The Good, the Bad, and the Serum Creatinine: Exploring the Effect of Muscle Mass and Nutrition

Abstract

Muscle wasting (sarcopenia) is one of the hallmarks of critical illness. Patients admitted to intensive care unit develop sarcopenia through increased protein catabolism, a decrease in protein syntheses, or both. Among the factors known to promote wasting are chronic inflammation and cytokine imbalance, insulin resistance, hypermetabolism, and malnutrition. Moreover, muscle wasting, known to develop in chronic kidney disease patients, is a harmful consequence of numerous complications associated with deteriorated renal function. Plenty of published data suggest that serum creatinine (SCr) reflects increased kidney damage and is also related to body weight. Based on the concept that urea and creatinine are nitrogenous end products of metabolism, the urea:creatinine ratio (UCR) could be applied but with limited clinical usability in case of kidney damage, hypovolemia, excessive, or protein intake, where UCR can be high and independent of catabolism. Recent data suggest that the sarcopenia index should be considered an alternative to serum creatinine. It is more reliable in estimating muscle mass than SCr. However, the optimal biomarker of catabolism is still an unresolved issue. The SCr is not a promising biomarker for renal function and muscle mass based on the influence of several factors. The present review highlights recent findings on the limits of SCr as a surrogate marker of renal function and the assessment modalities of nutritional status and muscle mass measurements.

Development of interpretable machine learning models for prediction of acute kidney injury after noncardiac surgery: a retrospective cohort study

“…An elevated serum creatinine level indicates impaired baseline renal function, which increases postoperative AKI risk 28 , 40 . However, serum creatinine levels may underestimate renal function impairment in populations with diminished muscle mass 41 , such as those suffering from sarcopenia or malnutrition. It has been demonstrated that these populations are at an increased risk of AKI 2 , 42 .…”

Modeling Pharmacokinetics in Individual Patients Using Therapeutic Drug Monitoring and Artificial Population Quasi-Models: A Study with Piperacillin

“…Calculation is based on Equation (1): where BW corresponds to body weight in kg, c 1 and c 2 are the first and second serum creatinine concentrations in mg/dL, respectively, P adj is the adjusted creatinine production in mg and CCR is the creatinine clearance in hundreds of mL per minute [ 20 ]. It must be noted that estimating creatinine clearance by measuring serum creatinine is not an optimal approach in the critically ill, as sarcopenia or a poor clinical status influence serum creatinine concentrations [ 31 ]. Furthermore, creatinine is not only filtered, but also secreted by the kidneys [ 32 ].…”

Development and comparison of machine-learning models for predicting prolonged postoperative length of stay in lung cancer patients following video-assisted thoracoscopic surgery

“…Total protein and creatinine have been identified as significant predictive factors for PPOLOS in lung cancer patients, a novel finding given the current scarcity of research on their predictive value in this context. Both creatinine and total protein are critical markers for assessing nutritional status, 36 , 37 with malnutrition known to be associated with increased mortality, compromised functional status, and extended hospital stays. 38 , 39 , 40 Consequently, the significance of preoperative nutritional management for lung cancer patients is increasingly recognized by oncology specialists as a means to enhance postoperative recovery and mitigate complications.…”