Adverse Drug Reactions in Patients with CKD : Clinical Journal of the American Society of Nephrology

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Original Articles: Chronic Kidney Disease

Adverse Drug Reactions in Patients with CKD

Laville, Solène M.1; Gras-Champel, Valérie2; Moragny, Julien2; Metzger, Marie1; Jacquelinet, Christian1,3; Combe, Christian4,5; Fouque, Denis6; Laville, Maurice6; Frimat, Luc7,8; Robinson, Bruce M.9; Stengel, Bénédicte1; Massy, Ziad A.1,10; Liabeuf, Sophie2,11;  on behalf of the Chronic Kidney Disease-Renal Epidemiology and Information Network (CKD-REIN) Study Group

Author Information
CJASN 15(8):p 1090-1102, August 2020. | DOI: 10.2215/CJN.01030120



Despite the highly regulated process of drug marketing authorization, no medicine is completely safe. Adverse drug reactions (ADRs) are relatively common; they cause 2%–7% of overall hospitalizations (1–234). Two French studies (2,5) have reported that 3.2%–3.6% of hospital admissions are related to ADRs. The concept of ADR has evolved over time, and today, it includes any harmful and unwanted reaction to a drug occurring at doses normally used in humans or resulting from drug misuse or error or from accidental or willful overdose (6). Most available studies have focused on ADR-related hospitalizations (with the ADR the cause of admission [2,3,5,7–8910], occurring during hospitalization [11,12], or both [1,13,14]); very few have examined ADRs in outpatient settings (4). Although clinicians recognize ADRs as a major problem in patients with CKD, few studies have investigated the incidence of and factors associated with ADRs in this population.

Drug-related nephrotoxicity is frequent and well documented (15). However, the kidney also plays an important role in the clearance of many drugs and toxic metabolites that can cause ADR due to their accumulation as kidney function declines. Despite impaired pharmacokinetics and pharmacodynamics (16–1718), patients with CKD use multiple medicines and are often exposed to some that are inappropriately prescribed (19). Until now, studies in patients with CKD have been on the basis of self-reported ADRs (20), have concerned specific drugs during clinical trials (21,22), or have been restricted to ADRs during hospitalization (23) or to specific types of ADRs (24). None of the studies reported therapeutic management after the ADR. No comprehensive evaluation exists of the incidence, probability of causation, and preventability of ADRs in both inpatients and outpatients belonging to this population.

The primary objective of this study was to estimate the incidence rates of overall and serious ADRs according to eGFR in patients with moderate or advanced CKD treated by a nephrologist. Secondary objectives aimed at assessing their causation, preventability, associated factors, and immediate therapeutic management.

Materials and Methods

Study Design and Participants

The Chronic Kidney Disease-Renal Epidemiology and Information Network (CKD-REIN) is a prospective cohort study conducted in 40 nationally representative nephrology outpatient facilities in France. Eligible patients were at least 18 years of age, had a confirmed diagnosis of moderate or advanced CKD, had an eGFR<60 ml/min per 1.73 m2, were not on dialysis, and had not been transplanted. From July 2013 to March 2016, CKD-REIN included 3033 patients. Details of the study protocol and flow chart have been published elsewhere (25). The institutional review board of the French National Institute of Health and Medical Research (reference: IRB00003888) approved the protocol, and the study was registered at (NCT03381950).


Data were collected at baseline and then annually by trained clinical research associates (CRAs) from participant interviews and medical records from the nephrology centers that included them. All of them contain patient histories, hospitalizations reports, imaging, and laboratory data from every ward of the hospital/clinic, but they are not standardized and may differ between these centers. Data collected included sociodemographic characteristics and a history of hypertension, diabetes, cardiovascular disease, dyslipidemia, or AKI, as defined previously (25). Medication adherence was assessed with the Girerd score (26), which was calculated by asking six questions that explore the primary determinants of adherence to chronic medication (its timing, remembering to take it, and remembering to renew the prescription). Serum creatinine, albumin, and hemoglobin were measured, as was urinary albumin or protein. We used the Chronic Kidney Disease Epidemiology Collaboration equation to estimate GFR (27). Participants were asked to bring to their inclusion appointment all of their current drug prescriptions for the previous 3 months (regardless of the prescribing physician) and all prescriptions for the year to each annual follow-up appointment. In France, all prescriptions are reimbursed similarly, except for medications determined by the Ministry of Health to have only moderate or insufficient medical benefits. Some differences in reimbursement also exist for patients with chronic expensive diseases and for patients who have not purchased supplementary health insurance, but none of these differences affect the recording and processing of prescriptions. Accordingly, drug prescriptions were continuously recorded from 3 months preceding inclusion through the end of follow-up. We used the international Anatomic Therapeutic and Chemical thesaurus (28) to code treatments and recorded their start and discontinuation dates (with causes, if any). Kidney failure events, defined as dialysis start or preemptive transplantation, and deaths were reported by the participants or their families, or they were identified from medical records or record linkage with the national kidney failure registry (29).

Identification and Validation of Adverse Drug Reactions

An ADR is defined as “an appreciably harmful or unpleasant reaction, resulting from an intervention related to the use of a medicinal product, which predicts hazard from future administration and warrants prevention or specific treatment, or alteration of the dosage regimen, or withdrawal of the product” (6). An ADR is considered serious when the patient outcome is death (or a life-threatening situation), hospitalization (initial or prolonged), disability or permanent damage, or another important medical event (30).

We collected ADRs over a 2-year follow-up via an electronic form designed specifically to include information critical for this study. We used several sources to identify ADRs: (1) medical records (examined by CRAs), (2) participant interviews by CRAs, and (3) hospital reports (Figure 1). Hospitalizations were identified from (1) electronic medical records, (2) nephrology records, and (3) participant interviews. For each hospitalization, we obtained a report to confirm the period and the cause. Causes of hospitalization were coded by a physician according to the tenth revision of the International Classification of Diseases. Every drug prescribed to the patient at the time of each ADR was recorded. Each identified ADR was reviewed by two pharmacists (S.L. and S.M.L.) who evaluated the potential causation of reported drug-related ADRs and coded the types of effect according to the medical dictionary for regulatory activities (MedDRA Dictionary), the severity of the ADR (nonserious or serious), the drug suspected of responsibility for the ADR, its dosage, and immediate medication management: discontinuation of the product, dose adaptation, or no change. If the ADR was considered serious, a larger committee of expert pharmacologists (J.M., S.L., S.M.L., and V.G.-C.) from the Amiens pharmacovigilance center further evaluated the potential causal relation of each drug (prescribed at the time of the ADR) and the preventability of the ADR.

Figure 1.:
Description of the process for identifying and validating adverse drug reactions in the Chronic Kidney Disease-Renal Epidemiology and Information Network (CKD-REIN) cohort.

Assessment of the Causes and Preventability of Serious Adverse Drug Reactions

We applied the Bégaud imputability method (31) (Supplemental Table 1A), which is the official procedure used in French pharmacovigilance centers to report serious ADRs to the French drug authorities. This algorithmic method attributes an intrinsic score on the basis of chronological and semiological criteria. The cause and effect relationship is assessed independently for each drug taken by the patient before the occurrence of the event and is not influenced by the extent of imputability to other drugs. This method allowed us to identify the drug most responsible for serious ADRs (i.e., that with the highest intrinsic score). During the ADR validation process, we globally evaluated all of the risk factors for ADRs, including a review of all drugs prescribed at the time of the ADR and evaluation of potential pharmacokinetic/pharmacodynamic interactions.

In addition, we used the Naranjo ten-question algorithm (Supplemental Table 1B) to confirm the causal relation of each reported serious ADR by determining the probability that an ADR is actually due to a drug rather than to any other factor (32). This analysis considers only ADRs categorized as definite, probable, or possible with both the Bégaud and Naranjo methods.

The preventability of ADRs was assessed with a seven-item ADR preventability scale (33) (Supplemental Table 1C) that classified ADRs in four categories: “preventable,” “potentially preventable,” “not assessable,” and “not preventable.” When items related to adherence to recommendations and the patient’s need for the prescription were uncertain, the expert committee rated preventability as “not assessable.”

Both outpatient and inpatient medical records were used to assess causality and preventability.

Statistical Analyses

Baseline characteristics were described for all participants and by subgroup according to baseline eGFR (<30 or ≥30 ml/min per 1.73 m2). ADRs were also described according to baseline eGFR. Results were expressed as means ± SDs, medians (interquartile ranges), or numbers (percentages). Fisher exact, t, or chi-squared tests were used to compare categorical variables. A sensitivity analysis was conducted by using the last eGFR preceding the ADR to describe it.

Crude incidence rates and 95% confidence intervals (95% CIs) of ADRs and serious ADRs per 100 person-years were estimated by Poisson regression for the overall population and by subgroups according to baseline eGFR; they were corrected for overdispersion by using the quasilikelihood approach.

We used cause-specific Cox proportional hazard models to investigate patient clinical characteristics associated with the ADR risk. Data were censored at the end of the 2-year follow-up, the last patient visit, death, or kidney failure, whichever came first (competing events). Variables from Table 1, preselected by a literature review, were analyzed in a crude model. Variables with a P value >0.10 in the crude model were excluded from the multivariable analyses. Age and sex were forced into the final model: that is, included because they were considered necessary for the model’s validity.

Table 1. - Baseline characteristics of participants in the Chronic Kidney Disease-Renal Epidemiology and Information Network
Characteristics All, n=3033 Baseline eGFR, ml/min per 1.73 m2 Participants with Missing Data, a %, n=3033
≥30, n=1670 <30, n=1363
Age, yr 69 [60–76] 68 [59–75] 70 [61–78] 0
 <60 716 (24%) 421 (25%) 295 (22%)
 60–75 1400 (46%) 803 (48%) 597 (44%)
 ≥75 917 (30%) 446 (27%) 471 (35%)
Men 1982 (65%) 1121 (67%) 861 (63%) 0
High school diploma or higher 1094 (36%) 648 (39%) 446 (33%) 1.7
BMI 28 [25–32] 28 [25–32] 28 [25–32] 2.1
 ≥30 kg/m2 1075 (35%) 573 (34%) 502 (37%)
Serum albumin 4.0 [3.8–4.3] 4.1 [3.8–4.3] 4.0 [3.7–4.3] 18.9
 <3.5 g/dl 293 (10%) 138 (8%) 155 (11%)
UACR, mg/g 11.2
 <30 846 (28%) 625 (37%) 221 (16%)
 30–300 955 (31%) 540 (32%) 415 (31%)
 >300 1232 (41%) 505 (31%) 727 (53%)
Anemia b 1236 (41%) 490 (29%) 746 (55%) 0.9
Smoking status 0.8
 Smoker 360 (12%) 197 (12%) 163 (12%)
 Nonsmoker 1252 (41%) 701 (42%) 551 (40%)
 Ex-smoker 1421 (47%) 773(46%) 648 (48%)
Diabetes 1304 (43%) 702 (42%) 602 (44%) 0.2
AKI history 710 (23%) 350 (21%) 360 (26%) 8.0
Cardiovascular history 1611 (53%) 854 (51%) 757 (56%) 1.4
Hypertension 2751 (91%) 1493 (89%) 1258 (92%) 0.2
Dyslipidemia 2229 (73%) 1216 (73%) 1011 (74%) 0.5
No. of drugs 8 [5–10] 7 [5–10] 8 [6–11] 0.6
 <5 593 (19%) 412 (25%) 181 (13%)
 5–10 1694 (56%) 915 (54%) 779 (57%)
 >10 747 (25%) 344 (21%) 403 (30%)
Poor adherence to medications 1888 (62%) 1010 (60%) 878 (64%) 1.0
Median (interquartile range) or n (%). BMI, body mass index; UACR, urine albumin-creatinine ratio.
aMissing data were imputed as specified in Materials and Methods.
bAnemia is defined by the 1968 World Health Organization (51) definition: <12 g/dl for women and <13 g/dl for men.

Because of the possibility of multiple ADRs per patient during the follow-up, we performed a sensitivity analysis using the Prentice, Williams, and Peterson gap-time recurrent event time-to-event analysis, with sandwich variance estimators, to determine the factors associated with ADRs (34,35).

To deal with the missing data (Supplemental Table 2), multiple imputations were performed (fully conditional specification method [36], ten iterations, ten datasets), including all patient characteristics from Table 1, the total number of ADRs per patient, and the number of serious ADRs per patient. Data patterns suggest that the assumption that data were missing at random was plausible. Cox model regression coefficients were estimated separately in each imputed dataset and combined according to Rubin rules.

Statistical analyses were performed with SAS software (version 9.4; SAS Institute, Cary, NC) and R software (version 3.5.0; Foundation for Statistical Computing, Vienna, Austria).


Baseline Characteristics

Participants were predominantly men; 43% had diabetes, 53% had cardiovascular disease, and 91% had hypertension (Table 1). Those with eGFR<30 ml/min per 1.73 m2 at baseline were older and had less education than those with higher eGFR. They also had anemia and a history of AKI more often, and they were prescribed more medications.

Incidence and Description of Adverse Drug Reactions

Over the 2-year follow-up, 751 ADRs were reported in 536 (18%) of 3033 participants; 150 ADRs in 125 participants (4%) were classified as serious (i.e., 14.4; 95% CI, 12.6 to 16.5 and 2.7; 95% CI, 1.7 to 4.3 per 100 person-years, respectively). Both were nearly twice as high in participants with eGFR<30 versus ≥30 ml/min per 1.73 m2 (Figure 2, Tables 2 and 3). Five percent of participants had more than one ADR. Sixty percent of ADRs were reported only in the medical record or hospitalization report, 20% were reported in both the medical record and participant interview, and 20% were only reported in the participant interview.

Figure 2.:
Higher incidence rates of adverse drug reactions (ADRs) and serious ADRs in patients with eGFR<30 ml/min per 1.73 m 2 . Incidence rates are represented with their 95% confidence interval whiskers. P values test the difference between incidence rates according to baseline eGFR.
Table 2. - Associations of participant characteristics with adverse drug reactions
Characteristics N (%) with Adverse Drug Reactions, n=536 Incidence Rate a Unadjusted Model Adjusted Model
Incidence Rate [95% Confidence Interval] Hazard Ratio [95% Confidence Interval] P Value Hazard Ratio [95% Confidence Interval] P Value
Age, yr 0.10 0.10
 <60 113 (16) 13.2 [9.9 to 17.6] Reference Reference
 60–75 271 (19) 15.2 [12.5 to 18.5] 1.25 [1.00 to 1.56] 1.06 [0.84 to 1.34]
 ≥75 152 (17) 14.0 [10.9 to 18.0] 1.08 [0.85 to 1.38] 0.85 [0.65 to 1.11]
Sex 0.08 0.04
 Men 332 (17) 13.2 [11.1 to 15.7] Reference Reference
 Women 204 (19) 16.6 [13.4 to 20.6] 1.17 [0.98 to 1.39] 1.21 [1.01 to 1.45]
Educational level 0.09 0.99
 High 179 (16) 13.0 [10.2 to 16.5] Reference Reference
 Low 357 (18) 15.2 [12.8 to 17.9] 1.17 [0.97 to 1.40] 1.00 [0.83 to 1.21]
eGFR, ml/min per 1.73 m 2 <0.001 <0.001
 ≥30 244 (15) 10.8 [8.9 to 13.2] Reference Reference
 <30 292 (21) 19.4 [16.2 to 23.2] 1.74 [1.47 to 2.07] 1.56 [1.30 to 1.87]
Serum albumin, g/dl 0.06 0.31
 ≥3.5 476 (17) 13.9 [12.0 to 16.0] Reference Reference
 <3.5 60 (20) 19.7 [12.9 to 29.9] 1.38 [1.00 to 1.90] 1.19 [0.85 to 1.65]
UACR, mg/g 0.06 0.90
 <30 139 (16) 13.1 [10.0 to 17.1] Reference Reference
 30–300 165 (17) 12.9 [10.0 to 16.7] 1.09 [0.85 to 1.39] 0.95 [0.75 to 1.22]
 >300 232 (19) 16.6 [13.5 to 20.4] 1.29 [1.03 to 1.62] 1.00 [0.79 to 1.27]
Anemia b <0.001 0.06
 Without anemia 287 (16) 12.3 [10.3 to 14.8] Reference Reference
 With anemia 249 (20) 17.7 [14.6 to 21.5] 1.45 [1.23 to 1.72] 1.19 [0.99 to 1.42]
Diabetes 0.01 0.78
 Without diabetes 274 (16) 12.1 [10.0 to 14.7] Reference Reference
 With diabetes 262 (20) 17.4 [14.4 to 21.0] 1.31 [1.10 to 1.55] 1.03 [0.85 to 1.24]
AKI history <0.001 0.01
 Without AKI history 379 (16) 12.9 [11.0 to 15.2] Reference Reference
 With AKI history 157 (22) 19.4 [15.0 to 25.1] 1.48 [1.21 to 1.81] 1.32 [1.08 to 1.61]
Cardiovascular history <0.001 0.03
 Without cardiovascular history 215 (15) 11.3 [9.1 to 14.0] Reference Reference
 With cardiovascular history 321 (20) 17.2 [14.6 to 20.4] 1.42 [1.19 to 1.69] 1.24 [1.02 to 1.50]
Hypertension 0.06 0.71
 Without hypertension 38 (13) 9.4 [5.4 to 16.1] Reference Reference
 With hypertension 498 (18) 14.9 [13.0 to 17.1] 1.37 [0.99 to 1.91] 1.07 [0.76 to 1.51]
Baseline no. of drugs per patient <0.001 0.01
 <5 62 (10) 7.5 [5.0 to 11.2] Reference Reference
 5–10 301 (18) 13.9 [11.6 to 16.7] 1.86 [1.41 to 2.44] 1.50 [1.12 to 2.02]
 >10 173 (9) 21.7 [17.3 to 27.3] 2.59 [1.93 to 3.46] 1.71 [1.21 to 2.41]
Adherence to medication <0.001 0.01
 Good 158 (14) 10.7 [8.3 to 13.7] Reference Reference
 Poor 378 (20) 16.7 [14.3 to 19.6] 1.52 [1.26 to 1.83] 1.36 [1.12 to 1.64]
P values used the Wald chi-squared test for global variable effect. UACR, urine albumin-creatinine ratio.
aIncidence rates are expressed per 100 person-years.
bAnemia is defined by the 1968 World Health Organization (51) definition: <12 g/dl for women and <13 g/dl for men.

Table 3. - Associations of participant characteristics with serious adverse drug reactions
Characteristics N (%) with Adverse Drug Reactions, n=125 Incidence Rate a Unadjusted Model Adjusted Model
Incidence Rate [95% Confidence Interval] Hazard Ratio [95% Confidence Interval] P Value Hazard Ratio [95% Confidence Interval] P Value
Age, yr 0.15 0.32
 <60 26 (4) 2.4 [0.9 to 6.9] Reference Reference
 60–75 52 (4) 2.4 [1.1 to 5.1] 1.02 [0.64 to 1.63] 0.71 [0.44 to 1.17]
 ≥75 47 (5) 3.4 [1.6 to 7.5] 1.45 [0.90 to 2.34] 0.91 [0.54 to 1.51]
Sex 0.91 0.74
 Men 82 (4) 2.7 [1.5 to 4.8] Reference Reference
 Women 43 (4) 2.8 [1.3 to 6.0] 0.98 [0.68 to 1.42] 1.06 [0.73 to 1.55]
eGFR, ml/min per 1.73 m 2 <0.001 0.01
 ≥30 49 (3) 1.8 [0.9 to 3.4] Reference Reference
 <30 76 (6) 4.0 [2.4 to 6.8] 2.17 [1.51 to 3.11] 1.82 [1.25 to 2.63]
BMI, kg/m 2 0.05 0.46
 <30 70 (4) 2.4 [1.3 to 4.5] Reference Reference
 ≥30 55 (5) 3.3 [1.6 to 6.8] 1.42 [0.99 to 2.04] 1.16 [0.79 to 1.70]
Anemia b 0.001 0.15
 Without anemia 60 (3) 2.0 [1.0 to 4.1] Reference Reference
 With anemia 65 (5) 3.9 [2.0 to 7.5] 1.77 [1.25 to 2.52] 1.31 [0.91 to 1.89]
Diabetes 0.03 0.89
 Without diabetes 60 (3) 2.3 [1.2 to 4.3] Reference Reference
 With diabetes 65 (5) 3.3 [1.8 to 6.1] 1.47 [1.03 to 2.09] 0.97 [0.65 to 1.44]
AKI history 0.01 0.12
 Without AKI history 84 (4) 2.3 [1.3 to 4.2] Reference Reference
 With AKI history 41 (6) 4.0 [1.8 to 9.3] 1.67 [1.12 to 2.49] 1.37 [0.92 to 2.05]
Cardiovascular history <0.001 0.01
 Without cardiovascular history 35 (2) 1.5 [0.7 to 3.4] Reference Reference
 With cardiovascular history 90 (6) 3.9 [2.4 to 6.3] 2.45 [1.65 to 3.63] 1.93 [1.25 to 2.98]
Baseline no. of drugs per patients <0.001 0.05
 <5 10 (2) 1.1 [0.2 to 4.6] Reference Reference
 5–10 62 (4) 2.4 [1.3 to 4.3] 2.29 [1.17 to 4.46] 1.53 [0.76 to 3.10]
 >10 53 (3) 5.0 [2.7 to 9.4] 4.70 [2.39 to 9.23] 2.31 [1.07 to 5.01]
Adherence to medication 0.01 0.03
 Good 30 (3) 1.8 [0.8 to 4.3] Reference Reference
 Poor 95 (5) 3.3 [2.0 to 5.4] 1.95 [1.29 to 2.94] 1.59 [1.05 to 2.42]
P values used the Wald chi-squared test for global variable effect. BMI, body mass index.
aIncidence rates are expressed per 100 person-years.
bAnemia is defined by the 1968 World Health Organization (51) definition: <12 g/dl for women and <13 g/dl for men.

Among the serious ADRs, 145 were associated with hospitalization: 65% as its cause and 35% as its consequence (Figure 3). Sixteen deaths resulted from an ADR, directly or indirectly, as did five life-threatening events. Five participants with serious ADRs (three medically important and two resulting in permanent disability) were not hospitalized.

Figure 3.:
Distribution of serious ADRs causing or resulting from hospitalization according to baseline eGFR ( n =145). Renal disorders and bleeding are the most frequent serious ADRs. Results are expressed as percentages. The denominators used are the total number of ADRs in patients with eGFR<30 or ≥30 ml/min per 1.73 m2.

Renal and urinary disorders were the most frequent type of ADR, particularly AKI, followed by gastrointestinal (mostly diarrhea), musculoskeletal, and connective tissue disorders (Table 4, Supplemental Table 3). Renal disorders and hemorrhages or bleeding accounted for two thirds of the 150 serious ADRs (Figure 3). Of the 16 deaths linked to an ADR, 11 were related to hemorrhages, which also accounted for 40% of the serious ADRs in participants with baseline eGFR <30 ml/min per 1.73 m2 and 19% in those with eGFR≥30 ml/min per 1.73 m2 (P=0.009) (Figure 3). Using the last eGFR before the ADR did not significantly change the proportions reported in Figure 3 and Table 4 (Supplemental Tables 4 and 5).

Table 4. - Description of adverse drug reactions according to baseline eGFR
Type of Adverse Drug Reaction All Adverse Drug Reactions, n=751 Adverse Drug Reactions in Patients with eGFR≥30, n=331 Adverse Drug Reactions in Patients with eGFR<30, n=420
Renal and urinary disorders 150 (20%) 62 (19%) 88 (21%)
 AKI 102 41 61
 Increased serum creatinine 40 20 20
 Other type of renal and urinary disorders 8 1 7
Gastrointestinal disorders 119 (16%) 61 (18%) 58 (14%)
 Diarrhea 57 35 22
 Gastrointestinal conditions 24 8 16
 Other type of gastrointestinal disorders 38 18 20
Musculoskeletal and connective tissue disorders 68 (9%) 34 (10%) 34 (8%)
 Contractures 35 21 14
 Muscle pain 22 10 12
 Other type of musculoskeletal and connective tissue disorders 11 3 8
Hemorrhages and bleeding 67 (9%) 18 (5%) 49 (12%)
 Hemorrhages 34 8 26
 Hematoma 19 7 12
 Other type of hemorrhages and bleeding 14 3 11
General disorders and administration site conditions 58 (8%) 26 (8%) 32 (8%)
 Peripheral edema 30 11 19
 Drug intolerance 8 3 5
 Other type of general disorders and administration site conditions 20 12 8
Other type of adverse drug reactions 289 (38%) 130 (39%) 159 (38%)
eGFR is expressed in milliliters per minute per 1.73 m2. Results are expressed as n (%). The denominator used in column 2 is the total number of adverse drug reactions, and the denominators used in columns 3 and 4 are those of the adverse drug reactions in patients with eGFR<30 versus ≥30, respectively. P=0.03 tests the difference in the distribution of adverse drug reaction type according to patient baseline eGFR.

Renin-angiotensin system (RAS) inhibitors, antithrombotic agents, and diuretics were the medications most frequently responsible for both nonserious and serious ADRs (Figure 4, Supplemental Table 6). Antithrombotic agents were responsible for 34% of the 150 serious ADRs: 34 were due to vitamin K antagonists, nine were due to heparin, six were due to platelet aggregation inhibitors, and two were due to direct factor Xa inhibitors. Three pharmacodynamic drug interactions were identified: two between vitamin K antagonist and heparins and one between vitamin K antagonist and an antibiotic.

Figure 4.:
The most common pharmacological classes responsible for ADRs and serious ADRs are renin-angiotensin system inhibitors, antithrombotic agents, and diuretics. Adverse drug reactions caused by agents acting on the renin-angiotensin system (RAS), antithrombotic agents, or diuretics accounted for 39% of ADRs. Serious ADRs caused by these three classes accounted for 58% of serious ADRs. Results are expressed as percentages. The denominators used are the total number of ADRs in patients with eGFR<30 or ≥30 ml/min per 1.73 m2.

Factors Associated with Adverse Drug Reactions and Serious Adverse Drug Reactions

Participants with a baseline eGFR <30 ml/min per 1.73 m2 had a risk 1.6 times higher of an ADR than those with an eGFR≥30 ml/min per 1.73 m2 after adjustment for other associated variables (Table 2). The risk of ADR also significantly increased with the participant’s baseline number of prescribed drugs, history of cardiovascular disease, history of AKI, and poor treatment adherence. Women were at higher risk of an ADR than men, but not of a serious ADR. There was no significant association with age.

Hazard ratios for serious ADRs were significantly higher in participants with eGFR<30 ml/min per 1.73 m2 compared with eGFR≥30 ml/min per 1.73 m2 as well as in those prescribed more than ten compared with less than five medications and in participants with poor adherence (Table 3). Age and sex were not associated with a higher risk of serious ADR.

A sensitivity analysis confirmed that the factors mentioned above were associated with ADRs (Supplemental Table 7A). It also showed that anemia was significantly associated with the risk of serious ADRs but that poor adherence no longer was (Supplemental Table 7B).

Immediate Management of Adverse Drug Reactions and Preventability

After an ADR, the drug considered responsible was discontinued in 71% of cases (e.g., in 78% of statin-linked ADRs), at least temporarily, and the dose was adjusted in 14% of cases; no change was made in the prescription in 11% (4% missing data). When the ADR was serious, 83% of the drugs blamed were discontinued at least temporarily right after the event.

The Olivier ADR preventability scale (33) allowed us to classify the 150 serious ADRs as preventable in 13% of cases (n=19) and potentially preventable in 19% (n=28). A quarter of the preventable ADRs were associated with participant self-medication. Overall, 37% of ADRs were inevitable, and 31% were not assessable (Supplemental Table 6).


This study presents a global descriptive view of the magnitude and diversity of ADRs in a well phenotyped CKD population. The central message here is that ADRs are common, often serious, and potentially preventable in patients with CKD and that these patients are vulnerable and their treatment is complex. It shows that three drug classes among those most prescribed in this population are responsible for almost 40% of ADRs, including RAS inhibitors, antithrombotic agents, and diuretics. The study especially points out the severity of ADRs caused by antithrombotic agents, to which one third of the serious events were imputed. In addition, we identify some care and patient characteristics that increase ADR risk; these include eGFR (<30 ml/min per 1.73 m2), a higher number of prescribed drugs, and poor adherence to medications. Importantly, a significant proportion of these ADRs may be preventable.

Our findings are difficult to compare with those of other studies, which differ from ours in several ways. Most of them assessed ADR incidence at hospital admission (1–23,5,7–8910,13) or during hospitalization (1,11–1213,23), and they used highly heterogeneous study settings, definitions of ADRs, and methods for ascertaining ADRs (spontaneous report, intensive chart review, or both). In this study, we evaluated ADR incidence in nephrology outpatients, with and without hospitalization; they were identified from an extensive review of medical records, hospitalization reports, and participant interviews. We compared rates according to eGFR and showed that ADR incidence increased when eGFR was lower than 30 ml/min per 1.73 m2. Overall, renal, urinary, gastrointestinal, musculoskeletal, and connective tissue disorders were the most commonly reported ADRs in our study, but renal disorders and bleeding largely predominated among the serious ADRs. Several studies have reported similar results in hospitalized patients with unknown CKD status (5,8–910). The known high susceptibility of patients with CKD for AKI explains the high frequency of renal and urinary ADRs. Cardiovascular medicines stand out among the most common suspected drugs in several studies of hospitalized patients with unknown CKD status (2–345,9,10). Similarly, we found that RAS inhibitors, antithrombotic agents, and diuretics were the pharmacologic classes to which ADRs were most commonly imputed in our study. The high prevalence of CKD-related cardiovascular complications explains the high use of cardiovascular drugs in patients with CKD (37), despite their high risk of ADR due to the combined effect of low eGFR, hemorrhagic risk, and electrolyte disturbance. The principal drugs suspected of causing ADRs were usually not directly nephrotoxic, and most ADRs resulted from reduced renal clearance. This conclusion has important clinical implications, notably regarding drug prescriptions for patients with CKD and the need to focus on regularly reassessing use or dose according to eGFR (especially when it drops below 30 ml/min per 1.73 m2), as well as on potential nephrotoxic agents. However, the clinical benefits of some of these drugs have been demonstrated by a high level of evidence. For instance, a moderate increase (of 20%–30%) in creatinine can be expected with RAS inhibitors; nephrologists may find this an acceptable trade-off in view of these drugs’ protective nature in the long term and their ability to slow CKD progression. This moderate increase is well below the Kidney Disease Improving Global Outcomes definition used for drug-related AKI events in our study, which is on the basis of a rise in creatinine of at least 50% (25).

Patients seen by nephrologists require the most complex care because of their multiple comorbidities and the complications associated with decreased kidney function (38). These result in the use of multiple medications as shown here: CKD-REIN participants were prescribed a median of eight different drugs daily. Moreover, the number of prescribed drugs increases as CKD progresses (19,39). High rates of ADRs in patients with CKD add to the complexity of their care. As we showed, treatments often need to be stopped, at least temporarily, or dosages need to be adjusted because of ADRs, which may affect therapeutic management and ultimately reduce the likelihood of slowing CKD progression and decreasing its complications. Lipid-lowering agents are a good example of treatments that are strongly recommended in patients with CKD because of their high cardiovascular risk but are often discontinued because of contractures, cramps, or myalgia (stopped in 78% of statin-linked ADRs). Schneider et al. (40) noted the underprescription of statins in patients with CKD, which may be partly explained by ADRs; a similar underprescription rate exists in the CKD-REIN cohort (41). The challenge for physicians is to assess the benefit-risk ratio between treating a new complication and adding a new drug. Increased awareness by the medical community of this difficulty and of the necessity to reassess this benefit-risk ratio regularly, especially when eGFR decreases, is essential. Pharmacists, too, must play a role given that most ADRs occur in outpatients. Finally, the importance of patient education in terms of drug use must be enhanced because one quarter of preventable serious ADRs were due to participant misuse.

The major factors identified in this study associated with ADRs overall and with serious ADRs are the number of prescribed drugs, cardiovascular disease, poor adherence to treatment, and eGFR. Reports have regularly shown that the number of drugs is a risk factor in hospitalized patients with unknown CKD status (8,9,14,23). Other than the increased risk of ADR, polypharmacy is also associated with deleterious health outcomes in elderly patients (42). Poor adherence to medication is associated with higher ADR risk, possibly reflecting patients’ misuse of drugs. However, the healthy user effect cannot be ruled out (43). Two other studies have also described cardiovascular disease as a risk factor for ADR (7,23). Although numerous studies show women to be at higher risk of serious ADR in populations with an unknown CKD status (2,9,10,14), this was not the case in our CKD population. Age was not associated with the risk of either ADR or serious ADR, consistent with previous reports (8,14,23). The risk of ADR tended to be slightly lower in older patients in the multivariable analyses, although not significantly; this finding may be related to their lower number of inappropriate prescriptions (19). This may indicate more careful prescriptions by physicians for elderly patients. Declining kidney function seems to be an important risk factor for patients with CKD and eGFR<30 ml/min per 1.73 m2 compared with ≥30 ml/min per 1.73 m2, in line with the results reported by Sharif-Askari et al. (23) in hospitalized patients with CKD. Corsonello et al. (44) found a similar association between ADR risk and declining kidney function in elderly hospitalized patients. This higher rate of ADR at eGFR<30 ml/min per 1.73 m2 seems related mainly to bleeding events due to antithrombotic agents, mostly vitamin K antagonists. This highlights the importance of reassessing prescriptions regularly as kidney function declines, especially for drugs such as vitamin K antagonists. Although these medications are metabolized by the liver, excreted in an inactive form in stool and urine (45) and, thus, not renally eliminated, CKD can impair their disposition (18). Specifically, it can cause the accumulation of uremic toxins in blood and organs with deleterious effects (46): for example, indoxyl sulfate, which impairs platelet activity (47).

Major strengths of this study include its large sample size of patients with confirmed CKD diagnoses recruited from a representative sample of nephrology outpatient facilities. The high sensitivity and specificity of our process for identifying and grading ADRs are also unique. Indeed, a major limitation in ADR research is the lack of reliable data about the true burden of these reactions related to their reporting process; the traditional ascertainment method, through the spontaneous reporting system in pharmacovigilance, results in their vast under-reporting. A previous study showed that health professionals spontaneously report only 6% of serious ADRs (48). Our study used different sources to capture these events, especially serious ADRs, through hospitalization reports, medical records, and participant interviews. Furthermore, all cases were reviewed by pharmacists, and serious cases were evaluated by a committee of experts. Finally, the use of standard international coding systems for both drug classes and ADRs, the availability of start and end dates for each treatment, and the reasons for treatment discontinuation contribute to the quality and novelty of our findings.

Our study also has limitations. Despite our sensitive method for identifying ADRs, their number may still be underestimated, mainly for those not hospitalized during follow-up; these may not have been reported by physicians in medical records or by participants either to physicians or during interviews due to memory bias or because an ADR is so well known that it tends to be poorly reported in hospitalization reports and medical records. However, participants were probably most likely to report ADRs with the most negative effects on their health and well-being. We may not have captured all hospitalizations and may also have missed drug effects that have never been reported as a potential ADR. Other sources of ADRs might exist but were not available to us. Several decision algorithms for causality assessment in ADRs exist (49). However, none of them have been accepted as a gold standard, and comparing them could lead to discrepancies in results (50). These algorithms do not replace medical diagnosis.

Another limitation of this study is the heterogeneous nature of the outcome (ADR) used in the multivariable analyses. Although these analyses allowed us to identify some specific and potentially modifiable risk factors, our basic aim was to describe the general characteristics of patients at high risk for ADR. We will further explore risk factors associated with ADRs more specifically for a number of drug classes and outcomes.

Finally, our study is generalizable to patients with CKD seen by nephrologists but not to all patients with an eGFR<60 ml/min per 1.73 m2 in the general population. However, because nephrologists probably handle drugs more carefully, the ADR incidence would likely have been even higher in the broader population of patients not seen by nephrologists.

The burden of ADRs is high in patients with moderate to advanced CKD, and incidence was higher when CKD was severe. Our results highlight the major risk of specific pharmacological classes, particularly antithrombotic agents, which must be used cautiously in patients with CKD, especially at low eGFRs. Greater awareness by the medical community of the importance of eGFR level in prescribing medications, increased involvement of pharmacists in systematically verifying eGFR for patient prescriptions, and enhanced patient education are key elements for preventing ADRs in this population at high risk. The effect of ADRs on health resources and patients’ quality of life requires further evaluation.


Z.A. Massy reports receiving grants for the CKD-REIN and other research projects from Amgen, Baxter, Fresenius Medical Care, GlaxoSmithKline, Merck Sharp and Dohme-Chibret, Sanofi-Genzyme, Lilly, Otsuka, and the French government, as well as fees and grants to charities from Amgen, Astellas, Daichii, and Sanofi-Genzyme. These sources of funding are not necessarily related to the content of this manuscript. B. Stengel reports receiving grants for the CKD-REIN from Amgen, Baxter, Fresenius Medical Care, GlaxoSmithKline, Merck Sharp and Dohme-Chibret, Sanofi-Genzyme, Lilly, Otsuka, and Vifor Fresenius, as well as speaker honoraria at the French Society of Diabetology from Lilly and at the French-speaking Society of Nephrology, Dialysis and Transplantation from MSD. All remaining authors have nothing to disclose.


The CKD-REIN is funded by the Agence Nationale de la Recherche through the 2010 “Cohortes-Investissements d’Avenir” program (ANR-IA-COH-2012/3731) and by the 2010 National Programme Hospitalier de Recherche Clinique. The CKD-REIN is also supported through a public-private partnership with Amgen, Fresenius Medical Care, and GlaxoSmithKline since 2012; Lilly France since 2013; Otsuka Pharmaceutical since 2015; Baxter and Merck Sharp and Dohme-Chibret from 2012 to 2017; Sanofi-Genzyme from 2012 to 2015; and Vifor Fresenius and AstraZeneca since 2018. French National Institute of Health and Medical Research Transfert set up and has managed this partnership since 2011. A specific project on drug optimization in patients with CKD has been funded by the French National Agency for Medicines and Health Products Safety.

Published online ahead of print. Publication date available at

See related editorial, “Adverse Drug Effects in Patients with CKD: Primum Non Nocere,” on pages .


The authors thank the CKD-REIN study coordination staff for their efforts in setting up the CKD-REIN cohort: M.M., Elodie Speyer, Céline Lange, Sophie Renault, Reine Ketchemin, Natalia Alencar de Pinho, and all of the CRAs. We thank Jo Ann Cahn for editing the English version.

Dr. Solène Marie Laville, Prof . Sophie Liabeuf, Prof. Ziad Massy, Dr. Marie Metzger, and Dr. Bénédicte Stengel designed this project; Dr. Valérie Gras-Champel, Dr. Solène Marie Laville, Prof. Sophie Liabeuf, and Dr. Julien Moragny evaluated the serious ADRs; Dr. Solène Marie Laville, Prof. Sophie Liabeuf, and Dr. Marie Metzger analyzed the data; Dr. Valérie Gras-Champel, Dr. Solène Marie Laville, Prof. Sophie Liabeuf, Prof. Ziad Massy, Dr. Marie Metzger, Dr. Julien Moragny, and Dr. Bénédicte Stengel contributed to the interpretation of the results; Dr. Solène Marie Laville, Prof. Sophie Liabeuf, Prof. Ziad Massy, and Dr. Bénédicte Stengel wrote the first draft of the article; Prof. Christian Combe, Prof. Denis Fouque, Prof. Luc Frimat, Dr. Valérie Gras-Champel, Dr. Christian Jacquelinet, Prof. Maurice Laville, Dr. Solène Marie Laville, Prof. Sophie Liabeuf, Prof. Ziad Massy, Dr. Marie Metzger, Dr. Julien Moragny, Dr. Robinson, and Dr. Bénédicte Stengel provided critical feedback; Prof. Christian Combe, Prof. Denis Fouque, Prof. Luc Frimat, Dr. Valérie Gras-Champel, Dr. Christian Jacquelinet, Prof. Maurice Laville, Dr. Solène Marie Laville, Prof. Sophie Liabeuf, Prof. Ziad Massy, Dr. Marie Metzger, Dr. Julien Moragny, Dr. Robinson, and Dr. Bénédicte Stengel helped shape the research, analysis, and final draft of the manuscript; Prof. Christian Combe, Prof. Denis Fouque, Prof. Luc Frimat, Dr. Valérie Gras-Champel, Dr. Christian Jacquelinet, Prof. Maurice Laville, Dr. Solène Marie Laville, Prof. Sophie Liabeuf, Prof. Ziad Massy, Dr. Marie Metzger, Dr. Julien Moragny, Dr. Robinson, and Dr. Bénédicte Stengel approved the version to be published; and Dr. Bénédicte Stengel is the principal investigator.

Supplemental Material

This article contains the following supplemental material online at

Supplemental Table 1. Algorithms to assess causation and preventability.

Supplemental Table 2. Baseline characteristics of participants in the CKD-Renal Epidemiology and Information Network (before imputation).

Supplemental Table 3. Details of types of adverse drug reactions.

Supplemental Table 4. Descriptions of adverse drug reactions according to the last eGFR reported before the reaction.

Supplemental Table 5. Distribution of serious adverse drug reactions causing or resulting from hospitalization according to the last eGFR reported before the reaction (n=145).

Supplemental Table 6. Details of imputed drugs responsible for adverse drug reactions and of type of adverse drug reaction for the five pharmacological classes most frequently imputed.

Supplemental Table 7. Sensitivity analyses by the Prentice, Williams, and Peterson gap-time recurrent event time-to-event analysis.


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    chronic kidney disease; pharmacoepidemiology; antithrombotic agents; adverse drug reactions; risk factors; diuretics; Renin-Angiotensin System; glomerular filtration rate; Cohort Studies; Renal Insufficiency; Chronic; Drug-Related Side Effects and Adverse Reactions; hospitalization; Medical Records

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