INTRODUCTION
Kidney impairment is not uncommon in patients presenting with acute ischemic stroke (AIS). The abnormal creatinine noted could be a due to acute kidney injury, chronic kidney disease (CKD) or both. CKD is characterized by irreversible structural or functional renal damage, and significant CKD is often defined in clinical literature as the sustained reduction in the estimated glomerular filtration rate (eGFR) below 60mL/min/1.73m2 with or without the presence of co-existing albuminuria for ≥ 3 months.1 Unlike the declining trends observed in multiple chronic disorders, recent data show that the prevalence of CKD in the United States is stable at about 15% of the adult population affected.2 CKD is a major independent risk factor for cardiovascular morbidity and mortality.3
Presence of CKD increases stroke risk by ~43% and increases mortality and adverse outcomes in AIS.4, 5 There is about a 7% increased risk of stroke for every 10mL/min/1.73m2 decrease in eGFR.6–8 Evidence further shows that low eGFR also increases the risk of hemorrhagic transformation in AIS.9 Among patients with intracerebral hemorrhage, CKD is associated with increased presence and number of cerebral microbleeds (CMB).10 CMB are an accumulation of small 2 to 10 mm foci of blood products that can be seen within the brain parenchyma on susceptibility-weighted imaging (SWI). CMB are associated with ischemic and hemorrhagic stroke and increased risk for dementia, cognitive decline, and mortality.11, 12 Both low eGFR and albuminuria have been associated with increased frequency and number of CMB among patients with ischemic stroke.13, 14 However, multiple variables including age, race, and etiology of CKD impact their presence and severity.14
Although some patients with kidney impairment at AIS have acute kidney injury, its overall prevalence has been reported to be low, but it has been shown to be associated with worse stroke outcomes.15, 16 The risk of death is 2–3 times higher in stroke patients with acute kidney injury.15, 16 In this study, we sought to evaluate the clinical and imaging characteristics and outcomes of AIS patients stratified by the presence of kidney impairment at the time of stroke presentation.
METHODS
Data source and study population
In our stroke center, patients with an admission diagnosis of AIS get a routine magnetic resonance imaging (MRI) brain unless there are contraindications for MRI, or if the patient is clinically unstable or claustrophobic. This retrospective observational study included consecutive AIS patients admitted to our tertiary comprehensive stroke center from July 2015 to June 2016. The Institutional Review Board at the University of Florida approved the study.
Patients with AIS were included in the study if they had interpretable diffusion-weighted imaging (DWI), SWI, and fluid-attenuated inversion recovery (FLAIR) sequences on MRI of the brain and if a stroke lesion was present on DWI. Patients were excluded if they had a transient ischemic attack, clinical diagnosis of ischemic stroke without stroke lesion on DWI, or uninterpretable MRI. Electronic medical records were reviewed for all included patients to abstract the relevant clinical, laboratory, and discharge data needed for the study. Discharge data included modified Rankin Scale (mRS) score and discharge disposition (home, home with home health services, acute inpatient rehabilitation, skilled nursing facility, long-term care facility, hospice, and death). Stroke etiology was determined by TOAST (Trial of Org 10172 in Acute Stroke Treatment) criteria.17 The National Institutes of Health stroke scale (NIHSS) score was used to quantify the severity of neurological deficits on a scale from 0 to 42. A higher score suggests more severe deficits. However, patients with lower NIHSS can still have severe disabling neurological deficits such as patients with isolated homonymous hemianopia or expressive aphasia with a NIHSS score of 2.
Estimated GFR was calculated based on CKD-EPI equation using patients’ admission creatinine, age, and gender. For the study, patients with admission eGFR ≥60 ml/min/1.73m2 were considered to have no kidney impairment. Patients with eGFR < 60 ml/min/1.73m2 were considered to have kidney impairment. Since some patients could have acute kidney injury when admitted for AIS, any previous documentation of creatinine more than 90 days from stroke admission, when available, was used to calculate eGFR and determine the presence of CKD.
Imaging protocol
MRI images were obtained from 1.5T Avanto or 3T Verio Siemens scanners as described in our previous study.18 Stroke protocol MRI included DWI, FLAIR, and SWI sequences. Typical parameters for DWI were TR/TE=4100/102 or 7300/80 or 8200/89 with b=0 and 1000 s/mm2, 4–5mm thickness; FLAIR TR/TE=9000/90 or 9000/126, 4mm thickness; and SWI, TR/TE=28/20 or 49/40, and 3mm thickness.
Imaging assessment
Two investigators blinded to clinical history independently evaluated the DWI, SWI, and FLAIR images.18 Any discrepancies in the image reading were resolved by consensus. The white matter hyperintensity (WMH) was evaluated on the FLAIR sequence using the semi-quantitative Fazekas rating scale (Table 1).19, 20 The total Fazekas score obtained from the sum of scores for D-WMH and PV-WMH was dichotomized as 0–3 (mild) versus 4–6 (severe) for analysis.
Table 1.
| Periventricular white matter hyperintensity | |
| Score 0 | No periventricular lesion |
| Score 1 | Caps or pencil-thin lining of the ventricle |
| Score 2 | Smooth halo around the ventricle |
| Score 3 | Irregular periventricular hyperintensities extending into the deep white matter |
| Deep white matter hyperintensity | |
| Score 0 | No deep white matter lesion |
| Score 1 | Punctate foci |
| Score 2 | Beginning confluence of foci |
| Score 3 | Large confluent areas |
Hemorrhagic transformation (HT) and CMB were evaluated on the SWI obtained during admission. The CMBs were classified using the Microbleed Anatomical Rating Scale (MARS),21 as it has good interrater reliability for presence of definite microbleeds. CMB were identified as circular, homogenously hypointense lesions measuring 2–10 mm in diameter on SWI. Hypointense lesions likely to be CMB mimics as described in MARS criteria were excluded. Basal ganglia calcifications that mimicked CMB were excluded by reviewing the CT head obtained at admission. Additionally, hypointense lesions were followed through sequential slices to exclude small vessels. CMB distribution was recorded and classified into lobar (frontal, parietal, temporal, occipital, insula), deep (basal ganglia, internal and external capsule, corpus callosum, thalamus, deep and periventricular white matte), and infratentorial (brainstem, cerebellum) per MARS scale. Definite and possible CMB were combined to obtain total count for analysis.
The Heidelberg bleeding classification system was used to classify HT.22 The hemorrhagic infarct (HI) was classified as HI1 or HI2 for scattered small petechiae or confluent petechiae without mass effect, respectively. Parenchymal hematoma (PH) was classified as PH1 or PH2 for hematoma occupying <30% or ≥30% with obvious mass effect of the infarcted tissues, respectively. Intraventricular hemorrhage, subdural hemorrhage, subarachnoid hemorrhage, and remote PH from the area of infarct were also noted.
Outcomes
The primary outcome was discharge outcome defined by mRS and discharge disposition. The mRS is a disability rating scale from 0–6, 0 indicates no symptoms, and 6 indicates death. Good functional outcome was defined as mRS 0, 1, or 2 at the time of discharge. Good discharge outcome was defined as discharge to home, home with home health services, and acute inpatient rehabilitation. Poor discharge outcome was defined as discharge to a skilled nursing facility, long-term care facility, hospice, and death. Secondary outcome was radiologically defined HT assessed on SWI. HT was also assessed among subgroup of patients with CMB and those who received alteplase.
Statistical analysis
The study dataset was divided into two groups ― patients with and without kidney impairment. Categorical variables were reported as percentages and analyzed with Chi-squared or Fisher’s exact test. Continuous variables were reported as mean with standard deviation or median with interquartile range and analyzed with univariate regression analysis to assess significance between two groups.
Multivariate logistic regression analysis was performed to evaluate the association of NIHSS score and WMH (Fazekas score) with kidney impairment. Pertinent significant variables in the unadjusted analysis and the variables considered as potential confounders were included as covariates. The covariates were demographics (age, sex, race) and medical history (hypertension, hyperlipidemia, transient ischemic attack, congestive heart failure, and tobacco use). To evaluate for factors associated with poor discharge outcomes, multivariate logistic regression analysis was performed with the above covariates and the NIHSS score, WMH (Fazekas score) and kidney impairment as independent variables.
Model goodness-of-fit was reported as c-statistic. The alpha level <0.05 was used for statistical significance. Odds ratio (OR) and 95% confidence intervals (CI) were reported for the results of regression models. Statistical analysis was performed using SAS version 9.4 SAS Institute Inc, Cary, NC.
RESULTS
Baseline characteristics
The study consisted of 285 patients. Among these 205 patients had eGFR ≥ 60mL/min/1.73m2, 69 patients had eGFR 30–59mL/min/1.73m2, and 11 patients had eGFR < 30mL/min/1.73m2 including seven patients on dialysis. A total of 30 (38%) patients had CKD defined as eGFR< 60mL/min/1.73m2 during admission for AIS and more than 90 days prior to stroke. Thirty-four (43%) patients did not have any prior creatinine tests performed and 16 (20%) patients had eGFR ≥ 60 mL/min/1.73m2 six months to 13 years prior to the stroke.
Patients with kidney impairment (eGFR < 60mL/min/1.73m2) were older than patients without kidney impairment (mean age ±SD: 74.7±12.9 vs 64.4±13.8 years, p<0.0001, Table 2). There was no difference in the sex, race, medical and social history between the two groups except that patients with kidney impairment were more likely to have hypertension (85% vs 74%, p=0.049), hyperlipidemia (49% vs 33%, p=0.01), previous transient ischemic attack (11% vs 5%, p=0.05), congestive heart failure (15% vs 6%, p=0.01), and less likely to have tobacco use (38% vs 54%, p=0.01, Table 2). Patients with kidney impairment had more neurological deficits on NIHSS score (median 8.5 vs 5, p=0.02) and stroke due to cardioembolism compared to patients without kidney impairment (Table 2).
Table 2.
Clinical characteristics
| Kidney Impairment Absent, n=205 |
Kidney Impairment Present, n=80 | p value | |
|---|---|---|---|
| Age, years, mean (SD) | 64.4 (13.8) | 74.7 (12.9) | <0.0001* |
| Sex, female, n (%) | 97 (47) | 43 (54) | 0.33 |
| Race, n (%) | |||
| 1. White | 167 (81) | 56 (70) | 0.10 |
| 2. Black | 37 (18) | 23 (29) | |
| 3. Other | 1 (1) | 1 (1) | |
| Ethnicity, Hispanic, n (%) | 9 (4) | 1 (1) | 0.29 |
| Past medical history, n (%) | |||
| 1. Hypertension | 152 (74) | 68 (85) | 0.049* |
| 2. Diabetes mellitus | 61 (30) | 31 (39) | 0.14 |
| 3. Hyperlipidemia | 68 (33) | 39 (49) | 0.01* |
| 4. Stroke | 47 (23) | 19 (24) | 0.88 |
| 5. Transient ischemic attack | 10 (5) | 9 (11) | 0.05 |
| 6. Atrial fibrillation | 32 (16) | 16 (20) | 0.37 |
| 7. Coronary artery disease | 39 (19) | 21 (26) | 0.18 |
| 8. Congestive heart failure | 12 (6) | 12 (15) | 0.01* |
| 9. Peripheral vascular disease | 4 (2) | 3 (4) | 0.40 |
| Social history, n (%) | |||
| 1. Tobacco use | 111 (54) | 30 (38) | 0.01* |
| 2. Alcohol use | 72 (35) | 20 (25) | 0.10 |
| Medication history, n (%) | |||
| 1. Antiplatelet | 76 (37) | 36 (45) | 0.22 |
| 2. Anticoagulants | 18 (9) | 7 (9) | 0.99 |
| 3. Antithrombotic (antiplatelet or anticoagulant) | 89 (43) | 41 (51) | 0.23 |
| Vitals sings, median (IQR) | |||
| 1. Systolic blood pressure, mm Hg | 153 (139–170) | 157 (136–179) | 0.11 |
| 2. Diastolic blood pressure, mm Hg | 85 (73–94) | 82 (69–98) | 0.53 |
| 3. Body mass index, kg/m2 | 27 (24–33) | 28 (25–34) | 0.20 |
| NIH stroke scale score, median (IQR)† | 5 (2–12) | 8.5 (3–17) | 0.02* |
| TOAST classification, n (%) | |||
| 1. Large artery disease | 41 (20) | 13 (16) | 0.04* |
| 2. Cardioembolism | 46 (22) | 31 (39) | |
| 3. Small vessel occlusion | 43 (21) | 14 (17) | |
| 4. Other determined etiology | 22 (11) | 3 (4) | |
| 5. Undetermined etiology | 53 (26) | 19 (24) | |
| Alteplase, n (%) | 55 (27) | 27 (34) | 0.25 |
| Last known well to CT head time, hours, median (IQR) | 8 (2–25) | 5 (2–17) | 0.05 |
SD = standard deviation; IQR = interquartile range;
Missing NIH stroke scale for 12 and 3 patients in kidney disease absent and present group respectively
p<0.05
Patients with kidney impairment had lower low-density lipoprotein (LDL) cholesterol (median 89 vs 102 mg/dL, p=0.05), lower hemoglobin (median 13 vs 14 g/dL, p<0.0001), and more severe WMH on FLAIR (Fazekas score 4–6: 55% vs 45%, p<0.0001) compared to no kidney impairment group (Table 3). CMBs were present in 85 (30%) patients – 66 patients had 1–5 CMBs, 7 patients had 6–10 CMBs, and 12 patients had >10 CMBs (range from 11 to 171). There was no difference in the number of CMBs between the two groups (34% vs 28%, p=0.37, Table 3). Table 4 shows the anatomical distribution of CMBs based on MARS scale.
Table 3.
Laboratory and imaging characteristics
| Kidney Impairment Absent, n=205 | Kidney Impairment Present, n=80 | p value | |
|---|---|---|---|
| Laboratory characteristics | |||
| Lipid profile, mg/dl, median (IQR) | |||
| 1. Low density lipoprotein | 102 (69–130) | 89 (64–116) | 0.05 |
| 2. High density lipoprotein | 46 (36–56) | 43 (38–55) | 0.51 |
| 3. Total cholesterol | 175 (144–206) | 161 (138–200) | 0.15 |
| 4. Triglycerides | 104 (74–152) | 105 (80–150) | 0.55 |
| Complete blood count, median (IQR) | |||
| 1. Hemoglobin, g/dl | 14 (13–15) | 13 (11–14) | <0.0001* |
| 2. Platelets, ×103/mL | 217 (181–263) | 199 (165–240) | 0.10 |
| Coagulation profile, median (IQR)† | |||
| 1. Prothrombin time, seconds | 13 (13–14) | 13 (13–15) | 0.15 |
| 2. INR | 1 (1–1.1) | 1 (1–1.2) | 0.21 |
| 3. Partial thromboplastin time, seconds | 28 (26–31) | 28 (25–31) | 0.58 |
| Hemoglobin A1c, %, median (IQR) | 5.9 (5.5–6.6) | 6.0 (5.6–6.8) | 0.85 |
| Imaging characteristics | |||
| Fazekas scale score, n (%) | |||
| 1. Periventricular hyperintensity | |||
| a) Score 0 | 40 (20) | 6 (8) | 0.001* |
| b) Score 1 | 79 (39) | 21 (26) | |
| c) Score 2 | 57 (28) | 30 (38) | |
| d) Score 3 | 29 (14) | 23 (29) | |
| 2. Deep white matter hyperintensity | |||
| a) Score 0 | 56 (27) | 9 (11) | <0.0001* |
| b) Score 1 | 97 (47) | 28 (35) | |
| c) Score 2 | 40 (20) | 32 (40) | |
| d) Score 3 | 12 (6) | 11 (14) | |
| 3. Total Fazakas score | |||
| a) Score 0–3 | 152 (74) | 53 (26) | <0.0001* |
| b) Score 4–6 | 36 (45) | 44 (55) | |
| Cerebral microbleeds, n (%) | 58 (28) | 27 (34) | 0.37 |
| 1. Lobar | 33 (16) | 11 (14) | 0.62 |
| 2. Deep | 29 (14) | 15 (19) | 0.33 |
| 3. Infratentorial | 25 (12) | 14 (18) | 0.24 |
Missing labs for 29 and 10 patients in kidney impairment absent and present group respectively;
p<0.05
IQR = interquartile range
Table 4.
Distribution of cerebral microbleed for each location based on Microbleed Anatomical Rating Scale (MARS)
| Location of microbleed | Definite | Possible |
|---|---|---|
| 1. Lobar, n (%) | 38 (13) | 18 (6) |
| a) Frontal | 21 (8) | 10 (4) |
| b) Parietal | 18 (6) | 6 (2) |
| c) Temporal | 19 (7) | 7 (2) |
| d) Occipital | 16 (6) | 4 (1) |
| e) Insula | 0 (0) | 0 (0) |
| 2. Deep, n (%) | 33 (12) | 19 (7) |
| a) Basal ganglia | 13 (5) | 14 (5) |
| b) Internal capsule | 2 (1) | 1 (1) |
| c) External capsule | 4 (1) | 0 (0) |
| d) Corpus callosum | 2 (1) | 1 (1) |
| e) Thalamus | 19 (7) | 4 (1) |
| f) Deep and periventricular white matter | 8 (3) | 0 (0) |
| 3. Infratentorial, n (%) | 29 (10) | 16 (6) |
| a) Brainstem | 11 (4) | 6 (2) |
| b) Cerebellum | 25 (9) | 12 (4) |
Outcomes
In unadjusted analysis, patients with kidney impairment were less likely to have a good functional outcome (mRS 0–2: 36% vs 57%, p=0.002) and good discharge outcome (68% vs 82%, p=0.008, Table 5). However, kidney impairment was not associated with poor discharge outcome on multivariate analysis with covariates (OR=1.62; 95% CI:0.75–3.53). The NIHSS score was significantly associated with poor outcome (OR=1.18; 95% CI:1.12–1.23). Patients with kidney impairment were almost twice as likely to have in-hospital mortality but this was not statistically significant (9% vs 5%, p=0.26). There was no difference in the HT of ischemic stroke between patients with and without kidney impairment. There was also no difference in the risk of HT among patients with CMB and those who received treatment with alteplase (Table 5).
Table 5.
Outcomes of stroke stratified by kidney disease
| Outcome | Kidney Impairment Absent (n=205) | Kidney Impairment Present (n=80) | p value |
|---|---|---|---|
| Good functional outcome, mRS (0–2), n (%) | 116 (57) | 29 (36) | 0.002* |
| Discharge outcome, n (%) | |||
| 1. Good discharge outcome | 168 (82) | 54 (68) | 0.008* |
| 2. Poor discharge outcome | 37 (18) | 26 (32) | |
| Discharge location, n (%) | |||
| a. Home | 41 (20) | 12 (15) | - |
| b. Home with home care | 62 (30) | 10 (13) | - |
| c. Inpatient rehabilitation | 65 (32) | 32 (40) | - |
| d. Skilled nursing facility | 17 (8) | 11 (14) | - |
| e. Long term care facility | 5 (2) | 5 (6) | - |
| f. Hospice | 5 (2) | 3 (4) | - |
| g. Death | 10 (5) | 7 (9) | - |
| Hemorrhagic transformation, n (%) | 37 (18) | 20 (25) | 0.19 |
| 1. Hemorrhagic infarction | 29 (14) | 14 (18) | |
| 2. Parenchymal hematoma | 8 (4) | 6 (7) | |
| HT among patients with CMB | 12 (21) | 5 (19) | 0.82 |
| HT among patients with alteplase | 19 (35) | 11 (41) | 0.58 |
HT= Hemorrhagic transformation; CMB=Cerebral microbleed
p≤0.05
Factors associated with presence of kidney impairment
On multivariate analysis, kidney impairment was associated with higher NIHSS score (OR=1.04; 95%CI=1.002–1.08), and severe WMH on FLAIR (OR=1.99; 95%CI=1.06–3.77, Table 6).
Table 6.
Multivariate logistic regression analysis for factors associated with kidney impairment
| Variable | OR (95% CI) | p value |
|---|---|---|
| 1. Age | 1.06 (1.03 – 1.09) | 0.0001* |
| 2. Sex | 0.88 (0.47 – 1.63) | 0.68 |
| 3. Race white vs others | 3.67 (1.70 – 7.93) | 0.0009* |
| 4. Hypertension | 1.54 (0.67 – 3.54) | 0.31 |
| 5. Hyperlipidemia | 1.48 (0.79 – 2.77) | 0.22 |
| 6. Transient ischemic attack | 1.95 (0.65 – 5.82) | 0.23 |
| 7. Congestive heart failure | 3.34 (1.23 – 9.05) | 0.02* |
| 8. Smoking | 0.64 (0.35 – 1.18) | 0.15 |
| 9. NIHSS score | 1.04 (1.002 – 1.08) | 0.04* |
| 10. Total Fazekas score 4–6 vs 0–3 | 1.99 (1.06 – 3.77) | 0.03* |
Model c-statistic = 0.802
Hosmer and Lemeshow Goodness-of-Fit test, p=0.23
P<0.05
DISCUSSION
In this study, we evaluated the clinical and imaging features and outcomes of AIS patients with and without kidney impairment at the time of stroke presentation. Patients with kidney impairment presented with more neurological deficits compared to patients without kidney impairment. Patient with kidney impairment also had severe WMH due to small vessel disease on FLAIR MRI. We did not find a difference in the presence of CMBs, the risk of HT, and discharge outcomes between patients with and without kidney impairment.
Stroke is a medical emergency and patients with stroke symptoms need to go to the nearest hospital for medical care. As a result, many patients seen for stroke may not have ongoing care in the same hospital and previous laboratory results such as renal function may not be available. We performed this study in a pragmatic real world setting and defined kidney impairment as eGFR < 60mL/min/1.73m2 at the time of stroke presentation and compared our findings with those published in the literature among patients with CKD.
As shown in previous studies, the baseline NIHSS score was a major predictor of stroke outcome in our study.23 Patients with kidney impairment had more neurological deficits with higher median NIHSS score (8.5 vs 5) compared to patients without kidney impairment. However, kidney impairment was not independently associated with poor discharge outcomes. In a prior study, CKD was associated with severe stroke at presentation, neurological deterioration during hospitalization, and poor outcome with higher mortality.24 In another study, CKD was found to be an independent predictor of poor clinical outcome after recurrent stroke and cardiovascular events among patients with recent subcortical strokes.25 It is possible that the mild increase in NIHSS score in patients with kidney impairment with an odds ratio of 1.04 may not have been sufficient to cause a difference in discharge outcomes in our study. Our study cohort also had patients with less severe kidney impairment compared to that in prior studies, and this could be another potential factor.
The Get With The Guidelines (GWTG)–Stroke is an in-hospital program implemented by the American Heart Association / American Stroke Association for improving stroke care by promoting consistent adherence to the most recent scientific treatment guidelines.26 Since its inception in 2003, more than 5 million patient records have been entered in the GWTG-Stroke registry by more than 2,000 hospitals. In a study from the GWTG–Stroke database, in-hospital mortality or discharge to hospice increased with decrease in eGFR: 9.1% in patients with eGFR≥60 ml/min/1.73m2 compared to 29.2% in patients with eGFR<15 ml/min/1.73m2.27 In our study, 9% of patients with kidney impairment died compared to 5% of patients without kidney impairment which was not statistically significant.
Previous studies have shown association of CKD with small vessel disease including WMH and CMB.10, 28–30 While it has been long-recognized that CKD is associated with a high burden of atherosclerosis and cardiovascular events, the spectrum of vascular disease changes as CKD progresses, with disproportionately increasing severity of microvascular disease.3 Albuminuria, a prominent feature of CKD severity, is an established marker of damage to the microvasculature of glomerular capillaries. Prior studies have shown strong correlations between albuminuria and cerebral microvascular changes, independent of its associations with declining eGFR.14 In our study, kidney impairment at admission was associated with severe WMH on FLAIR indicating the presence of small vessel disease in this patient population with shared common vascular risk factors. In one study, the association of renal impairment with imaging findings of cerebral small vessel disease (WMH, CMB, lacunes and enlarged perivascular spaces) was attenuated in older age (≥ 60 years) when adjusted for shared risk factors including sex, history of hypertension and diabetes mellitus.31 However, renal impairment was significantly associated with small vessel disease among patients <60 years even after adjusting for vascular risk factors.31
Despite an older population and greater preponderance of black race factors strongly associated with CMB in prior studies10 we did not find a difference in the presence of CMB between patients with and without kidney impairment. Patients presenting with AIS could have low eGFR suggesting kidney impairment related to acute kidney injury, although the reported incidence of acute kidney injury among AIS is low. In a study that pooled data from stroke clinical trials, 36.1% of patients had increased levels of creatinine but only 3.5% were found to have acute kidney injury.16 Another study reported prevalence of acute kidney injury in 11.6% of AIS.15 Unfortunately, it is difficult to ascertain the cause of abnormal creatinine in an acute stroke setting. Due to the non-availability of prior eGFR, we could only confirm the presence of CKD in 38% of the patients in our cohort. It is plausible that the negative association of CMB with kidney impairment on admission is likely due to heterogeneous patient population in the kidney impairment group including those with CKD and acute kidney injury.
In one study, low eGFR was an independent predictor of HT of AIS not treated with alteplase.9 There is uncertainty if CKD is associated with increased risk of HT among patients treated with alteplase.32–34 In our study, there was no increased risk of HT in patients with kidney impairment. Moreover, a subgroup analysis of patients with CMB and those treated with alteplase did not show increased risk of HT between patients with and without kidney impairment. It is possible that the severity of CKD could be a potential confounding factor for the mixed results and that patients with more severe reduction in eGFR < 60mL/min/1.73m2 are more likely to have HT of AIS.33 One study reported the association of blood urea nitrogen/creatinine ratio with HT in AIS among patients with diabetes mellitus but not among those without diabetes mellitus.35
Detailed evaluation of clinical and imaging variables for association with kidney impairment is a major strength of our study. Our study has limitations, a major one being the small sample size and lack of eGFR at 3 months before stroke to confirm CKD in about half of the patients with kidney impairment. Although the kidney impairment group in our study is a heterogeneous group, it represents the real-world setting. We did not have the details of the mRS or functional status prior to the stroke for comparison with the mRS at discharge. The lack of pre-stroke functional status confounds the interpretation of our study findings as patients with kidney impairment could have poor baseline with co-morbidities. Although we did not find poor discharge outcomes with the adjusted analysis in our heterogenous cohort of patients with kidney impairment, patients with CKD and acute kidney injury can have poor outcomes when present with AIS. It may provide opportunities to study whether stroke outcome improves with therapeutic intervention to improve the renal function in some patients with kidney disease at stroke presentation. The risk of in-hospital complications and death are significantly higher in hospitalized patients with acute kidney injury, and it is reported to be about 2–3 times higher in stroke patients with acute kidney injury.15, 16 Prompt nephrology referral, identification and treatment of any acute precipitating factors responsible for kidney impairment may provide opportunities for improved outcomes among these AIS patients. Our study was limited by lack of follow-up data to assess long-term outcome.
CONCLUSION
Presence of kidney impairment at the time of stroke presentation, regardless of prior renal status, is associated with more severe stroke. Kidney impairment is associated with severe WMH likely due to common vascular risk factors.
FUNDING
Research reported in this publication was supported in part by the National Center For Advancing Translational Sciences of the National Institutes of Health under Award Number UL1TR001427. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
DISCLOSURES
Shukla AM reports the following Grant supports: I01CX001661: Management of cardiovascular disease in advanced CKD & I01HX002639: A system-wide strategy for KDE to improve the health and health services outcomes among Veterans from the Department of Veterans Affairs.
Nagaraja N, Farooqui A, and Ballur Narayana Reddy V: report no relevant disclosures.
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