Predictors for repeated hyperkalemia and potassium trajectories in high-risk patients — A population-based cohort study

Adelborg, Kasper; Nicolaisen, Sia Kromann; Hasvold, Pål; Palaka, Eirini; Pedersen, Lars; Thomsen, Reimar Wernich

doi:10.1371/journal.pone.0218739

Cited by 28 publications

(37 citation statements)

References 16 publications

(25 reference statements)

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“…3,36 In patients with CKD and/or chronic HF receiving RAASi, risk factors for repeated hyperkalemia within 6 months of the first event include moderate to severe initial hyperkalemia (!5.6 mEq/L), low eGFR (<45 mL/min per 1.73 m 2 ), diabetes, and spironolactone use. 37 Hyperkalemia risk is slightly higher in men than in women after initiation of RAASi therapy 3 and differs among racial groups, in whom ethnicity, diet, and socioeconomic factors may contribute. 38 These factors currently do not impact hyperkalemia management; however, the potentially additive effects of these differences may increase hyperkalemia risk.…”

Section: Risk Factorsmentioning

confidence: 99%

Clinical Management of Hyperkalemia

Palmer

Carrero

Clegg

et al. 2021

Mayo Clinic Proceedings

110

106

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Hyperkalemia is an electrolyte abnormality with potentially life-threatening consequences. Despite various guidelines, no universally accepted consensus exists on best practices for hyperkalemia monitoring, with variations in precise potassium (K þ) concentration thresholds or for the management of acute or chronic hyperkalemia. Based on the available evidence, this review identifies several critical issues and unmet needs with regard to the management of hyperkalemia. Real-world studies are needed for a better understanding of the prevalence of hyperkalemia outside the clinical trial setting. There is a need to improve effective management of hyperkalemia, including classification and K þ monitoring, when to reinitiate previously discontinued renin-angiotensin-aldosterone system inhibitor (RAASi) therapy, and when to use oral K þ-binding agents. Monitoring serum K þ should be individualized; however, increased frequency of monitoring should be considered for patients with chronic kidney disease, diabetes, heart failure, or a history of hyperkalemia and for those receiving RAASi therapy. Recent clinical studies suggest that the newer K þ binders (patiromer sorbitex calcium and sodium zirconium cyclosilicate) may facilitate optimization of RAASi therapy. Enhancing the knowledge of primary care physicians and internists with respect to the safety profiles of these newer K þ binders may increase confidence in managing patients with hyperkalemia. Lastly, the availability of newer K þ-binding agents requires further study to establish whether stringent dietary K þ restrictions are needed in patients receiving K þ-binder therapy. Individualized monitoring of serum K þ among patients with an increased risk of hyperkalemia and the use of newer K þ-binding agents may allow for optimization of RAASi therapy and more effective management of hyperkalemia.

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Section: Risk Factorsmentioning

confidence: 99%

Clinical Management of Hyperkalemia

Palmer

Carrero

Clegg

et al. 2021

Mayo Clinic Proceedings

110

106

View full text Add to dashboard Cite

show abstract

“…36 In previous literature, prior laboratory values for elevated serum potassium (K + ≥6 mmol/L) have also been shown to be a strong predictor of recurrent ED encounters for hyperkalemia. 27 Cumulative hours of dialysis in the prior 2 weeks and an average ultrafiltration rate ≥10 mL/kg/h were also significant predictors of ED encounters for hyperkalemia. Longer dialysis hours may be capturing an appropriate clinical response to treat patients with persistently elevated potassium, chronic volume overload, or uremic complications.…”

Section: Discussionmentioning

confidence: 93%

“…Prior studies have explored clinical and demographic factors associated with health care encounters for hyperkalemia, 27 - 29 while others have examined the health outcomes (particularly mortality) among hemodialysis patients with elevated serum potassium levels. 30 - 32 To our knowledge, this is the first multivariable prediction model that has been derived and internally validated to identify maintenance hemodialysis patients at increased risk for hyperkalemia-related ED encounters.…”

Section: Discussionmentioning

confidence: 99%

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Derivation and Internal Validation of a Clinical Risk Prediction Tool for Hyperkalemia-Related Emergency Department Encounters Among Hemodialysis Patients

Ronksley

Wick

Elliott

et al. 2020

Can J Kidney Health Dis

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Background: Approximately 10% of emergency department (ED) visits among dialysis patients are for conditions that could potentially be managed in outpatient settings, such as hyperkalemia. Objective: Using population-based data, we derived and internally validated a risk score to identify hemodialysis patients at increased risk of hyperkalemia-related ED events. Design: Retrospective cohort study. Setting: Ten in-center hemodialysis sites in southern Alberta, Canada. Patients: All maintenance hemodialysis patients (≥18 years) between March 2009 and March 2017. Measurements: Predictors of hyperkalemia-related ED events included patient demographics, comorbidities, health-system use, laboratory measurements, and dialysis information. The outcome of interest (hyperkalemia-related ED events) was defined by International Classification of Diseases (10th Revision; ICD-10) codes and/or serum potassium [K+] ≥6 mmol/L. Methods: Bootstrapped logistic regression was used to derive and internally validate a model of important predictors of hyperkalemia-related ED events. A point system was created based on regression coefficients. Model discrimination was assessed by an optimism-adjusted C-statistic and calibration by deciles of risk and calibration slope. Results: Of the 1533 maintenance hemodialysis patients in our cohort, 331 (21.6%) presented to the ED with 615 hyperkalemia-related ED events. A 9-point scale for risk of a hyperkalemia-related ED event was created with points assigned to 5 strong predictors based on their regression coefficients: ≥1 laboratory measurement of serum K+ ≥6 mmol/L in the prior 6 months (3 points); ≥1 Hemoglobin A1C [HbA1C] measurement ≥8% in the prior 12 months (1 point); mean ultrafiltration of ≥10 mL/kg/h over the preceding 2 weeks (2 points); ≥25 hours of cumulative time dialyzing over the preceding 2 weeks (1 point); and dialysis vintage of ≥2 years (2 points). Model discrimination (C-statistic: 0.75) and calibration were good. Limitations: Measures related to health behaviors, social determinants of health, and residual kidney function were not available for inclusion as potential predictors. Conclusions: While this tool requires external validation, it may help identify high-risk patients and allow for preventative strategies to avoid unnecessary ED visits and improve patient quality of life. Trial registration: Not applicable—observational study design.

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“…A large meta-analysis of real-world data conducted by Kovesdy et al,11 found that reduced eGFR and increased albumin-to-creatinine ratio, both indicative of kidney function impairment, were associated with the incidence of HK at both >5.0 and >5.5 mmol/l K + thresholds. Furthermore, low eGFR was also found to be a risk factor for recurrent HK (2nd or subsequent event defined as K + >5.0 mmol/L) in a population-based cohort study in Denmark 14. With regards to medication use, the use of ACEIs, ARBs, MRAs, and anti-hyperglycaemic agents was generally associated with increased risk of HK, while the use of diuretics (albeit not K + -sparing diuretics, which were considered separately and only retained in a single model) was generally protective against HK.…”

mentioning

confidence: 90%

Risk factors associated with the incidence and recurrence of hyperkalaemia in patients with cardiorenal conditions

et al. 2021

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Introduction Hyperkalaemia (HK) is associated with increased mortality risk. Prior studies suggest that the causes of HK are multifactorial. This study aimed to examine risk factors for incident and recurrent HK in six large real‐world cohorts of UK patients that could be considered at elevated HK risk because of underlying disease pathology and/or medication use. Methods This retrospective, observational cohort study utilised UK primary and secondary care data from Clinical Practice Research Datalink (CPRD) and linked Hospital Episode Statistics (HES), respectively. Patients were included if they were aged ≥18 years and had a record of ≥1 condition of interest (chronic kidney disease [CKD] stage 3+, heart failure, resistant hypertension [RHTN], dialysis, diabetes) and/or renin‐angiotensin‐aldosterone system inhibitors (RAASi) use between 01 January 2003 and 30 June 2018. Based on their diagnosis/ RAASi prescription record, patients were assigned to overlapping cohorts. The outcomes assessed were HK and recurrent HK, the latter defined as second or subsequent HK episode during follow‐up. HK was defined as a serum K+ measurement ≥5.0 mmol/L; thresholds of ≥5.5 and ≥ 6.0 mmol/L were also explored. Results Of 931 460 meeting the eligibility criteria, 310 535 (33.3%) patients experienced ≥1 HK event and 187 719 (20.2%) experienced HK recurrence. The probability of subsequent HK events increased with event number from 60.5% for the second event to 76.5% for the sixth and the corresponding time to the next HK event decreased from 15.8 months to 6.1 months. Amongst the key risk factors, serum creatinine, serum phosphorus, systolic blood pressure, and white cell count demonstrated direct relationships with incidence and recurrence of HK, while inverse relationships were observed for estimated glomerular filtration rate (eGFR), haemoglobin and diastolic blood pressure. The relationship for Charlson's Comorbidity Index was mixed. The use of RAASi and anti‐hyperglycaemic agents was associated with an increased risk of HK, while the use of diuretics (non‐K+‐sparing) was protective against HK. Conclusion Several risk factors for HK that are easily measured in routine clinical practice were identified, facilitating the identification of patients who are at the highest risk of experiencing HK, including recurrent HK.

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Predictors for repeated hyperkalemia and potassium trajectories in high-risk patients — A population-based cohort study

Cited by 28 publications

References 16 publications

Clinical Management of Hyperkalemia

Clinical Management of Hyperkalemia

Derivation and Internal Validation of a Clinical Risk Prediction Tool for Hyperkalemia-Related Emergency Department Encounters Among Hemodialysis Patients

Risk factors associated with the incidence and recurrence of hyperkalaemia in patients with cardiorenal conditions

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