Cause of death and influencing factors of chronic renal failure on maintenance hemodialysis

Objective

To investigate the causes of death in patients with chronic renal failure (CRF) on maintenance hemodialysis and its influencing factors.

Methods

This is a retrospective study. A total of 300 patients with chronic renal failure undergoing maintenance hemodialysis who were admitted to the Affiliated Hospital of Hebei University from March 2020 to October 2022 were selected as subjects. Various information of patients were collected. In addition, 80 dead patients in this group were investigated for the cause of death, including cardiovascular and cerebrovascular diseases, infections, multi organ failure, and other causes, and the death-related conditions of cardiovascular and cerebrovascular diseases, such as triglyceridr,,total cholesterol, and in blood lipid levels were analyzed.

Results

Among the 80 dead patients, cardiovascular and cerebrovascular diseases accounted for a higher proportion of death (66%). Univariate Logistic regression analysis showed that advanced age, plasma homocysteine, blood parathyroid hormone, hyperphosphatemia, hypertension, high volume load and left ventricular hypertrophy were risk factors for death in patients with chronic renal failure on maintenance hemodialysis. Multivariate Logistic regression analysis showed that high volume load, left ventricular hypertrophy and anemia were risk factors for death on maintenance hemodialysis. The levels of hemoglobin (HGB) and high-density lipoprotein (HDL) in patients who died of cardiovascular and cerebrovascular diseases were significantly lower than those in the non-cardio-cerebrovascular death group (P=0.00), and the levels of serum phosphorus, TG and TC were significantly higher than those in the non-cardio-cerebrovascular death group (P, P=0.00; TG, P=0.02; TC, P=0.01).

Conclusion

Cardiovascular and cerebrovascular diseases are the leading cause of death in patients with chronic renal failure on maintenance hemodialysis. Adequate dialysis and normal hemoglobin levels are favorable protective factors.

Use machine learning to help identify possible sarcopenia cases in maintenance hemodialysis patients

BACKGROUND

Maintenance hemodialysis (MHD) patients often suffer from sarcopenia, which is strongly associated with their long-term mortality. The diagnosis and treatment of sarcopenia, especially possible sarcopenia for MHD patients are of great importance. This study aims to use machine learning and medical data to develop two simple sarcopenia identification assistant tools for MHD patients and focuses on sex specificity.

METHODS

Data were retrospectively collected from patients undergoing MHD and included patients' basic information, body measurement results and laboratory findings. The 2019 consensus update by Asian working group for sarcopenia was used to assess whether a MHD patient had sarcopenia. Finally, 140 male (58 with possible sarcopenia or sarcopenia) and 102 female (65 with possible sarcopenia or sarcopenia) patients' data were collected. Participants were divided into sarcopenia and control groups for each sex to develop binary classifiers. After statistical analysis and feature selection, stratified shuffle split and Synthetic Minority Oversampling Technique were conducted and voting classifiers were developed.

RESULTS

After eliminating handgrip strength, 6-m walk, and skeletal muscle index, the best three features for sarcopenia identification of male patients are age, fasting blood glucose, and parathyroid hormone. Meanwhile, age, arm without vascular access, total bilirubin, and post-dialysis creatinine are the best four features for females. After abandoning models with overfitting or bad performance, voting classifiers achieved good sarcopenia classification performance for both sexes (For males: sensitivity: 77.50% ± 11.21%, specificity: 83.13% ± 9.70%, F1 score: 77.32% ± 5.36%, the area under the receiver operating characteristic curves (AUC): 87.40% ± 4.41%. For females: sensitivity: 76.15% ± 13.95%, specificity: 71.25% ± 15.86%, F1 score: 78.04% ± 8.85%, AUC: 77.69% ± 7.92%).

CONCLUSIONS

Two simple sex-specific sarcopenia identification tools for MHD patients were developed. They performed well on the case finding of sarcopenia, especially possible sarcopenia.

Advanced Glycation End Products and Inflammatory Cytokine Profiles in Maintenance Hemodialysis Patients After the Ingestion of a Protein-Dense Meal

OBJECTIVE

The goal of this investigation was to evaluate circulating and skeletal muscle inflammatory biomarkers between maintenance hemodialysis (MHD) and demographic-matched control subjects (CON) before and after ingestion of a protein-rich meal.

DESIGN AND METHODS

CON (n = 8; 50 ± 2 years; 31 ± 1 kg/m2) and MHD patients (n = 8; 56 ± 5 years; 32 ± 2 kg/m2) underwent a basal blood draw and muscle biopsy and serial blood draws after the ingestion of a mixed meal on a nondialysis day. Plasma advanced glycation end products (AGEs) and markers of oxidation were assessed via liquid chromatography-tandem mass spectrometry before and after the meal (+240 min). Circulating inflammatory cytokines and soluble receptors for AGE (sRAGE) isoforms (endogenous secretory RAGEs and cleaved RAGEs) were determined before and after the meal (+240 min). Basal muscle was probed for inflammatory cytokines and protein expression of related signaling components (RAGE, Toll-like receptor 4, oligosaccharyltransferase subunit 48, TIR-domain-containing adapter-inducing interferon-β, total IκBα, and pIκBα).

RESULTS

Basal circulating AGEs were 7- to 343-fold higher (P < .001) in MHD than those in CON, but only MG-H1 increased in CON after the meal (P < .001). There was a group effect (MHD > CON) for total sRAGEs (P = .02) and endogenous secretory RAGEs (P < .001) and a trend for cleaved RAGEs (P=.09), with no meal effect. In addition, there was a group effect (MHD < CON; P < .05) for circulating fractalkine, interleukin (IL)10, IL17A, and IL1β and a trend (P < .10) for IL6 and macrophage inflammatory protein 1 alpha, whereas tumor necrosis factor alpha was higher in MHD (P < .001). In muscle, Toll-like receptor 4 (P = .03), TIR-domain-containing adapter-inducing interferon-β (P = .002), and oligosaccharyltransferase subunit 48 (P = .02) expression was lower in MHD than that in CON, whereas IL6 was higher (P = .01) and IL8 (P = .08) tended to be higher in MHD.

CONCLUSION

Overall, MHD exhibited an exaggerated, circulating, and skeletal muscle inflammatory biomarker environment, and the meal did not appreciably affect the inflammatory status.

Long-term impacts of hemodialysis on the right ventricle: Assessment via 3-dimensional speckle-tracking echocardiography

BACKGROUND

Right ventricular (RV) dysfunction is a major cause of death in patients undergoing maintenance hemodialysis (MHD). We used 3-dimensional speckle-tracking echocardiography (3DSTE) to evaluate long-term impacts of MHD on RV function.

HYPOTHESIS

In this study, RV dysfunction in MHD patients will be revealed and studied in depth by 3DSTE.

METHODS

Echocardiography was performed on 110 consecutively enrolled individuals: 30 controls and 80 patients with MHD. Conventional echocardiographic parameters and 3DSTE parameters were obtained and compared between groups. Univariate and multivariate logistic regression analysis identified independent predictors of intradialytic hypotension (IDH).

RESULTS

Compared with the control group, RV end-diastolic volume (RVEDV) was markedly enlarged (46.1 ± 11.8 mL/m² vs 42.3 ± 8.6 mL/m² ; P = 0.047), whereas RV ejection fraction (RVEF) was significantly lower in the MHD group (50.6% ± 5.8% vs 55.2% ± 3.7%; P < 0.001). RV global, septal, and lateral wall longitudinal strains were also decreased in the MHD group (-18.2 ± 3.6 vs -22.6 ± 4.3%; -13.1 ± 3.8 vs -17.5 ± 5.5%; and -23.4 ± 4.7 vs -27.7 ± 4.0%, respectively; all P < 0.001). RVEF (odds ratio [OR]: 0.72, 95% confidence interval [CI]: 0.51 to 1.01, P = 0.038) and history of diabetes (OR: 11.14, 95% CI: 1.16 to 106.71, P = 0.036) were 2 independent predictors of IDH. Ultrafiltration rate was an independent factor associated with RVEF (β = -0.01, 95% CI: -0.019 to 0.001, P = 0.039).

CONCLUSIONS

RVEF by 3DSTE could be an important predictor of IDH in MHD patients, and lower ultrafiltration rate was protective for RVEF. 3DSTE may have potential in RV evaluation and risk stratification in MHD patients.