| Establishment of a hyperkalemia assessment model for critically ill patients |
| Received:December 03, 2022 Revised:October 13, 2023 Click here to download the full text |
| Citation of this paper:LU Xiao-qing,LIU Ya-min,ZHOU Chun-yu,HUO Yan,WANG Pei.Establishment of a hyperkalemia assessment model for critically ill patients[J].Chinese Journal of Clinical Medicine,2023,30(6):993-998 |
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| Author Name | Affiliation | E-mail | | LU Xiao-qing | Department of Blood Purification Center, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan, China | | | LIU Ya-min | Department of Blood Purification Center, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan, China | | | ZHOU Chun-yu | Department of Blood Purification Center, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan, China | | | HUO Yan | Department of Blood Purification Center, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan, China | | | WANG Pei | Department of Blood Purification Center, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan, China | wangpei146@hotmail.com |
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| Abstract:Objective To explore risk factors of hyperkalemia among patients in intensive care unit (ICU) and to establish a risk assessment model for evaluating hyperkalemia. Methods The clinical data of 4 963 hospitalized patients admitted to ICU in the First Affiliated Hospital of Zhengzhou University from October 2019 to December 2020 were retrospectively collected. According to serum potassium level, patients were divided into a normal serum potassium of 3.5-5.5 mmol/L group (n=4 535) and a hyperkalemia group (n=428) with serum potassium level above 5.5 mmol/L. All Patients were then randomly divided into a training set (n=3 474) and a validation set (n=1 489) in a 7:3 ratio. Logistic regression analysis was used to construct a risk assessment model to evaluate the occurrence of hyperkalemia in ICU patients. ROC curve was used to evaluate the value of the model, and the model was validated in the validation set. Results Multivariate logistic analysis showed that male, ICU length of stay ≥ 5 days, estimated glomerular filtration rate (eGFR)<90 mL·min-1·(1.73 m2)-1, APACHE Ⅱ score>12, diabetes, acute respiratory distress syndrome (ARDS), cirrhosis, septic shock, multiple organ dysfunction syndrome (MODS) were independent related factors for hyperkalemia in severe patients. The area under the ROC curve (AUC) of this assessment model in the training set was 0.777, the cut-off value was 5, with 76.4% of the sensitivity and 66.6% of specificity; the validation set suggests that the model has the AUC of 0.777, with 80.5% of sensitivity, and 67.8% of specificity. Conclusions This risk assessment model is helpful to assess occurrence of hyperkalemia in ICU patients, which offers an alternative approach for the prevention and intervention of hyperkalemia. |
| keywords:hyperkalemia critical illness risk factor assessment model |
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