Corticosteroid use before ICU admission and 90-day all-cause readmission risk in patients with acute exacerbation of chronic obstructive pulmonary disease: an analysis of the MIMIC-IV database

Introduction

Chronic obstructive pulmonary disease (COPD) is a chronic respiratory condition characterized by persistent airflow limitation (1). According to the Global Burden of Disease Study, COPD was responsible for 212.3 million cases and 3.3 million deaths in 2019, making it a critical disease that significantly impacts patients’ health and quality of life (2). Patients with COPD frequently experience acute exacerbations, known as acute exacerbations of COPD (AECOPD), which are marked by increased shortness of breath, cough, and sputum production (3). These exacerbations are not only key contributors to adverse outcomes but are also closely associated with elevated readmission rates (4-6). A meta-analysis revealed that the readmission rates for AECOPD patients at 30, 60, 90, 180, and 365 days were 11%, 17%, 17%, 30%, and 37%, respectively (6). Frequent readmissions are linked to poor prognoses for patients and significant increases in economic burden on families and healthcare resource utilization (7,8).

According to the Global Initiative for COPD 2025 (GOLD), corticosteroids are recommended for use in the treatment of AECOPD due to their potent anti-inflammatory effects (3,9). The guidelines indicate that systemic corticosteroids can improve the forced expiratory volume in the first second and accelerate recovery in AECOPD patients, and the recommended course of treatment should not exceed 5 days (A-level evidence) (9). Corticosteroid therapy significantly reduces the risk of treatment failure and disease relapse within one month, shortens hospital stays for patients who do not require mechanical ventilation in the intensive care unit (ICU), and accelerates improvements in lung function and clinical symptoms (10). AECOPD patients who receive corticosteroid therapy during their first hospitalization have a lower risk of recurrence compared to non-users and an effectively reduced disease progression (11). However, adverse effects associated with corticosteroid therapy have been reported in multiple studies. A retrospective study indicated that short-term use of oral corticosteroids is associated with an elevated incidence of sepsis, venous thromboembolism, and fractures (12), while another meta-analysis identified corticosteroid use during hospitalization as a predictive factor for readmission in COPD patients (13). This difference in corticosteroid efficacy may stem from differences in research design, disease severity, comorbidities, and medication regimens (dosage, route of administration, course of treatment). However, there is currently a lack of research on the specific impact of corticosteroid use on the risk of all-cause readmission in AECOPD patients.

Therefore, this study aimed to utilize data from Medical Information Mart for Intensive Care IV (MIMIC-IV) to systematically evaluate relationships between systemic corticosteroid use before ICU admission and 90-day all-cause readmission rates in AECOPD patients. Our findings may provide crucial evidence for clinicians to weigh the benefits and risks of corticosteroid therapy in AECOPD management, facilitating the development of more personalized treatment strategies and improving patient outcomes. We present this article in accordance with the STROBE reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1154/rc).

Methods

Data source

Data were from MIMIC-IV (version 2.2), a longitudinal, single-center repository (https://physionet.org/content/mimiciv/2.2/) that includes 73,181 ICU admission records collected from Beth Israel Deaconess Medical Center from 2008 through 2019 (14). To protect patient privacy, all personal information in the database underwent rigorous de-identification processes, replacing patient identifiers with randomly generated codes. Consequently, informed consent and ethical approval were not required. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. All methodologies employed adhered to relevant guidelines and regulations.

Study population

AECOPD patients were identified using International Classification of Diseases, Ninth Revision (ICD-9) code 491.21, 491.22 and the ICD-10 codes J44.0, J44.1. Considering that AECOPD patients often have multiple exacerbations and repeated hospitalizations, we only included the first ICU admission record and patients who were readmitted for the first time after ICU discharge to avoid data duplication and statistical bias, thus ensuring the chronological order of exposure and outcomes, and focusing on short-term risks. After excluding patients with ICU stays of less than 24 hours, those under 18 years of age, patients who were not admitted to the ICU for the first time, and those who were not readmitted for the first time after the first ICU discharge, a total of 1,219 patients were included in this study (Figure 1).

Figure 1 Flowchart of patient inclusion and exclusion from the MIMIC-IV database. AECOPD, acute exacerbation of chronic obstructive pulmonary disease; ICU, intensive care unit; MIMIC-IV, Medical Information Mart for Intensive Care IV.

Data extraction

Clinical data were extracted using Structured Query Language (SQL) via Navicat Premium software (version 16.0.11) to connect with the MIMIC-IV database. The exposure variable of this study was whether corticosteroids were used before the first admission to the ICU. The drug records of patients from admission to the first admission to the ICU were screened based on the generic sequence number (GSN) in the prescription information table, which is based on the standard drug classification. Based on this, the use of hydrocortisone, methylprednisolone, prednisone, and dexamethasone was identified (15). The primary endpoint was the 90-day readmission rate.

We also collected patients’ demographic characteristics, comorbidities, vital signs, laboratory test results, disease severity scores, and treatment information as covariates. Demographic characteristics included gender, age, and marital status. Comorbidities comprised congestive heart failure, peripheral vascular disease, cerebrovascular disease, renal disease, diabetes, hypertension, hyperlipidemia and respiratory tract infection. Vital signs included temperature, heart rate, mean arterial pressure, respiratory rate, oxygen saturation, and blood glucose levels. Change in blood glucose was defined as the difference between the average blood glucose level on the first day of ICU admission and that on the first day of general ward admission. If the result was >0, an increase in blood glucose was indicated. Laboratory tests included anion gap, bicarbonate concentration, chloride concentration, hematocrit, hemoglobin, platelet count, potassium concentration, activated partial thromboplastin time, international normalized ratio, prothrombin time, sodium concentration, blood urea nitrogen, white blood cell count, red blood cell count, red cell distribution width, mean corpuscular hemoglobin, mean corpuscular hemoglobin concentration, and mean corpuscular volume. Vital signs and biochemical data were collected within the first 24 hours of ICU admission. To ensure the representativeness of the variables, for results with multiple measurements, vital signs were taken as the average, and laboratory indicators were selected based on clinical significance to reflect the most severe degree of the disease (such as the highest or lowest value). The specific value standards are shown in Table S1. Disease severity was assessed using the Simplified Acute Physiology Score II (SAPS II), Sequential Organ Failure Assessment (SOFA), and Acute Physiology Score III (APS III). Treatment information included whether patients received invasive ventilation, renal replacement therapy, vasopressor therapy, and antibiotic treatment on the first day in the ICU.

Statistical analysis

All statistical analyses were conducted using R software (version 4.4.1). We checked the proportion of missing values for all variables and excluded variables with a missing rate exceeding 20% to reduce the potential bias and uncertainty of the results caused by a large proportion of missing data. Variables with a missing rate ≤20% were subjected to multiple imputation using the random forest method in the Mice package of R software, while setting seeds to ensure reproducibility. The missing proportion of all variables is shown in Table S2. Baseline characteristics were summarized using the tableone package, with continuous variables expressed as means and standard deviations, and independent sample t-tests used for intergroup comparisons. Categorical variables were presented as counts and percentages, with chi-squared tests applied for comparisons between groups.

We performed multicollinearity analysis, excluding variables with variance inflation factors greater than 4 (Table S3). To balance baseline characteristics between the groups, we employed inverse probability of treatment weighting (IPTW) based on propensity score (PS). Specifically, patient baseline characteristics served as independent variables, while corticosteroid use was the dependent variable, allowing us to calculate PS for each patient using a multivariate logistic regression model. Subsequently, weights of 1/PS were assigned to patients receiving corticosteroids, and weights of 1/(1-PS) were assigned to those not receiving treatment, thereby constructing a weighted cohort (16).

A multivariate logistic regression model with robust standard errors was constructed using the survey package to evaluate the association between corticosteroid use and 90-day readmission risk among AECOPD patients in both the original and weighted cohorts. We further applied multiple logistic regression models in the original cohort to investigate the association between corticosteroid dose (expressed as equivalent dose of prednisolone per day) and the risk of all-cause readmission at 90 days. To account for dose differences among different corticosteroid preparations, we calculated the daily equivalent dose of prednisone based on standard conversion factors (hydrocortisone 20 mg = prednisone 5 mg = methylprednisolone 4 mg = dexamethasone 0.75 mg). After adjusting for all confounding factors, we conducted exploratory subgroup analysis and stratified evaluation by gender, invasive ventilation, antibiotic treatment and concomitant diseases (diabetes, hypertension, hyperlipidemia, congestive heart failure) to explore the potential impact of gender differences, disease severity, infection management and concomitant diseases on the association between systemic corticosteroid treatment and 90-day all-cause readmission risk. Furthermore, to explore the mediating effect of elevated blood glucose on the association between corticosteroid use and 90-day readmission risk through mediation analysis. The mediation analysis is based on two assumptions: (I) there are no unmeasured confounding factors, that is, there are no common causes missed between exposure, mediation, and outcome; (II) there is a clear chronological and causal relationship between exposure, mediation, and outcome. By using the Bootstrap method, the mediation ratio was estimated, the average causal mediation effect (ACME), average direct effect (ADE), and total effect were calculated. P<0.05 indicates statistically significant.

Results

Baseline characteristics

This study included 1,219 AECOPD patients with a mean age of 72.08±10.99 years. Among them, 350 patients were readmitted within 90 days post-discharge, resulting in a readmission rate of 28.7%. Compared to the non-corticosteroid group, the corticosteroid group had a higher proportion of females, elevated heart rates, increased blood glucose levels, a greater percentage of patients with elevated blood glucose, higher bicarbonate concentrations, elevated white blood cell counts, and lower mean corpuscular hemoglobin (P<0.001). Notably, the 90-day readmission rate for patients in the corticosteroid group was significantly higher than that of the other group (39.0% vs. 26.3%, P<0.001) (Table 1). After IPTW adjustment, all potential confounding factors, except for changes in blood glucose levels, were well balanced between the two groups, showing no statistical differences (Table S4).

Relationship between pre-ICU corticosteroid use and 90-day readmission rate in AECOPD patients

Table 2 presents the association between pre-ICU corticosteroid use and the 90-day readmission rate in AECOPD patients. In the original cohort, both unadjusted and adjusted models indicated that the risk of 90-day readmission was significantly higher in the corticosteroid group compared to the non-corticosteroid group [odds ratios (ORs) >1, P<0.001]. In the IPTW-adjusted cohort, this association was further strengthened. In the model adjusted for all confounding factors, patients who used corticosteroids had a significantly increased risk of 90-day readmission compared to those who did not use corticosteroids [original cohort: OR =1.933, 95% confidence interval (CI): 1.400–2.664, P<0.001]; post-IPTW cohort: OR =1.970, 95% CI: 1.417–2.738, P<0.001) (Table 2). We further found that the daily equivalent dose of prednisolone was significantly positively correlated with the 90-day all-cause readmission risk in AECOPD patients in the original cohort (OR =1.003, 95% CI: 1.000–1.006, P=0.047) (Table S5).

Subgroup analysis

To assess heterogeneity of association between corticosteroid use and readmission risk, we conducted subgroup analyses based on gender, invasive ventilation, antibiotic treatment, and comorbidities. The results showed that patients who used corticosteroids had a significantly increased risk of 90-day all-cause readmission in most subgroups (OR >1, P<0.05), and the effect trends before and after weighting were basically consistent across subgroups. In the analysis without IPTW, diabetes showed a significant interaction (P for interaction =0.036). In the subgroup with diabetes, corticosteroid was significantly positively correlated with the risk of all-cause readmission (OR =2.919, 95% CI: 1.701–5.057, P<0.001), while in the subgroup without diabetes, there was no significant correlation (OR =1.509, 95% CI: 0.981–2.302, P=0.058). After IPTW, the interaction of diabetes is no longer significant (Figure 2).

Figure 2 Subgroup analysis results before and after IPTW. CI, confidence interval; IPTW, inverse probability of treatment weighting; OR, odds ratio.

Mediation analysis

As indicated in Table S4, after IPTW adjustment, the proportion of patients experiencing elevated blood glucose levels in the corticosteroid group remained significantly higher than that in the non-corticosteroid group (38.1% vs. 25.5%, P<0.001). Corticosteroid treatment is associated with a higher incidence of clinically significant hyperglycemia compared to placebo (17), and COPD patients with hyperglycemia face heightened readmission risks (18). Based on this, we investigated the mediating role of elevated blood glucose in the relationship between corticosteroid use and 90-day readmission risk. The mediation analysis revealed that, in both the original and IPTW-adjusted cohorts, elevated blood glucose levels mediated the positive correlation between pre-admission corticosteroid use and 90-day readmission risk, accounting for 29.7% and 17.4% of the effect, respectively (Figure 3).

Figure 3 Mediation effect of blood glucose elevation on the association between pre-ICU corticosteroid use and 90-day readmission risk. Values in parentheses represent 95% confidence intervals. ICU, intensive care unit; IPTW, inverse probability of treatment weighting.

Discussion

This study, through analysis of the MIMIC-IV database, reveals a significant association between pre-ICU corticosteroid use and heightened 90-day readmission risk in AECOPD patients. The association is consistent across subgroups. Furthermore, we identified elevated blood glucose as a mediating factor in this association. These findings are essential for informing clinical treatment strategies in AECOPD management.

An observational study indicated that prolonged use of systemic corticosteroids during hospitalization may elevate the risk of readmission within 30 days post-discharge for AECOPD patients (19). Additionally, a meta-analysis revealed that corticosteroid treatment is linked to higher readmission rates (21.5%) in patients with community-acquired pneumonia compared to those without corticosteroid treatment (17.7%) (20). Both community-acquired pneumonia and AECOPD involve airway inflammation and dysregulated immune responses, with corticosteroids serving an anti-inflammatory role in both conditions (21). Thus, the impact of corticosteroids on the prognosis of these patient groups may exhibit some similarities, supporting our findings.

Corticosteroids may increase the 90-day readmission risk for AECOPD patients through multiple mechanisms. Firstly, the immunosuppressive effects of corticosteroids can elevate the risk of infections, including upper respiratory infections and pneumonia (22). A clinical trial demonstrated that patients receiving systemic corticosteroid treatment had a significantly higher incidence of infectious complications compared to controls (12.7% vs. 8.0%, P<0.001), with infection risk escalating in a dose-dependent manner (23). Such secondary infections could be key factors for readmission in AECOPD patients. Secondly, excessive corticosteroid use hinders osteoblast proliferation and differentiation, drives apoptosis of osteoblasts/osteocytes and increases the generation and lifespan of osteoclasts, ultimately causing osteoporosis and elevated fracture risks (24,25). Corticosteroids can also induce various metabolic abnormalities, such as hypertension, hyperglycemia, weight gain, and dyslipidemia (26,27). Corticosteroids may reduce muscle mass by fostering protein degradation and decreasing protein synthesis in skeletal muscle, triggering extensive muscle atrophy and the onset of myopathy (28), which can further delay patient recovery. We hypothesize that these adverse effects may interact synergistically, worsening patient outcomes and elevating readmission risk.

Our study also uncovered potential indirect mechanisms by which corticosteroids influence readmission risk through mediation analysis. The results indicated that elevated blood glucose accounted for 29.7% and 17.4% of the mediation effect in the original and IPTW-adjusted cohorts, respectively. Additionally, we observed that diabetes had a significant interaction between corticosteroid use and all-cause readmission risk in the original cohort: corticosteroid use was positively correlated with the all-cause readmission risk of AECOPD patients with diabetes, while there was no significant correlation in patients without diabetes. These findings suggest that elevated blood glucose levels may play an important role in the increased risk of readmission due to corticosteroids. Corticosteroids induce systemic insulin resistance by facilitating hepatic gluconeogenesis and lipolysis in adipose tissue while impairing pancreatic β-cell function, ultimately leading to hyperglycemia (29). Hyperglycemia may exacerbate AECOPD in various ways. Airway inflammation and hyperglycemia can elevate glucose concentrations in airway surface liquid, providing a carbon source for pathogens such as Staphylococcus aureus and Pseudomonas aeruginosa, thereby worsening pulmonary infections (30). Immunologically, elevated glucose levels can significantly impair neutrophil chemotaxis and induce extracellular trap formation and macrophage inflammatory responses (31,32). This compromised immune function, combined with the inherent immunosuppressive effects of corticosteroids, may substantially heighten the risk of infections. Moreover, hyperglycemia could impair respiratory muscle function by influencing mitochondrial activity. Diabetes is closely related to mitochondrial dysfunction, with manifestations including reduced mitochondrial numbers, impaired lipid oxidation, and excessive reactive oxygen species production. This mitochondrial dysregulation can induce a shift in muscle fibers from oxidative to glycolytic, ultimately leading to muscle weakness (33,34). Numerous clinical studies have confirmed a decline in respiratory muscle strength among diabetic patients, including significant reductions in maximum inspiratory and expiratory pressures (35,36). Thus, corticosteroids and hyperglycemia may jointly affect respiratory muscle function, heightening readmission risk. Finally, corticosteroid-induced hyperglycemia may necessitate additional glycemic interventions, which could raise readmission risk (18).

Subgroup analysis after IPTW adjustment revealed that the positive association between systemic corticosteroid use and readmission risk remained consistent across all subgroups, including variations in gender, invasive ventilation, antibiotic use, and comorbidities, indicating the universality of this risk factor. The uniformity of results among subgroups indicates the necessity for thorough risk evaluations for all AECOPD patients receiving corticosteroid therapy to prevent unnecessary usage.

In clinical practice, when using corticosteroids to treat AECOPD, it is necessary to fully consider the patient’s treatment responsiveness. A randomized placebo-controlled trial showed that the therapeutic effect of prednisolone was even worse than placebo (37). In addition, compared with standard treatment with prednisolone combined with antibiotics, individualized strategies based on biomarkers (i.e., placebo combined with antibiotics for patients with eosinophil counts ≤2%, and prednisolone combined with antibiotics for patients >2%) showed better efficacy (37). These results suggest that measuring eosinophil levels can help identify populations with poor response to corticosteroids, thereby avoiding corticosteroid abuse and mitigating the risk of adverse outcomes.

In recent years, biologics targeting eosinophil-associated inflammatory pathways have gradually received attention. Mepolizumab targeting interleukin-5 (IL-5), benralizumab targeting interleukin-5 receptor (IL-5R), and dupilumab targeting IL-4R have shown certain therapeutic effects in some COPD patients, especially for those with a history of elevated or frequently aggravated blood eosinophils (38,39). According to the update of GOLD 2025, dupilumab has been included as an optional treatment option for patients with blood eosinophils ≥300 cells/µL and worse condition after triple inhalation therapy (9,40,41).

This study has significant clinical and public health value. For AECOPD patients who need to be treated with corticosteroids, we recommend that the risk factors of hyperglycemia, including age, body mass index (BMI), and family history, be evaluated before starting treatment. Moreover, fasting blood glucose and hemoglobin A1c (HbA1c) should be measured, and the previous history of diabetes should be recorded. After the start of corticosteroid therapy, plasma glucose levels should be monitored for at least 1–3 days for timely personalized intervention (29).

There are some limitations in this study. First, the data were drawn exclusively from a single-center MIMIC-IV database, which may limit the generalizability of our findings. Second, we did not analyze detailed information about corticosteroid use, such as specific duration and routes of administration, all of which could impact how we interpret the results. Thirdly, we are unable to analyze the severity of AECOPD, which makes it difficult for us to stratify the effectiveness of corticosteroid therapy based on patient condition. Additionally, due to constraints within the database, we were unable to identify the specific reasons for patient readmissions, which restricts our ability to explore the relationship between corticosteroid use and different types of readmissions in depth.

Conclusions

The use of systemic corticosteroids before a patient’s first ICU admission is significantly linked to an increased risk of readmission within 90 days for AECOPD patients, and this association remains stable across various populations. Mediation analysis indicates that elevated blood glucose levels play a mediating role in the relationship between corticosteroid use and the increased readmission risk. These findings underscore the need for clinicians to thoroughly consider the benefits and risks of corticosteroid treatment for AECOPD patients, highlighting the importance of monitoring and managing blood glucose levels.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1154/rc

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1154/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1154/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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