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HOME > Acute Crit Care > Volume 39(4); 2024 > Article
Original Article
CPR/Resuscitation Incidence of hypoglycemia in hyperkalemia patients after treatment with insulin and dextrose in the emergency department of a tertiary care hospital in India: a prospective observational study
Vivek Chaurasia1,#orcid, Nayer Jamshed2orcid, Praveen Aggrawal2orcid, Sanjeev Bhoi2orcid, Meera Ekka2orcid, Tej Prakash Sinha2orcid, Akshay Kumar2orcid, Prakash Ranjan Mishra2orcid, Anand Kumar Das2orcid
Acute and Critical Care 2024;39(4):499-506.
DOI: https://doi.org/10.4266/acc.2024.00661
Published online: November 22, 2024

1Department of Critical Care Medicine, BLK-Max Hospital, New Delhi, India

2Department of Emergency Medicine, All India Institute of Medical Sciences, New Delhi, India

Corresponding Author: Nayer Jamshed Department of Emergency Medicine, All India Institute of Medical Sciences, Ansari Nagar, New Delhi 110029, India Tel: +91-11-26588500, Fax: +91-11-26588663, E-mail: jamshednayer@gmail.com
#Current affiliation: Department of Emergency Medicine, Santosh Hospital, Ghaziabad, Uttar Pradesh, India
• Received: April 23, 2024   • Revised: August 21, 2024   • Accepted: August 28, 2024

© 2024 The Korean Society of Critical Care Medicine

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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  • Background
    Hypoglycemia is a serious, often overlooked complication of treating hyperkalemia with insulin and dextrose. If not recognized and managed, it can increase morbidity and mortality. This study aimed to estimate the incidence of hypoglycemia in hyperkalemic patients treated with 10 units of intravenous insulin, 50 ml of 50% dextrose, 10 ml of 10% calcium gluconate, and salbutamol nebulization. Additionally, the timing of hypoglycemia onset and its associated factors were studied.
  • Methods
    This prospective observational study included hyperkalemic patients (serum potassium >5.5 mmol/L) who visited the emergency department between January 26, 2020, and August 26, 2021. The primary outcome was hypoglycemia (blood glucose <70 mg/dl) within 3 hours of receiving the standard treatment. Glucose levels were measured hourly for 3 hours. Univariate and multivariate logistic regression identified factors associated with hypoglycemia.
  • Results
    Of 100 patients, 69% were male, and the median age was 46 years (IQR, 30–60 years). Hypoglycemia occurred in 44%, and 10% developed severe hypoglycemia (blood glucose <54 mg/dl). The median time for hypoglycemia onset was 2 hours (IQR, 1–2 hours). Low pretreatment blood glucose (<100 mg/dl) was significantly associated with hypoglycemia, according to both univariate and multivariate analyses.
  • Conclusions
    The study found a higher incidence of hypoglycemia in hyperkalemia treatment than reported in retrospective studies, suggesting the need for standardized management protocols with integrated glucose monitoring.
  • Keywords: dextrose; hyperglycemia; hyperkalemia; hypoglycemia; insulin
Potassium is a predominant intracellular cation that helps in maintaining normal transmembrane voltage gradient and plays a key role in determining the transmembrane potentials of “excitable membrane” present in skeletal muscle, cardiac muscle, smooth muscle, and nerve cells [1]. The kidney is the primary organ responsible for potassium regulation in the body; 90% of potassium excretion is performed by the kidneys and the remaining 10% through the gastrointestinal system [2-4]. Due to reduced renal clearance, patients with end-stage renal disease are at an increased risk of hypoglycemia [5,6]. Hyperkalemia is a common potentially life-threatening electrolyte disorder encountered in emergency departments (EDs) and can be fatal if untreated [7]. Normal serum potassium level ranges from 3.5–5.0 mmol/L. Although there is no internationally agreed upon definition for hyperkalemia, the European Resuscitation Council defines hyperkalemia as a plasma level >5.5 mmol/L and severe hyperkalemia as plasma level >6.5 mmol/L [8]. Due to the high risk of cardiac complications, hyperkalemia should be treated urgently in patients with electrocardiogram (ECG) abnormalities associated with hyperkalemia or serum potassium ≥6 mmol/L [9]. Treatment includes stabilizing the cardiac membrane with intravenous (IV) calcium, shifting potassium into cells with IV insulin and albuterol/salbutamol nebulization, and elimination of potassium from the body via hemodialysis or sodium-potassium exchange resin binders [10]. The recommended regimen for insulin from the Heart Association and the Washington Manual of Critical Care is 10 units of regular IV insulin with 25 g dextrose [11]. Despite concurrent administration of dextrose with insulin, some patients develop serious adverse drug events such as hypoglycemia. Behavioral abnormalities, cognitive impairment, seizure, and death are associated with hypoglycemia [8]. Even a single episode of hypoglycemia in the setting of concomitant critical illness has been shown to be independently associated with increased mortality and morbidity [12]. Few studies have analyzed development of hypoglycemia after treatment with insulin and dextrose in hyperkalemic patients. Furthermore, most of the existing evidence on the incidence of hypoglycemia during treatment for hyperkalemia is based on retrospective record-based observational studies that suffered from incomplete data and other biases [13-18].
Therefore, our primary objective was prospective estimation of incidence of hypoglycemia in hyperkalemic patients treated with the standard dose of 10 units of IV insulin and dextrose, 10 ml of 10% calcium gluconate, and salbutamol nebulization. Additionally, we studied the timing of hypoglycemia development and associated factors.
A prospective observational study was conducted in the ED of All India Institite of Medical sciences located in Delhi, India, between January 2020 and August 2021. Our institute is one of the largest academic research institutes in India and our ED caters to approximately 100,000 patients per year. Ethical approval was obtained from the Ethics Committee of All India Institite of Medical sciences, New Delhi (No. IECPG- 623/28.11.2019). Written informed consent was obtained from the patients.
All adult patients (>18 years) presenting to the ED with blood potassium >5.5 mmol/L on initial venous/arterial blood gas with a blood glucose >70 mg/dl were eligible and included in the study. Patients receiving repeat correction for hyperkalemia with insulin and dextrose within 3 hours of first correction, cardiac arrest patients, patients with post-cardiopulmonary resuscitation status, and patients with initial blood glucose <70 mg/dl or >200 mg/dl were excluded from the study. In addition, this study was part of an MD thesis during the coronavirus disease 2019 (COVID-19) pandemic; thus, a convenience sample of 100 patients was available for the study. After obtaining informed consent, all relevant data were collected in pre-designed standardized proforma and included presenting complaint; demographic characteristics such as patient age, sex, comorbidities (e.g., diabetes, kidney disease, liver disease, malignancy, sepsis); and treatment received as documented by the treating physician. Venous/arterial blood gas analysis was performed for all patients meeting the eligibility criteria. Potassium and glucose values were recorded during hyperkalemia treatment. Patients with a potassium level >5.5 mmol/L on venous blood gas were given 10 units of human regular insulin with 25 g (50 ml 50%) dextrose infusion, 10 ml of 10% calcium gluconate IV, and salbutamol nebulization 10 mg in 4 ml of normal saline to correct hyperkalemia. Capillary blood glucose was monitored every hour for 3 hours to detect hypoglycemia (blood glucose <70 mg/dl) or severe hypoglycemia (blood glucose <54 mg/dl). If the patient developed hypoglycemia in the 3-hour period after hyperkalemic correction, the time was recorded and the patient was administered hypoglycemic correction with 25 g (50 ml 50%) of dextrose. The primary endpoint of the study was development of hypoglycemia within 3 hours of hyperkalemia correction and secondarily for outcome at 3 hours following treatment. This standardized treatment regimen was used for all patients to avoid errors due to differential drug use.
All the data were entered into a Microsoft Excel spread sheet. Data were summarized and analyzed using SPSS version 24 (IBM Corp.). Continuous data were expressed as either mean with standard deviation (SD) or median with IQR, and categorical data were expressed as frequency and percentage. Quantitative data were tested for normality using the Kolmogorov-Smirnov test/Shapiro-Wilk test. For comparison of categorical variables among hypoglycemic and non-hypoglycemic patients, chi-square test or Fisher’s exact test was used. Univariate and stepwise multivariate logistic regression analyses were performed to determine the associations of various factors with development of hypoglycemia and were adjusted for confounders. A P-value <0.05 was considered statistically significant.
A total of 100 patients was included in the present study. The flow of patients is presented in Figure 1. The proportion of male participants (69%) was higher than that of females (31%). The median age of the participants was 46 years (IQR, 30–60 years). The comorbidity profile of the study participants (n=100) is shown in Figure 2. ECG was performed in 65 participants and could not be performed for the remaining 35 patients before hyperkalemia correction because their potassium level was >7 mmol/L and there were symptoms that warranted immediate treatment for hyperkalemia. ECG changes associated with hyperkalemia were observed in 37 participants (57% of 65). Among those 37 patients, tall peak T waves were observed in 33 (89.2%), decrease in P wave amplitude was noted in 10 (27%), idioventricular rhythm in 4 (10.8%.), bradycardia and QRS widening in 3 (8.1%), and flattening of the T wave and prolonged PR interval in 1 patient each (2.7%).
Mean blood potassium level of study participants in blood gas at presentation was 6.24 mmol/L (SD, 0.66 mmol/L) and median potassium level was 6.1 mmol/L (IQR, 5.76–6.63 mmol/L). The mean blood glucose level of study participants in blood gas at presentation was 113.12 mg/dL (SD, 32.86 mg/dl) and median blood glucose level at presentation was 105 mg/dl (IQR, 91.23–133.75 mg/dl). The remaining blood parameters on blood gas analysis and blood investigations are presented in Table 1.
Development of Hypoglycemia and Associated Factors
Among the 100 participants studied, 44 developed hypoglycemia during the observation period and 10 developed severe hypoglycemia. Mean time for development of hypoglycemia was 1.2 hours (SD, 0.73 hours) and median time was 2 hours (IQR, 1–2 hours). The distributions of demographic variables, various comorbidities, and their association with development of hypoglycemia are shown in Table 2. Furthermore, 52.3% of hypoglycemic (23/44) and 30.4% of non-hypoglycemic (17/56) patients had low pretreatment blood glucose levels (≤100 mg/dl). There was a significant association between low pretreatment blood glucose levels and development of hypoglycemia (P<0.05). Thus, patients with low pretreatment blood glucose level <100 mg/dl had a 1.53-fold higher risk (95% CI for relative risk, 1.02–2.29) of developing hypoglycemia than those who had pretreatment blood glucose level >100 mg/dl. No other demographic or clinical variables were significantly associated with occurrence of hypoglycemia. In addition, the two groups showed comparable proportions of comorbidities, indicating that the groups did not differ based on the possible confounders. The numbers of patients developing hypoglycemia at 1, 2, and 3 hours are shown in Figure 3.
Multivariate Analysis: Logistic Regression
Binomial logistic regression was applied for multivariate analysis to estimate the effects of variables on hypoglycemia development. The first model was prepared considering all the variables. Because the dependent variable had 44 events (i.e., 44 patients developed hypoglycemia), subsequent models were prepared using four variables each. The choice of subsequent variables depended on clinical importance and evidence of significant effect on hypoglycemia development in the literature. To summarize, the various models prepared for multivariate analysis to determine the predictors of hypoglycemia revealed pretreatment blood glucose level, both as a continuous variable and a categorical variable (where low pretreatment blood glucose level was defined as <100 mg/dl), as a significant predictor of hypoglycemia development after adjusting for all the confounding variables. The odds of developing hypoglycemia changed at the rate of 0.021, 0.016, and 0.017 per 1 mg/dl increase in pretreatment blood glucose levels across various models, indicating that the coefficient for pretreatment blood glucose levels was similar across all models. The most parsimonious model that was statistically significant and explained the highest proportion of variability (Table 3) in the log odds of occurrence of hypoglycemia among all models included the four predictors of pretreatment blood glucose levels, serum urea levels, history of kidney disease, and history of diabetes mellitus. Although diabetes mellitus was associated with lower risk of hypoglycemia, increased serum urea levels and kidney disease were associated with increased risk of hypoglycemia in this model. However, these underlying comorbidities did not have a significant effect on development of hypoglycemia as shown in Table 3.
The incidence rates of hypoglycemia (44%) and severe hypoglycemia (10%) in our study were higher than those in most previous studies. Schafers et al. [13] conducted a retrospective analysis of medical records and reported an incidence of hypoglycemia (blood glucose level <70 mg/dl) of 8.7% and of severe hypoglycemia (blood glucose <40 mg/dl) of 2.3% (n=217), lower than our findings. Due to the retrospective design of that previous study, a large number of patient records could be accessed; however, their data lacked proper documentation and had inadequate as well as missing information. Similarly, lower rates of hypoglycemia incidence were reported in other retrospective studies, such as 17% by Scott et al. in 2018 [14], 19.8% by Jacob et al. in 2018 [15], 17.5% by Boughton et al. in 2019 [16], 22% by Aljabri et al. in 2019 [17], and 18.2% by Tee et al. in 2021 [9].
The systematic review by Harel and Kamel [18] reported an 18% incidence of hypoglycemia following treatment of hyperkalemia with insulin. However, most of the studies included in the systematic review had significant bias and were retrospective in nature. In a study by LaRue et al. [19] in 2017, the incidence of hypoglycemia was 28.6%. All the patients in that study received an additional 25 g of dextrose at 1 hour after treatment. After this supplementation, the incidence was 28.6%, indicating much higher incidence with the standard dose of 10 units of insulin and 25 g of dextrose than in our study.
Most studies estimating the incidence of hypoglycemia in patients being treated for hyperkalemia were conducted retrospectively through medical record review. In such an instance, missing or inaccurate recording of blood glucose can result in missed episodes of hypoglycemia. Because our study is one of the first few to estimate the incidence of hypoglycemia prospectively, the possibility of missed episodes was minimal. Other factors that could explain the discrepancy in incidence include difference in protocols for blood glucose measurement and treatment. Schafers et al. [13] measured glucose within 6 hours post-insulin treatment, possibly missing many asymptomatic hypoglycemic patients. Our study measured hourly blood glucose for 3 hours, allowing identification of many patients who became hypoglycemic after hyperkalemia treatment. Other reasons include differences in monitoring protocols and thresholds for severe hypoglycemia, such as 40 mg/dl in the study by Jacob et al. [15] versus 54 mg/dl in our study. In several other studies, lack of a standardized treatment protocol led to the administration of different doses of insulin, possibly affecting the estimates [13,14]. Despite reported variation in the incidence of hypoglycemia, the time of hypoglycemia development was similar across all studies, including ours (i.e., approximately 2 hours post-insulin administration). This warrants close glucose monitoring of hyperkalemic patients receiving insulin as treatment, especially in the initial few hours.
In our study, univariate analysis of hypoglycemic patients with non-hypoglycemic subjects with respect to comorbidities and biochemical markers revealed that only low pretreatment blood glucose was significantly associated with development of hypoglycemia, with a 1.53-fold higher risk of hypoglycemia in subjects with low pretreatment blood glucose (<100 mg/dl) (95% CI for relative risk, 1.02–2.29) than in individuals who did not have low pretreatment blood glucose. No other factors were significantly associated with hypoglycemia development. Multiple models were prepared and multivariate analysis was performed to determine the predictors of hypoglycemia. The models revealed pretreatment blood glucose level (both as continuous and categorical variables where the low pretreatment blood glucose was defined at blood glucose level <100 mg/dl) and serum urea were significant predictors of hypoglycemia development, indicating decreased odds of hypoglycemia development with increased pretreatment blood glucose and urea levels.
A significant association between pretreatment blood glucose level and development of hypoglycemia was reported by Scott et al. [14], Jacob et al. [15], Boughton et al. [16], Apel et al. [20], and Brown et al. [11]. Other authors have also shown such an association, but the results were not statistically significant. Pretreatment blood glucose was associated with development of hypoglycemia in most studies including ours. Thus, titration of insulin doses and strict blood glucose monitoring post-insulin administration are recommended.
Kidney disease has been observed in higher proportions in hypoglycemics than in non-hypoglycemics. Insulin requires a high degree of renal clearance for elimination from the body, and renal dysfunction may be associated with a greater likelihood of developing hypoglycemia. However, a significant association between the two has been reported in only a few studies. Diabetes was found to be protective in some studies, as in ours; however, the association was not statistically significant. The mean pretreatment blood glucose level is generally higher in patients with prior diagnosis of diabetes than in non-diabetics, possibly explaining their lower incidence of hypoglycemia.
Convenience sampling (non-random) was performed in our study, and the results might not be generalizable to a larger population. The duration of hypoglycemia monitoring was shorter than reported in previous studies and other parenteral or enteral forms of glucose were not considered. Because the study was performed in a single center, the generalizability of the results may be limited. Finally, the data collection did not include the complications arising from hypoglycemia during the treatment of hyperkalemia.
In our prospective study, the incidence of hypoglycemia in hyperkalemia patients treated with insulin was 44% and severe hypoglycemia occurred in 10% within 3 hours of observation. This rate was higher than previously recorded estimates based on retrospective studies. Our study is one of the first to adopt a prospective design to investigate the incidence of hypoglycemia in hyperkalemia patients and was conducted in the ED of a large tertiary care center using a standardized treatment protocol. The results demonstrated a high incidence of hypoglycemia during treatment for hyperkalemia with insulin and dextrose. Because hypoglycemia is a serious and neglected complication, development of a standardized protocol for hyperkalemia management is needed as well as monitoring for hypoglycemia in hyperkalemia patients.
Various protocols have been developed by different organizations to mitigate the development of hypoglycemia in hyperkalemia patients, such as the U.K. Renal Association guidelines (July 2020), Trust Protocol, and Rush protocol [9,20]. A single algorithm will not prevent all hypoglycemic events due to variability of patient response; thus, careful patient assessment and blood glucose monitoring should be used to prevent this complication. The development of a safer, effective protocol and dosing algorithms that consider patient specific factors, such as baseline blood glucose, with a goal of promoting better patient safety outcomes should be a priority in EDs.
Based on the results of our study, we propose a pretreatment glucose-based treatment protocol for hyperkalemic patients as follows. Pre-treatment blood glucose <100 mg/dl: 10 units of IV insulin infusion with 25 g of dextrose, 10 ml of 10% calcium gluconate, and salbutamol nebulization for hyperkalemia management, with an additional 25 g of dextrose administered at 1 hour posttreatment to prevent hypoglycemia. Active measurement of capillary blood glucose was performed hourly for the first 3 hours, followed by every 2 hours for the next 6 hours. Pre-treatment (100–200 mg/dl): 10 units of IV insulin infusion with 25 g dextrose, 10 ml 10% of calcium gluconate, and salbutamol nebulization were administered for hyperkalemia management. Active measurement of capillary blood glucose hourly for the first 3 hours was followed by assessment every 2 hours for the next 6 hours. Pre-treatment: (>200 mg/dl): 10 units of IV insulin infusion, 10 mL 10% of calcium gluconate, and salbutamol nebulization were administered for hyperkalemia management, with active measurement of capillary blood glucose hourly for the first 3 hours. Furthermore, due to the differences between our study and previous retrospective studies and considering the limitations, further multi-center studies should be conducted on this topic.
▪ Our study was conducted in the emergency department of a tertiary care hospital reporting a 44% hypoglycemia incidence (10% severe) within 3 hours of hyperkalemia treatment with insulin—surpassing previously documented rates.
▪ As the first prospective analysis in this domain, this study indicated an underestimation of hypoglycemia risk during hyperkalemia management with insulin and dextrose in contrast to prior retrospective studies.
▪ Our findings emphasize the need for standardized protocols for hyperkalemia management and integration of hypoglycemia monitoring strategies.

CONFLICT OF INTEREST

No potential conflict of interest relevant to this article was reported.

FUNDING

None.

ACKNOWLEDGMENTS

The study was part of the MD thesis of one of the authors (VC).

AUTHOR CONTRIBUTIONS

Conceptualization: VC, NJ, PA, SB, ME, TPS, AK, PRM. Data curation: VC, NJ, AKD. Formal analysis: VC, NJ. Methodology: VC, NJ, PA, SB, ME, TPS, AK, PRM. Project administration: all authors. Visualization: NJ, VC. Writing original draft: VC. Writing - review & editing: VC, NJ, PA, SB, ME, TPS, AK, PRM. All authors read and agreed to the published version of the manuscript.

Figure 1.
Flow of the patients in the study. ED: emergency department.
acc-2024-00661f1.jpg
Figure 2.
Comorbidity profile of study participants (n=100).
acc-2024-00661f2.jpg
Figure 3.
Development of hypoglycaemia in study participants (n=100).
acc-2024-00661f3.jpg
Table 1.
Baseline profile of study participants (n=100)
Parameter Mean±SD Median IQR
pH 7.29±0.11 7.31 7.23–7.37
pCO2 (mm Hg) 34.1±15.0 31.2 24.5–38.8
pO2 (mm Hg) 66.1±53.6 44.4 35.6–76.6
HCO3 (mmol/L) 16.6±5.9 16.6 12.1–20.5
Na+ (mmol/L) 133.0±6.6 132.9 128.6–137.5
K+ (mmol/L) 6.2±0.7 6.1 5.8–6.6
Glucose (mg/dl) 113.1±32.9 105.0 91.3–133.8
Lactate (mmol/L) 2.4±2.6 1.5 0.9–2.9
Hemoglobin (g/dl) 9.7±3.3 9.1 7.4–11.2
Total leukocytes (cells/μl) 14,294.3±13,944.2 12,000 7,350–15,925
Platelet (cells/μ) 168,573±130,101 154,500 96,250–217,500
Total bilirubin (mg/dl) 3.2±6.1 0.8 0.5–2.6
Serum creatinine (mg/dl) 6.0±5.7 3.9 1.9–9.5
Serum urea (mg/dl) 132.0±69.7 129 69.7–175.8

SD: standard deviation; IQR: interquartile range.

Table 2.
Comparison of hypoglycaemics and non-hypoglycaemics and association of factors with development of hypoglycaemia
Characteristic Hypoglycemics (n= 44) Non-hypoglycemics (n= 56) P-valuea) Relative risk (95% CI)
Male (%) 31 60.3 0.78 0.95 (0.66–1.37)
Age (yr), mean±SD 46±18 47±14 - -
Renal replacement therapy (%) 14 13 0.37 1.22 (0.80–1.9)
Diabetes mellitus (%) 6 13 0.23 0.78 (0.54–1.12)
Hypertension (%) 26 26 0.21 1.25 (0.89–1.78)
Malignancy (%) 4 3 0.70 1.33 (0.55–3.12)
Kidney disease (%) 20 19 0.24 1.25 (0.85–1.82)
Liver disease (%) 11 11 0.52 1.15 (0.73–1.82)
Congestive heart failure (%) 1 3 0.63 0.74 (0.40–1.34)
Sepsis (%) 15 15 0.49 1.18 (0.78–1.76)

SD: standard deviation.

a)Chi-square test/Fisher’s exact test.

Table 3.
Results of most parsimonious binary logistic regression applied for estimating the effect of pretreatment glucose, serum urea, diabetes mellitus and kidney disease
Variable Coefficient Significance level OR CI for OR P-value of the model Nagelkerke’s R2
Pretreatment glucose level –0.017 0.047 0.984 0.968–1.000 0.014 0.2
Serum urea 0.011 0.009 1.101 1.003–1.020
H/o DM –0.722 0.267 0.486 0.136–1.740
H/o kidney disease 0.039 0.944 1.040 0.351–3.080

OR: odds ratio; H/o: history of; DM: diabetes mellitus.

  • 1. Long B, Warix JR, Koyfman A. Controversies in management of hyperkalemia. J Emerg Med 2018;55:192-205.ArticlePubMed
  • 2. Kline JA, Weisberg LS. Acid-base, electrolyte, and metabolic abnormalities. In: Parrillo JE, , Dellinger RP. In: Critical care medicine: principles of diagnosis and management in the adult. Elsevier. 2008, pp 1203-43.
  • 3. Mount DB. Disorders of potassium balance. In: Yu AS, Chertow GM, Luyckx V, Marsden A, Skorecki K, Taal MW, editors. Brenner and Rector's the kidney. Elsevier; 2008. p. 547-87.
  • 4. Brown RS. Potassium homeostasis and clinical implications. Am J Med 1984;77(5A):3-10.ArticlePubMed
  • 5. Fischer KF, Lees JA, Newman JH. Hypoglycemia in hospitalized patients: causes and outcomes. N Engl J Med 1986;315:1245-50.ArticlePubMed
  • 6. Gerich JE, Meyer C, Woerle HJ, Stumvoll M. Renal gluconeogenesis: its importance in human glucose homeostasis. Diabetes Care 2001;24:382-91.ArticlePubMed
  • 7. McNicholas BA, Pham MH, Carli K, Chen CH, Colobong-Smith N, Anderson AE, et al. Treatment of hyperkalemia with a low-dose insulin protocol is effective and results in reduced hypoglycemia. Kidney Int Rep 2017;3:328-36.ArticlePubMedPMC
  • 8. Truhlář A, Deakin CD, Soar J, Khalifa GE, Alfonzo A, Bierens JJ, et al. European Resuscitation Council Guidelines for Resuscitation 2015: Section 4. Cardiac arrest in special circumstances. Resuscitation 2015;95:148-201.ArticlePubMed
  • 9. Tee SA, Devine K, Potts A, Javaid U, Razvi S, Quinton R, et al. Iatrogenic hypoglycaemia following glucose-insulin infusions for the treatment of hyperkalaemia. Clin Endocrinol (Oxf) 2021;94:176-82.ArticlePubMedPDF
  • 10. Acker CG, Johnson JP, Palevsky PM, Greenberg A. Hyperkalemia in hospitalized patients: causes, adequacy of treatment, and results of an attempt to improve physician compliance with published therapy guidelines. Arch Intern Med 1998;158:917-24.ArticlePubMed
  • 11. Brown DR, Brown CC, Delay TA, Hayes GL, Campbell RC. Incidence of hypoglycemia in patients with renal dysfunction treated for hyperkalemia with regular insulin: a single center, retrospective cohort study. Int Arch Clin Pharmacol 2019;5:018. Article
  • 12. Fisch C. Relation of electrolyte disturbances to cardiac arrhythmias. Circulation 1973;47:408-19.ArticlePubMed
  • 13. Schafers S, Naunheim R, Vijayan A, Tobin G. Incidence of hypoglycemia following insulin-based acute stabilization of hyperkalemia treatment. J Hosp Med 2012;7:239-42.ArticlePubMedPDF
  • 14. Scott NL, Klein LR, Cales E, Driver BE. Hypoglycemia as a complication of intravenous insulin to treat hyperkalemia in the emergency department. Am J Emerg Med 2019;37:209-13.ArticlePubMed
  • 15. Jacob BC, Peasah SK, Chan HL, Niculas D, Shogbon Nwaesei A. Hypoglycemia associated with insulin use during treatment of hyperkalemia among emergency department patients. Hosp Pharm 2019;54:197-202.ArticlePubMedPMCPDF
  • 16. Boughton CK, Dixon D, Goble E, Burridge A, Cox A, Noble-Bell G, et al. Preventing hypoglycemia following treatment of hyperkalemia in hospitalized patients. J Hosp Med 2019;14:284-7.ArticlePubMed
  • 17. Aljabri A, Perona S, Alshibani M, Khobrani M, Jarrell D, Patanwala AE. Blood glucose reduction in patients treated with insulin and dextrose for hyperkalaemia. Emerg Med J 2020;37:31-5.ArticlePubMed
  • 18. Harel Z, Kamel KS. Optimal dose and method of administration of intravenous insulin in the management of emergency hyperkalemia: a systematic review. PLoS One 2016;11:e0154963.ArticlePubMedPMC
  • 19. LaRue HA, Peksa GD, Shah SC. A comparison of insulin doses for the treatment of hyperkalemia in patients with renal insufficiency. Pharmacotherapy 2017;37:1516-22.ArticlePubMedPDF
  • 20. Apel J, Reutrakul S, Baldwin D. Hypoglycemia in the treatment of hyperkalemia with insulin in patients with end-stage renal disease. Clin Kidney J 2014;7:248-50.ArticlePubMedPMC

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        Incidence of hypoglycemia in hyperkalemia patients after treatment with insulin and dextrose in the emergency department of a tertiary care hospital in India: a prospective observational study
        Acute Crit Care. 2024;39(4):499-506.   Published online November 22, 2024
        DOI: https://doi.org/10.4266/acc.2024.00661
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      Incidence of hypoglycemia in hyperkalemia patients after treatment with insulin and dextrose in the emergency department of a tertiary care hospital in India: a prospective observational study
      Image Image Image
      Figure 1. Flow of the patients in the study. ED: emergency department.
      Figure 2. Comorbidity profile of study participants (n=100).
      Figure 3. Development of hypoglycaemia in study participants (n=100).

      Figure 1.

      Figure 2.

      Figure 3.

      Incidence of hypoglycemia in hyperkalemia patients after treatment with insulin and dextrose in the emergency department of a tertiary care hospital in India: a prospective observational study
      Parameter Mean±SD Median IQR
      pH 7.29±0.11 7.31 7.23–7.37
      pCO2 (mm Hg) 34.1±15.0 31.2 24.5–38.8
      pO2 (mm Hg) 66.1±53.6 44.4 35.6–76.6
      HCO3 (mmol/L) 16.6±5.9 16.6 12.1–20.5
      Na+ (mmol/L) 133.0±6.6 132.9 128.6–137.5
      K+ (mmol/L) 6.2±0.7 6.1 5.8–6.6
      Glucose (mg/dl) 113.1±32.9 105.0 91.3–133.8
      Lactate (mmol/L) 2.4±2.6 1.5 0.9–2.9
      Hemoglobin (g/dl) 9.7±3.3 9.1 7.4–11.2
      Total leukocytes (cells/μl) 14,294.3±13,944.2 12,000 7,350–15,925
      Platelet (cells/μ) 168,573±130,101 154,500 96,250–217,500
      Total bilirubin (mg/dl) 3.2±6.1 0.8 0.5–2.6
      Serum creatinine (mg/dl) 6.0±5.7 3.9 1.9–9.5
      Serum urea (mg/dl) 132.0±69.7 129 69.7–175.8
      Characteristic Hypoglycemics (n= 44) Non-hypoglycemics (n= 56) P-valuea) Relative risk (95% CI)
      Male (%) 31 60.3 0.78 0.95 (0.66–1.37)
      Age (yr), mean±SD 46±18 47±14 - -
      Renal replacement therapy (%) 14 13 0.37 1.22 (0.80–1.9)
      Diabetes mellitus (%) 6 13 0.23 0.78 (0.54–1.12)
      Hypertension (%) 26 26 0.21 1.25 (0.89–1.78)
      Malignancy (%) 4 3 0.70 1.33 (0.55–3.12)
      Kidney disease (%) 20 19 0.24 1.25 (0.85–1.82)
      Liver disease (%) 11 11 0.52 1.15 (0.73–1.82)
      Congestive heart failure (%) 1 3 0.63 0.74 (0.40–1.34)
      Sepsis (%) 15 15 0.49 1.18 (0.78–1.76)
      Variable Coefficient Significance level OR CI for OR P-value of the model Nagelkerke’s R2
      Pretreatment glucose level –0.017 0.047 0.984 0.968–1.000 0.014 0.2
      Serum urea 0.011 0.009 1.101 1.003–1.020
      H/o DM –0.722 0.267 0.486 0.136–1.740
      H/o kidney disease 0.039 0.944 1.040 0.351–3.080
      Table 1. Baseline profile of study participants (n=100)

      SD: standard deviation; IQR: interquartile range.

      Table 2. Comparison of hypoglycaemics and non-hypoglycaemics and association of factors with development of hypoglycaemia

      SD: standard deviation.

      Chi-square test/Fisher’s exact test.

      Table 3. Results of most parsimonious binary logistic regression applied for estimating the effect of pretreatment glucose, serum urea, diabetes mellitus and kidney disease

      OR: odds ratio; H/o: history of; DM: diabetes mellitus.

      Table 1.

      Table 2.

      Table 3.

      ACC : Acute and Critical Care
      © The Korean Society of Critical Care Medicine.
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