DOI: https://doi.org/10.21203/rs.3.rs-1900275/v1
Background: Sepsis is the most common cause of death in hospitals, and intra-abdominal infection (IAI) accounts for a large portion of the causes of sepsis. We investigated the clinical outcomes and factors influencing mortality of patients with sepsis due to IAI.
Methods: This post-hoc analysis of a prospective cohort study included 2,126 patients with sepsis who visited 16 tertiary care hospitals in Korea (September 2019–February 2020). The analysis included 219 patients aged > 19 years who were admitted to intensive care units owing to sepsis caused by IAI.
Results: The incidence of septic shock was 47% and was significantly higher in the non-survivor group (58.7% vs 42.3%, p=0.028). The overall 28-day mortality was 28.8%. In multivariate logistic regression, after adjusting for age, sex, Charlson comorbidity index, and lactic acid, only coagulatory dysfunction (p=0.001, odds ratio: 2.78 [1.47–5.23]) was independently associated, and after adjusting for each risk factor, only simplified acute physiology score III (p=0.014) and continuous renal replacement therapy (p<0.001) were independently associated with higher 28-day mortality.
Conclusions: Considering the independent risk factors influencing 28-day mortality, more intensive care may be needed for patients with coagulopathy than for patients with other organ dysfunctions caused by IAI.
Sepsis is an uncontrolled reaction of the host to infection, which can be potentially life-threatening. Accurate calculation of the global burden of sepsis is difficult. A recent study has reported approximately 48.9 million cases and 11 million sepsis-related deaths in 2017. This accounts for nearly 20% of all deaths worldwide, and sepsis is the most common cause of death in hospitals in the United States [1, 2]. Sepsis is a major public health issue, and the costs for treating sepsis in hospitals have increased, exceeding US $24 billion per year [2, 3]. Likewise, the incidence of sepsis and the treatment costs in Korea have steadily increased, particularly among older adults.
Intra-abdominal infection (IAI) is defined as an inflammatory reaction to bacteria and their toxins in the peritoneum, resulting in a purulent exudate in the peritoneal cavity [4–7]. Among all the causes of sepsis, IAI is reportedly the second most common cause, with a relatively high mortality rate of nearly 30.0% [8–10]. In particular, most sepsis cases in surgical intensive care units (ICUs) are caused by IAI. Source control and antibiotic use are essential in the treatment of these patients. Various forms of IAIs may exist, including those in the hepatobiliary tract, stomach, small bowel, and colon. In addition, there are differences in mortality and clinical outcomes according to the type of organ, degree of anatomical disruption, and duration of IAI [4, 6, 8]. Treatment of IAI can be difficult because the spectrum of infection is wide compared with that of other infection causes and source control, wherein drainage or surgical treatment is often required.
However, studies on the clinical outcomes and impact of organ dysfunction in patients with sepsis due to IAI are limited. Therefore, the primary objective of our study was to investigate the clinical outcomes and the factors affecting the mortality in patients with sepsis due to IAI. The secondary objective was to determine the impact of organ dysfunction on mortality rates.
This post-hoc analysis of a prospective cohort study was performed by the Korean Sepsis Alliance (KSA) encompassing 16 tertiary or university-affiliated hospitals in Korea. The Steering Committee developed the research data collection methods to manage the sepsis data platform, periodically reviewed the progress of each study, and supervised the overall research progress in association with the Korea Disease Control and Prevention Agency (KDCA). The data used in this study were screened from all consecutive patients who visited the participating hospitals for six months (September 1, 2019, to February 29, 2020).
This prospective cohort study analyzed data from the Korean sepsis registry, and this study was already deliberated as a service project by the KDCA. The study was approved by the institutional review boards (IRB) of all participating hospitals, including the IRB of Asan Medical Center (approval number 2018 − 0675). Data were collected and analyzed in an ethical manner while protecting the patients' right to privacy. The requirement for informed consent was waived owing to the non-interventional, observational characteristics by the IRB of all participating hospitals, including the IRB of Asan Medical Center (approval number 2018 − 0675).
Our study enrolled a total of 2,126 patients with sepsis who were admitted to the participating hospitals for 6 months. Of these patients, 901 were treated in ICUs. Finally, the study included 219 patients who were admitted to the ICU due to sepsis caused by IAI (Fig. 1). Sepsis patients aged ≥ 19 years were included and followed up until death or discharge. As defined by the Clinical Criteria of the Third International Consensus Definition (Sepsis-3), sepsis was defined as a life-threatening organ dysfunction resulting from an uncontrolled host response to infection [11]. Organ dysfunction was included in the definition of sepsis, and the presence or absence of organ dysfunction was determined using a Sequential Organ Failure Assessment (SOFA) score. In this study, sepsis was diagnosed if the patient met the following two conditions: (1) suspicion or confirmation of infection and (2) increase in SOFA score by two points or more when an event occurred. The base SOFA score of each organ was assumed to be zero for patients with no known pre-existing organ dysfunction, and patients with a SOFA score of two or higher at the time of the event were enrolled in the study. In community-acquired sepsis, time zero was defined as the time of an emergency room triage visit. In-hospital-acquired sepsis, time zero was defined as the first time the rapid response team recognized the sepsis. Source control was defined as the actual practice of percutaneous drainage or surgical treatment to eliminate IAI-causing infectious sources.
All trained research coordinators in each participating hospital completed their entry into the shared data platform, and the coordinating hospital evaluated the quality of the data for completeness and logical errors. The data collected retrospectively in each hospital were as follows: (1) patient characteristics, including age, sex, body mass index (BMI), Charlson comorbidity index (CCI), physiological status, medical history, SOFA score, simplified acute physiology score III (SAPS 3), and laboratory data at time zero; (2) clinical results, including the duration from time zero to antibiotic administration, source control implementation, and duration from time zero to source control implementation; (3) infection and microbiological data, including the type of isolated bacteria and fungi, bacteremia occurrence, multidrug resistance (MDR) occurrence, and location of infection; and (4) organ dysfunction data, including the type of organ dysfunction results and analysis of the number of organ dysfunctions. Additional data compared with those in previous studies were collected. However, these were not used in our study.
Statistical analysis was conducted by the staff of the coordinating center and by a professor at the Department of Clinical Epidemiology and Biostatistics, Asan Medical Center, who did not participate in data collection.
Data are presented as numbers (percentages) or as mean ± standard deviation. The characteristics and clinical data of the survivor and non-survivor groups were compared using the chi-square test or Fisher’s exact test (for categorical variables) and Student’s t-test (for continuous variables). Risk factors associated with 28-day mortality were analyzed by univariate and then multivariate logistic regression, and the degree of association with 28-day mortality was presented as an independent factor by means of odds ratios (ORs) with their corresponding 95% confidence intervals. Infection profile data were analyzed using the number (percentage) or mean ± standard deviation. The microbiological data were described by total numbers and proportions, which showed the distribution of bacteria and fungi in patients with sepsis due to IAI. Multivariate logistic regression analysis was used to estimate the association between organ dysfunction and 28-day mortality, with unadjusted and adjusted evaluations. We adjusted 28-day mortality for age, sex, CCI, and lactic acid levels. We used OR to present the impact of organ dysfunction on 28-day mortality and analyzed the impact of the number of organ dysfunctions on 28-day mortality using ORs in the logistic regression analysis. Differences were considered statistically significant at P < 0.05. All analyses were conducted using SPSS software (version 25.0; IBM Corp., Armonk, NY, USA).
During the 6-month study period, total 2,126 patients were admitted owing to sepsis at the participating hospitals; 219 (10.3%) were admitted to the ICU owing to sepsis caused by IAI according to collected data review. The 28-day mortality rate of all enrolled patients with sepsis was 28.1% (n = 598/2,126). Among these patients, the mortality rate was 28.8% (n = 63/219) for sepsis due to IAI in the ICU.
Patient characteristics and clinical data at the time of sepsis diagnosis are summarized in Table 1. The mean age of the patients was 69.4 ± 13.1 years, and 53.9% were men. The mean BMI was 23.0 ± 4.2 kg/m2; no significant difference was noted in BMI between the survivor and non-survivor groups. The mean CCI in the non-survivor group was higher than that of the survivor group, with significant differences (5.9 ± 3.0 vs. 5.1 ± 2.3, p = 0.011). The initial Eastern Cooperative Oncology Group scores ranged from 0 to 4. However, there was no significant difference in the scores between the two groups (p = 0.075). The incidence of septic shock was 47%, and was significantly higher in the non-survivor group than in the survivor group (58.7% vs. 42.3%, p = 0.028). The initial lactate level was significantly higher in the non-survivor group than in the survivor group (7.2 ± 5.0 vs. 4.5 ± 3.1, p < 0.001). In addition, the initial SOFA score was significantly higher in the non-survivor group than in the survivor group (12.2 ± 4.6 vs. 8.4 ± 3.1, p < 0.001). Moreover, patients who underwent continuous renal replacement therapy (CRRT) had a higher mortality rate than those who did not undergo CRRT (68.3% vs. 16%, p < 0.001). By contrast, no significant difference was noted in the number of patients who were prescribed steroids to treat sepsis between the two groups (26.9% vs. 34.9%, p = 0.239). In the initial laboratory tests at time zero, total bilirubin, C-reactive protein, procalcitonin, and brain natriuretic peptide levels were higher in the non-survivor group.
All patients (n = 219) |
Survivors (n = 156) |
Non-survivors (n = 63) |
P-value |
|
---|---|---|---|---|
Age (years), mean (± SD) |
69.4 ± 13.1 |
69.1 ± 13.0 |
70.2 ± 13.5 |
0.886 |
Sex, n (%) |
0.538 |
|||
Male |
118 (53.9) |
82 (52.6) |
36 (57.1) |
|
BMI (kg/m2), mean (± SD) |
23.0 ± 4.2 |
22.8 ± 3.9 |
23.6 ± 4.8 |
0.091 |
Charlson comorbidity index, mean (± SD) |
5.3 ± 2.6 |
5.1 ± 2.3 |
5.9 ± 3.0 |
0.011 |
Initial ECOG score, n (%) |
0.075 |
|||
0 |
52 (23.7) |
39 (25.0) |
13 (20.6) |
|
1 |
59 (26.9) |
46 (29.5) |
13 (20.6) |
|
2 |
47 (21.5) |
31 (19.9) |
16 (25.4) |
|
3 |
38 (17.4) |
21 (13.5) |
17 (27.0) |
|
4 |
23 (10.5) |
19 (12.2) |
4 (6.3) |
|
Septic shock, n (%) |
103 (47.0) |
66 (42.3) |
37 (58.7) |
0.028 |
Initial lactate level (mmol/L), mean (± SD) |
5.3 ± 4.0 |
4.5 ± 3.1 |
7.2 ± 5.0 |
< 0.001 |
Initial SOFA score, mean (± SD) |
9.5 ± 4.0 |
8.4 ± 3.1 |
12.2 ± 4.6 |
< 0.001 |
SAPS 3 score, mean (± SD) |
73.9 ± 16.4 |
70.1 ± 14.4 |
83.4 ± 17.3 |
0.098 |
CRRT, n (%) |
68 (31.1) |
25 (16.0) |
43 (68.3) |
< 0.001 |
Steroid use, n (%) |
64 (29.2) |
42 (26.9) |
22 (34.9) |
0.239 |
Initial laboratory results |
||||
Platelet count (103/uL) |
170.7 ± 125.6 |
184.5 ± 130.0 |
136 ± 107.2 |
0.299 |
Creatinine level (mg/dL) |
2.1 ± 1.9 |
1.96 ± 2.0 |
2.40 ± 1.5 |
0.796 |
Total bilirubin level (mg/dL) |
3.0 ± 5.1 |
2.2 ± 2.8 |
4.9 ± 8.2 |
< 0.001 |
CRP level (mg/dL) |
14.2 ± 10.3 |
14.3 ± 9.5 |
14.0 ± 12.2 |
0.027 |
Procalcitonin level (ng/ml) |
37.0 ± 67.2 |
31.7 ± 50.0 |
50.6 ± 97.9 |
0.006 |
BNP level (pg/mL) |
699.0 ± 1207.3 |
458.6 ± 886.0 |
1312.0 ± 1659.0 |
< 0.001 |
Time zero to time of antibiotics administration (min) |
184.7 ± 303.0 |
171.4 ± 238.8 |
217.5 ± 422.8 |
0.495 |
Source control, n (%) |
90 (41.1) |
73 (46.8) |
17 (27.0) |
0.007 |
Source control time (h) |
22.1 ± 37.0 |
22.9 ± 39.4 |
18.5 ± 24.9 |
0.489 |
Number of organ dysfunction, n (%) |
1.7 ± 1.3 |
1.4 ± 1.21 |
2.3 ± 1.4 |
0.019 |
Data are shown as mean ± standard deviation or number (percentage). | ||||
SD, standard deviation; BMI, body mass index; ECOG, Eastern Cooperative Oncology Group; SOFA, Sequential Organ Failure Assessment; SAPS 3, simplified acute physiology score III; CRRT, continuous renal replacement therapy; CRP, C-reactive protein; BNP, brain natriuretic peptide |
In addition, there was no significant difference between the two groups in the duration from time zero to the administration of antibiotics and source control. However, the number of patients who underwent source control through percutaneous drainage or surgical treatment was significantly higher in the survivor group than in the non-survivor group (46.8% vs. 27%, p = 0.007). The mean number of organ dysfunction was significantly higher in the non-survivor group than in the survivor group (2.3 ± 1.4 vs. 1.4 ± 1.2, p = 0.019).
Table 2 shows the distribution of the isolated microbiological pathogens expressed by per species percentage of bacteria and fungi from patients with sepsis due to IAI. Of the 219 patients, 157 (71.7%) were identified with a causative pathogen. Among the patients with isolated pathogens, gram-negative bacteria were found in 81.5%, gram-positive bacteria in 32.5%, and fungi in 4.5% of patients. Among the isolated causative pathogens in our study, the most common pathogen was Escherichia coli (48.4%), followed by Klebsiella pneumoniae (22.9%), Enterococcus faecium (8.9%), and Enterococcus faecalis (5.7%). Additionally, Acinetobacter baumannii (4.5%), Enterobacter cloacae (3.8%), Klebsiella oxytoca (3.2%), and Pseudomonas aeruginosa (3.2%) were among the gram-negative bacteria, and Staphylococcus aureus (1.8%) and Corynebacterium striatum (0.5%) were among the gram-positive bacteria. Moreover, Candida albicans (3.2%), Candida glabrata (2.5%), and Candida krusei (0.6%) were the identified fungi.
No. of Patients (Total, n = 157) |
% Total |
|
---|---|---|
Gram-positive |
51 |
32.5 |
Enterococcus faecium |
14 |
8.9 |
Enterococcus faecalis |
9 |
5.7 |
Staphylococcus aureus |
4 |
1.8 |
Corynebacterium striatum |
1 |
0.5 |
Others |
26 |
11.9 |
Gram-negative |
128 |
81.5 |
Escherichia coli |
76 |
48.4 |
Klebsiella pneumoniae |
36 |
22.9 |
Acinetobacter baumannii |
7 |
4.5 |
Enterobacter cloacae |
6 |
3.8 |
Klebsiella oxytoca |
5 |
3.2 |
Pseudomonas aeruginosa |
5 |
3.2 |
Others |
24 |
15.3 |
Fungus |
7 |
4.5 |
Candida albicans |
5 |
3.2 |
Candida glabrata |
4 |
2.5 |
Candida krusei |
1 |
0.6 |
There was no significant difference in the rate of identified causative bacteria between the survivor and non-survivor groups (75% vs. 63.5%, p = 0.087). Bacteremia occurred in 49.3% of patients. However, no significant difference was noted between the two groups (50.8% vs. 48.7%, p = 0.781). Among the identified pathogens, the survivor and non-survivor groups showed almost similar ratios in gram-positive bacteria. Fungi were detected in 4.5% of patients with identified pathogens. However, there was no significant difference in rate of identified fungi between the two groups (5.1% vs. 2.5%, p = 0.390). Mixed growth was defined as the detection of more than one type of gram-positive, gram-negative, and fungal pathogens. A mixed growth accounted for 19.1% of all patients with identified causative pathogens, with no significant difference, although the rate was higher in the non-survivor group than in the survivor group (27.5% vs. 16.2%, p = 0.304). MDR was defined as the antimicrobial resistance of a microorganism to at least one antibiotic in three or more antimicrobial categories [12]. The overall rate of MDR pathogens was higher in the survivor group than in the non-survivor group. However, there was no significant difference between the two groups (47.9% vs. 40.0%, p = 0.134). Among the MDR pathogens, the most common were Enterobacteriaceae (54.2%), followed by Enterococcus spp. (12.5%), Acinetobacter spp. (4.2%), Staphylococcus aureus (2.8%), and Pseudomonas aeruginosa (2.8%). Of the 219 patients in our study, 61.6% cases (n = 135) were community-acquired and 38.4% (n = 84) were healthcare-acquired. However, no significant difference was noted in the mortality rate depending on where the infection was acquired (p = 0.960) (Table 3).
All patients (n = 219) |
Survivors (n = 156) |
Non-survivors (n = 63) |
P-value |
|
---|---|---|---|---|
Identified pathogens, n (%) |
157 (71.1) |
117 (75.0) |
40 (63.5) |
0.087 |
Bacteremia, n (%) |
108 (49.3) |
76 (48.7) |
32 (50.8) |
0.781 |
Type of bacteria, n (%) |
||||
Gram-positive |
51 (32.5) |
34 (29.1) |
17 (42.5) |
0.112 |
Gram-negative |
128 (81.5) |
95 (81.2) |
33 (82.5) |
0.322 |
Fungus, n (%) |
7 (4.5) |
6 (5.1) |
1 (2.5) |
0.390 |
Mixed growth, n (%) |
30 (19.1) |
19 (16.2) |
11 (27.5) |
0.304 |
MDR, n (%) |
72 (45.9) |
56 (47.9) |
16 (40.0) |
0.134 |
Enterobacteriaceae |
39 (54.2) |
30 (53.6) |
9 (56.3) |
0.387 |
Enterococcus spp. |
9 (12.5) |
5 (8.9) |
4 (25.0) |
0.289 |
Acinetobacter spp. |
3 (4.2) |
2 (3.6) |
1 (6.3) |
0.860 |
Staphylococcus aureus |
2 (2.8) |
1 (1.8) |
1 (6.3) |
0.505 |
Pseudomonas aeruginosa |
2 (2.8) |
2 (3.6) |
0 |
0.367 |
Others |
21 (29.2) |
18 (32.1) |
3 (18.8) |
0.123 |
Location of infection, n (%) |
||||
Community-acquired |
135 (61.6) |
96 (61.5) |
39 (61.9) |
0.960 |
Healthcare-acquired |
84 (38.4) |
60 (38.5) |
24 (38.1) |
0.960 |
MDR, multidrug resistance |
In the organ dysfunction analysis, the most common type of organ dysfunction in patients with sepsis due to IAI was respiratory dysfunction (36.5%), followed by renal (36.1%), coagulatory (34.2%), cardiovascular (25.6%), central nervous system (CNS) (19.6%), and liver (18.3%) dysfunctions. Among the dysfunctional organs, the mortality rate associated with each organ dysfunction was the highest in patients with CNS dysfunction (44.2%, p = 0.013), followed by coagulatory (44.0%, p < 0.001), renal (38.0%, p = 0.024), respiratory (37.5%, p = 0.03), cardiovascular (35.7%, p = 0.183), and liver (27.5%, p = 0.845) dysfunctions (Table 4).
All patients (n = 219) |
Survivors (n = 156) |
Non-survivors (n = 63) |
P-value |
|
---|---|---|---|---|
Organ dysfunction, n (%) |
||||
Respiratory |
80 (36.5) |
50 (62.5) |
30 (37.5) |
0.030 |
Coagulatory |
75 (34.2) |
42 (56.0) |
33 (44.0) |
< 0.001 |
Liver |
40 (18.3) |
29 (72.5) |
11 (27.5) |
0.845 |
Cardiovascular |
56 (25.6) |
36 (64.3) |
20 (35.7) |
0.183 |
CNS |
43 (19.6) |
24 (55.8) |
19 (44.2) |
0.013 |
Renal |
79 (36.1) |
49 (62.0) |
30 (38.0) |
0.024 |
IAI, intra-abdominal infection; CNS: central nervous system |
Multivariate logistic regression analysis was used to estimate the association between organ dysfunction and 28-day mortality. Among the organ dysfunctions, the 28-day mortality rate was more significantly affected with coagulatory (p < 0.001, OR = 2.99 [1.63–5.48]), CNS (p = 0.014, OR = 2.38 [1.19–4.75]), renal (p = 0.024, OR = 1.99 [1.09–3.61]), and respiratory (p = 0.031, OR = 1.93 [1.06–3.5]) dysfunctions. Furthermore, after adjusting for age, sex, CCI, and lactic acid level, only coagulatory dysfunction appeared to (p = 0.001, OR = 2.78 [1.47–5.23]) affect 28-day mortality significantly (Table 5 and Fig. 2).
Variable |
Crude |
Adjusted |
||
---|---|---|---|---|
OR (95% CI) |
P |
OR (95% CI) |
P-value |
|
Respiratory |
1.93 (1.06 ~ 3.5) |
0.031 |
1.71 (0.9 ~ 3.25) |
0.102 |
Coagulatory |
2.99 (1.63 ~ 5.48) |
< 0.001 |
2.78 (1.47 ~ 5.23) |
0.001 |
Liver |
0.93 (0.43 ~ 1.99) |
0.845 |
0.99 (0.44 ~ 2.25) |
0.979 |
Cardiovascular |
1.55 (0.81 ~ 2.96) |
0.185 |
1.35 (0.67 ~ 2.71) |
0.398 |
Central nervous system |
2.38 (1.19 ~ 4.75) |
0.014 |
1.79 (0.85 ~ 3.79) |
0.127 |
Renal |
1.99 (1.09 ~ 3.61) |
0.025 |
1.45 (0.76 ~ 2.76) |
0.260 |
IAI, intra-abdominal infection; OR, odds ratio; CI, confidence interval |
On studying the association between the number of organ dysfunctions and the 28-day mortality rate, mortality was found to be 24.7% (n = 20/81, p = 0.307) in patients with one organ dysfunction and 18.4% (n = 9/49, p = 0.068) in patients with two organ dysfunctions. The 28-day mortality was 55.6% in patients with three organ dysfunctions (p < 0.001, OR = 4.07 [1.94–8.54]) and 50% in patients with four or more organ dysfunctions (p = 0.033, OR = 2.76 (1.09–6.99]). In patients with three or more organ dysfunctions, 28-day mortality was more than twice that of single organ dysfunction (Table 6 and Fig. 3). In time, the mortality rate in patients with more than three organ dysfunctions distinctly increased.
Number of organ dysfunction |
n |
Mortality |
OR (95% CI) Crude |
P-value |
---|---|---|---|---|
0 |
33 |
4/33 (12.1) |
0.30 (0.10–0.88) |
0.029 |
1 |
81 |
20/81 (24.7) |
0.72 (0.39–1.35) |
0.308 |
2 |
49 |
9/49 (18.4) |
0.48 (0.22–1.07) |
0.072 |
3 |
36 |
20/36 (55.6) |
4.07 (1.94–8.54) |
< 0.001 |
≥ 4 |
20 |
10/20 (50.0) |
2.76 (1.09–6.99) |
0.033 |
OR, odds ratio; CI, confidence interval |
CCI, septic shock, initial lactate level, initial SOFA score, SAPS 3 score, CRRT, source control, and the number of dysfunctional organs were associated with 28-day mortality in the univariate analyses. In the multivariate logistic regression analysis, after adjusting for each risk and confounding factor, only the SAPS 3 score (p = 0.014) and CRRT (p < 0.001) were independently associated with higher 28-day mortality (Table 7).
Variable |
Univariable |
Multivariable |
||
---|---|---|---|---|
OR (95% CI) |
P-value |
OR (95% CI) |
P-value |
|
Age (years), mean (± SD) |
1.01 (0.98–1.03) |
0.581 |
||
BMI (kg/m2), mean (± SD) |
1.04 (0.97–1.12) |
0.239 |
||
Charlson comorbidity index, mean (± SD) |
1.13 (1.00–1.26) |
0.039 |
1.02 (0.88–1.18) |
0.770 |
Septic shock, n (%) |
1.94 (1.07–3.51) |
0.029 |
1.04 (0.49–2.23) |
0.915 |
Initial lactate level (mmol/L), mean (± SD) |
1.19 (1.9–1.3) |
< 0.001 |
1.06 (0.96–1.17) |
0.220 |
Initial SOFA score, mean (± SD) |
1.24 (1.12–1.36) |
< 0.001 |
0.94 (0.74–1.19) |
0.615 |
SAPS 3 score, mean (± SD) |
1.05 (1.03–1.08) |
< 0.001 |
1.04 (1.01–1.07) |
0.014 |
CRRT, n (%) |
109.58 (24.89–482.48) |
< 0.001 |
6.64 (3.1–14.22) |
< 0.001 |
Bacteremia, n (%) |
1.09 (0.61–1.95) |
0.780 |
||
Time zero to time of antibiotic administration (min) |
1.00 (1.00–1.01) |
0.330 |
||
Source control, n (%) |
2.38 (1.26–4.51) |
0.008 |
2.10 (0.96–4.63) |
0.065 |
Source control time (h), mean (± SD) |
1.00 (1.00–1.00) |
0.660 |
||
Number of organ dysfunction, n (%) |
1.66 (1.30–2.13) |
< 0.001 |
1.2 (0.66–2.18) |
0.548 |
MDR, n (%) |
0.61 (0.32–1.17) |
0.136 |
||
IAI, intra-abdominal infection; OR, odds ratio; CI, confidence interval; BMI, body mass index; SOFA, Sequential Organ Failure Assessment; SAPS 3, simplified acute physiology score III; CRRT, continuous renal replacement therapy; MDR, multidrug resistance |
Despite the increased incidence of sepsis and septic shock, recent studies have consistently shown a decrease in sepsis mortality over time, owing to advances in medical technology [1, 13]. However, the overall in-hospital mortality rate due to sepsis was quite high at 29.0% in some recent studies in Korea [9, 14]. Similarly, our study showed that the overall in-hospital mortality rate with sepsis was 28.1%, and the mortality rate for sepsis caused by IAI was 23.3%. Moreover, the mortality rate of all patients with sepsis treated in the ICU and the mortality rate of patients treated for sepsis due to IAI in the ICU were even higher at 35.1% and 28.8%, respectively.
There have been many studies on tools for predicting the progress and prognosis of the disease, which are still underway [15–17]. One of the most important factors affecting the mortality and clinical outcomes in sepsis is comorbidity, and the CCI can quantify a patient's comorbidity. In this time of aging populations, the CCI of patients is increasing. The CCI is widely used as a tool to predict the mortality rate of patients with sepsis due to IAI and determine their prognosis in advance [14, 18, 19]. In our study, the mean CCI in the non-survivor group was higher than that in the survivor group, with significant differences (5.9 ± 3.0 vs. 5.1 ± 2.3, p = 0.011). In addition, CCI (p = 0.039, OR = 1.13 [1.00–1.26]) was an independent risk factor for mortality prediction in the univariate logistic regression analysis.
Multicenter research and efforts are being conducted worldwide to improve the clinical outcomes of patients with sepsis. For instance, the Surviving Sepsis Campaign released new guidelines for the treatment of sepsis and a new updated “Hour-1 bundle” for sepsis treatment [20, 21]. Immediate resuscitation, initial early screening, antibiotic treatment, and source control are imperative to reduce the social burden and improve patient outcomes [14]. In addition, initial lactate levels and initial SOFA scores can be used to predict clinical progress and prognosis of sepsis. A large number of studies have already shown that, the higher the initial lactate level and initial SOFA score, the higher the mortality rate in patients with sepsis [22, 23]. In our study, initial lactate level and SOFA score were also independent risk factors in predicting the mortality rate in patients with sepsis caused by IAI (p < 0.001).
Many studies have shown that patients with septic shock have higher mortality rates than those without septic shock [9, 24, 25]. There were more patients with septic shock in the non-survivor group, and the study of predicting risk factors can interpret that patients with septic shock have a 1.94 times higher risk of mortality than those without septic shock (p = 0.029).
In the treatment of patients with sepsis due to IAI, the usage of antibiotics and source control is very important. Adequate and swift antibiotic administration and coverage from the time of recognition of sepsis are vital [26–29]. Although no significant difference was noted, the non-survivor group showed a tendency of delayed antibiotic administration in our study compared with that in the survivor group (217.5 ± 422.8 min vs. 171.4 ± 238.8 min, p = 0.495). Sepsis caused by IAI due to biliary sepsis, intestinal perforation, postoperative leakage, and intra-abdominal abscess can be controlled using open laparotomy, percutaneous transhepatic biliary drainage, and percutaneous catheter drainage insertion. Ultimately, the prognosis of patients with sepsis depends on the source controls, and the faster the source control, the lower is the mortality rate [30, 31]. Our study showed a significantly higher number of survivors in the source control group (46.8% vs. 27.0%, p = 0.007). In addition, patients who did not perform source control have a 2.38-fold higher association with mortality than patients who did (p = 0.008, OR = 2.38 [1.26 ~ 4.51]).
In several studies on IAI, E. coli and K. pneumoniae were the most common gram-negative causative pathogens. In gram-positive pathogens, most of them were E. faecalis and E. faecium [5, 8]. In our study, the same pathogens were detected and the proportion was similar, as previously mentioned. The mortality rate was higher in patients whose causative pathogens were not identified. However, there was no significant difference in our study (p = 0.087). Additionally, some studies on IAI have shown that MDR is an independent risk factor for mortality [5, 8, 32]. However, the impact of MDR on mortality was not significant in our study (p = 0.136).
Organ dysfunction is a useful prognostic indicator for mortality in patients with sepsis, and the mortality rate increases significantly as the number of organ dysfunctions increases [33–35]. In one study by Takeshi et al., patients with three (23.5%) and four or more organ dysfunctions (38.9%) had over two and four times the ICU mortality rates, respectively, compared with that of single organ dysfunction (8.9%). In addition, the hazard ratios were 1.6, 2.0, and 2.7 in 2-, 3-, and 4 or more organ dysfunctions, respectively, showing an increasing trend as the number of organ dysfunctions increases [33]. In our study, the mortality rate was more than two-fold higher in patients with three organ dysfunctions (55.6%) and four or more organ dysfunctions (50.0%) than that of patients with single organ dysfunction (24.7%). The ORs were also 4.07 (p < 0.001) and 2.76 (p = 0.028) in patients with three and four or more organ dysfunctions, respectively. Similarly, the dysfunction of three or more organs in our study could be considered as an independent risk factor for mortality.
The impact of each organ dysfunction on mortality and the proportion of organ dysfunction occurring in patients with sepsis varies between the studies. In addition, in several studies of organ dysfunction in patients with sepsis, the most frequent cause of respiratory and cardiovascular system dysfunction is organ dysfunction [13, 33]. In contrast to the above-mentioned studies, respiration (36.5%), renal (36.1%), coagulation (34.2%), cardiovascular (25.6%), CNS (19.6%), and liver (18.3%) were observed in patients with sepsis caused by IAI in our study. And in patients with sepsis, respiratory and cardiovascular dysfunctions have a higher mortality rate than other organ dysfunctions [13, 33–35]. By contrast, our study showed the mortality rate of each organ dysfunction was highest in patients with CNS dysfunction (44.2%, p = 0.013), followed by coagulation (44.0%, p < 0.001), renal dysfunction (38.0%, p = 0.024), respiration (37.5%, p = 0.03), cardiovascular dysfunction (35.7%, p = 0.183), and liver dysfunction (27.5%, p = 0.845).
Microvascular thrombosis and ischemia are the most important processes in sepsis, causing tissue damage and multiple organ dysfunctions [36, 37]. In addition, the coagulation cascade may be abrogated owing to the aberrant expression of cytokines and tissue factors in response to systemic inflammation. As the coagulation system is deranged, sepsis-induced coagulopathy occurs, and manifestations of bleeding increase [36–38]. Coagulopathy in patients with sepsis is highly associated with mortality [39, 40]. Moreover, after adjusting for age, sex, CCI, and lactic acid level, coagulatory dysfunction (p < 0.001, OR = 2.99 [1.63–5.48]) had the greatest impact on mortality among the organ dysfunctions in our study.
This study has several limitations. First, this was a retrospective study based on medical records conducted in multiple institutions. Each hospital differed in its treatment policy, level, and system, including its facilities. As this study did not only focus on sepsis caused by IAI, the data may also be inadequate. To overcome these limitations, a prospective study of patients with sepsis caused by IAIs may be needed.
In our study, CCI, septic shock, initial lactate level, initial SOFA score, SAPS 3 score, acute kidney injury with CRRT, source control, and the number of dysfunctional organs were found to be independent risk factors affecting 28-day mortality. Among the organ dysfunctions in sepsis caused by IAI, coagulopathy was found to be an independent risk factor for 28-day mortality. Therefore, more intensive care may be needed because the prognosis could be worse in patients with coagulopathy than in those with other organ dysfunctions due to IAI.
Intra-abdominal infection (IAI), intensive care units (ICUs), Korean Sepsis Alliance (KSA), Korea Disease Control and Prevention Agency (KDCA), Sequential Organ Failure Assessment (SOFA), body mass index (BMI), Charlson comorbidity index (CCI), simplified acute physiology score III (SAPS 3), multidrug resistance (MDR), odds ratios (ORs), continuous renal replacement therapy (CRRT), central nervous system (CNS)
Ethics approval and consent to participate
This study was conducted according to the guidelines of the Declaration of Helsinki. The study was approved by the Institutional Review Board of Asan Medical Center (approval number 2018-0675). And this study also approved by the Institutional Review Boards of all participating hospitals; Chonnam national university hospital (approval number CNUH2029075), Chungnam national university hospital (approval number 2019-11-048-001), Daegu Catholic University Medical Center (approval number CR-18-163-L), Hallym University Sacred heart hospital (approval number 2018-09-004), Hanyang University Guri Hospital (approval number 2020-08-015), Inje University Sanggye Paik Hospital (approval number 2018-08-014), Jeju National University Hospital (approval number 2018-06-012), Jeonbuk national university hospital (approval number CUH 2018-10-027), Kangwon national university hospital (approval number 2018-08-004-001), Korea University Anam Hospital (approval number 2 0 1 9 A N 0 0 2 7), Pusan National University Yangsan Hospital (approval number 05–2019–092), Samsung Medical Center (approval number 2018-05-108), Seoul National University Bundang Hospital (approval number B-1810-500-402), Seoul national university hospital (approval number H-1808-135-967), Ulsan university hospital (approval number UUH 2018-08-003).
Data were collected and analyzed in an ethical manner while protecting the patients' right to privacy. The requirement for informed consent was waived owing to the non-interventional, observational characteristics by the Institutional Review Boards (IRB) of all participating hospitals; Asan Medical Center Institutional Review Board (approval number 2018-0675), Chonnam national university hospital (approval number CNUH2029075), Chungnam national university hospital (approval number 2019-11-048-001), Daegu Catholic University Medical Center (approval number CR-18-163-L), Hallym University Sacred heart hospital (approval number 2018-09-004), Hanyang University Guri Hospital (approval number 2020-08-015), Inje University Sanggye Paik Hospital (approval number 2018-08-014), Jeju National University Hospital (approval number 2018-06-012), Jeonbuk national university hospital (approval number CUH 2018-10-027), Kangwon national university hospital (approval number 2018-08-004-001), Korea University Anam Hospital (approval number 2 0 1 9 A N 0 0 2 7), Pusan National University Yangsan Hospital (approval number 05–2019–092), Samsung Medical Center (approval number 2018-05-108), Seoul National University Bundang Hospital (approval number B-1810-500-402), Seoul national university hospital (approval number H-1808-135-967), Ulsan university hospital (approval number UUH 2018-08-003).
Consent for publication
Not applicable.
Availability of Data and Materials
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
Competing interests
All authors declare that they have no competing interests.
Funding
This work was supported by the Research Program funded by the Korea Disease Control and Prevention Agency (fund code 2020E280700).
Author contributions
CH analyzed and interpreted the patient data regarding sepsis patients. JW and HJ reviewed the literature and contributed to manuscript drafting. All authors read and approved the final manuscript.
Acknowledgements
Not applicable.