Acute kidney injury (AKI) is a critical medical condition marked by a sudden decline in kidney function, often resulting from various medical issues, including cerebrovascular accidents (CVA). The development of AKI in patients with ischemic or hemorrhagic strokes has become increasingly acknowledged as a major factor affecting patient outcomes. Research on AKI has shown that it is associated with longer hospital stays, increased mortality, and long-term negative consequences.1,2

Tests for renal function, especially serum creatinine and blood urea levels, play a vital role in diagnosing AKI and forecasting patient prognoses. Elevated levels of these renal markers are closely associated with higher mortality rates and unfavorable outcomes following acute medical incidents like myocardial infarction and cardiac procedures.3,4 In situations such as Systemic Inflammatory Response Syndrome and sepsis, prompt detection and treatment of AKI are crucial for enhancing patient results.5,6

The causes and mechanisms behind acute kidney injury (AKI) in stroke patients involve various processes, such as fluctuations in blood flow, inflammation, and endothelial dysfunction. These elements play a role in both the emergence and worsening of kidney impairment, further deteriorating the patient's overall health.7,8 Additionally, chronic kidney disease is identified as a possible contributing factor to strokes, indicating a reciprocal relationship between renal function and cerebrovascular health.9,10

Recent guidelines and definitions, such as those provided by KDIGO, have highlighted the significance of early detection and intervention in acute kidney injury (AKI) to reduce its effects on patient outcomes. Despite these initiatives, the relationship and incidence of AKI in patients with cerebrovascular accidents continue to be a crucial area that is underexplored in research.

This study aims to clarify the incidence and prevalence of AKI in patients with cerebrovascular accidents and assess the predictive value of renal parameters in understanding the outcomes for both stroke subtypes.11,12 By improving our comprehension of these connections, we aspire to guide clinical practices and contribute to the ongoing improvement of investigation and treatment protocols for this at-risk patient population.

OBJECTIVES:  

1. To determine the incidence of acute kidney injury (AKI) in patients admitted with cerebrovascular accidents (stroke).
2. To assess changes in renal function parameters (serum creatinine, blood urea nitrogen, eGFR) in stroke patients over time.
3. To evaluate the association between AKI and stroke subtypes (ischemic vs. hemorrhagic) in terms of severity and clinical outcomes.
4. To determine whether early renal dysfunction (within 72 hours) predicts worse clinical outcomes (e.g., mortality, disability, hospital stay duration) in stroke patients.
5. To investigate potential risk factors (e.g., hypertension, diabetes, nephrotoxic drugs) contributing to AKI development in stroke patients.

Study Design: Longitudinal case series study.   

Study area:  The study was conducted in Department of General Medicine, Teaching hospital AIMSR & District headquarters hospital, Chittoor.

Study Period: November 2022- October 2023.    

Study population: Patients admitted in medical ward at AIMSR & DHH, Chittoor with Cerebrovascular Accident (ischemic and hemorrhagic), diagnosis is based on clinical presentation and confirmation is made by computed tomography.

Sample size: The study consisted of a total of 60 cases.

60 patients admitted in the department of General Medicine at AIMSR&DHH, Chittoor. After diagnostic confirmation of stroke based on clinical presentation and imaging (Computed tomography or MRI), their renal parameters will be studied with respect to both the subtypes of stroke.

Purposive sampling and attempt will be made to enroll consequently to the extent possible.

Where, n – sample size, σ - population standard deviation, E - margin of error, zα/2 - is to be calculated for 99% confidence interval.

The sample size for the study is 60 based on estimating the incidence rate with confidence level of 95% and relative perception of 0.25

Sampling Technique:  Purposive sampling.   

Inclusion Criteria:

• Enrolment included patients of all ages and both sexes who were admitted for ischemic and hemorrhagic stroke during the research period.
• Patients who signed the Informed consent.
• Patients who stayed in the hospital for at least five days duration.

Exclusion criteria:

• Patients with Subarachnoid haemorrhage
• Brain tumor
• Head trauma
• Patients denying consent
• Transient Ischemic Attack patients
• Patient with known kidney disease or previous dialysis
• Patient who died within two days of admission.

Ethical consideration: Institutional Ethical committee permission was taken before the commencement of the study.

Study tools and Data collection procedure:

According to the Proforma, pre-specified questions will be posed to each participant. We will draw blood samples to use in our laboratory research. Clinical presentation and head computed tomography reveal the presence of ischemic/ hemorrhagic stroke. Investigations on renal parameters were conducted on the day of admission, after 24 hours, 48 hours, 72 hours and 96 hours. Data is entered in MS Excel Sheet and will be analysed for proportions, rates and ratios. Where applicable, Averages, median, standard deviation will be calculated. Statistical tests of significance will be applied if appropriate. The statistical tools (chi-square test) and software (SPSS version22.0) if any used to be described. Review or follow up for a period of 4 weeks by advising the patients to attend the outpatient department or by phone call (in case patient cannot attend the OP). Informed consent and inclusion of patients meeting the study criteria are ensured. This approach upholds the principles of patient autonomy and transparency in the research process.

Statistical analysis:

Data was entered into Microsoft Excel and analysis was done using IBM Statistical for the Social Science (SPSS) version 22. Descriptive and frequency analysis was done. Mean and Standard deviation were used for continuous variables. The chi-square test and Mann-Whitney U test were used to find the associations and a p-value less than 0.05 was considered significant.

Table 1: Shows the data interpretation of age in the (N=60) study population.

The age distribution of research population is displayed, with a minimum age of 40 years and a highest age of 87 years, the mean ± SD is 62.36 ± 11.31. 54% of the study's participants are females, while 46% are males.

Table 2: Data interpretation of Urea level in the (N=60) study population

Table 3: Data interpretation of creatinine level in the study population (N = 60)

Table 4: Data interpretation of eGFR in the study population (N=60)

Table 5: Mean Age comparison between stroke types (N=60)

The stroke type and age distribution are displayed in the above table, which is statistically significant.

The stroke variants sex-wise distribution is not statistically significant.

Table 6: Diabetic mellitus comparison by stroke type (N=60)

The existence of diabetes mellitus in the hemorrhagic and ischemic forms is displayed in the above table and bar chart. Diabetes has a statistically significant correlation with the ischemic variation compared to the hemorrhagic form (P value <0.001), suggesting that it is a substantial risk factor for renal failure.

Systemic hypertension is present in both hemorrhagic and ischemic patients, as seen by the above table and bar chart, however there is no statistically significant difference between the two variables in this study.

Table 7: Mean level of Blood Urea comparison by stroke subtype (N = 60)

The comparison of mean urea between the ischemic and hemorrhagic variations. The Unpaired t test P value <0.001 indicates that the difference is statistically significant.

Table 8: Mean level of Creatinine by stroke subtype (N = 60) Comparison

The mean creatinine for the ischemic and hemorrhagic variations with time. A difference between the two variants that is statistically significant is shown by an Unpaired t test P value of less than 0.0001.

Table 9: Mean eGFR comparison by type (N=60)

The study finds a statistically significant difference (Unpaired t test P value less than 0.001) between the GFRs of the ischemic and hemorrhagic variations.

Our research highlights the notable prevalence of acute kidney injury (AKI) in patients who have suffered cerebrovascular accidents (CVA), covering both ischemic and hemorrhagic strokes. Our findings reveal that AKI is a frequent and serious complication among stroke patients, emphasizing the essential need for careful monitoring and timely intervention.

This discussion will examine the ramifications of our results, comparing them with the current literature and investigating the possible mechanisms that lead to AKI in stroke individuals. Moreover, we will assess the predictive capability of renal function tests, such as serum creatinine levels and estimated glomerular filtration rate (eGFR), in assessing patient outcomes following a stroke. By comprehending these connections, we seek to provide insights that could guide clinical practices and enhance patient management approaches, ultimately improving recovery and lowering mortality rates in this at-risk population.

The mean age of patients with AKI in CVA in the study (62.36 ± 11.31 years) is correlating with results of former researches, reporting older adults, particularly those in their early 60s, are at a higher risk of developing AKI following a stroke. There is statistically significant risk of AKI following Ischemic stroke than hemorrhagic stroke in older patients. This reinforces the importance of monitoring and managing kidney function in this age group to improve patient outcomes. Covic et al. (2008) investigated the impact of acute AKI on short-term survival following cerebrovascular accident, mean age of this population was 66.1 +/- 11.5 years.13 Khatri et al. (2014) explored the association between AKI and increased hospital mortality in CVA patients. Mean age of their population was 64 years.14 Kes et al. (2016) found that there is exponential raise in the incidence of stroke after thirty years of age leading to about 65% in the age group more than or equal to 65 years.15 In summary, our study's identification of older age as determinant of AKI post- stroke (mean age 62.36 ± 11.31 years) is consistently supported by various studies cited, emphasising the critical need for targeted monitoring and management of renal function in older stroke patients to improve clinical outcomes.

In this study of 60 CVA patients (33 females and 27 males), there’s a greater share of ischemic strokes in both genders compared to hemorrhagic strokes, with a notable imbalance between the number of female and male patients in each stroke category. Specifically:

• Ischemic Stroke: 76% of females (23 out of 33) vs. 63% of males (17 out of 27).
• Hemorrhagic Stroke: 30% of females (10 out of 33) vs. 37% of males (10 out of 27).

This implies, there can be a slight predominance of ischemic strokes among females compared to males in the research sample.

Kes et al.15 (2016) found significant sex and age differences in acute stroke hospital patients. Hiraga et al.16 (2017) discussed gender differences and stroke outcomes, highlighting that females have greater rate and worse outcomes after ischemic stroke, particularly due to longer life expectancy and the prevalence of risk factors such as atrial fibrillation, hypertension, hyperlipidemia. Girijala et al. (2017) studied the sexual dimorphism in stroke. The higher incidence and worse outcomes in women can be due to their long-life span.17

In this study population, 40 out of 60 patients were diabetic, and the distribution of diabetes mellitus among the stroke variants showed a statistically significant difference. Specifically, 80% (32/40) of ischemic stroke patients were diabetic, whereas 40% (8/20) of hemorrhagic stroke patients were diabetic, with a p- value <0.001. Chen et al.18 (2016) studied the association between Stroke and Diabetes and implied that Diabetes the significant modifiable risk factor of stroke is associated with higher mortality and worse outcomes post stroke especially in ischemic subtype. Kaarisalo et al.19 (2005) investigated the relationship between diabetes and the outcome ischemic stroke. Mehta et al.20 (2007) done a retrospective analysis on prevalence of DM in AKI patients post cardiac surgery and there is a prevalence of 49%, which is significantly higher compared to ones without AKI (30%).

In the research population, 28 out of 60 patients were hypertensive, with a higher prevalence of hypertension in ischemic stroke patients, 21 among 40 (51.5%) compared to hemorrhagic stroke patients, 7 among 20 (35%). This difference was not statistically significant. Lawes CM et al.21 (2004) conducted studies on stroke and relevance of blood pressure, the mean age of subjects was around 70 years and the results showed significant reduction (33.3%) in risk of stroke by reducing 10 mmHg of systolic blood pressure. Cipolla et al.22 (2018) explored the impact of comorbidities on ischemic stroke outcomes, emphasising that longstanding hypertension effects cerebral circulation leading to ischemic strokes. They identified hypertension as a critical modifiable risk factor of stroke which is also associated with worst outcome. The incidence of ischemic stroke was proportional to systolic and diastolic. Qureshi et al.23 (2001) have extensively reviewed the prevalence and risks associated with hypertension in stroke patients.

In the study, incidence of AKI was found in 11 individuals out of 60 CVA patients, which is 18%. Mean creatinine levels at admission were 1.23 ± 0.247 mg/dl, raising to 1.31 ± 0.27 mg/dl after 24 hours, 1.38 ± 0.34 mg/dl after 48 hours, and 1.43 ± 0.41 mg/dl by 72 hours and after 96 hours 1.42 ± 0.42 mg/dl. Creatinine levels at admission were 1.035 ± 0.20 mg/dl in hemorrhagic stroke patients and 1.332 ± 0.202 mg/dl in ischemic stroke patients (P <0.001). After 24 hours, creatinine levels were 1.15 ± 0.22 mg/dl in hemorrhagic stroke patients and 1.39 ± 0.254 mg/dl in ischemic stroke patients (P <0.0005) and after 48 hours it was 1.18 ± 0.10 mg/dl in hemorrhagic and 1.487 ± 0.35 in Ischemic stroke patients (P <0.0008) and by 72 hours it was 1.235 ± 0.12 mg/dl and 1.537 ± 0.435 mg/dl in hemorrhagic and ischemic stroke patients respectively (P <0.0005), and after 96 hours it was 1.235 ± 0.12 mg/dl and 1.522 ± 0.455 mg/dl in hemorrhagic and ischemic stroke patients respectively (P 0.00541).

Mean Urea levels at admission were 33.1 ± 6.09 mg/dl, raising to 39.48 ± 8.26 mg/dl after 24 hours, and to 44.13.40 ± 8.65 mg/dl after 48 hours and to 48.21 ± 9.9 mg/dl after 72 hours and after 96 hours it was 49.7 ± 10.03 mg/dl. Urea levels at admission were 29.55 ± 3.35 mg/dl in hemorrhagic stroke patients and 35 ± 6.34 mg/dl in ischemic stroke patients (P <0.0007), after 24 hours it was 33.3 ± 5.55 mg/dl in hemorrhagic and 42.575 ± 7.631 mg/dl in ischemic stroke patients (P <0.0001), after 48 hours it was 37.95 ± 6.82 mg/dl and 47.225 ± 7.776 mg/dl in hemorrhagic and ischemic stroke patients (P <0.0001) respectively and after 72 hours it was 40.6 ± 8.80 mg/dl and 52.025 ± 8.063 mg/dl in hemorrhagic and ischemic stroke patients respectively (P <0.0001) and after 96 hours it was 41.7 ±10.56 mg/dl and 53.7 ± 6.867 mg/dl in hemorrhagic and ischemic stroke patients (P <0.0001) respectively. The trend of eGFR at admission was 79.635 ± 19.38 ml/min/1.73 m² in hemorrhagic stroke and 51.905 ± 14.871 ml/min/1.73 m² in ischemic patients (P <0.0001); 70.11 ± 16.71 ml/min/1.73 m² in hemorrhagic stroke patients and 49.80 ± 15.586 ml/min/1.73 m² in ischemic stroke patients after 24 hours (P < 0.0001); 67.95 ± 15.76 ml/min/1.73 m² in hemorrhagic stroke patients and 47.17 ± 16.275 ml/min/1.73 m² in ischemic stroke patients after 48 hours (P < 0.0001), and after 72 hours it was 65.16 ± 17.08 ml/min/1.73 m² and 46.015 ± 15.621 ml/min/1.73 m² in hemorrhagic and ischemic stroke patients respectively (P <0.0001), after 96 hours it was 65.32 ± 18.08 ml/min/1.73 m² and 47.53 ± 18.381 ml/min/1.73 m² in hemorrhagic and ischemic stroke patients respectively (P <0.0008). There is statistically significant raise in serum creatinine and urea levels and decline in estimated Glomerular Filtration Rate in ischemic stroke patients compared to hemorrhagic stroke patients.

Khatri et al.14 (2014) conducted a study related to in-hospital mortality due to AKI and post stroke. And reported that AKI is a common cause of in-patient deaths admitted with either type of stroke. They reported that almost 79% of all Acute Kidney Injury was stage-1 according to AKIN, emphasising the importance of even minimal raise in serum creatinine levels in hospital stay. Arnold et al.24 (2018) conducted a systematic review and meta-analysis on the incidence and impact of acute kidney injury (AKI) after a stroke. They found that below par baseline renal function at admission was linked to increased frequency of AKI occurrence. It identified the determinants for development of AKI as worse renal function at admission, geriatric age group, high NIHSS score at admission and comorbidities like IHD and HFrEF/ HFpEF. This study correlates with our data showing high incidence of AKI in patients with deranged renal parameters at admission. This highlights the need for monitoring renal parameters at admission and paying attention to the ones with deranged kidney function.

Covic et al.13 (2008) reported the impact of AKI on short term survival in CVA patients. Frequency of AKI development is more in lower GFR and higher serum creatinine at baseline, old age, preexisting cardiac conditions like chronic heart failure or ischemic heart disease. The also reported baseline kidney function as an independent marker for short term survival after Acute Ischemic Stroke or Acute Hemorrhagic Stroke, and as a contributor for AKI post CVA. This correlates with my study demonstrating the widespread impact of renal impairment on stroke prognosis. Jiang et al.25 (2019) explored biomarkers predicting stroke-associated AKI and reported Serum Cystatin C levels at ICU admission as an important marker for predicting AKI and twenty-eight-day mortality. This paves a path for introducing Serum Cystatin C levels in studies on CVA and AKI in future.

Zorrilla-Vaca et al.25 (2018) conducted a meta-analysis that found that pooled prevalence of Acute Kidney Injury after Ischemic stroke was higher than that of hemorrhagic stroke but statistically insignificant. This correlates with my data showing high incidence of AKI post AIS in comparison to HS. They also found that AKI is a significant contributor of mortality in AIS patients. Grosjean et al.27 (2019) noted a higher incidence of AKI in hemorrhagic and cardioembolic stroke patients. They also reported that at administered NIHSS score and glomerular filtration rates as independent predictors of AKI development in hospitalised patients. This necessitates strict monitoring of renal parameters in hemorrhagic and cardioembolic stroke patients.

Kamouchi et al.28 (2013) identified the predictors for AKI development, which are ischemic stroke, baseline serum creatinine levels and infection related complications at admission. This correlates with my study for monitoring serum creatinine levels. Ischemic stroke patients on Edavarone had reduction in AKI development risk. Saeed et al.29 (2014) found that in Acute Kidney Injury patients post-Acute Ischemic Stroke patients there is increased in-hospital complications, death and disability in contrast to ones without AKI. This necessitates the constant renal function monitoring for early identification and intervention of AKI.

Anderson et al.35 (2011) conducted a study on AKI in geriatric age group. The structural changes (sclerosis of vessels, and glomeruli, weight reduction) and functional changes (fall in glomerular filtration rate, increased hydrostatic pressure of glomerular capillaries) that kidney undergoes with age makes it susceptible for AKI. AKI diagnosis is based on serum creatinine levels and/ glomerular filtration rate, but the creatinine levels are based on creatinine levels which is not only influenced by GFR but also by creatinine production, tubular secretion and muscle mass etc. also GFR and Serum Creatinine are late in occurrence to establish the diagnosis which further delays the management. So, markers like Cystatin C must be used to evaluate renal function and this establishes the need for research on novel biomarkers to predict and monitor kidney function.

AKI occurs in 18% of stroke patients, with a higher incidence in ischemic stroke (20%) than hemorrhagic stroke (15%). Older age, especially over 60, increases AKI risk, particularly after ischemic stroke (P <0.001). Diabetes is significantly more common in ischemic stroke patients (80% vs. 40%, P <0.001). Although hypertension is more prevalent in ischemic stroke, this was not statistically significant. Ischemic stroke patients also show worse kidney function, with higher serum creatinine and urea, and lower eGFR (P <0.001). These findings highlight the need for close renal monitoring, especially in ischemic stroke patients with diabetes

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