Serum Osmolarity and Vasopressin Concentration in Acute Heart Failure-Influence on Clinical Course and Outcome

Spot urine sodium-to-creatinine ratio surpasses sodium in identifying poor diuretic response in acute heart failure

AIMS

We aim to identify the most accurate marker for early prediction of poor diuretic response in acute heart failure (AHF) patients with signs of congestion requiring intravenous diuretic treatment.

METHODS

In this single-centre, prospective observational study, AHF patients with signs of congestion received a standardized intravenous furosemide dose (1 mg/kg of body weight; 40 mg in bolus and remaining dose in 2 h continuous infusion). Subsequently, we assessed spot urine composition at 2 h post-administration, comparing it with total urine output at 6 h. Various potential urine markers were analysed for predicting urine output using receiver operating characteristic (ROC) curves and logistic regression models. We investigated guideline-recommended markers, including spot urine sodium (UNa+) and its cut-off, and introduced the UNa+/UCr (urine creatinine concentration) ratio adjusting UNa+ for urine dilution.

RESULTS

Out of 111 patients (85% males, 66.4 ± 13.9 years old, NTproBNP 7290 [4493-14 582] pg/ml), there were 18 (16%) with a poor diuretic response (cumulative urine output <600 ml during the first 6 h). The mean 6 h cumulative diuresis in patients with poor and good diuretic response was 406 ± 142 and 2114 ± 1164 ml, respectively, P < 0.005. After an initial evaluation of several potential biomarkers, only UNa+, UCr and UNa+/UCr were selected as candidates with the highest predictive value. The cut-off for UNa+ adjusted for urine dilution: UNa+/UCr ratio <0.167 mmol/mg × 10-1 was determined by ROC analysis with the highest area under the curve (95% confidence interval): 0.956 (0.915-0.997), P < 0.001. When compared with the guideline-recommended cut-off (UNa+ <50 mmol/L as a reference, specificity-0.97; sensitivity-0.83), the odds ratio (OR) for UNa+/UCreat to identify a poor diuretic response was 2.5 times greater, regardless of kidney function (OR for estimated glomerular filtration rate in the logistic regression model was 0.978 [0.945-1.013, P = 0.222]).

CONCLUSIONS

The UNa+/UCr ratio in a spot urine sample 2 h after intravenous diuretic administration is a simple, highly predictive marker for the identification of AHF patients with poor diuretic response, surpassing guidelines-recommended markers like UNa+.

The U-shaped association between serum osmolality and 28-day mortality in patients with sepsis: a retrospective cohort study

BACKGROUND

Sepsis is a recognized global health challenge that places a considerable disease burden on countries. Although there has been some progress in the study of sepsis, the mortality rate of sepsis remains high. The relationship between serum osmolality and the prognosis of patients with sepsis is unclear.

METHOD

Patients with sepsis who met the criteria in the Medical Information Mart for Intensive Care IV database were included in the study. Hazard ratios (HRs) and 95% confidence intervals (CIs) were determined using multivariable Cox regression. The relationship between serum osmolality and the 28-day mortality risk in patients with sepsis was investigated using curve fitting, and inflection points were calculated.

RESULTS

A total of 13,219 patients with sepsis were enrolled in the study; the mean age was 65.1 years, 56.9 % were male, and the 28-day mortality rate was 18.8 %. After adjusting for covariates, the risk of 28-day mortality was elevated by 99% (HR 1.99, 95%CI 1.74-2.28) in the highest quintile of serum osmolality (Q5 >303.21) and by 59% (HR 1.59, 95%CI 1.39-1.83) in the lowest quintile (Q1 ≤285.80), as compared to the reference quintile (Q3 291.38-296.29). The results of the curve fitting showed a U-shaped relationship between serum osmolality and the risk of 28-day mortality, with an inflection point of 286.9 mmol/L.

CONCLUSION

There is a U-shaped relationship between serum osmolality and the 28-day mortality risk in patients with sepsis. Higher or lower serum osmolality is associated with an increased risk of mortality in patients with sepsis. Patients with sepsis have a lower risk of mortality when their osmolality is 285.80-296.29 mmol/L.

Renal Assessment in Acute Cardiorenal Syndrome

Cardiorenal syndrome (CRS) is a complex, heterogeneous spectrum of symptoms that has kept cardiologists awake for decades. The heart failure (HF) population being burdened with multimorbidity poses diagnostic and therapeutic challenges even for experienced clinicians. Adding deteriorated renal function to the equation, which is one of the strongest predictors of adverse outcome, we measure ourselves against possibly the biggest problem in modern cardiology. With the rapid development of new renal assessment methods, we can treat CRS more effectively than ever. The presented review focuses on explaining the pathophysiology, recent advances and current practices of monitoring renal function in patients with acute CRS. Understanding the dynamic interaction between the heart and the kidney may improve patient care and support the selection of an effective and nephroprotective treatment strategy.

Machine Learning Approach to Understand Worsening Renal Function in Acute Heart Failure

Acute heart failure (AHF) is a common and severe condition with a poor prognosis. Its course is often complicated by worsening renal function (WRF), exacerbating the outcome. The population of AHF patients experiencing WRF is heterogenous, and some novel possibilities for its analysis have recently emerged. Clustering is a machine learning (ML) technique that divides the population into distinct subgroups based on the similarity of cases (patients). Given that, we decided to use clustering to find subgroups inside the AHF population that differ in terms of WRF occurrence. We evaluated data from the three hundred and twelve AHF patients hospitalized in our institution who had creatinine assessed four times during hospitalization. Eighty-six variables evaluated at admission were included in the analysis. The k-medoids algorithm was used for clustering, and the quality of the procedure was judged by the Davies–Bouldin index. Three clinically and prognostically different clusters were distinguished. The groups had significantly (p = 0.004) different incidences of WRF. Inside the AHF population, we successfully discovered that three groups varied in renal prognosis. Our results provide novel insight into the AHF and WRF interplay and can be valuable for future trial construction and more tailored treatment.