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Original Article
Infection Association between 30-day mortality and serially measured hematologic markers in patients with septic shock in South Korea
Acute and Critical Care 2026;41(3):564-577.
DOI: https://doi.org/10.4266/acc.000858
Published online: August 31, 2026

Department of Anesthesiology and Pain Medicine, Anesthesia and Pain Research Institute, Yonsei University College of Medicine, Seoul, Korea

Corresponding author: Sungwon Na Department of Anesthesiology and Pain Medicine, Anesthesia and Pain Research Institute, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea Tel: +82-2-2228-2420, Fax: +82-2-2227-7897, Email: nswksj@yuhs.ac
• Received: January 28, 2026   • Revised: June 5, 2026   • Accepted: July 8, 2026

© 2026 The Korean Society of Critical Care Medicine

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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  • Background
    Hematologic markers derived from complete blood counts have emerged as potential cost-effective prognostic indicators. Sepsis-induced left ventricular diastolic dysfunction (LVDD) is associated with increased mortality rates. We evaluated the predictive value of serially measured hematologic markers for 30-day mortality and their relationship with LVDD in patients with septic shock.
  • Methods
    This retrospective cohort study analyzed adult patients diagnosed with septic shock in the emergency department of a university hospital between March 2014 and May 2018. Serial neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio, and lymphocyte-to-monocyte ratio (LMR) values were recorded from admission to day 5. The relationship between hematologic markers and LVDD was evaluated in patients who underwent transthoracic echocardiography (TTE).
  • Results
    In total, 431 patients were included, with a 30-day mortality rate of 12.5%. The NLR on day 5 and NLR day 5/day 1 ratio had the highest predictive performance (area under the receiver operating characteristic curve [AUROC], 0.743 and 0.746, respectively). Similarly, the LMR on day 5 and the LMR day 5/day 1 ratio showed strong prognostic value (AUROC, 0.707 and 0.753, respectively). In the subgroup analysis of 204 patients who underwent TTE, a higher NLR at admission was significantly associated with LVDD (odds ratio, 1.016; 95% CI, 1.000–1.031; P=0.043).
  • Conclusions
    Serial measurements of the NLR and LMR showed better predictive value for 30-day mortality in patients with septic shock than measurements from a single time point. These findings support the use of hematologic markers as adjunctive tools for risk stratification of patients with septic shock.
  • Key Words: left ventricular diastolic dysfunction; mortality; neutrophil-to-lymphocyte ratio; septic shock
Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. Septic shock is a subset of sepsis characterized by profound circulatory and cellular/metabolic abnormalities that substantially increase mortality [1]. Sepsis and septic shock are severe medical conditions that remain leading causes of death. In sepsis, several serum inflammatory biomarkers such as the white blood cell (WBC) count, C-reactive protein (CRP), and procalcitonin have been used to assess disease severity and predict mortality [2-5]. However, the predictive roles of the WBC count and CRP level remain controversial and are easily affected by non-infectious factors [3]. Procalcitonin has shown good predictive ability; however, measuring it is expensive and difficult to access routinely [5].
Neutrophils play a pivotal role in the hyperinflammation of sepsis. Excessive neutrophil levels can cause tissue damage and organ dysfunction in sepsis, and they can also affect coagulation through platelet activation and consumption; therefore, patients often develop thromboembolic complications or multiple organ failure [6,7]. Lymphocyte exhaustion in patients with sepsis is associated with poor outcomes due to immunosuppression [8]. Additionally, monocytes play an important role in the inflammatory response, and their activation is associated with several inflammatory diseases [9]. The combination of increased neutrophil and monocyte counts and decreased lymphocyte levels can indicate a dysregulated immune reaction in the context of sepsis. Therefore, several blood leukocyte ratios and hematologic markers derived from complete blood counts have been evaluated as rapid, cost-effective, and widely accessible predictors of sepsis outcomes [10,11]. Previous studies have mainly focused on single baseline measurements. The prognostic significance of serial changes during the first few days of septic shock remains unclear. Because immune-inflammatory responses and treatment effects evolve dynamically during the initial treatment period, important clinical trajectories, including deterioration or recovery, often become apparent within the first few days after presentation. Evaluating dynamic changes during this period could provide prognostic information not captured by baseline measurements alone. Therefore, we investigated the association between 30-day mortality and hematologic markers—the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR)—serially measured during the first 5 days of septic shock. Additionally, we explored whether dynamic changes in those markers could provide complementary prognostic information beyond conventional risk indicators. Furthermore, as a secondary objective, we evaluated the relationship between blood leukocyte ratios at admission and left ventricular diastolic dysfunction (LVDD) assessed by transthoracic echocardiography (TTE).
This study was approved by the Institutional Review Board of Severance Hospital (No. 4-2019-0967). The requirement for informed consent was waived by the Board due to the retrospective design of the study.
Study Design and Patients
This single-center, retrospective cohort study analyzed data from patients aged ≥18 years who were diagnosed with septic shock in the emergency room of a university hospital between March 2014 and May 2018. Data were obtained from electronic medical records. The diagnostic criteria and management protocols at our hospital during this period were based on the 2012 Surviving Sepsis Campaign. Sepsis was defined as a systemic response to infection manifested by two or more systemic inflammatory response syndrome criteria. Septic shock was defined as sepsis-induced hypotension despite adequate fluid resuscitation of more than 30 ml/kg. Hypotension was defined as a systolic blood pressure <90 mm Hg or a mean arterial blood pressure <65 mm Hg. Patients who met the criteria for septic shock were treated immediately with standardized antibiotics and fluid resuscitation, in accordance with the critical pathway protocol of our institution.
In the subgroup analysis of patients who underwent TTE, we used the algorithm for the diagnosis of LVDD proposed in the American Society of Echocardiography guidelines [12]. The following values measured using TTE were used to grade diastolic dysfunction: early diastolic transmitral flow velocity (E), ratio of early (E) to late (A) transmitral flow velocities (E/A), ratio of transmitral early diastolic velocity (E) to mitral annular early diastolic tissue velocity (e′) E/e′, septal e′ velocity, tricuspid regurgitation velocity, and left atrium volume index.
Demographics, the origin of sepsis, and antibiotic administration times were measured. Age-adjusted Charlson Comorbidity Index (CCI) [13,14] and Sequential Organ Failure Assessment (SOFA) scores were calculated to estimate the severity of the condition. The following outcomes were measured: intensive care unit (ICU) admission and duration, hospital stay, mechanical ventilation days, vasopressor-free days, and 30-day mortality.
The procalcitonin level, red blood cell distribution width (RDW), and lactate levels were recorded on the day of admission. Serially measured WBC counts, NLR, PLR, LMR, and CRP levels were collected from the day of hospital admission only until day 5 because data completeness beyond day 5 was inadequate. Additionally, later measurements might, in part, reflect the influence of interventions or complications not directly related to the underlying trajectory of sepsis.
Statistical Analyses
Continuous variables are presented as the mean and standard deviation, or median and interquartile range (IQR), as appropriate. Categorical variables are presented as frequencies and proportions. Intergroup comparisons were performed using an independent t-test or Mann-Whitney U-test for continuous variables and Fisher’s exact test or chi-square test for categorical variables. The Bonferroni correction was applied for multiple comparisons. To analyze changes in WBC counts, CRP levels, NLR, PLR, and LMR, linear mixed models were used to adjust the first measured values between the two groups. The first values of each parameter were used as covariates. Differences in baseline characteristics between the groups were adjusted by including baseline variables and those considered to be clinically relevant as covariates in the model.
Univariate and multivariate logistic regression analyses were conducted to evaluate how consecutively measured hematologic factors were associated with 30-day mortality. We used the multivariate analysis to adjust for sex, SOFA score, sepsis origin, age-adjusted CCI, and antibiotic administration time. Kaplan-Meier survival curves were generated, and differences between groups were analyzed using the log-rank test. To account for the longitudinal aspect of the serial biomarker measurements and mitigate potential survivor bias, additional time-dependent Cox proportional hazards regression analyses were performed using predefined worsening patterns of serial hematologic markers. Clinical worsening was defined as an incremental NLR change (NLR day 5/day 1 >1) or a decremental LMR change (LMR day 5/day 1 <1). Those binary worsening indicators were then evaluated using Cox regression models. The area under the receiver operating characteristic curve (AUROC) and 95% CIs were calculated to measure the ability of the serially measured NLR and LMR values to predict 30-day mortality. The AUROC was also calculated to determine how well the RDW, lactate level, and SOFA scores on day 1 predicted 30-day mortality. The optimal cutoff value was determined by maximizing the Youden index. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) analyses were conducted to assess the incremental prognostic value of the hematologic markers beyond established predictors. In the subgroup analysis for LVDD, we used univariate and multivariate logistic regression analyses adjusted for age, sex, and a history of hypertension, diabetes, heart failure, atrial fibrillation, or coronary artery occlusive disease.
All analyses were performed using SAS statistical software version 9.4 (SAS Institute Inc.) or IBM SPSS version 25 (IBM Corp.). A P-value <0.05 was considered statistically significant.
Between March 2014 and May 2018, 491 patients were diagnosed with septic shock at the emergency room of a tertiary hospital in Seoul, South Korea, of whom 431 patients were included in this analysis (Figure 1). The baseline characteristics of the study groups are presented in Table 1. The median age of the patients was 70.0 years (IQR, 58.0−77.0), and 44.8% of the patients were male. The most common origins of sepsis were urinary tract infections (45.2%), intra-abdominal infections (21.3%), respiratory tract infections (18.3%), soft tissue infections (7.7%), and other unknown origins (7.5%). The median age-adjusted CCI was 4.0 (IQR, 2.0−6.0). The median SOFA score was 10.0 (IQR, 8.0−13.0). The median time to the administration of antibiotics was 54.5 minutes (IQR, 37.5−72.0). In total, 164 patients (38.1%) were admitted to the ICU, and 79 patients (18.3%) underwent mechanical ventilation. Overall, 54 patients (12.5%) died within 30 days of admission and were categorized as the non-survivor group. Of the 54 non-survivors, 26 died before day 5.
In the demographic findings, age, SOFA scores, and age-adjusted CCI scores were significantly higher in the non-survivors than the survivors (Table 2). ICU admission and mechanical ventilation rates were also higher in non-survivors. The number of patients with available serial hematologic measurements progressively decreased over time because of early mortality, clinical improvement with ward transfer or discharge, and incomplete laboratory follow-up. Table 3 presents the values of several biomarkers in the survivor and non-survivor groups. Compared with the survivor group, the non-survivor group showed significantly higher lactate levels (1.75 [1.10−2.50] vs. 5.25 [3.60−9.30]; P<0.001) and RDW (13.90 [13.0−14.90] vs. 15.70 [14.10−16.80]; P<0.001) at admission. The serially measured CRP level, CRP day 5/day 1 ratio, and percentage of incremental CRP change (CRP day 5/day 1 >1) showed no significant differences between the groups. The absolute WBC count was higher in the non-survivor group on day 3. However, the WBC day 5/day 1 ratio and percentage of incremental WBC change (WBC day 5/day 1 >1) did not differ significantly between the groups. The non-survivor group showed a higher NLR on days 3, 4, and 5 than the survivor group. The NLR day 5/day 1 ratio and percentage of incremental NLR change (NLR day 5/day 1 >1) were also higher in the non-survivor group. The PLR showed no significant differences between the groups during 5 consecutive days. The PLR day 5/day 1 ratio and percentage of incremental PLR change (PLR day 5/day 1 >1) also showed no significant differences between the groups. The LMR was lower in the non-survivor group on days 4 and 5. The LMR day 5/day 1 ratio was lower, and the proportion of patients with decremental LMR changes was higher in the non-survivor group. To compare the changes in parameters between the groups, we created a linear mixed model after adjusting for differences between the groups in baseline characteristics and factors considered clinically relevant. Sex, origin of sepsis, SOFA score, age-adjusted CCI, and antibiotic administration time were included as fixed effects. As shown in Figure 2, we found significant differences between the groups in the WBC count, NLR, and LMR over time (P<0.001, P=0.001 and P<0.001, respectively).
The multivariate regression analysis showed that the NLR on day 5, incremental NLR change, PLR on days 2 and 5, LMR on days 1 and 2, LMR day 5/day 1 ratio, and decremental LMR change (LMR day 5/day 1 <1) were associated with 30-day mortality after adjusting for sex, SOFA score, sepsis origin, age-adjusted CCI, and antibiotic administration time (Table 4). Procalcitonin, RDW, and lactate levels measured on day 1 were also associated with 30-day mortality in the adjusted model. A significant gradient in 30-day mortality was observed between patients with incremental and decremental LMR changes (log-rank P=0.004) (Figure 3). However, the difference between incremental and decremental NLR changes was not significant (log-rank P=0.08). A day 5 landmark analysis was performed for the NLR and LMR to assess potential survivor bias associated with the use of day 5 measurements. Patients who died before day 5 (n=26) or who lacked day 5 hematologic measurements were excluded, and the survival time origin was reset to day 5. The direction of the associations remained unchanged (log-rank P=0.12 for NLR and P=0.005 for LMR) (Supplementary Figure 1). In additional time-dependent Cox proportional hazards regression analyses using predefined worsening patterns of serial hematologic markers, incremental NLR change (NLR day 5/day 1 >1) and decremental LMR change (LMR day 5/day 1 <1) were both independently associated with increased 30-day mortality (hazard ratio [HR] 3.695, 95% CI 1.741–7.843, P<0.001; HR 3.597, 95% CI 1.577–8.207, P=0.002, respectively).
Figure 4 and Table 5 show how well serial values of the NLR and LMR and initial lactate, RDW, and SOFA scores predicted 30-day mortality. The predictive value of the NLR and LMR for 30-day mortality increased over time. The NLR measured on day 5 demonstrated the best predictive performance (AUROC, 0.743; 95% CI, 0.615−0.872), and its optimal cutoff value was 21.69 (sensitivity, 64.0%; specificity, 88.4%). The AUROC of the NLR day 5/day 1 ratio was 0.746 (95% CI, 0.649–0.843), with an optimal cutoff value of 0.695 (sensitivity, 76.0%; specificity, 67.4%). The AUROC for incremental change in the NLR was 0.688 (95% CI, 0.571−0.805). The LMR showed a performance pattern similar to that of the NLR. The LMR on day 5 showed the best performance among the first 5 days. The AUROC was 0.707 (95% CI, 0.583−0.831), with an optimal cutoff value of 1.105 (sensitivity, 56.0%; specificity, 85.1%). The AUROC of the LMR day 5/day 1 ratio was 0.753 (95% CI, 0.673−0.833), with an optimal cutoff value of 1.050 (sensitivity, 92.0%; specificity, 55.8%). The AUROC of decremental LMR change was 0.701 (95% CI, 0.604−0.798). The RDW and lactate levels measured on day 1 showed AUROCs of 0.734 (95% CI, 0.662−0.806) and 0.845 (95% CI, 0.752−0.938), respectively. The AUROC of the day 1 SOFA score was 0.744 (95% CI, 0.671–0.818). Additional analyses using the NRI and IDI suggested that the NLR day 5 and dynamic LMR indices might provide incremental prognostic information beyond the SOFA score and lactate level (Supplementary Table 1).
Predictors of LV Diastolic Dysfunction
Among the 431 patients with septic shock, 238 underwent TTE to evaluate their cardiac function, as prescribed by the attending physician. The performance of TTE was associated with reduced 30-day mortality after adjusting for sex, SOFA score, sepsis origin, age-adjusted CCI, and antibiotic administration time (odds ratio [OR], 0.357; 95% CI, 0.168−0.756; P=0.007; data not shown). Among the 238 TTE results, 34 were inconclusive in identifying diastolic function. Therefore, 204 patients were divided into two groups according to their LV diastolic function: 83 patients had normal LV diastolic function, and 121 were diagnosed with LVDD (Supplementary Figure 2). The baseline demographics and laboratory data are presented in Supplementary Table 2. The median age of the patients in the LVDD group was higher than that of the patients in the normal group. The incidences of male sex, hypertension, diabetes, atrial fibrillation, and coronary artery occlusive disease were higher in the LVDD group than in the normal LV diastolic function group. However, patient outcomes did not differ significantly between the groups.
We compared laboratory findings between the normal LV diastolic function and LVDD groups (Table 6). Among the inflammatory markers, the NLR and CRP levels on the day of admission were significantly higher in the LVDD group (P=0.046 and P=0.010, respectively). No significant difference between the groups was observed in the WBC count, PLR, LMR, RDW, or procalcitonin levels.
The multivariate analysis of the biomarkers showed that the NLR and CRP levels were associated with LVDD after adjusting for age, sex, hypertension, diabetes, heart failure, atrial fibrillation, and coronary artery occlusive disease (OR 1.016, 95% CI 1.000−1.031, P=0.043; OR 1.003, 95% CI 1.000−1.005, P=0.041; respectively) (Table 7). A receiver operating characteristic (ROC) curve was constructed to determine the NLR required to detect LVDD. The AUROC of the NLR was 0.585 (95% CI, 0.506−0.664), and the cutoff value was 18.07 (sensitivity, 54.2%; specificity, 63.9%) (data not shown). The AUROC of the CRP level was 0.610 (95% CI, 0.51−0.66), and its cutoff value was 153.25 (sensitivity, 54.2%; specificity, 68.7%) (data not shown).
In this study, we focused on dynamic hematologic changes during the first 5 days of septic shock and evaluated their incremental prognostic value using serial measurements and reclassification analyses. We found that dynamic changes in the NLR and LMR during the early treatment period were more strongly associated with 30-day mortality than initial measurements alone. These findings suggest that persistent abnormalities or unfavorable trajectories of hematologic markers during the early treatment period are more informative for risk stratification than isolated baseline values. Although previous studies have primarily evaluated admission values, our findings suggest that hematologic trajectories during the first few days after presentation provide additional prognostic information for risk stratification.
The NLR reflects the balance between innate and adaptive immune responses and has been associated with poor outcomes in sepsis [15-18]. However, most previous studies focused on single baseline measurements, and the optimal prognostic cutoff value remained inconsistent across studies. In this study, the NLR on day 5 and the ratio of the NLR between day 5 and day 1 showed the strongest prognostic performance among the evaluated hematologic markers. In contrast, the NLR measured on day 1 did not differ significantly between the survivor and non-survivor groups. A persistent or incrementally increased NLR during the early phase of septic shock might reflect sustained dysregulated inflammatory responses despite initial treatment, which could explain the higher prognostic performance of the NLR on day 5 and incremental NLR change observed in this study.
A low LMR, reflecting decreased lymphocyte counts and increased monocyte counts, might be associated with a poor prognosis in sepsis because it indicates persistent inflammation and immune dysregulation [19-21]. In our study, a decremental change in the LMR was significantly associated with 30-day mortality. Additionally, the LMR measured on day 5 and the ratio of the LMR between days 5 and 1 showed the highest ability to predict 30-day mortality (AUROC of 0.707 and 0.753, respectively). However, the LMR values measured on day 1 did not differ significantly between the survivors and non-survivors. Similarly, a decremental change in the LMR during the early phase of septic shock might reflect persistent immune dysregulation and ongoing systemic inflammation despite treatment. That could explain why the dynamic LMR indices showed stronger prognostic associations than single baseline measurements.
Although the predictive performance of serial NLR and LMR measurements was moderate, their prognostic ability was comparable to that of the SOFA score and RDW measured at admission. On the other hand, the lactate level demonstrated better predictive performance than the hematologic markers evaluated in this study. Therefore, serial NLR and LMR measurements should not be interpreted as replacements for established prognostic markers, but rather as complementary indicators reflecting dynamic immune-inflammatory responses during the early phase of septic shock. In addition, the NRI and IDI analyses suggest that selected serial hematologic markers, particularly the NLR day 5 and dynamic LMR indices, provide incremental prognostic information beyond established predictors such as the SOFA score and lactate level. Given that these hematologic markers are inexpensive and routinely available in clinical practice, they could serve as supplementary tools for prognostic assessment in patients with septic shock.
In contrast, the PLR showed little prognostic value in this study, which is consistent with previous reports in septic shock [22,23]. Sepsis-associated thrombocytopenia, antibiotic-related platelet suppression, and platelet transfusions during admission might have influenced the PLR values and reduced their prognostic utility [24,25]. Meanwhile, the RDW measured at admission demonstrated prognostic value comparable to that reported in previous studies of septic shock [26-29].
Because sepsis-associated cardiac dysfunction is associated with adverse outcomes and can influence hemodynamic management, we also evaluated the relationship between the leukocyte ratios and LVDD [30-35]. We found that patients with LVDD had significantly higher NLR values than those without LVDD, and the NLR remained independently associated with LVDD after adjustment for conventional cardiovascular risk factors. These findings suggest that a greater inflammatory burden might be associated with diastolic dysfunction during septic shock. Although the underlying mechanisms remain uncertain, inflammatory cytokine activation and oxidative stress might contribute to myocardial dysfunction in this setting [36]. However, the predictive performance of the NLR for LVDD was modest, and its utility for identifying patients with LVDD requires further investigation.
This study has some limitations. First, it was conducted retrospectively at a single tertiary center, which limits the generalizability of the results. However, all patients in this study were enrolled using the same diagnostic processes and received consistent critical care management according to our center’s protocol, including fluid management, administration of empirical antibiotics, and vasopressor use, which might have made it possible to maintain homogeneity in our cohort. Second, septic shock was diagnosed and managed according to the 2012 Surviving Sepsis Campaign guidelines [37]. In one study, 55.8% of patients diagnosed with septic shock according to the Sepsis-2 definition met the Sepsis-3 criteria [38]. Another study reported severe illness and increased mortality in the Sepsis-2 patient group [39]. Therefore, diagnosing and managing septic shock using more recent guidelines could produce different outcomes. Third, although we adjusted risk factors for predicting 30-day mortality, other confounding factors—such as corticosteroid use, malignancy, hematologic disorders, and chemotherapy—can separately affect leukocyte counts. Fourth, because several analyses were based on day 5 hematologic measurements, patients who died before day 5 or who lacked day 5 laboratory data were excluded from the landmark analysis. Although this approach was used to reduce potential survivor bias, it might have preferentially included a survivor population with relatively less severe conditions. Therefore, caution is warranted when generalizing the prognostic performance of serial hematologic markers to patients with rapidly progressive septic shock. In addition, laboratory data obtained after day 5 were less consistently available. Therefore, sensitivity analyses including later time points were not performed, which might have increased the risk of selection bias and reduced statistical reliability. Fifth, because the assessment of LVDD was performed after the incidence of septic shock, whether LVDD was pre-existing or induced by sepsis remains uncertain. However, after adjusting for pre-existing risk factors for LVDD, the NLR was significantly associated with the presence of LVDD. Therefore, considering that the NLR is associated with severe inflammatory reactions, we cannot rule out LVDD induced by acute sepsis-related stress conditions. Sixth, the timing of LVDD assessment using TTE was inconsistent among patients. This might have imparted the low ability of the NLR on day 1 to predict LVDD. Finally, the decision to perform TTE was at the clinician’s discretion. Therefore, the observed association between the NLR and LVDD should be interpreted with caution due to potential selection bias.
In conclusion, our findings suggest that monitoring early hematologic trajectories during the first 5 days of septic shock provides prognostic information beyond single baseline measurements. Serial assessment of the NLR and LMR might therefore serve as a practical adjunctive tool for risk stratification during the early treatment of septic shock. Patients with a higher NLR might require particularly close monitoring and evaluation for LVDD to ensure appropriate volume management. However, given their moderate predictive performance, these markers should be considered as adjunctive tools, rather than standalone predictors. Further prospective, multicenter studies are required to validate these findings and explore potential interventions based on leukocyte ratios.
▪ Serial measurements of the neutrophil-to-lymphocyte ratio (NLR) and lymphocyte-to-monocyte ratio (LMR) showed better predictive value than measurements from a single time point for 30-day mortality in patients with septic shock.
▪ Incremental NLR and decremental LMR changes are strong prognostic indicators.
▪ Elevated NLR at admission was associated with left ventricular diastolic dysfunction, suggesting a potential link between systemic inflammation and cardiac dysfunction in septic shock.

CONFLICT OF INTEREST

No potential conflicts of interest relevant to this article was reported.

FUNDING

None.

ACKNOWLEDGMENTS

None.

AUTHOR CONTRIBUTIONS

Conceptualization: SN. Data curation: SJ. Formal analysis: SJ. Methodology: JK. Project administration: JK. Visualization: SJ, JK. Writing – original draft: SJ, JK. Writing – review & editing: JK, SN. All authors read and agreed to the published version of the manuscript.

Supplementary materials can be found via https://doi.org/10.4266/acc.000858.
Supplementary Table 1.
Incremental prognostic value of hematologic markers assessed by NRI and IDI analyses
acc-000858-Supplementary-Table-1.pdf
Supplementary Table 2.
Demographics and laboratory findings of the enrolled patients on admission
acc-000858-Supplementary-Table-2.pdf
Supplementary Figure 1.
Day 5 landmark analysis of neutrophil-to-lymphocyte ratio (NLR) and lymphocyte-to-monocyte ratio (LMR) to assess potential survivor bias.
acc-000858-Supplementary-Figure-1.pdf
Supplementary Figure 2.
Flow diagram for analyzing the relationship between laboratory markers and left ventricular diastolic dysfunction. TTE: transthoracic echocardiography.
acc-000858-Supplementary-Figure-2.pdf
Figure 1.
Study flow diagram. ER: emergency room; NLR: neutrophil-to-lymphocyte ratio; WBC: white blood cell.
acc-000858f1.jpg
Figure 2.
Changes in white blood cell (WBC), neutrophil-to-lymphocyte ratio (NLR), C-reactive protein (CRP), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR) during the first 5 consecutive days after septic shock diagnosis. Values are presented as the least squares means with standard error values. The P-value from a linear mixed model was used to compare changes in each parameter over time between the survivor and non-survivor groups.
acc-000858f2.jpg
Figure 3.
Thirty-day survival curves according to incremental or decremental neutrophil-to-lymphocyte ratio (NLR; A) and lymphocyte-to-monocyte ratio (LMR; B) changes.
acc-000858f3.jpg
Figure 4.
Receiver operating characteristic curve analyses of the ability of serial neutrophil-to-lymphocyte ratio (NLR; A) and lymphocyte-to-monocyte ratio (LMR; B) values and the NLR and LMR day 5/day 1 ratios to predict 30-day mortality in patients with septic shock.
acc-000858f4.jpg
Table 1.
Baseline characteristics of all enrolled patients
Variable Value
All patients 431
Age (yr) 70.0 (58.0−77.0)
Male sex 193 (44.8)
BMI (kg/m2) 22.67 (20.20−24.99)
Comorbidity
 Hypertension 251 (58.2)
 Diabetes 148 (34.3)
 Heart failure 21 (4.9)
 Atrial fibrillation 52 (12.1)
 Coronary artery occlusive disease 53 (12.3)
 Cerebrovascular accident 110 (25.5)
 Chronic kidney disease 73 (16.9)
 Malignancy 128 (29.7)
 Chronic liver disease 41 (9.5)
 Chronic obstructive pulmonary disease 44 (10.2)
Sepsis origin
 Respiratory 79 (18.3)
 Urinary tract 195 (45.2)
 Intra-abdominal infection 92 (21.3)
 Soft tissue infection 33 (7.7)
 Other/unknown 32 (7.5)
Age-adjusted CCI 4.0 (2.0−6.0)
SOFA score 10.0 (8.0−13.0)
Antibiotic administration time (min) 54.5 (37.5−72.0)
Outcome
 Hospital day 19.0 (9.0−30.0)
 30-Day mortality 54 (12.5)
 Vasopressor-free day 9.0 (5.0−18.0)
 ICU admission 164 (38.1)
 ICU day (n=164) 4.0 (2.0−8.0)
 Mechanical ventilation 79 (18.3)
 Mechanical ventilation day (n=79) 6.0 (2.0−12.0)

Values are presented as median (interquartile range) or number (%).

BMI: body mass index; CCI: Charlson Comorbidity Index; SOFA: Sequential Organ Failure Assessment; ICU: intensive care unit.

Table 2.
Demographics of survivors and non-survivors
Variable Survivor (n=377) Non-survivor (n=54) P-value
Age (yr) 69.0 (56.0−77.0) 75.5 (64.0−80.0) 0.001
Male sex 170 (45.1) 23 (42.6) 0.842
Comorbidity
 Hypertension 215 (57.0) 36 (66.7) 0.232
 Diabetes 127 (33.7) 21 (38.9) 0.549
 Heart failure 18 (4.8) 3 (5.6) >0.999
 Atrial fibrillation 42 (11.1) 10 (18.5) 0.182
 Coronary artery occlusive disease 46 (12.2) 7 (13.0) >0.999
 Cerebrovascular accident 95 (25.2) 15 (27.8) 0.811
 Chronic kidney disease 64 (17.0) 9 (16.7) >0.999
 Malignancy 110 (29.2) 18 (33.3) 0.641
 Chronic obstructive pulmonary disease 37 (9.8) 7 (13.0) 0.635
Sepsis origin 0.369
 Respiratory 68 (18.0) 11 (20.4)
 Urinary tract 176 (46.7) 19 (35.2)
 Intra-abdominal infection 76 (20.2) 16 (29.6)
 Soft tissue infection 30 (8.0) 3 (5.6)
 Other/unknown 27 (7.2) 5 (9.3)
SOFA score 8.0 (6.0−10.0) 12.0 (8.0−14.0) <0.001
Age-adjusted CCI 4.0 (2.0−6.0) 5.0 (4.0−6.0) 0.005
Antibiotic administration time (min) 56.0 (36.0−76.0) 57.5 (43.0−77.0) 0.341
Outcome
 Hospital day 14.0 (9.0−24.0) 3.5 (2.0−13.0) <0.001
 Vasopressor-free day 11.0 (6.0−19.0) 0 (0−2.0) <0.001
 ICU admission 130 (34.5) 34 (63.0) <0.001
 ICU day (n=164) 4.0 (2.0−7.0) 3.0 (2.0−9.0) 0.413
 Mechanical ventilation 45 (11.9) 34 (63.0) <0.001
 Mechanical ventilation day (n=79) 8.0 (5.0−18.0) 2.0 (2.0−8.0) 0.001

Values are presented as median (interquartile range) or number (%).

SOFA: Sequential Organ Failure Assessment; CCI: Charlson Comorbidity Index; ICU: intensive care unit.

Table 3.
Systemic inflammatory biomarkers in survivors and non-survivors
Variable All patients (n=431) Survivor (n=377) Non-survivor (n=54) P-value
Procalcitonin day 1 (ng/ml) 7.63 (1.27−39.74) 7.01 (1.26−38.81) 16.88 (1.29−48.43) 0.392
Lactate day 1 (mmol/L) 1.80 (1.20−3.40) 1.75 (1.10−2.50) 5.25 (3.60−9.30) <0.001
RDW day 1 (%) 14.0 (13.10−15.35) 13.90 (13.0−14.90) 15.70 (14.10−16.80) <0.001
CRP (mg/L)
 Day 1 (431) 131.90 (56.40−217.0) 130.2 (56.30−217.60) 136.80 (63.50−214.9) >0.999
 Day 2 (57) 196.90 (131.90−277.80) 212.75 (150.40−285.30) 147.60 (70.50−247.10) 0.601
 Day 3 (121) 174.20 (105.40−252.60) 174.70 (106.85−252.90) 96.40 (71.60−217.80) >0.999
 Day 4 (157) 99.0 (55.20−146.90) 97.90 (55.20−140.70) 127.25 (87.35−182.0) 0.807
 Day 5 (119) 53.20 (25.50−97.45) 52.60 (25.30−97.45) 66.15 (34.45−132.25) >0.999
 Day 5/day 1 (119) 0.39 (0.23−0.85) 0.37 (0.21−0.84) 0.59 (0.34−1.30) 0.241
 Day 5/day 1 >1 (119) 21 (17.6) 19 (17.1) 2 (25.0) 0.630
WBC (×109/L)
 Day 1 (431) 13.20 (7.28−18.75) 13.20 (7.32−18.62) 13.09 (6.60−21.96) >0.999
 Day 2 (421) 15.77 (9.98−22.26) 15.90 (10.42−22.13) 14.20 (7.10−23.87) >0.999
 Day 3 (376) 13.04 (8.56−18.60) 12.69 (8.51−18.06) 18.50 (9.51−26.71) 0.014
 Day 4 (321) 10.44 (6.95−15.03) 10.15 (6.95−14.94) 13.10 (8.07−25.65) 0.279
 Day 5 (272) 8.06 (5.39−12.07) 8.02 (5.29−11.62) 10.86 (6.19−22.29) 0.555
 Day 5/day 1 (272) 0.67 (0.41−1.11) 0.63 (0.41−1.07) 0.90 (0.54−1.26) 0.146
 Day 5/day 1 >1 (272) 79 (29.0) 68 (27.5) 11 (44.0) 0.134
NLR
 Day 1 (431) 15.70 (7.80−28.86) 15.70 (8.03−28.63) 15.74 (6.28−30.75) >0.999
 Day 2 (419) 20.04 (10.38−37.06) 20.52 (10.66−36.20) 19.72 (7.16−46.0) >0.999
 Day 3 (374) 15.57 (8.03−29.85) 14.74 (7.68−29.04) 25.98 (10.48−51.42) 0.040
 Day 4 (319) 9.86 (5.05−19.26) 9.55 (4.90−18.01) 21.12 (9.87−43.20) 0.003
 Day 5 (267) 6.68 (3.56−15.02) 6.26 (3.53−13.38) 25.17 (11.16−40.62) <0.001
 Day 5/day 1 (267) 0.47 (0.19−1.03) 0.42 (0.18−0.89) 1.52 (0.70−2.92) <0.001
 Day 5/day 1 >1 (267) 69 (25.8) 54 (22.3) 15 (60.0) <0.001
PLR
 Day 1 (431) 259.09 (148.78−446.06) 266.32 (155.76−449.68) 182.0 (111.26−344.12) 0.104
 Day 2 (419) 250.0 (143.67−407.04) 259.37 (150.94−400.0) 203.51 (77.42−546.88) >0.999
 Day 3 (374) 171.34 (110.61−300.0) 172.11 (112.29−300.0) 163.0 (78.87−250.39) >0.999
 Day 4 (319) 144.80 (87.72−244.95) 144.44 (86.54−243.75) 153.55 (90.0−263.33) >0.999
 Day 5 (267) 133.93 (90.77−234.83) 135.02 (92.94−232.95) 129.31 (87.18−341.30) >0.999
 Day 5/day 1 (267) 0.59 (0.31−1.01) 0.59 (0.30−1.01) 0.69 (0.41−1.33) 0.141
 Day 5/day 1 >1 (267) 70 (26.3) 61 (25.3) 9 (36.0) 0.359
LMR
 Day 1 (430) 2.05 (1.14−3.69) 1.96 (1.13−3.45) 3.0 (1.38−5.0) 0.160
 Day 2 (417) 1.50 (0.90−2.43) 1.47 (0.90−2.41) 1.65 (1.0−2.82) >0.999
 Day 3 (374) 1.78 (1.15−2.69) 1.78 (1.19−2.73) 1.63 (0.87−2.41) 0.317
 Day 4 (319) 2.13 (1.37−3.41) 2.18 (1.42−3.44) 1.31 (0.71−2.08) 0.019
 Day 5 (267) 2.10 (1.37−3.33) 2.13 (1.48−3.48) 1.04 (0.72−2.23) 0.003
 Day 5/day 1 (267) 1.08 (0.48−2.05) 1.18 (0.55−2.15) 0.45 (0.23−0.91) <0.001
 Day 5/day 1 <1 (267) 127 (47.6) 106 (43.8) 21 (84.0) <0.001

Values are presented as median (interquartile range) or number (%).

RDW: red blood cell distribution width; CRP: C-reactive protein; WBC: white blood cell count; NLR: neutrophil-to-lymphocyte ratio; PLR: platelet-to-lymphocyte ratio; LMR: lymphocyte-to-monocyte ratio.

P-values were adjusted using Bonferroni’s method.

Table 4.
Univariate and multivariate analyses of parameters for predicting 30-day mortality
Unadjusted model P-value Adjusted modela) P-value
NLR Day 1 1.004 (0.997−1.011) 0.280 1.003 (0.995−1.011) 0.427
Day 2 1.001 (0.998−1.003) 0.547 1.000 (0.996−1.004) 0.876
Day 3 1.001 (0.998−1.004) 0.388 0.999 (0.996−1.003) 0.677
Day 4 1.023 (1.009−1.036) 0.001 1.011 (0.996−1.026) 0.167
Day 5 1.050 (1.028−1.071) <0.001 1.043 (1.020−1.067) <0.001
Day 5/day 1 0.997 (0.974−1.020) 0.803 0.999 (0.976−1.023) 0.962
Day 5/day 1 >1 5.222 (2.220−12.285) <0.001 4.893 (1.870−12.806) 0.001
PLR Day 1 1.000 (0.999−1.001) 0.450 1.000 (1.000−1.001) 0.301
Day 2 1.000 (1.000−1.000) 0.717 1.000 (1.000−1.001) 0.041
Day 3 1.001 (1.000−1.002) 0.081 1.001 (1.000−1.002) 0.075
Day 4 1.001 (1.000−1.003) 0.036 1.002 (1.000−1.004) 0.067
Day 5 1.002 (1.001−1.004) 0.012 1.003 (1.001−1.006) 0.007
Day 5/day 1 1.142 (0.797−1.635) 0.470 1.069 (0.716−1.596) 0.745
Day 5/day 1 >1 1.660 (0.698−3.949) 0.252 1.573 (0.590−4.192) 0.365
LMR Day 1 1.052 (1.004−1.102) 0.035 1.066 (1.012−1.123) 0.015
Day 2 1.156 (1.046−1.279) 0.005 1.135 (1.023−1.259) 0.017
Day 3 0.972 (0.788−1.200) 0.792 1.086 (0.918−1.285) 0.336
Day 4 0.856 (0.650−1.128) 0.269 1.002 (0.824−1.219) 0.982
Day 5 0.581 (0.388−0.870) 0.008 0.689 (0.452−1.052) 0.085
Day 5/day 1 0.243 (0.107−0.553) 0.001 0.245 (0.097−0.620) 0.003
Day 5/day 1 <1 6.736 (2.244−20.215) 0.001 5.457 (1.724−17.277) 0.004
WBC (×109/L) Day 1 1.018 (0.989−1.048) 0.230 1.003 (0.972−1.035) 0.849
Day 2 1.002 (0.973−1.032) 0.895 0.992 (0.960−1.024) 0.613
Day 3 1.058 (1.027−1.090) <0.001 1.042 (1.004−1.081) 0.030
Day 4 1.050 (1.019−1.083) 0.001 1.023 (0.986−1.061) 0.233
Day 5 1.053 (1.008−1.099) 0.020 1.038 (0.988−1.090) 0.142
Day 5/day 1 0.897 (0.642−1.254) 0.524 0.836 (0.580−1.204) 0.336
Day 5/day 1 >1 2.068 (0.895−4.779) 0.089 1.985 (0.789−4.993) 0.145
CRP (mg/L) Day 1 1.000 (0.997−1.002) 0.962 0.998 (0.996−1.001) 0.285
Day 2 0.994 (0.986−1.001) 0.111 0.991 (0.979−1.002) 0.116
Day 3 1.000 (0.994−1.006) 0.991 0.997 (0.992−1.003) 0.403
Day 4 1.005 (0.998−1.012) 0.137 1.001 (0.993−1.010) 0.789
Day 5 1.007 (0.995−1.018) 0.272 1.002 (0.988−1.017) 0.747
Day 5/day 1 0.960 (0.713−1.293) 0.788 0.892 (0.602−1.323) 0.570
Day 5/day 1 >1 1.614 (0.302−8.615) 0.575 0.894 (0.131−6.092) 0.909
Procalcitonin (ng/ml) Day 1 1.001 (0.998−1.005) 0.472 0.995 (0.990−1.000) 0.046
RDW (%) Day 1 1.521 (1.306−1.771) <0.001 1.478 (1.246−1.753) <0.001
Lactate (mmol/L) Day 1 1.584 (1.342−1.869) <0.001 1.688 (1.237−2.305) 0.001

Values are presented as hazard ratio (95% CI).

NLR: neutrophil-to-lymphocyte ratio; PLR: platelet-to-lymphocyte ratio; LMR: lymphocyte-to-monocyte ratio; WBC: white blood cell; CRP: C-reactive protein; RDW: red blood cell distribution width.

a)Adjusted for sex, Sequential Organ Failure Assessment score, origin of sepsis, age-adjusted Charlson Comorbidity Index, and antibiotic administration time.

Table 5.
Receiver operating characteristic curve analyses of the ability of several parameters to predict 30-day mortality
AUROC (95% CI) P-value Optimal cutoff value Sensitivity (%) Specificity (%) Youden index J
NLR Day 1 0.471 (0.381−0.560) 0.484 32.64 24.1 80.4 0.044
Day 2 0.481 (0.382−0.580) 0.660 57.21 24.5 87.6 0.121
Day 3 0.634 (0.530−0.738) 0.008 23.02 55.6 70.1 0.257
Day 4 0.705 (0.590−0.820) 0.001 14.28 73.1 67.6 0.407
Day 5 0.743 (0.615−0.872) <0.001 21.69 64.0 88.4 0.524
Day 5/day 1 0.746 (0.649−0.843) <0.001 0.695 76.0 67.4 0.434
Day 5/day 1 >1 0.688 (0.571−0.805) 0.002 - 60.0 77.7 -
LMR Day 1 0.409 (0.327−0.491) 0.032 0.480 3.8 98.7 0.024
Day 2 0.464 (0.368−0.560) 0.420 0.445 14.6 96.7 0.113
Day 3 0.593 (0.489−0.696) 0.063 1.095 40.5 79.5 0.201
Day 4 0.669 (0.536−0.801) 0.004 1.675 66.7 67.5 0.341
Day 5 0.707 (0.583−0.831) 0.001 1.105 56.0 85.1 0.411
Day 5/day 1 0.753 (0.673−0.833) <0.001 1.050 92.0 55.8 0.478
Day 5/day 1 <1 0.701 (0.604−0.798) 0.001 - 84.0 56.2 -
RDW (%) Day 1 0.734 (0.662−0.806) <0.001 14.45 74.1 66.0 0.401
Lactate (mmol/L) Day 1 0.845 (0.752−0.938) <0.001 3.25 84.6 81.5 0.662
SOFA score Day 1 0.744 (0.671−0.818) <0.001 11.5 51.9 86.2 0.381

AUROC: area under the receiver operating characteristic curve; NLR: neutrophil-to-lymphocyte ratio; LMR: lymphocyte-to-monocyte ratio; RDW: red blood cell distribution width; SOFA: Sequential Organ Failure Assessment.

Table 6.
Comparison of biomarkers measured on day 1 according to the diastolic function groups
Normal diastolic function (n=83) Diastolic dysfunction (n=121) P-value
WBC (×109/L) 14.27 (6.87−17.80) 13.62 (8.56−19.75) 0.569
NLR 13.95 (6.56−26.27) 19.43 (8.03−34.18) 0.046
PLR 240.0 (119.38−409.08) 240.63 (149.50−439.29) >0.999
LMR 2.08 (1.29−3.64) 1.62 (1.04−2.83) 0.209
RDW (%) 13.80 (13.20−15.35) 14.10 (13.30−15.10) 0.212
CRP (mg/L) 94.50 (53.50−194.05) 166.90 (79.50−244.90) 0.010
Procalcitonin (ng/ml) 5.52 (0.99−45.20) 18.56 (1.51−76.30) 0.100
NT-proBNP (pg/ml) 1,029.50 (416.0−4,920.0) 4,927.0 (1,338.50−12,846.0) <0.001

Values are presented as median (interquartile range).

WBC: white blood cell; NLR: neutrophil-to-lymphocyte ratio; PLR: platelet-to-lymphocyte ratio; LMR: lymphocyte-to-monocyte ratio; RDW: red blood cell distribution width; CRP: C-reactive protein; NT-proBNP: N-terminal pro-brain natriuretic peptide.

Table 7.
Univariate and multivariate analyses of biomarkers associated with diastolic dysfunction measured on the day of admission
Unadjusted model P-value Adjusted modela) P-value
WBC (×10⁹/L) 1.012 (0.981−1.045) 0.456 1.004 (0.969−1.040) 0.818
NLR 1.011 (0.998−1.025) 0.095 1.016 (1.000−1.031) 0.043
PLR 1.000 (0.999−1.001) 0.513 1.000 (0.999−1.001) 0.546
LMR 0.993 (0.930−1.060) 0.831 0.970 (0.899−1.048) 0.444
RDW (%) 1.048 (0.881−1.248) 0.595 1.027 (0.845−1.248) 0.787
CRP (mg/L) 1.002 (1.000−1.005) 0.054 1.003 (1.000−1.005) 0.041
Procalcitonin (ng/ml) 1.002 (0.998−1.005) 0.329 1.002 (0.998−1.005) 0.418
NT-proBNP (pg/ml) 1.000 (1.000−1.000) 0.003 1.000 (1.000−1.000) 0.008

Values are presented as odds ratio (95% CI).

WBC: white blood cell; NLR: neutrophil-to-lymphocyte ratio; PLR: platelet-to-lymphocyte ratio; LMR: lymphocyte-to-monocyte ratio; RDW: red blood cell distribution width; CRP: C-reactive protein; NT-proBNP: N-terminal pro-brain natriuretic peptide.

a)Adjusted for age, sex, hypertension, diabetes, heart failure, atrial fibrillation, and coronary artery occlusive disease.

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        Association between 30-day mortality and serially measured hematologic markers in patients with septic shock in South Korea
        Acute Crit Care. 2026;41(3):564-577.   Published online August 31, 2026
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      Association between 30-day mortality and serially measured hematologic markers in patients with septic shock in South Korea
      Image Image Image Image
      Figure 1. Study flow diagram. ER: emergency room; NLR: neutrophil-to-lymphocyte ratio; WBC: white blood cell.
      Figure 2. Changes in white blood cell (WBC), neutrophil-to-lymphocyte ratio (NLR), C-reactive protein (CRP), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR) during the first 5 consecutive days after septic shock diagnosis. Values are presented as the least squares means with standard error values. The P-value from a linear mixed model was used to compare changes in each parameter over time between the survivor and non-survivor groups.
      Figure 3. Thirty-day survival curves according to incremental or decremental neutrophil-to-lymphocyte ratio (NLR; A) and lymphocyte-to-monocyte ratio (LMR; B) changes.
      Figure 4. Receiver operating characteristic curve analyses of the ability of serial neutrophil-to-lymphocyte ratio (NLR; A) and lymphocyte-to-monocyte ratio (LMR; B) values and the NLR and LMR day 5/day 1 ratios to predict 30-day mortality in patients with septic shock.

      Figure 1.

      Figure 2.

      Figure 3.

      Figure 4.

      Association between 30-day mortality and serially measured hematologic markers in patients with septic shock in South Korea
      Variable Value
      All patients 431
      Age (yr) 70.0 (58.0−77.0)
      Male sex 193 (44.8)
      BMI (kg/m2) 22.67 (20.20−24.99)
      Comorbidity
       Hypertension 251 (58.2)
       Diabetes 148 (34.3)
       Heart failure 21 (4.9)
       Atrial fibrillation 52 (12.1)
       Coronary artery occlusive disease 53 (12.3)
       Cerebrovascular accident 110 (25.5)
       Chronic kidney disease 73 (16.9)
       Malignancy 128 (29.7)
       Chronic liver disease 41 (9.5)
       Chronic obstructive pulmonary disease 44 (10.2)
      Sepsis origin
       Respiratory 79 (18.3)
       Urinary tract 195 (45.2)
       Intra-abdominal infection 92 (21.3)
       Soft tissue infection 33 (7.7)
       Other/unknown 32 (7.5)
      Age-adjusted CCI 4.0 (2.0−6.0)
      SOFA score 10.0 (8.0−13.0)
      Antibiotic administration time (min) 54.5 (37.5−72.0)
      Outcome
       Hospital day 19.0 (9.0−30.0)
       30-Day mortality 54 (12.5)
       Vasopressor-free day 9.0 (5.0−18.0)
       ICU admission 164 (38.1)
       ICU day (n=164) 4.0 (2.0−8.0)
       Mechanical ventilation 79 (18.3)
       Mechanical ventilation day (n=79) 6.0 (2.0−12.0)
      Variable Survivor (n=377) Non-survivor (n=54) P-value
      Age (yr) 69.0 (56.0−77.0) 75.5 (64.0−80.0) 0.001
      Male sex 170 (45.1) 23 (42.6) 0.842
      Comorbidity
       Hypertension 215 (57.0) 36 (66.7) 0.232
       Diabetes 127 (33.7) 21 (38.9) 0.549
       Heart failure 18 (4.8) 3 (5.6) >0.999
       Atrial fibrillation 42 (11.1) 10 (18.5) 0.182
       Coronary artery occlusive disease 46 (12.2) 7 (13.0) >0.999
       Cerebrovascular accident 95 (25.2) 15 (27.8) 0.811
       Chronic kidney disease 64 (17.0) 9 (16.7) >0.999
       Malignancy 110 (29.2) 18 (33.3) 0.641
       Chronic obstructive pulmonary disease 37 (9.8) 7 (13.0) 0.635
      Sepsis origin 0.369
       Respiratory 68 (18.0) 11 (20.4)
       Urinary tract 176 (46.7) 19 (35.2)
       Intra-abdominal infection 76 (20.2) 16 (29.6)
       Soft tissue infection 30 (8.0) 3 (5.6)
       Other/unknown 27 (7.2) 5 (9.3)
      SOFA score 8.0 (6.0−10.0) 12.0 (8.0−14.0) <0.001
      Age-adjusted CCI 4.0 (2.0−6.0) 5.0 (4.0−6.0) 0.005
      Antibiotic administration time (min) 56.0 (36.0−76.0) 57.5 (43.0−77.0) 0.341
      Outcome
       Hospital day 14.0 (9.0−24.0) 3.5 (2.0−13.0) <0.001
       Vasopressor-free day 11.0 (6.0−19.0) 0 (0−2.0) <0.001
       ICU admission 130 (34.5) 34 (63.0) <0.001
       ICU day (n=164) 4.0 (2.0−7.0) 3.0 (2.0−9.0) 0.413
       Mechanical ventilation 45 (11.9) 34 (63.0) <0.001
       Mechanical ventilation day (n=79) 8.0 (5.0−18.0) 2.0 (2.0−8.0) 0.001
      Variable All patients (n=431) Survivor (n=377) Non-survivor (n=54) P-value
      Procalcitonin day 1 (ng/ml) 7.63 (1.27−39.74) 7.01 (1.26−38.81) 16.88 (1.29−48.43) 0.392
      Lactate day 1 (mmol/L) 1.80 (1.20−3.40) 1.75 (1.10−2.50) 5.25 (3.60−9.30) <0.001
      RDW day 1 (%) 14.0 (13.10−15.35) 13.90 (13.0−14.90) 15.70 (14.10−16.80) <0.001
      CRP (mg/L)
       Day 1 (431) 131.90 (56.40−217.0) 130.2 (56.30−217.60) 136.80 (63.50−214.9) >0.999
       Day 2 (57) 196.90 (131.90−277.80) 212.75 (150.40−285.30) 147.60 (70.50−247.10) 0.601
       Day 3 (121) 174.20 (105.40−252.60) 174.70 (106.85−252.90) 96.40 (71.60−217.80) >0.999
       Day 4 (157) 99.0 (55.20−146.90) 97.90 (55.20−140.70) 127.25 (87.35−182.0) 0.807
       Day 5 (119) 53.20 (25.50−97.45) 52.60 (25.30−97.45) 66.15 (34.45−132.25) >0.999
       Day 5/day 1 (119) 0.39 (0.23−0.85) 0.37 (0.21−0.84) 0.59 (0.34−1.30) 0.241
       Day 5/day 1 >1 (119) 21 (17.6) 19 (17.1) 2 (25.0) 0.630
      WBC (×109/L)
       Day 1 (431) 13.20 (7.28−18.75) 13.20 (7.32−18.62) 13.09 (6.60−21.96) >0.999
       Day 2 (421) 15.77 (9.98−22.26) 15.90 (10.42−22.13) 14.20 (7.10−23.87) >0.999
       Day 3 (376) 13.04 (8.56−18.60) 12.69 (8.51−18.06) 18.50 (9.51−26.71) 0.014
       Day 4 (321) 10.44 (6.95−15.03) 10.15 (6.95−14.94) 13.10 (8.07−25.65) 0.279
       Day 5 (272) 8.06 (5.39−12.07) 8.02 (5.29−11.62) 10.86 (6.19−22.29) 0.555
       Day 5/day 1 (272) 0.67 (0.41−1.11) 0.63 (0.41−1.07) 0.90 (0.54−1.26) 0.146
       Day 5/day 1 >1 (272) 79 (29.0) 68 (27.5) 11 (44.0) 0.134
      NLR
       Day 1 (431) 15.70 (7.80−28.86) 15.70 (8.03−28.63) 15.74 (6.28−30.75) >0.999
       Day 2 (419) 20.04 (10.38−37.06) 20.52 (10.66−36.20) 19.72 (7.16−46.0) >0.999
       Day 3 (374) 15.57 (8.03−29.85) 14.74 (7.68−29.04) 25.98 (10.48−51.42) 0.040
       Day 4 (319) 9.86 (5.05−19.26) 9.55 (4.90−18.01) 21.12 (9.87−43.20) 0.003
       Day 5 (267) 6.68 (3.56−15.02) 6.26 (3.53−13.38) 25.17 (11.16−40.62) <0.001
       Day 5/day 1 (267) 0.47 (0.19−1.03) 0.42 (0.18−0.89) 1.52 (0.70−2.92) <0.001
       Day 5/day 1 >1 (267) 69 (25.8) 54 (22.3) 15 (60.0) <0.001
      PLR
       Day 1 (431) 259.09 (148.78−446.06) 266.32 (155.76−449.68) 182.0 (111.26−344.12) 0.104
       Day 2 (419) 250.0 (143.67−407.04) 259.37 (150.94−400.0) 203.51 (77.42−546.88) >0.999
       Day 3 (374) 171.34 (110.61−300.0) 172.11 (112.29−300.0) 163.0 (78.87−250.39) >0.999
       Day 4 (319) 144.80 (87.72−244.95) 144.44 (86.54−243.75) 153.55 (90.0−263.33) >0.999
       Day 5 (267) 133.93 (90.77−234.83) 135.02 (92.94−232.95) 129.31 (87.18−341.30) >0.999
       Day 5/day 1 (267) 0.59 (0.31−1.01) 0.59 (0.30−1.01) 0.69 (0.41−1.33) 0.141
       Day 5/day 1 >1 (267) 70 (26.3) 61 (25.3) 9 (36.0) 0.359
      LMR
       Day 1 (430) 2.05 (1.14−3.69) 1.96 (1.13−3.45) 3.0 (1.38−5.0) 0.160
       Day 2 (417) 1.50 (0.90−2.43) 1.47 (0.90−2.41) 1.65 (1.0−2.82) >0.999
       Day 3 (374) 1.78 (1.15−2.69) 1.78 (1.19−2.73) 1.63 (0.87−2.41) 0.317
       Day 4 (319) 2.13 (1.37−3.41) 2.18 (1.42−3.44) 1.31 (0.71−2.08) 0.019
       Day 5 (267) 2.10 (1.37−3.33) 2.13 (1.48−3.48) 1.04 (0.72−2.23) 0.003
       Day 5/day 1 (267) 1.08 (0.48−2.05) 1.18 (0.55−2.15) 0.45 (0.23−0.91) <0.001
       Day 5/day 1 <1 (267) 127 (47.6) 106 (43.8) 21 (84.0) <0.001
      Unadjusted model P-value Adjusted modela) P-value
      NLR Day 1 1.004 (0.997−1.011) 0.280 1.003 (0.995−1.011) 0.427
      Day 2 1.001 (0.998−1.003) 0.547 1.000 (0.996−1.004) 0.876
      Day 3 1.001 (0.998−1.004) 0.388 0.999 (0.996−1.003) 0.677
      Day 4 1.023 (1.009−1.036) 0.001 1.011 (0.996−1.026) 0.167
      Day 5 1.050 (1.028−1.071) <0.001 1.043 (1.020−1.067) <0.001
      Day 5/day 1 0.997 (0.974−1.020) 0.803 0.999 (0.976−1.023) 0.962
      Day 5/day 1 >1 5.222 (2.220−12.285) <0.001 4.893 (1.870−12.806) 0.001
      PLR Day 1 1.000 (0.999−1.001) 0.450 1.000 (1.000−1.001) 0.301
      Day 2 1.000 (1.000−1.000) 0.717 1.000 (1.000−1.001) 0.041
      Day 3 1.001 (1.000−1.002) 0.081 1.001 (1.000−1.002) 0.075
      Day 4 1.001 (1.000−1.003) 0.036 1.002 (1.000−1.004) 0.067
      Day 5 1.002 (1.001−1.004) 0.012 1.003 (1.001−1.006) 0.007
      Day 5/day 1 1.142 (0.797−1.635) 0.470 1.069 (0.716−1.596) 0.745
      Day 5/day 1 >1 1.660 (0.698−3.949) 0.252 1.573 (0.590−4.192) 0.365
      LMR Day 1 1.052 (1.004−1.102) 0.035 1.066 (1.012−1.123) 0.015
      Day 2 1.156 (1.046−1.279) 0.005 1.135 (1.023−1.259) 0.017
      Day 3 0.972 (0.788−1.200) 0.792 1.086 (0.918−1.285) 0.336
      Day 4 0.856 (0.650−1.128) 0.269 1.002 (0.824−1.219) 0.982
      Day 5 0.581 (0.388−0.870) 0.008 0.689 (0.452−1.052) 0.085
      Day 5/day 1 0.243 (0.107−0.553) 0.001 0.245 (0.097−0.620) 0.003
      Day 5/day 1 <1 6.736 (2.244−20.215) 0.001 5.457 (1.724−17.277) 0.004
      WBC (×109/L) Day 1 1.018 (0.989−1.048) 0.230 1.003 (0.972−1.035) 0.849
      Day 2 1.002 (0.973−1.032) 0.895 0.992 (0.960−1.024) 0.613
      Day 3 1.058 (1.027−1.090) <0.001 1.042 (1.004−1.081) 0.030
      Day 4 1.050 (1.019−1.083) 0.001 1.023 (0.986−1.061) 0.233
      Day 5 1.053 (1.008−1.099) 0.020 1.038 (0.988−1.090) 0.142
      Day 5/day 1 0.897 (0.642−1.254) 0.524 0.836 (0.580−1.204) 0.336
      Day 5/day 1 >1 2.068 (0.895−4.779) 0.089 1.985 (0.789−4.993) 0.145
      CRP (mg/L) Day 1 1.000 (0.997−1.002) 0.962 0.998 (0.996−1.001) 0.285
      Day 2 0.994 (0.986−1.001) 0.111 0.991 (0.979−1.002) 0.116
      Day 3 1.000 (0.994−1.006) 0.991 0.997 (0.992−1.003) 0.403
      Day 4 1.005 (0.998−1.012) 0.137 1.001 (0.993−1.010) 0.789
      Day 5 1.007 (0.995−1.018) 0.272 1.002 (0.988−1.017) 0.747
      Day 5/day 1 0.960 (0.713−1.293) 0.788 0.892 (0.602−1.323) 0.570
      Day 5/day 1 >1 1.614 (0.302−8.615) 0.575 0.894 (0.131−6.092) 0.909
      Procalcitonin (ng/ml) Day 1 1.001 (0.998−1.005) 0.472 0.995 (0.990−1.000) 0.046
      RDW (%) Day 1 1.521 (1.306−1.771) <0.001 1.478 (1.246−1.753) <0.001
      Lactate (mmol/L) Day 1 1.584 (1.342−1.869) <0.001 1.688 (1.237−2.305) 0.001
      AUROC (95% CI) P-value Optimal cutoff value Sensitivity (%) Specificity (%) Youden index J
      NLR Day 1 0.471 (0.381−0.560) 0.484 32.64 24.1 80.4 0.044
      Day 2 0.481 (0.382−0.580) 0.660 57.21 24.5 87.6 0.121
      Day 3 0.634 (0.530−0.738) 0.008 23.02 55.6 70.1 0.257
      Day 4 0.705 (0.590−0.820) 0.001 14.28 73.1 67.6 0.407
      Day 5 0.743 (0.615−0.872) <0.001 21.69 64.0 88.4 0.524
      Day 5/day 1 0.746 (0.649−0.843) <0.001 0.695 76.0 67.4 0.434
      Day 5/day 1 >1 0.688 (0.571−0.805) 0.002 - 60.0 77.7 -
      LMR Day 1 0.409 (0.327−0.491) 0.032 0.480 3.8 98.7 0.024
      Day 2 0.464 (0.368−0.560) 0.420 0.445 14.6 96.7 0.113
      Day 3 0.593 (0.489−0.696) 0.063 1.095 40.5 79.5 0.201
      Day 4 0.669 (0.536−0.801) 0.004 1.675 66.7 67.5 0.341
      Day 5 0.707 (0.583−0.831) 0.001 1.105 56.0 85.1 0.411
      Day 5/day 1 0.753 (0.673−0.833) <0.001 1.050 92.0 55.8 0.478
      Day 5/day 1 <1 0.701 (0.604−0.798) 0.001 - 84.0 56.2 -
      RDW (%) Day 1 0.734 (0.662−0.806) <0.001 14.45 74.1 66.0 0.401
      Lactate (mmol/L) Day 1 0.845 (0.752−0.938) <0.001 3.25 84.6 81.5 0.662
      SOFA score Day 1 0.744 (0.671−0.818) <0.001 11.5 51.9 86.2 0.381
      Normal diastolic function (n=83) Diastolic dysfunction (n=121) P-value
      WBC (×109/L) 14.27 (6.87−17.80) 13.62 (8.56−19.75) 0.569
      NLR 13.95 (6.56−26.27) 19.43 (8.03−34.18) 0.046
      PLR 240.0 (119.38−409.08) 240.63 (149.50−439.29) >0.999
      LMR 2.08 (1.29−3.64) 1.62 (1.04−2.83) 0.209
      RDW (%) 13.80 (13.20−15.35) 14.10 (13.30−15.10) 0.212
      CRP (mg/L) 94.50 (53.50−194.05) 166.90 (79.50−244.90) 0.010
      Procalcitonin (ng/ml) 5.52 (0.99−45.20) 18.56 (1.51−76.30) 0.100
      NT-proBNP (pg/ml) 1,029.50 (416.0−4,920.0) 4,927.0 (1,338.50−12,846.0) <0.001
      Unadjusted model P-value Adjusted modela) P-value
      WBC (×10⁹/L) 1.012 (0.981−1.045) 0.456 1.004 (0.969−1.040) 0.818
      NLR 1.011 (0.998−1.025) 0.095 1.016 (1.000−1.031) 0.043
      PLR 1.000 (0.999−1.001) 0.513 1.000 (0.999−1.001) 0.546
      LMR 0.993 (0.930−1.060) 0.831 0.970 (0.899−1.048) 0.444
      RDW (%) 1.048 (0.881−1.248) 0.595 1.027 (0.845−1.248) 0.787
      CRP (mg/L) 1.002 (1.000−1.005) 0.054 1.003 (1.000−1.005) 0.041
      Procalcitonin (ng/ml) 1.002 (0.998−1.005) 0.329 1.002 (0.998−1.005) 0.418
      NT-proBNP (pg/ml) 1.000 (1.000−1.000) 0.003 1.000 (1.000−1.000) 0.008
      Table 1. Baseline characteristics of all enrolled patients

      Values are presented as median (interquartile range) or number (%).

      BMI: body mass index; CCI: Charlson Comorbidity Index; SOFA: Sequential Organ Failure Assessment; ICU: intensive care unit.

      Table 2. Demographics of survivors and non-survivors

      Values are presented as median (interquartile range) or number (%).

      SOFA: Sequential Organ Failure Assessment; CCI: Charlson Comorbidity Index; ICU: intensive care unit.

      Table 3. Systemic inflammatory biomarkers in survivors and non-survivors

      Values are presented as median (interquartile range) or number (%).

      RDW: red blood cell distribution width; CRP: C-reactive protein; WBC: white blood cell count; NLR: neutrophil-to-lymphocyte ratio; PLR: platelet-to-lymphocyte ratio; LMR: lymphocyte-to-monocyte ratio.

      P-values were adjusted using Bonferroni’s method.

      Table 4. Univariate and multivariate analyses of parameters for predicting 30-day mortality

      Values are presented as hazard ratio (95% CI).

      NLR: neutrophil-to-lymphocyte ratio; PLR: platelet-to-lymphocyte ratio; LMR: lymphocyte-to-monocyte ratio; WBC: white blood cell; CRP: C-reactive protein; RDW: red blood cell distribution width.

      Adjusted for sex, Sequential Organ Failure Assessment score, origin of sepsis, age-adjusted Charlson Comorbidity Index, and antibiotic administration time.

      Table 5. Receiver operating characteristic curve analyses of the ability of several parameters to predict 30-day mortality

      AUROC: area under the receiver operating characteristic curve; NLR: neutrophil-to-lymphocyte ratio; LMR: lymphocyte-to-monocyte ratio; RDW: red blood cell distribution width; SOFA: Sequential Organ Failure Assessment.

      Table 6. Comparison of biomarkers measured on day 1 according to the diastolic function groups

      Values are presented as median (interquartile range).

      WBC: white blood cell; NLR: neutrophil-to-lymphocyte ratio; PLR: platelet-to-lymphocyte ratio; LMR: lymphocyte-to-monocyte ratio; RDW: red blood cell distribution width; CRP: C-reactive protein; NT-proBNP: N-terminal pro-brain natriuretic peptide.

      Table 7. Univariate and multivariate analyses of biomarkers associated with diastolic dysfunction measured on the day of admission

      Values are presented as odds ratio (95% CI).

      WBC: white blood cell; NLR: neutrophil-to-lymphocyte ratio; PLR: platelet-to-lymphocyte ratio; LMR: lymphocyte-to-monocyte ratio; RDW: red blood cell distribution width; CRP: C-reactive protein; NT-proBNP: N-terminal pro-brain natriuretic peptide.

      Adjusted for age, sex, hypertension, diabetes, heart failure, atrial fibrillation, and coronary artery occlusive disease.

      Table 1.

      Table 2.

      Table 3.

      Table 4.

      Table 5.

      Table 6.

      Table 7.

      ACC : Acute and Critical Care
      © The Korean Society of Critical Care Medicine.
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