Literature DB >> 33553315

Association between comorbid diabetes mellitus and prognosis of patients with sepsis in the intensive care unit: a retrospective cohort study.

Shan Lin1, Shanhui Ge1, Wanmei He1, Mian Zeng1.   

Abstract

BACKGROUND: Sepsis patients hospitalized in the intensive care unit (ICU) often have comorbid diabetes mellitus (DM). However, the clinical impact of DM on the clinical outcomes of critically ill sepsis patients has yet to be determined. Therefore, the current study aimed to analyze the association of comorbid DM with the prognosis of sepsis patients in the ICU.
METHODS: Data of patients with sepsis and comorbid DM were obtained from a large-scale intensive care database. The primary outcome was 28-day mortality after ICU admission. Associations of comorbid DM with the primary outcome were assessed using a multivariable Cox regression model. Different adjusted models, such as the propensity score method, were used to determine the prognosis of the patients.
RESULTS: Overall, 12,321 sepsis patients were enrolled, including 3,509 (28.48%) with comorbid DM. After adjusting and matching, we found that comorbid DM was not an independent risk factor for 28-day mortality in critically ill sepsis patients and was even associated with lower mortality. Propensity score matching showed a dramatically lower 28-day mortality for sepsis patients with comorbid DM in comparison to patients without comorbid DM [hazard ratio (HR): 0.86, 95% confidence interval (CI): 0.77-0.97, P=0.0167]. The relationship of comorbid DM with 28-day mortality was broadly consistent for all subgroup variables. In the stratified analysis, a significant interaction was observed only for glucose concentration (P<0.0001). Patients with comorbid DM and a glucose level of 140-200 mg/dL (7.8-11.1 mmol/L) or ≥200 mg/dL (11.1 mmol/L) had a significantly lower 28-day mortality rate (HR 0.83, 95% CI: 0.71-0.98, P=0.0250 and HR: 0.49, 95% CI: 0.38-0.64, P<0.0001, respectively).
CONCLUSIONS: Critically ill patients with sepsis and comorbid DM were not found to have increased 28-day mortality compared to those without comorbid DM, and may even have a lower risk of mortality. Notably, this association remained in the setting of hyperglycemia. 2021 Annals of Translational Medicine. All rights reserved.

Entities:  

Keywords:  Comorbidity; critical care; diabetes mellitus; prognosis; seps

Year:  2021        PMID: 33553315      PMCID: PMC7859737          DOI: 10.21037/atm-20-4360

Source DB:  PubMed          Journal:  Ann Transl Med        ISSN: 2305-5839


Introduction

Diabetes mellitus (DM) is now rapidly rising as a worldwide epidemic. An estimated 451 million people globally are living with the condition, and it is expected to increase to 693 million by 2045 (1). Patients with DM are susceptible to bacterial infections and sepsis (2-4). Moreover, clinical experience has revealed that DM is correlated with fatal infections and poor clinical outcomes, due to factors including immune abnormalities, metabolic disorders, and impaired immune cell function caused by hyperglycemia (5,6). A study from the Netherlands reported that 19.5% of patients with sepsis in the intensive care unit (ICU) had DM, and these patients had higher rates of hospital and ICU mortality than without DM patients (7). Another retrospective study indicated that 22.7% of patients with sepsis had DM, although 28-day mortality was comparable between the diabetic and non-diabetic groups (8). Unsurprisingly, DM has emerged as a common comorbidity in patients with sepsis in the ICU. How comorbid DM affects the clinical endpoints of patients with sepsis in the ICU has not been well established. Additionally, studies linking the outcomes of sepsis patients with critical illness to comorbid DM have proved controversial. Because DM is commonly associated with other comorbidities, this study was aimed to investigate the implications of comorbid DM on the progress of sepsis patients. We present the following article in accordance with the STROBE reporting checklist (available at http://dx.doi.org/10.21037/atm-20-4360).

Methods

Patient data

The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). This study was carried out using the publicly accessible Medical Information Mart for Intensive Care III database, which contains anonymous data on 58,976 patients hospitalized in Beth Israel Deaconess Medical Center (9). The ethics committees of Beth Israel Deaconess Medical Center and Massachusetts Institute of Technology Affiliates granted access to the database (Record ID: 33460949). Due to the anonymity of the data, patient consent was waived. From the database, we enrolled patients who were at least 18 years old and diagnosed with sepsis based on a sequential organ failure assessment (SOFA) score of ≥2 points and suspected infection within the first day of ICU admission (10). Patients whose follow-up was <1 day and multiple ICU admissions were screened out. The glucose variable for the first of 24 hours after ICU admission was extracted to control confounding by glucose levels. In addition to the exposure factor (comorbid DM or not) and clinical outcomes, the other remaining variables were also extracted, including the Elixhauser Comorbidity Index (SID30) (11), renal replacement therapy on the first day, mechanical ventilation on the first day, infection site, SOFA, age, sex, and other comorbidities. As described previously, structured query language (SQL) was used to extract the data with Navicat (12). The code that facilitates documentation of the website and MIMIC-III is accessible to the public, and input from users is encouraged (13).

Outcomes

The primary outcome was 28-day mortality after ICU admission, and the secondary outcome was ICU mortality.

Propensity score models

In addition to conventional multivariate analysis, we constructed propensity scores for adjustment and matching. In the final model, a covariate was included as potential confounders if it changed the estimate of comorbid DM on 28-day mortality by >10% or was associated markedly with 28-day mortality. The propensity scores were derived using a logistic regression model that included the following baseline covariates: age, sex, SOFA, infection site, renal replacement therapy on the first day, mechanical ventilation on the first day, glucose, depression, drug abuse, alcohol abuse, fluid and electrolyte disorders, solid tumor, obesity, metastatic cancer, lymphoma, acquired immune deficiency syndrome (AIDS), renal failure, liver disease, chronic pulmonary disease, hypertension, peripheral vascular disease, valvular disease, cardiac arrhythmias, congestive heart failure, and other neurological diseases (14). By using a 1:1 matching protocol with the exclusion of replacement (greedy match algorithm), the propensity score matching (PSM) was carried out by a caliper width of 0.01 of the standard deviation of the logit of the propensity score.

Statistical analysis

Data were expressed as median (interquartile range, IQR) or mean ± standard deviation for continuous variables, and as numbers and percentages for categorical variables. Patient characteristics were analyzed as follows: continuous variables were analyzed using Kruskal–Wallis (or Fisher’s exact) tests and categorical variables were to be compared using chi-square tests. Cox regression models were applied to explore the relationship between comorbid DM and 28-day mortality, and logistic regression models were also applied to investigate the association between comorbid DM and ICU mortality. Four different adjusted models were employed to evaluate the clinical outcomes of sepsis patients with comorbid DM. In model I, we adjusted for covariates of age, sex, SOFA, SID30, mechanical ventilation on the first day, infection site, renal replacement therapy on the first day, and glucose. In model II, we used other comorbidities such as depression, drug abuse, alcohol abuse, fluid and electrolyte disorders, obesity, solid tumor, metastatic cancer, lymphoma, neurological disease, hypertension, peripheral vascular disease, valvular disease, cardiac arrhythmias, congestive heart failure, chronic pulmonary disease, liver disease, renal failure, and AIDS instead of SID30, and the other remaining variables were the same as in model I. In models III and IV, we used propensity score adjusted and matching models as described previously. The Kaplan-Meier (KM) method and log-rank tests were utilized to analyze survival differences across sepsis patients with and without comorbid DM. Stratified analyses and interaction tests were performed on the basis of age (<65 and ≥65 years), sex, glucose (<140, 140–200, and ≥200 mg/dL), renal replacement therapy on the first day, mechanical ventilation on the first day, infection site and SOFA (<5, 5–10, 10–15, ≥15). Both R (http://www.R-project.org, version 3.4.3) and EmpowerStats(R) (www.empowerstats.com, X&Y solutions, Inc., Boston, MA, USA) were used for data analysis. Statistical significance was P<0.05.

Results

Patient characteristics

Of the total 12,321 sepsis patients were enrolled, including 3,509 (28.48%) who had comorbid DM. In the original cohort, the average age was 67.10±16.42 years, with no difference between sepsis patients with and without comorbid DM (67.23±16.15 vs. 66.78±17.06 years, P=0.166). Males accounted for a higher proportion of the patients with DM; however, the difference between the two groups was not significant (51.78% vs. 53.06%, P=0.198). Patients with comorbid DM showed markedly elevated blood glucose concentrations relative to non-diabetic patients (165.42±53.64 vs. 132.92±36.64 mg/dL, P<0.001). The SOFA, SID30, infection site, and those who needed renal replacement therapy or mechanical ventilation on the first day after ICU admission were similar between the diabetic and non-diabetic groups. For more detailed results are shown in . After matching, no significant differences were found in the baseline characteristics for the two groups ().
Table 1

Characteristics of the original cohort

VariablesAll patients (N=12,321)Without DM (N=8,812)With DM (N=3,509)P value
Age (years)67.10±16.4267.23±16.1566.78±17.060.166
Sex0.198
   Male6,493 (52.70)4,676 (53.06)1,817 (51.78)
   Female5,828 (47.30)4,136 (46.94)1,692 (48.22)
Glucose (mg/dL)142.23±44.70132.92±36.64165.42±53.64<0.001
Infection site0.359
   Bloodstream5,440 (44.15)3,929 (44.59)1,511 (43.06)
   Pulmonary807 (6.55)568 (6.45)239 (6.81)
   Abdominal265 (2.15)189 (2.14)76 (2.17)
   Urinary tract2,596 (21.07)1,867 (21.19)729 (20.78)
   Others3,213 (26.08)2,259 (25.64)954 (27.19)
SOFA5.00 (3.00–7.00)5.00 (3.00–7.00)5.00 (3.00–7.00)0.646
Mechanical ventilation on first day6,132 (49.77)4,384 (49.75)1,748 (49.81)0.949
Renal replacement therapy on first day604 (4.90)432 (4.90)172 (4.90)0.999
Length of ICU stay (days)3.33 (1.83–7.86)3.33 (1.83–7.89)3.33 (1.83–7.82)0.305
Length of hospital stay (days)10.85 (6.36–19.04)10.91 (6.40–19.39)10.65 (6.29–18.47)0.128
Elixhauser Comorbidity Index (SID30)17.00 (8.00–26.00)17.00 (8.00–26.00)17.00 (8.00–26.00)0.632
28-day mortality, n (%)2,263 (18.37)1,656 (18.79)607 (17.30)0.053
In-hospital mortality, n (%)2,037 (16.53)1,515 (17.19)522 (14.88)0.002
ICU mortality, n (%)1,309 (10.62)981 (11.13)328 (9.35)0.004
Other comorbidities, n (%)
   Congestive heart failure4,168 (33.83)2,636 (29.91)1,532 (43.66)<0.001
   Cardiac arrhythmias4,173 (33.87)2,842 (32.25)1,331 (37.93)<0.001
   Valvular disease1,747 (14.18)1,219 (13.83)528 (15.05)0.081
   Peripheral vascular disease985 (7.99)872 (9.90)539 (15.36)<0.001
   Hypertension6,522 (52.93)4,102 (46.55)2,420 (68.97)<0.001
   Other neurological disease1,719 (13.95)1,308 (14.84)411 (11.71)<0.001
   Chronic pulmonary disease2,716 (22.04)1,910 (21.67)806 (22.97)0.118
   Liver disease1,258 (10.21)901 (10.22)357 (10.17)0.933
   Renal failure2,226 (18.07)1,160 (13.16)1,066 (30.38)<0.001
   AIDS180 (1.46)163 (1.85)17 (0.48)<0.001
   Lymphoma309 (2.51)246 (2.79)63 (1.80)0.001
   Metastatic cancer840 (6.82)677 (7.68)163 (4.65)<0.001
   Solid tumor647 (5.25)469 (5.32)178 (5.07)0.575
   Obesity708 (5.75)310 (3.52)398 (11.34)<0.001
   Fluid and electrolyte disorders5,228 (42.43)3,668 (41.63)1,560 (44.46)0.004
   Alcohol abuse923 (7.49)761 (8.64)162 (4.62)<0.001
   Drug abuse405 (3.29)345 (3.92)60 (1.71)<0.001
   Depression1,029 (8.35)723 (8.20)306 (8.72)0.350

DM, diabetes mellitus; ICU, intensive care unit; SOFA, sequential organ failure assessment; AIDS, acquired immune deficiency syndrome.

Table 2

Characteristics of the PSM cohort

VariablesAll patients (N=5,774)Without DM (N=2,887)With DM (N=2,887)P value
Age (years)66.75±16.6966.73±16.4466.78±16.950.968
Sex, n (%)0.833
   Male3,002 (51.99)1,505 (52.13)1,497 (51.85)
   Female2,772 (48.01)1,382 (47.87)1,390 (48.15)
Glucose (mg/dL)152.30±44.77151.32±46.00153.28±43.490.096
Infection site, n (%)0.579
   Bloodstream2,516 (43.57)1,273 (44.09)1,243 (43.06)
   Pulmonary374 (6.48)177 (6.13)197 (6.82)
   Abdominal128 (2.22)66 (2.29)62 (2.15)
   Urinary tract1,213 (21.01)618 (21.41)595 (20.61)
   Others1,543 (26.72)753 (26.08)790 (27.36)
   SOFA5.00 (3.00–7.00)5.00 (3.00–7.00)5.00 (3.00–7.00)0.264
Mechanical ventilation on first day, n (%)2,874 (49.77)1,446 (50.09)1,428 (49.46)0.636
Renal replacement therapy on first day, n (%)303 (5.25)154 (5.33)149 (5.16)0.768
Length of ICU stay (days)3.39 (1.85–7.94)3.39 (1.89–8.05)3.36 (1.82–7.78)0.340
Length of hospital stay (days)10.77 (6.37–19.04)10.68 (6.46–19.83)10.82 (6.30–18.60)0.367
ICU mortality, n (%)635 (11.00)367 (12.71)268 (9.28)<0.001
In-hospital mortality, n (%)975 (16.89)543 (18.81)432 (14.96)<0.001
28-day mortality, n (%)1,081 (18.72)581 (20.12)500 (17.32)0.006
Other comorbidities, n (%)
   Congestive heart failure2,368 (41.01)1,184 (41.01)1,184 (41.01)1.000
   Cardiac arrhythmias2,160 (37.41)1,084 (37.55)1,076 (37.27)0.828
   Valvular disease916 (15.86)475 (16.45)441 (15.28)0.221
   Peripheral vascular disease841 (14.57)428 (14.83)413 (14.31)0.576
   Hypertension3,737 (64.72)1,858 (64.36)1,879 (65.08)0.563
   Other neurological disease735 (12.73)383 (13.27)352 (12.19)0.221
   Chronic pulmonary disease1,309 (22.67)659 (22.83)650 (22.51)0.777
   Liver disease593 (10.27)298 (10.32)295 (10.22)0.897
   Renal failure1,472 (25.49)730 (25.29)742 (25.70)0.717
   AIDS35 (0.61)19 (0.66)16 (0.55)0.611
   Lymphoma112 (1.94)57 (1.97)55 (1.91)0.849
   Metastatic cancer305 (5.28)149 (5.16)156 (5.40)0.680
   Solid tumor298 (5.16)147 (5.09)151 (5.23)0.812
   Obesity474 (8.21)232 (8.04)242 (8.38)0.632
   Fluid and electrolyte disorders2,472 (42.81)1,231 (42.64)1,241 (42.99)0.790
   Alcohol abuse321 (5.56)166 (5.75)155 (5.37)0.528
   Drug abuse116 (2.01)60 (2.08)56 (1.94)0.708
   Depression492 (8.52)250 (8.66)242 (8.38)0.706

DM, diabetes mellitus; ICU, intensive care unit; SOFA, sequential organ failure assessment; AIDS, acquired immune deficiency syndrome.

DM, diabetes mellitus; ICU, intensive care unit; SOFA, sequential organ failure assessment; AIDS, acquired immune deficiency syndrome. DM, diabetes mellitus; ICU, intensive care unit; SOFA, sequential organ failure assessment; AIDS, acquired immune deficiency syndrome.

Clinical outcomes of participants

In the original cohort (), hospital mortality (14.88% vs. 17.19%, P=0.002) and ICU mortality (9.35% vs. 11.13%, P=0.004) were lower in diabetic patients than in non-diabetic patients. At the end of the 28 days, 2,263 (18.37%) of the participants died after ICU admission. Moreover, a lower 28-day mortality rate was observed in patients with DM than in patients without DM (17.30% vs. 18.79%); however, the P value was equal to 0.053. In the PSM cohort (), the 28-day mortality, ICU mortality, and in-hospital mortality were all considerably lower in patients with comorbid DM than in those without comorbid DM. The length of ICU stay and length of hospital stay were comparable between patients with and without comorbid DM in the original and PSM cohorts. The KM survival curve of the original cohort showed a significant survival benefit in patients with DM within 28 days after ICU admission (log-rank test: P=0.044) ().
Figure 1

Kaplan-Meier survival curves of the original cohort.

Kaplan-Meier survival curves of the original cohort.

Association of comorbid DM with clinical outcomes

Multivariable Cox regression analysis showed that comorbid DM was not a risk factor for 28-day mortality (HR: 0.91, 95% CI: 0.83–1.00, P=0.0439). After adjustments and matching, we found that comorbid DM was still not an independent risk factor and was even associated with lower mortality, with consistent and significant results in the four different models (). In model IV, the 28-day mortality rate in the comorbid DM group decreased by 14% compared to the without comorbid DM group (HR: 0.86, 95% CI: 0.77–0.97, P=0.0167). Similar results were obtained for ICU mortality (). In model IV, comorbid DM was observed to have a lower risk of ICU mortality (OR: 0.73, 95% CI: 0.62–0.87, P=0.0003).
Table 3

Associations between comorbid DM and clinical outcomes

Clinical outcomesGroupsHR (95% CI)/OR (95% CI)P value
28-day mortality
   CrudeWithout DM1
With DM0.91 (0.83–1.00)0.0439
   Model IWithout DM1
With DM0.84 (0.76–0.93)0.0006
   Model IIWithout DM1
With DM0.84 (0.76–0.93)0.0012
   Model IIIWithout DM1
With DM0.85 (0.77–0.94)0.0026
   Model IVWithout DM1
With DM0.86 (0.77–0.97)0.0167
ICU mortality
   CrudeWithout DM1
With DM0.82 (0.72–0.94)0.0037
   Model IWithout DM1
With DM0.69 (0.60–0.80)<0.0001
   Model IIWithout DM1
With DM0.70 (0.60–0.82)<0.0001
   Model IIIWithout DM1
With DM0.71 (0.61–0.82)<0.0001
   Model IVWithout DM1
With DM0.73 (0.62–0.87)0.0003

Model I was adjusted by age, sex, SOFA, SID30, infection site, mechanical ventilation on first day, renal replacement therapy on first day, glucose. Model II was adjusted by age, sex, SOFA, infection site, mechanical ventilation on first day, renal replacement therapy on first day, glucose, congestive heart failure, cardiac arrhythmias, valvular disease, peripheral vascular disease, hypertension, other neurological disease, chronic pulmonary disease, liver disease, renal failure, AIDS, lymphoma, metastatic cancer, solid tumor, obesity, fluid and electrolyte disorders, alcohol abuse, drug abuse, and depression. Model III was adjusted by propensity score calculated by age, sex, SOFA, infection site, mechanical ventilation on first day, renal replacement therapy on first day, glucose, congestive heart failure, cardiac arrhythmias, valvular disease, peripheral vascular disease, hypertension, other neurological disease, chronic pulmonary disease, liver disease, renal failure, AIDS, lymphoma, metastatic cancer, solid tumor, obesity, fluid and electrolyte disorders, alcohol abuse, drug abuse, and depression. Model IV was propensity score matching conducted using age, sex, SOFA, infection site, mechanical ventilation on first day, renal replacement therapy on first day, glucose, congestive heart failure, cardiac arrhythmias, valvular disease, peripheral vascular disease, hypertension, other neurological disease, chronic pulmonary disease, liver disease, renal failure, AIDS, lymphoma, metastatic cancer, solid tumor, obesity, fluid and electrolyte disorders, alcohol abuse, drug abuse, and depression. DM, diabetes mellitus; HR, hazard ratio; OR, odds ratio; CI, confidence interval.

Model I was adjusted by age, sex, SOFA, SID30, infection site, mechanical ventilation on first day, renal replacement therapy on first day, glucose. Model II was adjusted by age, sex, SOFA, infection site, mechanical ventilation on first day, renal replacement therapy on first day, glucose, congestive heart failure, cardiac arrhythmias, valvular disease, peripheral vascular disease, hypertension, other neurological disease, chronic pulmonary disease, liver disease, renal failure, AIDS, lymphoma, metastatic cancer, solid tumor, obesity, fluid and electrolyte disorders, alcohol abuse, drug abuse, and depression. Model III was adjusted by propensity score calculated by age, sex, SOFA, infection site, mechanical ventilation on first day, renal replacement therapy on first day, glucose, congestive heart failure, cardiac arrhythmias, valvular disease, peripheral vascular disease, hypertension, other neurological disease, chronic pulmonary disease, liver disease, renal failure, AIDS, lymphoma, metastatic cancer, solid tumor, obesity, fluid and electrolyte disorders, alcohol abuse, drug abuse, and depression. Model IV was propensity score matching conducted using age, sex, SOFA, infection site, mechanical ventilation on first day, renal replacement therapy on first day, glucose, congestive heart failure, cardiac arrhythmias, valvular disease, peripheral vascular disease, hypertension, other neurological disease, chronic pulmonary disease, liver disease, renal failure, AIDS, lymphoma, metastatic cancer, solid tumor, obesity, fluid and electrolyte disorders, alcohol abuse, drug abuse, and depression. DM, diabetes mellitus; HR, hazard ratio; OR, odds ratio; CI, confidence interval.

Interaction and stratified analysis

The association of comorbid DM with 28-day mortality was broadly consistent for all subgroup variables ( and ). The correlations between comorbid DM and 28-day mortality was similar for almost strata (Interaction P value >0.05). A significant interaction was observed only with glucose (P<0.0001). Patients with comorbid DM and a glucose of 140–200 mg/dL (7.8–11.1 mmol/L) or ≥200 mg/dL (11.1 mmol/L) had a significantly lower risk of 28-day mortality (HR: 0.83, 95% CI: 0.71–0.98, P=0.0250 and HR: 0.49, 95% CI: 0.38–0.64, P<0.0001, respectively). Additional analyses were conducted of blood glucose concentrations (per 1 mmol/L) in patients with and without comorbid DM (). After adjustments for potential confounders, no dramatic increase was observed in 28-day mortality in the comorbid DM group with increasing blood glucose levels (HR: 1.01, 95% CI: 0.98–1.03, P=0.6265), whereas there was a remarkable increase in 28-day mortality with increasing blood glucose levels in patients without DM (HR: 1.07, 95% CI 1.05–1.09, P<0.0001).
Table 4

Effect size of comorbid DM on 28-day mortality rate in prespecified and exploratory subgroups in each subgroup

Y= 28-day mortalityN (%)Without DMWith DM (HR, 95% CI)P valueInteraction P value
Age (years)0.1029
   <655,012 (40.68)1.01.01 (0.83–1.23)0.9307
   ≥657,309 (59.32)1.00.79 (0.70–0.90)0.0002
Sex0.4481
   Male6,493 (52.70)1.00.85 (0.74–0.98)0.0283
   Female5,828 (47.30)1.00.83 (0.71–0.97)0.0190
Glucose (mg/dL)<0.0001
   <1407,037 (57.11)1.00.99 (0.85–1.15)0.9269
   ≥140, <2003,965 (32.18)1.00.83 (0.71–0.98)0.0250
   ≥2001,319 (10.71)1.00.49 (0.38–0.64)<0.0001
Mechanical ventilation on first day0.0876
   No6,189 (50.23)1.00.80 (0.69–0.93)0.0031
   Yes6,132 (49.77)1.00.89 (0.76–1.03)0.1048
Renal replacement therapy on first day0.8129
   No11,717 (95.10)1.00.83 (0.75–0.93)0.0010
   Yes604 (4.90)1.00.98 (0.65–1.48)0.9169
Infection site0.8896
   Bloodstream5,440 (44.15)1.00.81 (0.69–0.94)0.0065
   Pulmonary807 (6.55)1.00.77 (0.51–1.16)0.2084
   Abdominal265 (2.15)1.00.97 (0.51–1.82)0.9216
   Urinary tract2,596 (21.07)1.00.85 (0.68–1.06)0.1538
   Others3,213 (26.08)1.00.91 (0.73–1.13)0.3725
SOFA0.0867
   <55,666 (45.99)1.00.80 (0.67–0.96)0.0148
   ≥5, <105,280 (42.85)1.00.82 (0.70–0.95)0.0110
   ≥10, <151,197 (9.72)1.01.08 (0.85–1.37)0.5287
   ≥15178 (1.44)1.00.46 (0.22–0.98)0.0451

Adjusted by age, sex, SOFA, infection site, mechanical ventilation on first day, renal replacement therapy on first day, glucose, congestive heart failure, cardiac arrhythmias, valvular disease, peripheral vascular disease, hypertension, other neurological disease, chronic pulmonary disease, liver disease, renal failure, AIDS, lymphoma, metastatic cancer, solid tumor, obesity, fluid and electrolyte disorders, alcohol abuse, drug abuse, and depression except for the subgroup variable. DM, diabetes mellitus; HR, hazard ratio; CI, confidence interval.

Figure 2

Forest plot of comorbid DM on 28-day mortality in prespecified and exploratory subgroups in each subgroup. DM, diabetes mellitus; ICU, intensive care unit; SOFA, sequential organ failure assessment; HR, hazard ratio; CI, confidence interval.

Table 5

Effect of blood glucose on 28-day mortality in patients with and without comorbid DM

Clinical outcomes (28-day mortality)GroupsHR (95% CI)P value
Crude (per 1 mmol/L)Without DM1.08 (1.05–1.10)<0.0001
With DM1.00 (0.97–1.03)0.9565
Adjusted model (per 1 mmol/L)Without DM1.07 (1.05–1.09)<0.0001
With DM1.01 (0.98–1.03)0.6265

Adjusted for age, sex, SOFA, infection site, mechanical ventilation on first day, renal replacement therapy on first day, congestive heart failure, cardiac arrhythmias, valvular disease, peripheral vascular disease, hypertension, other neurological disease, chronic pulmonary disease, liver disease, renal failure, AIDS, lymphoma, metastatic cancer, solid tumor, obesity, fluid and electrolyte disorders, alcohol abuse, drug abuse, and depression. DM, diabetes mellitus; HR, hazard ratio; CI, confidence interval.

Adjusted by age, sex, SOFA, infection site, mechanical ventilation on first day, renal replacement therapy on first day, glucose, congestive heart failure, cardiac arrhythmias, valvular disease, peripheral vascular disease, hypertension, other neurological disease, chronic pulmonary disease, liver disease, renal failure, AIDS, lymphoma, metastatic cancer, solid tumor, obesity, fluid and electrolyte disorders, alcohol abuse, drug abuse, and depression except for the subgroup variable. DM, diabetes mellitus; HR, hazard ratio; CI, confidence interval. Forest plot of comorbid DM on 28-day mortality in prespecified and exploratory subgroups in each subgroup. DM, diabetes mellitus; ICU, intensive care unit; SOFA, sequential organ failure assessment; HR, hazard ratio; CI, confidence interval. Adjusted for age, sex, SOFA, infection site, mechanical ventilation on first day, renal replacement therapy on first day, congestive heart failure, cardiac arrhythmias, valvular disease, peripheral vascular disease, hypertension, other neurological disease, chronic pulmonary disease, liver disease, renal failure, AIDS, lymphoma, metastatic cancer, solid tumor, obesity, fluid and electrolyte disorders, alcohol abuse, drug abuse, and depression. DM, diabetes mellitus; HR, hazard ratio; CI, confidence interval.

Discussion

In this study, we selected a specific study population comprising patients with sepsis and comorbid DM in the ICU from a sizable critical care database, and explored the association between sepsis patients with comorbid DM and clinical outcomes. Comorbid DM was not found to be an independent risk factor for patients with sepsis in the ICU; moreover, a decrease of approximately 14% was observed in the risk of 28-day mortality in sepsis patients with comorbid DM compared to those without comorbid DM, which remained valid in the setting of hyperglycemia. While clinical experience points toward an association between DM and poor prognosis, observational studies have yielded conflicting results. However, only a few studies have accurately reported the relationship between prognosis in patients with sepsis and comorbid DM. A study by van Vught et al. (7) identified 41,492 patients with sepsis (including 8,085 with comorbid DM) and indicated that those with comorbid DM had higher 90-day, in-hospital, and crude ICU mortality than those without DM. After adjustment, no relationship was found between DM and the risk of 90-day mortality (7). However, van Vught et al.’s study only evaluated the relationship between 90-day mortality and sepsis patients with comorbid DM, and covariates were not adjusted for in-hospital mortality or ICU mortality. In our study, lower ICU and 28-day mortality were observed for ICU sepsis patients with comorbid diabetes in four different models. Another large sample study of 217,280 patients by de Miguel-Yanes et al. found that in-hospital mortality among sepsis patients with comorbid type 2 DM was decreased by 12% compared to those without type 2 DM (OR: 0.88, 95% CI: 0.86–0.90) (15). Our results were consistent with those of Miguel-Yanes et al., suggesting that comorbid DM is a potential protective factor in patients with sepsis. van Vught et al. (7) and de Miguel-Yanes et al. (15) appear to be the only large-sample studies currently available that explore the impact of comorbid DM on the clinical endpoints of patients with sepsis in the ICU. Another study involving 830 patients with sepsis indicated no difference in 28- or 90-day mortality between diabetic and non-diabetic patients (8). With regard to organ dysfunction, there were some studies comparing the prevalence of acute lung injury in sepsis patients with and without comorbid DM, implying a protective role with a lower risk of acute lung injury from comorbid DM (16,17). The findings regarding the relationship between comorbid DM and organ dysfunction were similar between the two studies (16,17); however, we did not analyze their endpoints. It is worth noting that we report for the first time that comorbid DM had a protective effect in patients with sepsis, even with glucose ≥200 mg/dL, compared with non-diabetic patients with sepsis. van Vught et al.’s study suggested that admission hyperglycemia is correlated with a high 30-day mortality in all subjects, although that study had a small sample size and involved only 218 sepsis patients with comorbid DM (18). van Niekerk et al. believed that glucose is essential for energy production and plays a central role in maintaining the function of activated immune cells (19), which may explain the protective effect of hyperglycemia in sepsis patients with comorbid DM. All of these studies, including ours, reveal a complex picture of the interaction between DM and the prognosis of sepsis. Diabetes causes immune dysfunction as well as metabolic disorders, including hyperglycemia. Furthermore, DM treatments (e.g., insulin, metformin, sulfonylureas, and thiazolidinediones), together with the effect of DM on the immune system, may modify the host response to sepsis and clinical outcomes (20,21). More research is urgently needed to completely understand the factors influencing the overall effect of DM on the prognosis of sepsis. There were also limitations to our study. No data were available regarding the type of DM (e.g., type 1 or type 2 DM) or medications (e.g., insulin, metformin, etc.); consequently, we could not assess their effects on the patients in our study. Furthermore, the duration and severity of DM, as well as medications prescribed prior to hospitalization, were also not available from the data, so the effects of these factors could not be measured either. Nevertheless, a strength of this study is that multiple models were applied to adjust for potential confounders (22). Other limitations include the selection bias resulting from the study’s retrospective nature, single-center design, and low external validity.

Conclusions

In this study, comorbid DM was not an independent risk factor for 28-day mortality or ICU mortality in patients with sepsis, and may instead be related to a lower mortality rate. Notably, the mortality-reducing effect persisted at glucose concentrations of 140–200 mg/dL as well as ≥200 mg/dL, indicating that a personalized glycemic control strategy in critically ill sepsis patients, both diabetic and non-diabetic, as a potential protective mechanism warrants further investigation. The article’s supplementary files as
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Authors:  J M de Miguel-Yanes; M Méndez-Bailón; R Jiménez-García; V Hernández-Barrera; N Pérez-Farinós; A López-de-Andrés
Journal:  Diabetes Res Clin Pract       Date:  2015-10-17       Impact factor: 5.602

4.  Increased risk of common infections in patients with type 1 and type 2 diabetes mellitus.

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5.  Association of delayed time in the emergency department with the clinical outcomes for critically ill patients.

Authors:  Shan Lin; Shanhui Ge; Wanmei He; Mian Zeng
Journal:  QJM       Date:  2020-06-09

6.  Diabetes does not alter mortality or hemostatic and inflammatory responses in patients with severe sepsis.

Authors:  Michiel E Stegenga; Jean-Louis Vincent; George M Vail; Jin Xie; Douglas J Haney; Mark D Williams; Gordon R Bernard; Tom van der Poll
Journal:  Crit Care Med       Date:  2010-02       Impact factor: 7.598

7.  The healthcare cost and utilization project: an overview.

Authors:  Claudia Steiner; Anne Elixhauser; Jenny Schnaier
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Review 8.  The impact of diabetes on the pathogenesis of sepsis.

Authors:  G C K W Koh; S J Peacock; T van der Poll; W J Wiersinga
Journal:  Eur J Clin Microbiol Infect Dis       Date:  2011-07-30       Impact factor: 3.267

Review 9.  Diabetes and Sepsis: Risk, Recurrence, and Ruination.

Authors:  Lynn M Frydrych; Fatemeh Fattahi; Katherine He; Peter A Ward; Matthew J Delano
Journal:  Front Endocrinol (Lausanne)       Date:  2017-10-30       Impact factor: 5.555

10.  MIMIC-III, a freely accessible critical care database.

Authors:  Alistair E W Johnson; Tom J Pollard; Lu Shen; Li-Wei H Lehman; Mengling Feng; Mohammad Ghassemi; Benjamin Moody; Peter Szolovits; Leo Anthony Celi; Roger G Mark
Journal:  Sci Data       Date:  2016-05-24       Impact factor: 6.444

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Review 1.  Impact of diabetes mellitus on outcomes of patients with sepsis: an updated systematic review and meta-analysis.

Authors:  Li Jiang; Mengdi Cheng
Journal:  Diabetol Metab Syndr       Date:  2022-03-05       Impact factor: 3.320

2.  UBE2D1 and COX7C as Potential Biomarkers of Diabetes-Related Sepsis.

Authors:  Xin Wang; Lan-Tao Wang; Bin Yu
Journal:  Biomed Res Int       Date:  2022-04-11       Impact factor: 3.246

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