Longitudinal Immune and Hematologic Adaptations During Neonatal Transport: Differential Effects of Air and Ground Transfer and the Emerging Role of MCVL

1. Introduction

Neonatal transport is an essential component of regionalized perinatal care, enabling critically ill newborns to access specialized diagnostic and therapeutic resources available in Level III and Level IV neonatal intensive care units (NICUs) [1,2]. Although antenatal transfer remains the preferred strategy whenever feasible, postnatal transport continues to be required for a substantial proportion of neonates needing advanced respiratory support, surgical intervention, or highly specialized intensive care [1,2,3,4]. Over recent decades, improvements in neonatal retrieval systems, transport incubator technology, respiratory support, and monitoring capabilities have significantly enhanced transport safety and survival outcomes [4,5,6,7].

Despite these advances, neonatal transport remains a complex physiological event. During transfer, newborns may be exposed to multiple stressors, including handling, environmental noise, vibration, acceleration forces, temperature fluctuations, and changes in respiratory support [5,8,9,10,11]. Consequently, most studies evaluating transport quality have focused on physiological stability indicators such as body temperature, oxygen saturation, blood pressure, and cardiorespiratory status [5,8,9,10,11,12,13,14]. Hypothermia, hypoxemia, and hemodynamic deterioration remain among the most frequently reported transport-related complications and have been associated with adverse neonatal outcomes [4,12,13,14,15].

In addition to the general stressors associated with interfacility transfer, air transport introduces unique physiological and operational challenges that distinguish it from ground transport. As altitude increases, atmospheric pressure decreases, resulting in lower partial pressure of oxygen and relative hypobaric hypoxia, even within pressurized aircraft cabins [7,16]. In addition, gas expansion according to Boyle's law may affect pulmonary, gastrointestinal, and pleural air spaces, potentially influencing respiratory and hemodynamic stability [16]. Consequently, transported neonates may require adjustment of respiratory support parameters, including FiO₂, airway pressures, ventilation settings, and gas flow rates during flight [16]. Furthermore, differences between rotary-wing and fixed-wing aircraft influence vibration exposure, cabin environment, transport duration, and operational logistics, all of which may affect patient management and physiological adaptation during transfer [7,17]. These considerations frequently necessitate individualized modification of respiratory support, fluid administration, vasoactive therapy, and sedation strategies throughout transport [16,17,18].

Although these transport-specific physiological challenges are well recognized in neonatal retrieval medicine, their potential impact on systemic immune responses and hematologic adaptation has received comparatively little attention.

However, physiological stability represents only one aspect of the biological response to transport. Emerging evidence indicates that stressful clinical exposures can trigger complex neuroendocrine and immunological adaptations even in the absence of overt physiological deterioration [19,20]. Activation of the hypothalamic–pituitary–adrenal axis and sympathetic nervous system leads to the release of cortisol and catecholamines, which directly influence leukocyte trafficking, cytokine production, endothelial interactions, and innate immune activation [20,21]. These mechanisms are particularly relevant in neonates, whose immune systems remain functionally immature and undergo rapid postnatal adaptation [22,23,24].

Neonatal innate immunity differs substantially from that of older children and adults. Newborns exhibit developmental differences in neutrophil production, chemotaxis, endothelial adhesion, and inflammatory signaling, resulting in immune responses that may not follow classical adult patterns [22,23,24]. Recent studies have highlighted the importance of leukocyte-derived inflammatory indices, such as the neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI), as accessible biomarkers reflecting immune activation and systemic stress across a variety of neonatal and pediatric conditions [25,26,27]. Nevertheless, the longitudinal behavior of these biomarkers during neonatal transport has received little attention.

Furthermore, novel composite hematologic indices may provide additional insight into transport-related biological adaptation. Among these, the mean corpuscular volume-to-lymphocyte ratio (MCVL) has recently emerged as a promising marker associated with inflammatory processes, oxidative stress, and prognostic pathways across several clinical settings, including inflammatory bowel disease, colorectal cancer, and pediatric inflammatory conditions [28,29,30,31]. Whether MCVL can capture transport-related immune adaptations in critically ill neonates remains unknown.

Therefore, the aim of the present study was to investigate longitudinal changes in physiological stability markers, hematologic parameters, and inflammatory indices during neonatal transport to Level III/IV centers. In addition, we sought to determine whether transport modality (air versus ground transport) influences the trajectory of these responses and to evaluate the potential role of MCVL as a novel biomarker of transport-related immune adaptation.

2. Materials and Methods

2.1. Study Design and Participants

This prospective observational study was conducted between January 2023 and December 2025 and included neonates requiring interfacility transfer to tertiary or quaternary neonatal intensive care units (NICUs). The primary objective was to evaluate longitudinal changes in physiological stability markers, hematologic parameters, and inflammatory indices during neonatal transport and to investigate the influence of transport modality on these responses.

A total of 161 consecutive neonates were enrolled during the study period. Newborns were transferred from maternity hospitals and neonatal units located within Dolj County and neighboring counties to one of three referral centers: the Neonatology Department of the Emergency County Clinical Hospital Craiova, the Neonatology Department of the Municipal Clinical Hospital Filantropia Craiova, or the Neonatology Department of the Pius Brînzeu County Emergency Clinical Hospital.

The study was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of the University of Medicine and Pharmacy of Craiova (approval no. 247/27 October 2023). Written informed consent was obtained from the parents or legal guardians of all enrolled neonates.

Neonates were transported either by specialized neonatal ground transport teams or by dedicated neonatal air transport services, depending on transport distance, clinical urgency, weather conditions, and resource availability.

Clinical, physiological, and laboratory data were collected at three predefined time points:

• T0 – immediately before transport initiation at the referring hospital;
• T1 – immediately after completion of transport and admission to the receiving Level III/IV center;
• T2 – 12 hours after admission to the receiving neonatal ICU.

At each evaluation point, physiological stability parameters, including heart rate (HR), peripheral oxygen saturation (SpO₂), and body temperature, were recorded.

Peripheral venous blood collected in EDTA Vacutainer tubes (Becton Dickinson Vacutainer, Franklin Lakes, NJ, USA) was used to perform a complete blood count (CBC). Using flow cytometry principles, we developed an extended leukocyte differential by analyzing five parameters on the automatic hematology analyzer (Alinity, Abbott, Abbott Park, IL, USA). This method enabled us to accurately identify and characterize various hematological markers: hemoglobin (Hb), white blood cells/leukocytes (WBC), neutrophils (NEU), lymphocytes (LYM), monocytes (MON), platelets (PLT), and hematocrit (Ht). The inflammation indices derived from the blood cell count, NLR, MLR, PLR, AISI, SII, SIRI, and MCVL were calculated based on these findings:

• NLR = neutrophil-to-lymphocyte ratio;
• MLR = monocyte-to-lymphocyte ratio;
• PLR = platelet-to-lymphocyte ratio;
• AISI = (neutrophils × monocytes × platelets)/lymphocytes;
• SII = (neutrophils × platelets)/lymphocytes;
• SIRI = (neutrophils × monocytes)/lymphocytes;
• MCVL = mean corpuscular volume to lymphocyte ratio [28,29,30,31,32,33].

2.2. Patient Selection

Inclusion Criteria

Neonates were eligible for inclusion if they fulfilled all of the following criteria:

• Age ≤28 days at the time of transport;
• Requirement for interfacility transfer to a Level III or Level IV NICU;
• Transfer performed by a specialized neonatal ground or air transport service;
• Availability of CBC measurements at all three predefined study time points (T0, T1, and T2);
• Availability of physiological stability measurements (HR, SpO₂, and body temperature) at all three study time points;
• Availability of complete transport documentation, including transport modality and transport duration.

Exclusion Criteria

Neonates were excluded if any of the following conditions were present:

• Major congenital malformations or chromosomal abnormalities likely to independently influence hematologic or immune parameters;
• Known primary immunodeficiency disorders;
• Congenital hematologic diseases, including severe hemolytic disorders or congenital bone marrow abnormalities;
• Exchange transfusion or massive blood transfusion prior to transport;
• Suspected or confirmed congenital metabolic disorders associated with significant hematologic abnormalities;
• Missing laboratory measurements at any of the three predefined study time points;
• Incomplete transport or clinical documentation;
• Lack of parental or legal guardian consent.

2.3. Statistical Analysis

Statistical analyses were performed using GraphPad Prism version 11.0.2 (92) (LLC, San Diego, CA, USA). Data distribution was assessed using the Shapiro–Wilk test. Normally distributed continuous variables are presented as mean ± standard deviation (SD), whereas non-normally distributed variables are reported as median and interquartile range [IQR]. Categorical variables are expressed as absolute numbers and percentages.

Baseline characteristics between air- and ground-transported neonates were compared using the independent-samples t-test or Mann–Whitney U test, as appropriate. Categorical variables were analyzed using the chi-square test or Fisher’s exact test when expected cell counts were less than five.

Longitudinal changes across transport time points (T0, T1, and T2) were evaluated separately for the overall cohort and for each transport modality. Repeated-measures analysis of variance (ANOVA) was used for normally distributed variables, whereas Friedman tests were applied to non-normally distributed variables. These analyses were used to assess the overall within-subject effect of time on physiological stability parameters, hematologic variables, and inflammatory indices.

To investigate whether temporal trajectories differed according to transport modality, linear mixed-effects models were subsequently applied. Time (T0, T1, and T2) was modeled as a within-subject fixed effect, transport modality (air vs. ground) as a between-subject fixed effect, and the Time × Transport interaction term was included to assess differential longitudinal responses between transport groups. A random intercept for each neonate was incorporated to account for repeated measurements and inter-individual variability.

Mixed-effects analyses were performed for physiological stability markers (heart rate, oxygen saturation, and body temperature), hematologic variables (hemoglobin, red blood cell count, mean corpuscular volume, platelet count, mean platelet volume, total leukocyte count, neutrophils, lymphocytes, and monocytes), and inflammatory indices (NLR, MLR, PLR, SII, SIRI, and MCVL). The significance of the main effect of time, the main effect of transport modality, and the Time × Transport interaction was evaluated for each parameter.

To determine whether transport-related immune adaptations remained independent of potential confounding factors, additional adjusted mixed-effects models were constructed for selected immune markers that showed significant Time × Transport interactions. Two complementary models were developed. Model A was adjusted for transport duration and sedation during transport, and was selected a priori based on its clinical relevance and unequal distribution between transport groups. Model B represented a sensitivity analysis that additionally incorporated mean oxygen saturation (SpO₂) during transport as a surrogate marker of physiological stability.

Because heart rate, oxygen saturation, and body temperature represent overlapping physiological domains and exhibit substantial collinearity, only mean SpO₂ was retained in the final sensitivity model. Model estimation was performed using maximum likelihood methods. Mixed-effects modeling was selected because of its robustness to unequal group sizes, repeated measurements, occasional missing observations, and violations of sphericity, which are common in neonatal transport studies.

All statistical tests were two-tailed, and a p-value < 0.05 was considered statistically significant.

3. Results

3.1. Baseline Characteristics of Transported Neonates

A total of 161 neonates were included in the study, of whom 40 underwent air transport and 121 underwent ground transport (Table 1). No significant differences were observed between transport groups regarding gestational age or birth weight. Median gestational age was 34.30 weeks [32.30–36.50] in the air transport group and 34.00 weeks [32.00–36.30] in the ground transport group (p = 0.787), while median birth weight was 1785.00 g [1200.00–2500.00] and 1870.00 g [1340.00–2490.00], respectively (p = 0.339). Similarly, sex distribution was comparable between groups, although a higher proportion of males was observed among air-transported neonates (67.5% vs. 48.8%); this difference did not reach statistical significance (p = 0.061).

In contrast, several clinically relevant differences were identified between transport modalities. Sedation during transport was significantly more frequent in the air transport group (30/40, 75.0%) compared with the ground transport group (51/121, 42.1%; p < 0.001). Marked differences were also observed in the distribution of primary diagnoses. Prematurity was substantially more common among ground-transported neonates (102/121 vs. 10/40; p < 0.001), whereas respiratory distress syndrome (RDS) predominated in the air transport group (30/40 vs. 19/121; p < 0.001).

Transport duration differed significantly between groups, with air transport being associated with a markedly shorter transfer interval (45.0 min [30.0–50.0]) compared with ground transport (120.0 min [107.5–150.0]; p < 0.001). Furthermore, the need for mechanical ventilation was significantly higher among air-transported neonates (29/40, 72.5%) than among ground-transported neonates (51/121, 42.1%; p = 0.002). Conversely, spontaneous breathing was more frequently observed in the ground transport group (70/121, 57.9%) than in the air transport group (11/40, 27.5%; p = 0.002).

Overall, these findings indicate that although the two groups were comparable with respect to major demographic and perinatal characteristics, air-transported neonates represented a clinically more severe subgroup, characterized by a higher prevalence of respiratory distress syndrome, increased need for sedation and mechanical ventilation, and substantially shorter transfer times. These baseline differences support the use of adjusted mixed-effects models in subsequent analyses to account for potential confounding related to disease severity and transport-related interventions.

3.2. Physiological Stability Parameters and Hematologic Dynamics Across Transport Time Points

3.2.1. Global Changes (Entire Cohort)

The longitudinal assessment of physiological stability parameters, hematologic variables, and inflammatory indices revealed substantial changes across the three transport time points (Table 2). Despite the clinical complexity of the study population, physiological parameters remained remarkably stable throughout transport. HR, SpO₂, and body temperature did not exhibit significant temporal variation (p = 0.754, p = 0.964, and p = 0.693, respectively), indicating that transport was performed under generally adequate physiological control and that no major hemodynamic, respiratory, or thermal deterioration occurred during transfer (Table 2).

In contrast, several hematologic parameters demonstrated significant dynamic changes over time. Hemoglobin concentration and RBC count progressively decreased from T0 to T2 (p < 0.001 for both), accompanied by a gradual reduction in MCV values (p < 0.001). These findings likely reflect a combination of hemodilution, repeated blood sampling, and physiological adaptation during transport and early stabilization after admission. Mean platelet volume (MPV) increased progressively across the three time points (p < 0.001), while platelet counts showed a marked rise from baseline to post-transport measurements (p < 0.001), suggesting activation of platelet production and mobilization during the transport period.

Leukocyte dynamics exhibited a distinct temporal pattern. Total leukocyte and neutrophil counts decreased substantially between T0 and T1, followed by partial stabilization at T2 (p < 0.001 for both). In contrast, lymphocyte counts increased progressively throughout transport (p < 0.001), whereas monocyte counts remained relatively stable, showing no significant temporal variation (p = 0.131). This divergent behavior of leukocyte subpopulations resulted in marked changes in several derived inflammatory indices.

Indeed, all major inflammatory indices, except PLR, showed significant reductions during transport. NLR decreased from 2.48 ± 1.66 at baseline to 0.96 ± 0.58 after arrival (p < 0.001), while MLR also declined significantly over time (p < 0.001). Similarly, composite inflammatory markers integrating multiple leukocyte populations, including SII, AISI, and SIRI, showed pronounced decreases from T0 to T2 (all p < 0.001). MCVL values followed the same pattern, decreasing significantly throughout transport (p < 0.001). In contrast, PLR increased progressively from baseline to post-transport measurements (p < 0.001), primarily driven by a substantial rise in platelet counts, accompanied by a concurrent increase in lymphocyte levels.

Overall, these findings indicate that although physiological stability was successfully maintained during neonatal transport, significant hematologic and immunologic adaptations occurred over time. The observed reduction in neutrophil-dominated inflammatory indices, together with increasing lymphocyte and platelet counts, suggests a dynamic redistribution of circulating immune cells during transport and early post-transfer stabilization. Importantly, these changes occurred without significant deterioration in physiological parameters, supporting the hypothesis that transport-related immune modulation may represent a distinct biological response rather than merely a consequence of acute physiological instability.

3.2.2. Evolution of Physiological Stability Markers, Hematologic Parameters, and Inflammatory Indices Stratified by Transport Modality

To further explore whether transport modality influenced the observed physiological and hematologic adaptations, longitudinal analyses were performed separately for air- and ground-transported neonates.

Temporal changes in physiological stability markers, hematologic variables, and inflammatory indices among air-transported neonates are presented in Table 3.

Among air-transported neonates, physiological stability was maintained throughout transport, with no significant changes observed in HR, SpO₂, or body temperature (p = 0.543, p = 0.419, and p = 0.306, respectively) (Table 3). These findings indicate that air transfer was performed under stable cardiorespiratory and thermal conditions, despite this subgroup's higher clinical severity.

Significant temporal changes were observed across multiple hematologic parameters. Hemoglobin concentration progressively declined from 19.62 ± 1.25 g/dL at T0 to 16.84 ± 1.88 g/dL at T2 (p < 0.001), accompanied by a parallel reduction in RBC count and MCV values (both p < 0.001). Mean corpuscular hemoglobin concentration demonstrated a modest but significant increase over time (p = 0.010), while MPV also increased significantly during transport (p = 0.034). These findings suggest active hematologic adaptation during transfer and early post-transport stabilization.

Leukocyte dynamics were particularly pronounced in the air transport group. Median WBC count decreased markedly from 21.80 ×10⁹/L [19.40–23.58] before transport to 11.54 ×10⁹/L [9.12–14.81] at mid-transport, followed by a partial increase after arrival (13.25 ×10⁹/L [11.73–15.35]; p < 0.001). Similarly, neutrophil counts declined dramatically from 14.02 ± 3.48 × 10⁹/L to 5.50 ± 1.97 × 10⁹/L (p < 0.001). In contrast, lymphocyte counts increased significantly over time (p = 0.005), while platelet counts rose progressively from 277.77 ± 92.14 ×10⁹/L to 411.73 ± 132.38 ×10⁹/L (p < 0.001). Monocyte counts also demonstrated significant temporal variation (p < 0.001).

These changes resulted in substantial modifications to inflammatory indices. NLR decreased from 3.53 ± 1.84 at baseline to 1.11 ± 0.54 after transport (p < 0.001), while MLR also declined significantly (p = 0.004). Composite inflammatory markers incorporating neutrophil, monocyte, platelet, and lymphocyte populations showed marked reductions, including SII, AISI, SIRI, and MCVL (all p ≤ 0.001). Conversely, PLR increased significantly during transport (p < 0.001), reflecting the combined effects of thrombocytosis and evolving leukocyte redistribution.

Overall, air-transported neonates exhibited pronounced hematologic and immunologic remodeling despite preserved physiological stability. The magnitude of change observed for leukocyte counts, neutrophils, NLR, SII, AISI, and SIRI suggests a strong transport-associated modulation of the neonatal immune response, characterized by attenuation of neutrophil-dominated inflammatory profiles and progressive increases in lymphocyte and platelet populations.

To determine whether these temporal immune adaptations were specific to air transport or represented a more general response to neonatal transfer, the same analyses were subsequently performed in ground-transported neonates. Temporal changes in physiological stability markers, hematologic variables, and inflammatory indices among ground-transported neonates are presented in Table 4.

Among ground-transported neonates, physiological stability was preserved throughout transport, as evidenced by the absence of significant changes in heart rate, oxygen saturation, and body temperature across the three sampling time points (p = 0.869, p = 0.839, and p = 0.846, respectively) (Table 4). These findings indicate that prolonged transport duration did not result in measurable deterioration of cardiorespiratory or thermal status.

Several hematologic parameters demonstrated significant temporal variation during transport. Hemoglobin concentration progressively declined from 14.93 ± 2.77 g/dL at baseline to 12.98 ± 2.48 g/dL after arrival (p < 0.001), accompanied by corresponding decreases in RBC count and MCV values (both p < 0.001). Significant changes were also observed for MCH, MCHC, and MPV (all p < 0.001), indicating ongoing hematologic adaptation during transport and subsequent stabilization at the referral center.

Leukocyte dynamics followed a pattern broadly similar to that observed in the overall cohort. Total leukocyte counts decreased significantly from a median of 12.00 ×10⁹/L [10.10–14.30] at T0 to 9.34 ×10⁹/L [8.00–10.66] at T1, followed by a partial recovery at T2 (10.50 ×10⁹/L [8.50–12.61]; p < 0.001). Neutrophil counts also declined significantly during transport (p < 0.001), whereas lymphocyte counts increased progressively across the three time points (p < 0.001). In parallel, platelet counts increased markedly from 292.45 ± 141.27 ×10⁹/L at baseline to 426.90 ± 140.10 ×10⁹/L after arrival (p < 0.001). Unlike the air transport group, monocyte counts remained relatively stable and showed no significant temporal variation (p = 0.967).

The observed shifts in leukocyte populations were reflected in significant modifications of inflammatory indices. NLR decreased progressively from 2.14 ± 1.44 at T0 to 0.91 ± 0.59 at T2 (p < 0.001), while MLR also showed a significant reduction over time (p < 0.001). Similarly, SII, AISI, SIRI, and MCVL all demonstrated significant declines across transport stages (all p < 0.001), indicating attenuation of neutrophil-driven inflammatory profiles. In contrast, PLR increased significantly from 81.21 ± 39.56 to 96.91 ± 47.29 (p = 0.005), largely reflecting the substantial rise in platelet counts observed during transport.

Overall, ground-transported neonates demonstrated significant hematologic and inflammatory adaptations despite stable physiological parameters throughout transfer. The combination of declining leukocyte-derived inflammatory indices and increasing lymphocyte and platelet counts suggests progressive modulation of the systemic immune response during transport and early post-transfer stabilization. Although the direction of these changes was similar to that observed in air-transported neonates, the magnitude of variation appeared less pronounced for several key inflammatory markers, particularly WBC, neutrophil counts, NLR, SII, AISI, and SIRI.

Collectively, both transport modalities were associated with significant temporal changes in hematologic and inflammatory parameters despite preserved physiological stability. However, the apparent differences in the magnitude of these responses suggest that transport modality may influence the trajectory of neonatal immune adaptation, a hypothesis formally evaluated in the subsequent mixed-effects analyses.

3.3. Mixed-Effects Analysis of Longitudinal Physiological, Hematologic, and Inflammatory Changes According to Transport Modality

To determine whether temporal changes observed during neonatal transport differed by transport modality, linear mixed-effects models were used to assess the independent effects of time, transport modality, and their interaction on physiological stability markers, hematologic variables, and inflammatory indices.

The results of the mixed-effects analyses are summarized in Table 5, which reports the significance of the main effects of time and transport modality, as well as the Time × Transport interaction for each evaluated parameter.

Mixed-effects modeling demonstrated that physiological stability parameters remained largely unaffected by transport modality. Heart rate, oxygen saturation, and body temperature showed no significant effects of time, transport modality, or their interaction, confirming that physiological stability was successfully maintained throughout transport regardless of transfer type.

In contrast, several hematologic variables exhibited significant time-dependent changes. Hemoglobin, RBC count, and MCV were all significantly influenced by time (all p < 0.001), whereas neither transport modality nor the Time × Transport interaction significantly affected these parameters. These findings indicate that erythrocyte-related changes represent a general response to transport and post-transfer stabilization rather than a transport modality-specific phenomenon.

Among platelet-related variables, platelet count demonstrated a significant effect of time (p < 0.001), while MPV was also significantly influenced by time (p = 0.001). However, neither parameter exhibited a significant Time × Transport interaction, suggesting that platelet adaptations occurred similarly in both transport groups.

The most prominent findings emerged within the leukocyte compartment. Total leukocyte count and neutrophil count were significantly associated with time, transport modality, and the Time × Transport interaction (all p < 0.001). Lymphocyte count also demonstrated significant effects of time (p = 0.007), transport modality (p = 0.006), and their interaction (p = 0.007). These results indicate that transport modality not only influences baseline leukocyte distributions but also modifies the trajectory of immune adaptation during transport and early post-transfer stabilization.

A similar pattern was observed for several inflammatory indices. NLR, SII, and SIRI exhibited highly significant effects of time, transport modality, and Time × Transport interaction (all p < 0.001), highlighting their sensitivity to transport-related immune modulation. In contrast, MLR was significantly associated with time and transport modality but showed no significant interaction effect (p = 0.230), whereas PLR showed significant main effects but only a borderline interaction effect (p = 0.082).

Particularly noteworthy was the behavior of MCVL, a relatively novel composite hematologic index. MCVL demonstrated significant effects of time (p = 0.017), transport modality (p = 0.003), and the Time × Transport interaction (p = 0.017). Unlike many conventional hematologic parameters, MCVL remained sensitive to all three components of the mixed-effects model. Among the evaluated composite hematologic indices, MCVL emerged as a novel marker demonstrating significant effects of time, transport modality, and their interaction, suggesting that it may capture transport-related immune adaptations beyond those reflected by conventional inflammatory ratios.

Overall, these findings indicate that the most pronounced transport modality-dependent responses were observed for leukocyte-related variables and composite inflammatory indices, whereas physiological stability markers and erythrocyte parameters were primarily influenced by time alone. The persistence of significant Time × Transport interactions for WBC, neutrophils, lymphocytes, NLR, SII, SIRI, and MCVL supports the concept that air and ground transport are associated with distinct trajectories of neonatal immune adaptation despite comparable physiological stability.

3.4. Adjusted Mixed-Effects Models of Transport-Related Immune Adaptation

To determine whether the observed transport-related immune changes remained independent of transport duration, sedation requirements, and physiological stability, adjusted mixed-effects models were subsequently applied. The results of the primary adjusted model (Model A) and the sensitivity analysis incorporating physiological stability (Model B) are presented in Table 6.

In the primary adjusted model (Model A), which controlled for transport duration and sedation during transport, the effects of time, transport modality, and their interaction remained highly significant for the principal leukocyte-derived markers. Total leukocyte count, neutrophil count, and NLR all demonstrated significant effects of time, transport modality, and Time × Transport interaction (all p < 0.001). These findings indicate that the distinct immune trajectories observed in air- and ground-transported neonates cannot be explained solely by differences in transport duration or sedation practices.

Lymphocyte counts also remained independently associated with time, transport modality, and their interaction, supporting the concept that neonatal transport influences both innate and adaptive immune cell populations. Similarly, the composite inflammatory indices SII and SIRI retained highly significant associations with all three model components (all p < 0.001), confirming that transport modality modifies the evolution of systemic inflammatory responses over time.

Among the evaluated inflammatory indices, MCVL demonstrated a particularly interesting behavior. Despite adjustment for transport-related confounders, MCVL remained significantly associated with time (p = 0.017), transport modality (p = 0.003), and the Time × Transport interaction (p = 0.017). These findings suggest that MCVL may capture aspects of transport-related immune adaptation that are not fully reflected by conventional inflammatory ratios.

To evaluate the robustness of these observations, a sensitivity analysis was subsequently performed incorporating mean oxygen saturation during transport as a surrogate marker of physiological stability (Model B). Importantly, the principal findings remained largely unchanged. WBC, neutrophils, lymphocytes, NLR, SII, SIRI, and MCVL all showed statistically significant effects of time, transport modality, and Time × Transport interaction. The magnitude and direction of the regression coefficients remained highly comparable to those observed in Model A, indicating that the observed immune trajectories were not primarily driven by differences in oxygenation status during transport.

Mean SpO₂ itself showed modest but statistically significant associations with several immune markers, including WBC, neutrophils, NLR, SII, SIRI, and MCVL. However, the inclusion of this physiological stability marker did not materially alter the transport-related effects observed in the primary model. This finding suggests that the differential immune responses associated with air and ground transport extend beyond transient respiratory instability and likely reflect broader biological adaptations to transport-related stress.

Particularly noteworthy was the consistency of MCVL across both adjusted models. Unlike many conventional hematologic variables, MCVL remained significantly associated with time, transport modality, and their interaction after adjustment for transport duration, sedation, and physiological stability. Among the evaluated composite hematologic indices, MCVL emerged as a novel marker demonstrating significant effects of time, transport modality, and their interaction, suggesting that it may capture transport-related immune adaptations beyond those reflected by conventional inflammatory ratios.

Overall, the persistence of significant Time × Transport interactions after multivariable adjustment supports the conclusion that transport modality independently influences neonatal immune adaptation. The robustness of these findings across both adjusted models strengthens the evidence that air and ground transport are associated with distinct patterns of leukocyte redistribution and systemic inflammatory modulation, even after accounting for differences in transport duration, sedation, and physiological stability.

Collectively, these findings indicate that transport modality acts as an independent determinant of neonatal immune response trajectories, with both conventional inflammatory indices and the emerging MCVL marker demonstrating sustained sensitivity to transport-related physiological stress.

4. Discussion

This study investigated the longitudinal evolution of physiological stability markers, hematologic variables, and inflammatory indices in neonates undergoing interfacility transfer to tertiary and quaternary neonatal intensive care centers. Although air-transported neonates presented with greater baseline clinical severity, physiological stability was successfully maintained throughout transport in both groups. Despite this apparent clinical stability, significant transport-related changes were observed in leukocyte populations and inflammatory indices. Importantly, several immune markers, including WBC, neutrophil count, NLR, SII, SIRI, and MCVL, remained significantly associated with transport modality and Time × Transport interactions even after adjustment for transport duration, sedation, and physiological stability, suggesting that neonatal transport is accompanied by measurable systemic immune adaptation rather than merely reflecting transient physiological instability.

4.1. Physiological Stability and Immune Adaptation During Neonatal Transport

A major finding of the present study is that neonatal transport was not associated with measurable deterioration in physiological stability parameters. Heart rate, oxygen saturation, and body temperature remained stable throughout transport, both in the overall cohort and after stratification according to transport modality. These findings indicate that contemporary neonatal transport systems can maintain cardiorespiratory and thermal homeostasis despite substantial differences in transport duration and baseline disease severity.

These observations are consistent with recent studies demonstrating progressive improvements in neonatal transport safety through specialized retrieval teams, advanced monitoring systems, and modern transport incubators [5,6,7,10,11]. Although hypothermia and respiratory instability remain among the most frequently reported complications of neonatal transfer [12,13,14,15,34], no significant deterioration in temperature or oxygenation was observed in our cohort. This likely reflects effective stabilization before transfer and the quality of contemporary neonatal transport practices.

Notably, preserved physiological stability contrasted with the marked hematologic and inflammatory changes observed during transport. This dissociation suggests that transport-related biological responses may occur independently of overt cardiorespiratory or thermal deterioration. Rather than reflecting hypoxemia, hypothermia, or hemodynamic instability, the observed immune changes may be driven by exposure to transport-related stressors such as handling, vibration, environmental noise, acceleration forces, and activation of neuroendocrine stress pathways. These findings indicate that traditional physiological variables alone may not fully capture the biological impact of neonatal transport.

4.2. Inflammatory Adaptation and Leukocyte Redistribution During Transport

One of the most striking findings of the present study was the dynamic redistribution of circulating leukocyte populations during transport. Total leukocyte and neutrophil counts progressively declined, whereas lymphocyte counts increased over time. Furthermore, significant Time × Transport interactions persisted after multivariable adjustment, indicating that transport modality independently influenced immune trajectories.

These observations should be interpreted within the context of neonatal immune physiology. Unlike adults, newborns possess an immature and actively developing immune system characterized by developmental differences in granulopoiesis, chemotaxis, endothelial adhesion, and inflammatory signaling [22,23,26,27]. Consequently, responses to physiological stressors may differ substantially from the classical adult pattern of stress-induced neutrophilia and lymphopenia.

The progressive decline in circulating neutrophils accompanied by relative lymphocyte recovery should be interpreted cautiously, particularly among air-transported neonates who presented with greater clinical severity and a substantially higher prevalence of mechanical ventilation. In this subgroup, the marked reduction in total leukocyte and neutrophil counts observed between T0 and T1 may not necessarily indicate attenuation of inflammatory activity. Instead, it may reflect acute leukocyte redistribution through endothelial margination, pulmonary sequestration, or early tissue recruitment of activated neutrophils. Similar phenomena have been described during severe physiological stress, acute lung injury, and systemic inflammatory activation, where circulating neutrophil counts may decline despite ongoing inflammatory processes. At the same time, neonatal stress exposures are known to influence leukocyte trafficking and immune maturation through neuroendocrine pathways [19,20]. Activation of the hypothalamic–pituitary–adrenal axis and sympathetic nervous system results in the release of cortisol and catecholamines, which regulate leukocyte migration, cytokine production, endothelial interactions, and innate immune responses [19,20,21]. Consequently, the observed reductions in circulating leukocyte populations may reflect a complex interplay between stress-induced immune redistribution, inflammatory cell recruitment, and neuroendocrine regulation rather than a simple resolution of inflammation.

Another plausible mechanism involves sterile inflammatory activation. Physiological stress can induce the release of danger-associated molecular patterns (DAMPs), which activate innate immune signaling pathways in the absence of infection [25]. Mechanical stress, respiratory interventions, and environmental exposures associated with transport may therefore contribute to transient immune activation and subsequent resolution, manifested by a decline in neutrophil predominance and progressive lymphocyte recovery.

The persistence of significant Time × Transport interactions after adjustment suggests that the transport modality itself contributes to the shaping of immune responses. Although the precise mechanisms remain unclear, differences in transport duration, vibration exposure, acceleration forces, cabin conditions, and handling intensity may influence neuroimmune signaling and leukocyte redistribution. Collectively, these findings support the concept that neonatal transport is a biologically active process that modulates immune adaptation independently of overt physiological instability.

4.3. Inflammatory Indices and the Emerging Role of MCVL

Beyond individual leukocyte populations, significant transport-related changes were observed in composite inflammatory indices. Among the evaluated biomarkers, NLR, SII, and SIRI demonstrated the strongest associations with time, transport modality, and Time × Transport interactions, even after adjustment for transport duration, sedation, and physiological stability.

NLR progressively declined throughout transport, reflecting the combined decrease in neutrophils and increase in lymphocytes. Although elevated NLR is generally considered a marker of systemic inflammation and physiological stress, interpretation of declining NLR values in critically ill neonates is more complex. Particularly among air-transported infants with greater illness severity and higher rates of mechanical ventilation, reductions in NLR may reflect leukocyte redistribution, endothelial margination, pulmonary sequestration, or tissue recruitment rather than true resolution of inflammatory activity. Therefore, declining NLR should be interpreted as evidence of altered immune-cell trafficking and inflammatory dynamics rather than as a direct marker of reduced inflammation. Similar patterns were observed for SII and SIRI, both of which integrate multiple immune cell populations and therefore provide a broader assessment of systemic inflammatory activity.

A particularly novel finding of this study was the consistent behavior of MCVL. Unlike conventional inflammatory ratios, MCVL combines an erythrocyte-derived parameter with a lymphocyte-derived immune component, potentially reflecting interactions between erythropoietic adaptation and immune regulation. MCVL remained significantly associated with time, transport modality, and their interaction across both unadjusted and adjusted analyses, suggesting that it captures dimensions of transport-related adaptation not reflected by traditional inflammatory indices.

Although MCVL has not previously been investigated in neonatal transport, emerging evidence supports its relevance in other inflammatory and oxidative stress-related conditions. Recent studies have demonstrated associations between MCVL and disease activity in colorectal cancer, ulcerative colitis, inflammatory bowel disease, pediatric inflammatory conditions, and acute pancreatitis [28,29,30,31,32,33]. The present findings extend these observations to neonatal transport and suggest that MCVL may serve as a sensitive biomarker of immune and hematologic adaptation during early-life stress exposure.

4.4. Clinical Implications

The present findings suggest that neonatal transport should not be evaluated exclusively through conventional physiological endpoints. Although heart rate, oxygen saturation, and body temperature remained stable throughout transfer, significant hematologic and inflammatory adaptations occurred, indicating that biological responses may develop despite preserved physiological stability.

Because NLR, SII, SIRI, and MCVL are inexpensive and readily available from routine complete blood counts, they may represent practical adjunctive tools for monitoring neonatal adaptation during transport. Serial assessment of these biomarkers could provide complementary information regarding biological stress responses and may help identify neonates requiring closer observation following transfer.

Future investigations integrating inflammatory biomarkers with neuroendocrine mediators, oxidative stress markers, cytokine profiles, and long-term clinical outcomes may further clarify the biological consequences of neonatal transport and improve risk stratification strategies for critically ill newborns.

4.5. Strengths and Limitations

This study has several strengths. It represents one of the first investigations to evaluate longitudinal immune and hematologic responses during neonatal transport using repeated measurements obtained before transport, immediately after transport, and 12 hours following admission to a tertiary or quaternary center. The inclusion of both air- and ground-transported neonates enabled direct comparison of transport modalities, while mixed-effects modeling allowed adjustment for transport duration, sedation, and physiological stability. Furthermore, the study evaluated both established inflammatory indices and the emerging MCVL biomarker, providing novel insights into transport-related immune adaptation.

Several limitations should also be acknowledged. First, the observational design precludes causal inference and limits definitive conclusions regarding the mechanisms responsible for the observed immune responses. Second, measurements of cytokines, catecholamines, cortisol, oxidative stress biomarkers, and danger-associated molecular patterns were not available, preventing direct evaluation of the neuroimmune and sterile inflammatory pathways proposed in this study. Moreover, because only complete blood count-derived biomarkers were available, it was not possible to distinguish between adaptive immune redistribution, endothelial margination, pulmonary sequestration, inflammatory cell consumption, or true resolution of inflammatory activation. Consequently, the biological interpretation of leukocyte dynamics remains inferential and should be confirmed by future studies incorporating cytokine profiling, stress hormones, endothelial biomarkers, and markers of neutrophil activation. Third, the cohort included neonates with heterogeneous underlying diagnoses and varying degrees of illness severity, which may have influenced baseline immune profiles. Fourth, although physiological stability was assessed using heart rate, oxygen saturation, and body temperature, additional markers of cardiovascular function were not systematically collected. Finally, MCVL remains an emerging biomarker with limited validation in neonatal populations, and its clinical utility should therefore be considered exploratory until confirmed by larger multicenter studies.

5. Conclusions

Neonatal transport was associated with significant immune and hematologic adaptations despite preserved physiological stability. Distinct longitudinal trajectories of leukocyte populations and inflammatory indices were observed between air- and ground-transported neonates, indicating that transport modality independently influences neonatal immune responses. Among the evaluated biomarkers, MCVL emerged as a novel and promising indicator, remaining significantly associated with time, transport modality, and their interaction across adjusted analyses. These findings suggest that transport-related biological adaptation extends beyond conventional physiological monitoring and support the integration of hematologic biomarkers into future neonatal transport research.