AIMC Topic: Creatinine

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The impact of paracentesis flow rate in patients with liver cirrhosis on the development of paracentesis induced circulatory dysfunction.

Clinical and molecular hepatology
BACKGROUND/AIMS: Ascites is a dreadful complication of liver cirrhosis associated with short survival. Large volume paracentesis (LVP) is used to treat tense or refractory ascites. Paracentesis induced circulatory dysfunction (PICD) develops if no pl...

Renal impairment and outcome in patients with takotsubo cardiomyopathy.

The American journal of emergency medicine
OBJECTIVES: The objectives were to ascertain the prevalence of renal impairment among patients with a takotsubo cardiomyopathy (TTC) episode and whether clinical outcomes are related to renal function.

Imatinib Increases Serum Creatinine by Inhibiting Its Tubular Secretion in a Reversible Fashion in Chronic Myeloid Leukemia.

Clinical lymphoma, myeloma & leukemia
BACKGROUND: Monitoring renal function is important in imatinib-treated patients with chronic myeloid leukemia because serum creatinine may increase during the course of therapy. The mechanism of this increase and its reversibility on treatment cessat...

RenalGuard system in high-risk patients for contrast-induced acute kidney injury.

American heart journal
BACKGROUND: High urine flow rate (UFR) has been suggested as a target for effective prevention of contrast-induced acute kidney injury (CI-AKI). The RenalGuard therapy (saline infusion plus furosemide controlled by the RenalGuard system) facilitates ...

Abnormal calcium, 25(OH)vitamin D, and parathyroid hormone after biliopancreatic diversion; correction through elongation of the common tract and reduction of the gastric pouch.

Surgery for obesity and related diseases : official journal of the American Society for Bariatric Surgery
BACKGROUND: Biliopancreatic diversion (BPD) is a surgical technique burdened, in some instances, by clinical evidence of malabsorption and intractable diarrhoea.

High-dimensional multiple imputation for partially observed confounders including natural language processing-derived auxiliary covariates.

American journal of epidemiology
Multiple imputation (MI) models can be improved with auxiliary covariates (ACs), but their performance in high-dimensional data remains unclear. We aimed to develop and compare high-dimensional MI (HDMI) methods using structured and natural language ...

Development and validation of multi-center serum creatinine-based models for noninvasive prediction of kidney fibrosis in chronic kidney disease.

Renal failure
OBJECTIVE: Kidney fibrosis is a key pathological feature in the progression of chronic kidney disease (CKD), traditionally diagnosed through invasive kidney biopsy. This study aimed to develop and validate a noninvasive, multi-center predictive model...

Machine learning algorithms for diabetic kidney disease risk predictive model of Chinese patients with type 2 diabetes mellitus.

Renal failure
BACKGROUND: Diabetic kidney disease (DKD) is a common and serious complication of diabetic mellitus (DM). More sensitive methods for early DKD prediction are urgently needed. This study aimed to set up DKD risk prediction models based on machine lear...

Risk prediction for acute kidney disease and adverse outcomes in patients with chronic obstructive pulmonary disease: an interpretable machine learning approach.

Renal failure
BACKGROUND: Little is known about acute kidney injury (AKI) and acute kidney disease (AKD) in patients with chronic obstructive pulmonary disease (COPD) and COPD mortality based on the acute/subacute renal injury. This study develops machine learning...

Machine learning using serial changes in proteinuria during initial steroid therapy to predict treatment response and immunosuppressant use in pediatric idiopathic nephrotic syndrome.

Clinical and experimental nephrology
BACKGROUND: Epidemiological studies on idiopathic nephrotic syndrome (INS) in children have identified no definitive factors predicting steroid-resistant nephrotic syndrome (SRNS) or frequent relapsing nephrotic syndrome. Research using machine learn...