Predictive value of the combined application of multiple critical illness scoring systems in neonatal respiratory distress syndrome

Introduction

Premature birth comorbidities are the leading cause of death in children under 5 years old worldwide, accounting for approximately 16% of all deaths and 35% of neonatal deaths (1). As a severe complication in premature birth, neonatal respiratory distress syndrome (NRDS) typically refers to progressive respiratory distress, grunting, cyanosis, and three types of retraction symptoms including subcostal retractions, intercostal retractions, and suprasternal retractions, that develop hours after the birth of a premature infant (2). It has been reported that the incidence of NRDS is inversely related to gestational age (GA). Specifically, the incidence is 57% for GA of 30 to 31 weeks, 76% for 28 to 29 weeks, and as high as 92% for 24 to 25 weeks (3). In severe cases, respiratory failure occurs, significantly threatening the health and life of the neonate (4). Therefore, the early identification of the severity and mortality risk of NRDS in affected infants is considered crucial for the development of accurate and rational diagnostic and treatment plans, which in turn has significant implications for alleviating the socioeconomic burden. However, beyond the immediate life-threatening risks of NRDS, it is important to consider the long-term sequelae of the condition. Previous studies have suggested that factors such as GA, intrauterine growth restriction (IUGR), and chorioamnionitis may have a stronger association with long-term outcomes than the occurrence of NRDS itself. For instance, IUGR has been linked to an increased risk of neurodevelopmental delays, cognitive impairments, and pulmonary complications, while chorioamnionitis is associated with a higher risk of cerebral palsy and other developmental disorders. Although the presence of NRDS is critical for predicting short-term survival, these maternal and prenatal factors are increasingly recognized for their role in long-term health outcomes. In this study, we have focused on the impact of NRDS and its immediate effects on mortality and comorbidities in neonates. However, it should be noted that extremely preterm infants who do not develop NRDS were excluded from the study population. While this exclusion helps to focus on the population most affected by the syndrome, future studies may benefit from including this subgroup of infants to better understand the broader spectrum of outcomes in preterm infants who do not develop NRDS. Further research is needed to explore how the absence of NRDS in extremely preterm infants influences their long-term development, particularly in terms of pulmonary and neurodevelopmental sequelae.

Currently, the Score for Neonatal Acute Physiology-II (SNAP-II) and the Score for Neonatal Acute Physiology Perinatal Extension-II (SNAPPE-II) are widely utilized internationally to rapidly assess the medical condition of infants (5). These scoring systems demonstrate a strong capability in evaluating the clinical severity of conditions in the neonatal intensive care unit (NICU) and provide good predictive value for the risk of mortality among the affected infants (6). In China, the neonatal critical illness score (NCIS) is developed by referencing the advanced experiences of developed countries (7). After several years of clinical application, NCIS has become widely used in major hospitals across the country and is confirmed to be a simple and effective assessment tool.

Therefore, it is considered essential to explore the applicability and clinical value of different scoring systems in NRDS, as well as to examine the rationale behind the differentiation of clinical severity using these scoring systems. In this study, we aimed to compare the predictive roles of NCIS, SNAP-II, and SNAPPE-II in predicting comorbidities and mortality in NRDS infants. We present this article in accordance with the TRIPOD reporting checklist (available at https://tp.amegroups.com/article/view/10.21037/tp-2024-563/rc).

Methods

Subjects

This retrospective study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study has been approved by the ethics committee of the Children’s Hospital of Soochow University (No. 2021CS039), and all neonatal guardians signed informed consent forms. A total of 192 infants diagnosed with NRDS at NICU of the hospital between January 2019 and August 2020 were included. Based on discharge outcomes, they were divided into the survival and mortality groups. The survival group included infants who were discharged after recovery, those who were discharged on their guardians’ request following improvement, and those who continued treatment at external facilities or who were still alive at the time of telephone follow-up. Telephone follow-up was performed at 1 year after discharge. The death group included infants who died during hospitalization, as well as those whose conditions were critically severe or whose parents chose to discontinue treatment due to financial constraints, with death confirmed during telephone follow-up.

Diagnostic, inclusion, and exclusion criteria

Diagnostic criteria for NRDS are following the fifth edition of “Practical Neonatology”. (I) The presence of typical clinical manifestations of neonatal respiratory distress syndrome; (II) one or more risk factors, including prematurity, elective cesarean section, gestational diabetes, pregnancy-induced hypertension, premature rupture of membranes, intrauterine distress, neonatal asphyxia, or intrauterine infection; (III) chest imaging exhibits typical findings, such as decreased lung transparency, homogeneous ground-glass opacities, peripheral bronchial aeration, blurred cardiac and diaphragmatic borders, and in severe cases, a “white lung” appearance in both lung fields; and (IV) blood gas analysis indicates hypoxemia (i.e., arterial oxygen pressure <60 mmHg) and/or hypercapnia (i.e., carbon dioxide pressure >50 mmHg), suggesting respiratory failure. Inclusion criteria: (I) premature infants or term infants who met the diagnostic criteria for NRDS within 28 days of birth were diagnosed by two attending physicians of at least senior level. This timeframe was selected to ensure that all infants with NRDS, including those with more gradual or delayed onset, were included in the study. Given that NRDS typically manifests in the first few hours to days after birth, and diagnosis may require a few days of monitoring, chest imaging, and blood gas analysis, the inclusion of neonates up to 28 days post-birth ensures that cases with variable presentation are not excluded. Additionally, the 28-day period aligns with the widely accepted definition of the neonatal period in clinical research; (II) progressive respiratory distress occurred within 24 hours after birth, characterized by symptoms such as tachypnea (>60 breaths per minute), grunting, frothing, and nasal flaring. (III) Physical examination revealed signs of inspiratory retractions, and auscultation indicated decreased breath sounds in both lungs; (IV) imaging demonstrated a generalized reduction in lung transparency, with typical RDS findings including diffuse, homogeneous fine reticular opacities, ground-glass opacities, or signs of bronchial aeration. Exclusion criteria: (I) infants presented with concomitant conditions affecting respiratory function, including congenital developmental anomalies, meconium aspiration syndrome, transient tachypnea, severe infections, significant asphyxia, neuromuscular diseases, and thoracic deformities; (II) severe congenital heart disease; (III) suspected congenital genetic metabolic disorders; (IV) the duration of hospitalization with less than 24 hours; (V) incomplete clinical data.

For the management of NRDS, surfactant therapy was administered based on the clinical guidelines followed at NICU of the hospital. The surfactants used included both natural and synthetic forms, such as Survanta (beractant) and Curosurf (poractant alfa). The initial dose of surfactant ranged from 100 to 200 mg/kg, depending on the severity of the disease. Surfactant was administered via endotracheal intubation in most cases, using the INSURE (intubation-surfactant-extubation) technique or, when appropriate, the LISA (less invasive surfactant administration) technique. Repeat dosing was administered if the clinical condition of the neonate did not improve after the first dose, typically within 12–24 hours, depending on the response to treatment. The decision for repeat doses was based on clinical signs of worsening oxygenation or persistent lung collapse, and the dosing schedule adhered to the recommended guidelines for surfactant administration in neonates.

Collection of clinical data

General information was collected for each neonate, including gender, GA, delivery mode, birth weight, encompassing symptoms, vital signs, complete blood count, blood gas analysis, biochemical results, X-rays, electrocardiograms, and echocardiograms. All enrolled infants underwent assessments using the NCIS, SNAP-II, and SNAPPE-II scoring systems. Comorbidities were defined as the presence of one or more of the following conditions: bronchopulmonary dysplasia (BPD), patent ductus arteriosus (PDA), neonatal sepsis, intraventricular hemorrhage (IVH; grades III–IV), necrotizing enterocolitis (NEC; stages II–III), and retinopathy of prematurity (ROP).

NCIS

The NCIS scoring was conducted based on the most abnormal values of various indicators within the first 24 hours of neonatal admission, with total scores ranging from 40 to 100 (8). Since the NCIS includes 11 parameters, some of which may be influenced by postnatal care and clinical interventions, a 24-hour assessment period was chosen to minimize these influences and ensure a stable evaluation. A lower score indicates a more critical condition. Specifically, non-critical patients were defined as those with scores greater than 90, critical patients have scores between 70 and 90, and extremely critical patients score less than 70. The scoring criteria include 11 parameters: heart rate, respiratory rate, arterial oxygen pressure, systolic blood pressure, blood pH, serum sodium, serum potassium, hematocrit, blood urea nitrogen or creatinine, and gastrointestinal manifestations. Additionally, there are 10 individual indicators. If one or more of these criteria are met, the patient could be classified as critical: (I) recurrent apnea unresponsive to stimulation or requiring mechanical ventilation via endotracheal intubation; (II) severe arrhythmias; (III) disseminated intravascular coagulation; (IV) recurrent seizures unresponsive to treatment, persisting for more than 24 hours; (V) coma, with no response after five or more foot stimuli; (VI) body temperature ≤30 ℃ or ≥41 ℃; (VII) skin induration covering ≥70% of the body; (VIII) blood glucose <1.1 mmol/L; (IX) hyperbilirubinemia with indications for exchange transfusion; and (X) birth weight ≤1,000 g.

SNAP-II

SNAP-II was performed as previously described (9). SNAP-II is conducted based on the most abnormal values of various indicators within the first 12 hours of admission, with total scores ranging from 0 to 115. This timeframe was determined based on prior studies, which showed that assessing within 12 hours provides predictive accuracy comparable to that within 24 hours while reducing the impact of postnatal clinical interventions. Additionally, for neonates admitted beyond 24 hours, the predictive effectiveness of SNAP-II declines. A higher score indicates a more critical condition. The specific scoring criteria include six parameters: minimum body temperature, mean blood pressure, the ratio of arterial oxygen pressure to inspired oxygen concentration, minimum blood pH, urine output within 12 hours, and the presence of seizures.

SNAPPE-II

SNAPPE-II was performed as previously described (9). SNAPPE-II is conducted based on the most abnormal values of various indicators within the first 12 hours of admission, with total scores ranging from 0 to 162. Like SNAP-II, this timing was chosen based on previous studies indicating that mortality prediction accuracy remains high within this timeframe while minimizing variability introduced by clinical interventions after birth. A higher score indicates a more critical condition. The SNAPPE-II score builds upon the SNAP-II score by adding three perinatal parameters: birth weight, the 5-minute Apgar score (which includes five components: pulse, muscle tone, reflex response, skin color, and breathing), and small for GA status.

Statistical analysis

Statistical analysis was performed using SPSS version 25.0. Categorical data were expressed as frequencies (n) and percentages (%). Comparisons between the two groups and multiple groups were conducted using the χ² test. For data that did not meet the χ² test conditions, Fisher’s exact probability method was employed. Continuous data were first assessed for normality. For normally distributed data, means ± standard deviation (SD) was reported, and comparisons between the two groups were made using the Least Significant Difference-t test. For non-normally distributed data, medians (25th and 75th percentiles) were reported, with comparisons between the two groups conducted using the Mann-Whitney U test and comparisons among three groups using the Kruskal-Wallis H test. Receiver operating characteristic (ROC) curves were constructed, and comparisons were made based on the area under the curve (AUC) to analyze the predictive value of different scoring methods for the prognosis and comorbidities in NRDS infants. A P<0.05 was considered statistically significant.

Results

Comparison of general clinical data

There were 116 males (60.4%) and 76 females (39.6%). Among them, 118 were delivered via cesarean section (61.5%), while 74 were delivered vaginally (38.5%). The minimum birth weight was 600 g, and the maximum was 4,400 g, with a median birth weight of 1,680 g [interquartile range (IQR), 1,100–2,300 g]. The GA ranged from 25 weeks to 40⁺¹ weeks. Among the infants, 163 survived (84.9%), while 29 died (15.1%). There were no statistically significant differences in gender, GA, or delivery mode (P=0.15, 0.08, or 0.94); however, a significant difference in birth weight was observed between the two groups (P<0.001, Table 1).

The results of the three scoring systems for both groups

The NCIS scores were median 78 (IQR, 72–85) in the survival group and median 65 (IQR, 58–72) in the death group, and the scores of deceased infants were significantly lower than those of survivors (t =7.530, P<0.001). For the SNAP-II scores, the survival group had an average of 15.88±11.93, whereas the death group had an average of 29.38±18.76, indicating that the scores of deceased infants were significantly higher than those of survivors (t =−3.741, P=0.001). The SNAPPE-II scores showed an average of 20.02±16.25 in the survival group and an average of 38.55±23.69 in the death group, demonstrating that deceased infants had significantly higher scores than survivors (t =−4.048, P<0.001).

Predictive value of different scoring systems for the prognosis of NRDS

ROC curves were constructed for the three scoring systems, using 100 minus the NCIS, SNAP-II, and SNAPPE-II scores as variables and neonatal mortality as the positive variable. The ROC diagnostic analysis model was established. As shown in Table 2 and Figure 1, all scoring systems demonstrated good predictive efficacy for neonatal mortality in NRDS infants, with the NCIS score exhibiting the highest predictive effectiveness (P<0.001).

Figure 1 ROC curves for predicting mortality risk in children with NRDS using three scoring methods. NCIS, neonatal critical illness score; NRDS, neonatal respiratory distress syndrome; ROC, receiver operating characteristic; SNAP-II, Score for Neonatal Acute Physiology-II; SNAPPE-II, Score for Neonatal Acute Physiology with Perinatal Extension-II.

Predictive value of combined scoring systems for the prognosis of NRDS

The scores from the three scoring systems were combined in pairs and as a trio to establish an ROC diagnostic analysis model, using mortality as the positive variable. As shown in Table 3 and Figure 2, the combined scoring systems demonstrated an improved predictive efficacy to some extent. The combination of NCIS and SNAPPE-II scores yielded the highest predictive effectiveness (P<0.001).

Figure 2 ROC curve for predicting the risk of death in children with NRDS using a combination of three scoring methods. NCIS, neonatal critical illness score; NRDS, neonatal respiratory distress syndrome; ROC, receiver operating characteristic; SNAP-II, Score for Neonatal Acute Physiology-II; SNAPPE-II, Score for Neonatal Acute Physiology with Perinatal Extension-II.

Comparison of comorbidities with the three scoring systems

The 192 NRDS infants were grouped based on the presence of comorbidities. A total of 95 infants (49.5%) had no comorbidities, while 97 infants (50.5%) had comorbidities. NCIS, SNAP-II, and SNAPPE-II scores were used to assess comorbidities, indicating that infants with comorbidities had higher scores than those without (P=0.001, 0.009, or 0.002, Table 4).

Predictive value of different scoring systems for the occurrence of comorbidities in NRDS infants

Using the presence of comorbidities as the positive variable, a ROC diagnostic analysis model was established. The analysis revealed that all the three scoring systems were effective in predicting the risk of comorbidities in NRDS infants, demonstrating a significant clinical value (P=0.001, 0.004, or 0.001, Table 5 and Figure 3).

Figure 3 ROC curves for predicting the risk of comorbidities in NRDS infants using three scoring methods. NCIS, neonatal critical illness score; NRDS, neonatal respiratory distress syndrome; ROC, receiver operating characteristic; SNAP-II, Score for Neonatal Acute Physiology-II; SNAPPE-II, Score for Neonatal Acute Physiology with Perinatal Extension-II.

Discussion

NRDS remains a leading cause of neonatal mortality worldwide, particularly among preterm infants. Studies have shown that the incidence of NRDS is strongly correlated with GA, with nearly 92% of infants born at 24–25 weeks developing the condition, while the incidence declines to 57% at 30–31 weeks (10). Despite improvements in neonatal intensive care, mortality remains high, especially in infants with severe respiratory failure (11). In this study, we assessed the predictive value of NCIS, SNAP-II, and SNAPPE-II for mortality and comorbidities in NRDS infants. However, it should be noted that this study excluded infants who did not develop NRDS, limiting the ability to compare outcomes between NRDS and non-NRDS neonates. Future research should incorporate non-NRDS populations to better evaluate the overall prognostic significance of these scoring systems. These infants often present complex conditions and rapid deterioration, posing significant challenges for clinical management and exhibiting high mortality rates and considerable risks of lifelong disabilities. Therefore, the importance of assessing the severity of neonatal diseases and the associated mortality risk in the NICU has gained widespread recognition. While NRDS primarily affects preterm infants, its incidence in term neonates has been increasing. However, the clinical characteristics and complications of NRDS in term neonates differ from those in preterm neonates, which may impact the predictive performance of the applied scoring systems. Given that chronic lung disease, NEC, and IVH are more commonly associated with preterm neonates, separate analyses or adjustments may be required to refine the predictive accuracy for term neonates. Future studies should consider developing or modifying scoring systems specifically tailored for term infants with NRDS.

The NCIS score, developed by the Chinese Medical Association, provides a unified standard for identifying critically ill newborns in China. The neonatal acute physiology scoring systems, which include the SNAP-II and SNAPPE-II scores, represent internationally recognized standards. This study employed the NCIS, SNAP-II, and SNAPPE-II scores in combination to comprehensively assess and predict the risks of mortality and comorbidities in NRDS infants. The aim was to explore the applicability and clinical value of different scoring systems in NRDS, investigate the rationale for distinguishing clinical severity using these scoring systems, and evaluate the risks of mortality and subsequent comorbidities in NRDS infants.

The findings of this study confirm that GA is a critical determinant of NRDS incidence and outcomes (12). Consistent with prior research (13,14), we observed a higher prevalence of NRDS among extremely preterm infants, with an associated increase in mortality risk. Our results also demonstrate that lower NCIS, SNAP-II, and SNAPPE-II scores correlate with higher mortality rates, reinforcing their utility in clinical prognostication. However, given the differences in the pathophysiology of NRDS between preterm and term neonates, further stratified analyses are warranted to refine the applicability of these scoring systems across different GA groups.

Our study population consisted predominantly of low-birth-weight infants (<2,500 g), with a high proportion of cesarean deliveries, consistent with previous reports on NRDS risk factors (14). The data also revealed that term neonates with NRDS were more frequently delivered via elective cesarean section, which has been associated with impaired pulmonary transition at birth due to delayed catecholamine surge and fluid clearance (15). Notably, term infants in our cohort exhibited more severe clinical presentations, highlighting the need for further investigations into NRDS phenotypes in this population.

After conducting assessments of all infants in the NICUs of multiple medical centers, it was found that the NCIS score can accurately distinguish between critically ill and non-critically ill newborns (16,17). In this study, there were 10 non-critical cases (5.2%), 160 critical cases (83.3%), and 22 extremely critical cases (11.5%). The critical cases included infants meeting both score criteria and those meeting individual criteria. Statistical analysis revealed that when both criteria were met, the mortality rate of diagnosed infants was the highest at 19.2%. In contrast, when only one criterion was met, the mortality rate was lower, with a statistically significant difference observed. This indicates that the NCIS score accurately differentiates the severity of illness in infants. By incorporating individual criteria into the scoring system, the predictive capacity for mortality in critically ill infants is enhanced, aligning with the conclusions of studies by Chen, He, and Pei (18-20).

In this study, ROC curves were generated after separately assessing the NCIS, SNAP-II, and SNAPPE-II scores, as well as their combinations. It was found that all the three scoring systems demonstrated good predictive efficacy for the risk of mortality in NRDS infants, with the NCIS score exhibiting the highest predictive. The diagnostic efficacy was somewhat enhanced when the scores were combined, which aligns with the findings of Wu, who observed that the combined use of multiple scoring systems provided superior diagnostic accuracy for neonatal respiratory diseases compared to the use of individual scores (21). The combination of scoring systems was employed to assess whether integrating multiple parameters from different scoring models could enhance predictive accuracy. While each scoring system evaluates specific physiological aspects, their combined use may improve overall assessment by capturing a broader range of neonatal risk factors.

When predicting the risk of comorbidities in surviving infants, all three scoring systems showed predictive value, offering relatively effective assistance to clinicians in assessing patient conditions. This contrasts slightly with the research by Wang et al., who reported an AUC of 0.923 for the NCIS score in a study involving 297 hospitalized infants, suggesting a high accuracy for predicting mortality risk (17). It is important to consider that Wang et al.’s study included a broader range of clinical conditions and more diverse clinical data among all hospitalized infants. Additionally, research by Sotodate et al. demonstrated the predictive capabilities of SNAP-II and SNAPPE-II for short-term morbidity and mortality in extremely preterm infants (6). Both scores were identified as excellent indicators for predicting early mortality; however, the SNAPPE-II score showed superior predictive performance. In this study, after calculating the AUC values, it was found that the SNAPPE-II score outperformed the SNAP-II score. This difference may be attributed to the inclusion of several perinatal factors in the SNAPPE-II score, particularly the status of being a small GA infant. Previous research has indicated that IUGR is an independent risk factor for mortality in preterm infants, and these infants also face an increased risk of long-term morbidity (22). Although NCIS exhibited the highest AUC, combined scoring may be beneficial for neonates with variable clinical presentations, particularly those with borderline scores in individual assessments.

There are also some limitations in this study. First, the sample size is relatively small, which may limit the ability to generalize the findings to the broader population of infants with NRDS. Future research should aim to include a larger, more diverse sample of infants across multiple institutions to improve the external validity of the results. Second, the clinical data from a single hospital may introduce bias. Conducting multi-center prospective studies would help to overcome this limitation by reducing selection bias and increasing the robustness of the findings. Additionally, while the study focused on the prediction of mortality and comorbidities, it did not assess long-term outcomes or other potential confounding factors, such as the impact of different treatment protocols or socioeconomic status. Future research should include long-term follow-up data and consider the influence of these variables on outcomes. Lastly, although the study used three widely accepted scoring systems (NCIS, SNAP-II, and SNAPPE-II), the potential for improvements in these scoring systems, such as the inclusion of new biomarkers or technological advancements in monitoring, warrants exploration in future studies to enhance their predictive accuracy. Since this study did not include multivariate analysis, we cannot conclude that NRDS itself is an independent risk factor for mortality. Future studies should incorporate multivariate regression models to adjust for confounding factors such as GA, birth weight, and comorbidities. Moreover, due to the retrospective nature of the study, certain key comorbidities commonly associated with preterm infants, such as BPD, PDA, and IVH, were not consistently documented across all cases. As a result, we were unable to include these complications in our analysis, which may limit the comprehensive evaluation of NRDS-related outcomes. Future prospective studies should aim to collect detailed data on these complications to refine the predictive value of the applied scoring systems.

Conclusions

This study analyzes the general conditions of NRDS infants and reveals that the risk of developing NRDS is significantly lower in full-term infants compared to preterm infants. However, when full-term infants do develop NRDS, they often present with additional high-risk factors resulting in more critical conditions. Therefore, greater clinical attention should be directed toward this population of infants. By combining the three scoring systems for assessment, it is possible to preliminarily evaluate the severity and prognosis of NRDS in infants. This is particularly important in primary care hospitals, where diagnostic equipment and resuscitation techniques may be limited. Timely assessments can facilitate the rational allocation of limited medical resources.

Acknowledgments

Thanks for the financial support of 2022 Medical Research Project of Jiangsu Provincial Health Commission (No. M2022058).

Footnote

Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://tp.amegroups.com/article/view/10.21037/tp-2024-563/rc

Data Sharing Statement: Available at https://tp.amegroups.com/article/view/10.21037/tp-2024-563/dss

Peer Review File: Available at https://tp.amegroups.com/article/view/10.21037/tp-2024-563/prf

Funding: This study was supported by the 2022 Medical Research Project of Jiangsu Provincial Health Commission (No. M2022058).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-2024-563/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This retrospective study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study has been approved by the ethics committee of the Children’s Hospital of Soochow University (No. 2021CS039), and all neonatal guardians signed informed consent forms.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Islam JY, Keller RL, Aschner JL, et al. Understanding the Short- and Long-Term Respiratory Outcomes of Prematurity and Bronchopulmonary Dysplasia. Am J Respir Crit Care Med 2015;192:134-56. [Crossref] [PubMed]
2. Chen H, Tan Q, Lai S, et al. Association between glycated hemoglobin and the risk of neonatal respiratory distress syndrome in preterm premature rupture of membranes pregnancies. Sci Rep 2024;14:27122. [Crossref] [PubMed]
3. Lei Y, Qiu X, Zhou R. Construction and evaluation of neonatal respiratory failure risk prediction model for neonatal respiratory distress syndrome. BMC Pulm Med 2024;24:8. [Crossref] [PubMed]
4. Yang H, Gao LJ, Lei J, et al. Relationship between neonatal respiratory distress syndrome pulmonary ultrasonography and respiratory distress score, oxygenation index, and chest radiography grading. World J Clin Cases 2024;12:4154-65. [Crossref] [PubMed]
5. Radfar M, Hashemieh M, Fallahi M, et al. Utilization of SNAP II and SNAPPE II Scores for Predicting the Mortality Rate Among a Cohort of Iranian Newborns. Arch Iran Med 2018;21:153-7. [PubMed]
6. Sotodate G, Oyama K, Matsumoto A, et al. Predictive ability of neonatal illness severity scores for early death in extremely premature infants. J Matern Fetal Neonatal Med 2022;35:846-51. [Crossref] [PubMed]
7. Xu J, Chu X, Zhang W, et al. Analysis of risk factors for death in 59 cases of critically ill neonates receiving continuous renal replacement therapy: a two-centered retrospective study. Eur J Pediatr 2023;182:353-61. [Crossref] [PubMed]
8. The Pediatrics Group of the Emergency Medicine Branch of the Chinese Medical Association. the Emergency Medicine Group and the Neonatology Group of the Science Branch of the Chinese Medical Association Draft scoring method for neonatal critical cases. Chinese Journal of Pediatrics 2001;16:694-5.
9. Richardson DK, Corcoran JD, Escobar GJ, et al. SNAP-II and SNAPPE-II: Simplified newborn illness severity and mortality risk scores. J Pediatr 2001;138:92-100. [Crossref] [PubMed]
10. World Health Organization. Preterm birth 2018. Available online: http://www.who.int/mediacentre/factsheets/fs363/en/
11. Lawrence M, Wambach J. Fanaroff and Martin’s neonatal-perinatal medicine diseases of the fetus and infant. Philadelphia: Mosby Elsevier; 2015:1074-86.
12. Lima RO, Ribeiro AP, Juliano Y, et al. Survival prognosis of newborns from an intensive care unit through the SNAP-PE II risk score. Clinics (Sao Paulo) 2020;75:e1731. [Crossref] [PubMed]
13. Smolarova S, Kocvarova L, Matasova K, et al. Impact of updated European Consensus Guidelines on the management of neonatal respiratory distress syndrome on clinical outcome of preterm infants. Adv Exp Med Biol 2015;835:61-6. [Crossref] [PubMed]
14. Hu Y, Chen XX, Zhang M. Complications and outcome analysis of 105 cases of neonatal respiratory distress syndrome. World's Latest Medical Information Digest 2020;20:14-5.
15. Verlato G, Cogo PE, Balzani M, et al. Surfactant status in preterm neonates recovering from respiratory distress syndrome. Pediatrics 2008;122:102-8. [Crossref] [PubMed]
16. Liu CD, Wang K, Wang XR, et al. The Application of Critical Neonatal Scoring in the Construction of Neonatal Transport Networks in Plateau Areas. Journal of Plateau Medicine 2015;25:46-8.
17. Wang ZS, Liu YL, Shi XY, et al. The Application of Different Scoring Systems in Predicting Mortality Risk in Critically Ill Newborns. Chinese Journal of Neonatology 2016;31:189-92.
18. Chen CY, Huang WM, Qian XH, et al. A comparative analysis of neonatal critical illness score and score for neonatal acute physiology, perinatal extension, version II. Zhongguo Dang Dai Er Ke Za Zhi 2017;19:342-5. [PubMed]
19. He L, Xia B, Hu CY, et al. Clinical Application of Scoring Methods for Critically Ill Newborns. Chinese Journal of Maternal and Child Health 2017;13:162-8. (Electronic Edition).
20. Pei GY, Jiang CQ. Accuracy and Clinical Value of Different Scoring Systems in Predicting the Risk of Mortality in Critically Ill Newborns. Journal of Wuhan University 2020;41:476-80. (Medical Edition).
21. Wu J, Han YM, Zhang JL, et al. Predictive Value of Critical Scoring for Respiratory Diseases in Near-Term and Term Newborns on the First Day of Life. Journal of Clinical Pediatrics 2019;37:345-50.
22. Eleftheriades M, Creatsas G, Nicolaides K. Fetal growth restriction and postnatal development. Ann N Y Acad Sci 2006;1092:319-30. [Crossref] [PubMed]