Challenges of assessing the burden of sepsis

Mechanisms of the septic heart: From inflammatory response to myocardial edema

Sepsis-induced myocardial dysfunction (SIMD), also known as sepsis-induced cardiomyopathy (SICM), is linked to significantly increased mortality. Despite its clinical importance, effective therapies for SIMD remain elusive, largely due to an incomplete understanding of its pathogenesis. Over the past five decades, research involving both animal models and human studies has highlighted several pathogenic mechanisms of SICM, yet many aspects remain unexplored. Initially thought to be primarily driven by inflammatory cytokines, current research indicates that these alone are insufficient for the development of cardiac dysfunction. Recent studies have brought attention to additional mechanisms, including excessive nitric oxide production, mitochondrial dysfunction, and disturbances in calcium homeostasis, as contributing factors in SICM. Emerging clinical evidence has highlighted the significant role of myocardial edema in the pathogenesis of SICM, particularly its association with cardiac remodeling in septic shock patients. This review synthesizes our current understanding of SIMD/SICM, focusing on myocardial edema's contribution to cardiac dysfunction and the critical role of the bradykinin receptor B1 (B1R) in altering myocardial microvascular permeability, a potential key player in myocardial edema development during sepsis. Additionally, this review briefly summarizes existing therapeutic strategies and their challenges and explores future research directions. It emphasizes the need for a deeper understanding of SICM to develop more effective treatments.

Prediction of 30-day mortality for ICU patients with Sepsis-3

BACKGROUND

There is a growing demand for advanced methods to improve the understanding and prediction of illnesses. This study focuses on Sepsis, a critical response to infection, aiming to enhance early detection and mortality prediction for Sepsis-3 patients to improve hospital resource allocation.

METHODS

In this study, we developed a Machine Learning (ML) framework to predict the 30-day mortality rate of ICU patients with Sepsis-3 using the MIMIC-III database. Advanced big data extraction tools like Snowflake were used to identify eligible patients. Decision tree models and Entropy Analyses helped refine feature selection, resulting in 30 relevant features curated with clinical experts. We employed the Light Gradient Boosting Machine (LightGBM) model for its efficiency and predictive power.

RESULTS

The study comprised a cohort of 9118 Sepsis-3 patients. Our preprocessing techniques significantly improved both the AUC and accuracy metrics. The LightGBM model achieved an impressive AUC of 0.983 (95% CI: [0.980-0.990]), an accuracy of 0.966, and an F1-score of 0.910. Notably, LightGBM showed a substantial 6% improvement over our best baseline model and a 14% enhancement over the best existing literature. These advancements are attributed to (I) the inclusion of the novel and pivotal feature Hospital Length of Stay (HOSP_LOS), absent in previous studies, and (II) LightGBM's gradient boosting architecture, enabling robust predictions with high-dimensional data while maintaining computational efficiency, as demonstrated by its learning curve.

CONCLUSIONS

Our preprocessing methodology reduced the number of relevant features and identified a crucial feature overlooked in previous studies. The proposed model demonstrated high predictive power and generalization capability, highlighting the potential of ML in ICU settings. This model can streamline ICU resource allocation and provide tailored interventions for Sepsis-3 patients.

Comparative efficacy of antioxidant therapies for sepsis and septic shock in the intensive care unit: A frequentist network meta-analysis

Background

Antioxidant therapy is gaining traction in managing sepsis and septic shock, owing to its perceived positive impact on patient outcomes. This study sought to compare the efficacy of five antioxidant therapies (melatonin, vitamin C, vitamin E, selenium, and N-acetylcysteine, both individually and in combination with other compounds such as vitamin B1, hydrocortisone, propolis, and glutamine) in treating sepsis or septic shock in the intensive care unit (ICU).

Methods

The study involved randomized and multi-arm trials with sepsis or septic shock patients using melatonin, vitamin C, vitamin E, selenium, or N-acetylcysteine. Studies were sourced from PubMed, Embase, Cochrane Library, ClinicalTrials.gov, and WHO - Clinical Trials Registry Platform for the frequentist network meta-analysis on 28-day mortality and Sequential Organ Failure Assessment (SOFA) scores. The risk of bias was assessed using the Physiotherapy Evidence Database scale. Therapies were compared directly and indirectly using R software.

Results

The study of 56 trials involving 9,366 patients was included. Bias assessment revealed that 89.3 % of trials achieved excellent or good quality. Based on treatment ranking and pairwise comparisons, melatonin with propolis (SUCRA = 93.29 %) is effective in improving SOFA scores, statistically significant, with no publication bias (p= 0.73). High-dose vitamin C (SUCRA = 83.97 %), vitamin C with vitamin B1 (SUCRA = 78.72 %), and melatonin (SUCRA = 67.03 %) are potential therapies for organ dysfunction. Melatonin (SUCRA = 88.22 %) and high-dose vitamin C (SUCRA = 80.75 %) were the most effective in reducing 28-day mortality rates. However, analysis indicated that the results for 28-day mortality rates were not statistically significant. Also, these results contained publication bias (p= 0.02).

Conclusion

The study offers fresh perspectives on antioxidant therapy treatments for sepsis or septic shock in ICU, emphasizing the combination of melatonin and propolis notably reduces SOFA scores for those patients.

Association Between Age and the 28-Day All-Cause Mortality in Tuberculosis Complicated by Sepsis in ICU Patients: A Retrospective Cohort Study

Purpose

Age is considered a vital factor in intensive care units (ICUs) because of its association with physiological frailty, comorbidities, and immune system function. Previous studies have examined the association between age and prognosis in patients with tuberculosis (TB) or sepsis; however, the association between age and prognosis in ICU patients with TB complicated by sepsis is rare. This study aimed to assess the association between age and the prognosis of patients in the ICU with TB complicated by sepsis.

Patients and Methods

Data from the ICU of the Public Health Clinical Center of Chengdu were analyzed using the multivariable Cox regression model, stratified analysis with interaction, restricted cubic spline (RCS), and threshold effect analysis to investigate the association between age and 28-day all-cause mortality in patients with TB complicated by sepsis.

Results

In total, 520 patients diagnosed with TB and sepsis were enrolled (120 women [23.1%]; median age, 64 years). The association between age and risk of death exhibited a J-shaped curve on the RCS (P for nonlinearity = 0.001). In the threshold analysis, the hazard ratio for the risk of death was 1.104 (95% confidence interval, 1.05-1.16) in participants aged ≥66.2 years. The risk of death increased by 10.4% with every 1-year increase in age in patients with TB complicated by sepsis. No significant association was found between age and 28-day all-cause mortality in patients aged <66.2 years.

Conclusion

A nonlinear relationship was observed between age and short-term all-cause mortality in patients in the ICU with TB complicated by sepsis. Patients with a higher age at admission may have a higher risk of death and require focused attention, close monitoring, and early treatment to reduce mortality.

How inflammation influences psychiatric disease

Recent studies highlight the strong correlation between infectious diseases and the development of neuropsychiatric disorders. In this editorial, we comment on the article "Anti-infective therapy durations predict psychological stress and laparoscopic surgery quality in pelvic abscess patients" by Zhang et al, published in the recent issue of the World Journal of Psychiatry 2023; 13 (11): 903-911. Our discussion highlighted the potential consequences of anxiety, depression, and psychosis, which are all linked to bacterial, fungal, and viral infections, which are relevant to the impact of inflammation on the sequelae in mental health as those we are observing after the coronavirus disease 2019 pandemic. We focus specifically on the immune mechanisms triggered by inflammation, the primary contributor to psychiatric complications. Importantly, pathophysiological mechanisms such as organ damage, post-injury inflammation, and infection-induced endocrine alterations, including hypocortisolism or autoantibody formation, significantly contribute to the development of chronic low-grade inflammation, promoting the emergence or development of psychiatric alterations in susceptible individuals. As inflammation can have long-term effects on patients, a multidisciplinary treatment plan can avoid complications and debilitating health issues, and it is crucial to recognize and address the mental health implications.