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Abstract

Disseminated intravascular coagulation (DIC) poses a high mortality risk, yet its exact impact remains contentious. This study investigates DIC's association with mortality in individuals with sepsis, emphasizing multiple organ function. Using data from the Peking University People's Hospital Investigation on Sepsis-Induced Coagulopathy database, we categorized patients into DIC and non-DIC groups based on DIC scores within 24 h of ICU admission (< 5 cutoff). ICU mortality was the main outcome. Initial data comparison preceded logistic regression analysis of mortality factors post-propensity score matching (PSM). Employing mediation analysis estimated direct and indirect associations. Of 549 participants, 131 were in the DIC group, with the remaining 418 in the non-DIC group. Following baseline characteristic presentation, PSM was conducted, revealing significantly higher nonplatelet sequential organ failure assessment (nonplt-SOFA) scores (6.3 ± 2.7 vs 5.0 ± 2.5, P < 0.001) and in-hospital mortality rates (47.3% vs 29.5%, P = 0.003) in the DIC group. A significant correlation between DIC and in-hospital mortality persisted (OR 2.15, 95% CI 1.29–3.59, P = 0.003), with nonplt-SOFA scores (OR 1.16, 95% CI 1.05-1.28, P = 0.004) and hemorrhage (OR 2.33, 95% CI 1.08-5.03, P = 0.032) as predictors. The overall effect size was 0.1786 (95% CI 0.0542-0.2886), comprising a direct effect size of 0.1423 (95% CI 0.0153-0.2551) and an indirect effect size of 0.0363 (95% CI 0.0034-0.0739), with approximately 20.3% of effects mediated. These findings underscore DIC's association with increased mortality risk in patients with sepsis, urging anticoagulation focus over bleeding management, with organ dysfunction assessment recommended for anticoagulant treatment efficacy.

Keywords

sepsis multiple organ function disseminated intravascular coagulation mediation analysis

Background

Sepsis, a condition characterized by life-threatening organ dysfunction, arises from an imbalanced host response to infection.¹ This condition is a significant challenge in the ICU and is responsible for approximately 30%–50% of mortality.^2,3 Sepsis is caused by various factors, such as excessive cytokine release, widespread inflammation, impaired endothelial function, capillary leakage, and abnormal blood clotting.^4–6 Clinically, patients with sepsis may exhibit coagulation activation, which can lead to thrombosis. Organ dysfunction is primarily caused by microvascular blood clotting and subsequent blockage and reduction of blood flow.⁷

Coagulopathy, characterized by disruptions in hemostasis caused by various factors leading to hemorrhage, clotting, or both, is a common complication in critical care settings and significantly affects prognosis.^8,9 DIC in sepsis is acquired and marked by thrombin generation throughout the body and injury to endothelial cells caused by infection. Additionally, it signifies an acute systemic inflammatory response that results in dysfunction of endothelial cells.^10,11 Severe coagulopathy can lead to the development of multiple organ dysfunction syndrome (MODS) and worse results. There have also been reports of hemorrhage in cases of late-stage DIC.^12,13

There are different viewpoints regarding the impact of DIC on blood clotting and hemorrhage. To date, only a limited number of studies have examined the association between DIC and fatality in relation to various organ functions or hemorrhage. Moreover, the degree to which risk factors mediate the correlation between DIC and mortality has not been conclusively determined or measured. Therefore, the present study aimed to explore the connection between DIC and death in patients with sepsis, with a specific focus on the impact on multiple organ functions.

Methods

Sources of Data and Participants in the Study

This study used a retrospective observational design, utilizing data from the Peking University People's Hospital Investigation on Sepsis-Induced Coagulopathy (PKUPH-ISIC) database. In 2023, the PKUPH-ISIC database was established, and approval was obtained from the Hospital Ethics Committee (approval number 2023PHB100–001). The database contains significant data regarding patients with sepsis who were admitted to a hospital in Beijing. The PKUPH-ISIC database, which contains data regarding patients from the ICU at Peking University People's Hospital, is continuously updated. To conduct this study, individuals from the database between January 1, 2013, and January 31, 2022 were selected. The diagnosis of sepsis followed the sepsis 3.0 guidelines, which require patients to show signs of suspected infection and have a sequential organ failure assessment (SOFA) score of 2 or higher within 24 h of admission.¹ To be eligible for our study, patients with sepsis who were aged ≥18 years or those who stayed in the ICU for more than 24 h after admission were considered. Individuals with progressive malignant tumors and disorders of the hematological system were excluded. Only the first ICU admission was considered if the patient had been admitted to the ICU multiple times.

Definition and Variables

The diagnoses of DIC were consistent with the definition given by the International Society on Haemostasis and Thrombosis (ISTH).¹⁴ Specifically, patients were evaluated for overt DIC using the ISTH scoring system. D-dimer is a fibrin-related marker used to meet ISTH criteria. D-dimer levels < 250, 250 to < 500, and ≥ 500 mg/L were categorized as no increase, moderate increase, and strong increase, respectively. Organ performance was evaluated using the SOFA scale.¹⁵ As both DIC and SOFA scores were calculated based on platelet counts, we created the nonplatelet (nonplt)-SOFA score as a substitute for the SOFA score to assess the performance of various organs while reducing the influence of platelets on these two scores. The nonplt-SOFA score represents the SOFA score without considering platelet count. The definition of acute kidney injury (AKI) followed the criteria set by the Kidney Disease Improving Global Outcomes.¹⁶ The variable Old65 was regarded as a categorical variable representing age, with two categories: individuals aged < 65 years and those aged ≥65 years. If a variable was documented multiple times within the first 24 h, we used the worst value for each variable.

The variables were as follows: 1) demographic characteristics, including sex, age, and body mass index (BMI); 2) chronic comorbidities, including hypertension, diabetes, chronic heart disease (CHD), and chronic obstructive pulmonary disease (COPD); 3) various primary sources of infection, including the bloodstream, abdomen, respiratory tract, urinary tract, skin soft tissue, and brain; and 4) ICU admission, emergency admission, or perioperative management.

The primary outcome variable was in-hospital mortality. The secondary outcomes included hemorrhage, mechanical ventilation, continuous renal replacement therapy (CRRT), AKI, SOFA without platelets (nonplt-SOFA score), and norepinephrine.

Statistical Analysis

Categorical variables were described using frequencies, and continuous variables were expressed as mean ± standard deviation. The Student's t-test or ANOVA was used to assess statistical significance based on the context. For categorical variables, the χ2 test was used to determine statistical significance, with the Fisher exact test applied where appropriate. The relationship between risk factors and mortality was analyzed using multivariate regression analysis.

To reduce the potential bias in assigning treatments and accounting for confounding factors, we created a propensity score using multivariate logistic regression to estimate the relationship between patient mortality in the two groups. The original model consisted of accessible variables (eg, sex, Old65, BMI, hypertension, diabetes, CHD, COPD, various primary sources of infection, emergency admission, or perioperative management). On the propensity score scale, we used calipers measuring 0.02 and sampling without replacement at a rate of 1 to 1. Before and after propensity score matching (PSM), the standardized mean difference was used to compare all patient characteristics involved in generating and distributing the propensity scores (Supplementary Fig S1). Values < 0.2 were deemed satisfactory. Finally, 129 patient-matched pairs were generated and subjected to further analysis. The relationships between DIC, nonplt-SOFA score, hemorrhage, and mortality were analyzed following the establishment of propensity score-matched cohorts. Consequently, DIC, nonplt-SOFA score, and mortality were considered suitable for inclusion in the causal mediation analysis.

Propensity score matching

The disentanglement of the overall impact into its direct and indirect effects was achieved using causal mediation analysis, a statistical method.¹⁷ The outcome is influenced by an indirect effect that operates through a mediator. To determine the impact of DIC on mortality through multiple organ functions, we used the R package ‘mediation’ and utilized bootstrapping techniques to compute the 95% confidence intervals (CIs) for this estimation. To establish the precision of this estimate, we used bootstrapping methods to compute 95% CIs. This research aimed to examine the relationship between DIC and mortality in patients with sepsis, specifically its impact on multiple organ functions.

Results

Demographic Data and Baseline Characteristics

Following an extensive examination of the data obtained from 754 individuals with sepsis, we identified 549 patients who met the criteria for participation in our study. Figure 1 shows a flow diagram demonstrating the process of selecting the study participants. Among the participants, 131 (23.9%) were diagnosed with DIC, and 418 (76.1%) did not exhibit this condition. Supplementary Table S1 concisely presents the baseline characteristics of patients in the DIC and non-DIC groups. Notably, participants with DIC tended to be younger (69.572 ± 15.668 vs 64.221 ± 16.486, P < 0.001) and showed a higher occurrence of diabetes (24.88% vs 16.03%, P = 0.035). Nevertheless, there were no notable disparities with regard to sex, BMI, a primary source of infection, or ICU admission between the two groups. The mortality rate in patients with sepsis was 36.1%. The DIC group exhibited significantly poorer outcomes than the non-DIC group ( Table 2 ), as evidenced by higher nonplt-SOFA scores (4.6 ± 2.3 vs 6.3 ± 2.7 P < 0.001), in-hospital mortality rates (32.5% vs 47.3% p = 0.002), and occurrences of mechanical ventilation (46.2% vs 59.5% P = 0.008), AKI (35.8% vs 64.1% P < 0.001), and CRRT (11% vs 24.4% P < 0.001). Notably, there was no discernible correlation between hemorrhage and DIC incidence (10.3% vs 14.5%, P = 0.183).

Figure 1.

Flow diagram of the current investigation.

the Relationship Between DIC and the Outcome Variables After PSM

After PSM, there was a significant reduction in the covariate imbalance between the DIC and non-DIC groups ( Table 1 ). The clinical outcome analysis of the two groups is compared in Table 2 and Supplementary Table S2. Compared to the non-DIC group, the DIC group exhibited significantly elevated nonplt-SOFA scores (6.3 ± 2.7 vs 5.0 ± 2.5, P < 0.001), as well as higher rates of in-hospital mortality (47.3% vs 29.5%, p = 0.003). Additionally, the incidences of mechanical ventilation, AKI, and CRRT were significantly higher in the DIC group. However, no correlation was observed between hemorrhage and DIC.

Table 1.

Comparison of the Baseline Characteristics Between the Patients from the Original and Matched Cohorts.

Variables	Original cohort				Matched cohort
Variables	Non-DIC	DIC	SMD	P valve	Non-DIC	DIC	SMD	P valve
N	418	131			129	129
Demographics
Male (%)	226.00 (54.07)	64.00 (48.85)	0.1044	0.297	62.00 (48.06)	62.00 (48.06)	<0.0001	1
Age, years	69.572 (15.668)	64.221 (16.486)	0.3327	< 0.001	65.651 (16.447)	64.062 (16.512)	0.0964	0.439
BMI, kg/m²	23.152 (4.222)	22.280 (3.719)	0.219	0.052	23.078 (4.659)	22.280 (3.720)	0.1892	0.155
Chronic comorbidity, n (%)
Hypertension (%)	189.00 (45.22)	48.00 (36.64)	0.175	0.084	51.00 (39.53)	48.00 (37.21)	0.0478	0.701
Diabetes (%)	104.00 (24.88)	21.00 (16.03)	0.2207	0.035	23.00 (17.83)	20.00 (15.50)	0.0624	0.616
CHD (%)	65.00 (15.55)	17.00 (12.98)	0.0736	0.471	12.00 (9.30)	16.00 (12.40)	0.0998	0.423
COPD (%)	13.00 (3.11)	2.00 (1.53)	0.1054	0.539	-	-	-
Primary source of infection (%)
Bloodstream	36.00 (8.61)	14.00 (10.69)	0.2797	0.252	14.00 (10.85)	14.00 (10.85)	0.0457	0.998
Abdomen	198.00 (47.37)	75.00 (57.25)			73.00 (56.59)	74.00 (57.36)
Respiratory tract	117.00 (27.99)	25.00 (19.08)			26.00 (20.16)	24.00 (18.60)
Urinary tract	38.00 (9.09)	11.00 (8.40)			10.00 (7.75)	11.00 (8.53)
Skin and soft tissue	26.00 (6.22)	6.00 (4.58)			6.00 (4.65)	6.00 (4.65)
Brain	3.00 (0.72)	0.00 (0.00)			-	-	-
Admission to ICU
Emergency (%)	150.00 (35.89)	59.00 (45.04)	0.1873	0.06	43.00 (33.33)	57.00 (44.19)	0.2242	0.074
Perioperation (%)	304.00 (72.73)	101.00 (77.10)	0.101	0.321	102.00 (79.07)	100.00 (77.52)	0.0376	0.763

Abbreviations: Variables are presented as the mean ± SD or N (%); ICU, intensive care unit; DIC, disseminated intravascular coagulation; BMI, body mass index; CHD, chronic heart disease; COPD, chronic obstructive pulmonary disease; SMD, standardized mean difference.

Table 2.

Comparisons of Outcomes Between the Patients from the Original and Matched Cohorts.

Outcomes	Original cohort			Matched cohort
Outcomes	Non-DIC	DIC	P valve	Non-DIC	DIC	P valve
N	418	131		129	129
Primary outcome
Mortality, n (%)	136 (32.5)	62 (47.3)	0.002	38 (29.5)	61 (47.3)	0.003
Secondary outcomes
Hemorrhage, n (%)	43 (10.3)	19 (14.5)	0.183	11 (8.5)	19 (14.7)	0.12
MV, n (%)	193 (46.2)	78 (59.5)	0.008	55 (42.6)	76 (58.9)	0.009
CRRT, n (%)	46 (11)	32 (24.4)	< 0.001	16 (12.4)	32 (24.8)	0.01
AKI, n (%)	149 (35.8)	84 (64.1)	< 0.001	42 (32.6)	83 (64.3)	< 0.001
Nonplt-SOFA score	4.6 ± 2.3	6.3 ± 2.7	< 0.001	5.0 ± 2.5	6.3 ± 2.7	< 0.001
Norepinephrine, n (%)	159 (38)	58 (44.3)	0.203	53 (41.1)	58 (45)	0.53

Abbreviations: ICU, intensive care unit; DIC, disseminated intravascular coagulation; MV, mechanical ventilation; CRRT, continuous renal replacement therapy; AKI, acute kidney injury; Nonplt-SOFA score, the score of Sequential Organ Failure Assessment without platelets

Analysis of Causal Mediation

To examine the effects of DIC on in-hospital mortality, a causal mediation analysis approach was used to analyze both direct and indirect consequences. Significantly, the indirect impact was observed when considering organ function as a mediator variable. Significant associations were observed between DIC, nonplt-SOFA score, hemorrhage, and mortality in the propensity score-matched sample via univariate logistic regression analyses, as indicated in Table 3. Specifically, a significant correlation was found between DIC and in-hospital mortality (OR 2.15, 95% CI 1.29–3.59, P = .003). Furthermore, nonplt-SOFA scores (OR 1.16, 95% CI 1.05-1.28, P = .004) and hemorrhage (OR 2.33, 95% CI 1.08-5.03, P = .032) remained predictors, as illustrated in Table 3 .

Table 3.

Associations Between DIC, Nonplt-SOFA Scores, Hemorrhage, and Mortality, as Assessed via Propensity Score Matching.

Variable	OR_95CI	P value
DIC	2.15 (1.29-3.59)	0.003
Nonplt-SOFA score	1.16 (1.05-1.28)	0.004
Hemorrhage	2.33 (1.08-5.03)	0.032

Abbreviations: DIC, disseminated intravascular coagulation; Nonplt-SOFA score, sequential organ failure assessment score without platelets.

Based on the flow diagram of the current study, the total effect was estimated to be 0.1786 (95% CI, 0.0542-0.2886), whereas the direct effect was 0.1423 (95% CI, 0.0153-0.2551). Furthermore, the indirect effect was 0.0363 (95% CI, 0.0034-0.0739), with a calculated mediation proportion of 20.3% (Table 4, Figure 2). It is important to mention that while DIC was not linked to hemorrhage, it was crucial to recognize that hemorrhage could still lead to death, regardless of the use of PSM. According to this study, the influence of DIC on mortality during hospitalization was partly influenced by the functioning of various organs rather than by hemorrhage. These findings suggest that the primary objective of intervention in DIC is to prevent organ dysfunction rather than hemorrhage.

Figure 2.

Causal mediation analysis for both organ function and hemorrhage as mediators. The effect of DIC on mortality is partly mediated through multiple organ functions, excluding hemorrhage. DIC, disseminated intravascular coagulation; Nonplt-SOFA score, the score of sequential organ failure assessment without platelets.

Table 4.

Causal Mediation Analysis for Organ Function Between DIC and Mortality.

Item	Mediation Effect	Mediation S.E.	Mediation LLCI	Mediation ULCI	Mediation p	Mediation z	Mediation P value	Mediation Boot 95CI.
Indirect (ab)	0.0363	0.0175	0.0034	0.0739	0.026	2.0737	0.0381	[0.0034, 0.0739]
Direct (c’)	0.1423	0.0618	0.0153	0.2551	0.032	2.3034	0.0213	[0.0153, 0.2551]
Total(c)	0.1786	0.0589	0.0542	0.2886	0	3.034	0.0024	[0.0542, 0.2886]

Discussion

Sepsis is commonly accompanied by alterations in the coagulation system, ranging from increased clotting activity to the excessive formation of thrombin and fibrin. Consequently, approximately 30%–60% of patients experience consumption of platelets and clotting factors.^18–20 DIC is defined by the initiation of the clotting process, accompanied by a compromised performance of internal anticoagulant mechanisms. Consequently, there is a broad occurrence of microvascular blood clots and concurrent hemorrhage caused by the reduction of clotting factors and platelets.^12,21 Previous research has identified DIC as an independent risk factor for mortality in patients with sepsis.^5,6 Moreover, a forthcoming investigation showed a clear link between the intensity of sepsis, the occurrence of DIC, and organ dysfunction.²² The differences in the occurrence of MODS and mortality rates between patients with DIC and those without DIC suggest that DIC is a predictive factor for MODS and mortality in individuals with severe sepsis.²³ To the best of our knowledge, there is insufficient explicit data on the relationship between DIC and mortality in terms of multiple organ function. Understanding the influence of DIC on mortality rates could help reduce the number of deaths; however, the precise mechanism underlying this occurrence remains unknown.

According to our investigation, the presence of DIC during the first 24 h was associated with significantly worse organ function and a higher hospital mortality rate than the absence of DIC. Organ function affected in-hospital mortality in the DIC group. In contrast, the presence of DIC showed no notable difference in terms of the occurrence of hemorrhagic complications following admission to the ICU. Therefore, we propose that hemorrhage does not play an important role in the complications associated with DIC. Death in patients with sepsis and DIC may be attributed to multiple organ dysfunction rather than hemorrhage. The incidence of organ dysfunction is higher than that of hemorrhage, and identifying high-risk patients with sepsis-associated DIC can increase the survival benefits of anticoagulants.^24,25 The results of this study accurately demonstrated the true effect of DIC in actual clinical settings and confirmed the potential benefits of anticoagulant treatment in patients with sepsis. Adaptive coagulation activation is a component of host defense mechanisms. However, when this activation becomes dysregulated and excessive, it can have detrimental effects.^26,27 Anticoagulant therapies were administered to reinstate the fragile equilibrium between the pathogen and the responsive host. Thus, anticoagulant therapy may be beneficial for patients with sepsis who show coagulopathy, in addition to antibiotics and source control.^8,28 Unfractionated heparin may be beneficial for patients with severe sepsis without hemorrhagic complications because it can decrease mortality within 28 days.²⁹ In this study, timely interventions targeting the prevention of DIC progression in patients with sepsis can reduce mortality rates by approximately 20%.

This study has a few limitations. First, the definition of sepsis relied on sepsis 3.0, which primarily emphasizes organ failure. However, the specific diagnoses of infection remained undefined.³⁰ Second, the data collection was retrospective, thereby limiting our ability to control for all variables despite the use of the PSM approach to mitigate potential data bias. In this study, data were collected from a solitary Chinese facility where ICU medical procedures, such as the administration of blood products or anticoagulants, were determined and implemented according to local standards and protocols. Finally, the analysis in this study was conducted using the worst recorded values of patients within 24 h of ICU admission. It is important to note that DIC is a dynamic and ongoing process. Further, as patients undergo monitoring and treatment, their condition may either deteriorate or improve, which was not accounted for in this research.

Conclusion

In conclusion, the presence of DIC in patients with sepsis is associated with an increased risk of mortality during hospitalization, which is potentially attributable to its impact on multiple organ dysfunction. Our primary focus should be on anticoagulation rather than being overly concerned about bleeding. It is advisable to assess the organ dysfunction in patients with sepsis in order to evaluate the efficacy of anticoagulant treatment. Further research will be required to determine the appropriate timing of anticoagulant administration and the type of anticoagulant to be administered.

Supplemental Material

sj-docx-1-cat-10.1177_10760296241271358 - Supplemental material for Exploring the Mediating Role of Multiple Organ Dysfunction in Sepsis-Induced Disseminated Intravascular Coagulation and Its Impact on Worsening Prognosis

Supplemental material, sj-docx-1-cat-10.1177_10760296241271358 for Exploring the Mediating Role of Multiple Organ Dysfunction in Sepsis-Induced Disseminated Intravascular Coagulation and Its Impact on Worsening Prognosis by Guangjie Wang, Chenxiao Hao, Sun Yao, Yiqin Wang, Zongtao Xu, Huiying Zhao and Youzhong An in Clinical and Applied Thrombosis/Hemostasis

Footnotes

Authors’ Contributions

GW contributed to the study's concept and design, performed statistical analysis, interpreted the results, and wrote the manuscript. YS contributed to the data collection and revision of the manuscript. CH was involved in the design of the study and the revision of the manuscript. YW was responsible for the study design and assisted in drafting the manuscript. ZX participated in data collection. HZ and YA designed and coordinated the study and contributed to the revision of the manuscript. All authors have approved the publication of the final manuscript.

Availability of Data and Materials

The datasets presented in the current study are available from our database in-hospital system.

Competing Interests

The authors declare no conflicts of interest.

Consent for Publication

Not applicable.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethics Approval and Consent to Participate

The Ethics Committee of Peking University People's Hospital granted ethical approval, as denoted by the approval number 2023PHB100-001. We affirm that our study adhered to the ethical standards outlined in the 1964 Declaration of Helsinki, along with its subsequent amendments or equivalent ethical benchmarks. All participants provided comprehensive written informed consent, and, where necessary, consent was also obtained from a parent or legal guardian.

Funding

This study was supported by the National Natural Science Foundation of China (Grant No.: 82202366), Clinical Medicine Plus X - Young Scholars Project, Peking University, the Fundamental Research Funds for the Central Universities (PKU2022LCXQ031), and Wu Jieping Medical Foundation Runze Fund for Critical Care Medicine (NO: 320·6750·2022-2-34).

ORCID iD

Guangjie Wang

Supplemental Material

Supplemental material for this article is available online.

Notes

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