CKD, also known as chronic kidney disease, or colloquially known as “kidney disease” is a condition in which the kidneys are damaged and cannot filter blood[1]. As a results, fluid and waste from blood remain in the body for longer than they should and can lead to other illnesses such as heart disease. According to the CDC, every 24 hours 360 people begin dialysis treatment for kidney failure[2] , or for every 1 hour, 15 people go on dialysis. Additionally, it is a leading cause of death in the United States, costing Medicare beneficiaries $87.2 billion dollars[3] . More than 1 in 7 (37 million) US adults are estimated to have CKD[4].
There are 5 stages of CKD, each one being worse than the last[5]. Each stage is characterized by eGFR (estimated glomerular filtration rate) and an additional marker, such as proteinuria and/or hematuria.[6] A nephrologist will typically order a series of blood and urine tests in order to assess kidney function. Common measures include but are not limited to: creatinine, eGFR, and blood urea nitrogen (BUN)[7]. There are many factors that can impact risk of CKD, such as creatinine levels, sex, and blood pressure level. Blood pressure especially, as kidney disease is closely associated with high blood pressure[8]. Also, creatinine is a waste product that is solely handled and filtered out by the kidneys[9]. A high creatinine concentration in the blood indicates that there is an issue in the kidneys[10]. There is a question of whether there is an observable difference in the effect between sex and baseline diastolic blood pressure in across sex between men and women.
Is there an observable difference in baseline creatinine levels and blood pressure between sexes?
In conclusion, there is a difference in baseline creatinine across sexes, and it is statistically significant. On average, women were over 20 µmol/L lower compared to men. This is consistent with literature that says that creatinine tends to be higher in men than in women.
There was no effect of blood pressure on serum creatinine. This could suggest that there are other factors at play not accounted for in the model.