The relationship between delta neutrophil index (DNI) and mortality during cardiopulmonary bypass: An observational study

Abstract

Objective

Systemic inflammation triggered by cardiopulmonary bypass (CPB) plays a critical role in postoperative complications and mortality. The Delta Neutrophil Index (DNI), which quantifies circulating immature neutrophils, is increasingly recognized as a marker of systemic inflammation. While its utility has been demonstrated in sepsis and non-cardiac surgeries, its role in cardiac procedures remains underexplored. This study aimed to evaluate the relationship between intraoperative DNI levels and postoperative mortality in patients undergoing open-heart surgery with CPB.

Methods

This retrospective observational study included 245 patients who underwent CPB between January 2022 and July 2023. DNI was measured at five predefined time points: induction, 5, 45, and 90 min after CPB initiation, and immediately postoperatively. Patients were categorized into two groups based on in-hospital mortality: those who experienced mortality (“Ex” group, n = 67) and those who survived (“Non-Ex” group, n = 178). Logistic regression was used to assess the association between DNI values and mortality.

Results

DNI levels were significantly higher in the Ex group at induction (1.22 ± 0.96 vs 0.47 ± 0.39; p = 0.002), 5 min (2.04 ± 1.07 vs 1.08 ± 0.58; p < 0.001), 90 min (1.76 ± 0.84 vs 1.07 ± 0.81; p = 0.004), and postoperatively (2.14 ± 1.38 vs 0.58 ± 0.32; p < 0.001). Each unit increase in postoperative DNI was associated with a 21.78-fold increase in mortality risk (95% CI: 6.12–67.92; p < 0.001). CPB and cross-clamp durations were also significantly longer in Ex patients.

Conclusions

Elevated intraoperative and postoperative DNI levels are strongly associated with increased in-hospital mortality following CPB. DNI may serve as a dynamic and practical biomarker to aid perioperative risk stratification, pending further validation. Incorporating DNI into routine intraoperative monitoring may enhance early identification of high-risk patients and improve postoperative outcomes.

Highlights

Elevated intraoperative and postoperative Delta Neutrophil Index (DNI) levels are strongly associated with in-hospital mortality after cardiopulmonary bypass.

Postoperative DNI was the strongest predictor of mortality, with a 21.78-fold increased risk per unit rise.

DNI may serve as a dynamic biomarker for early risk stratification in cardiac surgery.

DNI offers real-time inflammatory monitoring beyond conventional risk scores.

This is the first study to evaluate serial DNI measurements during CPB.

Introduction

Patients undergoing cardiovascular surgery frequently experience postoperative complications due to preoperative comorbidities and the inherently high-risk nature of these procedures. ¹ Postoperative mortality rates in cardiovascular surgeries are disproportionately high compared to other surgical specialties, with mortality rates reaching 2–3% following valve replacement and 4% after coronary artery bypass grafting (CABG), posing a significant challenge to patient outcomes. ² Early identification of patients at higher risk of complications, even among those classified as low-risk, allows for timely intervention and improved survival outcomes. The ability to identify these high-risk patients early can significantly reduce postoperative morbidity and mortality rates, especially in the setting of complex cardiac surgeries where inflammatory responses play a crucial role.

Cardiac surgery performed with cardiopulmonary bypass (CPB) triggers systemic inflammatory response syndrome (SIRS). Potential causes include contact activation between blood components and the artificial surface of the bypass circuit, ischemia-reperfusion injury, endotoxemia, and operative trauma. This inflammatory reaction contributes to postoperative complications such as myocardial dysfunction, respiratory failure, renal and neurological dysfunction, coagulopathies, liver dysfunction, and ultimately, multi-organ failure (MOF).

The Delta Neutrophil Index (DNI), a biomarker representing circulating immature neutrophils, is recognized as an indicator of systemic inflammation. Furthermore, its dynamic nature allows it to reflect real-time changes in inflammatory responses, making it a potentially valuable marker for predicting not only postoperative complications but also long-term recovery trajectories in high-risk surgical patients. It has been widely studied for predicting clinical outcomes in high-risk patients experiencing systemic inflammatory responses or undergoing major non-cardiac surgeries.^3–5 Despite its well-established role in other high-risk surgical procedures, the use of DNI in cardiac surgery has been relatively underexplored, making this study a pivotal contribution to the field. The inflammatory response during cardiac surgery has been linked to postoperative complications and mortality. In particular, the activation of neutrophils, as reflected by the DNI, provides a window into the severity of systemic inflammation and its impact on postoperative recovery. This study investigates the impact of intraoperative DNI levels during CPB on mortality rates, highlighting its potential as a prognostic marker. This study addresses a critical gap by evaluating the prognostic role of DNI in cardiac surgery and exploring its potential in enhancing perioperative risk prediction.

Materials and methods

This retrospective, observational cohort study was conducted at Mersin University Faculty of Medicine Education and Research Hospital, a tertiary academic center providing cardiovascular surgery services. The study included consecutive patients who underwent open-heart surgery with cardiopulmonary bypass between January 1, 2022, and July 30, 2023. This study follows the STROBE guidelines for reporting observational research.

Data collection

Study design

The study utilized a nested case-control design within the cohort. The estimated odds ratio (OR) for exposure factors associated with ex was assumed to be at least 1.5. To achieve a type I error of ≤5% and statistical power of ≥80%, the sample size was determined to be 245 patients. A 1:3 ratio was maintained for Ex and Non-Ex cases. The sample size was determined using a standard formula for unmatched case-control studies, assuming an OR of 1.5, α = 0.05, and power = 0.80. Calculations were performed using G*Power 3.1.

Data collection

This retrospective observational study included a total of 245 patients who underwent open-heart surgery with cardiopulmonary bypass (CPB) between January 1, 2022, and July 30, 2023, at a tertiary cardiovascular surgery center. Patients were consecutively enrolled, and data were extracted from institutional electronic medical records. To ensure cohort homogeneity and minimize confounding factors that may independently influence systemic inflammation or mortality risk, strict exclusion criteria were applied. Patients undergoing emergency cardiac surgery, those diagnosed with acute type A aortic dissection, and individuals requiring preoperative mechanical circulatory support or urgent revascularization were excluded. Additionally, patients with end-stage liver disease (Child-Pugh class C), chronic kidney disease requiring renal replacement therapy, active systemic infections, autoimmune or rheumatologic disorders, hematological malignancies, or any known active malignancy were not included in the analysis. Patients receiving chronic immunosuppressive or corticosteroid therapy were also excluded. Furthermore, patients with incomplete intraoperative DNI measurements, missing perioperative laboratory data, or insufficient anesthesia or surgical records were omitted from the final cohort. These exclusion criteria were implemented to reduce variability in inflammatory responses and to focus the analysis on elective open-heart surgery cases with stable preoperative profiles. The study population was stratified into two groups based on in-hospital mortality: the Ex group (patients who experienced mortality; n = 67) and the Non-Ex group (survivors; n = 178). It is important to clarify that the observed 27.3% mortality rate in this study does not reflect the actual in-hospital mortality rate of our institution. For the purposes of robust statistical analysis, particularly to improve the power of logistic regression modeling, a nested case-control design was employed with a 1:3 ratio of patients who experienced mortality (Ex) to those who did not (Non-Ex). The actual overall in-hospital mortality at our institution during the study period was substantially lower. The relatively high mortality rate reported in this study (27.3%) does not represent the true institutional mortality but rather reflects the intentional case–control enrichment applied to strengthen statistical power. In this nested case–control design, all available mortality cases during the study period were included, and three matched survivors per case were selected to improve comparability and analytical robustness. Therefore, the proportion of mortality cases in the analyzed dataset is artificially elevated relative to the real-world incidence, which remains within expected limits for elective open-heart procedures at our center (<5%). This methodological approach was adopted to enhance model sensitivity without distorting the overall representativeness of clinical outcomes. Furthermore, all cases included in the analysis were elective surgeries; emergency cases, as well as patients with end-stage liver or kidney disease, were excluded to maintain clinical homogeneity. The distribution of surgical procedures was as follows: coronary artery bypass grafting (CABG) accounted for 65% of the cohort, valve surgeries (isolated or combined) for 20%, aortic surgeries for 10%, and other complex procedures for 5%. Notably, no patients undergoing acute type A aortic dissection were included. This procedural breakdown underscores the surgical diversity in our center while maintaining a relatively controlled perioperative risk profile.

Collected variables included demographic characteristics (age and sex), presence of comorbidities (diabetes mellitus [DM] and hypertension [HT]), and intraoperative parameters such as total CPB duration and cross-clamp time. To ensure uniform intraoperative conditions across the cohort, key physiological parameters during cardiopulmonary bypass (CPB) were strictly maintained within institutional and internationally accepted standards. These included nadir hemoglobin levels, lowest core body temperature during hypothermic perfusion, and perfusion index values. All parameters were continuously monitored and regulated by experienced perfusionists and anesthesiologists using standardized institutional protocols. None of the patients experienced perfusion anomalies or critical deviations from these targets. These measures ensured hemodynamic stability and minimized variability in systemic inflammatory response attributable to perfusion-related factors. Age was recorded in years, and both CPB and cross-clamp times were measured in minutes. The Delta Neutrophil Index, a hematologic biomarker representing the percentage of circulating immature granulocytes (IG%), was also measured. DNI values were obtained at five predefined time points: induction (pre-CPB), 5 min after CPB initiation, 45 min into CPB, 90 min into CPB, and immediately postoperative. All hematologic analyses were performed using a Sysmex XE-2100 automated hematology analyzer (Sysmex Corporation, Kobe, Japan), which calculates DNI based on the difference between the leukocyte subfractions detected in the myeloperoxidase and nuclear lobularity channels. Although there is no universally accepted cut-off for DNI in cardiac surgery, values exceeding 1.5% in our institutional laboratory are considered indicative of heightened inflammatory response.

In addition to DNI, laboratory parameters including white blood cell (WBC) count, hemoglobin, and platelet counts were documented. The integrity of the data was validated by cross-referencing laboratory information with surgical records and anesthesia charts to ensure accuracy and consistency across all perioperative time points.

Data analysis

Statistical analysis

Continuous variables were summarized using mean ± standard deviation, medians, and minimum-maximum values, while categorical variables were described with frequencies and percentages. Independent group means were compared using the Student’s t-test, and relationships between categorical variables were assessed using the Chi-square test. Factors associated with ex were evaluated with odds ratios and 95% confidence intervals (CI). Statistical significance was defined as p < 0.05. Although multivariable logistic regression was performed to identify independent predictors of mortality, DNI values were not included in the multivariable model due to their strong collinearity with other variables such as neutrophil count, CPB duration, and postoperative inflammatory markers. Preliminary analyses showed high variance inflation factors (VIF), indicating potential multicollinearity. Additionally, the exceptionally high odds ratio of postoperative DNI in univariate analysis (OR: 21.78; p < 0.001) suggested a dominant predictive effect, which could mask the contribution of other clinically relevant covariates in multivariable modeling. Therefore, DNI was evaluated independently using stratified univariate logistic models.

Software

Data analysis was performed using IBM SPSS version 21 and MedCalc statistical software. Parametric tests were applied without normality testing due to the Central Limit Theorem’s applicability for continuous measures.

Results

In this retrospective study, intraoperative DNI levels were measured at specific intervals in 245 patients undergoing open-heart surgery with CPB. Patients were categorized into two groups based on outcomes: those who survived Non-Ex and those who did not Ex. DNI values were recorded at induction, intraoperatively at 5, 45, and 90 min, and postoperatively.

A total of 245 patients were included in the study, with a mean age of 59.6 ± 12.4 years; 61.2% were male, and the prevalence of diabetes mellitus and hypertension was 55.1% and 58.8%, respectively. The mean cardiopulmonary bypass (CPB) and cross-clamp durations were 121 ± 46 min and 70 ± 29 min, respectively. The overall in-hospital mortality rate within the analytical cohort was 25.3%, reflecting the case–control enrichment design (Table 1).

Table 1.

Sociodemographic and Clinical Characteristics of Patients (n = 245).

Feature	Mean ± SD	Median (Min-Max)
Age	59.6 ± 12.4	62 (19-80)
	n	(%)
Gender
Male	155	61.2
Female	95	38.8
Ex
Yes	67	25.3
No	178	72.7
DM
No	110	44.9
Yes	135	55.1
HT
No	101	41.2
Yes	144	58.8

	Mean ± SD	Min-max
CPB duration	121.1 ± 46.5	114.5 (36-254)
Cross-clamp duration	69.8 ± 28.9	61 (12-143)

Statistical comparisons in this table were performed using the Student’s t-test for continuous variables (such as age, CPB duration, and cross-clamp duration), and the Chi-square test for categorical variables (including gender, diabetes mellitus status, hypertension status, and mortality). Numerical values are expressed as mean ± standard deviation (SD) for normally distributed continuous variables and as median (minimum–maximum) where appropriate. Categorical variables are presented as numbers and percentages. In the table, values showing statistically significant differences (p < 0.05) are displayed in bold. The p-value represents the probability that the observed differences occurred by chance; p < 0.05 is considered statistically significant.

Abbreviations: CPB = Cardiopulmonary Bypass, HT = Hypertension, DM = Diabetes Mellitus, SD = Standard Deviation, Ex = Mortality (Exitus).

Compared with survivors (Non-Ex group), patients who died (Ex group) were older, had lower ejection fraction, and demonstrated significantly longer CPB and cross-clamp times (Tables 2 and 3). Postoperative renal parameters (creatinine, urea) and inflammatory indices (neutrophil count, CRP, DNI) were markedly elevated in the Ex group, whereas lymphocyte, platelet, and albumin levels were lower (Table 2). These findings indicate a more pronounced inflammatory and metabolic stress in patients with adverse outcomes.

Table 2.

Comparison of preoperative and postoperative biochemical parameters by ex status (n = 245).

Parameter	Non-Ex (n = 178)	Ex (n = 67)	p-value*
Ejection fraction (%)	56.4 ± 5.9	48.7 ± 7.8	<0.001
Pre-creatinine (mg/dL)	0.87 ± 0.31	0.96 ± 0.46	0.27
Post-creatinine (mg/dL)	0.91 ± 0.36	1.52 ± 0.53	<0.001
Pre-urea (mg/dL)	34.9 ± 13.2	39.6 ± 15.1	0.16
Post-urea (mg/dL)	37.8 ± 12.7	61.3 ± 19.4	<0.001
Pre-NEU (10 3 /μL)	5.01 ± 1.98	6.42 ± 2.36	0.004
Post-NEU (10 3 /μL)	9.87 ± 3.21	14.21 ± 5.04	<0.001
Pre-LYM (10 3 /μL)	2.28 ± 0.65	2.11 ± 0.77	0.51
Post-LYM (10 3 /μL)	1.34 ± 0.49	1.03 ± 0.54	0.009
Pre-PLT (10 3 /μL)	251.3 ± 71.8	221.4 ± 68.9	0.03
Post-PLT (10 3 /μL)	163.2 ± 44.6	129.6 ± 62.7	0.001
Pre-CRP (mg/L)	5.6 ± 2.3	6.4 ± 6.5	0.15
Post-CRP (mg/L)	87.4 ± 8.9	154.2 ± 61.3	0.05
Pre-albumin (mg/L)	39.2 ± 2.8	37.6 ± 4.5	0.67
Post-albumin (mg/L)	30.1 ± 10.4	22.4 ± 5.6	<0.001

Statistical comparisons were performed using the following tests: Student’s t-test for continuous variables between groups (Ex vs Non-Ex), Paired t-test for within-group preoperative and postoperative measurements, and Chi-square test for categorical variables. Data are presented as mean ± standard deviation (SD). Statistically significant differences (p < 0.05) are indicated in bold. The p-value represents the probability that the observed difference occurred by chance.

Abbreviations: EF = Ejection Fraction, CRP = C-Reactive Protein, NEU = Neutrophil Count, LYM = Lymphocyte Count, PLT = Platelet Count, SD = Standard Deviation, Ex = Mortality (Exitus).

Table 3.

Comparison of Sociodemographic and Clinical Features by Ex Status (n = 245).

	Ex (n = 67)	Non-Ex (178)	p value
Feature	Mean ± SD	Mean ± SD
Age	65.9 ± 11.2	58.1 ± 12.3	<0.001
	n	(%)
Gender
Male	39 (58.2%)	116 (65.2%)	0.56
Female	28 (41.8%)	62 (34.85)
DM
No	25 (37.3%)	85 (47.8%)	0.71
Yes	42 (62.7%)	93 (52.2%)
HT
No	23 (34.3%)	78 (43.8%)	0.43
Yes	44 (65.7%)	100 (56.2%)

	Mean ± SD	Mean ± SD
CPB duration	172.6 ± 41.8	106.4 ± 34.2	<0.001
Cross-clamp duration	112.7 ± 22.3	58.6 ± 17.9	<0.001

Statistical comparisons between patients with and without in-hospital mortality (Ex vs Non-Ex groups) were conducted using the Student’s t-test for continuous variables (such as age, cardiopulmonary bypass [CPB] duration, and cross-clamp duration), and the Chi-square test for categorical variables (such as gender, diabetes mellitus [DM], and hypertension [HT] status). Data for continuous variables are presented as mean ± standard deviation (SD). Categorical variables are expressed as number of patients and percentages. In the table, statistically significant differences (defined as p < 0.05) are highlighted in bold. The p-value represents the probability that the observed difference occurred by chance; values less than 0.05 were considered to indicate statistically significant associations.

Abbreviations: CPB = Cardiopulmonary Bypass, HT = Hypertension, DM = Diabetes Mellitus, SD = Standard Deviation, Ex = Mortality.

Logistic regression analysis confirmed that age, CPB duration, and cross-clamp time were significantly associated with mortality (Table 4). DNI values were consistently higher in the Ex group at nearly all time points, with postoperative DNI showing the strongest association (OR = 21.78; 95% CI: 6.12–67.92; p < 0.001) (Tables 5 and 6).

Table 4.

Factors Associated with Ex Status (Mortality).

Feature	Odds Ratio	%95 CI (Lower-Upper)	p value
Age	1.08	1.02-1.14	<0.002
CPB duration	1.06	1.03-1.09	0.004
Cross-clamp duration	1.12	1.07-1.18	<0.001

Logistic regression analysis was performed to determine factors associated with in-hospital mortality (Ex status). Each variable was modeled as a continuous predictor of mortality, and results are presented as odds ratios (OR) with corresponding 95% confidence intervals (CI). The OR indicates the change in odds of mortality for each unit increase in the predictor variable. A p-value less than 0.05 was considered statistically significant, and significant associations are shown in bold in the table. The p-value represents the probability that the observed association occurred by chance; lower values suggest stronger statistical evidence.

Abbreviations: OR = Odds Ratio, CI = Confidence Interval, CPB = Cardiopulmonary Bypass, Ex = Mortality.

Table 5.

Comparison of Ig% (DNI) Measurements by Pump Time and Ex Status (n = 245).

<

	Ex (n = 67)	Non-Ex (=178)	p value
Measurement	Mean ± SD	Mean ± SD
Ig% (DNI)- induction İnInduction<	1.22 ± 0.96	0.47 ± 0.39	0.002
Ig% (DNI)-5 min	2.04 ± 1.07	1.08 ± 0.58	<0.001
Ig% (DNI)-45 min	1.41 ± 0.91	1.28 ± 0.87	0.217
Ig% (DNI)-90 min	1.76 ± 0.84	1.07 ± 0.81	0.004
Ig% (DNI)-postop	2.14 ± 1.38	0.58 ± 0.32	<0.001

Statistical comparisons of DNI (Ig%) measurements at various time points during cardiopulmonary bypass between Ex (mortality) and Non-Ex groups were performed using the Student’s t-test for independent continuous variables. Data are presented as mean ± standard deviation (SD). In the table, statistically significant differences (defined as p < 0.05) are indicated in bold. The p-value reflects the likelihood that the observed difference occurred by chance, and lower values imply stronger evidence for statistical significance.

Abbreviations: DNI = Delta Neutrophil Index, Ig% = Immature Granulocyte Percentage, SD = Standard Deviation, Ex = Mortality, postop = Postoperative.

Table 6.

Factors Associated with Ex Status Based on DNI Measurements at Pump Times (n = 245).

Measurement	Odds Ratio	%95 CI (Lower-Upper)	p value
Ig% (DNI)- induction	6.32	2.78-14.38	0.003
Ig% (DNI)-5 min	1.93	1.38-2.69	0.001
Ig% (DNI)-45 min	1.19	0.92-1.54	0.201
Ig% (DNI)-90 min	2.01	1.31-3.07	0.004
Ig% (DNI)-postop	21.78	6.12-67.92	<0.001

Logistic regression analysis was performed to evaluate the association between Delta Neutrophil Index (DNI) measurements at different intraoperative time points and in-hospital mortality (Ex status). Results are expressed as odds ratios (OR) with corresponding 95% confidence intervals (CI). The OR represents the change in odds of mortality for each unit increase in DNI at the specified time point. A p-value less than 0.05 was considered statistically significant, and significant findings are marked in bold in the table. The p-value reflects the probability that the observed association is due to chance; smaller values indicate stronger evidence for a real effect.

Abbreviations: DNI = Delta Neutrophil Index, Ig% = Immature Granulocyte Percentage, OR = Odds Ratio, CI = Confidence Interval, Ex = Mortality, postop = Postoperative.

Discussion

This single-center retrospective study suggests that the Delta Neutrophil Index (DNI) may serve as a valuable prognostic indicator of in-hospital mortality among patients undergoing cardiopulmonary bypass. Notably, postoperative DNI levels were markedly higher in non-survivors compared to survivors (2.14 ± 1.38 vs 0.58 ± 0.32, p < 0.001), and each unit increase in postoperative DNI was associated with a 21.78-fold increase in the odds of mortality (95% CI: 6.12–67.92; p < 0.001). These findings support the potential utility of DNI in enhancing perioperative risk stratification and informing postoperative management strategies; however, further prospective validation is warranted. Echoing prior studies that highlight the central role of CPB-induced inflammation in postoperative complications, our findings reinforce that elevated DNI levels serve as a robust indicator of systemic inflammation, with a clear correlation to increased mortality in patients undergoing CPB. Because of multicollinearity with inflammatory and time-related covariates, DNI was assessed outside the multivariable model; nevertheless, its strong univariate association supports clinical utility while warranting prospective confirmation of independent effect. While our univariate results strongly suggest prognostic significance, further multivariable and prospective analyses are warranted to confirm its independent predictive value. Although subgroup analyses for high-risk profiles such as elderly, diabetic, or prolonged CPB groups would offer further insights, sample size limitations prevented statistically meaningful stratification. These findings support the potential value of enhanced inflammatory monitoring strategies during cardiac surgery. To further elucidate the complex nature of systemic inflammation, the conceptual framework proposed by Evgenii Gusev and collaborators offers important mechanistic insights. Their research emphasizes that systemic inflammation extends beyond the elevation of single biomarkers, encompassing a multifactorial process involving cytokine signaling, endothelial activation, and cellular immune dysregulation. In this context, distinguishing systemic inflammation from individual acute-phase reactants such as C-reactive protein (CRP) is critical. While CRP reflects downstream hepatic response, systemic inflammation represents a dynamic network of immunologic and vascular interactions that ultimately influence postoperative outcomes and mortality risk in cardiac surgery. ⁶

Kirklin identified CPB as a trigger for a “whole-body inflammatory response”. ⁷ This phenomenon, now widely recognized as systemic inflammatory response syndrome, manifests as reduced systemic vascular resistance, increased cardiac output, capillary leak, fluid retention, leukocytosis, and organ dysfunction. ⁸ The risk appears to worsen with prolonged CPB durations. Studies have attempted to link CPB and cross-clamp durations with the magnitude of inflammatory responses. Yu et al. found a significant linear relationship between CPB duration and plasma IL-6 concentrations, but not with cross-clamp time. ⁹ Similarly, Safaric et al. found TNF-α and IL-8 levels correlated with bypass duration and systemic inflammatory/multi-organ dysfunction syndromes, though no relationship was found with IL-1b or IL-6 levels. ¹⁰

The role of CPB and cross-clamp durations in predicting postoperative complications remains debated. While previous studies, such as Pahwa et al., have explored the impact of CPB and cross-clamp durations on postoperative complications, our findings provide robust evidence that elevated Delta Neutrophil Index (DNI) levels, particularly during the intraoperative and postoperative periods, are strongly associated with mortality, emphasizing DNI’s potential as a dynamic marker for assessing systemic inflammation and its link to adverse outcomes. Hess et al. identified CPB times exceeding 150 min as a predictor of major gastrointestinal complications.^11,12 Hess et al. found CPB times significantly longer in CABG patients with gastrointestinal complications compared to those without, though this was not observed in valve replacement surgeries. ¹¹ CPB duration has also been associated with non-surgical blood loss and prolonged intubation, with CPB being the sole intraoperative factor linked to increased respiratory failure risk. ¹³ In alignment with previous research linking prolonged CPB duration to increased postoperative complications, our study identifies extended CPB durations and higher DNI levels as critical predictors of mortality, emphasizing the role of DNI as a complementary tool in assessing the risk of respiratory failure and other complications. Additionally, CPB has been implicated in “pump-related ARDS,” with neutrophil entrapment in pulmonary capillaries contributing to postoperative pulmonary complications.^14–16 Renal dysfunction was found to be associated with prolonged durations of cardiopulmonary bypass, particularly in cases where CPB time exceeded 3 hours, indicating an elevated risk. ¹⁷

Neutrophils, critical cells in innate immunity, mediate tissue damage during ischemia-reperfusion injury. ¹⁸ As demonstrated in Tables 2 and 5, at the Pre-CPB time point, neutrophil counts were significantly lower, while platelet counts were higher, in the Non-Ex group compared with the Ex group—a difference that persisted postoperatively. Several physiological factors may explain this discrepancy. Patients who ultimately survived likely had a more balanced preoperative inflammatory status and less bone marrow activation, resulting in lower circulating immature granulocyte levels at baseline. Conversely, Ex patients may have experienced subclinical preoperative stress or systemic inflammation leading to increased myeloid activation and early neutrophil mobilization. Since the mobilization of immature granulocytes from the bone marrow is a gradual process occurring over several hours, elevated pre-CPB counts in the Ex group likely reflect preexisting proinflammatory activation rather than an acute intraoperative response. This finding reinforces the importance of baseline hematologic status as a determinant of postoperative inflammatory trajectories and outcomes. Echoing the findings of Nteliopoulos et al. (2022), who highlighted the critical role of neutrophils in ischemia-reperfusion injury, our study confirms the significant relationship between elevated DNI and postoperative mortality, suggesting that DNI serves as a powerful prognostic marker, directly reflecting the degree of systemic inflammation and immune activation during CPB. Patients with high DNI levels had poorer postoperative outcomes than those with lower DNI. The significant relationship between inflammatory responses and cardiac surgery outcomes supports the development of objective inflammatory markers for risk stratification. ¹⁹ Previous studies have demonstrated DNI’s value in predicting 30-days mortality in STEMI patients and as a diagnostic marker for severe sepsis and septic shock (DNI >6.5%) within 24 h of ICU admission.^20,21 Similar to Bilgiç et al. (2025) and Kong et al. (2017), who demonstrated the utility of DNI in predicting 30-days mortality in STEMI patients, our study extends this finding by establishing DNI as a predictive marker for early postoperative mortality following CPB, highlighting its potential to guide perioperative management and improve patient outcomes in the cardiac surgery setting.^20,22 While CPB-induced inflammation is sterile in nature, it shares pathophysiological features with infectious responses such as neutrophil mobilization and immature granulocyte release.^23–26

Surgical factors such as trauma, ischemia, and CPB exacerbate inflammation. ²⁷ Platelet activation by heparin, hypothermia, and CPB further intensifies tissue damage. Cardiac surgery’s systemic inflammatory response is associated with adverse clinical outcomes, with SIRS observed in 96.2% of patients within the first 24 h postoperatively. ²⁸ DNI’s ability to predict systemic inflammation outcomes highlights its role as a valuable prognostic marker. ²⁹ Existing risk prediction models such as EuroSCORE II, STS score, and Japan’s National Clinical Database (NCD) are well-established tools for estimating perioperative mortality in cardiac surgery. From an implementation standpoint, we propose integrating DNI into the intraoperative checklist at predefined time points (induction, 5, 45, and 90 min after CPB initiation, and immediately post-CPB), using our laboratory’s action threshold of IG% > 1.5 to trigger predefined responses—e.g., closer hemodynamic and temperature optimization with the anesthesia–perfusion team, lung-protective ventilation adjustments, and intensified early postoperative monitoring (arterial blood gas frequency, renal-protective bundle). However, these models primarily rely on preoperative variables and do not dynamically reflect intraoperative or real-time inflammatory changes. In contrast, DNI provides perioperative insight into the patient’s evolving systemic inflammatory response, which may not be captured by static scoring systems. In clinical scenarios where patients present with low EuroSCORE II but develop excessive inflammatory responses during CPB—as evidenced by elevated DNI—DNI could serve as a real-time “warning signal” for postoperative deterioration. Although our study did not include direct comparisons with EuroSCORE II or STS risk models, the significant association between DNI and mortality underscores its potential as a complementary biomarker, especially in cases where traditional models may underestimate intraoperative or immunologic risk. As an easily measurable and dynamic biomarker, DNI can be incorporated into routine clinical practice to enhance individualized patient management, potentially improving overall surgical outcomes. The parallel elevation of postoperative CRP and intraoperative DNI supports the premise that DNI is not only a prognostic marker, but also a dynamic and practical tool for real-time monitoring of systemic inflammation during CPB.

DNI should complement—not replace—clinical assessment and established risk factors. DNI could help identify patients without high preoperative risk but with poor postoperative recovery or increased morbidity and mortality risk. This study observed significantly higher morbidity and mortality in the high DNI group compared to the low DNI group.

Compared to prior studies focusing on long-term mortality, this study emphasizes short-term outcomes using DNI as a marker. Patients with normal DNI levels intraoperatively had better survival outcomes, underscoring its importance in risk classification. Notably, this is the first study to evaluate serial DNI measurements during CPB, filling a gap in the literature.

Despite limitations such as its retrospective design and single-center scope, this study analyzed robust data from 245 patients, providing meaningful insights. DNI is a strong predictor of mortality in CPB patients, significantly correlating with intraoperative and short-term outcomes. These findings highlight its utility in risk assessment and management of complications that increase postoperative mortality. Prospective, multicenter validation with protocolized DNI-guided actions will clarify whether acting on intraoperative thresholds can translate prognostic signal into outcome benefit.

Limitations of the study

Although this study included a relatively large sample size of 245 patients, several limitations should be acknowledged. First, the retrospective and single-center nature of the design inherently limits the generalizability of the findings. Institutional practices, surgical expertise, patient selection, and perioperative management protocols may vary across centers, potentially influencing DNI dynamics and clinical outcomes. Second, subgroup analyses for specific high-risk populations—such as patients with advanced heart failure, severely reduced left ventricular ejection fraction, or elevated EuroSCORE—could not be adequately performed due to the lack of granularity in risk stratification and relatively small subgroup sizes, which may have underpowered such comparisons.

Third, although in-hospital mortality was clearly defined as the primary endpoint, no stratification was made according to specific causes of death (e.g., sepsis, multiorgan failure, or cardiovascular collapse). This limits the ability to assess whether elevated DNI is more strongly associated with certain mortality etiologies. Fourth, perioperative confounding factors that may influence systemic inflammation—such as preoperative infections, steroid or immunosuppressive therapy, perioperative transfusion burden, intraoperative hypotension, or postoperative renal replacement therapy—were not systematically controlled or adjusted for in the analysis, which may have impacted DNI values and outcomes.

Fifth, although multivariate logistic regression was used to mitigate potential confounding, the observational design precludes establishing causality. The association between DNI and mortality may be influenced by unmeasured variables that were not accounted for, including cytokine profiles or genetic predispositions to exaggerated inflammatory responses. Sixth, DNI was measured at fixed intraoperative time points, but individual variability in inflammatory kinetics may require more continuous or patient-specific measurement protocols to optimize its prognostic relevance.

Lastly, external validation in prospective, multicenter cohorts is essential to confirm the reproducibility and clinical utility of DNI as a prognostic marker. Future studies incorporating dynamic modeling, time-dependent covariates, and mechanistic laboratory correlations (e.g., IL-6, CRP, procalcitonin) would provide deeper insights into the inflammatory pathways linking DNI elevation to adverse surgical outcomes.

Conclusions

The Delta Neutrophil Index is a powerful prognostic marker for mortality in patients undergoing cardiopulmonary bypass, strongly associated with elevated intraoperative and postoperative mortality risks. By capturing CPB-induced inflammatory burden, DNI enables early identification of high-risk patients and guides tailored interventions. Integrating DNI into clinical practice could significantly improve surgical outcomes and reduce mortality.