Free Light Chains, High Mobility Group Box 1, and Mortality in Hemodialysis Patients

Lacquaniti, Antonio; Campo, Susanna; Falliti, Giuseppe; Caruso, Daniele; Gargano, Romana; Giunta, Elena Enrica; Monardo, Paolo

doi:10.3390/jcm11236904

Cited by 5 publications

(3 citation statements)

References 53 publications

(58 reference statements)

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“…Additionally, ischemia-reperfusion injury is a common cause of AKI, and experimental studies suggest that sex hormones are involved in the regulation of cellular pathways of this injury and may therefore contribute to AKI susceptibility [ 26 , 32 , 33 ]. Furthermore, recently investigated biomarkers of mortality, such as free light chains (FLCs) or serum high mobility group box 1 (HMGB1), may serve as important parameters that reflect inflammation and immune dysfunction in CKD and AKI patients [ 34 , 35 ].…”

Section: Discussionmentioning

confidence: 99%

Association of Sex Differences with Mortality and Organ Dysfunction in Patients with Sepsis and Septic Shock

Mewes

Runzheimer

Böhnke³

et al. 2023

JPM

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Background: Despite recent advances in the clinical management and understanding of sepsis and septic shock, these complex clinical syndromes continue to have high mortality rates. The effect of sex on these diseases’ mortality, clinical presentation and morbidity remains controversial. This study aimed to investigate the association of sex with mortality and organ dysfunction in patients with sepsis and septic shock. Methods: Prospectively enrolled patients with clinically defined sepsis and septic shock in three intensive care units at University Medical Center Göttingen, Germany, were investigated. The primary outcomes were 28- and 90-day mortality, while the secondary endpoints included the evaluation of organ dysfunction as measured by clinical scores and laboratory parameters. Results: A total of 737 septic patients were enrolled, including 373 in septic shock, 484 males, and 253 females. No significant differences in 28- and 90-day mortality were observed in the cohort. However, men with sepsis had significantly higher SOFA scores, SOFA respiratory and renal subscores, bilirubin and creatinine values, and lower weight-adapted urine outputs, indicating higher organ dysfunction compared to women. Conclusions: Our findings revealed notable differences in organ dysfunction between male and female patients, with males exhibiting more pronounced dysfunction across multiple clinical indicators. These results highlight the potential influence of sex on sepsis disease severity and suggest the need for tailored approaches in sepsis management according to patient sex.

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Section: Discussionmentioning

confidence: 99%

Association of Sex Differences with Mortality and Organ Dysfunction in Patients with Sepsis and Septic Shock

Mewes

Runzheimer

Böhnke³

et al. 2023

JPM

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“…Furthermore, hormonal changes resulting from comorbidities such as diabetes contribute to the loss of lean body mass [ 48 ]. The process of PEW is both complex and dynamic, requiring multiple strategies of nutritional, medical and lifestyle intervention [ 10 , 45–47 ]. As improvements in dialysis treatment (such as improved filtration and biocompatibility of medical materials) continue to evolve, dynamic methods to assess their application are increasingly appropriate [ 44–47 ] For providers to accurately assess REE, and its changes over time would provide a powerful tool in monitoring the ongoing need and effectiveness of such interventional strategies.…”

Section: Discussionmentioning

confidence: 99%

Machine learning models using non-linear techniques improve the prediction of resting energy expenditure in individuals receiving hemodialysis

et al. 2023

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Purpose Approximately 700,000 people in the USA have chronic kidney disease requiring dialysis. Protein-energy wasting (PEW), a condition of advanced catabolism, contributes to three-year survival rates of 50%. PEW occurs at all levels of Body Mass Index (BMI) but is devastating for those people at the extremes. Treatment for PEW depends on an accurate understanding of energy expenditure. Previous research established that current methods of identifying PEW and assessing adequate treatments are imprecise. This includes disease-specific equations for estimated resting energy expenditure (eREE). In this study, we applied machine learning (ML) modelling techniques to a clinical database of dialysis patients. We assessed the precision of the ML algorithms relative to the best-performing traditional equation, the MHDE. Methods This was a secondary analysis of the Rutgers Nutrition and Kidney Database. To build the ML models we divided the population into test and validation sets. Eleven ML models were run and optimized, with the best three selected by the lowest root mean squared error (RMSE) from measured REE. Values for eREE were generated for each ML model and for the MHDE. We compared precision using Bland-Altman plots. Results Individuals were 41.4% female and 82.0% African American. The mean age was 56.4 ± 11.1 years, and the median BMI was 28.8 (IQR = 24.8 − 34.0) kg/m 2 . The best ML models were SVR, Linear Regression and Elastic net with RMSE of 103.6 kcal, 119.0 kcal and 121.1 kcal respectively. The SVR demonstrated the greatest precision, with 91.2% of values falling within acceptable limits. This compared to 47.1% for the MHDE. The models using non-linear techniques were precise across extremes of BMI. Conclusion ML improves precision in calculating eREE for dialysis patients, including those most vulnerable for PEW. Further development for clinical use is a priority.

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“…Both impairment and activation pathways are shown to be involved in immune natural cells in hemodialysis (HD) patients that also have active infections. These studies reported a need for a discrete method for measuring adaptive immune system dysregulation and identifying a distinct inflammatory endotype that reflects reduced defense mechanisms such as phagocytic capabilities or the impairment of the antigen presentation function [ 43 , 44 ]. This distinct immune dysfunction profile was observed in our cohort of patients who were critically ill with severe COVID-19: when compared to the sepsis and septic shock patients, the patients with COVID-19 demonstrated a weakened CD4 T cell response and a reduction in the naïve cell response after CRRT.…”

Section: Methodsmentioning

confidence: 99%

Parallel Dysregulated Immune Response in Severe Forms of COVID-19 and Bacterial Sepsis via Single-Cell Transcriptome Sequencing

et al. 2023

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Critically ill COVID-19 patients start developing single respiratory organ failure that often evolves into multiorgan failure. Understanding the immune mechanisms in severe forms of an infectious disease (either critical COVID-19 or bacterial septic shock) would help to achieve a better understanding of the patient’s clinical trajectories and the success of potential therapies. We hypothesized that a dysregulated immune response manifested by the abnormal activation of innate and adaptive immunity might be present depending on the severity of the clinical presentation in both COVID-19 and bacterial sepsis. We found that critically ill COVID-19 patients demonstrated a different clinical endotype that resulted in an inflammatory dysregulation in mild forms of the disease. Mild cases (COVID-19 and bacterial non severe sepsis) showed significant differences in the expression levels of CD8 naïve T cells, CD4 naïve T cells, and CD4 memory T cells. On the other hand, in the severe forms of infection (critical COVID-19 and bacterial septic shock), patients shared immune patterns with upregulated single-cell transcriptome sequencing at the following levels: B cells, monocyte classical, CD4 and CD8 naïve T cells, and natural killers. In conclusion, we identified significant gene expression differences according to the etiology of the infection (COVID-19 or bacterial sepsis) in the mild forms; however, in the severe forms (critical COVID-19 and bacterial septic shock), patients tended to share some of the same immune profiles related to adaptive and innate immune response. Severe forms of the infections were similar independent of the etiology. Our findings might promote the implementation of co-adjuvant therapies and interventions to avoid the development of severe forms of disease that are associated with high mortality rates worldwide.

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Free Light Chains, High Mobility Group Box 1, and Mortality in Hemodialysis Patients

Cited by 5 publications

References 53 publications

Association of Sex Differences with Mortality and Organ Dysfunction in Patients with Sepsis and Septic Shock

Association of Sex Differences with Mortality and Organ Dysfunction in Patients with Sepsis and Septic Shock

Machine learning models using non-linear techniques improve the prediction of resting energy expenditure in individuals receiving hemodialysis

Parallel Dysregulated Immune Response in Severe Forms of COVID-19 and Bacterial Sepsis via Single-Cell Transcriptome Sequencing

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