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Pronounced effects of the sepsis–obesity paradox in elderly and male individuals without septic shock and the role of immune–inflammatory status: an analysis of MIMIC-IV data

BMC Infectious Diseases volume 25, Article number: 545 (2025) Cite this article

Abstract

Background

Obesity has been shown to reduce short-term mortality in sepsis patients, but the main subgroups and its role in immune-related inflammatory status require further research. The aim of this study was to identify the primary beneficiaries of the sepsis–obesity paradox and to investigate the involvement of immune–inflammatory status.

Methods

In this study, we analyzed data from 6602 sepsis patients from the MIMIC-IV database. Body mass index (BMI) was divided into quartiles, and mortality rates were assessed for each interval. Logistic trend tests and subgroup and restricted cubic spline (RCS) analyses were performed. Blood biochemical indicators were compared across different BMI ranges and between survivors and non-survivors. The receiver operating characteristic (ROC) curve for 28-day mortality was also evaluated.

Results

The 28-day mortality of sepsis patients followed a U-shaped pattern with increasing BMI. Trend analysis confirmed that BMI was a significant risk factor for 28-day mortality (p < 0.05). Subgroup analysis revealed an interactive effect of BMI on 28-day mortality in elderly (≥ 65 years old), male, and non-septic shock individuals (p < 0.05). A higher BMI was associated with an increased lymphocyte proportion and decreased neutrophil proportion, neutrophil-to-lymphocyte ratio (NLR), and systemic immune–inflammation index (SII) (p < 0.05). Compared with survivors, non-survivors had lower lymphocyte proportions and higher neutrophil proportions, NLRs, and SIIs. ROC analysis revealed that the lymphocyte and neutrophil proportions, NLR, and SII had predictive value for 28-day mortality. Subgroup and RCS analyses revealed that increased BMI was associated with reduced 28-day mortality in sepsis patients, mainly in elderly, male, and septic shock individuals, with protective BMIs ranging from 27.8 ~ 41.7 kg/cm2, 28.4 ~ 37.7 kg/cm2, and > 28.6 kg/cm2, respectively.

Conclusions

The sepsis–obesity paradox significantly affects elderly (≥ 65 years old), male, and non-septic shock individuals, displaying a U-shaped pattern for 28-day mortality. BMI may mediate this phenomenon by influencing the body’s immune–inflammatory status.

Peer Review reports

Background

The sepsis–obesity paradox refers to the phenomenon in which obese patients often have better outcomes and lower mortality rates than do normal- or underweight sepsis patients, contradicting the common belief that obesity increases disease risk [1,2,3,4,5]. Sepsis has become a global public health issue with high incidence and mortality rates [6,7,8], and a significant portion of patients hospitalized for sepsis each year are overweight or obese [9]. Therefore, further research is needed to understand how overweight or obesity affects sepsis mortality and the underlying mechanisms.

Currently, research on the impact of body mass index (BMI) on sepsis mortality has focused primarily on clinical studies, with varying conclusions. However, the central theme remains the sepsis–obesity paradox, which states that obese or overweight individuals have lower sepsis mortality rates [5, 10, 11]. Numerous studies, including meta-analyses, have explored the impact of obesity on sepsis mortality, yielding conclusions that support the above paradox and provide a reference for clinicians to assess the mortality of such patients during hospitalization [12, 13]. Moreover, most researchers have concluded that obesity or overweight can reduce sepsis mortality [14,15,16], despite the known harmful effects of obesity on health, including an increased risk of developing cardiovascular and cerebrovascular diseases [17, 18]. Thus, the relationship of BMI with sepsis mortality is likely not linear, as it may not have a protective effect after a certain threshold and could even increase sepsis mortality. Furthermore, it is unclear whether this phenomenon is due to unique levels of cellular immune inflammation in obese patients, and additional research is needed to determine whether the effect varies across different age and sex groups.

In this study, 6602 sepsis patients from the MIMIC-IV database were divided into BMI quartile groups; 28-day mortality was observed at each interval, and indicators such as white blood cell count, lymphocyte and neutrophil proportions, the neutrophil‒lymphocyte ratio (NLR), and the systemic immune‒inflammation index (SII) were analyzed. Subgroup and restricted cubic spline (RCS) analyses were also conducted. The present study revealed that an increase in BMI within a certain range can reduce 28-day sepsis mortality, with its impact on mortality showing a U-shaped pattern. Moreover, BMI may affect sepsis mortality by mediating indicators such as lymphocyte and neutrophil proportions, the NLR, and the SII, which influence the body’s immune–inflammatory status.

Materials and methods

Data sources

The data utilized in this study were sourced from the MIMIC-IV public database, which includes patients admitted to the intensive care unit (ICU) at the Beth Israel Deaconess Medical Center (BIDMC) in Boston, Massachusetts, spanning from 2008 to 2019. Demographic, biochemical, and prognostic indicators were extracted from the MIMIC-IV database. Prior to the research, the author completed the “Protecting Human Research Participants” course (certificate number: 63495433) and obtained approval from the Institutional Review Board of the Massachusetts Institute of Technology and BIDMC, granting access to the MIMIC-IV database.

Patient selection

The inclusion criteria were as follows: (1) sepsis patients aged 18 ~ 100 years; (2) no sex restrictions; and (3) first-time ICU admission. To analyze blood biochemical changes during sepsis, diseases significantly affecting the blood system were excluded (Fig. 1). The exclusion criteria were as follows: (1) immune system diseases; (2) aplastic anemia; and (3) malignant tumors.

Fig. 1
figure 1

Flow diagram

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Data extraction

We utilized pgAdmin software (Enterprise DB Company, USA), which primarily includes age, sex, weight, height, and the Sequential Organ Failure Assessment (SOFA) score at first admission, to extract patient data. Blood biochemical indicators included the first admission white blood cell count, lymphocyte percentage, neutrophil percentage, monocyte percentage, and platelet count. Patient prognostic indicators included hospital length of stay, ICU length of stay, 28-day in-hospital mortality, and 28-day mortality in the ICU (Table 1). Variables with more than 20% missing values were excluded, and multiple imputation was used to fill in missing values for variables with less than 20% missing data. In this study, two derived indicators, the NLR and the SII [19], were used to evaluate the level of inflammation in the body. Their calculation formulas are as follows:

$$\eqalign{& NLR = \cr& \,\,\,\,\,\,\,\,\,\,\,\,\,{\matrix{(\rm{White\,blood\,cell\,count}( \times {10^9}/\rm{L}) \times \hfill \cr\rm{Neutrophils\,percentage}(\% )) \hfill \cr} \over \matrix{(\rm{White\,blood\,cell\,count}( \times {10^9}/\rm{L}) \times \hfill \cr\rm{Lymphocytes\,percentage}(\% )) \hfill \cr} } \cr} $$
(1)
$$\eqalign{& SII = \cr& {\matrix{(\rm{Plateletcount}( \times {10^9}/L) \times \hfill \cr\rm{White\,blood\,cell\,count}( \times {10^9}/L) \times Neutrophils\,percentage(\% )) \hfill \cr} \over \matrix{(\rm{White\,blood\,cell\,count}( \times {10^9}/L) \times \hfill \cr\rm{Lymphocytes\,percentage}(\% )) \hfill \cr} } \cr} $$
(2)
Table 1 Clinical characteristics of individuals by BMI quartile
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Statistical analysis

In this study, data analysis was conducted using R software (version 4.4.1) and SPSS 26.0. The data are expressed as the means ± SDs or quartiles. Intergroup comparisons were performed via one-way ANOVA or the Kruskal‒Wallis nonparametric test. For comparisons between two groups, the independent sample t test or Mann‒Whitney test was used. The chi-square test was used to compare rates between two groups, and chi-square segmentation with Bonferroni correction was applied for comparisons among multiple groups. For binary logistic regression, the median of each group was used as a continuous variable for trend testing, and subgroup analysis was conducted to analyze different subgroups. RCSs were drawn using the rms and ggplot packages, and a correlation heatmap matrix was created using the Hmisc and corrplot packages.

Results

The analysis revealed that the 28-day mortality of sepsis patients (n = 6602) first decreased, reaching its lowest point at BMI quartile 3, but then increased with increasing BMI (Fig. 2a). After BMI reached the quartile 4 range, the 28-day mortality of patients tended to increase, and the mortality rate changed in a “U” shape with increasing BMI (Fig. 2b).

Fig. 2
figure 2

(a) As BMI increases, the proportion of 28-day mortality in sepsis patients first decreases but then increases, reaching its lowest point at BMI quartile 3 and showing an increasing trend at BMI quartile 4. (b) Line chart of 28-day mortality for sepsis patients in the 4 BMI ranges. Q1: quartile 1; Q2: quartile 2; Q3: quartile 3; and Q4: quartile 4

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Collinearity

Prior to conducting logistic regression, variable correlation analysis was performed to exclude collinearity among variables. The results revealed that the correlation between variables was less than 0.8, meeting the conditions for conducting binary logistic regression (Fig. 3).

Fig. 3
figure 3

Before conducting trend analysis, the collinearity between variables was tested, and the correlation between each variable was less than 0.8, meeting the conditions for logistic regression

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Trend analysis

Logistic trend analysis revealed that BMI significantly affected the 28-day mortality rate of sepsis patients (Table 2), and there was a linear relationship between the 28-day mortality rate of sepsis patients and BMI (ptrend=0.001).

Table 2 Trend analysis
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Subgroup analysis

An analysis of age, sex, septic shock, white blood cell count, monocyte percentage, neutrophil percentage, and lymphocyte percentage as subgroup variables revealed that BMI had an interactive effect on the 28-day mortality of sepsis patients in the age, sex and septic shock subgroups (pinteraction<0.05) (Fig. 4; Additional files 1), indicating that BMI significantly affected the 28-day mortality of sepsis patients in the age, sex, and septic shock subgroups (pinteraction<0.05).

Fig. 4
figure 4

Subgroup analysis of BMI quartiles 1 and 2 revealed a significant interaction effect between BMI and 28-day mortality in elderly (≥ 65 years) individuals (pinteraction<0.05)

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RCS sensitivity analysis

In the sepsis population, an increase in BMI within the range from 28.6 ~ 47.2 kg/cm2 was associated with a reduced 28-day mortality rate (Fig. 5a) (p < 0.0001), with an odds ratio (OR) < 1. Subgroup analysis revealed that BMI did not affect 28-day mortality in those under 65 years of age (Fig. 5b) (p > 0.05) but did affect mortality mainly in those over 65 years of age (Fig. 5c) (p < 0.0001). Additionally, BMI primarily affected 28-day mortality in male sepsis patients, showing a U-shaped protective effect (Fig. 5d) (p < 0.0001) and a weaker effect in females (Fig. 5e) (p = 0.052). In the non-septic shock subgroup, BMI (> 28.6 kg/cm2) was a protective factor, with a reduced 28-day mortality rate (Additional file 2).

Fig. 5
figure 5

(a) BMI had a U-shaped protective effect on 28-day mortality in sepsis patients (p < 0.0001). (b) In those under 65 years of age, BMI had no significant effect on sepsis mortality (p > 0.05). (c) For those over 65 years of age, BMI had a U-shaped relationship with sepsis mortality (p < 0.0001), with a protective BMI ranging from 27.8 ~ 41.7 kg/cm2. (d) In males, BMI had a U-shaped protective effect (p < 0.0001), with a protective BMI ranging from 28.4 ~ 37.7 kg/cm2. (e) In females, BMI had no significant protective effect (p = 0.052)

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Blood biochemical indicators in subgroups

The results revealed that with increasing BMI, the number of white blood cells and the proportion of lymphocytes increased, whereas the proportions of neutrophils and monocytes and the NLR and SII decreased (Additional file 3). Analysis of the age, sex, and septic shock subgroups revealed that this phenomenon was primarily observed in individuals over 65 years old and in both male and non-septic shock populations. Indicators that trended in a similar manner as did mortality included lymphocyte and neutrophil proportions and the NLR and SII, indicating that in elderly individuals over 65 years of age, males, and non-septic shock individuals, as BMI increased, the lymphocyte percentage, reflecting the patient’s immune level, increased, whereas the neutrophil percentage and the NLR and SII, reflecting systemic inflammation levels, decreased. A similar but less pronounced trend was observed in individuals younger than 65 years of age, females, and septic shock patients (Fig. 6; Additional file 4).

Fig. 6
figure 6

(a ~ f) White blood cell count, monocyte percentage, neutrophil percentage, lymphocyte percentage, NLR, and SII in the population under 65 years of age. (g ~ l) White blood cell count, monocyte percentage, neutrophil percentage, lymphocyte percentage, NLR, and SII in individuals over 65 years old

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Blood biochemical indicators of survivors and non-survivors

The sepsis population was divided into survivors (n = 5455) and non-survivors (n = 1057). The survivors presented lower white blood cell counts, neutrophil percentages, NLRs, and SIIs, along with higher lymphocyte and monocyte percentages (Additional file 5). Analysis of the age, sex, and septic shock subgroups revealed that these differences persisted and were unaffected by age or sex (Fig. 7; Additional file 6). Moreover, this phenomenon occurred mainly in non-septic shock patients (Additional file 7).

Fig. 7
figure 7

(a ~ f) White blood cell count, monocyte percentage, neutrophil percentage, lymphocyte percentage, NLR, and SII of survivors and non-survivors in the population under 65 years of age. (g ~ l) White blood cell count, monocyte percentage, neutrophil percentage, lymphocyte percentage, NLR, and SII of survivors and non-survivors in the population over 65 years of age

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ROC curve analysis

ROC curve analysis revealed that the white blood cell count, monocyte percentage, lymphocyte percentage, neutrophil percentage, NLR, and SII could influence the 28-day mortality of sepsis patients (n = 6602) to some extent. The AUC values for lymphocyte and neutrophil percentages, the NLR, and the SII were 0.66 95% (0.65 ~ 0.68), 0.60 95% (0.57 ~ 0.61), 0.65 95% (0.64 ~ 0.67), and 0.62 95% (0.60 ~ 0.63), respectively. The results indicated that all of these factors had some predictive effect on 28-day sepsis mortality across age, sex, and non-septic shock subgroups, with the lymphocyte percentage, neutrophil percentage, NLR, and SII demonstrating better overall predictive ability (Fig. 8; Additional file 8).

Fig. 8
figure 8

(a ~ d) The AUROC for the white blood cell count; monocyte, lymphocyte, and neutrophil percentages; NLR; and SII for the prediction of 28-day mortality in sepsis patients across age and sex subgroups. Notably, the neutrophil and lymphocyte proportions and the NLR and SII were better at predicting sepsis mortality

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Sepsis mortality in elderly, male, and non-septic shock subgroups

The analysis revealed a statistically significant U-shaped relationship between BMI and sepsis mortality in the population aged over 65 years, males, and the non-septic shock population (p < 0.05) (Fig. 9; Additional file 9). This trend, mirrored in blood biochemical indicators, suggested that BMI might impact 28-day mortality by influencing neutrophil and lymphocyte percentages, the NLR, and the SII, particularly in males (p < 0.05).

Fig. 9
figure 9

(a, b) In the population under 65 years of age, no significant change in sepsis mortality was observed with increasing BMI (p > 0.05). (c, d) Conversely, in the population over 65 years of age, a significant decrease in sepsis mortality was evident with increasing BMI (p < 0.05), exhibiting a U-shaped trend

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Discussion

This study revealed that an increase in BMI between 27.8 ~ 41.7 kg/cm2, 28.4 ~ 37.7 kg/cm2, and > 28.6 kg/cm2 in elderly (≥ 65 years), male, and non-septic shock individuals could reduce the 28-day mortality of sepsis patients. Compared with sepsis patients, obese and overweight elderly and male sepsis patients had lower neutrophil percentages, NLRs, and SIIs and higher lymphocyte percentages, revealing similar trends in 28-day mortality to those of sepsis patients in different BMI ranges. By analyzing the differences between survivors and non-survivors and using receiver operating characteristic (ROC) curves, the proportions of lymphocytes and neutrophils, NLR, and SII were found to be closely related to the 28-day mortality rate of sepsis patients. These findings suggested that BMI might affect the 28-day mortality of sepsis patients by influencing the immune–inflammatory status of elderly and male sepsis patients.

Our research revealed that as BMI increased, the mortality rate of sepsis patients showed a U-shaped change, which may be due to the increased risk of cardiovascular mortality when BMI is too high, thereby offsetting the protective effect of the increased BMI [20,21,22]. Through trend and subgroup analysis, it was found that this clinical phenomenon had the most significant effect on individuals over 65 years of age, males, and the non-septic shock individuals. Why the sepsis–obesity paradox played a more significant role in the elderly population and its underlying mechanism are not fully understood.

According to previous studies [23], the possible reasons for the more significant role of the sepsis–obesity paradox in the elderly population are as follows. (1) The elderly population has severe muscle loss, and fat has become an important source of energy storage instead of skeletal muscle. With increasing age, the body experiences considerable muscle loss and a decline in skeletal muscle function. Skeletal muscle loss and dysfunction can not only affect the physical coordination but also weaken the immune resistance of the elderly population [24,25,26], especially in the context of severe infectious diseases such as sepsis. During sepsis, the body is in a high metabolic state [27, 28]. Among young and elderly people with the same BMI, young people often have greater muscle reserves, and even those with a low BMI still have greater muscle fiber quantity and quality than do older individuals. The main way for elderly people to compensate for muscle loss caused by aging is through fat. For example, elderly people with a low BMI do not have sufficient fat reserves during sepsis, which theoretically increases the short-term mortality rate of sepsis patients. Some of the results of this study indirectly validated the above hypotheses (Fig. 9b and d). (2) The immunity of elderly individuals decreases, and effectively removing invading pathogens becomes difficult. With increasing age, the immune system of elderly individuals also ages, which is caused mainly by chronic inflammatory immune disorders in the body. Unlike younger individuals, when elderly individuals are faced with serious infectious diseases, the body is often unable to effectively eliminate the pathogens [29,30,31], which may partially explain why the younger sepsis population had lower mortality (Fig. 9b and d). The elderly population with a high BMI has greater fat accumulation, and fat factors, including leptin and adiponectin, can regulate the body’s imbalanced immune status to a certain extent [32,33,34], which can in part reduce the body’s inflammatory response (Fig. 6k and l), especially the excessive infiltration of inflammatory cells such as neutrophils into tissues and organs (Fig. 6i), and activate adaptive immune responses, including lymphocytes (Fig. 6j). Some of the results of this study indirectly validated our hypothesis. This study revealed similar changes in the proportions of lymphocytes and neutrophils and in the NLR, SII, and mortality rates across different BMI ranges. However, there was no similar trend in the proportion of white blood cells or monocyte percentage, and this phenomenon was mainly manifested in elderly and male individuals. An analysis of the differences between survivors and non-survivors revealed that survivors had a greater proportion of lymphocytes, a lower proportion of neutrophils, and a lower NLR and SII, indicating that survivors often had lower levels of inflammation and greater adaptive immunity in the early stages of sepsis. On the basis of previous research conclusions and the ROC curve in the present study, the above blood biochemical indicators have good predictive ability for sepsis mortality [35,36,37,38]. Therefore, we infer that BMI can affect the 28-day mortality of sepsis in elderly and male populations by influencing the level of immune inflammation in the body.

This study also revealed that the sepsis–obesity paradox has a more significant effect on the male population, although the underlying mechanisms require further investigation. Several factors may account for this phenomenon. (1) Male patients typically possess greater muscle mass, which has been shown can somewhat reduce the mortality rate in sepsis patients [39, 40]. This improved muscle mass not only decreases the severity of sepsis but also decelerates immune system aging, allowing it to function optimally during infection. (2) Fat is in different activation states in different sexes. The fat in the female population is distributed mainly in the thighs, buttocks, hips, and other areas, whereas the fat in the male population is more distributed around the internal organs in the abdomen [41,42,43]. Previous studies have shown that abdominal fat often has increased activity, and perhaps the accumulation of abdominal fat in male populations can better regulate the body’s immune system [44]. According to the results of the present study, the male population was better able to regulate the proportion of lymphocytes and neutrophils, the NLR, and the SII in the body (Additional files 4: Figure S5), which indirectly reflects the lower activity of adipocytes and the aging immune system in female patients than in male patients. Although adipocytes in female patients can regulate the immune inflammatory state of the body to some extent, they cannot reduce the short-term mortality of sepsis patients like they can in male patients (Additional files 9: Figure S12c, S12d).

This study revealed that the phenomenon of the sepsis obesity paradox was more pronounced in non-septic shock patients. During the process of progressing from non-septic shock to septic shock, the underlying mechanism faces more complex metabolic and hemodynamic changes [45, 46]. Obesity has greater metabolic reserve and immune regulation advantages in non-septic shock patients, but this compensatory advantage becomes less significant as the severity of the sepsis worsens.

The limitations of this study are as follows. (1) There may be certain differences in obesity rates among different races, and the impact of obesity on sepsis mortality across different races was not assessed. Therefore, the results may not fully reflect the situation among races. (2) The relationship between diabetes and sepsis prognosis was not discussed in detail, and future studies should consider assessing the impact of diabetes status on sepsis prognosis.

Conclusions

The sepsis–obesity paradox plays a significant role in elderly (≥ 65 years old), male, and non-septic shock individuals, displaying a U-shaped relationship between BMI and the 28-day mortality of sepsis patients. Moreover, this phenomenon may be mediated by the immune–inflammatory status of the body.

Data availability

Data analyzed during the present study are stored in the Medical Information Mart for Intensive Care (MIMIC-IV).

Abbreviations

BMI:

Body mass index

RCS:

Restricted cubic spline

ROC:

Receiver operating characteristic

SII:

Systemic immune–inflammation index

NLR:

Neutrophil‒lymphocyte ratio

WBC:

White blood cell

ICU:

Intensive care unit

BIDMC:

Beth Israel Deaconess Medical Center

SOFA:

Sequential Organ Failure Assessment

APS III:

Acute Physiology Score III

GCS:

Glasgow Coma Scale

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Acknowledgements

We would like to thank all the participants of this project for collecting the data.

Funding

This study was supported by the National Natural Science Foundation of China (82222038 and 82260372), the Chongqing Outstanding Youth Fund (CSTB2022NSCQ-JQX0017), the Science and Technology Program of Guizhou Province (gzwkj2023-382), and the General Medical Research Fund Program (TYYLKYJJ-2023-029 and TYYLKYJJ-2023-036).

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Author notes

  1. Zhe Xu, Zhuojie Li, and Ruguo Zhang contributed equally to this work.

Authors and Affiliations

  1. Department of Emergency, The Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, China

    Zhe Xu, Zhuojie Li, Guoxuan Peng & Jin Deng

  2. Department of Orthopedics, Guihang Guiyang Hospital, Guiyang, 550025, China

    Zhe Xu, Ruguo Zhang, Jingzhong Ge & Chen Liu

  3. Department of Orthopedics, The Fifth Hospital of Guiyang City, Guiyang, 550004, China

    Shanpeng Luo

  4. Department of Trauma Medical Center, Daping Hospital, State Key Laboratory of Trauma, Burns and Combined Injury, Army Medical University, Chongqing, 400042, China

    Ling Zeng

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  1. Zhe Xu
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Contributions

ZX, ZL, and RZ contributed to the data analysis, figures, and article writing. GP and JG conducted the data collection and writing. SL contributed to the data collection. CL took responsibility for the formal analysis and review. LZ and JD contributed to conceptualization and writing (review and editing). All the authors read and approved the final manuscript.

Corresponding authors

Correspondence to Ling Zeng or Jin Deng.

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Our IRB requirement was waived. All methods were conducted in accordance with relevant guidelines and the Declaration of Helsinki. All the information was obtained from the MIMIC IV database and was anonymized.

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The authors declare no competing interests.

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Xu, Z., Li, Z., Zhang, R. et al. Pronounced effects of the sepsis–obesity paradox in elderly and male individuals without septic shock and the role of immune–inflammatory status: an analysis of MIMIC-IV data. BMC Infect Dis 25, 545 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12879-025-10938-y

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Keywords

BMC Infectious Diseases

ISSN: 1471-2334

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