Study setting
The study was conducted in the outpatient clinics and the inpatient wards of the Internal Medicine Department, Alexandria Main University Hospital, which is the tertiary referral hospital for all patients from four governorates (Alexandria, El Beheira, Kafr-El Sheikh, and Marsa Matrouh).
Study design
A cross-sectional study was carried out.
Study population
Adult (18+ years) CKD patients diagnosed in pre-ESRD (i.e., before dialysis or transplantation) were included in the study. Patients < 18 years of age; those who were in stage 5 CKD (ESRD), on dialysis, with previous renal transplantation, and with acute renal injury; and pregnant women were excluded from the study.
Sample size and sampling techniques
The sample size was determined using Epi-info software 7.2.2.6 (CDC, 2018) based on power 80%, with confidence level of 95% and prevalence of using NSAIDs among CKD patients of 65.8% [8]. The minimum required sample size was 340 patients. The sample was rounded to 350 patients. Patients were consecutively included on daily basis from the outpatient clinics and the inpatient wards until the required sample was reached.
Data collection
A predesigned interview questionnaire was used to collect data from the patients about their personal characteristics (sociodemographic characteristics and smoking), history of comorbid diseases, history of selected drugs interacting with NSAIDs (For patients who were illiterate, the researchers had to show them the boxes of the drugs to know which one is taken.), and NSAID use including the type, purpose, pattern, and source of advice. In addition, knowledge about the adverse effects of NSAIDs was determined.
Concerning smoking, patients were classified into never smokers (those who have not smoked 100 cigarettes during their lifetime), current smokers (those who report smoking at least 100 cigarettes in their lifetime and who smoke cigarettes every day or some days), and former smokers (those who has smoked at least 100 cigarettes in their lifetime but does not smoke cigarettes) [9].
Blood pressure, weight, and height were measured, and standardized serum creatinine was collected from the patients’ records.
Regarding weight, patients were classified according to body mass index (BMI) [10] (weight in kilograms/height in meters2) into underweight (< 18.5 kg/m2), normal weight (18.5–24.9 kg/m2), overweight (25–29.9 kg/m2), and obese (≥ 30 kg/m2).
The estimated glomerular filtration rate (eGFR) was calculated by CKD-EPI equation [11]
$$ \mathrm{eGFR}=141\times \min {\left(\mathrm{Scr}/\kappa, 1\right)}^{\alpha}\times \max {\left(\mathrm{Scr}/\kappa, 1\right)}^{-1.209}\times {0.993}^{\mathrm{age}}\times 1.018\left[\mathrm{if}\ \mathrm{female}\right] $$
where Scr is serum creatinine (mg/dl), ĸ is 0.7 for females and 0.9 for males, α is − 0.329 for females and − 0.411 for males, min indicates the minimum of Scr/ĸ or 1, and max indicates the maximum of Scr/ĸ.
CKD was defined according to the 2012 KDIGO guidelines [1] according to the presence of the following criteria for more than 3 months:
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1.
Markers of kidney damage (one or more)
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Albuminuria (AER ≥ 30 mg/24 h; ACR ≥ 30 mg/g [≥ 3 mg/mmol])
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Urine sediment abnormalities
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Electrolyte and other abnormalities due to tubular disorders
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Abnormalities detected by histology
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Structural abnormalities detected by imaging
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History of kidney transplantation
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2.
Decreased GFR (GFR < 60 ml/min/1.73 m2 (GFR categories G3a–G5))
CKD is classified into the following stages:
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G1: normal or high GFR (> 90 ml/min/1.73 m2)
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G2: mild decrease in GFR (60–89 ml/min/1.73 m2)
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G3a: mild to moderate decrease in GFR (45–59 ml/min/1.73 m2)
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G3b: moderate to severe decrease in GFR (30–44 ml/min/1.73 m2)
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G4: severe decrease in GFR (15–29 ml/min/1.73 m2)
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G5: kidney failure (GFR < 15)
We excluded patients in CKD stage 5 as those patients already reached ESRD and so prevention of NSAID use will not add any benefits to the disease progression.
Statistical analysis
Data was summarized using mean ± SD, medians and inter-quartile ranges or frequencies and percentage, as appropriate. Comparison between the variables was done using t test, Mann-Whitney or chi-square according to the data type. Correlation between the renal function and duration of NSAID use was done by Pearson’s correlation. The factors associated with the use of NSAIDs were identified using multiple logistic regression analysis. The model included all variables which were significantly related to NSAID use in bivariate analysis. Results are considered significant when p < 0.05.