Patent Ductus Arteriosus Management in Very Preterm Infants: Center-Level Treatment Strategies and Outcomes Across the Neocosur Network

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Study Design Retrospective multicenter cohort study using prospectively collected data from the Neocosur Neonatal Network (2015–2021). Infants born at ≤ 28 weeks’ gestation with PDA were included. Centers were classified into quartiles according to PDA treatment rate. The primary outcome was BPD or death. Mixed-effects logistic regression models with a random intercept for center were fitted and adjusted for gestational age. Results The cohort included 2,777 infants from 32 NICUs. PDA treatment rates varied widely across centers. After accounting for center-level clustering, treatment attitude was not associated with BPD or death. Gestational age showed a strong inverse association with the outcome. Approximately 8% of outcome variability was attributable to between-center differences. Conclusions Center-level PDA treatment intensity was not associated with major outcomes, supporting individualized, physiology-informed management. Health sciences/Medical research/Epidemiology Health sciences/Health care/Paediatrics Figures Figure 1 Figure 2 Introduction The management of patent ductus arteriosus (PDA) in very preterm infants (born ≤ 28 weeks’ gestation) has evolved significantly over recent years, shifting toward more conservative strategies, including a reduction in pharmacologic and surgical interventions 1 – 3 . Several studies have examined the impact of these evolving practices on neonatal outcomes, yielding conflicting results 4 – 6 . The pathophysiology of a significant left-to-right ductal shunt is well established and has been strongly associated with complications of prematurity, including bronchopulmonary dysplasia (BPD) and mortality 7 – 9 . However, evidence supporting clear long-term benefits of either medical or surgical PDA closure remains insufficient 10 , and although both pharmacologic and surgical approaches have been linked to adverse outcomes in some studies, this association remains uncertain, with other reports suggesting no definitive causal relationship 11 – 13 . Although first proposed more than a decade ago, the concept of an individualized, physiology-based approach to PDA management remains highly relevant today. This perspective challenges the assumption that less treatment universally leads to better outcomes, suggesting that timing and criteria for intervention are critical and that a one-size-fits-all strategy may not be appropriate. Consequently, a uniform strategy applied at the institutional level, whether aggressively intervening or minimally treating, may not adequately reflect patient-level physiologic needs 14 . The Neocosur Neonatal Network is a voluntary non-profit South American collaboration comprising 40 neonatal units across Argentina, Chile, Paraguay, Peru, and Uruguay. These University-affiliated centers represent a mix of public and private tertiary-care institutions. Since 2001, the network prospectively collects standardized data on morbidity, mortality, as well as antenatal and postnatal care practices in very low birth weight (VLBW) infants ( www.neocosur.org ). Despite decades of research, no clear consensus exists on PDA management, and practices vary widely across neonatal intensive care units (NICUs), regions, and countries, particularly among very preterm infants. Whether this variation at the center level is associated with clinically meaningful differences in outcomes is still unclear. Therefore, our objective was to explore the center-level variation in PDA treatment rates across the Neocosur Network and evaluate whether the overall treatment attitude of a NICU, ranging from highly conservative to highly interventional, was associated with the combined outcome of BPD or death in very preterm infants. Methods Methods Study Design This was a retrospective, observational, multicenter cohort study using prospectively collected data from very preterm infants enrolled in the Neocosur Neonatal Network between 2015 and 2021. The Network includes university-affiliated public and private tertiary-care neonatal units across Argentina, Chile, Paraguay, Peru, and Uruguay, and maintains a harmonized database with standardized definitions and prospective data collection. Study Population Infants were eligible for inclusion if they were born between 24 + 0 and 28 + 6 weeks of gestation and had a clinical and/or echocardiographic diagnosis of patent ductus arteriosus (PDA). We excluded infants with major congenital malformations, delivery room deaths, missing information for the primary outcome, and births at centers with fewer than 10 years of continuous network participation. This strategy ensured stable center-level estimates of treatment rates. Exposure: Center-Level Treatment Attitude PDA treatment was defined as receipt of pharmacologic therapy (indomethacin, ibuprofen, or acetaminophen) and/or surgical ligation any time prior NICU discharge or death. No percutaneous closure procedures were performed during the enrollment time. For each center, the PDA treatment rate was calculated as the proportion of infants with PDA who received any treatment. All obtained center treatment rate distribution were then separated into four exact quartiles of treatment rate, representing 4 intensity of treatment levels: very low treatment attitude, low treatment attitude, moderate treatment attitude and high treatment attitude. These quartiles reflect each NICU’s overall management tendency rather than individual clinical decisions. To examine whether PDA treatment practices changed over time, we evaluated temporal trends in center-level treatment rates. First, we fitted a mixed-effects logistic regression model with standardized year of birth as a fixed effect and center as a random intercept to assess the overall temporal trajectory of PDA treatment across the Network. Second, within-center temporal trends were assessed by fitting individual binomial models of annual treatment rate versus year for each NICU. These analyses identified a minority of centers with statistically significant slopes. Because of the small contribution of each center to the overall effect, all centers were retained in the primary analysis. Then a sensitivity analysis was conducted, repeating the primary analysis after excluding centers with significant temporal trends, to evaluate the robustness of the findings. Outcomes The primary outcome was the composite of death or bronchopulmonary dysplasia (BPD), with BPD defined according to the 2018 NICHD criteria. Secondary outcomes included BPD alone and death before discharge. Covariates Candidate covariates were selected a priori based on biological plausibility and known determinants of illness severity and maturity: birthweight, small-for-gestational-age status according to Fenton charts, sex, multiple gestation, antenatal steroids, magnesium sulfate, chorioamnionitis, Apgar scores (1 and 5 minutes), and delivery room resuscitation intensity. To select the adjusting variables set a two-step classical confounding strategy was applied. First, bivariate comparisons across quartiles of treatment attitude (χ², ANOVA/Kruskal–Wallis) were used to identify variables imbalanced across exposure levels. Variables showing imbalance or clinical relevance were entered into separate mixed-effects logistic models with treatment attitude as the dependent variable. A variable was considered a confounder if adjusting for it produced a ≥ 20% change in any treatment-attitude coefficient. Using this approach, gestational age was identified as the only covariate meeting confounding criteria. No other candidate variable changed the treatment-attitude coefficients meaningfully or improved model fit. Therefore, gestational age was included as the sole fixed-effect adjustment variable. Statistical Analysis Continuous variables were summarized using means (SD) or medians (median absolute deviation). Categorical variables were described using counts and percentages. To evaluate the association between treatment attitude and outcomes, we initially fitted a bivariate mixed-effects logistic regression including treatment attitude as the fixed effect and center as a random intercept to capture clustering and baseline heterogeneity between NICUs. Then the adjusted mixed-effects logistic regression including treatment attitude, gestational age, and the center random intercept. And finally an exploratory interaction model to assess modification effect between treatment attitude and gestational age. Model Performance and Diagnostics Calibration was evaluated using calibration plots by deciles of predicted risk and by estimating the calibration intercept and slope. Because the objective was explanatory rather than predictive, discrimination was assessed only internally using the area under the ROC curve (AUC). Residual diagnostics and model assumptions were examined using simulated residuals and included normal distribution of the random effects, significant outliers and heteroscedasticity. Sample Size Calculations We used all eligible cases from the Neocosur registry between 2015 and 2021; no formal a priori sample size calculation was performed. The final cohort included 2777 infants from 32 centers with > 1700 primary outcome events, yielding an events-per-variable ratio far above conventional recommendations for logistic mixed-effects models and an ICC of 0.08 for the primary outcome, supporting adequate power and model stability. Data Analysis Software Specifications The statistical analysis was performed on R software with RStudio environment 15 , 16 . Mixed Models were fit using the glmmTMB package, model assumptions were checked through simulated residuals with the DHARMA package, performance metrics were obtained using the pROC package while data processing and graphics were performed through ggplot2 package 17 – 20 . Ethical Considerations All participating centers had local institutional review board approval for data collection. Data were obtained in accordance with either a waiver of consent or written informed consent from parents or legal guardians, depending on local regulations. The Neocosur database is registered and approved by the Institutional Review Board of Universidad Austral, Buenos Aires, Argentina (CIE #15–038). Results Study Population After applying inclusion and exclusion criteria, 2777 very preterm infants with PDA from 32 Neocosur centers were included (Fig. 1a). Treatment attitude quartiles showed wide variation in PDA treatment rates (Fig. 1b). We also found crude significant differences between quartiles in gestational age, multiple birth, IUGR, prenatal steroids, chorioamnionitis, magnesium sulfate, surfactant administration and delivery room CPAP, intermittent positive pressure ventilation and chest compressions defining potential confounders (Table 1 ). Table 1 Demographic Characteristics and Treatment Attitudes cutoff points Treatment Attitude Rate (Cutoff points) Quartile 1 Very Low (≤ 62.5%) N = 658 Quartile 2 Low (62.6–83.6%) N = 492 Quartile 3 Moderate (83.7–87.4%) N = 927 Quartile 4 High (≥ 87.5%) N = 700 BW (gr)* 889 (229) 907 (225) 887 (223) 906 (213) GA (wk)** 27 (24–28) 26 (24–28) 26 (24–28) 27 (24–28) Gender (Male %) 358 (54.4%) 274 (55.7%) 518 (55.9%) 375 (53.6%) Multiple Birth 481 (73.1%) 378 (76.8%) 716 (77.2%) 568 (81.1%) Prenatal Steroids 574 (87.2%) 426 (86.6%) 803 (86.6%) 511 (73.0%) Chorioamnionitis 111 (16.9%) 71 (14.4%) 163 (17.6%) 82 (11.7%) Magnesium Sulfate 338 (51.4%) 230 (46.7%) 460 (49.6%) 248 (35.4%) IUGR 148 (22.5%) 101 (20.5%) 136 (14.7%) 83 (11.9%) AGA (PC ≥ 10th ) 574 (87.2%) 446 (90.7%) 847 (91.4%) 636 (90.9%) SGA (PC < 10th & ≥ 3rd ) 56 (8.5%) 31 (6.3%) 58 (6.3%) 48 (6.9%) VSGA (PC < 3rd ) 28 (4.3%) 15 (3.0%) 22 (2.4%) 16 (2.3%) Apgar Score 1 minute** 5 (0–10) 5 (0–9) 5 (0–10) 6 (0–9) Apgar Score 5 minutes** 8 (0–10) 8 (1–10) 8 (0–10) 8 (0–9) CPAP in DR 356 (54.1%) 355 (72.2%) 445 (48.0%) 308 (44.0%) IPPV in DR 545 (82.8%) 426 (86.6%) 692 (74.6%) 499 (71.3%) Chest Compressions in DR 63 (9.6%) 44 (8.9%) 131 (14.1%) 47 (6.7%) Surfactant Administration 562 (85.4%) 447 (90.9%) 814 (87.8%) 637 (91.0%) Table 1 Footnotes: * Mean (Standard Deviation) ** Median (Range) BW: Birthweight, GA: Gestational Age, IUGR: Intrauterine Growth Restriction, AGA: Adequate for Gestational Age, SGA: Small for Gestational Age, VSGA: Very Small for Gestational Age, DR: Delivery Room, CPAP: Continuous Positive Airway Pressure, PPV: Intermittent Positive Pressure Ventilation The overall incidence of the primary outcome (death or BPD) was 61.9%, ranging from 28.1% to 87.8% across centers. Detailed center-level demographic characteristics and treatment rates are provided in Supplementary Table S1 . Primary Outcome In crude comparisons, treatment attitude was associated with the composite outcome: the distribution of BPD or death differed significantly across quartiles (Pearson’s χ² = 24.4, p < 0.001). However, this association disappeared once center-level clustering was incorporated. In the unadjusted mixed-effects logistic model with treatment attitude as the only fixed effect and center as a random intercept, none of the treatment quartiles differed significantly from the very low treatment group (Table 2 ). Pairwise comparisons yielded odds ratios close to 1 with wide, overlapping confidence intervals (all Tukey-adjusted p-values > 0.75). Table 2 Unadjusted and Adjusted Mixed Logistic Regression for BPD or Death Variable Unadjusted OR 95% CI Adjusted OR Standard Error 95% CI p-value Very Low Treatment Attitude (Q1) 1 -- 1 1 -- 1 Low Treatment Attitude (Q2) 0.9 0.54–1.64 0.81 0.31 0.44–1.50 0.501 Moderate Treatment Attitude (Q3) 0.93 0.57–1.52 0.81 0.28 0.47–1.38 0.434 High Treatment Attitude (Q4) 1.24 0.74–2.10 1.24 0.30 0.70–2.21 0.464 GA (wk) -- -- 0.53 0.04 0.50–0.57 < 0.001 Table 2 Footnotes: GA: Gestational Age, Q1-Q4: Quartile of Treatment Attitude from Very Low to High The intraclass correlation coefficient (ICC) was 0.08, indicating that approximately 8% of the variability in BPD or death was attributable to between-center differences rather than treatment attitude. In the gestational-age–adjusted model, treatment attitude remained unassociated with the primary outcome, while gestational age showed a strong inverse association with BPD or death. Estimated effects for all treatment quartiles were close to the null and showed no consistent trend (Table 2 ). The model including an interaction term between treatment attitude and gestational age did not reveal statistically significant effect modification (all interaction p-values between 0.24–0.94; Supplementary Table S2). Figure 2a displays overlapped adjusted predicted probabilities for BPD or death by treatment attitude quartile. Figure 2b shows center-specific random intercepts, highlighting substantial baseline risk heterogeneity beyond treatment intensity. Additional details on assumptions, residual diagnostics and calibration are provided in the Supplementary File (Figures S2 and S3). Temporal Trends We evaluated whether PDA treatment practices changed during the study period. In the overall mixed-effects model, year of birth showed a small but statistically significant positive association with treatment (β = 0.166, SE 0.050, p = 0.0009), indicating a modest increase in treatment over time. When examining centers individually, 9 of 32 NICUs (28%) demonstrated significant temporal trends, whereas the remaining 23 maintained stable treatment patterns. The sensitivity analysis that excluded these centers showed no significant differences between treatment attitude quartiles after Tukey pairwise correction test. Full estimates are provided in Supplementary Figure S1 . Secondary Outcomes Secondary outcomes were consistent with the primary analysis. Neither death nor BPD, examined separately in gestational-age–adjusted mixed-effects models, differed meaningfully across treatment attitude quartiles after accounting for center-level clustering. Full estimates are provided in Supplementary Table S3. Discussion In this multicenter cohort of 2777 very preterm infants across 32 NICUs within the Neocosur Network, we observed substantial variability in PDA treatment practices. However, after accounting for gestational age and center-level clustering, we found no association between center treatment attitude and the risk of BPD or death. This suggests that, independently of infants gestational age, treatment frequency at the institutional level, by itself, does not determine major clinical outcomes. These findings should be interpreted within the intrinsic heterogeneity of the Neocosur Network, where centers differ in resources, thresholds for intervention, clinical philosophies, and co-intervention patterns. Such diversity reflects real-world practice in Latin America and may contribute to the absence of an association between aggregated treatment attitude and outcomes. Importantly, the lack of association at this highly aggregated level does not imply that individual PDA strategies are equivalent for specific infants. Rather, it highlights that PDA management is multifactorial, shaped by physiology, timing, and patient-specific vulnerability, factors that may be partially hidden when treatment practices are summarized into center-level categories. Prior studies examining center-level or temporal variation in PDA management have reported heterogeneous findings. Isayama et al. described a U-shaped pattern in observed-to-expected treatment ratios across international networks 21 , while Hagadorn et al. noted increased mortality among the most immature infants during periods of declining treatment 22 . Kaluarachchi et al. observed rising rates of moderate–severe BPD despite lower treatment intensity in infants 26–28 weeks’ gestation 5 and Altit et al., in a comparative two-center study, reported that the adoption of a strict non-intervention policy resulted in worsening outcomes in extremely preterm infants (< 26 weeks' gestation) 23 . These studies underscore ongoing uncertainty regarding the population-level consequences of shifting PDA practices and illustrate that center-level treatment intensity is influenced by multiple contextual and clinical factors. Our results did not find significant differences in BPD, death, or the composite outcome across treatment attitude quartiles. Thus, although variability in PDA treatment was substantial, treatment frequency at center level did not predict major outcomes in our cohort. Instead, our data aligns with emerging frameworks advocating for physiology-based decision-making. Approaches proposed by El-Khuffash, Weisz, and McNamara emphasize the identification of infants with clinically significant shunts and the use of tailored, timing-sensitive interventions rather than uniformly conservative or interventionist institutional policies 24 . In this context, our observations reinforce the idea that the key question is not how often a NICU treats PDA, but which infants are selected for treatment and at what time. Variations in clinical practice likely reflect the absence of a clear consensus and limitations in the current evidence base. Much of this uncertainty stems from shortcomings in existing and ongoing randomized controlled trials 25 – 27 . In a recent editorial, Clyman 28 provides a thoughtful critique of these studies, suggesting that many have struggled to identify the infants most likely to benefit from intervention, due to broad inclusion criteria and issues with timing. His perspective underscores the ongoing challenge of defining a truly high-risk subgroup for whom PDA closure may offer meaningful benefit and highlights the need for future research that better aligns treatment strategies with physiological vulnerability. A key strength of our study is the restriction of the cohort to very preterm infants (≤ 28 weeks’ gestation), a population in which uncertainty regarding PDA management remains particularly high. In relatively mature preterm infants, spontaneous ductal closure occurs more frequently, and the potential benefits of treatment may not consistently outweigh its risks. In contrast, among very preterm infants, PDA management decisions are inherently more complex, and clinical equipoise regarding intervention persists 29 . Focusing on this population allowed us to examine center-level treatment variability precisely in the clinical context where the balance between conservative and interventional strategies is most clinically relevant. Further strengths include the large, multinational sample and the opportunity to capture real-world variation across NICUs serving diverse populations, including those from low- and middle-income settings. This diversity, often viewed as a challenge, may instead represent strength, offering insight into how PDA practices perform under a range of resource and organizational conditions. Finally, temporal analyses demonstrated modest network-wide variation and predominantly stable within-center treatment patterns, suggesting that secular trends were unlikely to account for our findings. Still, limitations must be acknowledged. The retrospective design precludes complete adjustment for unmeasured confounding, including echocardiographic markers of PDA significance and timing of intervention. In addition, the number of extremely preterm infants (23–25 weeks’ gestation) was small, limiting subgroup-specific conclusions. Finally, although center-level treatment rate is an informative descriptor of practice attitude, it is not a proxy for optimal care. Without physiological detail, we cannot establish whether the infants who received PDA closure, or those managed conservatively, were the ones most likely to benefit. Conclusions Marked variability in PDA treatment across Neocosur centers reflects persistent uncertainty regarding optimal management. Despite this variability, we found no clear relationship between treatment intensity and major outcomes. These results reinforce the need to move beyond uniform policies and toward individualized, physiology-informed approaches that integrate gestational age, hemodynamics, and clinical context. Future work, ideally through well-designed randomized or stratified trials, will be essential to define which infants benefit most from PDA intervention. Declarations Conflict of Interest The authors declare that they have no competing financial interests related to this study. Funding This study did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Ethics approval and consent to participate This study involved the analysis of prospectively collected data from the Neocosur Neonatal Network. All participating centers obtained approval from their respective local institutional review boards for data collection. Data were collected in accordance with national regulations, with either written informed consent from parents or legal guardians or a waiver of consent, depending on local requirements. The Neocosur database is approved by the Institutional Review Board of Universidad Austral, Buenos Aires, Argentina (CIE #15–038). The study was conducted in accordance with the Declaration of Helsinki. Consent for Publication Not applicable. This manuscript does not contain any individual person’s identifiable data. Availability of data and materials Data that supports the findings of this study is available from the Neocosur Neonatal Network, but restrictions apply to their availability as they contain sensitive patient-level information and are subject to institutional and ethical approvals. Data may be made available to qualified researchers upon reasonable request and with permission from the Neocosur Network. Author Contributions C.C.: Conceptualization, Methodology, Software, Formal analysis, Writing – Original Draft, Writing – Review & Editing. Acknowledgments The authors thank Dr. Luis Prudent for his generous and thoughtful review of the manuscript. 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Early Treatment of the Presymptomatic Patent Ductus Arteriosus. JAMA Pediatr . Published online May 27, 2025. doi: 10.1001/jamapediatrics.2025.1022 de Klerk JCA, Engbers AGJ, van Beek F, et al. Spontaneous Closure of the Ductus Arteriosus in Preterm Infants: A Systematic Review. Front Pediatr . Frontiers Media S.A. 2020;8. doi: 10.3389/fped.2020.00541 Additional Declarations There is NO conflict of interest to disclose. Supplementary Files SupplementalMaterial.pdf Supplemental Material Cite Share Download PDF Status: Posted Version 1 posted 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-8476037","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":573234816,"identity":"7ac1e0fe-3faa-4ec7-a71d-8fe13a5596ed","order_by":0,"name":"Cecilia Cocucci","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIiWNgGAWjYJCCAw8M4GwJOYgIIS0JSFqMISKErEFWkNiALoIO+NubHx5IKLADMZ5J/KixSJ8fdhgowmAnp9uAXYvEmWMGQIclgxhmkj3HJHI33k4DijAkG5sdwK7FQCIH5BdmEINNmrEBqGV2AkjLgcRtuLTIvwFpqYdrSTecnf4BvxYJHpCWw3AtCfLSOfhtkTgDcrnBcR6gX4wtgX4x3CCdUwDyHU6/8Lcffvzhw59qOVDQ3fhRUycvPzt984cPFXZyuLTAAA/CqWCVBrgUYgPyDaSoHgWjYBSMgpEAAF0NW4D9i7JhAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0009-0000-4616-8835","institution":"Hospital Universitario Austral","correspondingAuthor":true,"prefix":"","firstName":"Cecilia","middleName":"","lastName":"Cocucci","suffix":""},{"id":573234817,"identity":"197d3623-2351-45ce-97b2-2c96ed3c8898","order_by":1,"name":"Maria Gabriela Deu","email":"","orcid":"","institution":"Hospital Universitario Austral","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"Gabriela","lastName":"Deu","suffix":""},{"id":573234818,"identity":"54de9b1c-e7a7-40bd-944b-13dbf8cb6341","order_by":2,"name":"Alvaro González","email":"","orcid":"https://orcid.org/0000-0002-0442-9109","institution":"Pontificia Universidad Catolica de Chile","correspondingAuthor":false,"prefix":"","firstName":"Alvaro","middleName":"","lastName":"González","suffix":""},{"id":573234819,"identity":"066ec9e2-ff88-48cf-8426-d6acc46b36f5","order_by":3,"name":"Milagros Risso","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Milagros","middleName":"","lastName":"Risso","suffix":""},{"id":573234820,"identity":"0f235110-7a0e-4ae6-bdd4-6a1a14f57c51","order_by":4,"name":"Jose L. Tapia","email":"","orcid":"","institution":"Universidad Catolica de Chile","correspondingAuthor":false,"prefix":"","firstName":"Jose","middleName":"L.","lastName":"Tapia","suffix":""},{"id":573234821,"identity":"edeec359-8828-4cc6-b76e-1da6ee195084","order_by":5,"name":"Gabriel Musante","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Gabriel","middleName":"","lastName":"Musante","suffix":""}],"badges":[],"createdAt":"2025-12-29 22:25:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8476037/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8476037/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":100401575,"identity":"5323619d-df1d-4825-b024-434096620764","added_by":"auto","created_at":"2026-01-16 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1","display":"","copyAsset":false,"role":"figure","size":1133824,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version\u003c/p\u003e","description":"","filename":"Figure1.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8476037/v1/97b4dc60cfa124f5ccbf4bd8.jpg"},{"id":100401216,"identity":"a37cde2d-e6a1-42d3-a187-805ad1ee147f","added_by":"auto","created_at":"2026-01-16 11:58:46","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1303721,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version\u003c/p\u003e","description":"","filename":"Figure2.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8476037/v1/9b8626a3a51905432fbd2654.jpg"},{"id":104397596,"identity":"4597a416-cf6d-4c2d-aa39-8c70840e7a29","added_by":"auto","created_at":"2026-03-11 11:52:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3200328,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8476037/v1/d25e5d4e-0979-40ce-af99-46c1699b3209.pdf"},{"id":100401556,"identity":"6df7c0f4-bb7d-4213-95d3-735ea9f3c91a","added_by":"auto","created_at":"2026-01-16 11:59:04","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":573764,"visible":true,"origin":"","legend":"Supplemental Material","description":"","filename":"SupplementalMaterial.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8476037/v1/f280818f5d576be2aec41a1b.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.","formattedTitle":"Patent Ductus Arteriosus Management in Very Preterm Infants: Center-Level Treatment Strategies and Outcomes Across the Neocosur Network","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe management of patent ductus arteriosus (PDA) in very preterm infants (born\u0026thinsp;\u0026le;\u0026thinsp;28 weeks\u0026rsquo; gestation) has evolved significantly over recent years, shifting toward more conservative strategies, including a reduction in pharmacologic and surgical interventions \u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Several studies have examined the impact of these evolving practices on neonatal outcomes, yielding conflicting results \u003csup\u003e\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe pathophysiology of a significant left-to-right ductal shunt is well established and has been strongly associated with complications of prematurity, including bronchopulmonary dysplasia (BPD) and mortality\u003csup\u003e\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. However, evidence supporting clear long-term benefits of either medical or surgical PDA closure remains insufficient \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, and although both pharmacologic and surgical approaches have been linked to adverse outcomes in some studies, this association remains uncertain, with other reports suggesting no definitive causal relationship \u003csup\u003e\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAlthough first proposed more than a decade ago, the concept of an individualized, physiology-based approach to PDA management remains highly relevant today. This perspective challenges the assumption that less treatment universally leads to better outcomes, suggesting that timing and criteria for intervention are critical and that a one-size-fits-all strategy may not be appropriate. Consequently, a uniform strategy applied at the institutional level, whether aggressively intervening or minimally treating, may not adequately reflect patient-level physiologic needs \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe Neocosur Neonatal Network is a voluntary non-profit South American collaboration comprising 40 neonatal units across Argentina, Chile, Paraguay, Peru, and Uruguay. These University-affiliated centers represent a mix of public and private tertiary-care institutions. Since 2001, the network prospectively collects standardized data on morbidity, mortality, as well as antenatal and postnatal care practices in very low birth weight (VLBW) infants (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.neocosur.org\u003c/span\u003e\u003cspan address=\"http://www.neocosur.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite decades of research, no clear consensus exists on PDA management, and practices vary widely across neonatal intensive care units (NICUs), regions, and countries, particularly among very preterm infants. Whether this variation at the center level is associated with clinically meaningful differences in outcomes is still unclear. Therefore, our objective was to explore the center-level variation in PDA treatment rates across the Neocosur Network and evaluate whether the overall treatment attitude of a NICU, ranging from highly conservative to highly interventional, was associated with the combined outcome of BPD or death in very preterm infants.\u003c/p\u003e \u003cp\u003eMethods\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003eStudy Design\u003c/h2\u003e\u003cp\u003eThis was a retrospective, observational, multicenter cohort study using prospectively collected data from very preterm infants enrolled in the Neocosur Neonatal Network between 2015 and 2021. The Network includes university-affiliated public and private tertiary-care neonatal units across Argentina, Chile, Paraguay, Peru, and Uruguay, and maintains a harmonized database with standardized definitions and prospective data collection.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Population\u003c/h2\u003e \u003cp\u003eInfants were eligible for inclusion if they were born between 24\u0026thinsp;+\u0026thinsp;0 and 28\u0026thinsp;+\u0026thinsp;6 weeks of gestation and had a clinical and/or echocardiographic diagnosis of patent ductus arteriosus (PDA). We excluded infants with major congenital malformations, delivery room deaths, missing information for the primary outcome, and births at centers with fewer than 10 years of continuous network participation. This strategy ensured stable center-level estimates of treatment rates.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eExposure: Center-Level Treatment Attitude\u003c/h3\u003e\n\u003cp\u003ePDA treatment was defined as receipt of pharmacologic therapy (indomethacin, ibuprofen, or acetaminophen) and/or surgical ligation any time prior NICU discharge or death. No percutaneous closure procedures were performed during the enrollment time. For each center, the PDA treatment rate was calculated as the proportion of infants with PDA who received any treatment.\u003c/p\u003e \u003cp\u003e All obtained center treatment rate distribution were then separated into four exact quartiles of treatment rate, representing 4 intensity of treatment levels: very low treatment attitude, low treatment attitude, moderate treatment attitude and high treatment attitude. These quartiles reflect each NICU\u0026rsquo;s overall management tendency rather than individual clinical decisions.\u003c/p\u003e \u003cp\u003eTo examine whether PDA treatment practices changed over time, we evaluated temporal trends in center-level treatment rates. First, we fitted a mixed-effects logistic regression model with standardized year of birth as a fixed effect and center as a random intercept to assess the overall temporal trajectory of PDA treatment across the Network. Second, within-center temporal trends were assessed by fitting individual binomial models of annual treatment rate versus year for each NICU. These analyses identified a minority of centers with statistically significant slopes. Because of the small contribution of each center to the overall effect, all centers were retained in the primary analysis. Then a sensitivity analysis was conducted, repeating the primary analysis after excluding centers with significant temporal trends, to evaluate the robustness of the findings.\u003c/p\u003e\n\u003ch3\u003eOutcomes\u003c/h3\u003e\n\u003cp\u003eThe primary outcome was the composite of death or bronchopulmonary dysplasia (BPD), with BPD defined according to the 2018 NICHD criteria. Secondary outcomes included BPD alone and death before discharge.\u003c/p\u003e\n\u003ch3\u003eCovariates\u003c/h3\u003e\n\u003cp\u003eCandidate covariates were selected a priori based on biological plausibility and known determinants of illness severity and maturity: birthweight, small-for-gestational-age status according to Fenton charts, sex, multiple gestation, antenatal steroids, magnesium sulfate, chorioamnionitis, Apgar scores (1 and 5 minutes), and delivery room resuscitation intensity.\u003c/p\u003e \u003cp\u003eTo select the adjusting variables set a two-step classical confounding strategy was applied. First, bivariate comparisons across quartiles of treatment attitude (χ\u0026sup2;, ANOVA/Kruskal\u0026ndash;Wallis) were used to identify variables imbalanced across exposure levels. Variables showing imbalance or clinical relevance were entered into separate mixed-effects logistic models with treatment attitude as the dependent variable. A variable was considered a confounder if adjusting for it produced a\u0026thinsp;\u0026ge;\u0026thinsp;20% change in any treatment-attitude coefficient.\u003c/p\u003e \u003cp\u003eUsing this approach, gestational age was identified as the only covariate meeting confounding criteria. No other candidate variable changed the treatment-attitude coefficients meaningfully or improved model fit. Therefore, gestational age was included as the sole fixed-effect adjustment variable.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were summarized using means (SD) or medians (median absolute deviation). Categorical variables were described using counts and percentages.\u003c/p\u003e \u003cp\u003eTo evaluate the association between treatment attitude and outcomes, we initially fitted a bivariate mixed-effects logistic regression including treatment attitude as the fixed effect and center as a random intercept to capture clustering and baseline heterogeneity between NICUs. Then the adjusted mixed-effects logistic regression including treatment attitude, gestational age, and the center random intercept. And finally an exploratory interaction model to assess modification effect between treatment attitude and gestational age.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eModel Performance and Diagnostics\u003c/h2\u003e \u003cp\u003eCalibration was evaluated using calibration plots by deciles of predicted risk and by estimating the calibration intercept and slope. Because the objective was explanatory rather than predictive, discrimination was assessed only internally using the area under the ROC curve (AUC). Residual diagnostics and model assumptions were examined using simulated residuals and included normal distribution of the random effects, significant outliers and heteroscedasticity.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSample Size Calculations\u003c/h3\u003e\n\u003cp\u003eWe used all eligible cases from the Neocosur registry between 2015 and 2021; no formal a priori sample size calculation was performed. The final cohort included 2777 infants from 32 centers with \u0026gt;\u0026thinsp;1700 primary outcome events, yielding an events-per-variable ratio far above conventional recommendations for logistic mixed-effects models and an ICC of 0.08 for the primary outcome, supporting adequate power and model stability.\u003c/p\u003e\n\u003ch3\u003eData Analysis Software Specifications\u003c/h3\u003e\n\u003cp\u003eThe statistical analysis was performed on R software with RStudio environment \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Mixed Models were fit using the glmmTMB package, model assumptions were checked through simulated residuals with the DHARMA package, performance metrics were obtained using the pROC package while data processing and graphics were performed through ggplot2 package\u003csup\u003e\u003cspan additionalcitationids=\"CR18 CR19\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eEthical Considerations\u003c/h2\u003e \u003cp\u003e All participating centers had local institutional review board approval for data collection. Data were obtained in accordance with either a waiver of consent or written informed consent from parents or legal guardians, depending on local regulations. The Neocosur database is registered and approved by the Institutional Review Board of Universidad Austral, Buenos Aires, Argentina (CIE #15\u0026ndash;038).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStudy Population\u003c/h2\u003e \u003cp\u003eAfter applying inclusion and exclusion criteria, 2777 very preterm infants with PDA from 32 Neocosur centers were included (Fig.\u0026nbsp;1a). Treatment attitude quartiles showed wide variation in PDA treatment rates (Fig.\u0026nbsp;1b). We also found crude significant differences between quartiles in gestational age, multiple birth, IUGR, prenatal steroids, chorioamnionitis, magnesium sulfate, surfactant administration and delivery room CPAP, intermittent positive pressure ventilation and chest compressions defining potential confounders (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\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\u003eDemographic Characteristics and Treatment Attitudes cutoff points\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eTreatment Attitude Rate (Cutoff points)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuartile 1\u003c/p\u003e \u003cp\u003eVery Low\u003c/p\u003e \u003cp\u003e(\u0026le;\u0026thinsp;62.5%)\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;658\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQuartile 2\u003c/p\u003e \u003cp\u003eLow\u003c/p\u003e \u003cp\u003e(62.6\u0026ndash;83.6%)\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;492\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eQuartile 3\u003c/p\u003e \u003cp\u003eModerate\u003c/p\u003e \u003cp\u003e(83.7\u0026ndash;87.4%)\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;927\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQuartile 4\u003c/p\u003e \u003cp\u003eHigh\u003c/p\u003e \u003cp\u003e(\u0026ge;\u0026thinsp;87.5%)\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;700\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBW (gr)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e889 (229)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e907 (225)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e887 (223)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e906 (213)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGA (wk)**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (24\u0026ndash;28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (24\u0026ndash;28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (24\u0026ndash;28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27 (24\u0026ndash;28)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender (Male %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e358 (54.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e274 (55.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e518 (55.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e375 (53.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple Birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e481 (73.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e378 (76.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e716 (77.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e568 (81.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrenatal Steroids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e574 (87.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e426 (86.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e803 (86.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e511 (73.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChorioamnionitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e111 (16.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71 (14.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e163 (17.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82 (11.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMagnesium Sulfate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e338 (51.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e230 (46.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e460 (49.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e248 (35.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIUGR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e148 (22.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101 (20.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e136 (14.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e83 (11.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAGA (PC\u0026thinsp;\u0026ge;\u0026thinsp;10th )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e574 (87.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e446 (90.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e847 (91.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e636 (90.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSGA (PC\u0026thinsp;\u0026lt;\u0026thinsp;10th \u0026amp; \u0026ge; 3rd )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56 (8.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (6.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58 (6.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVSGA (PC\u0026thinsp;\u0026lt;\u0026thinsp;3rd )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (3.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16 (2.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApgar Score 1 minute**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (0\u0026ndash;10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (0\u0026ndash;9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (0\u0026ndash;10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 (0\u0026ndash;9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApgar Score 5 minutes**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (0\u0026ndash;10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (1\u0026ndash;10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (0\u0026ndash;10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8 (0\u0026ndash;9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCPAP in DR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e356 (54.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e355 (72.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e445 (48.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e308 (44.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIPPV in DR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e545 (82.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e426 (86.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e692 (74.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e499 (71.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChest Compressions in DR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63 (9.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (8.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e131 (14.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurfactant Administration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e562 (85.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e447 (90.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e814 (87.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e637 (91.0%)\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\u003eTable 1 Footnotes:\u003c/p\u003e\n\u003cp\u003e* \u0026nbsp;Mean (Standard Deviation)\u003c/p\u003e\n\u003cp\u003e** Median (Range)\u003c/p\u003e\n\u003cp\u003eBW: Birthweight, GA: Gestational Age, IUGR: Intrauterine Growth Restriction, AGA: Adequate for Gestational Age, SGA: Small for Gestational Age, VSGA: Very Small for Gestational Age, DR: Delivery Room, CPAP: Continuous Positive Airway Pressure, PPV: Intermittent Positive Pressure Ventilation\u003c/p\u003e\u003cp\u003eThe overall incidence of the primary outcome (death or BPD) was 61.9%, ranging from 28.1% to 87.8% across centers. Detailed center-level demographic characteristics and treatment rates are provided in Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003ePrimary Outcome\u003c/h2\u003e \u003cp\u003eIn crude comparisons, treatment attitude was associated with the composite outcome: the distribution of BPD or death differed significantly across quartiles (Pearson\u0026rsquo;s χ\u0026sup2; = 24.4, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). However, this association disappeared once center-level clustering was incorporated.\u003c/p\u003e \u003cp\u003eIn the unadjusted mixed-effects logistic model with treatment attitude as the only fixed effect and center as a random intercept, none of the treatment quartiles differed significantly from the very low treatment group (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Pairwise comparisons yielded odds ratios close to 1 with wide, overlapping confidence intervals (all Tukey-adjusted p-values\u0026thinsp;\u0026gt;\u0026thinsp;0.75).\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\u003eUnadjusted and Adjusted Mixed Logistic Regression for BPD or Death\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\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\u003eUnadjusted OR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdjusted OR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStandard Error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery Low Treatment Attitude (Q1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow Treatment Attitude (Q2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.54\u0026ndash;1.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.44\u0026ndash;1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.501\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate Treatment Attitude (Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.57\u0026ndash;1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.47\u0026ndash;1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.434\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh Treatment Attitude (Q4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.74\u0026ndash;2.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.70\u0026ndash;2.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.464\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGA (wk)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.50\u0026ndash;0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\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\u003eTable 2 Footnotes:\u003c/p\u003e\n\u003cp\u003eGA: Gestational Age, Q1-Q4: Quartile of Treatment Attitude from Very Low to High\u003c/p\u003e \u003cp\u003eThe intraclass correlation coefficient (ICC) was 0.08, indicating that approximately 8% of the variability in BPD or death was attributable to between-center differences rather than treatment attitude.\u003c/p\u003e \u003cp\u003eIn the gestational-age\u0026ndash;adjusted model, treatment attitude remained unassociated with the primary outcome, while gestational age showed a strong inverse association with BPD or death. Estimated effects for all treatment quartiles were close to the null and showed no consistent trend (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The model including an interaction term between treatment attitude and gestational age did not reveal statistically significant effect modification (all interaction p-values between 0.24\u0026ndash;0.94; Supplementary Table S2).\u003c/p\u003e \u003cp\u003eFigure 2a displays overlapped adjusted predicted probabilities for BPD or death by treatment attitude quartile. Figure\u0026nbsp;2b shows center-specific random intercepts, highlighting substantial baseline risk heterogeneity beyond treatment intensity.\u003c/p\u003e \u003cp\u003eAdditional details on assumptions, residual diagnostics and calibration are provided in the Supplementary File (Figures S2 and S3).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eTemporal Trends\u003c/h2\u003e \u003cp\u003eWe evaluated whether PDA treatment practices changed during the study period. In the overall mixed-effects model, year of birth showed a small but statistically significant positive association with treatment (β\u0026thinsp;=\u0026thinsp;0.166, SE 0.050, p\u0026thinsp;=\u0026thinsp;0.0009), indicating a modest increase in treatment over time.\u003c/p\u003e \u003cp\u003eWhen examining centers individually, 9 of 32 NICUs (28%) demonstrated significant temporal trends, whereas the remaining 23 maintained stable treatment patterns. The sensitivity analysis that excluded these centers showed no significant differences between treatment attitude quartiles after Tukey pairwise correction test. Full estimates are provided in Supplementary Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eSecondary Outcomes\u003c/h2\u003e \u003cp\u003eSecondary outcomes were consistent with the primary analysis. Neither death nor BPD, examined separately in gestational-age\u0026ndash;adjusted mixed-effects models, differed meaningfully across treatment attitude quartiles after accounting for center-level clustering. Full estimates are provided in Supplementary Table S3.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this multicenter cohort of 2777 very preterm infants across 32 NICUs within the Neocosur Network, we observed substantial variability in PDA treatment practices. However, after accounting for gestational age and center-level clustering, we found no association between center treatment attitude and the risk of BPD or death. This suggests that, independently of infants gestational age, treatment frequency at the institutional level, by itself, does not determine major clinical outcomes.\u003c/p\u003e \u003cp\u003eThese findings should be interpreted within the intrinsic heterogeneity of the Neocosur Network, where centers differ in resources, thresholds for intervention, clinical philosophies, and co-intervention patterns. Such diversity reflects real-world practice in Latin America and may contribute to the absence of an association between \u003cem\u003eaggregated treatment attitude\u003c/em\u003e and outcomes. Importantly, the lack of association at this highly aggregated level does not imply that individual PDA strategies are equivalent for specific infants. Rather, it highlights that PDA management is multifactorial, shaped by physiology, timing, and patient-specific vulnerability, factors that may be partially hidden when treatment practices are summarized into center-level categories.\u003c/p\u003e \u003cp\u003ePrior studies examining center-level or temporal variation in PDA management have reported heterogeneous findings. Isayama et al. described a U-shaped pattern in observed-to-expected treatment ratios across international networks \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, while Hagadorn et al. noted increased mortality among the most immature infants during periods of declining treatment \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Kaluarachchi et al. observed rising rates of moderate\u0026ndash;severe BPD despite lower treatment intensity in infants 26\u0026ndash;28 weeks\u0026rsquo; gestation \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e and Altit et al., in a comparative two-center study, reported that the adoption of a strict non-intervention policy resulted in worsening outcomes in extremely preterm infants (\u0026lt;\u0026thinsp;26 weeks' gestation) \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. These studies underscore ongoing uncertainty regarding the population-level consequences of shifting PDA practices and illustrate that center-level treatment intensity is influenced by multiple contextual and clinical factors.\u003c/p\u003e \u003cp\u003eOur results did not find significant differences in BPD, death, or the composite outcome across treatment attitude quartiles. Thus, although variability in PDA treatment was substantial, treatment frequency at center level did not predict major outcomes in our cohort.\u003c/p\u003e \u003cp\u003eInstead, our data aligns with emerging frameworks advocating for physiology-based decision-making. Approaches proposed by El-Khuffash, Weisz, and McNamara emphasize the identification of infants with clinically significant shunts and the use of tailored, timing-sensitive interventions rather than uniformly conservative or interventionist institutional policies \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. In this context, our observations reinforce the idea that the key question is not how often a NICU treats PDA, but which infants are selected for treatment and at what time.\u003c/p\u003e \u003cp\u003eVariations in clinical practice likely reflect the absence of a clear consensus and limitations in the current evidence base. Much of this uncertainty stems from shortcomings in existing and ongoing randomized controlled trials \u003csup\u003e\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. In a recent editorial, Clyman\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e provides a thoughtful critique of these studies, suggesting that many have struggled to identify the infants most likely to benefit from intervention, due to broad inclusion criteria and issues with timing. His perspective underscores the ongoing challenge of defining a truly high-risk subgroup for whom PDA closure may offer meaningful benefit and highlights the need for future research that better aligns treatment strategies with physiological vulnerability.\u003c/p\u003e \u003cp\u003eA key strength of our study is the restriction of the cohort to very preterm infants (\u0026le;\u0026thinsp;28 weeks\u0026rsquo; gestation), a population in which uncertainty regarding PDA management remains particularly high. In relatively mature preterm infants, spontaneous ductal closure occurs more frequently, and the potential benefits of treatment may not consistently outweigh its risks. In contrast, among very preterm infants, PDA management decisions are inherently more complex, and clinical equipoise regarding intervention persists \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Focusing on this population allowed us to examine center-level treatment variability precisely in the clinical context where the balance between conservative and interventional strategies is most clinically relevant.\u003c/p\u003e \u003cp\u003eFurther strengths include the large, multinational sample and the opportunity to capture real-world variation across NICUs serving diverse populations, including those from low- and middle-income settings. This diversity, often viewed as a challenge, may instead represent strength, offering insight into how PDA practices perform under a range of resource and organizational conditions. Finally, temporal analyses demonstrated modest network-wide variation and predominantly stable within-center treatment patterns, suggesting that secular trends were unlikely to account for our findings.\u003c/p\u003e \u003cp\u003eStill, limitations must be acknowledged. The retrospective design precludes complete adjustment for unmeasured confounding, including echocardiographic markers of PDA significance and timing of intervention. In addition, the number of extremely preterm infants (23\u0026ndash;25 weeks\u0026rsquo; gestation) was small, limiting subgroup-specific conclusions.\u003c/p\u003e \u003cp\u003eFinally, although center-level treatment rate is an informative descriptor of practice attitude, it is not a proxy for optimal care. Without physiological detail, we cannot establish whether the infants who received PDA closure, or those managed conservatively, were the ones most likely to benefit.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eMarked variability in PDA treatment across Neocosur centers reflects persistent uncertainty regarding optimal management. Despite this variability, we found no clear relationship between treatment intensity and major outcomes. These results reinforce the need to move beyond uniform policies and toward individualized, physiology-informed approaches that integrate gestational age, hemodynamics, and clinical context. Future work, ideally through well-designed randomized or stratified trials, will be essential to define which infants benefit most from PDA intervention.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflict of Interest\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing financial interests related to this study.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis study did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e \u003cp\u003eEthics approval and consent to participate\u003c/p\u003e \u003cp\u003eThis study involved the analysis of prospectively collected data from the Neocosur Neonatal Network. All participating centers obtained approval from their respective local institutional review boards for data collection. Data were collected in accordance with national regulations, with either written informed consent from parents or legal guardians or a waiver of consent, depending on local requirements. The Neocosur database is approved by the Institutional Review Board of Universidad Austral, Buenos Aires, Argentina (CIE #15\u0026ndash;038). The study was conducted in accordance with the Declaration of Helsinki.\u003c/p\u003e \u003cp\u003e Consent for Publication\u003c/p\u003e \u003cp\u003eNot applicable. This manuscript does not contain any individual person\u0026rsquo;s identifiable data.\u003c/p\u003e \u003cp\u003eAvailability of data and materials\u003c/p\u003e \u003cp\u003eData that supports the findings of this study is available from the Neocosur Neonatal Network, but restrictions apply to their availability as they contain sensitive patient-level information and are subject to institutional and ethical approvals. Data may be made available to qualified researchers upon reasonable request and with permission from the Neocosur Network.\u003c/p\u003e\u003ch2\u003eAuthor Contributions\u003c/h2\u003e \u003cp\u003eC.C.: Conceptualization, Methodology, Software, Formal analysis, Writing \u0026ndash; Original Draft, Writing \u0026ndash; Review \u0026amp; Editing.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003e The authors thank Dr. Luis Prudent for his generous and thoughtful review of the manuscript. We also acknowledge Dr. Ivonne D\u0026rsquo;Apremont and the Database Unit of the Neocosur Network for their work in managing and maintaining the registry, as well as the collaborators in each participating center (listed in the Supplementary Material) for their continuous dedication to data entry and follow-up.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLokku A, Mirea L, Lee S, Shah P. Trends and Outcomes of Patent Ductus Arteriosus Treatment in Very Preterm Infants in Canada. \u003cem\u003eAm J Perinatol\u003c/em\u003e. 2016;34(05):441\u0026ndash;450. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1055/s-0036-1593351\u003c/span\u003e\u003cspan address=\"10.1055/s-0036-1593351\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHagadorn JI, Brownell EA, Trzaski JM, et al. 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Published online May 27, 2025. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/jamapediatrics.2025.1022\u003c/span\u003e\u003cspan address=\"10.1001/jamapediatrics.2025.1022\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Klerk JCA, Engbers AGJ, van Beek F, et al. Spontaneous Closure of the Ductus Arteriosus in Preterm Infants: A Systematic Review. \u003cem\u003eFront Pediatr\u003c/em\u003e.\u003cem\u003eFrontiers Media S.A.\u003c/em\u003e 2020;8. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fped.2020.00541\u003c/span\u003e\u003cspan address=\"10.3389/fped.2020.00541\" 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":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8476037/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8476037/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo assess whether center-level variation in patent ductus arteriosus (PDA) treatment intensity is associated with bronchopulmonary dysplasia (BPD) or death in very preterm infants.\u003c/p\u003e\u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eRetrospective multicenter cohort study using prospectively collected data from the Neocosur Neonatal Network (2015\u0026ndash;2021). Infants born at \u0026le;\u0026thinsp;28 weeks\u0026rsquo; gestation with PDA were included. Centers were classified into quartiles according to PDA treatment rate. The primary outcome was BPD or death. Mixed-effects logistic regression models with a random intercept for center were fitted and adjusted for gestational age.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe cohort included 2,777 infants from 32 NICUs. PDA treatment rates varied widely across centers. After accounting for center-level clustering, treatment attitude was not associated with BPD or death. Gestational age showed a strong inverse association with the outcome. Approximately 8% of outcome variability was attributable to between-center differences.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eCenter-level PDA treatment intensity was not associated with major outcomes, supporting individualized, physiology-informed management.\u003c/p\u003e","manuscriptTitle":"Patent Ductus Arteriosus Management in Very Preterm Infants: Center-Level Treatment Strategies and Outcomes Across the Neocosur Network","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-16 09:02:36","doi":"10.21203/rs.3.rs-8476037/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d2419018-d04d-492b-aea5-f292f3b7d74d","owner":[],"postedDate":"January 16th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":60989696,"name":"Health sciences/Medical research/Epidemiology"},{"id":60989697,"name":"Health sciences/Health care/Paediatrics"}],"tags":[],"updatedAt":"2026-02-23T15:45:30+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-16 09:02:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8476037","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8476037","identity":"rs-8476037","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}