Pattern of Electrolyte Imbalance in Stroke Patients With Type I Diabetes Mellitus Admitted in a Tertiary Care Hospital: A Cross-Sectional Study
1 Background
Stroke is the second leading cause of death worldwide and the most common cause of permanent disability [1]. Patients with diabetes have a 1.5–2 times higher risk of stroke compared to the general population, and this risk increases with the duration of diabetes [2]. Stroke-related mortality can result from either the primary disease or complications, with dyselectrolytemia being one of the major contributors. Sodium and potassium imbalances are among the most frequent electrolyte disturbances observed in acute stroke patients. These imbalances primarily arise due to abnormal secretion of antidiuretic hormones (ADH), elevated levels of atrial and brain natriuretic peptides, vomiting, and improper fluid management, which can lead to severe complications such as seizures and even death [3].
A study among Bangladeshi stroke patients found that 70% of acute stroke cases had electrolyte disturbances [4]. Additionally, two separate studies from Pakistan and Bangladesh reported that 35% of acute stroke patients experienced hypokalemia. Hyponatremia, in particular, has been linked to a 70% mortality rate among stroke patients [3, 5]. These electrolyte imbalances can be further exacerbated by insulin deficiency, excess glucagon, and acidosis, all of which are common in diabetic patients [6].
Despite the clinical significance of electrolyte disturbances in stroke patients with diabetes mellitus, there is limited data on their prevalence, particularly in developing countries. This study aimed to determine the patterns of electrolyte imbalances in acute stroke patients with type II diabetes mellitus admitted to a tertiary care hospital in Bangladesh. By identifying the most common electrolyte disturbances in this high-risk patient population, the study may provide valuable insights for improved clinical management in the future.
2 Methods
2.1 Study Design and Setting
This cross-sectional study was conducted among acute stroke patients with type II diabetes mellitus in the Department of Medicine at Sir Salimullah Medical College and Mitford Hospital, Dhaka. Data collection was carried out from March to August 2022.
2.2 Sample Criteria
Acute stroke patients with type II diabetes mellitus who presented within 48 h of onset, were admitted to the inpatient department of the aforementioned hospital, were over 18 years of age, and were willing to participate, were included in the study. Patients with type I or gestational diabetes, those experiencing diabetic emergencies, or those who had undergone recent surgery or trauma were excluded.
2.3 Sample Size
A significant proportion of stroke patients (16%–24%) either have diabetes or are later diagnosed with it, with estimates possibly reaching 30% in this hospital [7]. Based on 80% power and a 5% margin of error, the required sample size is 100 stroke patients.
2.4 Data Collection Procedure
Sociodemographic and diagnosis-related data were collected from the hospital case sheets. Within 24 h of admission, 5 mL of venous blood was collected aseptically in a vacutainer tube by trained nurses in the Department of Medicine. Biochemical analysis included serum sodium, serum potassium, serum bicarbonate, serum chloride, serum calcium, serum magnesium, serum phosphate, serum creatinine, and random blood sugar. Blood samples for biochemical analysis were analyzed using the Automated Analyzer: Atellica, Siemens, Germany, in the Biochemistry Department. Afterward, reports were collected and recorded in the data collection form. At the end of the study, we gathered the patient outcomes (death or discharge) from the hospital records.
2.5 Data Analysis
All data were analyzed by SPSS version 22.0 after editing and logical checking. Categorical variables such as sociodemographic data and electrolyte imbalance patterns were reported as frequency and percentage. Continuous variables such as biochemical reports were presented in mean, SD, and median as appropriate.
2.6 Ethical Considerations
Ethical approval (Approval No.: BCPS/44235; Date: 01/01/2022) for the research was obtained from the Ethical Review Committee of Bangladesh College of Physicians and Surgeons (BCPS). The written informed consent was taken from all the eligible patients and/or their primary caregivers.
3 Results
The majority (60%) of patients were male and the mean age of the participants was 58.49 ± 12.53 years. Nearly half (42%) of the patients were in 51–60 years age group. More than half (58%) of patients had ischemic stroke, followed by hemorrhagic stroke (41%) and only 1% had multiple infarcts. Half (52%) of the patients had hypertension, and 19% had ischemic heart disease (IHD) in addition to diabetes. The mean value of random blood sugar (12.74 ± 2.29) showed poor glycemic control (Table 1).
| Variables | Frequency | Percentage |
|---|---|---|
| Sex | ||
| Male | 60 | 60.0 |
| Female | 40 | 40.0 |
| Age | ||
| ≤ 40 | 5 | 5.0 |
| 41–50 | 26 | 26.0 |
| 51–60 | 42 | 42.0 |
| ≥ 61 | 27 | 27.0 |
| Mean ± SD | 58.49 ± 12.53 (30–92) | |
| Comorbidities | ||
| Diabetes (type II) | 100 | 100.0 |
| Hypertension | 52 | 52.0 |
| Heart disease | 19 | 19.0 |
| Type of stroke | ||
| Ischemic stroke | 58 | 58.0 |
| Multiple infarcts | 1 | 1.0 |
| Hemorrhagic stroke | 41 | 41.0 |
| Biochemical variables | Mean ± SD | Min–Max |
|---|---|---|
| Serum electrolytes | ||
| Sodium (mmol/L) | 136.68 ± 5.85 | 109.00–145.00 |
| Potassium (mmol/L) | 3.90 ± 0.62 | 2.29–5.80 |
| Bicarbonate (mmol/L) | 30.32 ± 2.56 | 24.00–38.00 |
| Chloride (mmol/L) | 98.18 ± 5.96 | 63.00–112.00 |
| Serum creatinine | 1.13 ± 0.29 | 0.80–2.30 |
| Blood Sugar | ||
| Random blood sugar (mmol/L) | 12.74 ± 2.29 | 8.30–22.90 |
Nearly half (42%) of the patients had hyponatremia, 12% had hypokalemia, and 2% had hyperkalemia. One patient developed hypercalcemia, one developed hypomagnesaemia, one developed hypocalcaemia, and one developed hypophosphatemia, while the remaining 13% reported hypochloremia. By the end of the study period, 16.1% of patients with electrolyte imbalances had died, while the remaining 83.9% were discharged home (Table 2).
| Serum electrolytes | Frequency | Percentage |
|---|---|---|
| Hyponatremia (Na < 135 mmol/L) | 42 | 42.0 |
| Hypokalemia (K < 3.5 mmol/L) | 12 | 12.0 |
| Hyperkalemia (K > 5.5 mmol/L) | 2 | 2.0 |
| Hypercalcemia (ionized Ca > 2.6 mmol/L) | 1 | 1.0 |
| Hypocalcaemia (ionized Ca < 2.6 mmol/L) | 1 | 1.0 |
| Hypomagnesaemia (Mg < 0.70 mmol/L) | 1 | 1.0 |
| Hypophosphatemia (PO4 < 0.65 mmol/L) | 1 | 1.0 |
| Hypochloremia (Cl < 96 mmol/L) | 13 | 13.0 |
| No electrolyte imbalance | 44 | 44.0 |
| Outcome (n = 56) | ||
| Death | 9 | 16.1 |
| Discharge | 47 | 83.9 |
4 Discussion
Nearly two-thirds (69%) of the stroke patients in our study were aged over 50 years. Our findings contrast with those of a meta-analysis, where stroke is more commonly reported among younger diabetic patients under 45 years [2]. However, another study reported that the incidence of stroke increases significantly with age, with two-thirds of all strokes occurring in people aged 75–85 years [8]. The difference in our results may be due to the presence of other concurrent comorbidities such as hypertension and IHD.
We also found that most of the patients presented with high blood sugar levels and various types of electrolyte imbalances. The most common type of electrolyte imbalance was hyponatremia. Our findings are similar to those of previous studies, where hyponatremia is commonly found among stroke patients [3, 5, 9-11]. However, the percentage of hyponatremia in our study is slightly higher than in previous studies, possibly due to the presence of poor glycemic control among our patients [3, 5, 6, 9]. Two other electrolyte imbalances observed were hypokalemia and hyperkalemia. Diabetic patients presenting with stroke are very vulnerable to developing potassium imbalances, and poor glycemic control also contributes to this [4, 6]. However, the presence of potassium imbalances was much lower among our patients compared to previous studies [3, 5, 10]. Additionally, 17% patients in our study presented with other electrolyte imbalances such as hypercalcemia, hypocalcemia, hypophosphatemia, hypomagnesaemia, and hypochloremia. A systematic review, however, suggests that electrolyte imbalances such as hypomagnesaemia and hypercalcemia are often overlooked and are associated with poor functional outcomes in acute stroke patients [10, 12, 13].
Additionally, 16.1% of the patients with electrolyte imbalances in our study died during the study period. Our findings are mostly consistent with previous studies [10, 14]. Although we did not investigate the association between mortality rate and type of electrolyte imbalances in our patients, several studies have reported that electrolyte imbalances, particularly hyponatremia and hypokalemia, are strongly associated with mortality in stroke patients, regardless of the presence of other comorbidities.
5 Conclusion
Acute stroke patients presented with type II diabetes mellitus are very vulnerable to develop dyselectrolytemia. This study highlights the prevalence of different electrolyte imbalances among stroke patients with type II diabetes mellitus, with hyponatremia being the most common disturbance, followed by hypokalemia and hyperkalemia. These findings underscore the importance of early and routine electrolyte monitoring in stroke patients with diabetes, regardless of their reason for admission.
6 Limitations
Our study has several limitations. First, it was conducted at a single center with a small sample size, limiting the generalizability of the findings. Additionally, the study did not explore the association between other comorbidities and diabetes on electrolyte levels. Furthermore, we did not investigate the effects of medications, stroke type, or other sociodemographic variables on the electrolyte status of the study population.
Author Contributions
Romena Hassan: conceptualization, investigation, funding acquisition, writing – original draft, methodology, validation, visualization, writing – review and editing, software, formal analysis, project administration, data curation, supervision, resources. Afroja Alam: conceptualization, investigation, funding acquisition, writing – original draft, methodology, validation, visualization, writing – review and editing, formal analysis, project administration, data curation, resources. Mahbuba Yesmin: conceptualization, investigation, funding acquisition, writing – original draft, methodology, validation, visualization, writing – review and editing, software, formal analysis, project administration, data curation, supervision, resources. Rifat Jahan: writing – review and editing, writing – original draft. Sayeda Sharmin Quadir: writing – original draft, writing – review and editing, supervision.
Acknowledgments
The authors gratefully acknowledge the contribution of Dr. Md. Matiur Rahman, Associate Professor, Department of Medicine, Sir Salimullah Medical College and Mitford Hospital, Dhaka, for his guidance in conducting this study. The authors received no specific funding for this work.
Ethics Statement
Ethical approval (Approval No.: BCPS/44235; Date: 01/01/2022) for the research was obtained from the Ethical Review Committee of Bangladesh College of Physicians and Surgeons (BCPS), Mohakhali, Dhaka.
Consent
The written informed consent was taken from all the eligible patients and/or their primary caregivers.
Conflicts of Interest
The authors declare no conflicts of interest.
Transparency Statement
The lead author Romena Hassan affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.
Open Research
Data Availability Statement
All data relevant to the study are available upon request to the corresponding author. All authors have read and approved the final version of the manuscript. Dr. Afrjoa Alam had full access to all of the data in this study and takes complete responsibility for the integrity of the data and the accuracy of the data analysis.
