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Jeon, Kim, Kim, Lee, Lee, Lee, Huh, Kwack, Chang, Kang, Lee, Kim, and on behalf of the MOSAICS II Study Group of Korean Society of Critical Care Medicine: Closed intensive care units and sepsis patient outcomes: a secondary analysis of data from a multicenter prospective observational study in South Korea
Original Article
Pulmonary

Acute Crit Care 2025;40(2):209-220.

Published online: 22 May 2025

DOI: https://doi.org/10.4266/acc.004128

Closed intensive care units and sepsis patient outcomes: a secondary analysis of data from a multicenter prospective observational study in South Korea

Kyeongman Jeon1, *, Jin Hyoung Kim2, *, Kyung Chan Kim3, Heung Bum Lee4, Hongyeul Lee5, Song I Lee6, Jin-Won Huh7, Won Gun Kwack8, Youjin Chang9, Yun-Seong Kang10, Won Yeon Lee11, Je Hyeong Kim12; on behalf of the MOSAICS II Study Group of Korean Society of Critical Care Medicine

1Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea

2Division of Respiratory and Critical Care Medicine, Department of Internal Medicine, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Korea

3Department of Internal Medicine, Daegu Catholic University Hospital, Daegu, Korea

4Department of Internal Medicine, Research Center for Pulmonary Disorders, Jeonbuk National University Medical School and Hospital, Jeonju, Korea

5Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Internal Medicine, Inje University Busan Paik Hospital, Inje University College of Medicine, Busan, Korea

6Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Internal Medicine, Chungnam National University College of Medicine, Daejeon, Korea

7Department of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea

8Division of Pulmonary, Allergy and Critical Care Medicine, Department of Internal Medicine, Kyung Hee University Hospital, Kyung Hee University College of Medicine, Seoul, Korea

9Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Sanggye Paik Hospital, Inje University College of Medicine, Seoul, Korea

10Division of Pulmonology and Critical Care Medicine, Dongguk University Ilsan Hospital, Dongguk University College of Medicine, Goyang, Korea

11Division of Pulmonary, Allergy and Critical Care Medicine, Department of Internal Medicine, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju, Korea

12Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Korea University Ansan Hospital, Korea University College of Medicine, Ansan, Korea

Corresponding author: Je Hyeong Kim Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Korea University Ansan Hospital, Korea University College of Medicine, 123 Jeokgeum-ro, Danwon-gu, Ansan 15355, Korea Tel: +82-31-412-5950 Fax: +82-31-413-5950 E-mail: chepraxis@korea.ac.kr

* These authors contributed equally to this work.

Received 28 October 2024       Revised 8 February 2025       Accepted 26 February 2025

© 2025 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.

Abstract

Background

Sepsis is a leading cause of intensive care unit (ICU) admission. However, few studies have evaluated how the ICU model affects the outcomes of patients with sepsis.

Methods

This post hoc analysis of data from the Management of Severe Sepsis in Asia’s Intensive Care Units II study included 537 patients with sepsis admitted to 27 ICUs in Korea. The outcome measures of interest were compared between the closed ICU group, patients admitted under the full responsibility of an intensivist as the primary attending physician, and the open ICU group. The association between a closed ICU and ICU mortality was evaluated using a logistic regression analysis.

Results

Altogether, 363 and 174 enrolled patients were treated in open and closed ICUs, respectively. Compliance with the sepsis bundles did not differ between the two groups; however, the closed ICU group had a higher rate of renal replacement therapy and shorter duration of ventilator support. The closed ICU group also had a lower ICU mortality rate than the open ICU group (24.7% vs. 33.1%). In a logistic regression analysis, management in the closed ICU was significantly associated with a decreased ICU mortality rate even after adjusting for potential confounding factors (adjusted odds ratio, 0.576; 95% CI, 0.342–0.970), and that association was observed for up to 90 days.

Conclusions

Sepsis management in closed ICUs was significantly associated with improved ICU survival and decreased length of ICU stay, even though the compliance rates for the sepsis bundles did not differ between open and closed ICUs.

Keywords: intensive care unit, organization and administration, patient care bundles, sepsis, treatment outcome

INTRODUCTION

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection [1], and it carries a high risk of death [2]. Recent advances in early identification and hemodynamic resuscitation have improved the management of sepsis patients in emergency departments (EDs) and hospital wards [3,4]. However, the clinical outcomes of critically ill sepsis patients depend on timely application of therapeutic interventions in an appropriate setting. Therefore, sepsis patients often need to be admitted to an intensive care unit (ICU). A previous multicenter cohort study on sepsis in Korea demonstrated that one-third of all sepsis patients who visit an ED require ICU admission [4].
Although the positive effects that prompt admission to the ICU have on the outcome of critically ill patients with sepsis has previously been described [5,6], few studies have explored how the ICU organizational model (open/closed) affects mortality among patients with sepsis. A prospective cohort study involving Asian ICUs reported no difference in hospital mortality between patients treated in open and closed ICU models [7]. Nationwide observational studies on sepsis in Japan showed contradictory findings about an association between the closed ICU model and the clinical outcomes of sepsis patients admitted to the ICU [8,9]. However, it is difficult to generalize conclusions from one country to other countries, even when all the countries under consideration are in Asia [7].
In Korea, a special payment system was implemented in August 2015 for hospitals that employ trained ICU intensivists. Recently, a population-based retrospective cohort study using national health insurance claims data reported how intensivist coverage affects the survival of critically ill patients [10]. However, no information is available to indicate whether closed ICUs perform better than open ICUs in terms of the clinical outcomes of sepsis patients admitted to ICUs in Korea. Therefore, using national data from a multinational, prospective point prevalence study that assessed the epidemiology, management, and outcomes of patients with sepsis in Asian ICUs [11], we evaluated the association between management in closed ICUs and the survival of patients with sepsis.

MATERIALS AND METHODS

Study Design and Setting

This post hoc analysis used data from the Management of Severe Sepsis in Asia’s Intensive Care Units II (MOSAICS II) study [11], which collected data on the management of patients with sepsis who were admitted to ICUs in Asia. In Korea, 27 adult ICUs (19 medical ICUs and 8 mixed-patient ICUs) from 27 hospitals participated in the MOSAICS II study. In this study, we evaluated the association between the ICU model and the outcomes of patients with sepsis by using the Korean database from the MOSAICS II study.
A closed ICU was defined as an ICU in which patient care is directed by an intensivist and the ICU team. Only ICU team doctors can write orders in a closed ICU. In an open ICU, on the other hand, patient care is managed by a variety of attending physicians, and intensivists are available for consultation. An intensivist is a physician who has passed the intensive care certification examinations, completed training in an accredited intensive care fellowship, or is recognized by their institution as an intensivist because they treat each patient as totality, not just a single organ system.
The Institutional Review Boards of each participating hospital reviewed and approved this study (No. 2018AS0248, Korea University Ansan Hospital), and the requirement for obtaining informed consent was waived because it was non-interventional and observational. Additionally, patient information was anonymized and de-identified prior to analysis. This study is reported following the Strengthening the Reporting of Observational Studies in Epidemiology guidelines for observational cohort studies [12].

Participants

All patients admitted to the participating ICUs on 4 days that represented the four different seasons of 2019 (January 9, April 3, July 3, and October 9) were screened for eligibility. We included all adult patients (≥18 years) who were diagnosed with sepsis, admitted to a participating ICU in Korea for sepsis, and still in the ICU from 00:00 to 23:59 on one of the study days (Figure 1). We defined sepsis as an infection with a Sequential Organ Failure Assessment (SOFA) score of ≥2 from baseline [1]. The baseline SOFA score was assumed to be zero in patients not known to have preexisting organ dysfunction [11]. Patients were divided into the following two groups: closed ICU (treated in closed ICUs) and open ICU (treated in open ICUs).

Data Collection

The MOSAICS II study used password-protected online case report forms. The details of data collection are described in the original study [11]. For this study, data compiled by the Korean investigators were obtained from the MOSACIS II database.
A questionnaire on the participating centers’ characteristics (e.g., hospital and ICU type, open or closed ICU model, university affiliation status, presence of accredited training program, and nurse-to-patient ratio) and microbiology-processing capabilities was completed by ICU representatives. Baseline characteristics (demographics, comorbidities, and details of admission) and parameters upon ICU admission (vital signs, laboratory findings, severity of illness using the Acute Physiology and Chronic Health Evaluation (APACHE) II score, site of infection, and microbiology performed to determine the true pathogen) were assessed.
The timing of the sepsis bundles and surgical source control were measured referencing Time 0, which was determined as follows: (1) time of triage in the ED for those presenting with sepsis to the ED, (2) time of clinical documentation of patient deterioration in general wards or other non-ED areas for those who developed sepsis after hospital admission, and (3) time of ICU admission when the first two time points for a patient could not be determined from the clinical documentation. The following sepsis bundle elements were evaluated based on the Surviving Sepsis Campaign’s 2018 update: antibiotic administration, blood cultures, lactate level measurement, fluid administration, and vasopressor initiation [13]. However, timings more than 24 hours from Time 0 were excluded. Finally, data about life-sustaining treatments provided during the ICU stay were also collected.
All patients were followed until hospital discharge, death in the ICU or hospital, or up to 90 days after enrollment, whichever was earliest. However, the main outcome measure was ICU mortality. The secondary outcome measures for this study were compliance with the sepsis bundle elements and length of ICU stay.

Statistical Analyses

Given that most of the data did not follow a normal distribution, all results and tables are presented as median and interquartile range (IQR) or number (percentage). Baseline patient characteristics and outcome measures of interest were compared between the closed and open ICU groups using the Mann-Whitney U-test for continuous variables and the chi-square or Fisher’s exact test for categorical variables. The association between the closed ICU model and ICU mortality was tested using multiple logistic regression analyses. The following three models were constructed: the first was adjusted for age and sex, the second model included severity of organ dysfunction at ICU admission, and the third model was additionally adjusted for all variables with a P-value <0.25 in the univariate analyses [14] and a priori variables that were clinically relevant [15]. To reduce the risk of multicollinearity, only one variable from closely correlated variables was a candidate for inclusion in the final model. The results are presented as odds ratios (ORs) with 95% CIs. A risk-adjusted 90-day survival curve was plotted from the proportional hazards model using the mean of covariates method [16]. A two-tailed P-value <0.05 was considered to be statistically significant for all analyses. Data were analyzed using IBM SPSS version 27.0 (IBM Corp.).

RESULTS

Overall, 537 critically ill sepsis patients were admitted to participating ICUs from an ED (n=348, 64.8%), general wards (n=153, 28.5%), and other routes (n=36, 6.7%). Among them, 300 patients (55.9%) met the clinical criteria for septic shock. The baseline characteristics at ICU admission are summarized in Table 1. The median age was 73 years (IQR, 62–81 years), and 63.5% of the patients were male. Diabetes (33.1%), cardiovascular diseases (26.1%), and chronic neurologic diseases (25.7%) were the most frequent comorbidities. The respiratory system (64.4%) was the most common site of infection, followed by the urinary system (17.5%) and gastrointestinal system (13.6%). The median SOFA score was 8 (IQR, 6–10), and the median APACHE II score was 21 (16–27). Among the participating ICUs, 9 (33.3%) operated on the closed model, and 18 (66.7%) operated on the open model.
Altogether, 363 and 174 patients were treated in the open and closed ICUs, respectively. The baseline characteristics of the two groups are compared in Table 1. The closed ICU group was younger and had lower proportions of chronic lung (12.6% vs. 22.9%, P=0.005) and chronic neurological (19.0% vs. 28.9%, P=0.015) diseases, but it had a higher proportion of hematologic malignancies (11.5% vs. 4.7%, P=0.006). The sites of infection were similar between the groups. Regarding disease severity, the median SOFA score was higher in the closed ICU group than the open ICU group (9 vs. 7, P<0.001), but the median APACHE II scores were comparable between the groups. A nurse-to-patient ratio of 1:2 was noted for 72.4% of the patients admitted to the closed ICUs, which was a higher proportion than in the open ICU group at 34.2% (P<0.001).
The completion rates for the 1-hour and 3-hour sepsis bundles were compared between the two groups, and no significant differences were found (Table 2). Comparisons of life-sustaining treatments during the ICU stay and clinical outcomes are presented in Table 3. Treatments during the ICU stay did not differ significantly between the groups, except for renal replacement therapy, which was provided at a higher rate in the closed ICU group (P=0.001). ICU mortality was lower in the closed ICU group than in the open ICU group (24.7% vs. 33.1%, P=0.049), but hospital mortality did not differ significantly between the groups (37.5% vs. 44.0%, P=0.167), with 13 patients (8 in the closed ICU group and 5 in the open ICU group) who were alive upon discharge from the relevant ICU stay but still hospitalized after 90 days excluded from the analysis. Additionally, the median length of the ICU stay was shorter in the closed ICU group (13 days) than the open ICU group (18 days) (P=0.006).
Univariate comparisons of the baseline characteristics and treatments between the survivors and non-survivors of the ICU stays are presented in Table 4. No significant differences in age, sex, site of infection, admission source, or nurse-to-patient ratio were found between the groups. However, ICU mortality was associated with illness severity, organ failure, and life-sustaining treatments during the ICU stay. The median APACHE II scores of the non-survivors were significantly higher than those of the survivors (P<0.001). Organ support using mechanical ventilation and renal replacement therapy was also greater in the non-survivors than the survivors (P<0.001 and P<0.001, respectively). The compliance rate for the 3-hour sepsis bundle was higher in the survivors than in the non-survivors (50.0% vs. 36.8%, P=0.005). The proportion of patients treated in a closed ICU was higher in the survivor group (35.0% vs. 26.4%, P=0.049).
The results of the multivariate analyses with multiple logistic regression models are shown in Table 5. The closed ICU model was associated with crude ICU mortality (OR, 0.665; 95% CI, 0.442–1.000; P=0.050). After adjusting for the a priori variables of age and sex (model 1), and severity of organ dysfunction at ICU admission (model 2), the association remained significant. The final logistic regression model (model 3) considered the a priori parameters of age, sex, severity of organ dysfunction at ICU admission; a priori variables that were clinically relevant; and other variables with P<0.25 in the univariate analysis (Table 4). In model 3, the closed ICU model was still significantly associated with a decreased ICU mortality rate (adjusted OR, 0.576; 95% CI, 0.342–0.970; P=0.038). The association between the closed ICU model and mortality was observed for up to 90 days (Figure 2). The other factors that were independently associated with ICU mortality were solid malignant tumor comorbidity (adjusted OR, 1.726; 95% CI, 1.024–2.910; P=0.041), the need for mechanical ventilation (adjusted OR, 3.460; 95% CI, 1.770–6.736; P<0.001) or renal replacement therapy (adjusted OR, 1.955; 95% CI, 1.210–3.157; P=0.006), and a do-not-resuscitate order (adjusted OR, 5.052; 95% CI, 3.182–8.024; P<0.001).

DISCUSSION

Using national data from a multinational, prospective point prevalence study assessing the epidemiology, management, and outcomes of sepsis patients admitted to ICUs in Asia, we evaluated the association between management in a closed ICU and the survival of patients with sepsis. The results of our observational study indicate that patient management in a closed ICU was significantly associated with improved ICU survival and decreased length of ICU stay, even though the rates of compliance with the 1-hour and 3-hour sepsis bundles did not differ between the open and closed ICU groups.
A trained intensivist can provide high-quality intensive care, possibly leading to improved outcomes [17]. Observational studies have shown that when physician staffing in ICUs includes an intensivist who is directly involved in patient care, the outcomes of critically ill patients are better than when an intensivist is involved only as a consultant [18-20]. Nonetheless, a recent cross-sectional study of ICU organizational practices in the United States found that approximately one-third of ICUs did not have an intensivist available regularly [21], despite recommendations from the American College of Critical Care Medicine [17]. This incomplete adoption of ICU staffing protocols linked to superior outcomes for patients might be caused by institutional barriers [22]. Additionally, the reported effects of ICU staffing on patient outcomes remain contradictory [23].
In a 2013 multinational survey of Asian ICUs [24], approximately 20% of the surveyed ICUs had no board-certified intensivist, although variations in physician staffing were considerable among the Asian ICUs. Additionally, two recent population-based cohort studies conducted in Korea [10] and Japan [25], where the National Health Insurance Service has a differential management payment system according to ICU staffing, reported that ICUs with intensivist coverage were associated with improved hospital mortality. Although those results suggest the benefits of high-intensity staffing for the outcomes of general ICU patients in Asia, a previous cohort study involving Asian ICUs did not confirm an association between intensivist physician staffing and coverage and a reduction in the in-hospital mortality rate in patients with sepsis [7].
The ICU models (open or closed) evaluated here use different organizational assumptions to inform ICU staffing (high- or low-intensity staffing) [18]. In a closed ICU, admitted patients are under the full responsibility of intensivists as the primary attending physicians. In contrast, in an open ICU, patient care is managed by another attending physician, and intensivists are available for consultation. A third model, the mandatory critical care consultation ICU model, is a high-intensity staffing model that is not altogether closed [18]. Previous studies on the effects of ICU staffing on patient outcome could not evaluate the effects of the different ICU models [26], but a recent meta-analysis found that the mortality rate was higher in the open ICU group than the closed ICU group [27].
Although 216 out of 335 (65%) of Asian ICUs surveyed in 2013 operated according to the closed model [24], Japan (54%) and Korea (56%) had a lower proportion of closed ICUs than China (87%) and Saudi Arabia (89%). Only a few previous studies evaluated how the closed ICU model affected the clinical outcomes of sepsis patients. A prospective cohort study investigating the outcomes of patients with sepsis in Asian ICUs reported that hospital mortality did not differ between the open and closed ICU groups [7]. Additionally, the rate of compliance with the entire resuscitation bundle did not differ between the ICU models. Recently, a nationwide observational study on sepsis conducted in Japan found significantly lower hospital mortality in the closed ICU group than the open ICU group [8]. However, that study compared the outcomes of patients with sepsis in the two ICU models based on a definition of sepsis that was subjectively reported by each institution. Additionally, it did not evaluate the details of differences in the quality of care for the initial management of sepsis. A subsequent analysis using the database from another multicenter study of sepsis in Japan showed that hospital mortality was similar between the closed and open ICU groups, even after adjusting for rates of sepsis bundle compliance, which were higher in the closed ICU group, and the different organizational structures [9]. In our study, the closed ICU model was found to be independently associated with decreased ICU mortality in a multivariate analysis that adjusted for potential confounding factors. Furthermore, a nurse-to-patient ratio of 1:2 was achieved more frequently in the closed ICUs than the open ICUs. Additionally, the closed ICU group had a higher rate of renal replacement therapy and shorter duration of ventilator support. These differences might be partly responsible for the significant association observed between management in a closed ICU and the survival of patients with sepsis, even though the rate of compliance with the 1-hour and 3-hour sepsis bundles, which were mostly performed before ICU admission, did not differ between the two ICU models.
The strengths of our study include the fact that it is the first analysis of the association between ICU models and the clinical outcomes of patients with sepsis in Korea, where daytime intensivist physician staffing has been expanded [10]. Moreover, we used prospective data and clear definitions of ICU models and staffing. Finally, missing data were minimal. These strengths increase the study’s representativeness.
To fully appreciate our results, however, potential limitations must be acknowledged. First, because this study was observational, selection bias might have influenced the significance of its findings. In addition, baseline characteristics and treatments received differed between the two groups. However, those differences were addressed by performing an adjusted multivariate analysis. Nonetheless, the potential for bias due to an unmeasured confounding factor remains. Second, we performed a sub-analysis of a multinational, prospective, four-day point prevalence study. A prevalence study shows only a snapshot of an overall situation in a limited number of patients. We are unable to confirm that the patients present in each ICU on each study day were representative of the population of patients with sepsis generally admitted to those ICUs. Nevertheless, this study addressed the limitations of previous observational studies [8,9] by, for example, using predefined ICU model definitions. Therefore, the apparent differences in mortality identified from our data after adjusting for multiple potentially confounding factors could be used in a future study to further explore the independent influences of the ICU model on the outcomes of sepsis.
In conclusion, this nationwide post hoc analysis of patients with sepsis in Korea has demonstrated that patient management in a closed ICU was significantly associated with improved ICU survival outcomes and decreased length of ICU stay. The superiority of a closed ICU model might be related to the high quality of care provided during the ICU stay.

KEY MESSAGES

▪ Few studies have tested how intensive care unit (ICU) models affect the outcomes of patients with sepsis.
▪ Compliance with the sepsis bundles did not differ between the closed and open ICUs.
▪ The closed ICU group had a lower ICU mortality rate than the open ICU group.

Notes

CONFLICT OF INTEREST

Kyeongman Jeon is an editorial board member of the journal but was not involved in the peer reviewer selection, evaluation, or decision process of this article. No other potential conflicts of interest relevant to this article were reported.

FUNDING

This work was supported by a Samsung Medical Center grant (OTA2202901).

ACKNOWLEDGMENTS

The authors thank the MOSAICS II Korean Study Group of the Korean Society of Critical Care Medicine: Kyung Chan Kim (Department of Internal Medicine, Daegu Catholic University Hospital, Daegu); Hyo Jin Han, Seung Yong Park, and Heung Bum Lee (Department of Internal Medicine, Research Center for Pulmonary Disorders, Jeonbuk National University Medical School and Hospital, Jeonju); Jin Hyoung Kim and Jong Joon Ahn (Division of Respiratory and Critical Care Medicine, Department of Internal Medicine, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan); Beong Ki Kim and Je Hyeong Kim (Division of Pulmonology and Critical Care Medicine, Department of Internal Medicine, Korea University Ansan Hospital, Korea University College of Medicine, Ansan); Kyeongman Jeon (Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul); Hongyeul Lee (Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Internal Medicine, Inje University Busan Paik Hospital, Inje University College of Medicine, Busan); Song I Lee and Jae Young Moon (Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Internal Medicine, Chungnam National University College of Medicine, Daejeon); Jin-Won Huh (Department of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul); Won Gun Kwack (Division of Pulmonary, Allergy and Critical Care Medicine, Department of Internal Medicine, Kyung Hee University, Seoul); Youjin Chang (Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Inje University College of Medicine Sanggye Paik Hospital, Seoul); Yun-Seong Kang (Division of Pulmonology and Critical Care Medicine, Dongguk University Ilsan Hospital, Dongguk University College of Medicine, Goyang); Won Yeon Lee (Division of Pulmonary, Allergy and Critical Care Medicine, Department of Internal Medicine, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju); Yoon Mi Shin (Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Chungbuk National University Hospital, Chungbuk National University College of Medicine, Cheongju); Jongmin Lee (Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul); Young Jae Cho (Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Bundang); In Byung Kim (Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Myongji Hospital, Goyang); Young Seok Lee (Division of Pulmonology, Allergy and Critical Care Medicine, Department of Internal Medicine, Korea University Guro Hospital, Korea University College of Medicine, Seoul); Tai Sun Park (Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri); Yong Jun Choi and Jae Hwa Cho (Division of Pulmonology and Critical Care Medicine, Department of Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul); Ho Cheol Kim (Division of Pulmonology and Critical Care Medicine, Department of Medicine, Gyeongsang National University Changwon Hospital, Gyeongsang National University College of Medicine, Changwon); Sunghoon Park (Department of Pulmonary, Allergy and Critical Care Medicine, Hallym University Sacred Heart Hospital, Anyang); Jinwoo Lee and Sang-Min Lee (Division of Pulmonology and Critical Care Medicine, Department of Internal Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul); Sojung Park (Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Mokdong Hospital, College of Medicine, Ewha Womans University, Seoul); Yun Su Sim (Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Internal Medicine, Hallym University Kangnam Sacred Heart Hospital, Seoul); Shin Young Kim (St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Suwon); Do Wan Kim (Department of Thoracic and Cardiovascular Surgery, Chonnam National University Hospital, Chonnam National University College of Medicine, Gwangju); Tae Yun Park (Division of Pulmonology and Critical Care Medicine, Department of Internal Medicine, Seoul National University Boramae Hospital, Seoul National University College of Medicine, Seoul); Su Hwan Lee (Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul), Korea.

AUTHOR CONTRIBUTIONS

Conceptualization: JK, JHK (Jin Hyoung Kim), JHK (Je Hyeong Kim). Data curation: JK, JHK (Jin Hyoung Kim), JHK (Je Hyeong Kim). Formal analysis: JK, JHK (Jin Hyoung Kim), JHK (Je Hyeong Kim). Funding acquisition: JK. Investigation: KJ, JHK, KCK, HBL, HL, SIL, JWH, WGK, YC, YSK, WYL, JHK. Methodology: JK, JHK (Jin Hyoung Kim), JHK (Je Hyeong Kim). Project administration: JHK (Je Hyeong Kim). Software: KJ, JHK, KCK, HBL, HL, SIL, JWH, WGK, YC, YSK, WYL, JHK. Supervision: JHK (Je Hyeong Kim). Validation: JHK (Je Hyeong Kim). Visualization: JK. Writing - original draft: JK . Writing - review & editing: JK, JHK (Jin Hyoung Kim), JHK (Je Hyeong Kim). All authors read and agreed to the pub­lished version of the manuscript.

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Figure 1.
Scheme of group distribution. ICU: intensive care unit; MOSAICS II: Management of Severe Sepsis in Asia’s Intensive Care Units II [11].
acc-004128f1.tif
Figure 2.
Adjusted 90-day survival curves plotted from the proportional hazards model comparing intensive care unit (ICU) models in patients with sepsis admitted to ICUs.
acc-004128f2.tif
Table 1.
Baseline characteristics of patients with sepsis admitted to intensive care units
Characteristic All (n=537) Open ICU (n=363) Closed ICU (n=174) P-value
Age (yr) 73 (62–81) 75 (64–81) 70 (59–79) 0.003
Male sex 341 (63.5) 233 (64.2) 108 (62.1) 0.633
Comorbiditya)
 Diabetes mellitus 178 (33.1) 120 (33.1) 58 (33.3) >0.999
 Cardiovascular disease 140 (26.1) 104 (28.7) 36 (20.7) 0.058
 Chronic lung disease 105 (19.6) 83 (22.9) 22 (12.6) 0.005
 Chronic kidney disease 83 (15.5) 51 (14.0) 32 (18.4) 0.203
 Chronic liver disease 37 (6.9) 26 (7.2) 11 (6.3) 0.856
 Chronic neurological disease 138 (25.7) 105 (28.9) 33 (19.0) 0.015
 Solid malignant tumor 108 (20.1) 70 (19.3) 38 (21.8) 0.492
 Hematological malignancy 37 (6.9) 17 (4.7) 20 (11.5) 0.006
 Immunosuppression 20 (3.7) 13 (3.6) 7 (4.0) 0.810
 Connective tissue disease 13 (2.4) 10 (2.8) 3 (1.7) 0.562
 Peptic ulcer disease 9 (1.7) 6 (1.7) 3 (1.7) >0.999
Site of infectiona)
 Respiratory 346 (64.4) 239 (65.8) 10 (61.5) 0.337
 Urinary tract 94 (17.5) 61 (16.8) 33 (19.0) 0.546
 Abdominal 73 (13.6) 44 (12.1) 29 (16.7) 0.178
 Neurological 9 (1.7) 5 (1.4) 4 (2.3) 0.480
 Bones or joints 8 (1.5) 6 (1.7) 2 (1.1) >0.999
 Skin or cutaneous sites 23 (4.3) 15 (4.1) 8 (4.6) 0.822
 Intravascular catheter 17 (3.2) 10 (2.8) 7 (4.0) 0.438
Severity
 APACHE II score 21 (16–27) 20 (15–27) 21 (17–29) 0.129
 SOFA score 8 (6–10) 7 (5–10) 9 (7–11) <0.001
Admission source 0.024
 Emergency department 348 (64.8) 244 (67.2) 104 (59.8)
 General wards 153 (28.5) 101 (27.8) 52 (29.9)
 Otherb) 36 (6.7) 18 (5.0) 18 (10.3)
Nurse-to-patient ratio <0.001
 1 Nurse: 2 patients 250 (46.6) 124 (34.2) 126 (72.4)
 1 Nurse: 3 or more patients 287 (53.4) 239 (65.8) 48 (27.6)

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

ICU: intensive care unknit; APACHE: Acute Physiology and Chronic Health Evaluation; SOFA: Sequential Organ Failure Assessment.

a) Cases are duplicated;

b) Other category includes admissions from other ICUs (n=21), operating rooms (n=8), and interhospital transfer (n=6). The remaining data are not defined (n=2).

Table 2.
Completion of the sepsis bundle elements
Variable All (n=537) Open ICU (n=363) Closed ICU (n=174) P-value
Completion of elements within 1 hour
 Lactate measurement 334 (62.2) 224 (61.7) 110 (63.2) 0.735
 Blood cultures 234 (43.6) 164 (45.2) 70 (40.2) 0.279
 Antibiotics 163 (30.4) 110 (30.3) 53 (30.5) 0.971
 Full bundle 98 (18.2) 73 (20.1) 25 (14.4) 0.107
Completion of elements within 3 hours
 Lactate measurement 397 (73.9) 263 (72.5) 134 (77.0) 0.260
 Blood cultures 355 (66.1) 239 (65.8) 116 (66.7) 0.850
 Antibiotics 351 (65.4) 237 (65.3) 114 (65.5) 0.959
 Full bundle 247 (46.0) 170 (46.8) 77 (44.3) 0.575

Values are presented as number (%).

ICU: intensive care unit.

Table 3.
Treatments received by the study participants during their intensive care unit stay and their clinical outcomes
Treatments and outcome All (n=537) Open ICU (n=363) Closed ICU (n=174) P-value
Life-sustaining treatments during ICU staya)
 Vasopressors/inotropes 300 (55.9) 196 (54.0) 104 (59.8) 0.228
 Renal replacement therapy 181 (33.7) 105 (28.9) 76 (43.7) 0.001
 Nonsurgical source control 93 (17.3) 60 (16.5) 33 (19.0) 0.542
 Surgical source control 34 (6.3) 27 (7.4) 7 (4.0) 0.184
 Respiratory supporta)
  Mechanical ventilation 408 (76.0) 281 (77.4) 127 (73.0) 0.281
   Duration of MV (day)b) 12 (7–22) 14 (8–25) 11 (5–18) 0.002
    Among survivors in ICU 12 (7–23) 14 (8–26) 11 (5–17) 0.005
    Among non-survivors in ICU 12 (8–21) 13 (8–24) 12 (6–19) 0.149
  Nonsurgical ventilation 12 (2.2) 10 (2.8) 2 (1.1) 0.354
  High-flow nasal oxygen 148 (27.6) 100 (27.5) 48 (27.6) >0.999
Clinical outcome
 In-ICU mortality 163 (30.4) 120 (33.1) 43 (24.7) 0.049
 In-hospital mortalityc) 208 (41.9) 148 (44.0) 60 (37.5) 0.167
 90-Day mortality 208 (41.9) 148 (40.8) 60 (34.5) 0.162
 LOS in ICU (day) 16 (7–30) 18 (7–33) 13 (6–24) 0.006
  Among survivors 15 (6–28) 17 (7–34) 12 (6–23) 0.017
  Among non-survivors 18 (10–32) 19 (10–33) 17 (8–28) 0.304
 LOS in hospital (day) 28 (17–52) 29 (18–53) 26 (14–52) 0.534
 Do-not-resuscitate order 131 (24.4) 96 (26.4) 35 (20.1) 0.110

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

ICU: intensive care unit; MV: mechanical ventilation; LOS: length of stay.

a) Cases are duplicated;

b) Data were obtained from 408 patients receiving MV support;

c) 13 Patients (8 in closed ICU group vs. 5 in open ICU group) who were alive upon discharge from the relevant ICU stay but still hospitalized after 90 days were excluded from this analysis.

Table 4.
Univariate comparisons of baseline characteristics and treatments between the survivors and non-survivors at the time of discharge from the intensive care units
Characteristics ICU survivor (n=374) ICU non-survivor (n=163) P-value
Age (yr) 74 (63–81) 72 (62–80) 0.328
Male sex 232 (62.0) 109 (66.9) 0.284
Comorbiditya)
 Diabetes mellitus 125 (33.4) 53 (32.5) 0.837
 Cardiovascular disease 92 (24.6) 48 (29.4) 0.239
 Chronic lung disease 70 (18.7) 35 (21.5) 0.459
 Chronic kidney disease 58 (15.5) 25 (15.3) 0.960
 Chronic liver disease 24 (6.4) 13 (8.0) 0.512
 Chronic neurological disease 103 (27.5) 35 (21.5) 0.139
 Solid malignant tumor 66 (17.6) 42 (25.8) 0.031
 Hematological malignancy 19 (5.1) 18 (11.0) 0.012
 Immunosuppression 11 (2.9) 9 (5.5) 0.147
Site of infectiona)
 Respiratory 233 (62.3) 113 (69.3) 0.118
 Urinary tract 72 (19.3) 22 (13.5) 0.107
 Abdominal 57 (15.2) 16 (9.8) 0.092
Severity
 APACHE II score 20 (15–17) 23 (16–30) 0.018
 SOFA score 8 (6–10) 8 (6–11) 0.145
Admission source 0.074
 Emergency department 256 (68.4) 92 (56.4)
 General wards 91 (24.3) 62 (38.0)
 Otherb) 27 (7.2) 9 (5.5)
Nurse-to-patient ratio 0.983
 1 Nurse: 2 patients 174 (46.5) 76 (46.6)
 1 Nurse: 3 or more patients 200 (53.5) 87 (53.4)
Completion of elements within 1 hour
 Lactate measurement 239 (63.9) 95 (58.3) 0.217
 Blood cultures 170 (45.5) 64 (39.3) 0.183
 Antibiotics 130 (34.8) 33 (20.2) 0.001
 Full bundle 75 (20.1) 23 (14.1) 0.101
Completion of elements within 3 hour
 Lactate measurement 263 (72.5) 134 (77.0) 0.260
 Blood cultures 263 (70.3) 92 (56.4) 0.002
 Antibiotics 263 (70.3) 88 (54.0) <0.001
 Full bundle 187 (50.0) 60 (36.8) 0.005
Closed ICU 131 (35.0) 43 (26.4) 0.049
Life-sustaining treatments during ICU stay
 Vasopressors/inotropes 299 (79.9) 146 (89.6) 0.006
 Renal replacement therapy 107 (28.6) 74 (45.4) <0.001
 Mechanical ventilation 259 (69.3) 149 (91.4) <0.001
Do-not-resuscitate order 51 (13.6) 80 (49.1) <0.001

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

ICU: intensive care unknit; APACHE: Acute Physiology and Chronic Health Evaluation; SOFA: Sequential Organ Failure Assessment.

a) Cases are duplicated;

b) Other category includes admissions from other ICUs (n=21), operating rooms (n=8), or inter-hospital transfers (n=6). The remaining data are not defined (n=2).

Table 5.
Associations between the closed model and intensive care unit mortality after adjusting for potential confounding factors
Closed ICU Variables in the equation
Coefficient SE P-value OR 95% CI
Crude state −0.408 0.208 0.050 0.665 0.442–1.000
Adjusted statea)
 Model 1 −0.422 0.210 0.045 0.656 0.434–0.990
 Model 2 −0.520 0.216 0.016 0.594 0.389–0.908
 Model 3 −0.552 0.266 0.038 0.576 0.342–0.970

ICU: intensive care unit; SE: standard error; OR: odds ratio.

a) Model 1 was adjusted for age and sex. Model 2 was additionally adjusted for the severity of organ dysfunction at ICU admission. Model 3 additionally included cardiovascular disease, chronic neurological disease, solid malignant tumor, hematological malignancy, and immunosuppression as comorbidities; sites of infection; admission source; nurse-to-patient ratio; compliance with the 1-hour and 3-hour sepsis bundles; the need for vasopressors/inotropes, renal replacement therapy, or mechanical ventilation; and a do-not-resuscitate order.

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