrata nasally and an equivalent distance temporally; and Zone III, the outermost zone, forms a crescent-shaped peripheral area. Plus disease, characterized by increased vascular dilation and tortuosity, can occur in any zone, with the highest risk of poor outcomes in Zone I and significantly lower risk in Zone III [13].
ROP progresses through five stages, beginning with mild vessel growth and a demarcation line in stage 1, progressing to a ridge in stage 2, and involving neovascular tissue in stage 3, where abnormal vessels extend into the vitreous. Stage 4 features partial retinal detachment, and stage 5 is characterized by total retinal detachment, potentially leading to blindness [14]. For treatment purposes, ROP is further categorized into two types: Type 1 ROP, which is more severe and requires prompt treatment, includes ROP in Zone I with plus disease, stage 3 in Zone I without plus disease, and stage 2 or 3 in Zone II accompanied by plus disease. Type 2 ROP is less severe and can often be managed with observation; it includes stage 1 or 2 ROP in Zone I without plus disease, and Zone II, stage 3 ROP without plus disease [12]. The main treatments for ROP—laser photocoagulation and intravitreal injections of anti-vascular endothelial growth factor (anti-VEGF) agents—focus on the proliferative phase of the disease, which leads to neovascularization rather than the initial phase [15,16]. Preventive measures are essential given the risks associated with treatment and the potential for long-term functional consequences [15,17,18].
Current screening guidelines primarily rely on birth weight (BW) and GA. However, numerous studies have proposed additional risk factors for ROP development [19]. Notably, few studies have differentiated between risk factors for the onset of ROP and those associated with its progression—an understanding critical for developing effective preventive strategies.
This study aims to analyze the incidence of ROP, as well as the risk factors contributing to both the development and progression of the disease.

2. Materials and Methods

2.1. Ethical Approval

The Scientific Council of the Faculty of Medicine of the University of Lisbon, along with the scientific councils of all participating hospital centers, the Ethics Committee of Centro Hospitalar Universitário de Lisboa Norte and Centro Académico de Medicina de Lisboa (CAML), as well as the ethics committees of all participating hospital centers, have granted their approval for this study. Written informed consent was obtained from parents. The study complied with the tenets of the Declarations of Helsinki and Tokyo.

2.2. Study Design and Population

This prospective, multicenter, and observational cohort study (ISRCTN16889608) included preterm infants born in eight Neonatal Intensive Care Units (NICUs) at hospital centers in the north, center, and south of Portugal. The study was conducted in phases in the different hospital centers between 19 November 2018 and 21 July 2021.
The inclusion and exclusion criteria were previously explained [20]. All infants born with a GA < 32 weeks or a BW < 1500 g were included. Infants with ocular diseases other than ROP (except conjunctivitis, keratitis, and congenital nasolacrimal duct obstruction), those with no known outcome of ROP, or those with insufficient clinical data were excluded.

2.3. Data Collection

Demographic, laboratory, and clinical data were collected. Biochemical parameters during the first week of life were determined using standardized methods.
Neonatal data included the following:
(1) Birth data: mode of delivery, GA, gender, body weight, small for GA (SGA) (BW percentile < 10), Apgar score, and need for resuscitation with endotracheal intubation.
(2) Postnatal data included the following:
  • Pathologies, such as early sepsis (onset in the first 72 h of life), late sepsis (onset after the first 72 h of life), moderate and severe bronchopulmonary dysplasia [21], peri-intraventricular hemorrhage grade ≥ 2 [22], cystic periventricular leukomalacia [22], hemodynamically significant patent ductus arteriosus [23], necrotizing enterocolitis, and phototherapy.
  • Treatments, including days of mechanical ventilation (invasive and non-invasive) and maximum fraction of inspired oxygen (FiO2), surfactant use, erythropoietin or darbepoetin, systemic and inhaled corticosteroid, non-steroidal anti-inflammatory, diuretic, red blood cell (RBC), platelets, and plasma transfusions received.
  • Metabolic acidosis (considered if pH < 7.2 and bicarbonate < 16 mmol/L) measured on the first day of life at two time points (within the first 2 h and between 2 and 24 h).
  • Body weight throughout the first month of life.
  • Number of days with hyperglycemia (blood glucose > 125 mg/dL, measured every 8 h using a point-of-care glucometer) in the first three weeks of life.
  • Nutritional data, including the day of the start of trophic, nutritious and total enteral nutrition, as well as breast milk feeding.
  • Length of hospital stay (in days).
  • Biochemical parameters during the first week of life: serum urea (mg/dL), creatinine (mg/dL), and total and direct bilirubin (mg/dL).
Maternal data included maternal age, family ancestry, level of education, behavioral habits, obstetric history (previous pregnancies, use of assisted reproductive technologies, single or multiple gestations), and maternal pathologies such as chronic or pregnancy-induced hypertension (gestational hypertension with or without preeclampsia/eclampsia), diabetes, and chorioamnionitis.

2.4. ROP Screening and Ophthalmological Data Collection

ROP screening and ophthalmological data collection were previously described [20]. An initial retinal examination was performed using indirect ophthalmoscopy or digital fundus retinography at 32 weeks of postmenstrual age or between 4 and 6 weeks of life, whichever occurred later. Scheduled follow-up examinations were conducted for each case based on the presence, severity, and location of ROP. These examinations were repeated until complete retinal vascularization or remission of ROP. Initial and follow-up assessments were recorded following the International Classification of ROP Revisited [11]. The indication for treatment of ROP followed the Early Treatment for ROP Study [24]. All infants diagnosed with type 1 ROP were treated with laser photocoagulation or anti-VEGF. The choice of treatment depended on the location and stage of the disease, the general condition of the infant, and the hospital center.

2.5. Statistical Analysis

Descriptive data for each categorical variable were presented as the absolute frequency and the corresponding proportion. The Pearson χ2 test was used to evaluate the significant differences between groups. The median and interquartile range or mean and standard deviation were presented for continuous variables. If the variables had normal distribution and homogeneity, the Student’s t-test was used; if not, Mann–Whitney was used to compare groups. To assess the risk factors for ROP versus No ROP or ROP not requiring treatment versus Type 1 ROP, a logistic regression analysis and the corresponding 95% CI were calculated. We first performed univariate analysis to approach relations between independent variables (GA, BW, Apgar score 5th minute, number of days with hyperglycemia, days of oxygen supplementation, RBC and platelets transfusions, bronchopulmonary dysplasia, persistent ductus arteriosus, sepsis, necrotizing enterocolitis, preeclampsia/eclampsia, and gestational diabetes) and outcomes (ROP vs. No ROP or ROP not requiring treatment vs. Type 1 ROP). When univariate analyses yielded a p-value < 0.1, those variables were incorporated into multivariable logistic regression models. Statistical analysis was executed with the IBM® SPSS® Statistics version 28.0 for Windows®, with a significant value of p < 0.05.

3. Results

3.1. Baseline Clinical Information

During the recruitment period, 647 infants met the inclusion criteria. Not including 42 infants without informed consent and 150 due to reasons that precluded complete data collection (62 deaths, 54 hospital transfers, 33 incomplete records, and 1 enrolled in another study), 455 infants were included in the final cohort. The median GA was 29.6 ± 3.2 weeks, and the median BW was 1175.7 ± 445.0 g, with 50.5% (n = 230) female (Table 1). Additional detailed data can be found in the supplementary materials (Supplementary Table S1).

3.2. Factors That Were Influencing ROP Development and Progression

Table 1 and Table 2 show the cohort’s demographic and clinical characteristics and their correlation with the development of ROP and its progression to ROP requiring treatment (type 1 ROP). Additional detailed data for Table 2 can be found in the supplementary materials (Supplementary Table S2). Table 3 shows maternal demographic and prenatal characteristics and their association with ROP development and progression. Further details are available in Supplementary Table S3. An increased mean number of RBC transfusions was significantly associated with a higher severity of ROP (p < 0.001). As depicted in Figure 1, infants with more severe ROP, including type 1, required more transfusions compared to those with milder stages or no ROP. The mean number of RBC transfusions progressively decreased from type 1 to stages 3, 2, and 1, with the lowest in infants without ROP. Logistic regression identified GA and the number of RBC transfusions as significant risk factors for both the development and progression of ROP. The clinical and demographic characteristics shown in Table 1, Table 2 and Table 3 were adjusted for these risk factors.
Therefore, GA, the number of RBC and platelet transfusions, maximum FiO2 at birth and in the second week of life, surfactant administration, and duration of hospitalization were significantly and independently associated with the development of ROP. Unexpectedly, being SGA was independently associated with a reduced likelihood of ROP development.
The variables significantly and independently associated with progression to ROP requiring treatment were GA, number of RBC transfusions, dystocic birth, resuscitation with intubation, early and late sepsis, day of initiation of trophic and nutritive enteral nutrition, Portuguese ancestry, level of mother education, assisted reproduction techniques, and maternal chronic arterial hypertension.

3.3. Characteristics of ROP

The incidence of ROP was 37.8% (172/455), and 4.6% (21/455) of the infants developed type 1 ROP. ROP stages 1 and 2 were the first and second most frequent, respectively (Table 4). None of the infants had ROP stage 4 or 5.
The mean postmenstrual age at the time of ROP diagnosis was 33.4 weeks in the group that developed type 1 ROP, slightly earlier than in those who did not require treatment for ROP, where the mean was 34.2 weeks. The postmenstrual age at the maximum stage of ROP was higher in infants who developed type 1 ROP, averaging 36.5 weeks, compared to 35.3 weeks in those who did not develop type 1 ROP. There was a statistically significant difference in the distribution of ROP across zones, with Zone II showing the highest prevalence (85.5%) (Figure 2). Additionally, the stages of ROP differed significantly across the zones (p = 0.003), as did the comparison between type 1 ROP and other stages (p < 0.001). In Zone I, only 6 infants were in stage 1 ROP, while 9 and 8 infants were in stages 2 and 3, respectively. Zone II was the most prevalent, encompassing all stages of ROP, whereas Zone III included only cases of stage 1 ROP. Type 1 ROP was identified in 42 eyes, with 76.2% occurring in Zone II and none in Zone III. Nearly all eyes with type 1 ROP were at stage 3, with only two at stage 2 (Table 4). Fourteen eyes were treated with anti-VEGF (bevacizumab), twenty-four with laser photocoagulation, and four initially received anti-VEGF but later required laser photocoagulation. Among these four, one subsequently required surgery due to vitreous hemorrhage. Anti-VEGF was administered for all cases of Type 1 ROP in Zone I and posterior Zone II. Importantly, no infant with stage 1 ROP required treatment.

4. Discussion

The incidence and severity of ROP vary significantly across countries, influenced by the quality of neonatal care and the availability of effective screening and treatment programs [25]. Comparing ROP incidence in population-based studies is challenging due to differences in study methodologies, survival rates, infants’ GA, and treatment protocols [1].
A recent meta-analysis reported an overall ROP prevalence of 31.9%, with 7.5% classified as severe ROP [26]. While overall ROP rates have remained stable over the past four decades (1985–2021), preterm infants with a GA of 28 weeks or less showed higher incidence. Lower-middle-income countries had higher overall ROP prevalence, whereas high-income countries had more severe cases [26].
In our study, 37.8% (172/455) of infants developed ROP, with 4.6% (21/455) requiring treatment. This study represents the most extensive prospective study on ROP in Portugal, encompassing eight NICUs.
A previous single-center prospective study in Portugal found that 21.7% (33/152) of neonates developed ROP, with 3.9% (6/152) requiring treatment [27]. Most Portuguese ROP studies are single-center and retrospective, resulting in varying incidence rates [28,29,30].
Multivariate regression analysis identified GA at birth and the number of RBC transfusions as crucial risk factors for ROP development and progression, highlighting their predominant role in ROP pathogenesis compared to other known risk factors. Notably, infants with a GA ≤ 28 weeks accounted for 65.1% of all ROP cases and 100% of those requiring treatment, consistent with findings from other studies that emphasize GA as a critical determinant of both the occurrence and severity of ROP [31]. This is likely due to the incomplete retinal vascular development in extremely preterm infants, which increases their vulnerability to oxidative stress.
Several studies have demonstrated a strong association between RBC transfusions and ROP [32]. Transfusing adult RBCs reduces the HbF to adult hemoglobin A (HbA) ratio, with this effect becoming more pronounced as the number of transfusions increases [32]. This reduction in HbF shifts the oxygen dissociation curve to the right, enhancing oxygen delivery to the retina, leading to increased oxidative stress and a reduced angiogenic stimulus [33]. HbF is critical in mitigating oxidative stress by preventing heme release and demonstrating superior pseudo-peroxidase activity, rapidly converting reactive ferryl-heme compared to HbA [34]. Our previous research suggested that a polymorphism in the lysine-specific histone demethylase 1A (KDM1A) gene, which regulates HbF suppression and erythroid maturation, might influence ROP susceptibility by affecting erythropoiesis and the transition from HbF to HbA [9]. Interventions that slow the decline in HbF following adult RBC transfusions should be explored to reduce ROP incidence and severity [34]. Approaches such as delayed umbilical cord clamping, blood-sparing sampling techniques, and the use of umbilical cord blood for transfusions show promise in maintaining physiological HbF percentages, potentially mitigating ROP risk [32,35,36]. The potential benefit of utilizing umbilical cord blood for transfusions is currently being investigated in a multicenter randomized trial (NCT05100212) [37].
While some variables, such as the frequency of RBC transfusions and GA, may represent secondary associations, the robust sample size provides strong statistical power to confirm their relevance. Our findings highlight the critical role of RBC transfusions and a low GA in ROP development and progression. The number of platelet transfusions was significantly associated with the development and progression of ROP, but only independently with its development. Several studies have linked platelet transfusions to ROP [38]. Similar to anemia, thrombocytopenia in preterm infants may result from a marked deficiency in erythropoietin production due to their immature kidneys, with the severity increasing as the GA at birth decreases [39]. Erythropoietin is an oxygen-regulated growth factor that, in addition to stimulating erythropoiesis and promoting angiogenesis, has anti-apoptotic effects and plays a role in thrombopoiesis [40,41]. Additionally, platelets contain crucial angiogenic factors; therefore, thrombocytopenia can impair angiogenesis in the incompletely vascularized retina [42].
Low BW is a recognized risk factor for ROP, although its impact varies across studies [43]. Our study confirmed a significant association between lower BW and both the development and progression of ROP, with this relationship being influenced by GA at birth and the number of RBC transfusions.
SGA was more prevalent among infants who did not develop ROP than among those who did. This finding may be attributed to the study’s criteria, which included SGA infants with a higher GA, allowing for more advanced retinal vascular development despite their lower BW. In contrast, a study in Brazil found no significant association between SGA and ROP [44].
Since ROP was first described, its development has been strongly linked to oxygen exposure [45]. Numerous studies have correlated ROP with high FiO2 levels and prolonged mechanical ventilation [46]. Our study further supports these findings, showing that higher maximum FiO2 levels during the first three weeks of life and extended mechanical ventilation significantly influence ROP development. Interestingly, the association between ROP and maximum FiO2 was independent at birth and in the second week of life. However, this association was not independent in the first week, likely due to the complex interplay of factors affecting ROP during this early period.
We identified a significant and independent association between surfactant use and ROP development, likely due to the increased need for supplemental oxygen in infants treated for respiratory distress syndrome (RDS) [47,48].
Our study highlights the significance of both early and late sepsis as independent risk factors for the progression of ROP. Systemic inflammation may predispose infants to ROP, with several studies identifying it as a crucial risk factor [49,50]. Sepsis can trigger the production of cytokines, chemokines, and growth factors, impairing angiogenesis and worsening retinal ischemia [51]. This process is often accompanied by hypotension, further compromising retinal perfusion [52]. In animal models of ROP, systemic inflammation has also been shown to disrupt retinal blood vessel development, leading to abnormal vascularization [53].
Delaying enteral nutrition was associated with ROP progression, suggesting the potential benefits of early feeding for at-risk preterm infants. However, since sicker infants typically start feeding later, this may have influenced our results. Further research is needed to clarify this relationship [54].
In our study, lower weight gain in the first 30 days of life was associated with the development and progression of ROP, although not independently. Slow postnatal weight gain has emerged as a potential predictor of ROP [55]. While low insulin-like growth factor-1 (IGF-1) levels, which are not routinely measured in NICUs, are associated with ROP risk, weight gain can serve as a proxy due to its correlation with IGF-1 and infant growth [56,57,58,59]. The WINROP model, introduced in 2006, uses postnatal weight gain to predict ROP risk and has been validated in various populations [60,61,62]. Our findings highlight the potential for refining ROP screening guidelines by incorporating weight gain data to reduce unnecessary examinations.
Dystocic birth was independently associated with type 1 ROP in our study. Of the 327 dystocic births, 322 (98.5%) were cesarean deliveries. The link between delivery type and ROP may be influenced by the maternal conditions leading to cesarean sections [63,64].
Resuscitation with endotracheal intubation at birth was significantly associated with ROP development and its progression, likely due to the associated risks of hypoxia and hyperoxia [65]. Low Apgar scores have been suggested as a potential risk factor for ROP development [66]; however, our study did not find an independent relationship. While bronchopulmonary dysplasia, which shares similar pathophysiological mechanisms with ROP in premature infants [67], was associated with ROP development and progression, this association was not independent.
In previous research, we identified an association between specific blood count parameters and ROP [20]. Our current study suggests that serum creatinine is associated with ROP development and progression. Serum urea, another potential ROP biomarker [68], was also associated with the development of ROP. Interestingly, elevated total bilirubin levels were associated with a lower risk of ROP, possibly due to its antioxidant effects or higher RBC counts [69]. Hyperglycemia in the first three weeks of life was associated with ROP development and progression, although a meta-analysis found otherwise [70]. None of these associations were independent.
The duration of hospitalization was significantly longer in infants with ROP, particularly those requiring treatment, reflecting greater morbidity.
Our study found that progression to type 1 ROP was associated with chronic arterial hypertension, lower maternal education levels, and Portuguese ancestry. Maternal chronic hypertension was independently associated with type 1 ROP, whereas pregnancy-induced hypertension appeared to have a protective effect, possibly due to preeclampsia’s role in stimulating HbF synthesis [71]. Although the impact of maternal education and socioeconomic status on ROP remains unclear, it may influence the quality of prenatal and postnatal care [72]. Additionally, since type 1 ROP is reported to be less common among Black preterm infants [73], the higher prevalence of type 1 ROP among those of Portuguese ancestry may be related to the greater proportion of African origin in the non-Portuguese population in Portugal.
Assisted reproductive techniques were independently associated with a reduced risk of ROP requiring treatment, likely due to close monitoring and less severe associated conditions [74,75].
Of the 337 eyes with ROP, 288 (85.5%) were in Zone II and 23 (6.8%) in Zone I. Among the 42 treated eyes, 10 (23.8%) had Zone I ROP and 32 (76.2%) had Zone II ROP. No ROP stage 4 or 5 cases were observed, and all treated cases achieved remission, underscoring the effectiveness of timely treatment and screening. Infants with type 1 ROP were diagnosed at stage 1 earlier than those who did not require treatment.
All cases treated with laser photocoagulation achieved remission, and while anti-VEGF therapy was also effective, four cases experienced recurrences that were successfully managed. These findings underscore the importance of close follow-ups to ensure long-term treatment success, particularly in patients treated with anti-VEGF agents, as recurrences can occur, with a significant number of these failures reported after 50 weeks postmenstrual age [76]. Current Portuguese guidelines recommend screening preterm infants with a GA < 32 weeks, BW < 1500 g, and BW < 2000 g with a prolonged need for supplemental oxygen or unstable clinical evolution [77]. Our study detected ROP in 2.2% of infants over 32 weeks GA, but none required treatment. Similarly, 1.3% of infants with BW > 1500 g developed ROP, with no cases requiring treatment. Our findings support the use of algorithmic models based on GA, BW, and weight gain to optimize ROP screening [78].
Efficient ROP screening should identify all at-risk preterm infants while minimizing the potential harms of over-screening, such as discomfort to the infant, excessive use of human resources, and high costs. Making an informed decision about the optimal screening method requires a thorough understanding and comprehensive analysis of the risk factors for ROP and its progression.
This study underscores the necessity of a multifaceted approach to ROP prevention, focusing on key risk factors such as oxygen management, transfusions, and sepsis prevention. Optimizing neonatal care practices, including perinatal interventions like delayed cord clamping and meticulous oxygen management, is essential in reducing ROP incidence by minimizing fluctuations in oxygen levels that contribute to oxidative stress in the retina. Additionally, strict infection control and careful management of RBC and platelet transfusions are crucial, as these directly affect retinal oxygenation and vascularization. These findings, consistent with previous research [13], highlight the need for ongoing refinement of neonatal care practices to prevent ROP progression and improve outcomes for preterm infants.
Future large-scale studies should validate these risk factors and explore innovative strategies, such as minimizing adult RBC transfusions, to enhance ROP management. This could lead to more effective screening models and tailored interventions, ultimately reducing the burden of ROP in preterm infants.
Integrating artificial intelligence (AI) into ROP screening and prevention offers transformative potential by improving early diagnosis and addressing the complex interplay of risk factors. AI can enhance screening accuracy by analyzing large NICU datasets and identifying patterns across diverse risk factors, such as transfusions and oxygen exposure, as well as by tracking the progression of ROP. This allows for more precise predictions and early identification of high-risk infants who could benefit from earlier or more frequent screenings. AI’s ability to automate retinal image analysis also ensures rapid and consistent assessments, reducing variability among examiners [79]. When combined with clinical data, AI can create comprehensive risk profiles for personalized care plans and monitor the effectiveness of interventions, dynamically adjusting treatment strategies to prevent ROP progression and optimize outcomes.
Our study has limitations. The multicentric design meant that different ophthalmologists conducted ROP screenings at various centers, which could introduce variability. Additionally, the exclusion of older preterm infants may have limited our ability to identify risk factors for ROP in this group. Despite these limitations, our prospective multicenter approach provides a representative sample from various regions of Portugal.

5. Conclusions

This study highlights several critical factors influencing the development and progression of ROP. Our findings suggest that a low GA and the number of RBC transfusions are potential predictors of both the onset and progression of ROP. Additionally, platelet transfusions, elevated maximum FiO2, and surfactant use were significantly associated with ROP development, while progression to severe ROP requiring treatment was associated with early and late sepsis, maternal chronic hypertension, and delayed initiation of enteral nutrition.
These results emphasize the importance of careful management in low-GA preterm infants, particularly concerning RBC and platelet transfusions, FiO2 levels, and vigilance for systemic inflammation. The association between postnatal weight gain and ROP reinforces the value of incorporating weight gain into predictive models, alongside GA and BW, to improve ROP screening accuracy. Moreover, the significant impact of GA and RBC transfusions underscores the need for strategies that preserve HbF percentages and optimize transfusion practices in preterm infants.
Integrating AI into ROP screening and prevention strategies offers significant potential for improving these efforts. AI-driven models can help develop personalized and effective screening protocols, improving early diagnosis and tailoring interventions to individual risk profiles. Future research should focus on validating these AI-driven approaches in diverse clinical settings and exploring their ability to transform neonatal care practices. Further research is necessary to validate these findings and refine predictive models. Enhancing screening accuracy and developing more effective intervention strategies are crucial to reducing the impact of ROP on preterm infants and improving their long-term visual outcomes.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/children11101154/s1, Table S1. Demographic and clinical characteristics of preterm infants according to the development (a) and progression (b) of retinopathy of prematurity (ROP). Table S2. Clinical data related to supplemental oxygen therapy and the number of RBC transfusions to preterm infants according to the development (a) and progression (b) of ROP. Table S3. Prenatal and maternal demographic and clinical characteristics according to the development (a) and progression (b) of ROP.

Author Contributions

Conceptualization: M.F.-M. and H.G. Formal analysis: M.F.-M. and H.G. Resources: M.B. Data curation: M.F.-M. and A.C.S. Writing—original draft preparation: M.F.-M. Writing—review and editing: M.F.-M., A.C.S., C.M.-N., M.B. and H.G. Project administration: M.F.-M. and M.B. Funding acquisition: M.F.-M. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Institute for Scientific Research Bento da Rocha Cabral, and the Genetics Laboratory, Environmental Health Institute (ISAMB), Associate Laboratory TERRA, Faculty of Medicine of the University of Lisbon. The writing of the manuscript was also supported by the Institute for Scientific Research Bento da Rocha Cabral and funds from the Foundation for Science and Technology to ISAMB (ref. UIDB/04295/2020 and UIDP/04295/2020), Ph.D. scholarship in medicine from the company CUF and the Portuguese Society of Ophthalmology.

Institutional Review Board Statement

The study (ISRCTN16889608) was conducted according to the guidelines of the Declarations of Helsinki and Tokyo. This study was approved by the Scientific Council of the Faculty of Medicine at the University of Lisbon and the Ethics Committees of several hospital centers. The respective protocol codes and approval dates are as follows: Centro Hospitalar Universitário de Lisboa Norte and Centro Académico de Medicina de Lisboa (CAML), protocol code 340/2018, approval on 19 October 2018; Ethics Committee of Hospital Professor Doutor Fernando Fonseca, protocol code 70/2018, approval on 12 December 2018; Ethics Committee of Centro Hospitalar Universitário de São João, protocol code 20–19, approval on 21 January 2019; Ethics Committee of Centro Hospitalar e Universitário de Coimbra, protocol code CHUC-014–019, approval on 16 April 2019; Ethics Committee of Centro Hospitalar Universitário do Porto, protocol code 031-DEFI/032-CE, approval on 21 May 2019; Ethics Committee of Hospital de Braga, protocol code 15/2019, approval on 20 March 2019; Ethics Committee of Hospital da Senhora da Oliveira Guimarães, protocol code 01/19-CAc, approval on 11 January 2019. All data collected were de-identified and treated as confidential clinical information to protect participants’ privacy.

Informed Consent Statement

Written informed consent was obtained from the parents of all infants involved in the study.

Data Availability Statement

The corresponding author can provide the datasets analyzed in this study upon reasonable request due to ethical reasons.

Acknowledgments

GenE-ROP Study Group. The following are the investigators involved in this research project and their respective affiliations: Grupo Ecogenética e Saúde Humana, Instituto de Saúde Ambiental-ISAMB, Laboratório Associado TERRA, Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal: Mariza Fevereiro-Martins; Ana Carolina Santos; Joana Ferreira; Lúcia Gomes; Maria Conceição Afonso; Carlos Marques-Neves; Manuel Bicho. Centro Hospitalar Universitário de Lisboa Norte, Lisbon, Portugal: Rita Espírito Santo; Filipa Teixeira; Rita Rosa; Cristina Vaz Carneiro; Marta Ferreira; Teresa Matos. Centro Hospitalar Universitário do Porto, Oporto, Portugal: Luísa Neiva; Sandra Pereira; Sofia Aires; Ricardo Parreira; Zuzana Melnik; João Faria. Hospital de Braga, Braga, Portugal: Joana Teixeira; Pedro Barros; Juliana Almeida; Bruna Malheiro; Patrícia Cunha Rodrigues; Luís Albuquerque. Hospital da Senhora da Oliveira, Guimarães, Portugal: Alice Freitas, Pedro Barros; Nadezda Kotchekova; Rui Freitas; Ana Cristina Silveira; Ana Ferreira. Hospital Professor Doutor Fernando Fonseca, Amadora, Portugal: Benvinda Morais; Susana Teixeira; Mafalda Mota; Maria Guerra; Lúcia Coimbra; João Gigante. Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal: Muriel Ferreira; Patrícia Lapa; Madalena Monteiro; Mário Alfaiate; Teresa Rodrigues; Teresa Pina. Centro Hospitalar Universitário de São João, Porto, Portugal: Marta Rosário; Renato Silva; Jorge Breda; Filipa Bazenga; João A. Pinto; Hercília Guimarães. We thank Sara Dias, from CUF, for her invaluable assistance with the statistical analysis and the CUF Academic Center for supporting this work.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Hellström, A.; Smith, L.E.H.; Dammann, O. Retinopathy of prematurity. Lancet 2013, 382, 1445–1457. [Google Scholar] [CrossRef] [PubMed]
  2. Bhatnagar, A.; Skrehot, H.C.; Bhatt, A.; Herce, H.; Weng, C.Y. Epidemiology of Retinopathy of Prematurity in the US From 2003 to 2019. JAMA Ophthalmol. 2023, 141, 479–485. [Google Scholar] [CrossRef] [PubMed]
  3. Bai, W.H.; Gu, D.F.; Dai, Y.; Chen, Y.H.; Yang, Z.M.; Lu, L.J. The relationship between probiotics and retinopathy of prematurity in preterm infants: A population-based retrospective study in China. Front. Pediatr. 2023, 11, 1055992. [Google Scholar] [CrossRef] [PubMed]
  4. Banjac, L.; Banjac, G.; Kotur-Stevuljević, J.; Spasojević-Kalimanovska, V.; Gojković, T.; Bogavac-Stanojević, N.; Jelić-Ivanović, Z.; Banjac, G. Pro-oxidants and antioxidants in retinopathy of prematurity. Acta Clin. Croat. 2018, 57, 458–463. [Google Scholar] [CrossRef] [PubMed]
  5. Elizabeth Hartnett, M. Discovering Mechanisms in the Changing and Diverse Pathology of Retinopathy of Prematurity: The Weisenfeld Award Lecture. Investig. Ophthalmol. Vis. Sci. 2019, 60, 1286–1297. [Google Scholar] [CrossRef] [PubMed]
  6. Hartnett, M.E. Advances in understanding and management of retinopathy of prematurity. Surv. Ophthalmol. 2017, 62, 257–276. [Google Scholar] [CrossRef]
  7. Hartnett, M.E.; Morrison, M.A.; Smith, S.; Yanovitch, T.L.; Young, T.L.; Colaizy, T.; Momany, A.; Dagle, J.; Carlo, W.A.; Clark, E.A.S.; et al. Genetic variants associated with severe retinopathy of prematurity in extremely low birth weight infants. Investig. Ophthalmol. Vis. Sci. 2014, 55, 6194–6203. [Google Scholar] [CrossRef]
  8. Bizzarro, M.J.; Hussain, N.; Jonsson, B.; Feng, R.; Ment, L.R.; Gruen, J.R.; Zhang, H.; Bhandari, V. Genetic susceptibility to retinopathy of prematurity. Pediatrics 2006, 118, 1858–1863. [Google Scholar] [CrossRef]
  9. Fevereiro-Martins, M.; Santos, A.C.; Marques-Neves, C.; Guimarães, H.; Bicho, M.; On behalf of the GenE-Rop Study Group. Genetic Modulation of the Erythrocyte Phenotype Associated with Retinopathy of Prematurity—A Multicenter Portuguese Cohort Study. Int. J. Mol. Sci. 2023, 24, 11817. [Google Scholar] [CrossRef]
  10. The Committee for the Classification of Retinopathy of Prematurity. An international classification of retinopathy of prematurity. Arch. Ophthalmol. 1984, 102, 1130–1134. [Google Scholar] [CrossRef]
  11. Quinn, G.E. The International Classification of Retinopathy of Prematurity revisited. Arch. Ophthalmol. 2005, 123, 991–999. [Google Scholar] [CrossRef]
  12. Chiang, M.F.; Quinn, G.E.; Fielder, A.R.; Ostmo, S.R.; Paul Chan, R.V.; Berrocal, A.; Binenbaum, G.; Blair, M.; Peter Campbell, J.; Capone, A.; et al. International Classification of Retinopathy of Prematurity, Third Edition. Ophthalmology 2021, 128, e51–e68. [Google Scholar] [CrossRef] [PubMed]
  13. Chan-Ling, T.; Gole, G.A.; Quinn, G.E.; Adamson, S.J.; Darlow, B.A. Pathophysiology, screening and treatment of ROP: A multi-disciplinary perspective. Prog. Retin. Eye Res. 2018, 62, 77–119. [Google Scholar] [CrossRef] [PubMed]
  14. Hartnett, M.E. Pathophysiology of Retinopathy of Prematurity. Annu. Rev. Vis. Sci. 2023, 9, 39–70. [Google Scholar] [CrossRef] [PubMed]
  15. Liegl, R.; Hellström, A.; Smith, L.E.H. Retinopathy of prematurity: The need for prevention. Eye Brain 2016, 8, 91–102. [Google Scholar] [CrossRef]
  16. Ryu, J. New Aspects on the Treatment of Retinopathy of Prematurity: Currently Available Therapies and Emerging Novel Therapeutics. Int. J. Mol. Sci. 2022, 23, 8529. [Google Scholar] [CrossRef]
  17. Mataftsi, A.; Dimitrakos, S.A.; Adams, G.G.W. Mediators involved in retinopathy of prematurity and emerging therapeutic targets. Early Hum. Dev. 2011, 87, 683–690. [Google Scholar] [CrossRef]
  18. Rivera, J.C.; Holm, M.; Austeng, D.; Morken, T.S.; Zhou, T.E.; Beaudry-Richard, A.; Sierra, E.M.; Dammann, O.; Chemtob, S. Retinopathy of prematurity: Inflammation, choroidal degeneration, and novel promising therapeutic strategies. J. Neuroinflammation 2017, 14, 165. [Google Scholar] [CrossRef]
  19. Kim, S.J.; Port, A.D.; Swan, R.; Campbell, J.P.; Chan, R.V.P.; Chiang, M.F. Retinopathy of prematurity: A review of risk factors and their clinical significance. Surv. Ophthalmol. 2018, 63, 618–637. [Google Scholar] [CrossRef]
  20. Fevereiro-Martins, M.; Santos, A.C.; Marques-Neves, C.; Guimarães, H.; Bicho, M.; Afonso, C.; Ferreira, J.; Santo, R.E.; Teixeira, F.; Rosa, R.; et al. Complete blood count parameters as biomarkers of retinopathy of prematurity: A Portuguese multicenter study. Graefe Arch. Clin. Exp. Ophthalmol. 2023, 261, 2997–3006. [Google Scholar] [CrossRef]
  21. Proença, E.; Vasconcellos, G.; Rocha, G.; Carreira, M.L.; Mateus, M.; Santos, I.D.; Sossai, M.D.R.; Morais, B.; Guimarães, I.M.H. Displasia broncopulmonar. Soc. Port. Neonatol. 2009. Available online: https://spp.pt/UserFiles/file/Protocolos/Displasia_Boncopulmonar_RN_2009.pdf (accessed on 12 January 2024).
  22. Taborda, A.; Pereira, A.; Graça, A.; Conceição, C.; Faria, C.; Trindade, C.; Chaves, F.; Pinto, F.; Corrêa, F.; Costa, J.; et al. Revisão do Consenso de Neuro-imagiologia Neonatal—versão maio 2013. Soc. Port. Neonatol. 2013. Available online: https://www.spneonatologia.pt/wp-content/uploads/2016/11/2010-Neuroimagiologia.pdf (accessed on 12 January 2024).
  23. Salazar, A.; Guedes, A.; Álvares, S.; Soares, P.; Morais, S.; Pires, A.; Tiago, J.; Andrade, H.; Fernandes, E.; Sampaio, M.A.; et al. Consenso nacional abordagem diagnóstica e terapêutica da persistência do canal arterial no recém-nascido pré-termo. Soc. Port. Neonatol. 2010. Available online: https://www.spp.pt/userfiles/file/protocolos/persistencia_canal_arterial_rn_pre_termo_2010.pdf (accessed on 11 January 2024).
  24. Good, W.V.; Hardy, R.J.; Dobson, V.; Palmer, E.A.; Phelps, D.L.; Quintos, M.; Tung, B. Revised Indications for the Treatment of Retinopathy of Prematurity: Results of the Early Treatment for Retinopathy of Prematurity Randomized Trial. Arch. Ophthalmol. 2003, 121, 1684–1696. [Google Scholar] [CrossRef]
  25. Leng, Y.; Huang, W.; Ren, G.; Cai, C.; Tan, Q.; Liang, Y.; Yang, W.; Gao, Z. The treatment and risk factors of retinopathy of prematurity in neonatal intensive care units. BMC Ophthalmol. 2018, 18, 301. [Google Scholar] [CrossRef]
  26. García, H.; Villasis-Keever, M.A.; Zavala-Vargas, G.; Bravo-Ortiz, J.C.; Pérez-Méndez, A.; Escamilla-Núñez, A. Global Prevalence and Severity of Retinopathy of Prematurity over the Last Four Decades (1985–2021): A Systematic Review and Meta-Analysis. Arch. Med. Res. 2024, 55, 102967. [Google Scholar] [CrossRef]
  27. Almeida, A.C.; Silva, G.A.; Santini, G.; Brízido, M.; Correia, M.; Coelho, C.; Borrego, L.M. Correlation between hyperglycemia and glycated albumin with retinopathy of prematurity. Sci. Rep. 2021, 11, 22321. [Google Scholar] [CrossRef]
  28. Almeida, R.L.; Costa, R.M.; Bennett, M.; Alfaiate, M.; Basto, L. Retinopathy of prematurity: Eight-year outcomes of a Portuguese neonatal intensive care unit. Nascer Crescer Birth Growth Med. J. 2023, 32, 82–88. [Google Scholar] [CrossRef]
  29. Figueiredo, R.; Sarmento, T.M.; Garrido, J.; Marques, M.I.N.; Almeida, T.; Carrasquinho, S. Applicability of the ROPScore as a predictive algorithm for early detection of retinopathy of prematurity. Rev. Soc. Port. Oftalmol. 2020, 44. [Google Scholar] [CrossRef]
  30. Malheiro, L.; Falcão, I.; Neiva, L.; Almeida, A.; Maia, S.; Miranda, V.; Parreira, R.; Menéres, P. Application of the WINROP model in Retinopathy of Prematurity (ROP) screening in a Portuguese cohort of premature infants. Rev. Bras. Oftalmol. 2019, 78, 30–36. [Google Scholar] [CrossRef]
  31. Yucel, O.E.; Eraydin, B.; Niyaz, L.; Terzi, O. Incidence and risk factors for retinopathy of prematurity in premature, extremely low birth weight and extremely low gestational age infants. BMC Ophthalmol. 2022, 22, 367. [Google Scholar] [CrossRef] [PubMed]
  32. Hellström, W.; Martinsson, T.; Morsing, E.; Gränse, L.; Ley, D.; Hellström, A. Low fraction of fetal haemoglobin is associated with retinopathy of prematurity in the very preterm infant. Br. J. Ophthalmol. 2022, 106, 970–974. [Google Scholar] [CrossRef] [PubMed]
  33. Chang, J.W. Risk factor analysis for the development and progression of retinopathy of prematurity. PLoS ONE 2019, 14, e0219934. [Google Scholar] [CrossRef] [PubMed]
  34. Teofili, L.; Papacci, P.; Bartolo, M.; Molisso, A.; Orlando, N.; Pane, L.; Giannantonio, C.; Serrao, F.; Bianchi, M.; Valentini, C.G.; et al. Transfusion-Free Survival Predicts Severe Retinopathy in Preterm Neonates. Front. Pediatr. 2022, 10, 814194. [Google Scholar] [CrossRef]
  35. Podraza, W. A new approach to neonatal medical management that could transform the prevention of retinopathy of prematurity: Theoretical considerations. Med. Hypotheses 2020, 137, 109541. [Google Scholar] [CrossRef]
  36. García González, E.; Casanova, M.A.; Samarkanova, D.; Aldecoa-Bilbao, V.; Teresa-Palacio, M.; Farssac Busquets, E.; Figueras-Aloy, J.; Salvia-Roigés, M.; Querol, S. Feasibility of umbilical cord blood as a source of red blood cell transfusion in preterm infants. Blood Transfus. 2021, 19, 510–517. [Google Scholar] [CrossRef]
  37. Teofili, L.; Papacci, P.; Orlando, N.; Bianchi, M.; Pasciuto, T.; Mozzetta, I.; Palluzzi, F.; Giacò, L.; Giannantonio, C.; Remaschi, G.; et al. BORN study: A multicenter randomized trial investigating cord blood red blood cell transfusions to reduce the severity of retinopathy of prematurity in extremely low gestational age neonates. Trials 2022, 23, 1010. [Google Scholar] [CrossRef]
  38. Ribeiro, C.; Rocha, G.; Flôr-de-Lima, F.; Ferreras, C.; Moita, R.; Silva, R.; Azevedo, I. Thrombocytopenia requiring platelet transfusions is predictive of retinopathy of prematurity in preterm infants. Minerva Pediatr. 2023. [Google Scholar] [CrossRef]
  39. Asada, N. Tubular immaturity causes erythropoietin-deficiency anemia of prematurity in preterm neonates. Sci. Rep. 2018, 8, 4448. [Google Scholar] [CrossRef]
  40. Hacein-Bey-Abina, S.; Estienne, M.; Bessoles, S.; Echchakir, H.; Pederzoli-Ribeil, M.; Chiron, A.; Aldaz-Carroll, L.; Leducq, V.; Zhang, Y.; Souyri, M.; et al. Erythropoietin is a major regulator of thrombopoiesis in thrombopoietin-dependent and -independent contexts. Exp. Hematol. 2020, 88, 15–27. [Google Scholar] [CrossRef]
  41. Suresh, S.; Rajvanshi, P.K.; Noguchi, C.T. The Many Facets of Erythropoietin Physiologic and Metabolic Response. Front. Physiol. 2020, 10, 1534. [Google Scholar] [CrossRef] [PubMed]
  42. Hellström, A.; Nilsson, A.K.; Wackernagel, D.; Pivodic, A.; Vanpee, M.; Sjöbom, U.; Hellgren, G.; Hallberg, B.; Domellöf, M.; Klevebro, S.; et al. Effect of Enteral Lipid Supplement on Severe Retinopathy of Prematurity: A Randomized Clinical Trial. JAMA Pediatr. 2021, 175, 359–367. [Google Scholar] [CrossRef] [PubMed]
  43. Hakeem, A.; Mohamed, G.; Othman, M. Retinopathy of prematurity: A study of prevalence and risk factors. Middle East Afr. J. Ophthalmol. 2012, 19, 289–294. [Google Scholar] [CrossRef] [PubMed]
  44. Fortes Filho, J.B.; Valiatti, F.B.; Eckert, G.U.; Da Costa, M.C.; Silveira, R.C.; Procianoy, R.S. Is being small for gestational age a risk factor for retinopathy of prematurity? A study with 345 very low birth weight preterm infants. J. Pediatr. 2009, 85, 48–54. [Google Scholar] [CrossRef] [PubMed]
  45. Rodriguez, S.H.; Ells, A.L.; Blair, M.P.; Shah, P.K.; Harper, C.A.; Martinez-Castellanos, M.A.; Prakalapakorn, S.G.; Denis, E.; Lusobya, R.C.; Greenwald, M.J.; et al. Retinopathy of Prematurity in the 21st Century and the Complex Impact of Supplemental Oxygen. J. Clin. Med. 2023, 12, 1228. [Google Scholar] [CrossRef]
  46. Mitsiakos, G.; Papageorgiou, A. Incidence and factors predisposing to retinopathy of prematurity in inborn infants less than 32 weeks of gestation. Hippokratia 2016, 20, 121–126. [Google Scholar]
  47. Lin, Y.W.; Chen, S.N.; Muo, C.H.; Sung, F.C.; Lin, M.H. Risk of Retinopathy of Prematurity in Preterm Births with Respiratory Distress Syndrome: A Population-Based Cohort Study in Taiwan. Int. J. Gen. Med. 2022, 15, 2149–2162. [Google Scholar] [CrossRef]
  48. de Pediatria, S.P.; Direção-Geral da Saúde. Prescrição de Surfactante Pulmonar na Síndrome de Dificuldade Respiratória do Recém-nascido. Available online: https://www.spp.pt/userfiles/file/evidencias em pediatria/dgs_012_2012_actualizada 08.2014.pdf (accessed on 25 January 2024).
  49. Dammann, O.; Stansfield, B.K. Neonatal sepsis as a cause of retinopathy of prematurity: An etiological explanation. Prog. Retin. Eye Res. 2024, 98, 101230. [Google Scholar] [CrossRef]
  50. Wang, X.; Tang, K.; Chen, L.; Cheng, S.; Xu, H. Association between sepsis and retinopathy of prematurity: A systematic review and meta-analysis. BMJ Open 2019, 9, e025440. [Google Scholar] [CrossRef]
  51. Bonafiglia, E.; Gusson, E.; Longo, R.; Ficial, B.; Tisato, M.G.; Rossignoli, S.; Caltran, G.; Pedrotti, E.; Beghini, R.; Marchini, G. Early and late onset sepsis and retinopathy of prematurity in a cohort of preterm infants. Sci. Rep. 2022, 12, 11675. [Google Scholar] [CrossRef]
  52. Bas, A.Y.; Demirel, N.; Koc, E.; Ulubas Isik, D.; Murat Hirfanoglu, İ.; Tunc, T. Clinical science Incidence, risk factors and severity of retinopathy of prematurity in Turkey (TR-ROP study): A prospective, multicentre study in 69 neonatal intensive care units. Br. J. Ophthalmol. 2018, 102, 1711–1716. [Google Scholar] [CrossRef] [PubMed]
  53. Hong, H.K.; Lee, H.J.; Ko, J.H.; Park, J.H.; Park, J.Y.; Choi, C.W.; Yoon, C.H.; Ahn, S.J.; Park, K.H.; Woo, S.J.; et al. Neonatal systemic inflammation in rats alters retinal vessel development and simulates pathologic features of retinopathy of prematurity. J. Neuroinflamm. 2014, 11, 87. [Google Scholar] [CrossRef] [PubMed]
  54. Gao, L.; Shen, W.; Wu, F.; Mao, J.; Liu, L.; Chang, Y.M.; Zhang, R.; Ye, X.Z.; Qiu, Y.P.; Ma, L.; et al. Effect of early initiation of enteral nutrition on short-term clinical outcomes of very premature infants: A national multicenter cohort study in China. Nutrition 2023, 107, 111912. [Google Scholar] [CrossRef] [PubMed]
  55. Bremner, A.; Yen Chan, L.; Jones, C.; Shah, S.P. Comparison of Weight-Gain-Based Prediction Models for Retinopathy of Prematurity in an Australian Population. J. Ophthalmol. 2023, 2023, 8406287. [Google Scholar] [CrossRef] [PubMed]
  56. Jensez, A.K.; Ying, G.S.; Huang, J.; Quinn, G.E.; Binenbaum, G. Postnatal Serum Insulin-like Growth Factor I and Retinopathy of Prematurity. Retina 2017, 37, 867–872. [Google Scholar] [CrossRef]
  57. Hellström, A.; Hård, A.L. Screening and novel therapies for retinopathy of prematurity—A review. Early Hum. Dev. 2019, 138, 104846. [Google Scholar] [CrossRef]
  58. Langford, K.; Nicoiaides, K.; Miell, J.P. Maternal and fetal insulin-like growth factors and their binding proteins in the second and third trimesters of human pregnancy. Hum. Reprod. 1998, 13, 1389–1393. [Google Scholar] [CrossRef]
  59. Pivodic, A.; Hård, A.L.; Löfqvist, C.; Smith, L.E.H.; Wu, C.; Bründer, M.C.; Lagrèze, W.A.; Stahl, A.; Holmström, G.; Albertsson-Wikland, K.; et al. Individual Risk Prediction for Sight-Threatening Retinopathy of Prematurity Using Birth Characteristics. JAMA Ophthalmol. 2020, 138, 21–29. [Google Scholar] [CrossRef]
  60. Löfqvist, C.; Hansen-Pupp, I.; Andersson, E.; Holm, K.; Smith, L.E.H.; Ley, D.; Hellström, A. Validation of a new retinopathy of prematurity screening method monitoring longitudinal postnatal weight and insulinlike growth factor I. Arch. Ophthalmol. 2009, 127, 622–627. [Google Scholar] [CrossRef]
  61. Choi, J.H.; Löfqvist, C.; Hellström, A.; Heo, H. Efficacy of the Screening Algorithm WINROP in a Korean Population of Preterm Infants. JAMA Ophthalmol. 2013, 131, 62–66. [Google Scholar] [CrossRef]
  62. Chaves-Samaniego, M.J.; Gómez Cabrera, C.; Chaves-Samaniego, M.C.; Escudero Gómez, J.; García Campos, J.M.; Muñoz Hoyos, A.; García Serrano, J.L. Multicenter validation study of the WINROP algorithm as a method for detecting retinopathy of prematurity. J. Matern. Neonatal Med. 2020, 33, 1302–1306. [Google Scholar] [CrossRef] [PubMed]
  63. Braimah, I.Z.; Enweronu-Laryea, C.; Sackey, A.H.; Kenu, E.; Agyabeng, K.; Ofori-Adjei, I.O.D.B.; Beyuo, V.; Oku, A.; Essuman, V.A. Incidence and risk factors of retinopathy of prematurity in Korle-Bu Teaching Hospital: A baseline prospective study. BMJ Open 2020, 10, e035341. [Google Scholar] [CrossRef] [PubMed]
  64. Wikstrand, M.H.; Hrd, A.L.; Niklasson, A.; Smith, L.; Löfqvist, C.; Hellström, A. Maternal and neonatal factors associated with poor early weight gain and later retinopathy of prematurity. Acta Paediatr. Int. J. Paediatr. 2011, 100, 1528–1533. [Google Scholar] [CrossRef] [PubMed]
  65. Lin, W.-C.; Jordan, B.K.; Scottoline, B.; Ostmo, S.R.; Coyner, A.S.; Singh, P.; Kalpathy-Cramer, J.; Erdogmus, D.; Chan, R.V.P.; Chiang, M.F.; et al. Oxygenation Fluctuations Associated with Severe Retinopathy of Prematurity Insights from a Multimodal Deep Learning Approach. Ophthalmol. Sci. 2024, 4, 100417. [Google Scholar] [CrossRef]
  66. Erdal, H.; Demirtas, M.S.; Kılıcbay, F.; Tunc, G. Evaluation of Oxidative Stress Levels and Dynamic Thiol-disulfide Balance in Patients with Retinopathy of Prematurity. Curr. Eye Res. 2023, 48, 1026–1033. [Google Scholar] [CrossRef]
  67. Stark, A.; Dammann, C.; Nielsen, H.C.; Volpe, M.A.V. A pathogenic relationship of bronchopulmonary dysplasia and retinopathy of prematurity? A review of angiogenic mediators in both diseases. Front. Pediatr. 2018, 6, 125. [Google Scholar] [CrossRef]
  68. Das, A.; Bhattacharjee, I.; Heis, F.; Sears, J.E.; Aly, H. Blood urea nitrogen, a marker for severe retinopathy of prematurity? HHS Public Access. J. Perinatol. 2023, 43, 830–832. [Google Scholar] [CrossRef]
  69. Hinds, T.D.; Stec, D.E. Bilirubin, a Cardiometabolic Signaling Molecule. Hypertension 2018, 72, 788–795. [Google Scholar] [CrossRef]
  70. Au, S.C.L.; Tang, S.M.; Rong, S.S.; Chen, L.J.; Yam, J.C.S. Association between hyperglycemia and retinopathy of prematurity: A systemic review and meta-analysis. Sci. Rep. 2015, 5, 9091. [Google Scholar] [CrossRef]
  71. Masoumi, Z.; Familari, M.; Källén, K.; Ranstam, J.; Olofsson, P.; Hansson, S.R. Fetal hemoglobin in umbilical cord blood in preeclamptic and normotensive pregnancies: A cross-sectional comparative study. PLoS ONE 2017, 12, e0176697. [Google Scholar] [CrossRef]
  72. Purisch, S.E.; Gyamfi-Bannerman, C. Epidemiology of preterm birth. Semin. Perinatol. 2017, 41, 387–391. [Google Scholar] [CrossRef] [PubMed]
  73. Port, A.D.; Chan, R.V.P.; Ostmo, S.; Choi, D.; Chiang, M.F. Risk factors for retinopathy of prematurity: Insights from outlier infants. Graefe Arch. Clin. Exp. Ophthalmol. 2014, 252, 1669–1677. [Google Scholar] [CrossRef] [PubMed]
  74. Esposito, G.; Cipriani, S.; Noli, S.; Franchi, M.; Corrao, G.; Parazzini, F.; Somigliana, E. The changing impact of assisted reproductive techniques on preterm birth during the period 2007–2020 in Lombardy, Northern Italy. Eur. J. Obstet. Gynecol. Reprod. Biol. 2022, 278, 51–56. [Google Scholar] [CrossRef] [PubMed]
  75. Dabir, S.; Mohankumar, A.; Srivatsa, D.V.; Munusamy, S.; Berendschot, T.T.J.M.; Rajan, M.; Azad, R. Retinopathy of prematurity in preterm infants born following assisted conception versus spontaneously conceived pregnancies—A 2-year retrospective observational study from an urban tertiary eye care referral center in South India. Indian J. Ophthalmol. 2023, 71, 408–410. [Google Scholar] [CrossRef] [PubMed]
  76. Xu, L.T.; Levine, D.A.; Hutchinson, A.K.; Rao, P.; Hubbard, G.B. Clinical Features and Outcomes of Infants with Retinopathy of Prematurity Who Fail Anti-VEGF Therapy. Retina 2021, 41, 2269–2277. [Google Scholar] [CrossRef]
  77. Henriques, G.; Brito, C.; Teixeira, S. Consenso Clínico Retinopatia da Prematuridade. Soc. Port. Pediatr. 2014. Available online: https://www.spneonatologia.pt/wp-content/uploads/2016/11/2014-ROP.pdf (accessed on 2 January 2024).
  78. Binenbaum, G.; Bell, E.F.; Donohue, P.; Quinn, G.; Shaffer, J.; Tomlinson, L.A.; Ying, G.S.; Donoh, P.; Nguyen, A.; Duros, T.B.; et al. Development of Modified Screening Criteria for Retinopathy of Prematurity: Primary Results From the Postnatal Growth and Retinopathy of Prematurity Study. JAMA Ophthalmol. 2018, 136, 1034–1040. [Google Scholar] [CrossRef]
  79. Parmar, U.P.S.; Surico, P.; Singh, R.; Romano, F.; Salati, C.; Spadea, L.; Musa, M.; Gagliano, C.; Mori, T.; Zeppieri, M. Artificial Intelligence (AI) for Early Diagnosis of Retinal Diseases. Medicina 2024, 60, 527. [Google Scholar] [CrossRef]
Children 11 01154 g001
Figure 1. Stage and severity of ROP in function of the mean number of RBC transfusions. † Patients who do not meet the criteria for Type 1 ROP. P, Chi-square test.
Figure 1. Stage and severity of ROP in function of the mean number of RBC transfusions. † Patients who do not meet the criteria for Type 1 ROP. P, Chi-square test.
Children 11 01154 g001
Children 11 01154 g002
Figure 2. Retinal zone distribution of the different stages of ROP: (a) regardless of the need for treatment; (b) considering the need for treatment (type 1 ROP). † Patients who do not meet the criteria for Type 1 ROP. P, Chi-square test.
Figure 2. Retinal zone distribution of the different stages of ROP: (a) regardless of the need for treatment; (b) considering the need for treatment (type 1 ROP). † Patients who do not meet the criteria for Type 1 ROP. P, Chi-square test.
Children 11 01154 g002
Table 1. Demographic and clinical characteristics of preterm infants according to the development (a) and progression (b) of retinopathy of prematurity (ROP).
Table 1. Demographic and clinical characteristics of preterm infants according to the development (a) and progression (b) of retinopathy of prematurity (ROP).
(a)(b)
Demographic and Clinical CharacteristicsNo ROP (n = 283)
n (%) or Median (Q1–Q3)		ROP (n = 172)
n (%) or Median (Q1–Q3)		PP *ROP Stages 1, 2, and 3 †
(n = 151)
n (%) or Median (Q1–Q3)		Type 1 ROP
(n = 21)
n (%) or Median (Q1–Q3)		PP *
BIRTH
Eutocic birth76 (27.0%)52 (30.2%)0.454 §0.56249 (32.5%)3 (14.3%)0.127 §0.027
Gestational age (weeks)30.4 (29.1–31.5)28.0 (26.4–29.3)<0.001 #NA28.3 (26.6–29.6)26.1 (25.1–27.2)<0.001 #0.013
≤2858 (20.5%)112 (65.1%)<0.001 §NA91 (60.3%)21 (100%)0.002 §NA
29–31160 (56.5%)50 (29.1%)50 (33.1%)0 (0%)
≥3265 (23.0%)10 (5.8%)10 (6.6%)0 (0%)
Birth weight (g)
≤100054 (19.1%)95 (55.2%)<0.001 §0.05576 (50.3%)19 (90.5%)0.002 §0.798
1001–1499171 (60.4%)71 (41.3%)69 (45.7%)2 (9.5%)
≥150058 (20.5%)6 (3.5%)6 (4.0%)0 (0%)
SGA81 (29.2%)45 (26.9%)0.603 §0.02739 (26.5%)6 (30.0%)0.790 §0.128
Gender
Female136 (48.1%)94 (54.7%)0.177 §0.18584 (55.6%)10 (47.6%)0.495 §0.487
Male147 (51.9%)78 (45.3%)67 (44.4%)11 (52.4%)
Resuscitation with endotracheal intubation39 (13.9%)80 (46.8%)0.001 §0.09969 (46.0%)11 (52.4%)0.645 §0.006
Oxygen191 (68.5%)148 (86.5%)< 0.001 §0.337131 (87.3%)17 (81.0%)0.491 §0.120
Maximum FiO2 (%)30.00 (27.25–40.00)42.50 (30.00–67.50)<0.001 #0.02842.50 (30.00–72.50)45.00 (30.00–52.50)0.382 #0.064
Apgar score 5th min < 714 (4.9%)26 (15.2%)<0.001 §0.15521 (14.0%)5 (23.8%)0.325 §0.699
POSTNATAL
Metabolic acidosis (first 2 h of life)2 (0.9%)8 (5.7%)0.008 §0.1657 (5.6%)1 (6.3%)1.000 §0.752
Metabolic acidosis 1st day (between 2 and 24 h)1 (0.6%)3 (2.4%)0.324 §0.0983 (2.8%)0 (0.0%)1.000 §0.999
Co-morbidities
Bronchopulmonary dysplasia moderate/ severe28 (10.0%)64 (37.4%)<0.001 §0.74147 (31.3%)17 (81.0%)<0.001 §0.053
Peri-intraventricular hemorrhage grade ≥ 220 (7.1%)37 (21.8%)<0.001 §0.38431 (20.8%)6 (28.6%)0.407 §0.713
Cystic periventricular leukomalacia4 (1.4%)9 (5.3%)0.022 §0.7677 (4.7%)2 (10.0%)0.289 §0.993
Necrotizing enterocolitis11 (3.9%)15 (9.0%)0.035 §0.83114 (9.6%)1 (5.0%)1.000 §0.071
Early sepsis26 (30.2%)25 (22.5%)0.252 §0.92619 (20.7%)6 (31.6%)0.366 §0.048
Late sepsis60 (69.8%)86 (77.5%)0.252 §0.92673 (79.3%)13 (68.4%)0.366 §0.048
Hemodynamically significant patent ductus arteriosus20 (7.1%)43 (25.1%)<0.001 §0.09531 (20.7%)12 (57.1%)0.001 §0.829
Hyperbilirubinemia with phototherapy237 (84.0%)162 (95.9%)<0.001 §0.275141 (95.3%)21 (100.0%)0.598 §0.999
Number of days with hyperglycemia (in the first 21 days)0.00 (0.00–2.00)2.00 (0.00–5.00)<0.001 #0.4852.00 (0.00–4.00)5.00 (3.00–7.00)0.001 #0.565
Treatments
RBC transfusions50 (17.7%)114 (66.3%)<0.001 §NA94 (62.3%)20 (95.2%)0.002 §NA
Platelet transfusions9 (3.2%)37 (21.5%)<0.001 §0.00829 (19.2%)8 (38.1%)0.084 §0.332
Days of invasive and non-invasive mechanical ventilation3.00 (1.00–11.00)32.00 (7.00–51.00)<0.001 #0.21726.00 (6.00–48.00)54.00 (39.50–78.00)<0.001 #0.481
Days of invasive mechanical ventilation0.00 (0.00–1.00)0.00 (3.00–17.75)<0.001 #0.0962.00 (0.00–15.00)27.00 (12.50–40.50)<0.001 #0.541
Surfactant92 (33.6%)127 (74.3%)<0.001 §0.015108 (72.0%)19 (90.5%)0.107 §0.793
Erythropoietin or darbepoetin9 (3.2%)13 (7.6%)0.043 §0.95911 (7.4%)2 (9.5%)0.665 §0.719
Systemic corticosteroid14 (5.0%)44 (25.7%)<0.001 §0.89131 (20.7%)13 (61.9%)<0.001 §0.133
Inhaled corticosteroid15 (6.0%)37 (25.2%)< 0.001 §0.24229 (22.3%)8 (47.1%)0.038 §0.239
Bronchodilator16 (5.7%)29 (16.9%)<0.001 §0.59524 (15.9%)5 (23.8%)0.358 §0.872
Non-steroidal anti-inflammatory13 (4.6%)32 (18.7%)<0.001 §0.31924 (16.0%)8 (38.1%)0.031 §0.944
Diuretics50 (17.7%)100 (58.1%)<0.001 §0.15783 (55.0%)17 (81.0%)0.032 §0.792
Weight increase
Mean daily weight increase up to the 10th day0.000 (−6.083–5.575)−2.900 (−7.944–1.273)<0.001 #0.072−3.300 (−8.136–0.782)−1.500 (−6.841–2.875)0.325 ¥0.089
Mean daily weight increase from the 11th to the 20th day22.753 (16.861–30.000)15.000 (10.417–21.700)<0.001 #0.91215.929 (12.000–22.000)9.778 (6.075–14.750)0.002 ¥0.426
Mean daily weight increase from the 21st to the 30th day28.700 (21.438–35.667)20.909 (13.300–28.800)<0.001 #0.91321.214 (15.000–29.706)12.000 (5.000–21.650)<0.001 ¥0.253
Nutrition
Day of the start of trophic enteral nutrition2.00 (2.00–3.00)3.00 (2.50–6.00)<0.001 #0.2282.00 (2.00–3.00)3.00 (2.50–6.00)<0.001 #0.032
Day of the start of nutritious enteral nutrition4.00 (3.00–6.00)9.50 (5.25–19.25)<0.001 #0.6815.00 (4.00–7.00)9.50 (5.25–19.25)<0.001 #0.022
Day of the start of total enteral nutrition10.00 (7.00–14.75)26.00 (16.50–46.50)<0.001 #0.12613.00 (9.00–20.00)26.00 (16.50–46.50)0.028 #0.932
Breast milk158 (82.7%)123 (78.3%)0.340 §0.745110 (79.7%)13 (68.4%)0.251 §0.731
Biochemical parameters
Urea (mg/dL)49.0 (33.5–64.5)61.6 (42.0–76.3)0.001 #0.08758.5 (41.0–74.8)65.0 (49.7–93.7)0.112 #0.956
Creatinine (mg/dL)0.7 (0.6–0.8)0.8 (0.6–0.9)<0.001 #0.7310.7 (0.6–0.8)0.9 (0.8–1.0)0.005 #0.092
Total bilirubin (mg/dL)7.3 (5.8–8.7)6.5 (5.3–7.5)0.001 #0.8256.6 (5.4–7.6)5.6 (4.4–7.1)0.087 #0.913
Direct bilirubin0.5 (0.4–0.6)0.7 (0.4–0.8)0.007 #0.2770.7 (0.5–0.8)0.4 (0.4–0.8)0.241 #0.095
Days of hospitalization41.7 (29.4–53.2)72.8 (53.2–94.5)<0.001 #<0.00168.6 (50.8–88.6)104.0 (88.9–128.1)<0.001 #0.082
N, number of individuals; NA, not applicable; P, p-value; P *, p-value adjusted for gestational age (GA) and number of red blood cell (RBC) transfusions. † Patients who do not meet the criteria for Type 1 ROP. § Chi-square test; ¥ Student’s t-test; # Mann–Whitney U test. p-values less than 0.05 are in bold.
Table 2. Clinical data related to supplemental oxygen therapy and the number of RBC transfusions to preterm infants according to the development (a) and progression (b) of ROP.
Table 2. Clinical data related to supplemental oxygen therapy and the number of RBC transfusions to preterm infants according to the development (a) and progression (b) of ROP.
(a)(b)
Clinical DataNo ROP (n = 283)
Mean ± SD		ROP (n = 172)
Mean ± SD		PP *ROP Stages 1, 2 and 3 †
(n = 151)
Mean ± SD		Type 1 ROP
(n = 21)
Mean ± SD		PP *
Oxygen
Maximum FiO2 1st week26.886 ± 43.15531.345 ± 16.841<0.001 #0.93630.412 ± 17.02738.347 ± 13.8090.001 #0.431
Maximum FiO2 2nd week21.167 ± 5.11028.512 ± 12.547<0.001 #0.04527.025 ± 10.47839.364 ± 19.7060.001 #0.132
Maximum FiO2 3rd week24.158 ± 6.10334.464 ± 17.579<0.001 #0.44431.953 ± 16.01446.537 ± 20.061<0.001 #0.250
Blood transfusions
Number of RBC transfusions0.29 ± 0.8352.19 ± 2.445<0.001 #NA1.80 ± 2.1264.95 ± 2.837<0.001 #NA
Number of platelet transfusions0.05 ± 0.3160.41 ± 1.025<0.001 #0.0490.34 ± 0.8570.86 ± 1.7970.048 #0.213
Number of plasma transfusions0.01 ± 0.1330.11 ± 0.452<0.001 #0.9290.11 ± 0.4700.10 ± 0.3010.748 # 0.146
N, number of individuals; NA, not applicable; P, p-value; P *, p-value adjusted for GA and number of RBC transfusions; SD, standard deviation. † Patients who do not meet the criteria for Type 1 ROP. # Mann–Whitney U test. p-values less than 0.05 are in bold.
Table 3. Prenatal and maternal demographic and clinical characteristics according to the development (a) and progression (b) of ROP.
Table 3. Prenatal and maternal demographic and clinical characteristics according to the development (a) and progression (b) of ROP.
(a)(b)
Demographic and Clinical CharacteristicsNo ROP (n = 283)
n (%) or Median (Q1–Q3)		ROP (n = 172)
n (%) or Median (Q1–Q3)		PP *ROP stages 1, 2, and 3 † (n = 151)
n (%) or Median (Q1–Q3)		Type 1 ROP (n = 21)
n (%) or Median (Q1–Q3)		PP *
Maternal age
<18 years1 (0.4%)2 (1.2%)0.534 §0.5982 (1.3%)0 (0%)0.749 §0.607
18–35 years206 (72.8%)121 (70.3%)105 (69.5%)16 (76.2%)
>35 years76 (26.9%)49 (28.5%)44 (29.1%)5 (23.8%)
Non-Portuguese family ancestry66 (23.6%)50 (29.4%)0.183 §0.16048 (32.2%)2 (9.5%)0.039 §0.045
Level of education
Primary education57 (21.0%)40 (24.8%)0.516 §0.23433 (23.4%)7 (35.0%)NA0.034
Lower secondary education8 (3.0%)9 (5.6%)8 (5.7%)1 (5.0%)
Upper secondary education86 (31.7%)50 (31.1%)40 (28.4%)10 (50.0%)
Post-secondary non-tertiary education2 (0.7%)1 (0.6%)1 (0.7%)0 (0.0%)
Tertiary education (any stage)118 (43.5%)61 (37.9%)59 (41.8%)2 (10.0%)
Behavioral habits
Tobacco44 (16.2%)30 (18.2%)0.601 §0.17926 (18.1%)4 (19.0%)1.000 §0.492
Alcohol6 (2.2%)3 (1.8%)1.000 §0.6783 (2.1%)0 (0.0%)1.000 §0.999
Illicit drugs2 (0.7%)3 (1.9%)0.368 §0.5112 (1.4%)1 (5.3%)0.314 §0.139
Obstetric history
Number of previous births
0176 (62.4%)105 (61.0%)0.958 §0.96398 (64.9%)7 (33.3%)0.021 §0.442
1–398 (34.8%)62 (36,0%)49 (32.5%)13 (61.9%)
≥48 (2.8%)5 (2.9%)4 (2.6%)1 (4.8%)
Pregnancy data
Assisted reproduction techniques34 (14.6%)23 (14.5%)1.000 §0.84322 (15.6%)1 (5.6%)0.475 §0.013
Multiple births97 (34.3%)39 (22.8%)0.011 §0.16435 (23.3%)4 (19.0%)0.787 §0.227
Pathologies in pregnancy
Chronic arterial hypertension18 (6.4%)25 (14.6%)0.005 §0.13719 (12.6%)6 (30.0%)0.084 §0.049
Pregnancy-induced hypertension105 (37.1%)44 (25.6%)0.012 §0.72239 (25.8%)5 (23.8%)1.000 §0.261
Chronic hypertension with preeclampsia12 (4.2%)11 (6.4%)0.312 §0.5618 (5.3%)3 (14.3%)0.136 §0.168
Diabetes39 (13.8%)22 (12.8%)0.799 §0.94818 (12.0%)4 (19.0%)0.483 §0.336
Chorioamnionitis29 (10.3%)25 (14.7%)0.179 §0.87223 (15.4%)2 (9.5%)0.743 §0.573
N, number of individuals; NA, not applicable; P, p-value; P *, p-value adjusted for GA and number of RBC transfusions. † Patients who do not meet the criteria for Type 1 ROP. § Chi-square test. p-values less than 0.05 are in bold.
Table 4. The outcome of different stages of ROP.
Table 4. The outcome of different stages of ROP.
Eyes (%)Outcome
ROP stage 1172 (18.9%)Spontaneous regression on follow-up
ROP stage 292 (10.0%)2 eyes treated with anti-VEGF
ROP stage 366 (7.4%)
  • 12 eyes treated with anti-VEGF
  • 24 eyes treated with laser photocoagulation
  • 3 eyes treated with anti-VEGF and laser
  • 1 eye treated with anti-VEGF, laser photocoagulation, and surgery
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MDPI and ACS Style

Fevereiro-Martins, M.; Santos, A.C.; Marques-Neves, C.; Bicho, M.; Guimarães, H.; on behalf of the GenE-ROP Study Group. Retinopathy of Prematurity in Eight Portuguese Neonatal Intensive Care Units: Incidence, Risk Factors, and Progression—A Prospective Multicenter Study. Children 2024, 11, 1154. https://doi.org/10.3390/children11101154

AMA Style

Fevereiro-Martins M, Santos AC, Marques-Neves C, Bicho M, Guimarães H, on behalf of the GenE-ROP Study Group. Retinopathy of Prematurity in Eight Portuguese Neonatal Intensive Care Units: Incidence, Risk Factors, and Progression—A Prospective Multicenter Study. Children. 2024; 11(10):1154. https://doi.org/10.3390/children11101154

Chicago/Turabian Style

Fevereiro-Martins, Mariza, Ana Carolina Santos, Carlos Marques-Neves, Manuel Bicho, Hercília Guimarães, and on behalf of the GenE-ROP Study Group. 2024. "Retinopathy of Prematurity in Eight Portuguese Neonatal Intensive Care Units: Incidence, Risk Factors, and Progression—A Prospective Multicenter Study" Children 11, no. 10: 1154. https://doi.org/10.3390/children11101154

APA Style

Fevereiro-Martins, M., Santos, A. C., Marques-Neves, C., Bicho, M., Guimarães, H., & on behalf of the GenE-ROP Study Group. (2024). Retinopathy of Prematurity in Eight Portuguese Neonatal Intensive Care Units: Incidence, Risk Factors, and Progression—A Prospective Multicenter Study. Children, 11(10), 1154. https://doi.org/10.3390/children11101154

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