| Literature DB >> 24904657 |
Jagadish Khanagavi1, Tanush Gupta1, Wilbert S Aronow2, Tushar Shah1, Jalaj Garg1, Chul Ahn3, Sachin Sule1, Stephen Peterson1.
Abstract
INTRODUCTION: The aim of the study was to investigate predictors of mortality in patients hospitalized with hyperkalemia.Entities:
Keywords: drug-induced hyperkalemia; in-hospital mortality; potassium supplements; prolonged hyperkalemia
Year: 2014 PMID: 24904657 PMCID: PMC4042045 DOI: 10.5114/aoms.2014.42577
Source DB: PubMed Journal: Arch Med Sci ISSN: 1734-1922 Impact factor: 3.318
Baseline characteristics of 408 patients hospitalized with hyperkalemia
| Variable | Results |
|---|---|
| Age, mean ± standard deviation [years] | 64 ±17 |
| Men, | 232 (57) |
| Women, | 176 (43) |
| GFR ≥ 60 with no CKD, | 95 (48) |
| GFR ≥ 60 with CKD, | 17 (4) |
| GFR 30–59, | 83 (20) |
| GFR 15–29, | 83 (20) |
| GFR < 15, | 30 (7) |
| Acute kidney injury, | 251 (62) |
| Diabetes mellitus, | 172 (42) |
| Blood transfusion, | 6 (4.58) |
| Tissue necrosis, | 8 (6.11) |
| Metabolic acidosis, | 48 (36.64) |
| Adrenal insufficiency, | 9 (6.87) |
| Coronary artery disease, | 110 (27) |
| Congestive heart failure, | 93 (23) |
| Hypertension, | 230 (57) |
| Atrial fibrillation, | 60 (15) |
| Liver cirrhosis, | 60 (15) |
| End-stage renal disease post renal transplant, | 32 (8) |
| End-stage liver disease post liver transplant, | 11 (3) |
| Bone marrow transplant, | 11 (3) |
| Solid tumors, | 56 (14) |
| Lymphoma/leukemia, | 47 (12) |
GFR – glomerular filtration rate (ml/1.73 m2); CKD – chronic kidney disease as defined by ICD-9 diagnosis codes
Prevalence of medications associated with hyperkalemia in patients with hyperkalemia
| Medications | Results |
|---|---|
| Angiotensin-converting enzyme inhibitors/ angiotensin receptor blockers, | 131 (32) |
| Amiloride/triamterene, | 4 (1) |
| Azole antifungals, | 42 (10) |
| β-Blockers, | 248 (61) |
| Cyclosporine, | 11 (3) |
| Digoxin, | 25 (6) |
| Eplerenone/spironolactone, | 70 (17) |
| Heparin, | 62 (15) |
| Hypertonic saline, | 1 (0.2) |
| Nonsteroidal anti-inflammatory drugs, | 25 (6) |
| Penicillin G, | 1 (0.2) |
| Pentamidine, | 1 (0.2) |
| Potassium supplements, | 45 (11) |
| Tacrolimus, | 32 (8) |
| Trimethoprim, | 32 (8) |
Stepwise Cox regression analysis for the time to hyperkalemia resolution
| Risk factors | Hazard ratio | 95% Confidence intervals | Value of |
|---|---|---|---|
| Tissue necrosis | 0.61 | 0.14–0.92 | 0.02 |
| Nonsteroidal anti-inflammatory drugs | 1.59 | 1.03–2.45 | 0.03 |
| Metabolic acidosis | 0.77 | 0.62–0.96 | 0.02 |
| Acute kidney injury | 0.77 | 0.62–0.96 | 0.02 |
| Serum potassium per 1 unit increase | 0.61 | 0.50–0.75 | < 0.001 |
Stepwise logistic regression analysis to determine the predictors of mortality in patients with hyperkalemia
| Risk factors | Odds ratio | 95% Confidence intervals | Value of |
|---|---|---|---|
| Tissue necrosis | 4.55 | 1.74–11.90 | 0.002 |
| Potassium supplements | 5.46 | 1.56–19.20 | 0.008 |
| Metabolic acidosis | 4.84 | 1.48–15.82 | 0.009 |
| Calcium gluconate | 4.62 | 1.60–13.35 | 0.005 |
| Acute kidney injury | 3.89 | 1.14–13.26 | 0.03 |
| Duration prior to resolution of hyperkalemia | 1.06 | 1.02–1.09 | < 0.001 |