Epidemiology and outcomes of sepsis among hospitalizations with systemic lupus erythematosus admitted to the ICU: a population-based cohort study

National Analysis of Preexisting Immunosuppressive Conditions and Infection-Related Readmissions Among Sepsis Survivors

BACKGROUND

Recurrent episodes of infection and subsequent sepsis are a frequent cause of readmission after sepsis hospitalization. Although persistent immune dysregulation initiated during the sepsis episode may play a role, the impact of preexisting immune suppression (including HIV, organ transplantation, and cancer) and common chronic diseases associated with immune suppression (diabetes and chronic kidney disease) on the risk of recurrent infections after sepsis is unknown.

OBJECTIVES

To investigate the role of preexisting immune-suppressive conditions (PISCs) and other common chronic diseases on infection-related readmissions after a sepsis admission.

METHODS

Using the US 2015 Nationwide Readmissions Database, we identified a retrospective cohort of adult patients with an unplanned sepsis index admission from April to September, excluding patients with sepsis during the preceding 90 days. We followed all sepsis survivors for subsequent infection-related admissions for 90 days. We identified clinical conditions using International Classification of Diseases coding.

RESULTS

We identified 649 029 unique unplanned sepsis admissions over 6 months; 189 604 (29.2%) had sepsis with PISC, and 459 425 (70.8%) had sepsis without PISC. Overall, sepsis survivors were older (median age, 70 years), and 145 156 (22.4%) experienced at least 1 infection-related readmission within 90 days. The incidence of infection-related readmission among sepsis survivors with PISC was 26.1%, whereas it was 20.8% for those without PISC. The excess risk of infection-related readmissions attributed to PISC was 5.3%, whereas the excess risk attributed to diabetes and chronic kidney disease was 3.7% and 4.7%, respectively. The background risk attributed to new-onset sepsis among participants with none of these conditions was 16.3%. Multivariable regression analysis adjusting for age, gender, and acute illness factors indicated that odds of infection-related readmission were strongly associated with PISC (odds ratio 1.30; 95% confidence interval, 1.29-1.32), closely followed by chronic kidney disease (1.28 [1.27-1.32]) and diabetes (1.17 [1.16-1.19]).

CONCLUSION

The risk of subsequent infection is higher among patients with PISC, although chronic kidney disease and diabetes are also important risk factors for subsequent infection and sepsis readmissions.

Rates, Diagnoses, and Predictors of Unplanned 30-Day Readmissions of Critical Care Survivors Hospitalized for Lung Involvement in Systemic Lupus Erythematosus: An Analysis of National Representative US Readmissions Data

INTRODUCTION/OBJECTIVES

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that frequently involves the lungs, contributing to significant morbidity in hospitalized patients. Critical care survivors with lung involvement in SLE are at particularly high risk for unplanned hospital readmissions, which can reflect the complexity of their disease, which often affects multiple organs and requires immunosuppressive therapy that increases infection risk. Severe pulmonary complications, critical illness sequelae, and challenges in medication adherence or follow-up care further contribute to their vulnerability. These factors result in frequent complications and flare-ups, making unplanned readmissions common in this population. This study assessed rates, most common reasons, and predictors of all-cause and SLE-related 30-day readmission among critically ill patients hospitalized for lung involvement in SLE.

METHODS

We analyzed the 2021 National Readmissions Database. Critically ill non-elective adult hospitalizations for lung involvement in SLE were identified for analysis using a combination of the ICD-10 diagnostic code for SLE with lung involvement (M32.13) and presence of any procedure codes for mechanical ventilation, tracheostomy, extracorporeal membrane oxygenation, or bronchoscopy. Non-lung-related SLE admissions, non-SLE-related lung disorders, patients with concomitant COPD, history of COVID-19 or severe asthma, patients transferred in from other hospitals or admitted for <24 hours, and patients with a DNR order were excluded. We used χ2 tests to compare baseline characteristics between readmissions and index hospitalizations. Stata ranking commands were used to identify the most recurrent diagnoses associated with 30-day readmissions. We used multivariate Cox regression analysis to identify independent predictors of readmissions.

RESULTS

Out of 3,472 index hospitalizations analyzed, 2,641 were discharged alive. Five hundred ninety-three (593; 22.5%) readmissions occurred within 30 days. Lung involvement in SLE was the most common reason for readmission (137; 23.1% of readmissions). Approximately 31.9% (189) of readmissions were due to other SLE-related complications. Readmissions were associated with higher inpatient mortality (18 (3.1%) versus 43 (1.6%); P=0.022), longer hospital stay (8 versus 5.2 days; P<0.001), younger mean age (26 versus 31 years; P=0.010), higher mean hospital costs (US $84,830 versus $64,628; P<0.001), and higher prevalence of heart failure (146 (24.6%) versus 526 (19.6%); P=0.024), CKD (435 (73.3%) versus 1,573 (58.6%); P<0.001), and anemia (138 (23.2%) versus 432 (16.1%); P=0.003) compared with index hospitalizations. Age ≥60 years (adjusted hazard ratio (AHR): 1.22; P=0.028), multiple (≥3) procedures during the initial admission (AHR: 2.57; P=0.003), discharge AMA (AHR: 1.68; P=0.047), lack of insurance/self-pay (AHR: 1.23; P=0.034), another coexisting autoimmune disorder (AHR: 1.19; P=0.041), index hospitalizations in the highest income quartile (AHR: 2.05; P=0.006), hyperlipidemia (AHR: 1.89; P=0.026), coexisting kidney disease (AHR: 1.56; P=0.017), and heart failure (AHR: 1.11; P=0.031) were significantly correlated with 30-day readmissions.

CONCLUSIONS

SLE lung readmissions were associated with worse outcomes than index hospitalization. Age ≥60 years, multiple procedures, discharge AMA, lack of insurance, kidney disease, and heart failure are significant predictors of readmission.

Prognostic impacts of repeated sepsis in intensive care unit on autoimmune disease patients: a retrospective cohort study

BACKGROUND

Autoimmune diseases (ADs) may be complicated by sepsis when intensive care unit (ICU) admission. But repeated sepsis among AD patients has not been studied yet. The aim of this study is to investigate the impact of repeated in-ICU sepsis on the 1-year overall-cause mortality, septic shock and in-ICU death of AD patients.

METHODS

Data of AD patients with sepsis retrieved from Medical Information Mart for Intensive Care IV (MIMIC-IV) database were divided into the single group and the repeated group according to the frequency of in-ICU sepsis. Propensity score matching was used to balance inter-group bias. Cox proportional hazard regression and sensitivity analysis were utilized to assess the variables on mortality.

RESULTS

The incidence of repeated in-ICU sepsis in baseline was 19.8%. The repeated in-ICU sepsis was a risk factor for 1-year overall-cause mortality among AD patients (adjusted hazard ratio [HR] = 1.50, 95% CI: 1.16-1.93, P = 0.002), with robust adjusted HRs by the adjustment for confounders in the sensitivity analysis (all P < 0.01). Maximum Sequential Organ Failure Assessment (Max SOFA), Charlson comorbidity index (CCI) and Simplified Acute Physiology Score-II (SAPS-II) were risk factors for 1-year overall-cause mortality among AD with repeated sepsis (Max SOFA: HR = 1.09, P = 0.002; CCI: HR = 1.08, P = 0.039; SAPS-II: HR = 1.03, P < 0.001).

CONCLUSIONS

Compared to single hit, repeated in-ICU sepsis was independently related to a higher risk of 1-year overall-cause mortality among AD patients. Assessment tools (Higher SOFA, CCI and SAPS-II scores) were closely linked to poor prognosis of AD with repeated sepsis and helped to reflect ill physical conditions for the patients.

Genetic associations between autoimmune diseases and the risks of severe sepsis and 28-day mortality: a two-sample Mendelian randomization study

BACKGROUND

Autoimmune diseases exhibit heterogenous dysregulation of pro-inflammatory or anti-inflammatory cytokine expression, akin to the pathophysiology of sepsis. It is speculated that individuals with autoimmune diseases may have an increased likelihood of developing sepsis and face elevated mortality risks following septic events. However, current observational studies have not yielded consistent conclusions. This study aims to explore the causal relationship between autoimmune diseases and the risks of sepsis and mortality using Mendelian randomization (MR) analysis.

METHODS

We conducted a two-sample MR study involving a European population, with 30 autoimmune diseases as the exposure factors. To assess causal relationships, we employed the inverse variance-weighted (IVW) method and used Cochran's Q test for heterogeneity, as well as the MR pleiotropy residual sum and outlier (MR-PRESSO) global test for potential horizontal pleiotropy.

RESULTS

Genetically predicted Crohn's disease (β = 0.067, se = 0.034, p = 0.046, OR = 1.069, 95% CI = 1.001-1.141) and idiopathic thrombocytopenic (β = 0.069, se = 0.031, p = 0.023, OR = 1.071, 95% CI = 1.009-1.136) were positively associated with an increased risk of sepsis in critical care. Conversely, rheumatoid arthritis (β = -0.104, se = 0.047, p = 0.025, OR = 0.901, 95% CI = 0.823-0.987), ulcerative colitis (β = -0.208, se = 0.084, p = 0.013, OR = 0.812, 95% CI = 0.690-0.957), and narcolepsy (β = -0.202, se = 0.092, p = 0.028, OR = 0.818, 95% CI = 0.684-0.978) were associated with a reduced risk of sepsis in critical care. Moreover, Crohn's disease (β = 0.234, se = 0.067, p = 0.001, OR = 1.263, 95% CI = 1.108-1.440) and idiopathic thrombocytopenic (β = 0.158, se = 0.061, p = 0.009, OR = 1.171, 95% CI = 1.041-1.317) were also linked to an increased risk of 28-day mortality of sepsis in critical care. In contrast, multiple sclerosis (β = -0.261, se = 0.112, p = 0.020, OR = 0.771, 95% CI = 0.619-0.960) and narcolepsy (β = -0.536, se = 0.184, p = 0.003, OR = 0.585, 95% CI = 0.408-0.838) were linked to a decreased risk of 28-day mortality of sepsis in critical care.

CONCLUSION

This MR study identified causal associations between certain autoimmune diseases and risks of sepsis in critical care, and 28-day mortality in the European population. These findings suggest that exploring the mechanisms underlying autoimmune diseases may offer new diagnostic and therapeutic strategies for sepsis prevention and treatment.

Association of autoimmune diseases with the occurrence and 28-day mortality of sepsis: an observational and Mendelian randomization study

BACKGROUND

Observational studies have indicated a potential association between autoimmune diseases and the occurrence of sepsis, with an increased risk of mortality among affected patients. However, whether a causal relationship exists between the two remains unknown.

METHODS

In the Mendelian randomization (MR) study, we accessed exposure Genome-wide association study (GWAS) data from both the MRC Integrative Epidemiology Unit (MRC-IEU) and the FinnGen consortium. GWAS data for sepsis and its 28-day mortality were obtained from MRC-IEU. We employed univariable, multivariable, and reverse MR analyses to explore potential associations between autoimmune disorders and sepsis and its 28-day mortality. Additionally, a two-step mediation MR analysis was performed to investigate indirect factors possibly influencing the relationship between autoimmune disorders and sepsis. Afterward, we conducted an observational analysis to further explore the relationship between autoimmune disease and occurrence as well as 28-day mortality of sepsis using a real-world database (the MIMIC-IV database). A cohort of 2537 patients diagnosed with autoimmune disease were extracted from the database for analysis. Multivariable logistic regression models were used to confirm the association between autoimmune diseases and the occurrence of sepsis, as well as the 28-day mortality associated with sepsis.

RESULTS

In univariable MR analysis, there appeared to be causal relationships between genetically predicted type 1 diabetes (OR = 1.036, 95% CI = 1.023-1.048, p = 9.130E-09), rheumatoid arthritis (OR = 1.077, 95% CI = 1.058-1.097, p = 1.00E-15) and sepsis, while a potential causal link was observed between celiac disease and sepsis (OR = 1.013, 95% CI = 1.002-1.024, p = 0.026). In a subsequent multivariable MR analysis, only rheumatoid arthritis was found to be independently associated with the risk of sepsis (OR = 1.138, 95% CI = 1.044-1.240, p = 3.36E-03). Furthermore, there was no causal link between autoimmune disorders and 28-day mortality from sepsis. In reverse MR analysis, sepsis was suggested to potentially trigger the onset of psoriasis (OR = 1.084, 95% CI = 1.040-1.131, p = 1.488E-04). In the real-world observational study, adjusting for multiple confounders, rheumatoid arthritis (OR = 1.34, 95% CI = 1.11-1.64, p = 0.003) and multiple sclerosis (OR = 1.31, 95% CI = 1.03-1.68, p = 0.02) were associated with a higher risk of sepsis. In addition, we did not find that autoimmune diseases were associated with 28-day mortality from sepsis.

CONCLUSION

Both in observational and MR analysis, only rheumatoid arthritis is highly correlated with occurrence of sepsis. However, autoimmune disease was not associated with an increased 28-day mortality in patient with sepsis. Sepsis may increase the risk of developing psoriasis.

Linking Sepsis with chronic arterial hypertension, diabetes mellitus, and socioeconomic factors in the United States: A scoping review

RATIONALE

Sepsis is a syndrome of life-threatening organ dysfunction caused by a dysregulated host immune response to infection. Social risk factors including location and poverty are associated with sepsis-related disparities. Understanding the social and biological phenotypes linked with the incidence of sepsis is warranted to identify the most at-risk populations. We aim to examine how factors in disadvantage influence health disparities related to sepsis.

METHODS

A scoping review was performed for English-language articles published in the United States from 1990 to 2022 on PubMed, Web of Science, and Scopus. Of the 2064 articles found, 139 met eligibility criteria and were included for review.

RESULTS

There is consistency across the literature of disproportionately higher rates of sepsis incidence, mortality, readmissions, and associated complications, in neighborhoods with socioeconomic disadvantage and significant poverty. Chronic arterial hypertension and diabetes mellitus also occur more frequently in the same geographic distribution as sepsis, suggesting a potential shared pathophysiology.

CONCLUSIONS

The distribution of chronic arterial hypertension, diabetes mellitus, social risk factors associated with socioeconomic disadvantage, and sepsis incidence, are clustered in specific geographical areas and linked by endothelial dysfunction. Such population factors can be utilized to create equitable interventions aimed at mitigating sepsis incidence and sepsis-related disparities.

Machine learning: Predicting hospital length of stay in patients admitted for lupus flares

BACKGROUND

Although rare, severe systemic lupus erythematosus (SLE) flares requiring hospitalization account for most of the direct costs of SLE care. New machine learning (ML) methods may optimize lupus care by predicting which patients will have a prolonged hospital length of stay (LOS). Our study uses a machine learning approach to predict the LOS in patients admitted for lupus flares and assesses which features prolong LOS.

METHODS

Our study sampled 5831 patients admitted for lupus flares from the National Inpatient Sample Database 2016-2018 and collected 90 demographics and comorbidity features. Four machine learning (ML) models were built (XGBoost, Linear Support Vector Machines, K Nearest Neighbors, and Logistic Regression) to predict LOS, and their performance was evaluated using multiple metrics, including accuracy, receiver operator area under the curve (ROC-AUC), precision-recall area under the curve (PR- AUC), and F1-score. Using the highest-performing model (XGBoost), we assessed the feature importance of our input features using Shapley value explanations (SHAP) to rank their impact on LOS.

RESULTS

Our XGB model performed the best with a ROC-AUC of 0.87, PR-AUC of 0.61, an F1 score of 0.56, and an accuracy of 95%. The features with the most significant impact on the model were "the need for a central line," "acute dialysis," and "acute renal failure." Other top features include those related to renal and infectious comorbidities.

CONCLUSION

Our results were consistent with the established literature and showed promise in ML over traditional methods of predictive analyses, even with rare rheumatic events such as lupus flare hospitalizations.

Outcome of critically ill patients with systemic lupus erythematosus from a medical intensive care unit in Southern India

OBJECTIVE

Systemic lupus erythematosus (SLE) has become the most prevalent autoimmune condition requiring admission in the intensive care units (ICU) in the last two decades. Here we analysed the clinical outcomes of SLE patients admitted to our ICU between 2011 and 2021, and studied the prognostic role of high-density lipoprotein (HDL) and procalcitonin in those enrolled after August 2019.

METHODS

Systemic lupus erythematosus (ACR/SLICC 2012) were enrolled, 72 retrospectively and 30 prospectively. Data on indications for ICU admission, complications, infections, and disease activity were recorded. Outcome was mortality at 90 days (prospective) whereas in the retrospective analysis outcome was hospital discharge or death in hospital. Serum HDL and procalcitonin (PCT) was estimated in the prospectively enrolled 30 patients and compared with 30 non ICU-SLE patients.

RESULTS

Indications for ICU admissions were respiratory causes in 78/102 (76.5%) patients; for haemodynamic monitoring and for invasive procedures in the remaining. Pneumonia was the primary reason for mechanical ventilation, followed by diffuse alveolar haemorrhage (DAH). Eighty-three (81.3%) patients died; infections (n = 54) and SLE related causes (n = 29). APACHE-II >16 (p = .026), lymphopenia (p = .021), infection (p = .002), creatinine >1.3 mg/dL (p = .023), and hypotension requiring vasopressor support (p = .006) emerged as significant predictors of non-survival on multivariable analysis. HDL (mg/dL) day 1 was significantly lower in SLE-ICU patients compared to non ICU-SLE (31.8 ± 14.3 vs 38.8 ± 11.4 mg/dl); p = .045. On day 1, PCT (ng/mL) in SLE-ICU was significantly higher when compared to non-ICU SLE; median (IQR): 0.53 (0.26-5.27) versus 0.13 (0.05-0.47), p < .001), respectively. It was also significantly higher on day 5 in SLE-ICU than non-ICU SLE (median (IQR): 4.18 (0.20-14.67) versus 0.10 (0.08-0.46), p = .004.

CONCLUSION

The mortality of SLE patients admitted to the ICU in this study is high, and infections were the principal reason for death. Baseline low HDL and higher procalcitonin are potential biomarkers to identify critically ill SLE patients.

Predictors of infection requiring hospitalization in patients with systemic lupus erythematosus: a time-to-event analysis

OBJECTIVES

To evaluate the predictors of serious infection in patients with systemic lupus erythematosus (SLE).

METHODS

Serious infections were identified in SLE patients in a prospectively-followed single centre cohort. Associations of serious infection with disease-related variables and medication use were analysed using Cox and related regression models.

RESULTS

346 patients were followed for a mean (SD) of 6.6 (3.7) years. 86 episodes of serious infection were observed, with an incidence rate of 3.8 episodes per 100 person-years. Patients who had serious infection had higher baseline SLE Damage Index (SDI) and Charlston Comorbidity Index (CCI); they were also more likely to have high disease activity status (HDAS), and higher disease activity in multiple clinical domains, higher flare rates, higher time-adjusted prednisolone dose exposure, and less time in lupus low disease activity state (LLDAS). Patients who have received cyclophosphamide, rituximab and mycophenolate were more likely to have experienced serious infection. After multivariable adjustment in Cox regression analysis, cyclophosphamide, higher SDI score, and higher disease activity were associated with an increased hazard of first serious infection. History of previous serious infection conferred the highest risk. Lymphopenia was also a modest but statistically significant predictor of serious infection.

CONCLUSION

History of previous serious infection was the strongest predictor of serious infection in our SLE cohort. This study also suggests that clinical factors such as damage accrual, disease activity, and choice of immunosuppressant, can each have an independent risk in predicting serious infection particularly the first episode.

Neuropsychiatric Lupus and Lupus Nephritis Successfully Treated with Combined IVIG and Rituximab: An Alternative to Standard of Care

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease with unpredictable course and flares. The clinical manifestation can vary from mild to severe and life-threatening disease. Infection is the primary cause of mortality in hospitalized SLE patients. There is a paucity of evidence to support the co-management of SLE with major organ involvement and sepsis. We describe the clinical response of a 35-year-old male diagnosed with SLE; then, he developed severe sepsis and a flare of SLE with major organ involvement including lupus nephritis (LN), myocarditis, and neuropsychiatric systemic lupus erythematosus (NPSLE). Based on the patient’s condition, a treatment dilemma was encountered, and after a multidisciplinary meeting, the decision was made to use a combination of rituximab (RTX), intravenous immunoglobulin (IVIG), and pulse steroid. Shortly, the patient’s condition started to improve, and his symptoms were resolved. In conclusion, our clinical case suggests that combined RTX, IVIG, and pulse steroid seem to be effective and safe in achieving clinical response, thus representing a good choice for managing severe SLE flares in sepsis.

Identification and Validation of Pathogenic Genes in Sepsis and Associated Diseases by Integrated Bioinformatics Approach

Sepsis is a clinical syndrome with high mortality and morbidity rates. In sepsis, the abrupt release of cytokines by the innate immune system may cause multiorgan failure, leading to septic shock and associated complications. In the presence of a number of systemic disorders, such as sepsis, infections, diabetes, and systemic lupus erythematosus (SLE), cardiorenal syndrome (CRS) type 5 is defined by concomitant cardiac and renal dysfunctions Thus, our study suggests that certain mRNAs and unexplored pathways may pave a way to unravel critical therapeutic targets in three debilitating and interrelated illnesses, namely, sepsis, SLE, and CRS. Sepsis, SLE, and CRS are closely interrelated complex diseases likely sharing an overlapping pathogenesis caused by erroneous gene network activities. We sought to identify the shared gene networks and the key genes for sepsis, SLE, and CRS by completing an integrative analysis. Initially, 868 DEGs were identified in 16 GSE datasets. Based on degree centrality, 27 hub genes were revealed. The gProfiler webtool was used to perform functional annotations and enriched molecular pathway analyses. Finally, core hub genes (EGR1, MMP9, and CD44) were validated using RT-PCR analysis. Our comprehensive multiplex network approach to hub gene discovery is effective, as evidenced by the findings. This work provides a novel research path for a new research direction in multi-omics biological data analysis.

Impact of systemic lupus erythematosus on the 5-year survival of critically ill septic patients

Background

Infectious disease is an increasing threat to patients with systemic lupus erythematosus (SLE); however, the long-term outcome in critically ill septic patients with SLE remains unclear, and we aimed to address the impact of SLE on 5-year survival in critically ill septic patients.

Methods

We used the 2003–2017 nationwide data with 825,556 patients with sepsis in Taiwan. We identified lupus cases with sepsis that required admission to the intensive care unit and mechanical ventilation and selected controls matched (1:4) for age, sex, and index-year. Conditional logistic regression analysis was used to determine risk factors for mortality risk and shown as odds ratios (HRs) with 95% confidence intervals (CIs).

Results

A total of 513 SLE-sepsis patients and 2052 matched non-SLE septic individuals were enrolled. The mortality rate was higher in the SLE group (38.5 per 100,000 person-year) than that in the non-SLE group (13.7 per 100,000 person-year), with an IRR of 2.8 (95% CI, 2.5–3.2). We found that SLE was independently associated with a high mortality rate after adjusting relevant variables (HR 1.47, 95% CI 1.27–1.77). In addition to SLE, a higher age (HR 1.02, 95% CI 1.02–1.02), more comorbidities, and receiving prednisolone equivalent dose higher than 5 mg/day (HR 1.55, 95% CI 1.27–1.90), methotrexate (HR 2.19, 95% CI 1.61–2.99), and immunosuppressants (HR 1.45, 95% CI 1.22–1.74) were also independent risks for mortality.

Conclusions

We identified that SLE affects the long-term mortality in critically ill septic patients, and more studies are warranted for the underlying mechanism.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13075-021-02649-x.

Systemic lupus erythematosus and critical illness polyneuropathy

Systemic lupus erythematosus (SLE) is a chronic disease of connective tissue with multi-organ involvement. Manifestation in the nervous system is one of the most difficult symptoms to assess and interpret. The aim of the study is to indicate diagnostic problems in patients with SLE in whom neurological symptoms are present at the time of diagnosis of SLE but also with complications that occurred after diagnosis.

In the presented case, the appearance of flaccid tetraparesis with areflexia suggested peripheral damage to the nervous system. In the electromyography performed in this patient, acute axonal polyneuropathy was mainly suspected. Further differential diagnosis should consider other acute and subacute developing polyneuropathies. Guillain-Barré polyneuropathy deserves special attention.

To our knowledge, this is the first case documented in the literature of the coexistence of critical illness polyneuropathy and SLE.

Development of a Novel Simple Model to Predict Mortality in Patients With Systemic Lupus Erythematosus Admitted to the Intensive Care Unit

Background: Patients with systemic lupus erythematosus (SLE) may sometimes require admission to the intensive care unit (ICU), and the outcome is poor. The aim of this study was to explore the clinical features of patients with SLE in the ICU, identify prognostic factors, and develop and evaluate a prognostic model to predict in-ICU mortality of patients with SLE. Patients and Methods: This was a single center retrospective study in a tertiary medical institution in China. A total of 480 SLE patients with 505 ICU admissions from 2010 to 2019 were screened, and 391 patients were enrolled. The clinical feature and outcomes of the patients were analyzed. According to the random number table, patients were divided into two mutually exclusively groups named derivation (n = 293) and validation (n = 98). Prognostic factors were identified by a Cox model with Markov Chain Monte Carlo simulation and evaluated by latent analysis. The risk score was developed based on the derivation group and evaluated using the validation group. Results: Among the 391 patients, 348 (89.0%) patients were females. The median age of patients was 34 years, and the median course of SLE was 6 months. The median APACHE II and SLEDAI were 17 and 10, respectively. The average in-ICU mortality was 53.4% (95% CI, 48.5-58.4%). A total of 186 patients were admitted to the ICU due to infection. Pneumonia (320/391, 81.8%) was the most common clinical manifestation, followed by renal disease (246/391, 62.9%). Nine prognostic factors were identified. The model had C statistic of 0.912 (95% CI, 0.889-0.948) and 0.807 (95% CI 0.703-0.889), with predictive range of 5.2-98.3% and 6.3-94.7% for the derivation and validation groups, respectively. Based on distribution of the risk score, 25.3, 49.5, and 25.2% of patients were stratified into the high, average, and low-risk groups, with corresponding in-ICU mortality of 0.937, 0.593, and 0.118, respectively. Conclusion: Nine prognostic factors including age, white blood cell count, alanine transaminase, uric acid, intracranial infection, shock, intracranial hemorrhage, respiratory failure, and cyclosporin A/tacrolimus usage were identified. A prognostic model was developed and evaluated to predict in-ICU mortality of patients with SLE. These findings may help clinicians to prognostically stratify patients into different risk groups of in-ICU mortality, and provide patients with intensive and targeted management.

Systemic Lupus Erythematosus and Critical Illness

Systemic lupus erythematosus is a chronic autoimmune disorder that causes a wide range of mild to life-threatening conditions that require hospitalization and critical care. The morbidity and mortality of systemic lupus erythematosus are associated with the organ system damage caused by intermittent or chronic disease activity and with the complications of long-term and toxic immunosuppressant medication regimens. This article reviews the epidemiologic, clinical, diagnostic, and therapeutic information essential for critical care clinicians who provide care to patients with systemic lupus erythematosus.

Sepsis Mortality Is high in Patients With Connective Tissue Diseases Admitted to the Intensive Care Unit (ICU)

Objectives:

Patients with connective tissue diseases (CTD) such as systemic lupus erythematosus (SLE) have an increased risk for infections. This study investigated the outcome and characteristics of CTD patients under intensive care unit (ICU) treatment for sepsis.

Methods:

A single-center retrospective analysis was conducted and reviewed all patients with a CTD diagnosis admitted to the ICU of a university hospital for sepsis between 2006 and 2019. Mortality was computed and multivariate logistic regression was used to detect independent risk factors for sepsis mortality. Furthermore, the positive predictive value of ICU scores such as Sequential Organ Failure Assessment (SOFA) score was evaluated.

Results:

This study included 44 patients with CTD (mean age 59.8 ± 16.1 years, 68.2% females), most of them with a diagnosed SLE (61.4%) followed by systemic sclerosis (15.9%). 56.8% (n = 25) were treated with immunosuppressives and 81.8% (n = 36) received glucocorticoids. Rituximab was used in 3 patients (6.8%). The hospital mortality of septic CTD patients was high with 40.9%. It was highest among systemic sclerosis (SSc) patients (85.7%). SOFA score and diagnosis of SSc were independently associated with mortality in multivariate logistic regression (P = 0.004 and 0.03, respectively). The Simplified Acute Physiology Score II (SAPS II), SOFA and Acute Physiology and Chronic Health Evaluation II (APACHE II) scores were good predictors of sepsis mortality in the investigated cohort (SAPS II AUC 0.772, P = 0.002; SOFA AUC 0.756, P = 0.004; APACHE II AUC 0.741, P = 0.007).

Conclusions:

In-hospital sepsis mortality is high in CTD patients. SSc diagnoses and SOFA were independently associated with mortality. Additionally, common ICU scores were good predictors for mortality.

Bacterial infections in lupus: Roles in promoting immune activation and in pathogenesis of the disease

BACKGROUND

Bacterial infections of the lung, skin, bloodstream and other tissues are common in patients with systemic lupus erythematosus (lupus) and are often more severe and invasive than similar infections in control populations. A variety of studies have explored the changes in bacterial abundance in lupus patients, the rates of infection and the influence of particular bacterial species on disease progression, using both human patient samples and mouse models of lupus.

OBJECTIVE

The aim of this review is to summarize human and mouse studies that describe changes in the bacterial microbiome in lupus, the role of a leaky gut in stimulating inflammation, identification of specific bacterial species associated with lupus, and the potential roles of certain common bacterial infections in promoting lupus progression.

METHODS

Information was collected using searches of the Pubmed database for articles relevant to bacterial infections in lupus and to microbiome changes associated with lupus.

RESULTS

The reviewed studies demonstrate significant changes in the bacterial microbiome of lupus patients as compared to control subjects and in lupus-prone mice compared to control mice. Furthermore, there is evidence supporting the existence of a leaky gut in lupus patients and in lupus-prone mice. This leaky gut may allow live bacteria or bacterial components to enter the circulation and cause inflammation. Invasive bacterial infections are more common and often more severe in lupus patients. These include infections caused by Staphylococcus aureus, Salmonella enterica, Escherichia coli, Streptococcus pneumoniae and mycobacteria. These bacterial infections can trigger increased immune activation and inflammation, potentially stimulating activation of autoreactive lymphocytes and leading to worsening of lupus symptoms.

CONCLUSIONS

Together, the evidence suggests that lupus predisposes to infection, while infection may trigger worsening lupus, leading to a feedback loop that may reinforce autoimmune symptoms.

Predicting 30-days mortality for MIMIC-III patients with sepsis-3: a machine learning approach using XGboost

BACKGROUND

Sepsis is a significant cause of mortality in-hospital, especially in ICU patients. Early prediction of sepsis is essential, as prompt and appropriate treatment can improve survival outcomes. Machine learning methods are flexible prediction algorithms with potential advantages over conventional regression and scoring system. The aims of this study were to develop a machine learning approach using XGboost to predict the 30-days mortality for MIMIC-III Patients with sepsis-3 and to determine whether such model performs better than traditional prediction models.

METHODS

Using the MIMIC-III v1.4, we identified patients with sepsis-3. The data was split into two groups based on death or survival within 30 days and variables, selected based on clinical significance and availability by stepwise analysis, were displayed and compared between groups. Three predictive models including conventional logistic regression model, SAPS-II score prediction model and XGBoost algorithm model were constructed by R software. Then, the performances of the three models were tested and compared by AUCs of the receiver operating characteristic curves and decision curve analysis. At last, nomogram and clinical impact curve were used to validate the model.

RESULTS

A total of 4559 sepsis-3 patients are included in the study, in which, 889 patients were death and 3670 survival within 30 days, respectively. According to the results of AUCs (0.819 [95% CI 0.800-0.838], 0.797 [95% CI 0.781-0.813] and 0.857 [95% CI 0.839-0.876]) and decision curve analysis for the three models, the XGboost model performs best. The risk nomogram and clinical impact curve verify that the XGboost model possesses significant predictive value.

CONCLUSIONS

Using machine learning technique by XGboost, more significant prediction model can be built. This XGboost model may prove clinically useful and assist clinicians in tailoring precise management and therapy for the patients with sepsis-3.

Acute myocardial dysfunction in lupus: outcomes in Asian Indians

BACKGROUND

Acute myocardial dysfunction is an uncommon but potentially fatal complication in systemic lupus erythematosus (SLE). We describe the outcome in a small series of Asian Indian patients and examine associated factors.

METHODS

SLE patients who fulfilled the 2012 SLICC criteria and developed new-onset myocardial dysfunction were included in this retrospective case series. Acute myocardial dysfunction was defined as global hypokinesia and left ventricular ejection fraction (LVEF)<50% on echocardiography (with or without symptoms) in patients with SLE. Survival was assessed using Kaplan-Meier survival analysis and Cox regression.

RESULTS

This study included 37 patients with mean age 28.2 ± 11.2 years and median (range) LVEF of 35% (18-48%) at presentation. A majority had active disease, with SLEDAI-2k ≥ 5 in 26 (of 28). All patients received oral corticosteroids and a majority received additional immunosuppression, including pulse methylprednisolone in 28 and cyclophosphamide in 27. Nine patients died during hospitalisation (25%), a majority due to infections. Death was significantly associated with elevated procalcitonin at presentation (p = 0.05), elevated white cell count (p = 0.02) and low complement C3 (p = 0.03). In those who survived, long-term outcomes were good, with complete myocardial recovery in 14 (64%). A higher ejection fraction at presentation was associated with complete recovery.

CONCLUSIONS

In this small series of patients of SLE with acute myocardial dysfunction, we report a significant in-hospital mortality due to infections. Many of the patients who died had elevated procalcitonin at presentation. A diligent search for infection seems prudent in lupus patients who present with acute myocardial dysfunction. Key Points • In patients of SLE with acute myocardial dysfunction who were treated with immunosuppression, there was significant short-term mortality due to infections. • This mortality was associated with elevated procalcitonin at baseline and may suggest some of them had pre-existing hidden sepsis. • A prudent search for infections in these patients before immunosuppression may help to decrease short-term mortality.

Systemic lupus erythematosus in the intensive care unit: a systematic review

Systemic lupus erythematosus (SLE) is an autoimmune disease with heterogeneous pathophysiologic mechanisms and diverse clinical manifestations. SLE is a frequent cause of intensive care unit (ICU) admissions. Multiple studies with controversial findings on the causes, evolution and outcomes of ICU-admitted patients with SLE have been published. The aim of this paper is to review the literature reporting the clinical characteristics and outcomes, such as mortality and associated factors, in such patients. Among the main causes of ICU admissions are SLE disease activity, respiratory failure, multi-organ failure and infections. The main factors associated with mortality are a high Acute Physiology and Chronic Health Evaluation (APACHE) score, the need for mechanical ventilation, and vasoactive and inotropic agent use. Reported mortality rates are 18.4%-78.5%. Therefore, it is important to evaluate SLE disease severity for optimizing clinical management and patient outcomes.

Clinical characterization, outcomes, and prognosis in patients with systemic lupus erythematosus admitted to the intensive care unit

OBJECTIVE

Systemic lupus erythematosus (SLE) is a clinically heterogeneous autoimmune disease, and in some conditions, admission to the intensive care unit (ICUs) is required. This study describes the clinical and prognostic factors in SLE patients admitted to the ICU.

METHODS

We conducted a retrospective study that reviewed all clinical records of patients with SLE admitted to the ICU between 2011 and 2018.

RESULTS

We evaluated 188 patients, with 279 ICU admissions. Most patients were female (n = 159; 84.57%) with a median age of 35 years (interquartile range (IQR) = 25-48 years). Infection was the leading cause of admission in 77 (27.60%) cases, followed by lupus flare. The average length of hospitalization was 5 days (IQR 3-11 days), and the SLE Disease Activity Index 2000, Acute Physiology, Age and Chronic Health Evaluation (APACHE II), and Sequential Organ Failure Assessment (SOFA) scores were 9 (IQR 2-17), 14 (IQR 10-17), and 3 (IQR 2-5), respectively. Non-survivors presented with higher APACHE II and SOFA scores. Infection was the leading cause of mortality (n = 38; 20.21%), and predictors of mortality included invasive mechanical ventilation, vasoactive medication requirement, higher SOFA scores, and antiphospholipid syndrome comorbidity.

CONCLUSIONS

We found that infection was the leading cause of ICU admissions and mortality in patients with SLE. Factors identified here as predictors of mortality should be accurately identified at admission for the prompt treatment of SLE patients.