High Serum Phosphate Level as a Risk Factor to Determine Renal Prognosis in Autosomal Dominant Polycystic Kidney Disease: A Retrospective Study

Factors associated with early-onset intracranial aneurysms in patients with autosomal dominant polycystic kidney disease

BACKGROUND

Recently, the importance of attribute-based medicine has been emphasized. The effects of early-onset intracranial aneurysms on patients can be significant and long-lasting. Herein, we compared the factors associated with intracranial aneurysms in patients with autosomal dominant polycystic kidney disease (ADPKD) according to age categories (≥ 50 years, < 50 years).

METHODS

We included 519 ADPKD patients, with a median age of 44 years, estimated glomerular filtration rate of 54.5 mL/min/1.73 m2, and total follow-up duration of 3104 patient-years. Logistic regression analyses were performed to determine factors associated with intracranial aneurysms.

RESULTS

Regarding the presence of intracranial aneurysm, significant interactions were identified between the age category (age ≥ 50 years), female sex (P = 0.0027 for the interaction) and hypertension (P = 0.0074 for the interaction). Female sex and hypertension were associated with intracranial aneurysm risk factors only in patients aged ≥ 50 years. The presence of intracranial aneurysm was significantly associated with chronic kidney disease (CKD) stages 4-5 (odds ratio [OR] = 3.87, P = 0.0007) and family history of intracranial aneurysm or subarachnoid hemorrhage (OR = 2.30, P = 0.0217) in patients aged < 50 years. For patients aged ≥ 50 years, in addition to the abovementioned factors [OR = 2.38, P = 0.0355 for CKD stages 4-5; OR = 3.49, P = 0.0094 for family history of intracranial aneurysm or subarachnoid hemorrhage], female sex (OR = 4.51, P = 0.0005), and hypertension (OR = 5.89, P = 0.0012) were also associated with intracranial aneurysm.

CONCLUSION

Kidney dysfunction and family history of intracranial aneurysm or subarachnoid hemorrhage are risk factors for early-onset intracranial aneurysm. Patients aged < 50 years with a family history of intracranial aneurysm or subarachnoid hemorrhage or with CKD stages 4-5 may be at an increased risk of early-onset intracranial aneurysm.

Visceral fat and attribute-based medicine in chronic kidney disease

Visceral adipose tissue plays a central role in obesity and metabolic syndrome and is an independent risk factor for both cardiovascular and metabolic disorders. Increased visceral adipose tissue promotes adipokine dysregulation and insulin resistance, leading to several health issues, including systemic inflammation, oxidative stress, and activation of the renin-angiotensin-aldosterone system. Moreover, an increase in adipose tissue directly and indirectly affects the kidneys by increasing renal sodium reabsorption, causing glomerular hyperfiltration and hypertrophy, which leads to increased proteinuria and kidney fibrosis/dysfunction. Although the interest in the adverse effects of obesity on renal diseases has grown exponentially in recent years, the relationship between obesity and renal prognosis remains controversial. This may be attributed to the long clinical course of obesity, numerous obesity-related metabolic complications, and patients' attributes. Multiple individual attributes influencing the pathophysiology of fat accumulation make it difficult to understand obesity. In such cases, it may be effective to elucidate the pathophysiology by conducting research tailored to individual attributes from the perspective of attribute-based medicine/personalized medicine. We consider the appropriate use of clinical indicators necessary, according to attributes such as chronic kidney disease stage, level of visceral adipose tissue accumulation, age, and sex. Selecting treatments and clinical indicators based on individual attributes will allow for advancements in the clinical management of patients with obesity and chronic kidney disease. In the clinical setting of obesity-related nephropathy, it is first necessary to accumulate attribute-based studies resulting from the accurate evaluation of visceral fat accumulation to establish evidence for promoting personalized medicine.

Associations between Phosphate Concentrations and Hospital Mortality in Critically Ill Patients Receiving Mechanical Ventilation

Phosphate concentrations change continuously throughout hospitalization; however, it is unclear which available phosphate measures are most clinically important for predicting hospital mortality. Therefore, we investigated phosphate concentrations in association with hospital mortality following admission to the intensive care unit. We retrospectively enrolled all adult patients receiving mechanical ventilation. Phosphate concentrations were divided into three categories: initially measured phosphate (iP); maximum−minimum phosphate values (ΔP); and phosphate arithmetic average (Pmean). In total, 175 patients were enrolled. The hospital mortality rate was 32.6%, and the most common primary diagnosis was respiratory failure. In multivariable logistic regression analyses, the odds ratios for hospital mortality in association with ΔP and Pmean values were 1.56 and 2.13, respectively (p < 0.0001). According to the obtained receiver operating characteristic curve, ΔP (0.75) and Pmean (0.72) each showed a fair predictive power for hospital mortality. In evaluating relative risks, we found that higher concentrations of Pmean and ΔP were each associated with a higher hospital mortality. ΔP and Pmean values were significantly associated with hospital mortality in critically ill patients, compared to iP. These findings showed that throughout hospitalization, it is important to reduce phosphate level fluctuations and maintain appropriate phosphate concentrations through consistent monitoring and corrections.

Development of a Biomarker Panel to Distinguish Risk of Progressive Chronic Kidney Disease

Chronic kidney disease (CKD) patients typically progress to kidney failure, but the rate of progression differs per patient or may not occur at all. Current CKD screening methods are sub-optimal at predicting progressive kidney function decline. This investigation develops a model for predicting progressive CKD based on a panel of biomarkers representing the pathophysiological processes of CKD, kidney function, and common CKD comorbidities. Two patient cohorts are utilised: The CKD Queensland Registry (n = 418), termed the Biomarker Discovery cohort; and the CKD Biobank (n = 62), termed the Predictive Model cohort. Progression status is assigned with a composite outcome of a ≥30% decline in eGFR from baseline, initiation of dialysis, or kidney transplantation. Baseline biomarker measurements are compared between progressive and non-progressive patients via logistic regression. In the Biomarker Discovery cohort, 13 biomarkers differed significantly between progressive and non-progressive patients, while 10 differed in the Predictive Model cohort. From this, a predictive model, based on a biomarker panel of serum creatinine, osteopontin, tryptase, urea, and eGFR, was calculated via linear discriminant analysis. This model has an accuracy of 84.3% when predicting future progressive CKD at baseline, greater than eGFR (66.1%), sCr (67.7%), albuminuria (53.2%), or albumin-creatinine ratio (53.2%).