Statistical Analysis Descriptive statistics are presented as means and standard deviations or percentages of participants. Results The final study population was chosen from the patients admitted in total. Figure 1.
Selection of hospital inpatients who were starting angiotensin-converting enzyme inhibitor or angiotensin receptor blocker use. Table 1. Baseline characteristics of the patients. Figure 2. Table 2. Causal relationship between hyperkalemia and antihypertensive drug use. References G. Grassi, D. Calhoun, G. Mancia, and R. Wang, J. Hu, T. Luo et al. Xie, Y. Liu, V. Perkovic et al. Krittanawong and T. Svensson, F. Gustafsson, S. Galatius, P. Hildebrandt, and D. Pham, J. Sexton, D. Wimer, I.
Rana, and T. Weir and M. Park, S. Sheen, D. Yoon et al. Levey, J. Bosch, J. Lewis, T. Greene, N. Rogers, and D. Ficheur, E. Chazard, J. Beuscart, B. Merlin, M. Luyckx, and R. Bandak, Y. Sang, A. Gasparini et al. View at: Google Scholar A. Chang, Y. Sang, J. Leddy et al. Nilsson, A. Gasparini, J. Arnold, T. Pianta, B. Pussell, Z. Endre, M. Kiernan, and A. Kang and S. Han, Y. Won, J. The use of prescription drugs at the time of the index potassium level was determined by chart review.
Drugs were classified according to pharmacological class. The type and dosage of ACE inhibitor were also determined by chart review. Age was determined using administrative records.
The case patients with hyperkalemia were followed up for 1 year after determination of their index potassium levels as a retrospective cohort to describe their subsequent clinical course.
Variables measured for case patients for 1 year following the index episode of hyperkalemia included changes in therapy with ACE inhibitors increase or decrease in dosage, change in type of ACE inhibitor, or discontinuation of ACE inhibitor therapy and maximum potassium values for each type of change. Vital status as of December 31, , was determined for case patients and controls using the Department of Veterans Affairs centralized administrative database at Austin, Tex, as well as by review of local administrative records.
Univariate comparisons of potential predictor variables for hyperkalemia between case patients and controls were performed using the Student t , Wilcoxon rank sum, and McNemar tests as appropriate. Multivariate analysis was performed using stepwise logistic regression to determine independent risk factors for the development of hyperkalemia.
Cutoff points for continuous variables were identified that maximally discriminated between status of case patients and controls. These cutoff points were used to create categorical variables for use in the logistic regression models.
One-way analysis of variance was used to compare mean potassium values between the different types of change in therapy with ACE inhibitors during follow-up.
Life-table analysis was used to determine whether hyperkalemia was associated with increased mortality. Cox proportional hazards models were used to determine factors associated with increased mortality among the case patients with hyperkalemia. Specifically, modeling was used to determine whether a level of hyperkalemia existed that was independently associated with increased mortality.
Of the case patients with hyperkalemia, 37 had an index potassium level of 5. Table 1 compares the clinical characteristics of case patients and controls at the time of the index potassium level determination. The laboratory data presented are the most recent values preceding the index potassium determination. Case patients with hyperkalemia had a significantly higher preceding mean serum urea nitrogen level than normokalemic controls 8.
Congestive heart failure, peripheral vascular disease, and cerebrovascular disease were also significantly more common in the group with hyperkalemia. Only 3 case patients with hyperkalemia and 1 normokalemic control were using potassium-sparing diuretic agents. There was no significant difference in the average age for the case patients compared with the controls Table 2 compares the type and dosage of ACE inhibitors used for case patients and controls.
The vast majority of subjects using a long-acting ACE inhibitor were prescribed lisinopril. The mean daily doses of each type of ACE inhibitor did not differ significantly between case patients and controls. Independent factors predicting hyperkalemia using logistic regression analysis are listed in Table 3.
The factors identified are listed in order of entry into the model. An elevated serum urea nitrogen level and an elevated creatinine level were both identified as independent risk factors for hyperkalemia. A combined variable of the serum urea nitrogen and creatinine ratio did not prove to be a better predictor than the individual factors.
Congestive heart failure was identified as an independent predictor of hyperkalemia. In addition, use of long-acting ACE inhibitors lisinopril or enalapril was independently associated with an increased risk of hyperkalemia. The use of thiazide and loop diuretic agents were each associated with a reduced risk of hyperkalemia in multivariate analysis.
Table 4 summarizes the changes in therapy with ACE inhibitors that occurred during the subsequent year among the case patients with hyperkalemia. For at least part of the follow-up period, patients remained on a regimen of an ACE inhibitor. Of these, had a follow-up potassium test while receiving ACE inhibitors. No significant differences were observed in the mean maximum potassium levels for those whose ACE inhibitor dosage was increased, decreased, remained the same, or was discontinued.
Univariate predictors for the development of severe hyperkalemia in patients remaining on a regimen of ACE inhibitors are shown in Table 5. Both elevated serum urea nitrogen and creatinine levels were associated with an increased risk of developing severe hyperkalemia during follow-up.
Other factors associated with an increased risk of severe hyperkalemia during follow-up included age greater than 70 years and a glucose level higher than In multivariate analysis, a serum urea nitrogen level of more than 8. Twenty deaths occurred among the case patients with hyperkalemia and 20 deaths among the normokalemic controls during the follow-up period. Cox proportional hazards models were used to determine whether a level of hyperkalemia during the follow-up period was associated with increased mortality among the cohort of case patients with hyperkalemia.
These models demonstrated that severe hyperkalemia during follow-up was associated with increased mortality, although a potassium level of 6. Hyperkalemia during the use of ACE inhibitors was relatively frequent among our medical outpatients. An elevated serum urea nitrogen level, an elevated creatinine level, and congestive heart failure were strongly and independently associated with hyperkalemia.
These factors, while expected, accounted for the majority of cases of hyperkalemia. The sensitivity of having any one of these factors for predicting hyperkalemia was 0. An additional increased risk of hyperkalemia was observed with the use of long-acting ACE inhibitors compared with a short-acting ACE inhibitor. Reduced risk associations for hyperkalemia were observed with the use of thiazide and loop diuretic agents by multivariate analysis.
Prior studies 26 - 42 have documented the increasing incidence of hyperkalemia associated with the use of ACE inhibitors in patients who have renal insufficiency. Additional factors reported to increase the risk of hyperkalemia during the use of ACE inhibitors have included the use of potassium-sparing diuretic agents 28 , 41 and potassium supplements. In our patients, these agents were infrequent explanations for hyperkalemia. Indeed, the proportion of patients using potassium supplements and nonsteroidal anti-inflammatory drugs was lower in the case patients with hyperkalemia than in the normokalemic controls.
No patients in the case or control groups were using trimethoprim-sulfamethoxazole at the time of their index potassium level determination. Congestive heart failure per se has not been reported as a risk factor for hyperkalemia while using ACE inhibitors. Instead, hyperkalemia during the use of ACEs for congestive heart failure has usually been attributed to concomitant use of potassium supplementation or potassium-sparing diuretic agents.
Few studies 51 - 54 have compared the relative risk of hyperkalemia between different types of ACE inhibitors. Although tissue models have been described that support the potential for differing degrees of hyperkalemia as a result of differing effects on suppression of the renin-aldosterone system, 55 our observation of differing relative risk between the use of long-acting and short-acting ACE inhibitors is a cautious one. All ACE inhibitors are primarily renally excreted. The potential for higher and more sustained suppression of aldosterone levels may be greater with the use of ACE inhibitors having longer half-lives, particularly in the presence of impaired renal function.
However, our case-control study design cannot reliably exclude whether bias in patient selection for receiving these agents may have predisposed patients receiving long-acting ACE inhibitors to hyperkalemia through other factors. An important component of this study was the observation of patients following the initial episode of hyperkalemia.
We are unaware of any data describing the clinical course of such patients to determine how to subsequently monitor them or whether to continue using ACE inhibitors. A large number of our patients remained on a regimen of an ACE inhibitor for at least part of the follow-up period. The 2 independent factors identified, serum urea nitrogen level higher than 8. While the utility of these factors in predicting severe hyperkalemia needs to be validated in other populations, they provide guidance in responding to hyperkalemia occurring during the use of ACE inhibitors.
The relative infrequency of hyperkalemia in patients with hypertension and normal renal function in previous studies supports these guidelines. We were interested in whether a level of hyperkalemia independently predicted increased mortality among our cases with hyperkalemia. Multivariate analysis showed a potassium level of 6. Understanding the mechanism of action of ACEi and ARB coupled with judicious drug use and clinical vigilance can minimize the risk to the patient of developing hyperkalemia.
Should hyperkalemia occur, prompt recognition and management can optimize clinical outcome. Abstract The aims of this article are to review the current understanding of hyperkalemia associated with angiotensin-converting enzyme inhibitor ACEi or angiotensin receptor blocker ARB therapy.
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