Prognostic Accuracy of the Different Scoring Systems for Assessing Coagulopathy in Sepsis: A Retrospective Study

Abstract

There is no gold standard for the diagnosis of coagulation dysfunction in sepsis, and the use of the current scoring systems is still controversial. The purpose of this study was to assess the performance of sepsis-induced coagulopathy (SIC), the Japanese Association for Acute Medicine Disseminated Intravascular Coagulation (JAAM DIC), and the International Society on Thrombosis and Haemostasis overt DIC (ISTH overt-DIC). The relationship between each scoring system and 28-day all-cause mortality was examined. Among 452 patients (mean age, 65 [48,76] years), 306 [66.7%] were men, the median SOFA score was 6 [4,9], and the median APACHE II score was 15 [11,22]. A total of 132 patients (29.2%) died within 28 days. Both the diagnosis of SIC (AUROC, 0.779 [95% CI, 0.728–0.830], P < 0.001) and ISTH overt-DIC (AUROC, 0.782 [95% CI, 0.732–0.833], P < 0.001) performed equally well in the discrimination of 28-day all-cause mortality (between-group difference: SIC versus ISTH overt-DIC, −0.003 [95% CI, −0.025–0.018], P = 0.766). However, the SIC demonstrated greater calibration for 28-day all-cause mortality than ISTH overt-DIC (the coincidence of the calibration curve of the former is higher than that of the latter). The diagnosis of JAAM DIC was not independently associated with 28-day all-cause mortality in sepsis (RR, 1.115, [95% CI 0.660–1.182], P = 0.684). The SIC scoring system demonstrated superior prognostic prediction ability in comparison with the others and is the most appropriate standard for diagnosing coagulopathy in sepsis.

Keywords

sepsis coagulopathy SIC JAAM DIC ISTH overt-DIC

Introduction

Sepsis, defined as life-threatening organ dysfunction caused by a dysregulated host response to infection, is listed as one of the major global public health issues by the World Health Organization (WHO) due to its high prevalence, high mortality, high costs, complex pathogenesis, clinical heterogeneity, and so on.^1,2 Studies have shown that the interaction of inflammation and coagulation during sepsis can lead to coagulation dysfunction by causing excessive activation of the coagulation system, damage to the anticoagulation system, inhibition of the fibrinolytic system, damage to vascular endothelial cells, and abnormal activation and aggregation of platelets.^3–5 As one of the common complications, coagulation dysfunction, deemed to be a systemic response that compromises tissue circulation to cause multiorgan dysfunction, often manifests in the early stage of sepsis, runs through, and even worsens with disease progression.⁶ The latest data show that the incidence of coagulation dysfunction is as high as 50–70%, of which approximately 35% of cases can develop disseminated intravascular coagulation (DIC), and the mortality rate of patients with DIC is as high as 28–43%.^7–9 Therefore, early identification and diagnosis of coagulation dysfunction and timely initiation of corresponding treatment are critical to improving the prognosis of patients with sepsis.

However, there is no gold standard for the diagnosis of coagulation disorders because of their extremely complex pathophysiological mechanisms and considerably dynamic changes.¹⁰ In addition, neither any clinical manifestation nor single biomarker has been found to have adequate sensitivity, specificity, and reliability to diagnose or exclude coagulation disorders.¹¹ Thus, at present, the use of scoring systems for diagnosis and monitoring is recommended internationally. The commonly used scoring systems include the sepsis-induced coagulopathy (SIC) criteria developed by the Scientific and Standardization Committee (SSC) on DIC of the International Society on Thrombosis and Haemostasis (ISTH) in 2017,¹² the Japanese Association for Acute Medicine Disseminated Intravascular Coagulation (JAAM DIC) scoring system proposed in 2006,¹³ and the ISTH overt-DIC scoring system defined in 2001.¹⁴ Each scoring system has advantages and disadvantages, and there remains controversy about their applications in previous clinical studies.

The current study aimed to assess the performance of the SIC scoring system, the JAAM DIC scoring system, and the ISTH overt-DIC scoring system within the first 24 h in discriminating 28-day all-cause mortality among patients with sepsis and coagulation abnormalities.

Patients and Methods

Study Design and Participants

This is a retrospective observational study that was conducted at a single center. Patients with sepsis and coagulation abnormalities were also admitted to Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, from January 2017 to December 2019. Each patient was included once.

The protocol for this study was reviewed and approved by the Ethics Committee of Ruijin Hospital of Shanghai Jiao Tong University School of Medicine, China (approval number: 20191101; approval date: August 20, 2020). Due to retrospective, observational design, waivers of informed consent and HIPAA authorization were granted. Procedures followed in this study were in accordance with the ethical standards of the Helsinki Declaration of 1975, as most recently amended. The datasets used during the current study are available from the corresponding author on a reasonable request.

The inclusion criteria were as follows: (1) young and older adults (aged ≥18 years); (2) diagnosed with sepsis, according to the International Guidelines for Management of Sepsis and Septic Shock 2021²; and (3) combined with coagulation abnormalities (meeting any of the following criteria) on the day of sepsis diagnosis: platelet count (PLT) < 150 × 10⁹/L or >300 × 10⁹/L, activated partial thromboplastin time (APTT) > 38.7 s, prothrombin time (PT) > 16.0 s, fibrinogen (FIB) < 1.8 g/L or >3.5 g/L, fibrin or fibrinogen degradation products (FDP) > 5.0 mg/L, and D-dimer (DDI, ranging from 0 to 0.55 mg/L) > 0.55 mg/L.

The exclusion criteria were as follows: (1) a history of hematological diseases (such as hematological malignancies, idiopathic thrombocytopenia, hemophilia, etc; (2) history of liver damage (Child‒Pugh class C); (3) history of chronic renal failure requiring long-term renal replacement therapy; (4) history of long-term use of steroids or immunosuppressants; (5) history of long-term use of anticoagulation or antiplatelet drugs; (6) received chemotherapy or radiotherapy within 1 month before diagnosis; (7) complicated emergency bleeding or thromboembolic events (such as acute myocardial infarction, etc); (8) received cardiopulmonary resuscitation or emergency surgery within 12 h before diagnosis; and (9) pregnant or breastfeeding. It should be noted that when the individual components of SIC, JAAM DIC, and ISTH overt-DIC were unknown, the patient was assigned a missing score and was excluded from the analysis.

Data Collection

The following data were extracted: (1) demographic information: age, sex, and BMI (body mass index); (2) clinical information: the initial site of infection, whether blood products were transfused (on the day of diagnosis), whether renal replacement therapy was received (on the day of diagnosis), whether respiratory support was required (invasive mechanical ventilation, noninvasive mechanical ventilation, or no respiratory support; on the day of diagnosis), whether anticoagulation therapy was taken (on the day of diagnosis), whether antiplatelet therapy was taken (on the day of diagnosis), the average daily coast of treatment; (3) scoring systems calculated by physiological and laboratory parameters recorded on the day of the sepsis diagnosis: SIRS status (range, 0[best] to 4[worst] criteria), SOFA scores (range, 0[best] to 24[worst] points), APACHE II scores (range, 0[best] to 71[worst] points), SIC scores (range, 0[best] to 6[worst] points), JAAM DIC scores (range, 0[best] to 8[worst] points), and ISTH overt-DIC (range, 0[best] to 8[worst] points).The SIC criteria, JAAM DIC criteria, and ISTH overt-DIC criteria are listed in Table s1.

The primary outcome of this study was 28-day all-cause mortality.

Statistical Analysis

The mean values and standard deviation were calculated for continuous variables; the median and interquartile ranges were calculated for nonparametric data; and the frequency and percentage were calculated for categorical variables. Group comparisons were conducted using Pearson's chi-square tests or Fisher's exact tests for equal proportions, t-tests for normally distributed data, and Mann‒Whitney U tests otherwise. A correlation analysis was performed using scatter plots and Spearman's rank correlation. Multinomial logistic regression models were used to adjust for differences in prognostic variables and severity of disease, using age, BMI, APACHE II score, intra-abdominal infection, respiratory infection, bone and soft tissue infection, receiving renal replacement therapy, transfusion of blood product, taking anticoagulation therapy, and receiving invasive mechanical ventilation on the day of diagnosis as covariates. Model calibration was assessed using the Hosmer‒Lemeshow goodness-of-fit test (P > 0.05) and calibration plots. Discriminatory power was determined by comparing the area under the receiver operating characteristic curve (AUROC) for each score individually (adjusted analysis). A P-value of <0.05 was considered to be statistically significant unless otherwise specified. All analyses were performed using IBM SPSS Statistics 26.0.

Results

Study Population

Data pertaining to 877 adult admissions were recorded, and a final cohort of 452 patients was identified (Figure 1). As shown in Table 1, the median age was 65 (48,76) years, 67.7% (n = 306) were male, and the most common site of infection was intra-abdominal (50.9%), followed by the respiratory tract (25.2%). The initial APACHE II score was 15 (11, 22) points, the initial SOFA score was 6 (4.9) points, and both were significantly higher among the nonsurvivors (P < 0.001). The average cost of treatment was approximately RMB 3567.39 (2390.05, 5650.66) yuan per day, and the cost for the nonsurvivors was higher (P < 0.001). There were 132 patients (29.2%) who had died within 28 days after the diagnosis of sepsis.

Figure 1.

Eligible population and exclusion criteria.

Table 1.

Baseline Characteristics of Patients.

	All (n = 452)	Survivor (n = 320)	Nonsurvivor (n = 132)	P
Male	306 (67.7)	218 (68.1)	88 (66.7)	0.763^b
Age (years)	65 (48, 76)	63 (45, 76)	67 (55, 77)	0.010^a
BMI (Kg/m²)	23.4 (20.3, 26.0)	23.8 (20.8, 26.3)	22.5 (19.3, 24.5)	0.001^a
The initial site of infection
Intra-abdominal	230 (50.9)	175 (54.7)	55 (41.7)	0.012^b
Respiratory	114 (25.2)	68 (21.3)	46 (34.8)	0.002^b
Bone and soft tissue	31 (6.9)	15 (11.4)	16 (5.0)	0.015^b
Bloodstream	26 (5.8)	20 (6.3)	6 (4.5)	0.479^b
Urinary tract	22 (4.9)	20 (6.3)	6 (4.5)	0.033^b
Others	52 (11.5)	38 (11.9)	14 (10.6)	0.701^b
SIRS	2 (2, 3)	3 (2, 3)	2 (2, 3)	0.831^a
SOFA	6 (4, 9)	6 (4, 9)	8 (5, 13)	<0.001^a
APACHE II	15 (11, 22)	14 (10, 19)	18 (14, 25)	<0.001^a
Laboratory parameters
PLT (*10^9/L)	131 (81, 219)	128 (82, 209)	146 (70, 229)	0.622^a
APTT (s)	33.1 (29.1, 37.9)	32.5 (28.6, 36.8)	35.3 (30.0, 45.0)	<0.001^a
PT (s)	14.5 (13.1, 16.2)	14.1 (13.0, 15.5)	15.9 (13.4, 19.4)	<0.001^a
PT-INR	1.24 (1.12, 1.39)	1.20 (1.11, 1.32)	1.36 (1.14, 1.65)	<0.001^a
FIB (g/L)	4.2 (2.7, 5.7)	4.5 (3.1, 5.9)	3.5 (2.0, 5.3)	<0.001^a
FDP (mg/L)	15.80 (7.73, 37.53)	14.90 (7.33, 34.40)	17.40 (8.40, 44.40)	0.124^a
DD (mg/L)	4.50 (2.22, 11.86)	4.34 (2.22, 10.27)	4.95 (2.27, 13.59)	0.232^a
The diagnosis of coagulopathy
SIC	115 (25.4)	64 (20.0)	51 (38.6)	<0.001^b
JAAM DIC	202 (44.7)	137 (42.8)	65 (49.2)	0.211^b
ISTH overt-DIC	55 (12.2)	24 (7.5)	31 (23.5)	<0.001^b
Treatment on the day of diagnosis
Renal replacement	16 (3.5)	6 (1.9)	10 (7.6)	0.009^c
Blood product	85 (18.8)	48 (15.0)	37 (28.0)	0.001^b
Anticoagulation	92 (20.4)	73 (22.8)	19 (14.4)	0.043^b
Antiplatelet	8 (1.8)	7 (2.2)	1 (0.8)	0.447^c
Respiratory support			0.001^b
Invasive	112 (24.8)	63 (19.7)	49 (37.1)	<0.001^b
Noninvasive	274 (60.6)	206 (64.4)	68 (51.5)	0.011^b
No	66 (14.6)	51 (15.9)	15 (11.4)	0.211^b
The average daily cost (RMB yuan/day)	3567.39 (2390.05, 5650.66)	2996.43 (2152.56, 4530.24)	6484.51 (4403.76, 10648.10)	<0.001^a

Abbreviations: BMI, body mass index; SIRS, Systemic Inflammatory Response Syndrome; SOFA, Sequential Organ Failure Assessment; APACHE II, Acute Physiology and Chronic Health Evaluation II; PLT, platelet count; APTT, activated partial thromboplastin time; PT, prothrombin time; PT-INR, prothrombin time-international normalized ration; FIB, fibrinogen; FDP, fibrin or fibrinogen degradation products; DD, D-dimer.

Mann–Whitney U test. ^bPearson's chi-square tests. ^cFisher's exact tests.

SIC, JAAM DIC, ISTH Overt-DIC, and Coagulation Parameters

Of the study cohort, 115 patients (25.4%) were diagnosed as positive for SIC, 202 patients (44.7%) had a diagnosis of JAAM DIC, and 55 patients (12.2%) had a disease that was consistent with ISTH overt-DIC (Table 1). There was a significant difference in the positive rate of SIC and ISTH overt-DIC between the survivors and the nonsurvivors (20.0% vs 38.6%, P < 0.001 and 23.5% vs 7.5%, P < 0.001, respectively), while there was no significant difference in the positive rate of JAAM DIC between the two groups (42.8% vs 49.2%, P = 0.211) (Table 1).

A total of 44 patients met the diagnostic criteria for both SIC and ISTH overt-DIC, 28 of which died within 28 days after enrollment. There are 96 patients who met the diagnostic criteria for both SIC and JAAM DIC, 41 of which died within 28 days after enrollment. There are 53 patients who met the diagnostic criteria for both JAAM DIC and ISTH overt-DIC, 30 of which died within 28 days after enrollment. The concordance was moderate for SIC and ISTH overt-DIC (κ=0.423, P < 0.001) and moderate between SIC and JAAM DIC (κ=0.416, P < 0.001). The concordance was poor between JAAM DIC and ISTH overt-DIC (κ=0.273, P < 0.001). Concordance among different scoring systems is shown in Figure s1.

The 28-day all-cause mortality of the patients with SIC was 44.3% (51 of 115 patients) versus that of without SIC 24.0% (81 of 337 patients), P < 0.001 (between-group difference). The 28-day all-cause mortality of the patients with ISTH overt-DIC was 56.4% (31 of 55 patients) versus that of without ISTH overt-DIC 25.4% (101 of 397 patients), P < 0.001 (between-group difference). The 28-day all-cause mortality of the patients with JAAM DIC was 32.3% (65 of 202 patients) versus that of without JAAM DIC 63.5% (101 of 250 patients), P = 0.211 (between-group difference). The distributions of each score and their relationship with 28-day all-cause mortality are presented in Figure s2.

For the coagulation parameters at baseline (Table 1), APTT, PT, and PT-INR were higher (P < 0.001), and FIB was lower (P < 0.001) among the nonsurvivors. In contrast, PLT, FDP, and DD did not differ between the survivors and the nonsurvivors (P = 0.622, P = 0.124, P = 0.232, respectively). The distribution of each coagulation parameter is detailed in Figure s3.

Univariate and Multivariate Analyses of 28-Day All-Cause Mortality

Both univariate logistic regression analyses and multivariate analyses were performed to examine the association between mortality and each variable (Table 2). The multivariate analyses showed that the diagnoses of SIC and ISTH overt-DIC were independently associated with 28-day all-cause mortality (RR, 2.493 [95% CI 1.414–4.396], P = 0.002 and RR, 3.925 [95% CI 1.810–8.512], P = 0.001), in contrast to the diagnosis of JAAM DIC (RR, 1.115, [95% CI 0.660–1.182], P = 0.684).

Table 2.

Univariate and Multivariate Analyses of 28-day All-Cause Mortality.

Predictor	Univariate		Multivariate
	Univariate		Model 1		Model 2		Model 3
	RR (95% CI)	P	RR (95% CI)	P	RR (95% CI)	P	RR (95% CI)	P
Male	1.069 (0.695, 1.645)	0.091
Age (years)	1.015 (1.004, 1.027)	0.008	1.011 (0.995, 1.027)	0.183	1.010 (0.995, 1.026)	0.198	1.015 (0.999, 1.032)	0.070
BMI (kg/m²)	0.931 (0.889, 0.976)	0.003	0.952 (0.901, 1.007)	0.086	0.953 (0.902, 1.007)	0.088	0.959 (0.906, 1.014)	0.141
The initial site of infection
Intra-abdominal	0.592 (0.393, 0.892)	0.012	1.281 (0.557, 2.948)	0.560	1.242 (0.548, 2.817)	0.604	1.543 (0.652, 3.654)	0.324
Respiratory	1.982 (1.268, 3.100)	0.003	3.032 (1.221, 7.530)	0.017	2.852 (1.163, 6.995)	0.022	3.439 (1.355, 8.728)	0.009
Bone and soft tissue	2.436 (1.167, 5.085)	0.018	4.166 (1.308, 13.263)	0.016	3.718 (1195, 11.563)	0.023	5.018 (1.545, 16.297)	0.007
Bloodstream	0.714 (0.280, 1.821)	0.481
Urinary tract	0.231 (0.053, 1.002)	0.050
Others	0.880 (0.460, 1.685)	0.701
SIRS	0.989 (0.823, 1.188)	0.905
SOFA	1.176 (1.117, 1.238)	<0.001
APACHE II	1.097 (1.061, 1.134)	<0.001	1.067 (1.018, 1.117)	0.006	1.075 (1.027, 1.125)	0.002	1.060 (1.011, 1.110)	0.015
Laboratory parameters
PLT (*10^9/L)	1.001 (0.999, 1.003)	0.483
APTT (s)	1.021 (1.007, 1.035)	0.003
PT (s)	1.203 (1.128, 1.284)	<0.001
PT-INR	7.943 (3.810, 16.558)	<0.001
FIB (g/L)	0.774 (0.668, 0.871)	<0.001
FDP (mg/L)	1.007 (1.000, 1.014)	0.044
DD (mg/L)	1.020 (1.000, 1.040)	0.055
The diagnosis of coagulopathy
SIC	2.519 (1.614, 3.929)	<0.001	2.493 (1.414, 4.396)	0.002
JAAM DIC	1.296 (0.863, 1.946)	0.212			1.115 (0.660, 1.882)	0.684
ISTH overt-DIC	3.785 (2.122, 6.753)	<0.001					3.925 (1.810, 8.512)	0.001
Treatment on the day of diagnosis
Renal replacement	4.290 (1.526, 12.058)	0.006	5.392 (1.538, 18.898)	0.008	5.880 (1.748, 19.783)	0.004	6.850 (1.939, 24.202)	0.003
Blood product	2.207 (1.354, 3.596)	0.001	1.733 (0.861, 3.488)	0.123	2.014 (1.032, 3.930)	0.040	1.804 (0.897, 3.629)	0.098
Anticoagulation	0.569 (0.328, 0.988)	0.045	0.253 (0.121, 0.531)	<0.001	0.921 (0.453, 1.871)	0.820	0.238 (0.112, 0.508)	<0.001
Antiplatelet	0.341 (0.042, 2.802)	0.317
Respiratory support
Invasive	2.644 (1.332, 5.252)	0.005	0.959 (0.461, 1.992)	0.910	1.115 (0.660, 1.882)	0.684	0.980 (00.471, 2.039)	0.957
Noninvasive	1.122 (0.593, 2.123)	0.723
No	-	0.001

Calibration and Discrimination for SIC and ISTH Overt-DIC (Adjust Analysis)

The calibration of 28-day all-cause mortality was significantly higher using SIC (χ² = 3.222, P = 0.920) than ISTH overt-DIC (χ² = 14.090, P = 0.079), with the difference being statistically significant (the former's expected curve was more coincident with its observed curve) when considered in conjunction with baseline prediction mortality (Figure 2). Both the diagnosis of SIC (AUROC, 0.779 [95% CI, 0.728–0.830], P < 0.001) and ISTH overt-DIC (AUROC, 0.782 [95% CI, 0.732–0.833], P < 0.001) performed equally well in the discrimination of 28-day all-cause mortality (between-group difference: SIC vs ISTH overt-DIC, −0.003 [95% CI, −0.025–0.018], P = 0.766) when adjusted (Figure 3).

Figure 2.

(a–b) SIC and ISTH overt-DIC calibration plot of expected versus observed rates of 28-day all-cause mortality (n = 364 after adjustment).

Figure 3.

Area under the receiver operating characteristic curves (AUROCs) for discriminatory capacity for 28-day all-cause mortality for SIC and ISTH overt-DIC (diagnose of each scoring system) (n = 364 after adjustment).

The calibration and discrimination of the JAAM DIC diagnosis were not reported in this article because it was not defined as an independent predictor of death, as previously described.

Discussion

In the early onset of sepsis, along with inflammation, the coagulation system is usually activated in the host as a defensive role to absorb and remove microorganisms. However, as inflammation continues, coagulation dysfunction occurs because of the widely activated coagulation system, the collapsed anticoagulation system, and so on. Coagulation dysfunction, manifested by thrombosis and the consumption of platelets and clotting factors, is considered to be an important factor leading to poor prognosis in sepsis. Therefore, the establishment of diagnostic criteria is crucial for identifying patients, guiding treatment, and determining prognosis.

However, there is no gold standard, and the results of previous studies are controversial. Although with high specificity, ISTH overt-DIC may lead to a delayed diagnosis and missed opportunities for intervention by ignoring the different characteristics of coagulopathy under their basic etiologies.¹⁵ JAAM DIC, reflecting the interaction of inflammation and coagulation, is rarely used outside Japan due to its low specificity.¹³ Although SIC is easy to calculate and consistent with the pathophysiology of fibrinolytic inhibition and high organ dysfunction in sepsis, its predictive performance needs to be proven to be sufficient.^12,16 For example, a retrospective study conducted in the ICU of The First Hospital of China Medical University showed that there was no significant difference in the prevalence of SIC between survivors and nonsurvivors (62.9% vs 74.3%, P = 0.055), and the predictive accuracy of SIC was less than that of ISTH overt-DIC (AUROC, 0.658 ± 0.036 vs 0.684 ± 0.033).¹⁷ This study retrospectively evaluated the application of SIC, JAAM DIC, and ISTH overt-DIC scoring systems in patients with sepsis.

In this study, a total of 452 patients were included, whose mortality was 29.9%, which was similar to the 24.4%–35.5% reported previously.^18–21 The positive rates of each scoring system were lower than those of previous studies (60.8%–84.8% for SIC,^{12,17,22–24} 61.0%–91.4% for JAAM DIC,^13,14,22,25 and 20.3%–29.3% for ISTH overt-DIC^{14,17,22,23,25}), which may be because the patients included in the previous studies, whose SOFA and APACHE II scores were higher than those in this research, were only admissible from the ICU, in addition to the general wards.^17,22–26 Consistent with previous studies, the positive rate of SIC in this current study was approximately twice than that of ISTH overt-DIC,^22,27,28 which may be related to the inclusion of FIB in the latter. FIB is an acute-phase protein important for the coagulation cascade,²⁹ but studies of its cutoff in sepsis with coagulopathy are inconclusive.³⁰ Previous studies and this study have shown that FIB levels are elevated in the early stage of sepsis, which may result from the release of plasminogen activation inhibitor-1 (PAI-1), and the activation of thrombin activates fibrinolytic inhibitors (TAFI).^31,32 Therefore, the cutoff value of FIB at ≤1.0 g/L in the ISTH overt-DIC scoring system may reduce the diagnostic efficacy.^33,34 It is worth mentioning that the prognostic calibration of SIC in this study was higher than that of ISTH overt-DIC, and there were no previous studies available for comparison.

We found that the positive rate of JAAM DIC was not significantly different between the survivors and the nonsurvivors, as was the mortality between the JAAM DIC positive and negative groups. We also found that the diagnosis of JAAM DIC was not independently associated with 28-day all-cause mortality in sepsis. These negative results should be related to the statistical indifference in SIRS (3 vs 2 points, P = 0.831), FDP (14.90 vs 17.40 mg/L, P = 0.124), and DD (4.34 vs 4.95 mg/L, P = 0.232). Several cohort studies have shown that the SIRS criteria, with its high sensitivity and low specificity, can lead to overdiagnosis and overtreatment.^35,36 In recent years, it has been found that FDP and DD, which are biomarkers of hypercoagulability and fibrinolysis, are generally elevated in patients with infection or suspected infection, regardless of the severity.³⁷

In conclusion, compared with JAAM DIC and ISTH overt-DIC, the SIC scoring system had the best prognostic prediction ability and was the simplest to calculate. However, questions such as the pathophysiological state of patients with the diagnosis of SIC and whether the SIC can be used to guide the selection of intervention timing still need further research. In addition, the combination of novel biomarkers (eg, neutrophil extracellular traps, NETs), emerging detection technologies (eg, thromboelastometry, TEG), or machine learning and traditional indicators is expected to be a new direction of research.^38–42

Strengths

This study had several strengths. First, this study, in which all of the patients in general wards and ICUs were included, covered a wider range of patients than other studies, which included patients with ICU admission only. Second, this study offered a more comprehensive and objective summary that can be useful in guiding clinical practice by conducting pairwise comparisons of different scoring systems.

Limitations

First, this study is a single-center, retrospective study of low quality, and the conclusions still need further verification by prospective, multicenter, and large-sample studies. Second, in this study, the relationship between continuous dynamic changes in coagulation function and prognosis could not be explored, and only the clinical data on the day of enrollment could be collected. Third, this study only evaluated the prognostic prediction performance of each scoring system, and whether each of them can be used to guide anticoagulation therapy needs further observation. Fourth, deep vein thrombosis, bleeding, and other indices were not included in this study due to data limitations.

Conclusions

In our study, the SIC scoring system, in comparison with JAAM DIC and ISTH overt-DIC, demonstrated superior prognostic prediction ability for 28-day all-cause mortality among patients with sepsis and abnormal coagulation. Research with a larger sample size, more comprehensive outcomes, and further confounders is necessary.

Supplemental Material

sj-docx-1-cat-10.1177_10760296231207630 - Supplemental material for Prognostic Accuracy of the Different Scoring Systems for Assessing Coagulopathy in Sepsis: A Retrospective Study

Supplemental material, sj-docx-1-cat-10.1177_10760296231207630 for Prognostic Accuracy of the Different Scoring Systems for Assessing Coagulopathy in Sepsis: A Retrospective Study by Yuwei Chen, Weiwei Chen, Fuhua Ba, Yanjun Zheng, Yi Zhou, Wen Shi, Jian Li, Zhitao Yang, Enqiang Mao, Erzhen Chen and Ying Chen in Clinical and Applied Thrombosis/Hemostasis

Footnotes

Non-standard Abbreviations and Acronyms

Acknowledgments

The study was conducted with the helpful contributions of all the emergency staff.

Authors’ Contributions

Chen YW and Chen WW contributed equally to this article and wrote the paper. Chen EZ and Mao EQ conceived the idea for this project. Chen Y, Yang ZT, Chen WW, and Chen YW designed the study. Ba FH, Zheng YJ, Zhou Yi, and Shi W contributed to the data analysis and synthesis of the study. Chen YW and Li J performed the statistical analyses. All authors contributed to the survey development, pilot phase, the revision of the paper, and approval of the final version for submission. All authors had full access to all the data in the study and had final responsibility for the decision to submit for publication. All authors read and approved the final manuscript.

Availability of Data and Materials

The datasets used during the current study are available from the corresponding author on reasonable request.

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 study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Ruijin Hospital of Shanghai Jiao Tong University School of Medicine, China (approval number: 20191101; approval date: August 20, 2020).

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by National Natural Science Foundation of China (grant number 82270087), Shanghai Municipal Human Resources Development Program for Outstanding Leaders in Medical Disciplines, Shanghai Shen Kang Hospital Development Center (grant number SHDC22021304, SHDC2020CR1028B) and Science and Technology Commission of Shanghai Municipality (grant number 21YF1440600).

ORCID iDs

Yuwei Chen

Enqiang Mao

Supplemental Material

Supplemental material for this article is available online.

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