Association of monocyte to lymphocyte ratio with length of stay in intensive care unit in neonatal apnea modified by treatment

Introduction

Apnea is a common respiratory condition in newborns, defined as a cessation of breathing for more than 15-20 seconds, usually accompanied by bradycardia and cyanosis (1). This condition primarily affects newborns with gestational age less than 34 weeks (2). The successful transition of a newborn from the womb to the outside world relies critically on effective lung ventilation, which requires the clearance of lung fluid, the production of normal surfactant, and adaptive changes in cardiovascular resistance (3). Apnea is closely associated with the immaturity of the central nervous system and respiratory instability (4). Apnea in premature infants is a major concern for neonatal caregivers in the intensive care unit (ICU), as it can impede cerebral blood flow, leading to ischemia (5). In addition, apnea may prolong the length of stay (LOS) in the ICU for neonates (6). Long hospitalization may lead to congestion in the ICU during epidemics and a high cost of care (7). Therefore, it is important to reduce the LOS in the ICU of neonates with apnea.

Inflammation and infection may induce apneic episodes in neonates (3). Spagnoli et al. highlighted that systemic inflammation and infections in neonates contribute to white matter damage, a key feature in neonatal neurological injury (8). The brainstem, which houses critical respiratory centers, plays a pivotal role in generating and coordinating the biomechanics of respiration (9). In models of systemic inflammation induced by lipopolysaccharide (LPS) in neonatal animals, alterations in respiratory activity have been observed, with cytokines in the brainstem modulating the function of neurons involved in respiratory control (10). These findings underscore the importance of understanding the mechanisms through which inflammation influences neonatal respiratory function and neurological outcomes.

A recent study indicated that monocytes and lymphocytes may be potential predictive factors for neonatal apnea (11). Monocytes are important circulating leukocytes in the innate immune system that play roles in immune defense, inflammation, and tissue remodeling (12). Lymphocytes are immune regulatory cells that primarily function in specific immunity (13). Blood parameters monocyte to lymphocyte ratio (MLR), established based on these two immune cells, can provide more comprehensive information than a single immune cell (14,15). The MLR can be easily calculated from routine blood tests and is an inexpensive and reliable marker of inflammation (16). It is a predictive factor for various diseases. For example, MLR predicts the length of hospitalization in patients with myocarditis (17). Qiu et al. found that ICU stays in type 2 diabetic chronic kidney disease patients with high levels of MLR were significantly higher than in the group with low levels of MLR (18). Given the role of systemic inflammation in neonatal apnea and the emerging evidence linking MLR to clinical outcomes, we hypothesize that MLR may also serve as a useful predictor of ICU LOS in neonates with apnea.

To our knowledge, the role of MLR in neonatal apnea has not been studied to date. Therefore, this study explored the potential association between MLR and the LOS in the ICU for neonatal apnea based on common databases, aiming to provide evidence-based medical support for the prognostic value of MLR in neonatal apnea. We present this article in accordance with the TRIPOD reporting checklist (available at https://tp.amegroups.com/article/view/10.21037/tp-2025-21/rc).

Methods

Study population

The data for this study were sourced from the Medical Information Mart for Intensive Care III (MIMIC III) database (https://mimic.mit.edu/), which includes information on 7,870 neonates. MIMIC III is a freely accessible database that contains ICU admission records from Beth Israel Deaconess Medical Center in Boston, Massachusetts, covering the years 2001 to 2008 (19). Due to the anonymity of the information in the database, individual patient consent was not required. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Neonatal apnea is defined as either ≥15 seconds of apnea or ≤20 seconds of apnea accompanied by bradycardia (<100 bpm), cyanosis, pallor, and/or significant hypotension (11), as defined by the International Classification of Diseases (ICD-9 and ICD-10). Based on this definition, out of the 7,870 neonates in MIMIC III, 1,164 were classified as having neonatal apnea. After excluding patients with an LOS in the ICU of less than 1 day and those with missing MLR data (either monocyte or lymphocyte counts), the final cohort included 1,120 patients. The flowchart of the population included is shown in Figure 1.

Figure 1 Flowchart of inclusion and exclusion criteria. ICU, intensive care unit; LOS, length of stay; MIMIC III, Medical Information Mart for Intensive Care III; MLR, monocyte to lymphocyte ratio.

Variable extraction

Data in this study was extracted from the MIMIC III database using structured query language and included demographic information such as age, height, birth weight, gender, gestational age, and race. Additional data encompassed comorbidities—acute kidney injury (AKI), jaundice, acidosis, anemia, pneumonia, intraventricular hemorrhage (IVH), congenital malformation, sepsis, treatments—caffeine, acetaminophen, vancomycin, dopamine, mechanical ventilation, and laboratory parameters—hematocrit, lymphocytes, neutrophils, basophils, eosinophils, monocytes, red blood cell (RBC), red blood cell distribution width (RDW), pH, partial pressure of oxygen (pO₂), partial pressure of carbon dioxide (pCO₂), total CO₂, urine output, platelet, white blood cell (WBC), anion gap, hemoglobin, base excess, bilirubin, LOS in the hospital, LOS in the ICU. All initial laboratory parameters were taken as the first measurement post-birth. To minimize potential bias, parameters with missing values greater than 30% were excluded. For variables with missing values less than 30%, the “missForest” package in R Studio was used for imputation.

Outcomes

The primary outcome of this study was LOS in the ICU, and the secondary outcome was LOS in the hospital.

Statistical analysis

Based on the median value of the baseline MLR level, the entire study population was divided into high MLR and low MLR groups. Continuous variables with a skewed distribution were reported as median (interquartile range), and comparisons between the two groups were made using the Mann-Whitney U test. Categorical variables were represented as counts (percentages), and differences between groups were assessed using the chi-squared test. Collinearity analysis was conducted to exclude variables with a variance inflation factor (VIF) greater than 2 to reduce multicollinearity (20). Generalized additive models (GAM) constructed by statsmodels 0.14.0 and pygam 0.8.0 were utilized to explore the nonlinear relationship between MLR and LOS in the ICU. In three different generalized linear models (GLMs), the relationships between MLR levels/MLR group by median value/MLR quartiles and LOS in the ICU/hospital were further examined. Model 1 was unadjusted; Model 2 adjusted for laboratory parameters; and Model 3 further adjusted for gestational age, comorbidities such as anemia, acidosis, and pneumonia, and treatments including caffeine, vancomycin, acetaminophen, and dopamine. Additionally, GLM analyses were conducted to investigate the association between MLR and LOS in the ICU across different comorbidity and treatment subgroups. Finally, mediation analysis was performed using pingouin 0.3.12 in Python to evaluate the mediating effect of MLR between caffeine/mechanical ventilation and LOS in the ICU. Furthermore, latent class trajectory modeling (LCTM) was employed to assess the trajectory changes of MLR at five different time points (the first measurement post-birth and four subsequent measurements). The Bayesian information criterion (BIC) and class scale were used to fit the models and determine the best-fitting model. All statistical analyses in this study were performed through R 4.2.3, Python 3.9, and SPSS 22.0, and P<0.05 was considered statistically significant.

Results

Baseline characteristics of subjects

A total of 1,120 neonates with apnea were included in the analysis, with a lower birth weight in high MLR group. Based on the initial median MLR value, the entire cohort was divided into a low MLR group (n=545) and a high MLR group (n=575). The high MLR group had a significantly lower birth weight than the low MLR group (P<0.001). There were significant differences in gestational age among demographic characteristics; acidosis, anemia, pneumonia, IVH, and sepsis among comorbidities; and caffeine, acetaminophen, vancomycin, and dopamine among treatments between the high-MLR and low-MLR groups (all P<0.05). However, no significant differences were observed for other variables in these three categories (Table 1). Additionally, significant differences were observed in initial hematocrit, lymphocytes, neutrophils, eosinophils, monocytes, MLR, RBC, RDW, pH, pO₂, urine output, anion gap, hemoglobin, base excess, and bilirubin levels between low and high MLR group (all P<0.05). The high-MLR group had a significantly longer LOS in the hospital and LOS in the ICU compared to the low-MLR group (P<0.001). No significant differences were observed in other laboratory parameters between the two groups, as detailed in Table 2.

To eliminate potential confounding factors, a collinearity analysis was conducted on the 24 variables with P<0.05 from Tables 1,2. Besides, MLR was calculated by monocytes and lymphocytes, thus the two variables were also excluded to avoid collinearity. After excluding variables with a VIF greater than 2, 18 variables were included in the subsequent analysis, including gestational age; comorbidities such as anemia, sepsis, acidosis, IVH, and pneumonia; treatments including caffeine, vancomycin, acetaminophen, and dopamine; and laboratory indicators such as bilirubin, neutrophils, anion gap, urine output, pO₂, MLR, RDW, and eosinophils (Table 3).

Association of MLR with LOS in the ICU

Subsequently, a GAM analysis was conducted to further investigate the relationship between initial MLR and LOS in the ICU. Figure 2A shows that P for nonlinear <0.001, and after adjusting for variables with VIF <2, the P for nonlinear remained <0.001 (Figure 2B). This indicates a non-linear relationship between initial MLR and LOS in the ICU, leading to the use of GLM analysis in the subsequent analyses. In Model 3, which adjusted for all variables, MLR levels {β=5.576 [95% confidence interval (CI): 2.270, 8.881], P=0.001} and group by the median value of MLR [β=2.989 (95% CI: 0.801, 5.177), P=0.008] were both significantly positively associated with LOS in the ICU (Table 4). Similar statistical results were observed in Model 1, which was unadjusted, and in Model 2, which was adjusted only for laboratory parameters. Furthermore, when MLR was evaluated as quartiles, the P for the trend across all models was <0.01. These results indicate that as MLR levels increase, LOS in the ICU also significantly increases, and this association is consistently reflected across different models and classifications of MLR levels.

Figure 2 Nonlinear relationships between MLR and LOS in the ICU. (A) GAM analysis in the unadjusted model. (B) GAM analysis in the model adjusting variables with VIF ≤2. The blue line represents coefficient values, the top red line is the 95% confidence interval high, and the bottom red line is the 95% confidence interval low. GAM, generalized additive model; ICU, intensive care unit; LOS, length of stay; MLR, monocyte to lymphocyte ratio; VIF, variance inflation factor.

Subgroup analysis

To confirm the relationship between MLR and LOS in the ICU, subgroup analyses were performed based on different comorbidities (AKI, jaundice, acidosis, anemia, pneumonia, IVH, and sepsis) and treatments (caffeine, acetaminophen, vancomycin, dopamine, and mechanical ventilation). The results indicated that MLR was significantly associated with LOS in the ICU across all subgroups except those with IVH or receiving caffeine and mechanical ventilation (Table 5). In populations without IVH, MLR showed a significant association with LOS in ICU [β=42.346 (95% CI: 34.702, 49.990), P<0.001], but this positive association was not significant in populations with IVH. In the caffeine treatment group, MLR was significantly positively correlated with LOS in the ICU [β=19.406 (95% CI: 13.387, 25.425), P<0.001], whereas no significant correlation was found between MLR and LOS in the ICU in the non-caffeine treatment group. A similar trend was observed between the groups receiving and not receiving mechanical ventilation. This suggests that the correlation between MLR and LOS in the ICU may be influenced by IVH, caffeine, and mechanical ventilation. Therefore, we further explored the regulatory roles among IVH/caffeine/mechanical ventilation, MLR, and LOS in the ICU through mediation analysis. As shown in Figure 3A, the indirect effect of IVH and LOS in ICU through MLR showed statistical significance (P<0.05), revealing MLR as a mediator between IVH and LOS in ICU. Additionally, there was a significant direct association between caffeine and LOS in the ICU, and the indirect association between the two variables through MLR was also significant (Figure 3B). This indicates that MLR is a mediator between caffeine and LOS in the ICU. Similarly, MLR also serves as a mediator between mechanical ventilation and LOS in the ICU (P<0.001, Figure 3C).

Figure 3 Mediation analysis. (A) MLR was a mediator between IVH and LOS in the ICU. (B) MLR was a mediator between caffeine and LOS in the ICU. (C) MLR was a mediator between mechanical ventilation and LOS in the ICU. ICU, intensive care unit; IVH, intraventricular hemorrhage; LOS, length of stay; MLR, monocyte to lymphocyte ratio.

Association of MLR with LOS in the hospital

Additionally, we investigated the association between MLR and the secondary outcome, LOS in the hospital. In three different GLM models, MLR levels or the MLR group were consistently positively correlated with LOS in the hospital (Table 6). For patients with neonatal apnea, LOS in the hospital increased with rising MLR levels (P for trend <0.001). In models 1 and 2, compared to low MLR levels (Q1), MLR levels in the range of 0.145–7.500 (Q3 and Q4) were significantly positively correlated with LOS in the hospital. In model 3, compared to Q1, MLR levels in the range of 0.260–7.500 (Q4) were significantly positively correlated with LOS in the hospital [β=5.462 (95% CI: 2.297, 8.627), P=0.001].

LCTM analysis

The above analyses explored the correlation between baseline MLR levels and LOS in the ICU/hospital. To further investigate the correlation between the two variables, we obtained five measurements (the first measurement after birth and four subsequent measurements) of longitudinal trajectories for monocytes and lymphocytes, and the corresponding longitudinal trajectory changes of MLR were then calculated. LCTM analysis was performed, and the results are shown in Table 7. The class 2 to 5 groups did not meet the criterion of having a category size ≥2%, indicating that the trend in MLR trajectory changes was consistent across all populations. Therefore, we did not continue to investigate the correlation between trajectory changes in MLR and the outcomes.

Discussion

Apnea is a clinical manifestation of immature respiratory control, commonly seen in neonatal ICU (5). In various clinical settings, the inflammatory response indicated by the MLR has emerged as a potential biomarker. In this study, we analyzed 1,120 neonates with apnea, revealing a significant association between MLR and clinical outcomes. Our results indicate that higher MLR was associated with longer LOS in the ICU concerning comorbidities and treatment subgroups except those with caffeine and mechanical ventilation treatment.

Respiratory control is a complex process, with neurons located in the brainstem’s respiratory centers responsible for rhythm generation (21). Lower gestational age at birth is directly correlated with poor neurodevelopmental outcomes. Studies indicate that 7% of neonates born at 34–35 weeks gestation experience apnea, the incidence is 15% for those born at 32–33 weeks, 54% at 30–31 weeks, and nearly all neonates born at <28 weeks gestation exhibit apnea-related symptoms (21-23). Among the 1,120 neonates with apnea included in our study, 5.179% had a gestational age <28 weeks. Neonatal apnea may be associated with the immaturity of the respiratory control systems. The adaptation from the intrauterine to the extrauterine environment is a complex process, with oxygen deprivation being a significant issue (24,25). Neonates are exposed to rapidly changing oxygen tensions, which disrupt redox balance and immune signaling, leading to stress response changes that affect neurodevelopment and cardiopulmonary homeostasis (25). Our analysis showed significant differences in birth weight, gestational age, and several complications between high and low MLR groups. MLR, based on the levels of monocytes and lymphocytes, reflects the inflammatory status within the body. Neonates may suffer from hypoxic injury at birth or during the perinatal period, leading to the activation of inflammatory cells (26). The significant differences in laboratory parameters between high and low MLR groups in our study further emphasize the importance of considering MLR in the treatment of neonatal apnea.

The immature immune system is a key factor contributing to the increased susceptibility of neonates to diseases (27). MLR is a useful marker of systemic inflammation, with monocytes playing a crucial role in activating pro-inflammatory pathways. The pro-inflammatory cytokine TNF-α released by monocytes promotes the development of chronic inflammation-related diseases in preterm infants (28). Activated IL-17A⁺ lymphocytes are key drivers of inflammation in preterm infants (29). These immune cell-mediated processes may also have broader implications for neonatal neurodevelopmental outcomes. Spagnoli et al. confirmed that systemic inflammation in neonates is associated with white matter injury, increasing the risk of neurological sequelae, including symptomatic seizures in preterm infants (8). In preterm neonates, inflammation disrupts the integrity of the blood-brain barrier, promoting the activation of microglia and astrocytes, leading to neuroinflammation. This neuroinflammatory environment can impair the function of the brainstem, affecting respiratory control (3,30). A study has shown that blocking lymphocyte trafficking can prevent hypoxic brain injury induced by neonatal inflammation (31). Huang et al. noted that blood indicators are effective predictors of neonatal apnea, with significant nonlinear associations between monocytes and lymphocytes and the risk of apnea (11). Our results showed a nonlinear relationship between MLR and LOS in the ICU among neonates with apnea. In multiple GLM models, a clear positive correlation exists between MLR levels and clinical outcomes of neonates with apnea. As MLR levels increase, LOS in the ICU also significantly rises. This further indicated that the higher the MLR, the more severe the inflammatory response, correlating with poorer clinical outcomes for neonates with apnea. Neonates exhibit inherent and adaptive immune system deficiencies, leading to increased susceptibility to infections (32). Inflammatory responses related to neonates adversely impact brain development and contribute to neurodevelopmental disorders (33). An elevated MLR suggests an exacerbated inflammatory response in neonates, potentially leading to adverse neurodevelopment that further impacts respiratory function, resulting in worse outcomes for neonates with apnea.

Moreover, subgroup analyses provide valuable insights into how comorbidities and treatments influence the relationship between MLR and LOS in the ICU. Interestingly, while MLR is significantly associated with LOS in most subgroups, no significant correlation was observed in neonates with IVH and those who did not receive caffeine or mechanical ventilation for apnea. In preterm neonates, IVH is the most common form of germinal matrix hemorrhage. A study has shown that IVH is an independent risk factor for neonatal pulmonary hemorrhage (34). After IVH, the breakdown of RBC components, such as hemoglobin, along with plasma proteins, may trigger inflammation (35). We hypothesize that in non-IVH neonates, MLR, as an indicator of inflammation, may directly influence the severity of apnea, thereby correlating with LOS in ICU. However, in neonates with IVH, the neuroimmune dysregulation caused by IVH may complicate the overall immune response, making MLR changes less reflective of the immune system’s impact on the condition, and thus not significantly associated with ICU stay. Treatment is required when apnea episodes are recurrent, fail to resolve spontaneously, and are associated with bradycardia/hypoxemia (21). Mechanical ventilation, one treatment method, can improve ventilation and oxygenation (36). However, when a neonate’s spontaneous breathing conflicts with the mechanical breaths from the ventilator, it can lead to lung injury and inflammation (37,38). Just two hours of ventilation can increase pro-inflammatory cytokines and reduce anti-inflammatory cytokines in plasma (39). Caffeine, a first-line treatment for apnea in preterm infants, acts by antagonizing adenosine receptors in the central nervous system (40,41). Dayanim et al. found that caffeine treatment exacerbated hyperoxic lung injury in neonatal rats (42). Our mediation analysis shows that MLR mediates the relationship between IVH, caffeine, or mechanical ventilation treatment and LOS in the ICU. We hypothesize that the brain inflammation and neurodamage caused by IVH, along with the pulmonary inflammation and injury induced by caffeine and mechanical ventilation, may be key factors contributing to the prolonged ICU stay in neonates. These findings suggest that IVH, caffeine, and mechanical ventilation treatments may influence the association between MLR and ICU stay of neonates with apnea.

Our findings advocate incorporating MLR as a routine laboratory measurement for neonates with apnea. Considering the relationship between MLR and LOS in the ICU can guide clinicians in risk stratification and intervention. However, it is important to acknowledge several limitations of this study. Firstly, MLR was derived from clinical records, which may have measurement errors or inconsistencies. The retrospective design also limits the ability to control for all potential confounders, and some relevant variables may not have been captured, which could have influenced the observed associations. Secondly, due to the high diversity of gestational age categories in the original data, we only categorized gestational age at a 28-week cutoff and could not examine the relationship between different gestational ages and LOS in the ICU for apneic neonates. Thirdly, although this study highlights the association between MLR and LOS in the ICU, it does not establish a causal relationship. Lastly, the generalizability of these findings may be constrained by the specific patient population included in this study. Future research should address these limitations by utilizing prospective study designs, employing multiple time-point measures of MLR, and examining the potential confounding factors more comprehensively. A deeper understanding of the biological pathways involved in neonatal immunity and the role of MLR in clinical outcomes could lead to novel therapeutic strategies and improvements in the management of neonatal apnea.

Conclusions

In conclusion, our study demonstrated a significant association between MLR and LOS in the ICU among neonates with apnea, with higher MLR levels correlating with longer ICU stays. These results underscore the importance of MLR as a prognostic factor in neonatal apnea. By incorporating MLR into clinical practice, healthcare providers can enhance their ability to predict outcomes and optimize care for neonates, ultimately improving patient management and resource allocation in the neonatal ICU.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://tp.amegroups.com/article/view/10.21037/tp-2025-21/rc

Peer Review File: Available at https://tp.amegroups.com/article/view/10.21037/tp-2025-21/prf

Funding: None.

Conflicts of Interest: Both authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-2025-21/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. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

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. Martin RJ, Abu-Shaweesh JM, Baird TM. Apnoea of prematurity. Paediatr Respir Rev 2004;5 Suppl A:S377-82.
2. Dong LB, Li YF, Zhang Y, et al. A pilot study of limb stimulation for the treatment of neonatal apnea. Medicine (Baltimore) 2018;97:e12827. [Crossref] [PubMed]
3. Vitaliti G, Falsaperla R. Chorioamnionitis, Inflammation and Neonatal Apnea: Effects on Preterm Neonatal Brainstem and on Peripheral Airways: Chorioamnionitis and Neonatal Respiratory Functions. Children (Basel) 2021;8:917. [Crossref] [PubMed]
4. Lopes JM. Neonatal apnea. J Pediatr (Rio J) 2001;77:S97-103. [Crossref] [PubMed]
5. Shirwaikar RD, Acharya U D, Makkithaya K, et al. Optimizing neural networks for medical data sets: A case study on neonatal apnea prediction. Artif Intell Med 2019;98:59-76. [Crossref] [PubMed]
6. Merritt TA, Pillers D, Prows SL. Early NICU discharge of very low birth weight infants: a critical review and analysis. Semin Neonatol 2003;8:95-115. [Crossref] [PubMed]
7. Sharma D, Murki S. Making neonatal intensive care: cost effective. J Matern Fetal Neonatal Med 2021;34:2375-83. [Crossref] [PubMed]
8. Spagnoli C, Falsaperla R, Deolmi M, et al. Symptomatic seizures in preterm newborns: a review on clinical features and prognosis. Ital J Pediatr 2018;44:115. [Crossref] [PubMed]
9. Stojanovska V, Miller SL, Hooper SB, et al. The Consequences of Preterm Birth and Chorioamnionitis on Brainstem Respiratory Centers: Implications for Neurochemical Development and Altered Functions by Inflammation and Prostaglandins. Front Cell Neurosci 2018;12:26. [Crossref] [PubMed]
10. Nault S, Creuze V, Al-Omar S, et al. Cardiorespiratory Alterations in a Newborn Ovine Model of Systemic Inflammation Induced by Lipopolysaccharide Injection. Front Physiol 2020;11:585. [Crossref] [PubMed]
11. Huang H, Shi Y, Hong Y, et al. A nomogram for predicting neonatal apnea: a retrospective analysis based on the MIMIC database. Front Pediatr 2024;12:1357972. [Crossref] [PubMed]
12. Kratofil RM, Kubes P, Deniset JF. Monocyte Conversion During Inflammation and Injury. Arterioscler Thromb Vasc Biol 2017;37:35-42. [Crossref] [PubMed]
13. Fan Z, Lu X, Long H, et al. The association of hemocyte profile and obstructive sleep apnea. J Clin Lab Anal 2019;33:e22680. [Crossref] [PubMed]
14. Mayito J, Meya DB, Miriam A, et al. Monocyte to Lymphocyte ratio is highly specific in diagnosing latent tuberculosis and declines significantly following tuberculosis preventive therapy: A cross-sectional and nested prospective observational study. PLoS One 2023;18:e0291834. [Crossref] [PubMed]
15. Zhai M, Sun X, Wang J, et al. The Monocyte-to-Lymphocyte Ratio Was Associated With Intraplaque Neovascularization of the Carotid Artery on AngioPLUS. Brain Behav 2024;14:e70058. [Crossref] [PubMed]
16. Yang Y, Xu Y, Lu P, et al. The prognostic value of monocyte-to-lymphocyte ratio in peritoneal dialysis patients. Eur J Med Res 2023;28:152. [Crossref] [PubMed]
17. Mirna M, Schmutzler L, Topf A, et al. Neutrophil-to-lymphocyte ratio and monocyte-to-lymphocyte ratio predict length of hospital stay in myocarditis. Sci Rep 2021;11:18101. [Crossref] [PubMed]
18. Qiu C, Liu S, Li X, et al. Prognostic value of monocyte-to-lymphocyte ratio for 90-day all-cause mortality in type 2 diabetes mellitus patients with chronic kidney disease. Sci Rep 2023;13:13136. [Crossref] [PubMed]
19. Johnson AE, Pollard TJ, Shen L, et al. MIMIC-III, a freely accessible critical care database. Sci Data 2016;3:160035. [Crossref] [PubMed]
20. Perng PS, Hsu HJ, Lee JS, et al. Outcomes of surgery and subsequent therapy for central nervous system oligoprogression in EGFR-mutated NSCLC patients. World J Surg Oncol 2023;21:368. [Crossref] [PubMed]
21. Erickson G, Dobson NR, Hunt CE. Immature control of breathing and apnea of prematurity: the known and unknown. J Perinatol 2021;41:2111-23. [Crossref] [PubMed]
22. Zhao J, Gonzalez F, Mu D. Apnea of prematurity: from cause to treatment. Eur J Pediatr 2011;170:1097-105. [Crossref] [PubMed]
23. Henderson-Smart DJ. The effect of gestational age on the incidence and duration of recurrent apnoea in newborn babies. Aust Paediatr J 1981;17:273-6. [Crossref] [PubMed]
24. Swanson JR, Sinkin RA. Transition from fetus to newborn. Pediatr Clin North Am 2015;62:329-43. [Crossref] [PubMed]
25. McDonald FB, Dempsey EM, O'Halloran KD. The impact of preterm adversity on cardiorespiratory function. Exp Physiol 2020;105:17-43. [Crossref] [PubMed]
26. Okazaki K, Nakamura S, Koyano K, et al. Neonatal asphyxia as an inflammatory disease: Reactive oxygen species and cytokines. Front Pediatr 2023;11:1070743. [Crossref] [PubMed]
27. Chen J, Yasrebinia S, Ghaedi A, et al. Meta-analysis of the role of neutrophil to lymphocyte ratio in neonatal sepsis. BMC Infect Dis 2023;23:837. [Crossref] [PubMed]
28. Chavez-Valdez R, Ahlawat R, Wills-Karp M, et al. Mechanisms of modulation of cytokine release by human cord blood monocytes exposed to high concentrations of caffeine. Pediatr Res 2016;80:101-9. [Crossref] [PubMed]
29. Cui TX, Brady AE, Zhang YJ, et al. IL-17a-producing γδT cells and NKG2D signaling mediate bacterial endotoxin-induced neonatal lung injury: implications for bronchopulmonary dysplasia. Front Immunol 2023;14:1156842. [Crossref] [PubMed]
30. Nault S, Tremblay S, Imane R, et al. Cardiorespiratory alterations in a newborn ovine model of systemic viral inflammation. Pediatr Res 2022;92:1288-98. [Crossref] [PubMed]
31. Yang D, Sun YY, Bhaumik SK, et al. Blocking lymphocyte trafficking with FTY720 prevents inflammation-sensitized hypoxic-ischemic brain injury in newborns. J Neurosci 2014;34:16467-81. [Crossref] [PubMed]
32. Garofoli F, Civardi E, Pisoni C, et al. Anti-Inflammatory and Anti-Allergic Properties of Colostrum from Mothers of Full-Term and Preterm Babies: The Importance of Maternal Lactation in the First Days. Nutrients 2023;15:4249. [Crossref] [PubMed]
33. Sewell E, Roberts J, Mukhopadhyay S. Association of Infection in Neonates and Long-Term Neurodevelopmental Outcome. Clin Perinatol 2021;48:251-61. [Crossref] [PubMed]
34. Gezmu AM, Tefera E, Mochankana K, et al. Pulmonary hemorrhage and associated risk factors among newborns admitted to a tertiary level neonatal unit in Botswana. Front Pediatr 2023;11:1171223. [Crossref] [PubMed]
35. Holste KG, Xia F, Ye F, et al. Mechanisms of neuroinflammation in hydrocephalus after intraventricular hemorrhage: a review. Fluids Barriers CNS 2022;19:28. [Crossref] [PubMed]
36. Sangsari R, Saeedi M, Maddah M, et al. Weaning and extubation from neonatal mechanical ventilation: an evidenced-based review. BMC Pulm Med 2022;22:421. [Crossref] [PubMed]
37. Brown MK, DiBlasi RM. Mechanical ventilation of the premature neonate. Respir Care 2011;56:1298-311; discussion 1311-3. [Crossref] [PubMed]
38. Inocencio IM, Bischof RJ, Xiang SD, et al. Exacerbation of Ventilation-Induced Lung Injury and Inflammation in Preterm Lambs by High-Dose Nanoparticles. Sci Rep 2017;7:14704. [Crossref] [PubMed]
39. Cannavò L, Perrone S, Viola V, et al. Oxidative Stress and Respiratory Diseases in Preterm Newborns. Int J Mol Sci 2021;22:12504. [Crossref] [PubMed]
40. Alhersh E, Abushanab D, Al-Shaibi S, et al. Caffeine for the Treatment of Apnea in the Neonatal Intensive Care Unit: A Systematic Overview of Meta-Analyses. Paediatr Drugs 2020;22:399-408. [Crossref] [PubMed]
41. Shah AS, Leu RM, Shah SP, et al. Images: Caffeine therapy for central sleep apnea, hypoxemia, and hypoventilation in a term neonate. J Clin Sleep Med 2023;19:1005-8. [Crossref] [PubMed]
42. Dayanim S, Lopez B, Maisonet TM, et al. Caffeine induces alveolar apoptosis in the hyperoxia-exposed developing mouse lung. Pediatr Res 2014;75:395-402. [Crossref] [PubMed]