Wide-field Digital Retinal Photography in 10,330 Newborns: Prevalence, Risk Factors and Clinical Implications in a Large Chinese Cohort

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Design: Retrospective, single-center cohort study. Participants: A total of 10,330 consecutive newborns who underwent universal wide-field digital retinal photography (WFDRP) screening within 72 hours of birth. Methods Two novel aggregated indices—the Neonatal Risk Count (summing complications across four domains: baseline risk, respiratory support, feeding/gastrointestinal issues, and hematologic/metabolic issues) and the Maternal High-Risk Count (summing peripartum risk factors)—were constructed. Fundus findings were classified as normal or abnormal. Univariable and multivariable logistic regression were used to assess associations, with multicollinearity assessed by variance inflation factors (VIF). Main Outcome Measures: Prevalence of any fundus abnormality; adjusted odds ratios (OR) for the association between abnormal fundus status and key predictors including birth weight, gestational age, Neonatal Risk Count, and Maternal High-Risk Count. Results Fundus abnormalities were detected in 3,079 infants (29.8%). Retinal hemorrhage was the most common finding (60.1% of abnormalities). In the final multivariable model, a higher Neonatal Risk Count (OR 1.42 per additional risk, 95% CI 1.23–1.63, p < 0.001), lower birth weight (OR 1.00 per gram, p < 0.001), and lower gestational age (OR 0.96, 95% CI 0.93–1.00, p = 0.05) were independent predictors of abnormal findings. The Maternal High-Risk Count showed a significant inverse association (OR 0.80, 95% CI 0.76–0.84, p < 0.001). Other neonatal clinical domain counts and sex were not significant. All VIFs were < 2. Conclusions In this large cohort, nearly one-third of newborns had detectable fundus abnormalities on WFDRP. Cumulative neonatal morbidity burden and perinatal immaturity were significant risk factors, while a higher aggregated maternal risk score was associated with lower odds of abnormality. These findings support the utility of WFDRP in universal newborn screening and highlight the importance of neonatal systemic health in ocular outcomes. Newborn Wide-field retinal image Retinal hemorrhage Fundus screening Perinatal factors Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction The early detection of ocular abnormalities during the neonatal period is crucial for the prevention of lifelong visual impairment and for facilitating timely interventions during the critical phase of visual development. Numerous neonatal retinal disorders originate from factors such as perinatal stress, hypoxia, prematurity, metabolic instability, or vascular dysregulation, and may remain asymptomatic without systematic examination. Although the red reflex test is recommended as the universal initial ocular screening tool, it exhibits limited sensitivity in detecting peripheral or subtle posterior-segment abnormalities, including small hemorrhages, vascular anomalies, or pigmentary changes 1 , 2 . In contrast, wide-field digital retinal photography (WFDRP) allows for high-resolution visualization of the posterior pole and ora serrata, demonstrating excellent feasibility and diagnostic utility in large-scale neonatal screening programs 3 – 5 . Retinal hemorrhage (RH) is consistently identified as the most prevalent neonatal fundus abnormality, with prevalence estimates ranging from approximately 10% to over 30%, depending upon the timing of imaging, delivery practices, and population characteristics 5 – 10 . While the majority of RHs resolve spontaneously, dense macular, multilayer, or fovea-involving hemorrhages have been associated with an increased risk of amblyopia, refractive error, and strabismus in later childhood 3 , 9 . Studies utilizing WFDRP have also revealed a broad spectrum of non-hemorrhagic abnormalities, including immature vascularization, retinal white-spot lesions, retinal pigment anomalies, optic disc variations, congenital cataract, persistent pupillary membrane (PPM), and vascular disorders such as familial exudative vitreoretinopathy (FEVR), many of which may be overlooked during conventional examinations 3 , 4 , 10 – 12 . Perinatal and maternal factors are critically influential in the development of neonatal retinal findings. Vaginal delivery, particularly spontaneous vertex delivery, is significantly associated with RH due to mechanical compression and alterations in venous pressure during labor. 6 , 13 . Lower gestational age and low birth weight are correlated with delayed retinal vascular maturation, rendering the neonate more susceptible to hemorrhage or persistent vascular anomalies 14 , 15 . Neonatal systemic instability, including conditions such as respiratory distress, sepsis, metabolic derangements, and hypoxia, can disrupt retinal vascular autoregulation, thereby increasing the likelihood of fundus abnormalities 16 – 18 . Furthermore, maternal complications, including hypertensive disorders, gestational diabetes, and placental insufficiency, can impair fetal oxygenation and angiogenic signaling. These disruptions may alter retinal and choroidal vascular development, thereby elevating the risk of adverse neonatal retinal outcomes 19 – 21 . Despite the increasing implementation of WFDRP 22 , there remains a paucity of large-scale studies that integrate both perinatal characteristics and maternal risk factors. The majority of existing research in China and other regions primarily focuses on descriptive epidemiology, with sample sizes ranging from several hundred to several thousand, and often lacks comprehensive multivariable risk modeling 3 , 4 , 12 . Consequently, the relative contributions of perinatal immaturity, neonatal morbidity burden, and maternal high-risk status to various types of fundus abnormalities are not well characterized. To address these gaps, we conducted a retrospective study involving 10,330 newborns who underwent universal WFDRP screening at our center. Our objectives were to: (1) characterize the prevalence and spectrum of neonatal fundus abnormalities; (2) evaluate the associations between abnormal fundus findings and key perinatal variables (such as gestational age, birth weight, and mode of delivery), neonatal morbidity burden (Neonatal Risk Count), and maternal risk burden (Maternal High-Risk Count); and (3) develop a predictive model for abnormal fundus outcomes and assess its stability and reliability. These findings aim to support evidence-based risk stratification and inform neonatal ocular screening pathways. 2. Methods 2.1 Study design and participants We conducted a retrospective review of all liveborn neonates at Maternal and Child Health Hospital in Lishui City between March 2019 and September 2025 who underwent WFDRP within 72 hours after birth. Exclusion criteria included poor-quality imaging, missing perinatal data, or major congenital ocular malformations diagnosed prenatally. 2.2 Imaging procedure After topical mydriasis, wide-field retinal images were acquired (RetCam III), covering posterior pole and peripheral fields (superior, inferior, nasal, temporal). Images were reviewed independently by two pediatric ophthalmologists; discrepancies resolved by consensus. 2.3 Data collection Perinatal variables collected included gestational age (weeks), birth weight (grams), delivery mode (vaginal, cesarean, assisted delivery), and sex. Neonatal clinical variables encompassed complications such as respiratory distress, gastrointestinal issues, metabolic and hematologic disturbances, sepsis, asphyxia, need for resuscitation, and NICU admission. To facilitate analysis, we developed aggregated indices by summing predefined risk factors. The Neonatal Risk Count was calculated by summing selected neonatal complications categorized into four domains: (1) Neonatal Risk, which includes premature birth, very low birth weight, low birth weight, and small for gestational age (SGA); (2) Respiratory Support, encompassing history of oxygen therapy, continuous positive airway pressure (CPAP), noninvasive ventilation, and invasive mechanical ventilation; (3) Feeding/Gastrointestinal Issues, which comprises gastric lavage, food allergies, necrotizing enterocolitis (NEC), gastroesophageal reflux disease (GERD), and transient neutropenia; and (4) Hematologic/Metabolic Issues, including hypoglycemia, hypocalcemia, hypomagnesemia, hypokalemia, anemia, polycythemia, and transient coagulopathy. Similarly, the Maternal High-Risk Count was determined by summing maternal peripartum risk factors such as preeclampsia, gestational diabetes, maternal anemia, chorioamnionitis, uterine scar, endometriosis, puerperal infection, cervicitis, uterine fibroids, placental abruption, intrahepatic cholestasis, liver dysfunction, Group B Streptococcus (GBS) carrier status, oligohydramnios, postpartum hypothyroidism, immediate hemorrhage, paddle-shaped placenta, and cord torsion. These aggregated counts were used in subsequent statistical analyses to evaluate their association with neonatal retinal outcomes. 2.4 Statistical analysis Continuous variables summarized as mean ± SD or median (IQR), categorical as counts (percent). Univariable and multivariable logistic regression models were built to estimate odds ratios (OR) and 95% confidence intervals (CI) for predictors of abnormal fundus status. Multicollinearity assessed via variance inflation factors (VIF); VIF < 5 considered acceptable. Trend/dose–response between all the risk count and abnormal fundus prevalence evaluated visually via scatter+jitter and by regression; stratified analyses by delivery mode performed. Statistical significance defined as two-sided p < 0.05. All analyses performed in R 4.4.1. 3. Results 3.1 Cohort characteristics and fundus findings A total of 10,330 neonates fulfilled the inclusion criteria, of which 5,043 (48.82%) were male. The mean gestational age was 38.58 ± 1.67 weeks, the mean birth weight was 3,241.71 ± 526.72 g, and the mean maternal age was 29.49 ± 4.86 years (Table 1 ). Fundus imaging revealed abnormal retinal findings in 3,079 infants (29.81%), while 7,251 infants (70.19%) exhibited normal retinal appearances. Table 1 Summary of Basic Information of the Participants Parameter Values Gender (%) Male 5043 (48.82%) Female 5287 (51.18%) Gestation Age (weeks) 38.58 ± 1.67 Birth Weight (g) 3241.71 ± 526.72 Maternal Age (years) 29.49 ± 4.86 Funds Image (%) Normal 7251 (70.19%) Abnormal 3079 (29.81%) Distribution of Abnormal Fundus Disease Count (%) 1 category 2798 (90.87%) 2 categories 258 (8.38%) 3 categories 21 (0.68%) 4 categories 2 (0.06%) 3.2 Spectrum and frequency of abnormalities Among those with abnormal findings, the majority (2,798; 90.87%) presented with a single category of abnormality; 258 infants (8.38%) exhibited two categories, 21 infants (0.68%) had three categories, and 2 infants (0.06%) had four categories of abnormalities (Table 1 ). Retinal hemorrhage was the most prevalent lesion, identified in 1,850 infants (60.08% of those with abnormal findings) (Table 2 ). Other frequent abnormalities included punctate pigmentation (384 infants; 12.47%), peripheral retinal white spots (324 infants; 10.52%), immature retina (277 infants; 9.00%), and pigment abnormality (132 infants; 4.29%). Less common but clinically significant findings comprised punctate choroidal defect (101 infants; 3.28%), vascular underdevelopment (61 infants; 1.98%), FEVR-like patterns (56 infants; 1.82%), unclear optic disc (52 infants; 1.69%), congenital cataract (29 infants; 0.94%), and retinopathy of prematurity (ROP) (19 infants; 0.62%) (Table 2 and Fig. 4 ). Table 2 Prevalence of Abnormal Fundus Findings Among the Participants Disease Count Percent (%) Retinal Hemorrhage 1850 60.08 Punctate Pigmentation 384 12.47 Peripheral Retinal White Spots 324 10.52 Immature Retina 277 9.00 Pigment Abnormality 132 4.29 Punctate Choroidal Defect 101 3.28 Vascular Underdevelopment 61 1.98 FEVR 56 1.82 Unclear Optic Disc 52 1.69 Congenital Cataract 29 0.94 Vascular Dysplasia 23 0.75 Persistent Pupillary Membrane 21 0.68 ROP 19 0.62 Albinism 14 0.45 PHPV 12 0.39 Vascular Dilatation 12 0.39 Vitreous Opacity 8 0.26 Iris Posterior Synechia 5 0.16 Vascular Tortuosity 4 0.13 Bilateral Punctate Lesions 1 0.03 3.3 Group comparisons Infants presenting with abnormal fundus findings exhibited significantly lower gestational ages (38.33 ± 2.04 weeks compared to 38.68 ± 1.47 weeks; t = 8.69; P < 0.001) and reduced birth weights (3,148.30 ± 531.56 g versus 3,281.38 ± 519.63 g; t = 11.72; P < 0.001) relative to those with normal fundus findings, as detailed in Table 3 . Although maternal age showed a marginal statistical difference (P < 0.001), the mode of delivery demonstrated significant variation (χ² = 568.53; P < 0.001). Specifically, vaginal delivery was predominant among the group with abnormal findings (69.54% compared to 44.26%), whereas cesarean delivery was more prevalent in the group with normal findings (54.12% compared to 28.65%), as illustrated in Table 4 . Table 3 Comparison of Gestation Age, Birth Weight, and Maternal Age Between Infants with Normal and Abnormal Fundus Findings Variable Mean ± SD (95%CI) t P Gestation Age 8.69 < 0.001 Normal 38.68 ± 1.47 (38.65–38.71) Abnormal 38.33 ± 2.04 (38.26–38.40) Birth Weight 11.72 < 0.001 Normal 3281.38 ± 519.63 (3269.41–3293.33) Abnormal 3148.30 ± 531.56 (3129.51–3167.08) Maternal Age −1.72 < 0.001 Normal 29.44 ± 4.85 (29.33–29.55) Abnormal 29.62 ± 4.89 (29.45–29.79) Table 4 Comparison of Delivery Method Between Infants With Normal and Abnormal Fundus Findings Delivery Method Count (%) χ² P Assisted 568.53 < 0.001 Normal 118 (1.63) Abnormal 56 (1.82) C Section Normal 3924 (54.12) Abnormal 882 (28.65) Vaginal Normal 3209 (44.26) Abnormal 2141 (69.54) 3.4 Regression Results and Visualization Both simple and multivariable logistic regression analyses produced consistent estimates, as detailed in Table S1 . In the final multivariable model (Table 5 ), the Neonatal Risk Count emerged as the most robust independent predictor of abnormal fundus findings, with an odds ratio (OR) of 1.42 (95% confidence interval [CI] 1.23–1.63, p < 0.001). Conversely, the Maternal High-Risk Count exhibited a significant inverse relationship (OR 0.80, 95% CI 0.76–0.84, p < 0.001). Birth weight maintained significance, albeit with a minimal per-gram effect (OR 1.00, p < 0.001), while gestational age demonstrated borderline significance (OR 0.96, 95% CI 0.93–1.00, p = 0.05). Other neonatal clinical factors and sex were not significant predictors. Table 5 Multiple Logistic Regression Model of Studied Variables Variable OR (95%CI) P (Intercept) 6.89 (1.88–25.28) < 0.001 Birth Weight 1.00 (1.00–1.00) < 0.001 Gestation Age 0.96 (0.93–1.00) 0.05 Neonatal Risk Count 1.42 (1.23–1.63) < 0.001 Maternal High-Risk Count 0.80 (0.76–0.84) < 0.001 Hematologic Metabolic Count 0.95 (0.82–1.09) 0.45 Respiratory Support Count 0.93 (0.82–1.05) 0.26 Feeding GI Issues Count 1.05 (0.88–1.24) 0.58 Gender 1.06 (0.97–1.16) 0.17 Note: AUC = 0.6 for multiple logistic regression. A forest plot was constructed to depict all regression coefficients and their 95% CIs, thereby illustrating the relative contribution of each variable (Fig. 2 ). Additionally, the scatter-jitter plots in the figure reveal distinct dose-response patterns: the prevalence of abnormal fundus findings shows a monotonically increasing trend with higher Neonatal Risk Counts. In contrast, a slight negative correlation trend is observed for Maternal High Risk Counts, indicating a modest decrease in the prevalence of abnormal fundus findings as the risk count increases (Fig. 3 ). These visual patterns were entirely consistent with the regression estimates. Model diagnostics confirmed good stability. The model diagnostics demonstrated satisfactory stability, as evidenced by all variance inflation factors (VIFs) being less than 2,, as detailed in Table S2, indicating an absence of problematic multicollinearity. Sensitivity analyses employing penalized logistic regression for rare outcomes yielded results that were directionally consistent with the primary model, thereby reinforcing its robustness. 4. Discussion In this large cohort of 10,330 neonates undergoing universal wide-field digital retinal photography (WFDRP), nearly one-third (29.81%) exhibited abnormal fundus findings. This prevalence is comparable to that reported in large-scale neonatal screening programs from China, India, Malaysia, and New Zealand, where abnormal posterior segment findings ranged from approximately 20% to 30% 5,12,23,24 . The high detection rate underscores that a substantial proportion of neonatal fundus abnormalities would likely remain unrecognized without systematic imaging-based screening. The spectrum of abnormalities observed in this study was dominated by retinal hemorrhage (RH), accounting for approximately 60% of all abnormal findings, followed by punctate pigmentation, peripheral retinal white spots, immature retina, and pigment abnormalities. This distribution closely mirrors prior WFDRP-based studies, in which RH consistently emerged as the most prevalent lesion among term and near-term infants 5 , 9 , 10 , 12 . RH in neonates is widely regarded as a manifestation of delivery-related mechanical stress, perinatal hypoxia, and abrupt changes in intracranial and ocular venous pressure. Ji et al. demonstrated that ocular compression during delivery—particularly with vacuum or forceps assistance—plays a major etiologic role in the development of RH 17 . Although the majority of RH cases are intraretinal and self-limited, resolving spontaneously within weeks, their high prevalence reinforces the value of early documentation and follow-up to distinguish benign transient findings from lesions requiring surveillance 9 , 25 , 26 . Beyond RH, the detection of vascular developmental variants, FEVR-like patterns, punctate choroidal defects, and rare congenital anomalies highlights the broader clinical value of universal screening. Large neonatal fundus-screening initiatives have consistently shown that WFDRP enables early identification of uncommon but potentially vision-threatening conditions, facilitating timely referral and intervention 3 , 6 . The presence of multiple categories of abnormalities in a subset of infants in our cohort further suggests that neonatal fundus pathology often reflects a cumulative burden of perinatal stress rather than isolated ocular events. Group comparisons revealed that infants with abnormal fundus findings had significantly lower gestational ages and birth weights than those with normal findings. These observations are consistent with extensive prior literature demonstrating that both gestational maturity and fetal growth are critical determinants of retinal vascular development 3 , 6 , 10 , 12 . Tang et al., in a multicenter study involving nearly 200,000 newborns, reported a clear gradient effect of birth weight on the prevalence of retinal abnormalities 6 . Current evidence links low birth weight and intrauterine growth restriction (IUGR) with abnormal retinal vascular development 27 . Studies have linked these conditions with long-term alterations in retinal vessel morphology, indicating that IUGR may disrupt normal vascular programming 28 . This disruption could predispose the retina to hemodynamic instability, potentially explaining a higher susceptibility to conditions such as retinal hemorrhage and optic disc anomalies. The biological plausibility of these associations is well supported. Retinal and choroidal vascularization continues through late gestation and into the early postnatal period, rendering the immature vasculature particularly vulnerable to fluctuations in oxygenation and perfusion 29 . Prior studies have shown that lower birth weight and younger gestational age are associated with abnormal retinal vessel morphology in moderately preterm infants 30 , delayed choroidal thickening 31 , and long-term alterations in macular vessel density and foveal avascular zone characteristics 32 . Collectively, these findings support the inclusion of birth weight and gestational age as key parameters in neonatal ocular risk stratification. Delivery mode differed markedly between infants with and without abnormal fundus findings, with vaginal delivery being substantially more common in the abnormal group, while cesarean delivery predominated among infants with normal fundus appearances. This pattern is concordant with previous reports linking vaginal delivery to a higher incidence of RH, likely due to increased mechanical compression of the globe and transient elevations in venous pressure during labor and delivery 9 , 17 . In contrast, cesarean delivery may mitigate these mechanical forces, thereby reducing the risk of birth-related retinal hemorrhage. Although delivery mode was not included as an independent variable in the final regression model, its strong univariate association highlights the importance of perinatal mechanical factors in shaping neonatal fundus outcomes. Multivariable logistic regression analysis further clarified the relative contributions of perinatal and systemic factors. Neonatal systemic burden, quantified by the Neonatal Risk Count, emerged as the strongest independent predictor of abnormal fundus findings. This result aligns with prior evidence linking systemic neonatal illness—including sepsis, asphyxia, respiratory failure, and metabolic instability—to retinal vascular injury through inflammatory pathways, impaired autoregulation, and altered perfusion 33 – 35 . Notably, neonatal sepsis has been proposed as an oxygen-independent contributor to retinopathy of prematurity in both cohort studies and narrative reviews 33 . The clear dose–response relationship observed between increasing Neonatal Risk Count and abnormal fundus prevalence in our cohort further supports a cumulative-risk model, in which systemic illness amplifies retinal vulnerability. In contrast, the Maternal High-Risk Count demonstrated a significant inverse association with abnormal fundus findings. Although this observation may appear counterintuitive, it is consistent with a growing body of literature suggesting that certain maternal complications do not uniformly increase neonatal ocular risk. In very-low-birth-weight infants, maternal preeclampsia has been associated with a reduced risk of ROP (adjusted OR = 0.65) 36 , with similar protective trends reported in other cohorts 37 . Conversely, in full-term infants, pregnancy-related hypertension has been linked to increased RH and other fundus abnormalities 38 , underscoring the heterogeneity of maternal risk effects. In our cohort, the aggregated maternal high-risk variable likely encompassed diverse conditions with differing pathophysiologic implications. The observed protective association may reflect intensified prenatal surveillance, planned delivery strategies (including higher rates of cesarean section), and optimized neonatal care among high-risk pregnancies. Such measures may reduce fetal hypoxia, hemodynamic instability, and birth trauma—key contributors to RH and retinal vascular abnormalities. These findings suggest that aggregated maternal risk scores may obscure condition-specific effects and highlight the need for future studies to disaggregate maternal risk subtypes and incorporate perinatal management variables when modeling neonatal retinal outcomes. Other neonatal clinical factors, including hematologic/metabolic abnormalities, respiratory support frequency, feeding or gastrointestinal issues, and sex, were not independently associated with abnormal fundus findings after adjustment. The similarity between simple and multivariable regression estimates, together with low variance inflation factors, indicates minimal confounding and limited multicollinearity among predictors, supporting the stability of the model. Sensitivity analyses using penalized regression approaches for rare outcomes yielded directionally consistent results, further reinforcing the robustness of the observed associations. Although the discriminative performance of the multivariable model was modest (AUC = 0.60), this finding should be interpreted in the context of the study objective. The primary aim was etiologic inference and population-level risk stratification rather than individual-level prediction. In neonatal screening research, particularly when outcomes are heterogeneous and largely transient, moderate AUC values are common and do not preclude clinical relevance 39 , 40 . Importantly, the model demonstrated internally consistent effect estimates, biologically plausible directions of association, and clear dose–response patterns for key predictors, such as Neonatal Risk Count and Maternal High-Risk Count (Figs. 1 – 2 ). These features suggest that the model captures meaningful population-level relationships even if its standalone predictive accuracy is limited. Future studies incorporating longitudinal outcomes and additional perinatal variables may further improve predictive performance. From a clinical and public health perspective, these findings provide additional support for universal WFDRP screening in neonates. Prior programs in India (KIDROP) and China have demonstrated that systematic imaging improves early detection, reduces missed diagnoses, and facilitates longitudinal monitoring of retinal health 10 , 20 , 41 . Clare O et al. emphasized that many neonatal and infantile ocular conditions are reversible if identified early, whereas delayed diagnosis may result in permanent visual impairment 42 . The present results indicate that even term infants without overt clinical risk factors may harbor fundus abnormalities linked to subtle perinatal and systemic stressors, arguing against overly restrictive, risk-based screening strategies in high-volume birth settings. The strengths of this study include its large sample size, the use of validated WFDRP technology, comprehensive characterization of neonatal and maternal risk factors, and consistent findings across multiple analytic approaches. Nevertheless, several limitations warrant consideration. The single-center design may limit generalizability, and the absence of long-term follow-up precludes confirmation of lesion resolution or long-term visual sequelae. Important obstetric variables, such as labor duration and detailed delivery mechanics, were unavailable, and inter-operator variability in image acquisition may have introduced measurement heterogeneity. In addition, the moderate discriminative performance of the regression model likely reflects the heterogeneous and largely transient nature of neonatal fundus findings rather than inadequate modeling. Future multicenter, longitudinal studies incorporating detailed perinatal management data, serial imaging, and long-term visual outcomes are needed to better delineate the natural history of neonatal fundus abnormalities and to refine screening strategies. 5. Conclusion Our findings confirm that neonatal posterior segment abnormalities are common and significantly influenced by birth weight, gestational age, neonatal systemic morbidity, and perinatal conditions. Universal WFDRP screening is feasible, safe, and clinically valuable for early identification of both transient and potentially vision-threatening lesions. These results support broader adoption of neonatal eye screening programs, particularly in regions with higher risk profiles and limited access to pediatric ophthalmology. Declarations Ethics approval and consent to participate This study was approved by the Ethics Committee of Lishui Maternity and Child Health Care Hospital (NO.2020030), and it is in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants. For participants under 16 years of age, parental or legal guardian consent was additionally secured prior to enrollment. Consent for publication Not applicable. Availability of data and materials The datasets are not publicly available due to patient privacy concerns but can be provided by the corresponding author upon reasonable request and approval from the institutional ethics committee. Competing interests The authors declare no competing interests. Funding This work was supported by the Lishui Science and Technology Bureau Public Welfare Technology Applied Research Project [Grant Number 2021SJZCO58]: “Application of RetCam III Wide-Field Digital Imaging System in Neonatal Eye Disease Screening.”. Authors' contributions Chunjuan Wang contributed to data collection and assisted in revising the manuscript. Lixing Zhou drafted the manuscript, led the writing of the article, and participated in data interpretation as well as table and figure preparation. Chunhong Ye and Shuzheng Chen was involved in the entire process of data collection and quality management. Qunda Shan and Jiao Liu served as corresponding authors. Chunjuan Wang and Lixing Zhou contributed equally to this work. All authors reviewed and approved the final manuscript and agree to be personally accountable for their own contributions and to ensure the integrity of the work. Acknowledgements Not applicable. Declaration of generative AI and AI-assisted technologies in the manuscript preparation process During the preparation of this work, the authors used DeepSeek (an AI language model by DeepSeek Company) for language polishing, grammar checking, and improving the clarity and fluency of the text. After using this tool, the authors thoroughly reviewed and edited the content as needed and take full responsibility for the content of the published article. References Subhi Y, Schmidt DC, Al-Bakri M, Bach-Holm D, Kessel L. Diagnostic Test Accuracy of the Red Reflex Test for Ocular Pathology in Infants: A Meta-analysis. 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Front Pediatr. 2023;11:1203068. 10.3389/fped.2023.1203068 . Laghmari M, Skiker H, Handor H, et al. [Birth-related retinal hemorrhages in the newborn: incidence and relationship with maternal, obstetric and neonatal factors. Prospective study of 2,031 cases]. J Fr Ophtalmol. 2014;37(4):313–9. 10.1016/j.jfo.2013.06.005 . Hughes LA, May K, Talbot JF, Parsons MA. Incidence, distribution, and duration of birth-related retinal hemorrhages: a prospective study. J AAPOS Off Publ Am Assoc Pediatr Ophthalmol Strabismus. 2006;10(2):102–6. 10.1016/j.jaapos.2005.12.005 . Kandasamy Y, Smith R, Wright IMR. Retinal microvascular changes in low-birth-weight babies have a link to future health. J Perinat Med. 2012;40(3):209–14. 10.1515/JPM.2011.116 . Maria Ortega-Molina J, De Larraya A, SP A, SM et al. Risk Factors of Retinopathy of Prematurity Associated with Delayed Retinal Vascular Development. Iran J Pediatr . 2017;In Press(In Press). 10.5812/ijp.7642 Lutty GA, McLeod DS. Development of the hyaloid, choroidal and retinal vasculatures in the fetal human eye. Prog Retin Eye Res. 2018;62:58–76. 10.1016/j.preteyeres.2017.10.001 . Allvin K, Hellström A, Dahlgren J, Andersson Grönlund M. Birth weight is the most important predictor of abnormal retinal vascularisation in moderately preterm infants. Acta Paediatr Oslo Nor 1992. 2014;103(6):594–600. 10.1111/apa.12599 . Mangalesh S, Toth CA. Preterm infant retinal OCT markers of perinatal health and retinopathy of prematurity. Front Pediatr. 2023;11:1238193. 10.3389/fped.2023.1238193 . Czeszyk A, Hautz W, Jaworski M, Bulsiewicz D, Czech-Kowalska J. Morphology and Vessel Density of the Macula in Preterm Children Using Optical Coherence Tomography Angiography. J Clin Med. 2022;11(5):1337. 10.3390/jcm11051337 . Dammann O, Stansfield BK. Neonatal sepsis as a cause of retinopathy of prematurity: An etiological explanation. Prog Retin Eye Res. 2024;98:101230. 10.1016/j.preteyeres.2023.101230 . Choi YJ, Jung MS, Kim SY. Retinal hemorrhage associated with perinatal distress in newborns. Korean J Ophthalmol KJO. 2011;25(5):311–6. 10.3341/kjo.2011.25.5.311 . Ying GS, Quinn GE, Wade KC, et al. Predictors for the development of referral-warranted retinopathy of prematurity in the telemedicine approaches to evaluating acute-phase retinopathy of prematurity (e-ROP) study. JAMA Ophthalmol. 2015;133(3):304–11. 10.1001/jamaophthalmol.2014.5185 . Yu XD, Branch DW, Karumanchi SA, Zhang J. Preeclampsia and retinopathy of prematurity in preterm births. Pediatrics. 2012;130(1):e101–107. 10.1542/peds.2011-3881 . Huang HC, Yang HI, Chou HC, et al. Preeclampsia and Retinopathy of Prematurity in Very-Low-Birth-Weight Infants: A Population-Based Study. PLoS ONE. 2015;10(11):e0143248. 10.1371/journal.pone.0143248 . Chen LN, He XP, Huang LP. A survey of high risk factors affecting retinopathy in full-term infants in China. Int J Ophthalmol. 2012;5(2):177–80. 10.3980/j.issn.2222-3959.2012.02.12 . Jin C, Yu X, Lei M, Deng P, Li X, Jiang W. A simple nomogram tool for predicting fetal chromosomal abnormalities based on ultrasound soft markers: a research note. BMC Res Notes. 2025;18:453. 10.1186/s13104-025-07512-9 . Tonyali NV, Sarsmaz K, Bayraktar B, et al. Delta neutrophil index (DNI) as a potential biomarker for fetal growth restriction: insights from maternal hematological changes and neonatal outcomes. BMC Pregnancy Childbirth. 2024;24:655. 10.1186/s12884-024-06853-w . Vinekar A, Jayadev C, Mangalesh S, Shetty B, Vidyasagar D. Role of tele-medicine in retinopathy of prematurity screening in rural outreach centers in India - a report of 20,214 imaging sessions in the KIDROP program. Semin Fetal Neonatal Med. 2015;20(5):335–45. 10.1016/j.siny.2015.05.002 . Stocks CO, Carson RA. Newborn and infant vision screening in primary care: A clinical review. J Spec Pediatr Nurs JSPN. 2024;29(1):e12421. 10.1111/jspn.12421 . Additional Declarations No competing interests reported. Supplementary Files supplementaryinformation.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 03 May, 2026 Reviews received at journal 13 Apr, 2026 Reviewers agreed at journal 21 Mar, 2026 Reviewers invited by journal 19 Mar, 2026 Editor invited by journal 16 Mar, 2026 Editor assigned by journal 16 Mar, 2026 Submission checks completed at journal 16 Mar, 2026 First submitted to journal 11 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9090581","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":609922868,"identity":"4d1cb1fd-6f09-4a03-8a43-92b1765245d1","order_by":0,"name":"Chunjuan Wang","email":"","orcid":"","institution":"Lishui Maternity and Child Health Care Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chunjuan","middleName":"","lastName":"Wang","suffix":""},{"id":609922869,"identity":"af75d76b-5351-4a09-9090-ebcadb74ace5","order_by":1,"name":"Lixing Zhou","email":"","orcid":"","institution":"Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Lixing","middleName":"","lastName":"Zhou","suffix":""},{"id":609922870,"identity":"ad4e3f3e-215b-4783-871b-ca580bdfb74e","order_by":2,"name":"Shuzheng Chen","email":"","orcid":"","institution":"Lishui Maternity and Child Health Care Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shuzheng","middleName":"","lastName":"Chen","suffix":""},{"id":609922872,"identity":"eb100f20-c733-4ef9-9f39-0d47e3420579","order_by":3,"name":"Chunhong Ye","email":"","orcid":"","institution":"Lishui Maternity and Child Health Care Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chunhong","middleName":"","lastName":"Ye","suffix":""},{"id":609922878,"identity":"6367fb07-f366-4b67-a5b4-6e8f41ad5dbb","order_by":4,"name":"Qunda Shan","email":"","orcid":"","institution":"Lishui Maternity and Child Health Care Hospital","correspondingAuthor":false,"prefix":"","firstName":"Qunda","middleName":"","lastName":"Shan","suffix":""},{"id":609922879,"identity":"ac6095ed-5025-448c-a79f-57d3802e62ce","order_by":5,"name":"Jiao Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwElEQVRIiWNgGAWjYBACfvbGxgcfDP7L8ROtRbLncLPhjAJmY8kGYrUYzHBvk+b5wJy44QDRWiQY2yRnGLAxbj6evIHhR8U2wlrMpRubLT4Y8DCbnXlWwNhz5jZhLZZzDjbenGEgwWZ2I8eAmbGNCC0GNxIbpHkMDHiMZ5CgpQmoJUHCQIJYLZI9B4GBbHDAQALol4NE+YWfvf3hgw9/DtT3tydvfPCjgggtSCDB4ABJ6sFaSNUxCkbBKBgFIwQAACRUQVkiTaewAAAAAElFTkSuQmCC","orcid":"","institution":"Lishui Maternity and Child Health Care Hospital","correspondingAuthor":true,"prefix":"","firstName":"Jiao","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2026-03-11 06:23:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9090581/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9090581/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105297404,"identity":"3153eb85-6dab-4aa3-bc81-118a6e149b01","added_by":"auto","created_at":"2026-03-24 13:19:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2832392,"visible":true,"origin":"","legend":"\u003cp\u003eGraphical Abstract: A Visual Summary of the Study\u003c/p\u003e\n\u003cp\u003eNote: This schematic summarizes the study rationale, methodology, principal results, and clinical implications. Abbreviations: WFDRP, wide-field digital retinal photography; OR, odds ratio; VIF, variance inflation factor; AUC, area under the curve.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-9090581/v1/434c3bd0efedd205f59e4603.png"},{"id":105297408,"identity":"ddbd9b16-5475-46e2-9deb-ad5104511bd6","added_by":"auto","created_at":"2026-03-24 13:19:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":416768,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eForest Plot of Studied Variables\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-9090581/v1/c1159af53eacb635e5604812.png"},{"id":105297406,"identity":"17dce649-a8f8-47dc-bdfe-0b47a439fb28","added_by":"auto","created_at":"2026-03-24 13:19:04","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1255769,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAssociation of Multiple Risk Factors with Abnormal Fundus in Neonates.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNote: Scatter-jitter plots with dashed lines indicating the proportion of abnormal fundus findings across increasing risk counts.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-9090581/v1/4f9026ce61ef549bbaa34540.png"},{"id":105297405,"identity":"95229470-9fb6-4d6b-a4bf-574a737c78da","added_by":"auto","created_at":"2026-03-24 13:19:04","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":612851,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePrevalence of Abnormal Fundus Findings Among Participants\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-9090581/v1/57621cf3fa638f712d5ea0f0.png"},{"id":105569117,"identity":"df2197bc-1f2a-4e6c-b8c7-71bcdd924875","added_by":"auto","created_at":"2026-03-27 13:11:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5567153,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9090581/v1/22b64725-d9a4-4383-ab41-6271f3eca0b4.pdf"},{"id":105564483,"identity":"a9ae4172-62b1-4cd7-bf84-2fecf248e6e2","added_by":"auto","created_at":"2026-03-27 12:49:44","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":20554,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryinformation.docx","url":"https://assets-eu.researchsquare.com/files/rs-9090581/v1/945e462335724a57ab8abacf.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Wide-field Digital Retinal Photography in 10,330 Newborns: Prevalence, Risk Factors and Clinical Implications in a Large Chinese Cohort","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe early detection of ocular abnormalities during the neonatal period is crucial for the prevention of lifelong visual impairment and for facilitating timely interventions during the critical phase of visual development. Numerous neonatal retinal disorders originate from factors such as perinatal stress, hypoxia, prematurity, metabolic instability, or vascular dysregulation, and may remain asymptomatic without systematic examination. Although the red reflex test is recommended as the universal initial ocular screening tool, it exhibits limited sensitivity in detecting peripheral or subtle posterior-segment abnormalities, including small hemorrhages, vascular anomalies, or pigmentary changes\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. In contrast, wide-field digital retinal photography (WFDRP) allows for high-resolution visualization of the posterior pole and ora serrata, demonstrating excellent feasibility and diagnostic utility in large-scale neonatal screening programs\u003csup\u003e\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eRetinal hemorrhage (RH) is consistently identified as the most prevalent neonatal fundus abnormality, with prevalence estimates ranging from approximately 10% to over 30%, depending upon the timing of imaging, delivery practices, and population characteristics\u003csup\u003e\u003cspan additionalcitationids=\"CR6 CR7 CR8 CR9\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. While the majority of RHs resolve spontaneously, dense macular, multilayer, or fovea-involving hemorrhages have been associated with an increased risk of amblyopia, refractive error, and strabismus in later childhood\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Studies utilizing WFDRP have also revealed a broad spectrum of non-hemorrhagic abnormalities, including immature vascularization, retinal white-spot lesions, retinal pigment anomalies, optic disc variations, congenital cataract, persistent pupillary membrane (PPM), and vascular disorders such as familial exudative vitreoretinopathy (FEVR), many of which may be overlooked during conventional examinations\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePerinatal and maternal factors are critically influential in the development of neonatal retinal findings. Vaginal delivery, particularly spontaneous vertex delivery, is significantly associated with RH due to mechanical compression and alterations in venous pressure during labor.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Lower gestational age and low birth weight are correlated with delayed retinal vascular maturation, rendering the neonate more susceptible to hemorrhage or persistent vascular anomalies\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Neonatal systemic instability, including conditions such as respiratory distress, sepsis, metabolic derangements, and hypoxia, can disrupt retinal vascular autoregulation, thereby increasing the likelihood of fundus abnormalities\u003csup\u003e\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Furthermore, maternal complications, including hypertensive disorders, gestational diabetes, and placental insufficiency, can impair fetal oxygenation and angiogenic signaling. These disruptions may alter retinal and choroidal vascular development, thereby elevating the risk of adverse neonatal retinal outcomes\u003csup\u003e\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eDespite the increasing implementation of WFDRP\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, there remains a paucity of large-scale studies that integrate both perinatal characteristics and maternal risk factors. The majority of existing research in China and other regions primarily focuses on descriptive epidemiology, with sample sizes ranging from several hundred to several thousand, and often lacks comprehensive multivariable risk modeling\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Consequently, the relative contributions of perinatal immaturity, neonatal morbidity burden, and maternal high-risk status to various types of fundus abnormalities are not well characterized. To address these gaps, we conducted a retrospective study involving 10,330 newborns who underwent universal WFDRP screening at our center. Our objectives were to: (1) characterize the prevalence and spectrum of neonatal fundus abnormalities; (2) evaluate the associations between abnormal fundus findings and key perinatal variables (such as gestational age, birth weight, and mode of delivery), neonatal morbidity burden (Neonatal Risk Count), and maternal risk burden (Maternal High-Risk Count); and (3) develop a predictive model for abnormal fundus outcomes and assess its stability and reliability.\u003c/p\u003e \u003cp\u003eThese findings aim to support evidence-based risk stratification and inform neonatal ocular screening pathways.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study design and participants\u003c/h2\u003e \u003cp\u003e We conducted a retrospective review of all liveborn neonates at Maternal and Child Health Hospital in Lishui City between March 2019 and September 2025 who underwent WFDRP within 72 hours after birth. Exclusion criteria included poor-quality imaging, missing perinatal data, or major congenital ocular malformations diagnosed prenatally.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e2.2 Imaging procedure\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eAfter topical mydriasis, wide-field retinal images were acquired (RetCam III), covering posterior pole and peripheral fields (superior, inferior, nasal, temporal). Images were reviewed independently by two pediatric ophthalmologists; discrepancies resolved by consensus.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e2.3 Data collection\u003c/b\u003e\u003c/h2\u003e \u003cp\u003ePerinatal variables collected included gestational age (weeks), birth weight (grams), delivery mode (vaginal, cesarean, assisted delivery), and sex. Neonatal clinical variables encompassed complications such as respiratory distress, gastrointestinal issues, metabolic and hematologic disturbances, sepsis, asphyxia, need for resuscitation, and NICU admission.\u003c/p\u003e \u003cp\u003eTo facilitate analysis, we developed aggregated indices by summing predefined risk factors. The Neonatal Risk Count was calculated by summing selected neonatal complications categorized into four domains: (1) Neonatal Risk, which includes premature birth, very low birth weight, low birth weight, and small for gestational age (SGA); (2) Respiratory Support, encompassing history of oxygen therapy, continuous positive airway pressure (CPAP), noninvasive ventilation, and invasive mechanical ventilation; (3) Feeding/Gastrointestinal Issues, which comprises gastric lavage, food allergies, necrotizing enterocolitis (NEC), gastroesophageal reflux disease (GERD), and transient neutropenia; and (4) Hematologic/Metabolic Issues, including hypoglycemia, hypocalcemia, hypomagnesemia, hypokalemia, anemia, polycythemia, and transient coagulopathy. Similarly, the Maternal High-Risk Count was determined by summing maternal peripartum risk factors such as preeclampsia, gestational diabetes, maternal anemia, chorioamnionitis, uterine scar, endometriosis, puerperal infection, cervicitis, uterine fibroids, placental abruption, intrahepatic cholestasis, liver dysfunction, Group B Streptococcus (GBS) carrier status, oligohydramnios, postpartum hypothyroidism, immediate hemorrhage, paddle-shaped placenta, and cord torsion. These aggregated counts were used in subsequent statistical analyses to evaluate their association with neonatal retinal outcomes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Statistical analysis\u003c/h2\u003e \u003cp\u003eContinuous variables summarized as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or median (IQR), categorical as counts (percent). Univariable and multivariable logistic regression models were built to estimate odds ratios (OR) and 95% confidence intervals (CI) for predictors of abnormal fundus status. Multicollinearity assessed via variance inflation factors (VIF); VIF\u0026thinsp;\u0026lt;\u0026thinsp;5 considered acceptable. Trend/dose\u0026ndash;response between all the risk count and abnormal fundus prevalence evaluated visually via scatter+jitter and by regression; stratified analyses by delivery mode performed. Statistical significance defined as two-sided p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. All analyses performed in R 4.4.1.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Cohort characteristics and fundus findings\u003c/h2\u003e \u003cp\u003eA total of 10,330 neonates fulfilled the inclusion criteria, of which 5,043 (48.82%) were male. The mean gestational age was 38.58\u0026thinsp;\u0026plusmn;\u0026thinsp;1.67 weeks, the mean birth weight was 3,241.71\u0026thinsp;\u0026plusmn;\u0026thinsp;526.72 g, and the mean maternal age was 29.49\u0026thinsp;\u0026plusmn;\u0026thinsp;4.86 years (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Fundus imaging revealed abnormal retinal findings in 3,079 infants (29.81%), while 7,251 infants (70.19%) exhibited normal retinal appearances.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of Basic Information of the Participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValues\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5043 (48.82%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5287 (51.18%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestation Age (weeks)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38.58\u0026thinsp;\u0026plusmn;\u0026thinsp;1.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth Weight (g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3241.71\u0026thinsp;\u0026plusmn;\u0026thinsp;526.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal Age (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29.49\u0026thinsp;\u0026plusmn;\u0026thinsp;4.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFunds Image (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7251 (70.19%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbnormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3079 (29.81%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistribution of Abnormal Fundus Disease Count (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 category\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2798 (90.87%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2 categories\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e258 (8.38%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3 categories\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21 (0.68%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4 categories\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (0.06%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Spectrum and frequency of abnormalities\u003c/h2\u003e \u003cp\u003eAmong those with abnormal findings, the majority (2,798; 90.87%) presented with a single category of abnormality; 258 infants (8.38%) exhibited two categories, 21 infants (0.68%) had three categories, and 2 infants (0.06%) had four categories of abnormalities (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Retinal hemorrhage was the most prevalent lesion, identified in 1,850 infants (60.08% of those with abnormal findings) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Other frequent abnormalities included punctate pigmentation (384 infants; 12.47%), peripheral retinal white spots (324 infants; 10.52%), immature retina (277 infants; 9.00%), and pigment abnormality (132 infants; 4.29%). Less common but clinically significant findings comprised punctate choroidal defect (101 infants; 3.28%), vascular underdevelopment (61 infants; 1.98%), FEVR-like patterns (56 infants; 1.82%), unclear optic disc (52 infants; 1.69%), congenital cataract (29 infants; 0.94%), and retinopathy of prematurity (ROP) (19 infants; 0.62%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrevalence of Abnormal Fundus Findings Among the Participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCount\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercent (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetinal Hemorrhage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1850\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePunctate Pigmentation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e384\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeripheral Retinal White Spots\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImmature Retina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePigment Abnormality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePunctate Choroidal Defect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVascular Underdevelopment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFEVR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnclear Optic Disc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCongenital Cataract\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVascular Dysplasia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePersistent Pupillary Membrane\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eROP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlbinism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePHPV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVascular Dilatation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVitreous Opacity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIris Posterior Synechia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVascular Tortuosity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBilateral Punctate Lesions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Group comparisons\u003c/h2\u003e \u003cp\u003eInfants presenting with abnormal fundus findings exhibited significantly lower gestational ages (38.33\u0026thinsp;\u0026plusmn;\u0026thinsp;2.04 weeks compared to 38.68\u0026thinsp;\u0026plusmn;\u0026thinsp;1.47 weeks; t\u0026thinsp;=\u0026thinsp;8.69; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and reduced birth weights (3,148.30\u0026thinsp;\u0026plusmn;\u0026thinsp;531.56 g versus 3,281.38\u0026thinsp;\u0026plusmn;\u0026thinsp;519.63 g; t\u0026thinsp;=\u0026thinsp;11.72; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) relative to those with normal fundus findings, as detailed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Although maternal age showed a marginal statistical difference (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), the mode of delivery demonstrated significant variation (χ\u0026sup2; = 568.53; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Specifically, vaginal delivery was predominant among the group with abnormal findings (69.54% compared to 44.26%), whereas cesarean delivery was more prevalent in the group with normal findings (54.12% compared to 28.65%), as illustrated in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of Gestation Age, Birth Weight, and Maternal Age Between Infants with Normal and Abnormal Fundus Findings\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestation Age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e38.68\u0026thinsp;\u0026plusmn;\u0026thinsp;1.47 (38.65\u0026ndash;38.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbnormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e38.33\u0026thinsp;\u0026plusmn;\u0026thinsp;2.04 (38.26\u0026ndash;38.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth Weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e3281.38\u0026thinsp;\u0026plusmn;\u0026thinsp;519.63 (3269.41\u0026ndash;3293.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbnormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e3148.30\u0026thinsp;\u0026plusmn;\u0026thinsp;531.56 (3129.51\u0026ndash;3167.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal Age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;1.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e29.44\u0026thinsp;\u0026plusmn;\u0026thinsp;4.85 (29.33\u0026ndash;29.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbnormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e29.62\u0026thinsp;\u0026plusmn;\u0026thinsp;4.89 (29.45\u0026ndash;29.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of Delivery Method Between Infants With Normal and Abnormal Fundus Findings\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDelivery Method\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCount (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eχ\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAssisted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e568.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e118 (1.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbnormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56 (1.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC Section\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3924 (54.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbnormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e882 (28.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaginal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3209 (44.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbnormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2141 (69.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Regression Results and Visualization\u003c/h2\u003e \u003cp\u003eBoth simple and multivariable logistic regression analyses produced consistent estimates, as detailed in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. In the final multivariable model (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), the Neonatal Risk Count emerged as the most robust independent predictor of abnormal fundus findings, with an odds ratio (OR) of 1.42 (95% confidence interval [CI] 1.23\u0026ndash;1.63, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Conversely, the Maternal High-Risk Count exhibited a significant inverse relationship (OR 0.80, 95% CI 0.76\u0026ndash;0.84, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Birth weight maintained significance, albeit with a minimal per-gram effect (OR 1.00, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while gestational age demonstrated borderline significance (OR 0.96, 95% CI 0.93\u0026ndash;1.00, p\u0026thinsp;=\u0026thinsp;0.05). Other neonatal clinical factors and sex were not significant predictors.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultiple Logistic Regression Model of Studied Variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(Intercept)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.89 (1.88\u0026ndash;25.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth Weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00 (1.00\u0026ndash;1.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestation Age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.96 (0.93\u0026ndash;1.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeonatal Risk Count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.42 (1.23\u0026ndash;1.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal High-Risk Count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.80 (0.76\u0026ndash;0.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHematologic Metabolic Count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.95 (0.82\u0026ndash;1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory Support Count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.93 (0.82\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFeeding GI Issues Count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.05 (0.88\u0026ndash;1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.06 (0.97\u0026ndash;1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eNote: AUC\u0026thinsp;=\u0026thinsp;0.6 for multiple logistic regression.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eA forest plot was constructed to depict all regression coefficients and their 95% CIs, thereby illustrating the relative contribution of each variable (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Additionally, the scatter-jitter plots in the figure reveal distinct dose-response patterns: the prevalence of abnormal fundus findings shows a monotonically increasing trend with higher Neonatal Risk Counts. In contrast, a slight negative correlation trend is observed for Maternal High Risk Counts, indicating a modest decrease in the prevalence of abnormal fundus findings as the risk count increases (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These visual patterns were entirely consistent with the regression estimates. Model diagnostics confirmed good stability.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe model diagnostics demonstrated satisfactory stability, as evidenced by all variance inflation factors (VIFs) being less than 2,, as detailed in Table S2, indicating an absence of problematic multicollinearity. Sensitivity analyses employing penalized logistic regression for rare outcomes yielded results that were directionally consistent with the primary model, thereby reinforcing its robustness.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIn this large cohort of 10,330 neonates undergoing universal wide-field digital retinal photography (WFDRP), nearly one-third (29.81%) exhibited abnormal fundus findings. This prevalence is comparable to that reported in large-scale neonatal screening programs from China, India, Malaysia, and New Zealand, where abnormal posterior segment findings ranged from approximately 20% to 30%\u003csup\u003e5,12,23,24\u003c/sup\u003e. The high detection rate underscores that a substantial proportion of neonatal fundus abnormalities would likely remain unrecognized without systematic imaging-based screening.\u003c/p\u003e \u003cp\u003e The spectrum of abnormalities observed in this study was dominated by retinal hemorrhage (RH), accounting for approximately 60% of all abnormal findings, followed by punctate pigmentation, peripheral retinal white spots, immature retina, and pigment abnormalities. This distribution closely mirrors prior WFDRP-based studies, in which RH consistently emerged as the most prevalent lesion among term and near-term infants\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. RH in neonates is widely regarded as a manifestation of delivery-related mechanical stress, perinatal hypoxia, and abrupt changes in intracranial and ocular venous pressure. Ji et al. demonstrated that ocular compression during delivery\u0026mdash;particularly with vacuum or forceps assistance\u0026mdash;plays a major etiologic role in the development of RH\u003csup\u003e17\u003c/sup\u003e. Although the majority of RH cases are intraretinal and self-limited, resolving spontaneously within weeks, their high prevalence reinforces the value of early documentation and follow-up to distinguish benign transient findings from lesions requiring surveillance\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBeyond RH, the detection of vascular developmental variants, FEVR-like patterns, punctate choroidal defects, and rare congenital anomalies highlights the broader clinical value of universal screening. Large neonatal fundus-screening initiatives have consistently shown that WFDRP enables early identification of uncommon but potentially vision-threatening conditions, facilitating timely referral and intervention\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. The presence of multiple categories of abnormalities in a subset of infants in our cohort further suggests that neonatal fundus pathology often reflects a cumulative burden of perinatal stress rather than isolated ocular events.\u003c/p\u003e \u003cp\u003eGroup comparisons revealed that infants with abnormal fundus findings had significantly lower gestational ages and birth weights than those with normal findings. These observations are consistent with extensive prior literature demonstrating that both gestational maturity and fetal growth are critical determinants of retinal vascular development\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Tang et al., in a multicenter study involving nearly 200,000 newborns, reported a clear gradient effect of birth weight on the prevalence of retinal abnormalities\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Current evidence links low birth weight and intrauterine growth restriction (IUGR) with abnormal retinal vascular development\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Studies have linked these conditions with long-term alterations in retinal vessel morphology, indicating that IUGR may disrupt normal vascular programming\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. This disruption could predispose the retina to hemodynamic instability, potentially explaining a higher susceptibility to conditions such as retinal hemorrhage and optic disc anomalies.\u003c/p\u003e \u003cp\u003eThe biological plausibility of these associations is well supported. Retinal and choroidal vascularization continues through late gestation and into the early postnatal period, rendering the immature vasculature particularly vulnerable to fluctuations in oxygenation and perfusion\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Prior studies have shown that lower birth weight and younger gestational age are associated with abnormal retinal vessel morphology in moderately preterm infants\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e, delayed choroidal thickening\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, and long-term alterations in macular vessel density and foveal avascular zone characteristics\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Collectively, these findings support the inclusion of birth weight and gestational age as key parameters in neonatal ocular risk stratification.\u003c/p\u003e \u003cp\u003eDelivery mode differed markedly between infants with and without abnormal fundus findings, with vaginal delivery being substantially more common in the abnormal group, while cesarean delivery predominated among infants with normal fundus appearances. This pattern is concordant with previous reports linking vaginal delivery to a higher incidence of RH, likely due to increased mechanical compression of the globe and transient elevations in venous pressure during labor and delivery\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. In contrast, cesarean delivery may mitigate these mechanical forces, thereby reducing the risk of birth-related retinal hemorrhage. Although delivery mode was not included as an independent variable in the final regression model, its strong univariate association highlights the importance of perinatal mechanical factors in shaping neonatal fundus outcomes.\u003c/p\u003e \u003cp\u003eMultivariable logistic regression analysis further clarified the relative contributions of perinatal and systemic factors. Neonatal systemic burden, quantified by the Neonatal Risk Count, emerged as the strongest independent predictor of abnormal fundus findings. This result aligns with prior evidence linking systemic neonatal illness\u0026mdash;including sepsis, asphyxia, respiratory failure, and metabolic instability\u0026mdash;to retinal vascular injury through inflammatory pathways, impaired autoregulation, and altered perfusion\u003csup\u003e\u003cspan additionalcitationids=\"CR34\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Notably, neonatal sepsis has been proposed as an oxygen-independent contributor to retinopathy of prematurity in both cohort studies and narrative reviews\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. The clear dose\u0026ndash;response relationship observed between increasing Neonatal Risk Count and abnormal fundus prevalence in our cohort further supports a cumulative-risk model, in which systemic illness amplifies retinal vulnerability.\u003c/p\u003e \u003cp\u003eIn contrast, the Maternal High-Risk Count demonstrated a significant inverse association with abnormal fundus findings. Although this observation may appear counterintuitive, it is consistent with a growing body of literature suggesting that certain maternal complications do not uniformly increase neonatal ocular risk. In very-low-birth-weight infants, maternal preeclampsia has been associated with a reduced risk of ROP (adjusted OR\u0026thinsp;=\u0026thinsp;0.65)\u003csup\u003e36\u003c/sup\u003e, with similar protective trends reported in other cohorts\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Conversely, in full-term infants, pregnancy-related hypertension has been linked to increased RH and other fundus abnormalities\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, underscoring the heterogeneity of maternal risk effects.\u003c/p\u003e \u003cp\u003eIn our cohort, the aggregated maternal high-risk variable likely encompassed diverse conditions with differing pathophysiologic implications. The observed protective association may reflect intensified prenatal surveillance, planned delivery strategies (including higher rates of cesarean section), and optimized neonatal care among high-risk pregnancies. Such measures may reduce fetal hypoxia, hemodynamic instability, and birth trauma\u0026mdash;key contributors to RH and retinal vascular abnormalities. These findings suggest that aggregated maternal risk scores may obscure condition-specific effects and highlight the need for future studies to disaggregate maternal risk subtypes and incorporate perinatal management variables when modeling neonatal retinal outcomes.\u003c/p\u003e \u003cp\u003eOther neonatal clinical factors, including hematologic/metabolic abnormalities, respiratory support frequency, feeding or gastrointestinal issues, and sex, were not independently associated with abnormal fundus findings after adjustment. The similarity between simple and multivariable regression estimates, together with low variance inflation factors, indicates minimal confounding and limited multicollinearity among predictors, supporting the stability of the model. Sensitivity analyses using penalized regression approaches for rare outcomes yielded directionally consistent results, further reinforcing the robustness of the observed associations.\u003c/p\u003e \u003cp\u003eAlthough the discriminative performance of the multivariable model was modest (AUC\u0026thinsp;=\u0026thinsp;0.60), this finding should be interpreted in the context of the study objective. The primary aim was etiologic inference and population-level risk stratification rather than individual-level prediction. In neonatal screening research, particularly when outcomes are heterogeneous and largely transient, moderate AUC values are common and do not preclude clinical relevance\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Importantly, the model demonstrated internally consistent effect estimates, biologically plausible directions of association, and clear dose\u0026ndash;response patterns for key predictors, such as Neonatal Risk Count and Maternal High-Risk Count (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These features suggest that the model captures meaningful population-level relationships even if its standalone predictive accuracy is limited. Future studies incorporating longitudinal outcomes and additional perinatal variables may further improve predictive performance.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFrom a clinical and public health perspective, these findings provide additional support for universal WFDRP screening in neonates. Prior programs in India (KIDROP) and China have demonstrated that systematic imaging improves early detection, reduces missed diagnoses, and facilitates longitudinal monitoring of retinal health\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Clare O et al. emphasized that many neonatal and infantile ocular conditions are reversible if identified early, whereas delayed diagnosis may result in permanent visual impairment\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. The present results indicate that even term infants without overt clinical risk factors may harbor fundus abnormalities linked to subtle perinatal and systemic stressors, arguing against overly restrictive, risk-based screening strategies in high-volume birth settings.\u003c/p\u003e \u003cp\u003eThe strengths of this study include its large sample size, the use of validated WFDRP technology, comprehensive characterization of neonatal and maternal risk factors, and consistent findings across multiple analytic approaches. Nevertheless, several limitations warrant consideration. The single-center design may limit generalizability, and the absence of long-term follow-up precludes confirmation of lesion resolution or long-term visual sequelae. Important obstetric variables, such as labor duration and detailed delivery mechanics, were unavailable, and inter-operator variability in image acquisition may have introduced measurement heterogeneity. In addition, the moderate discriminative performance of the regression model likely reflects the heterogeneous and largely transient nature of neonatal fundus findings rather than inadequate modeling. Future multicenter, longitudinal studies incorporating detailed perinatal management data, serial imaging, and long-term visual outcomes are needed to better delineate the natural history of neonatal fundus abnormalities and to refine screening strategies.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eOur findings confirm that neonatal posterior segment abnormalities are common and significantly influenced by birth weight, gestational age, neonatal systemic morbidity, and perinatal conditions. Universal WFDRP screening is feasible, safe, and clinically valuable for early identification of both transient and potentially vision-threatening lesions. These results support broader adoption of neonatal eye screening programs, particularly in regions with higher risk profiles and limited access to pediatric ophthalmology.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of Lishui Maternity and Child Health Care Hospital (NO.2020030), and it is in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants. For participants under 16 years of age, parental or legal guardian consent was additionally secured prior to enrollment.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets are not publicly available due to patient privacy concerns but can be provided by the corresponding author upon reasonable request and approval from the institutional ethics committee.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Lishui Science and Technology Bureau Public Welfare Technology Applied Research Project [Grant Number 2021SJZCO58]: \u0026ldquo;Application of RetCam III Wide-Field Digital Imaging System in Neonatal Eye Disease Screening.\u0026rdquo;.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChunjuan Wang contributed to data collection and assisted in revising the manuscript. Lixing Zhou drafted the manuscript, led the writing of the article, and participated in data interpretation as well as table and figure preparation. Chunhong Ye and Shuzheng Chen was involved in the entire process of data collection and quality management. Qunda Shan and Jiao Liu served as corresponding authors. Chunjuan Wang and Lixing Zhou contributed equally to this work. All authors reviewed and approved the final manuscript and agree to be personally accountable for their own contributions and to ensure the integrity of the work.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eDeclaration of generative AI and AI-assisted technologies in the manuscript preparation process\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the preparation of this work, the authors used DeepSeek (an AI language model by DeepSeek Company) for language polishing, grammar checking, and improving the clarity and fluency of the text. After using this tool, the authors thoroughly reviewed and edited the content as needed and take full responsibility for the content of the published article.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSubhi Y, Schmidt DC, Al-Bakri M, Bach-Holm D, Kessel L. 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Semin Fetal Neonatal Med. 2015;20(5):335\u0026ndash;45. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.siny.2015.05.002\u003c/span\u003e\u003cspan address=\"10.1016/j.siny.2015.05.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStocks CO, Carson RA. Newborn and infant vision screening in primary care: A clinical review. J Spec Pediatr Nurs JSPN. 2024;29(1):e12421. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/jspn.12421\u003c/span\u003e\u003cspan address=\"10.1111/jspn.12421\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-ophthalmology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"boph","sideBox":"Learn more about [BMC Ophthalmology](http://bmcophthalmol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/boph","title":"BMC Ophthalmology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Newborn, Wide-field retinal image, Retinal hemorrhage, Fundus screening, Perinatal factors","lastPublishedDoi":"10.21203/rs.3.rs-9090581/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9090581/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo characterize the prevalence and spectrum of fundus abnormalities in a large newborn cohort and to evaluate the association of these abnormalities with perinatal immaturity, a novel composite neonatal morbidity index, and a composite maternal high-risk index.\u003c/p\u003e\u003ch2\u003eDesign:\u003c/h2\u003e \u003cp\u003eRetrospective, single-center cohort study.\u003c/p\u003e\u003ch2\u003eParticipants:\u003c/h2\u003e \u003cp\u003eA total of 10,330 consecutive newborns who underwent universal wide-field digital retinal photography (WFDRP) screening within 72 hours of birth.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eTwo novel aggregated indices\u0026mdash;the Neonatal Risk Count (summing complications across four domains: baseline risk, respiratory support, feeding/gastrointestinal issues, and hematologic/metabolic issues) and the Maternal High-Risk Count (summing peripartum risk factors)\u0026mdash;were constructed. Fundus findings were classified as normal or abnormal. Univariable and multivariable logistic regression were used to assess associations, with multicollinearity assessed by variance inflation factors (VIF).\u003c/p\u003e\u003ch2\u003eMain Outcome Measures:\u003c/h2\u003e \u003cp\u003ePrevalence of any fundus abnormality; adjusted odds ratios (OR) for the association between abnormal fundus status and key predictors including birth weight, gestational age, Neonatal Risk Count, and Maternal High-Risk Count.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eFundus abnormalities were detected in 3,079 infants (29.8%). Retinal hemorrhage was the most common finding (60.1% of abnormalities). In the final multivariable model, a higher Neonatal Risk Count (OR 1.42 per additional risk, 95% CI 1.23\u0026ndash;1.63, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), lower birth weight (OR 1.00 per gram, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and lower gestational age (OR 0.96, 95% CI 0.93\u0026ndash;1.00, p\u0026thinsp;=\u0026thinsp;0.05) were independent predictors of abnormal findings. The Maternal High-Risk Count showed a significant inverse association (OR 0.80, 95% CI 0.76\u0026ndash;0.84, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Other neonatal clinical domain counts and sex were not significant. All VIFs were \u0026lt;\u0026thinsp;2.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eIn this large cohort, nearly one-third of newborns had detectable fundus abnormalities on WFDRP. Cumulative neonatal morbidity burden and perinatal immaturity were significant risk factors, while a higher aggregated maternal risk score was associated with lower odds of abnormality. These findings support the utility of WFDRP in universal newborn screening and highlight the importance of neonatal systemic health in ocular outcomes.\u003c/p\u003e","manuscriptTitle":"Wide-field Digital Retinal Photography in 10,330 Newborns: Prevalence, Risk Factors and Clinical Implications in a Large Chinese Cohort","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-24 13:18:57","doi":"10.21203/rs.3.rs-9090581/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"166159279818121954669241412536616535669","date":"2026-05-03T20:55:32+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-13T11:22:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"210632353928579768134689841885184152704","date":"2026-03-21T15:50:15+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-19T09:16:49+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-16T09:59:31+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-16T04:16:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-16T04:16:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Ophthalmology","date":"2026-03-11T06:06:18+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-ophthalmology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"boph","sideBox":"Learn more about [BMC Ophthalmology](http://bmcophthalmol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/boph","title":"BMC Ophthalmology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d75f408a-e593-43a0-9bc1-504d1d74dea0","owner":[],"postedDate":"March 24th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"166159279818121954669241412536616535669","date":"2026-05-03T20:55:32+00:00","index":48,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-24T13:18:57+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-24 13:18:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9090581","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9090581","identity":"rs-9090581","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}