Predialysis serum lactate levels could predict dialysis withdrawal in Type 1 cardiorenal syndrome patients

L-shaped association between lean body mass to visceral fat mass ratio with hyperuricemia: a cross-sectional study

BACKGROUND

Insufficient attention has been given to examining the correlation between body composition and hyperuricemia, leading to inconsistent findings. The primary objective of this research is to explore the association between lean body mass index (LMI), visceral fat mass index (VFMI), and hyperuricemia. A specific emphasis will be placed on assessing the link between the ratio of lean body mass to visceral fat mass (LMI/VFMI) and hyperuricemia.

METHODS

The present study employed a cross-sectional design and involved a total of 9,646 individuals who participated in the National Health and Nutrition Examination Survey (NHANES). To explore the associations among the variables, logistic and linear regressions were employed. Additionally, subgroup analyses and sensitivity analyses were conducted based on various characteristics.

RESULTS

The results showed that LMI was positively associated with hyperuricemia (for Per-SD: OR = 1.88, 95%CI: 1.75, 2.01; for quartiles [Q4:Q1]: OR = 5.37, 95%CI: 4.31, 6.69). Meanwhile, VFMI showed a positive association with hyperuricemia (for Per-SD: OR = 2.02, 95%CI: 1.88, 2.16; for quartiles [Q4:Q1]: OR =8.37, 95%CI: 6.70, 10.47). When considering the effects of In LMI/VFMI, an L-shaped negative association with hyperuricemia was observed (for Per-SD: OR = 0.45, 95%CI: 0.42, 0.49; for quartiles [Q4:Q1]: OR = 0.16, 95%CI: 0.13, 0.20). Subgroup and sensitivity analyses demonstrated the robustness of this association across different subgroups. Additionally, the segmented regression analysis indicated a saturation effect of 5.64 for the In LMI/VFMI with hyperuricemia (OR = 0.20, 95%CI: 0.17, 0.24). For every 2.72-fold increase of In LMI/VFMI, the risk of hyperuricemia was reduced by 80%.

CONCLUSION

The LMI/VFMI ratio is non-linearly associated with serum uric acid. Whether this association is causal needs to be confirmed in further longitudinal studies or Mendelian randomization.

Unsupervised clustering identifies sub-phenotypes and reveals novel outcome predictors in patients with dialysis-requiring sepsis-associated acute kidney injury

INTRODUCTION

Heterogeneity exists in sepsis-associated acute kidney injury (SA-AKI). This study aimed to perform unsupervised consensus clustering in critically ill patients with dialysis-requiring SA-AKI.

PATIENTS AND METHODS

This prospective observational cohort study included all septic patients, defined by the Sepsis-3 criteria, with dialysis-requiring SA-AKI in surgical intensive care units in Taiwan between 2009 and 2018. We employed unsupervised consensus clustering based on 23 clinical variables upon initializing renal replacement therapy. Multivariate-adjusted Cox regression models and Fine-Gray sub-distribution hazard models were built to test associations between cluster memberships with mortality and being free of dialysis at 90 days after hospital discharge, respectively.

RESULTS

Consensus clustering among 999 enrolled patients identified three sub-phenotypes characterized with distinct clinical manifestations upon renal replacement therapy initiation (n = 352, 396 and 251 in cluster 1, 2 and 3, respectively). They were followed for a median of 48 (interquartile range 9.5-128.5) days. Phenotypic cluster 1, featured by younger age, lower Charlson Comorbidity Index, higher baseline estimated glomerular filtration rate but with higher severity of acute illness was associated with an increased risk of death (adjusted hazard ratio of 3.05 [95% CI, 2.35-3.97]) and less probability to become free of dialysis (adjusted sub-distribution hazard ratio of 0.55 [95% CI, 0.38-0.8]) than cluster 3. By examining distinct features of the sub-phenotypes, we discovered that pre-dialysis hyperlactatemia ≥3.3 mmol/L was an independent outcome predictor. A clinical model developed to determine high-risk sub-phenotype 1 in this cohort (C-static 0.99) can identify a sub-phenotype with high in-hospital mortality risk (adjusted hazard ratio of 1.48 [95% CI, 1.25-1.74]) in another independent multi-centre SA-AKI cohort.

CONCLUSIONS

Our data-driven approach suggests sub-phenotypes with clinical relevance in dialysis-requiring SA-AKI and serves an outcome predictor. This strategy represents further development toward precision medicine in the definition of high-risk sub-phenotype in patients with SA-AKI.Key messagesUnsupervised consensus clustering can identify sub-phenotypes of patients with SA-AKI and provide a risk prediction.Examining the features of patient heterogeneity contributes to the discovery of serum lactate levels ≥ 3.3 mmol/L upon initializing RRT as an independent outcome predictor.This data-driven approach can be useful for prognostication and lead to a better understanding of therapeutic strategies in heterogeneous clinical syndromes.

Risk factors and 180-day mortality of acute kidney disease in critically ill patients: A multi-institutional study

Background

Critically ill patients with acute kidney injury (AKI) have a poor prognosis. Recently, the Acute Disease Quality Initiative (ADQI) proposed to define acute kidney disease (AKD) as acute or subacute damage and/or loss of kidney function post AKI. We aimed to identify the risk factors for the occurrence of AKD and to determine the predictive value of AKD for 180-day mortality in critically ill patients.

Methods

We evaluated 11,045 AKI survivors and 5,178 AKD patients without AKI, who were admitted to the intensive care unit between 1 January 2001 and 31 May 2018, from the Chang Gung Research Database in Taiwan. The primary and secondary outcomes were the occurrence of AKD and 180-day mortality.

Results

The incidence rate of AKD among AKI patients who did not receive dialysis or died within 90 days was 34.4% (3,797 of 11,045 patients). Multivariable logistic regression analysis indicated that AKI severity, underlying early CKD, chronic liver disease, malignancy, and use of emergency hemodialysis were independent risk factors of AKD, while male gender, higher lactate levels, use of ECMO, and admission to surgical ICU were negatively correlated with AKD. 180-day mortality was highest among AKD patients without AKI during hospitalization (4.4%, 227 of 5,178 patients), followed by AKI with AKD (2.3%, 88 of 3,797 patients) and AKI without AKD (1.6%, 115 of 7,133 patients). AKI with AKD had a borderline significantly increased risk of 180-day mortality (aOR 1.34, 95% CI 1.00-1.78; p = 0.047), while patients with AKD but no preceding AKI episodes had the highest risk (aOR 2.25, 95% CI 1.71-2.97; p < 0.001).

Conclusion

The occurrence of AKD adds limited additional prognostic information for risk stratification of survivors among critically ill patients with AKI but could predict prognosis in survivors without prior AKI.

Circulating Fibroblast Growth Factor-23 Levels Can Predict Rapid Kidney Function Decline in a Healthy Population: A Community-Based Study

BACKGROUND

Fibroblast growth factor-23 (FGF-23) associates with decreased kidney function in patients with chronic kidney disease (CKD). However, the correlation between circulating FGF-23 levels and the rate of renal function decline in healthy individuals is largely unknown. We aimed to evaluate the predictive performance of FGF-23 for rapid kidney function decline (RKFD) in a community-based study.

METHODS

A total of 2963 people residing in northern Taiwan were enrolled from August 2013 to May 2018 for an annual assessment of kidney function for five years. The baseline estimated glomerular filtration rates (eGFR) were calculated using the 2009 and 2021 Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation, which aggregates the values of serum creatinine and cystatin C (eGFRcr-cys). The outcome was RKFD-a 15% decrease in estimated glomerular filtration rate (eGFR) within the first four years, and a reduction in eGFR without improvement in the 5th year. A generalized additive model (GAM) was used to determine the cut-off value of FGF-23 to predict RKFD.

RESULTS

The incidence of RKFD was 18.0% (114/634). After matching for age and sex at a 1:1 ratio, a total of 220 subjects were analyzed. eGFRcr-cys was negatively correlated with total vitamin D level but seemed irrelevant to FGF-23. Multivariable logistic regression analysis showed that FGF-23, eGFRcr-cys, and urine albumin-to-creatinine ratio (UACR) were independent predictors of the possibility of RKFD. FGF-23 showed the best predictive performance for RKFD (AUROC: 0.803), followed by baseline eGFRcr-cys (AUROC: 0.639) and UACR (AUROC: 0.591). From the GAM, 32 pg/mL was the most appropriate cut-off value of FGF-23 with which to predict RKFD. The subgroup and sensitivity analyses showed consistent results that high-FGF-23 subjects had higher risks of RKFD.

CONCLUSIONS

Circulating FGF-23 level could be a helpful predictor for RKFD in this community-based population.

Serum Cystatin C Levels Could Predict Rapid Kidney Function Decline in A Community-Based Population

BACKGROUND

Several biomarkers have been correlated with the prevalence and severity of chronic kidney disease (CKD); however, the association between biomarkers and rapid kidney function decline (RKFD) is unknown. This study aimed to evaluate the predictive performance of biomarkers to determine who is likely to develop RKFD in a healthy population.

METHODS

A community-based cohort of 2608 people residing in northern Taiwan were enrolled, and their renal function was followed annually from January 2014 to December 2019. The outcomes of interest were RKFD, defined as a 15% decrease in the estimated glomerular filtration rate (eGFR) within the first 4 years, and a decrease in eGFR without improvement in the fifth year. Clinical variables and potential predictors of RKFD, namely adiponectin, leptin, tumor necrosis factor-alpha, and cystatin C, were measured and analyzed.

RESULTS

The incidence of RKFD was 17.0% (105/619). After matching for age and sex at a 1:1 ratio, a total of 200 subjects were included for analysis. The levels of cystatin C and total vitamin D were significantly negatively correlated with eGFR. eGFR was negatively correlated with the levels of cystatin C and total vitamin D. Among the biomarkers, cystatin C showed the best predictive performance for RKFD (area under the receiver operating characteristic curve: 0.789). Lower serum cystatin C was associated with a higher rate of RKFD in healthy subjects. A generalized additive model showed that 0.82 mg/L was an adequate cut-off value of cystatin C to predict RKFD. Multivariable logistic regression analysis further indicated that low cystatin C and eGFR were independent predictors of the possibility of RKFD.

CONCLUSIONS

Serum cystatin C level could predict the possibility of RKFD. We suggest that a low cystatin C level should be considered as a risk factor for RKFD in healthy subjects.