Abstract
Aim: Although a lower level of non-high-density lipoprotein cholesterol (HDL-C) was reported to be inversely associated with spontaneous intracranial hemorrhage (ICH), no enough evidence has verified whether lipid profiles modify hemorrhagic transformation and functional outcomes in patients with acute ischemic treated with thrombolysis.
Methods: This multicenter cohort study included 2373 patients with acute ischemic stroke treated with intravenous thrombolysis between December 2004 and December 2016. Of these, 1845 patients were categorized into either the hyperlipidemia or non-hyperlipidemia group. Symptomatic ICH (SICH) rates within 24–36 h of thrombolytic onset and functional outcomes at 30 and 90 days were longitudinally surveyed. Models of predicting hemorrhagic transformation were used to validate our findings.
Results: For enrolled 1845 patients, SICH rates were ≥ 2-fold reduced for the hyperlipidemia group by the NINDS (adjusted RR: 0.488 [0.281–0.846], p = 0.0106), the ECASS II (adjusted RR: 0.318 [0.130–0.776], p = 0.0119), and SITS-MOST standards (adjusted RR: 0.214 [0.048–0.957], p = 0.0437). The favorable functional rates between the two groups were not significantly different. Lower levels of LDL-C were showed in robust association with SICH. With a cut-off LDL-C value of < 130 mg/dL, new models are more robust and significant in predicting hemorrhagic transformation within 24–36 h.
Conclusions: This study supports the strong association between reduced LDL-C and increased SICH, but not for functional outcomes in patients with acute ischemic stroke treated with intravenous thrombolysis. LDL-C level of < 130 mg/dL is supposed to a candidate marker for predicting SICH within 24–36 h.
Keywords: Stroke, Cholesterol, Low-density lipoprotein cholesterol (LDL-C), Thrombolysis, Intracranial hemorrhage
Introduction
The level of non-high-density lipoproteins (non-HDL-C) was recognized as a possible modifying factor of intracranial hemorrhage in the multinational INTERSTROKE case–control study1). Later, several studies found decreased total or low-density cholesterol (LDL-C) as the candidate risk factor for spontaneous intracranial hemorrhage2–4). A 2007 study with a small sample of 104 patients provided the first evidence supporting the association between cholesterol levels and hemorrhagic transformation after intravenous (IV) thrombolysis for acute ischemic stroke5). Nevertheless, later studies on similar topics reported inconsistent results5–10). These studies were possibly limited by their smaller sample sizes (enrolling fewer than 500 patients)5–7, 10), retrospective design5–8, 10), and missing lipid profiles in a substantial portion of patients9). By contrast, none of the studies determined as to how much a lower level of cholesterol contributed to the increase in symptomatic intracranial hemorrhage (SICH)5) or conducted a longitudinal research on changes in the functional status in these patients. Thus, the association between decreased cholesterol levels and increased hemorrhagic transformation for acute ischemic stroke treated with IV thrombolysis is yet to be elucidated7, 11, 12).
The Taiwan Thrombolytic Therapy for Acute Ischemic Stroke (TTT-AIS) registry is a nationwide cohort in Taiwan and contains longitudinal follow-up data with each patient's clinical and laboratory characteristics for 90 days13, 14). We sought to determine whether lipid profiles (1) modified the incidence of hemorrhagic transformation at 24–36 h, and (2) altered the functional status changes in patients with acute ischemic stroke patients treated with IV thrombolysis among ethnic Chinese (i.e., Taiwanese).
Methods
Design and Participants
This multicenter cohort study included 30 hospitals in Taiwan, and the data were prospectively collected and registered in the TTT-AIS registry system. For patients with acute ischemic stroke, IV alteplase was adopted as the thrombolytic regimen at arrival within 3 h of stroke onset. Eligible patients fulfilled the inclusion criteria of (1) treatment with IV thrombolysis adhering to the National Institute for Neurological Disorders (NINDS) standard15) and (2) measurement of total cholesterol, LDL-C, HDL-C, and triglycerides (TG) in a fasting state (measured during 24–72 h following IV alteplase administration). Exclusion criteria for IV thrombolysis referred to the SITS-MOST study standard16). All enrolled patients with acute ischemic stroke underwent brain computed tomography (CT) on arrival at the emergency department, and another routine repeat brain CT was conducted within 24–36 h post IV thrombolysis. Baseline demographic data including age, sex, weight, history of hypertension, diabetes mellitus, hyperlipidemia, coronary artery disease, atrial fibrillation, alcohol consumption, blood pressure on arrival, use of antiplatelet and anticoagulant medications, baseline National Institutes of Health Stroke Scale (NIHSS) score, the alteplase dose, and time from stroke onset to IV thrombolysis were retrieved by investigators. Patients with a capacity of will signed the informed consent themselves, whereas it was signed by legal surrogate in case of patients without a capacity of will. This study was approved by the institutional review board of Kaohsiung Medical University Hospital.
Outcomes Measures
Regarding primary and secondary objectives, we evaluated the relationship between SICH and lipid profiles in two ways: (1) groups of hyperlipidemia and non-hyperlipidemia (the hyperlipidemia group was defined as total cholesterol of ≥ 200 mg/dL or LDL-C of ≥ 130 mg/dL or TG of ≥ 200 mg/dL) and (2) total cholesterol, LDL-C, HDL-C, and TG as continuous variables (mg/dL). Patients were longitudinally surveyed at 30 and 90 days for functional outcome measurement. The modified Rankin Scale (mRS) of 0–1 or 0–2 was defined as favorable functional outcomes17). SICH was defined by three criteria: (1) the National Institute of Neurological Disorders (NINDS) study standard in which any intracranial hemorrhage with deterioration of NIHSS scores of ≥ 1 or death within 36 h15), (2) the European Cooperative Acute Stroke Study (ECASS) II standards in which any apparently extravascular blood in the cranium with deterioration of NIHSS scores of ≥ 4 or led to death18), and (3) the SITS-MOST standards in which a type 2 parenchymal hemorrhage (a local or remote parenchymal intracranial hemorrhage exceeding 30% of the infarct) with clinical deterioration of NIHSS scores of ≥ 4 or death within 36 h16).
Validation Study
As a separate part of the study, we verified which lipid profile was a candidate marker for predicting SICH. In the current systems, there were seven validated risk-scoring models available for us to predict hemorrhagic transformation for acute ischemic stroke treated with IV thrombolysis. The candidate lipid profile was then incorporated into to the original risk-scoring models, which in succession became the new model. We certified a lipid profile that was in actual association with SICH by contrasting the original and new risk-scoring models (when new models had significantly better diagnostic ability than the original one). These risk-scoring systems contained the Hemorrhage After Thrombolysis (HAT) score19), the Safe Implementation of Thrombolysis in Stroke (SITS-SICH) score20), the Cucchiara score21), the blood Sugar, Early infarct signs and hyperDense cerebral artery sign, Age, and NIHSS (SEDAN) score22), the Stroke Prognostication using Age and National Institutes of Health Stroke Scaleand-100 (SPAN-100) index23), the Glucose Race Age Sex Pressure Stroke Severity (GRASPS) score24), and the Totaled Health Risks in Vascular Events (THRIVE) score25) (Supplemental Table 1). As a separate part of the study, we investigated the subcohort of possibly statin-naive patients. Because the Taiwan National Health Insurance (TNHI) system had strict payment rule for statin, the subcohort was defined as exclusion of the TNHI rule (LDL-C of ≥ 130 mg/dL or total cholesterol of ≥ 200 mg/dL with diabetes mellitus or more than one of the following cardiovascular risk factors: HDL of < 40 mg/dL, hypertension, male patient aged ≥ 40 years, female menopausal patient aged ≥ 55 years, or smoking). These results are shown in Supplemental Fig. 3 and Table 4.
Supplemental Table 1. The Risk-scoring Models Used in Validation Study.
| Model | Variables Needed | Cut-off values (points obtained for each item) |
Original Definition of SICH |
|---|---|---|---|
| HAT score1 | NIHSS, Glucose > 200 mg/dl or Diabetes mellitus, Hypodensity on CT |
15–20 (1), > 20 (2), yes (1), < 1/3 of MCA territory (1), ≥ 1/3 of MCA territory (2), |
NINDS |
| SICH score2 | Age, NIHSS, Glucose, Systolic blood pressure, Weight, Onset to thrombolytic time, Aspirin monotherapy, Aspirin + clopidogrel, Hypertension, |
≥ 72 (1), 7–12 (1), ≥ 13 (2), ≥ 180 mg/dl (2), ≥ 146 mmHg (1), ≥ 95 kg (1), ≥ 180 min (1), yes (2), yes (3), yes (1), |
SITS-MOST |
| Cucchiara Score3 | Age, NIHSS, Glucose, Platelet count, |
>60 (1), >10 (1), >150 mg/dl (1), < 150,000/mm3 (1) |
NINDS |
| SEDAN Score4 | Glucose, Early infarct on CT Dense cerebral artery sign on CT, Age, NIHSS, |
145–216 mg/dl (1), >216 mg/dl (2) yes (1) yes (1), >75 (1), ≥ 10 (1), |
ECASS II |
| SPAN-100 index5 | Age + NIHSS | ≥ 100 (1) | NINDS |
| GRASP score6 | Age, NIHSS, Glucose, Systolic blood pressure, Ethnicity, Gender |
≤ 60 (8), 61–70 (11), 71–80 (15), > 80 (17), 0–5 (20), 6–10 (27), 11–15 (34), 16–20 (40), >20 (42), <100 (2) 100–149 (6), ≥ 150 (8) <120 (10), 120–149 (14), 150–179 (18), ≥ 180 (21), Asian (9), Non–Asian (0), Male (4), Female (0), |
NINDS |
| THRIVE score7 | Age, NIHSS, Hypertension, Diabetes mellitus, Atrial fibrillation, |
60–79 (1), ≥ 80 (2), 11–20 (2), ≥ 21 (4), yes (1), yes (1), yes (1), |
ECASS II, the European Cooperative Acute Stroke Study II; GRASPS, the Glucose Race Age Sex Pressure Stroke Severity study; HAT, the Hemorrhage After Thrombolysis study; MCA, middle cerebral artery; NINDS, the National Institute of Neurological Disorders and Stroke study; SEDAN, the blood Sugar, Early infarct signs and hyperDense cerebral artery sign, Age, and NIHSS; SICH, symptomatic intracerebral hemorrhage; SPAN-100, the Stroke Prognostication using Age and National Institutes of Health Stroke Scaleand-100 index.
Supplemental Fig. 3.
Flow diagram of subcohort identification of possibly statin-naïve patients according to the Taiwan National Health Insurance (TNHI) payment rule.
Supplemental Table 4. Subcohort Analysis of Association between Lipid Profile and Symptomatic Intracranial Hemorrhage for Possibly Statin-naïve Patients.
| Variable | RR | p value | Adjusted RR | p value |
|---|---|---|---|---|
| (N = 1245) | (95% CI) | (95% CI)† | ||
| Total cholesterol (per 10 mg/dl increase) | ||||
| SICH by NINDS | 0.948 (0.869–1.035) | 0.2341 | 0.971 (0.879–1.072) | 0.5599 |
| SICH by ECASS II | 1.009 (0.900–1.132) | 0.8760 | 0.997 (0.879–1.130) | 0.9582 |
| SICH by SITS-MOST | 0.985 (0.837–1.159) | 0.8536 | 0.934 (0.764–1.140) | 0.4998 |
| LDL-C (per 10 mg/dl increase) | ||||
| SICH by NINDS | 0.866 (0.789–0.950) | 0.0023* | 0.873 (0.783–0.973) | 0.0143* |
| SICH by ECASS II | 0.894 (0.791–1.012) | 0.0760 | 0.856 (0.746–0.983) | 0.0270* |
| SICH by SITS-MOST | 0.991 (0.821–1.198) | 0.9289 | 0.932 (0.743–1.170) | 0.5447 |
| HDL-C (per 10 mg/dl increase) | ||||
| SICH by NINDS | 1.076 (0.998–1.159) | 0.0550 | 1.064 (0.984–1.190) | 0.1036 |
| SICH by ECASS II | 1.080 (0.982–1.189) | 0.1145 | 1.115 (0.995–1.249) | 0.0608 |
| SICH by SITS-MOST | 1.031 (0.878–1.212) | 0.7093 | 1.051 (0.855–1.292) | 0.6363 |
| TG (per 10 mg/dl increase) | ||||
| SICH by NINDS | 0.982 (0.938–1.027) | 0.4262 | 1.000 (0.959–1.044) | 0.9901 |
| SICH by ECASS II | 1.001 (0.967–1.053) | 0.6845 | 1.006 (0.960–1.055) | 0.7929 |
| SICH by SITS-MOST | 0.944 (0.850–1.048) | 0.2788 | 0.882 (0.761–1.022) | 0.0935 |
HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; N, total number of subcohort patients; NINDS, National Institute of Neurological Disorders and Stroke; RR, relative risk, CI, confidence interval; SITS-MOST, Safe Implementation of Thrombolysis in Stroke-Monitoring Study; TG, triglycerides.
Statistically significant at p < 0.05.
Poisson regression adjusted for age, weight, atrial fibrillation, baseline NIHSS, and dose of alteplase.
Statistical Analysis
To compare the two groups, Student t-test was used for continuous variables and Chi-squared test was used for categorical variables. For outcomes measures, Poisson regression model was used to determine the relative risk (RR) of SICH in the 24–36 h of interval and Binomial regression model was used to evaluate the RR for the functional outcomes at 30 and 90 days. The multivariate regressions were applied to adjust the significantly imbalanced covariates between the hyperlipidemia and non-hyperlipidemia groups. However, covariates of the antithrombotic medications were not adjusted because of missing values in most subjects. In the validation study, receiver of operating characteristics (ROC) curves were conducted to examine the diagnostic ability of each model. The Hosmer–Lemeshow test was used to examine the model of fitness (good fitness of the model was defined as p > 0.05). The integrated discriminatory improvement (IDI) test was used to compare the predictive ability between the original and new models26, 27). Statistical significance was set at a p value of < 0.05. All analyses were performed using SAS 9.4 software (SAS Institute, Cary, NC, USA).
Results
Baseline Demographic Characteristics
A total of 2373 patients with acute ischemic stroke who completed the IV thrombolysis treatment between December 1, 2004 and December 31, 2016 were registered in TTT-AIS I and II systems (Fig. 1). Complete lipid profile data in a fasting state were measured in 1845 patients following admission (Table 1). The hyperlipidemia cohort included 747 patients, and the non-hyperlipidemia cohort included 1093 patients. The non-hyperlipidemia group was more likely to include older patients, those with a comorbidity of atrial fibrillation, those using aspirin, those with higher baseline NIHSS scores, and those using low-dose alteplase. The hyperlipidemia group consisted of more patients with higher systolic and diastolic blood pressure at arrival. There were no significant differences in the sex distribution; comorbidities of hypertension, diabetes mellitus, coronary artery disease, and alcoholism; or time from stroke onset to IV thrombolysis between the two groups.
Fig. 1.
The flow diagram of the research. Patients were followed up at 24–36 for intracranial hemorrhage outcomes, and at 30 and 90 days for functional outcomes.
Table 1. Demographic Characteristics of Patients with and without Hyperlipidemia.
| Variable | Hyperlipidemia | No hyperlipidemia | p value |
|---|---|---|---|
| (N = 747) | (N = 1093) | ||
| Age (years) | 67.1 ± 12.3 | 69.8 ± 13.3 | < 0.0001* |
| Female sex; n (%) | 278 (37.2%) | 388 (35.5%) | 0.4517 |
| Lipids (mg/dL) | |||
| Total cholesterol | 219.1 ± 37.9 | 156.5 ± 25.6 | < 0.0001* |
| LDL-C | 142.4 ± 36.8 | 91.1 ± 24.4 | < 0.0001* |
| HDL-C | 45.3 ± 35.2 | 46.7 ± 21.5 | 0.3296 |
| TG | 162.5 ± 110.6 | 93.0 ± 38.3 | < 0.0001* |
| Body weight (kg) | 66.4 ± 13.1 | 64.6 ± 12.7 | 0.0061* |
| Medical history; n/total N (%) | |||
| Hypertension | 547/747 (73.2%) | 786/1093 (71.9%) | 0.5356 |
| Diabetes mellitus | 237/747 (31.7%) | 314/1093 (28.7%) | 0.1679 |
| Coronary artery disease | 88/747 (11.8%) | 142/1093 (13.0%) | 0.4404 |
| Atrial fibrillations | 272/618 (44.0%) | 524/933 (56.2%) | < 0.0001* |
| Alcoholism; n/total N (%) | 65/747 (8.7%) | 79/1093 (7.2%) | 0.2478 |
| NIHSS on arrival | 12.9 ± 7.6 | 13.8 ± 6.8 | 0.0064* |
| Mean of Alteplase dose (mg/kg) | 0.81 ± 0.13 | 0.79 ± 0.14 | 0.0009* |
| Groups of Alteplase dosage | 0.0002* | ||
| Standard dose (0.9 mg/kg) | 408/747 (54.6%) | 501/1093 (45.8%) | |
| Low dose (< 0.9 mg/kg) | 339/747 (45.4%) | 592/1093 (54.2%) | |
| Blood pressure on arrival | |||
| Systolic blood pressure (mmHg) | 164.4 ± 31.1 | 157.6 ± 29.6 | < 0.0001* |
| Diastolic blood pressure (mmHg) | 93.1 ± 19.8 | 89.8 ± 19.4 | 0.0006 |
| Time to treatment (min) | 132.7 ± 46.7 | 131.7 ± 46.7 | 0.6452 |
| Antithrombotic medications | |||
| Aspirin | 79/506 (15.6%) | 164/739 (22.2%) | 0.0040* |
| Clopidogrel | 21/506 (4.2%) | 33/739 (4.5%) | 0.7885 |
| Ticlopidine | 6/506 (1.2%) | 12/739 (1.6%) | 0.5248 |
| Warfarin | 19/506 (3.8%) | 31/739 (4.2%) | 0.6978 |
HDL-C, high density lipoprotein-cholesterol; LDL-C, low density lipoprotein-cholesterol; NIHSS, National Institutes of Health Stroke Scale; TG, Triglycerides. Continuous variables are expressed as the mean ± standard deviation.
Statistically significant at p < 0.05.
Primary Objective (Hyperlipidemia vs Non-Hyperlipidemia Group)
The rates of any intracranial hemorrhage (ICH) were 12.3% and 15.6% for hyperlipidemia and non-hyperlipidemia groups, respectively (Fig. 1). Rates of SICH for hyperlipidemia and non-hyperlipidemia groups according to the NINDS, ECASS II, and SITS-MOST standards are shown in Table 2. The hyperlipidemia group had a significantly reduced incidence rate of SICH than the non-hyperlipidemia group by the NINDS standard (2.28% vs 4.85%; adjusted RR, 0.509; 95% CI, 0.277–0.933; p = 0.0290), the ECASS II standard (1.07% vs 2.74%; adjusted RR, 0.318; 95% CI, 0.130–0.777; p = 0.0119), and the SITS-MOST standard (0.27% vs 1.46%; adjusted RR, 0.216; 95% CI, 0.048–0.966; p = 0.0119). The continuing survey showed that the hyperlipidemia group had more patients who attained favorable functional outcomes (mRS of 0–1) than the non-hyperlipidemia group at 30 days (29.9% vs 26.2%; adjusted RR, 0.990; 95% CI, 0.860–1.141; p = 0.8963) and 90 days (35.3% vs 32.9%; adjusted RR, 0.962; 95% CI, 0.839–1.104; p = 0.5815). There was no significance difference for obtaining the favorable functional outcomes between the two groups (Fig. 2).
Table 2. Analysis of the Risk of Symptomatic Intracranial Hemorrhage (SICH) for the Two Cohorts at 24–36 h.
| Variable | Hyperlipidemia | Non-hyperlipidemia | RR (95% CI) |
p value | Adjusted RR (95% CI)† |
p value |
|---|---|---|---|---|---|---|
| SICH at 24–36 hrs | ||||||
| by NINDS standard | 17/747 (2.28%) | 53/1093 (4.85%) | 0.469 (0.274–0.804) | 0.0059 | 0.509 (0.277–0.933) | 0.0290* |
| by ECASS II standard | 8/747 (1.07%) | 30/1093 (2.74%) | 0.390 (0.179–0.851) | 0.0180* | 0.318 (0.130–0.777) | 0.0119* |
| by SITS-MOST standard | 2/747 (0.27%) | 16/1093 (1.46%) | 0.183 (0.042–0.795) | 0.0235* | 0.216 (0.048–0.966) | 0.0450* |
| Functional outcomes at 30 days | ||||||
| mRS of 0–1 | 206/689 (29.9%) | 259/987 (26.2%) | 1.052 (0.990–1.119) | 0.1042 | 0.990 (0.860–1.141) | 0.8936 |
| mRS of 0–2 | 283/689 (41.1%) | 375/987 (38.0%) | 1.052 (0.972–1.139) | 0.2073 | 0.998 (0.855–1.164) | 0.9782 |
| Functional outcomes at 90 days | ||||||
| mRS of 0–1 | 227/643 (35.3%) | 315/959 (32.9%) | 1.038 (0.966–1.116) | 0.3120 | 0.962 (0.839–1.104) | 0.5815 |
| mRS of 0–2 | 343/643 (53.3%) | 530/959 (55.3%) | 1.036 (0.945–1.136) | 0.4508 | 0.957 (0.805–1.138) | 0.6207 |
CI, confidence interval; NINDS, National Institute of Neurological Disorders and Stroke; RR relative risk; SITS-MOST, Safe Implementation of Thrombolysis in Stroke-Monitoring Study; TG, Triglycerides.
Statistically significant at p < 0.05.
Poisson regression was adjusted for age, weight, atrial fibrillation, baseline NIHSS, and dose of alteplase.
Fig. 2.
The distribution of functional outcomes at 30 and 90 days.
Secondary Objective (Each Lipid Profile)
The association between SICH and each lipid profile is shown in Table 3. Increasing total cholesterol and TG levels decreased the risk of developing SICH, but they showed solitary significance in the ECASS II standard (adjusted RR, 0.908 per 10 mg/dL; 95% CI, 0.830–0.992; p = 0.0331) and the SITS-MOST (adjusted RR, 0.837 per 10 mg/dL; 95% CI, 0.722–0.970; p = 0.0331), respectively. By contrast, only LDL-C showed a significant association with all SICH standards—the NINDS standard (adjusted RR, 0.912 per 10 mg/dL; 95% CI, 0.848–0.982; p = 0.0145), the ECASS II standard (adjusted RR, 0.823 per 10 mg/dL; 95% CI, 0.742–0.913; p = 0.0002), and the SITS-MOST standard (adjusted RR, 0.846 per 10 mg/dL; 95% CI, 0.724–0.989; p = 0.0358). The increased HDL-C level manifested an increased risk of SICH, but it was exclusively significant for the ECASS II standard (adjusted RR, 0.837 per 10 mg/dL; 95% CI, 0.722–0.970; p = 0.0182).
Table 3. Analysis of the Risk of Symptomatic Intracranial Hemorrhage (SICH) for Each Lipid Profile.
| Variable | RR | p value | Adjusted RR | p value |
|---|---|---|---|---|
| (95% CI) | (95% CI)† | |||
| Total cholesterol (per 10 mg/dl increase) | ||||
| SICH by NINDS | 0.947 (0.895–1.002) | 0.0603 | 0.956 (0.896–1.021) | 0.1797 |
| SICH by ECASS II | 0.937 (0.867–1.013) | 0.0999 | 0.908 (0.830–0.992) | 0.0331* |
| SICH by SITS-MOST | 0.895 (0.798–1.004) | 0.0588 | 0.919 (0.766–1.102) | 0.3623 |
| LDL-C (per 10 mg/dl increase) | ||||
| SICH by NINDS | 0.907 (0.852–0.967) | 0.0026* | 0.912 (0.848–0.982) | 0.0145* |
| SICH by ECASS II | 0.874 (0.801–0.954) | 0.0026* | 0.823 (0.742–0.913) | 0.0002* |
| SICH by SITS-MOST | 0.881 (0.776–0.999) | 0.0493* | 0.846 (0.724–0.989) | 0.0358* |
| HDL-C (per 10 mg/dl increase) | ||||
| SICH by NINDS | 1.077 (1.013–1.144) | 0.0171* | 1.064 (0.992–1.140) | 0.0826 |
| SICH by ECASS II | 1.087 (1.005–1.175) | 0.0171* | 1.085 (1.005–1.171) | 0.0379 |
| SICH by SITS-MOST | 1.053 (0.921–1.207) | 0.4453 | 1.045 (0.910–1.200) | 0.5311 |
| TG (per 10 mg/dl increase) | ||||
| SICH by NINDS | 0.957 (0.916–0.999) | 0.0465* | 0.976 (0.932–1.023) | 0.3076 |
| SICH by ECASS II | 0.981 (0.934–1.031) | 0.4533 | 0.977 (0.922–1.036) | 0.4389 |
| SICH by SITS-MOST | 0.904 (0.809–1.091) | 0.0719 | 0.837 (0.722–0.970) | 0.0182* |
HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; NINDS, National Institute of Neurological Disorders and Stroke; RR, relative risk, CI, confidence interval; SITS-MOST, Safe Implementation of Thrombolysis in Stroke-Monitoring Study; TG, triglycerides.
Statistically significant at p < 0.05.
Poisson regression adjusted for age, weight, atrial fibrillation, baseline NIHSS, and dose of alteplase.
Validation Study
LDL-C, which exhibited the most robust association with SICH in our study, was incorporated into all of our available and validated hemorrhagic transformation predicting models in two ways: continuous level and discrete points. To obtain a higher sensitivity, we determined a cut-off of LDL-C of 100–mg/dL as a point of 1, and LDL-C < 100 mg/dL as a point of 2. For the new models with LDL-C as continuous levels, all the models showed significantly exceeding improvement in diagnostic ability. The ROC contrast results were all significant as well (Supplemental Table 2). In addition, the diagnostic ability of all models improved on adding the LDL-C discrete points, and most of them were effective in model stability and fitness (Supplemental Table 3). By applying the new models, our patients had better predictability of SICH in the NINDS standard (Fig. 3), the ECASS II standard (Supplemental Fig. 1), and STIS-MOST standard (Supplemental Fig. 2).
Supplemental Table 2. The Original and New Models with LDL variable (continuous) for Predicting Symptomatic Intracranial Hemorrhage.
| Model Odds Ratio (per score change) |
P value | LDL Odds Ratio (per mg/dL change) |
P value | ROC c statistics |
IDI (%) |
P value | Hosmer-Lemeshow statistics (χ2) |
P value | |
|---|---|---|---|---|---|---|---|---|---|
| Original Models by the NINDS Standard | |||||||||
| HAT | 1.739 (1.427–2.120) | < 0.0001* | – | – | 0.6575 | – | – | 0.153 (4 groups) | 0.9265 |
| SITS-SICH | 1.312 (1.179–1.461) | < 0.0001* | – | – | 0.6310 | – | – | 4.259 (7 groups) | 0.5128 |
| Cucchiara | 1.750 (1.375–2.227) | < 0.0001* | – | – | 0.6358 | – | – | 2.596 (4 groups) | 0.2731 |
| SEDAN | 1.599 (1.334–1.917) | < 0.0001* | – | – | 0.6521 | – | – | 3.338 (5 groups) | 0.3424 |
| SPAN-100 | 2.147 (1.308–3.525) | 0.0025* | – | – | 0.5567 | – | – | – | – |
| GRASPS | 1.074 (1.047–1.102) | < 0.0001* | – | – | 0.6698 | – | – | 6.995 (9 groups) | 0.4294 |
| THRIVE | 1.299 (1.162–1.453) | < 0.0001* | – | – | 0.6392 | – | – | 2.338 (7 groups) | 0.8007 |
| New model with LDL-C by the NINDS Standard | |||||||||
| HAT | 1.740 (1.404–2.157) | < 0.0001* | 0.990 (0.984–0.997) | 0.0023* | 0.6850 | 0.707 | 0.0034* | 2.723 (10 groups) | 0.9505 |
| SITS-SICH | 1.319 (1.172–1.484) | < 0.0001* | 0.990 (0.984–0.997) | 0.0023* | 0.6701 | 0.691 | 0.0100* | 11.856 (10 groups) | 0.1578 |
| Cucchiara | 1.956 (1.504–2.545) | < 0.0001* | 0.990 (0.984–0.997) | 0.0023* | 0.6842 | 0.904 | 0.0003* | 3.308 (10 groups) | 0.9136 |
| SEDAN | 1.664 (1.364–2.031) | < 0.0001* | 0.990 (0.984–0.997) | 0.0023* | 0.7040 | 0.817 | 0.0018* | 20.615 (10 groups) | 0.0082* |
| SPAN-100 | 2.498 (1.472–4.241) | 0.0007* | 0.990 (0.984–0.997) | 0.0023* | 0.6369 | 0.775 | 0.0006* | 13.589 (10 groups) | 0.0931 |
| GRASPS | 1.074 (1.043–1.105) | < 0.0001* | 0.990 (0.984–0.996) | 0.0020* | 0.6873 | 0.626 | 0.0087* | 5.629 (10 groups) | 0.6887 |
| THRIVE | 1.323 (1.170–1.496) | < 0.0001* | 0.990 (0.984–0.997) | 0.0023* | 0.6713 | 0.773 | 0.0010* | 12.108 (10 groups) | 0.1465 |
| Original Models by the ECASS II Standard | |||||||||
| HAT | 1.702 (1.321–2.194) | < 0.0001* | – | – | 0.6532 | – | – | 0.9222 (4 groups) | 0.6306 |
| SITS-SICH | 1.377 (1.215–1.586) | < 0.0001* | – | – | 0.6638 | – | – | 5.6208 (7 groups) | 0.3449 |
| Cucchiara | 1.807 (1.322–2.469) | 0.0002* | – | – | 0.6434 | – | – | 9.6871 (4 groups) | 0.0079* |
| SEDAN | 1.791 (1.420–2.258) | < 0.0001* | – | – | 0.6975 | – | – | 5.6336 (5 groups) | 0.1309 |
| SPAN-100 | 1.905 (0.990–3.665) | 0.0536 | – | – | 0.5466 | – | – | – | – |
| GRASPS | 1.084 (1.048–1.122) | < 0.0001* | – | – | 0.6890 | – | – | 7.0191 (9 groups) | 0.4269 |
| THRIVE | 1.279 (1.107–1.476) | 0.0008* | – | – | 0.6361 | – | – | 3.9933 (7 groups) | 0.5504 |
| New model with LDL-C by the ECASS II Standard | |||||||||
| HAT | 1.735 (1.311–2.297) | < 0.0001* | 0.988 (0.980–0.996) | 0.0042* | 0.7082 | 0.475 | 0.0577 | 9.989 (10 groups) | 0.2658 |
| SITS-SICH | 1.414 (1.219–1.641) | < 0.0001* | 0.988 (0.980–0.996) | 0.0042* | 0.7067 | 0.732 | 0.0217* | 12.162 (10 groups) | 0.1441 |
| Cucchiara | 2.012 (1.425–2.843) | < 0.0001* | 0.988 (0.980–0.996) | 0.0042* | 0.6997 | 0.656 | 0.0184* | 12.171 (10 groups) | 0.1437 |
| SEDAN | 1.978 (1.524–2.567) | < 0.0001* | 0.988 (0.980–0.996) | 0.0042* | 0.7670 | 0.651 | 0.0054* | 14.015 (10 groups) | 0.0814 |
| SPAN-100 | 2.657 (1.346–5.246) | 0.0049* | 0.988 (0.980–0.996) | 0.0042* | 0.6524 | 0.659 | 0.0051* | 14.253 (10 groups) | 0.0754 |
| GRASPS | 1.088 (1.047–1.130) | < 0.0001* | 0.988 (0.980–0.996) | 0.0038* | 0.7231 | 0.510 | 0.0684 | 7.303 (10 groups) | 0.5043 |
| THRIVE | 1.324 (1.127–1.556) | 0.0006* | 0.988 (0.980–0.996) | 0.0042* | 0.6981 | 0.529 | 0.0330* | 14.008 (10 groups) | 0.0815 |
| Original Models by the SITS-MOST Standard | |||||||||
| HAT | 2.359 (1.634–3.495) | < 0.0001* | – | – | 0.7526 | – | – | 0.3629 (4 groups) | 0.8341 |
| SITS-SICH | 1.416 (1.179–1.701) | 0.0002* | – | – | 0.7090 | – | – | 4.7692 (7 groups) | 0.4447 |
| Cucchiara | 2.169 (1.378–3.414) | 0.0008* | – | – | 0.6894 | – | – | 24.080 (4 groups) | 0.0001* |
| SEDAN | 1.936 (1.398–2.680) | < 0.0001* | – | – | 0.7185 | – | – | 2.869 (5 groups) | 0.4122 |
| SPAN-100 | 2.394 (0.998–5.742) | 0.0504 | – | – | 0.5679 | – | – | – | – |
| GRASPS | 1.093 (1.041–1.147) | 0.0003* | – | – | 0.7041 | – | – | 6.046 (9 groups) | 0.5343 |
| THRIVE | 1.387 (1.128–1.705) | 0.0019* | – | – | 0.6792 | – | – | 10.576 (7 groups) | 0.0605 |
| New model with LDL-C by the SITS-MOST Standard | |||||||||
| HAT | 2.662 (1.733–4.091) | < 0.0001* | 0.987 (0.975–0.999) | 0.0373* | 0.8098 | 0.613 | 0.0541 | 3.894 (10 groups) | 0.8665 |
| SITS-SICH | 1.489 (1.207–1.836) | 0.0002* | 0.987 (0.975–0.999) | 0.0373* | 0.7680 | 0.419 | 0.0384* | 8.473 (10 groups) | 0.3887 |
| Cucchiara | 3.156 (1.831–5.441) | < 0.0001* | 0.987 (0.975–0.999) | 0.0373* | 0.7851 | 0.982 | 0.0391* | 9.803 (10 groups) | 0.2792 |
| SEDAN | 2.444 (1.655–3.610) | < 0.0001* | 0.987 (0.975–0.999) | 0.0373* | 0.8179 | 0.347 | 0.0207* | 12.351 (10 groups) | 0.1362 |
| SPAN-100 | 3.987 (1.554–10.245) | 0.0040* | 0.987 (0.975–0.999) | 0.0373* | 0.6713 | 0.553 | 0.0277* | 11.385 (10 groups) | 0.1808 |
| GRASPS | 1.107 (1.042–1.175) | < 0.0001* | 0.987 (0.974–0.999) | 0.0356* | 0.7512 | 0.476 | 0.0329* | 2.384 (10 groups) | 0.9669 |
| THRIVE | 1.497 (1.170–1.916) | 0.0013* | 0.987 (0.975–0.999) | 0.0373* | 0.7389 | 0.542 | 0.0839 | 14.946 (10 groups) | 0.0602 |
ECASS II, the European Cooperative Acute Stroke Study II; GRASPS, Glucose Race Age Sex Pressure Stroke Severity; HAT, Hemorrhage After Thrombolysis; LDL-C, lower density lipoprotein-cholesterol; NINDS, National Institute of Neurological Disorders and Stroke; ROC, receiver operating characteristic; SICH, symptomatic intracerebral hemorrhage; SPAN-100, Stroke Prognostication using Age and National Institutes of Health Stroke Scaleand-100.
Supplemental Table 3. Original and New Risk Scoring Systems Models with (discrete) LDL-C Scores for Predicting Symptomatic Intracranial Hemorrhage.
| Model Odds Ratio (per score change) |
P value | ROC c statistics |
Hosmer –Lemeshow statistics |
P value | |
|---|---|---|---|---|---|
| Original models | |||||
| HAT | 1.739 (1.427–2.120) | < 0.0001* | 0.6575 | 0.1527 (4 groups) | 0.9265 |
| SITS-SICH | 1.312 (1.179–1.461) | < 0.0001* | 0.6310 | 4.2587 (7 groups) | 0.5128 |
| Cucchiara | 1.750 (1.375–2.227) | < 0.0001* | 0.6358 | 2.5957 (4 groups) | 0.2731 |
| SEDAN | 1.599 (1.334–1.917) | < 0.0001* | 0.6521 | 3.3382 (5 groups) | 0.3424 |
| SPAN-100 | 2.147 (1.308–3.525) | 0.0025* | 0.5567 | – | – |
| GRASPS | 1.074 (1.047–1.102) | < 0.0001* | 0.6698 | 6.9952 (9 groups) | 0.4294 |
| THRIVE | 1.299 (1.162–1.453) | < 0.0001* | 0.6392 | 2.3377 (7 groups) | 0.8007 |
| New models with LDL-C risk scores by NINDS criteria | |||||
| HAT | 1.589 (1.352–1.869) | < 0.0001* | 0.6687 | 4.4057 (6 groups) | 0.3539 |
| SITS-SICH | 1.327 (1.200–1.467) | < 0.0001* | 0.6567 | 0.6450 (7 groups) | 0.9859 |
| Cucchiara | 1.530 (1.283–1.826) | < 0.0001* | 0.6434 | 0.1585 (5 groups) | 0.9840 |
| SEDAN | 1.560 (1.333–1.825) | < 0.0001* | 0.6756 | 4.5016 (5 groups) | 0.2117 |
| SPAN-100 | 1.543 (1.202–1.983) | 0.0007* | 0.5980 | 2.2371 (4 groups) | 0.3268 |
| GRASPS | 1.077 (1.049–1.104) | < 0.0001* | 0.6756 | 4.0071 (10 groups) | 0.8565 |
| THRIVE | 1.297 (1.172–1.435) | < 0.0001* | 0.6499 | 8.4462 (7 groups) | 0.1333 |
| New models with LDL-C risk scores by ECASS II criteria | |||||
| HAT | 1.601 (1.300–1.973) | < 0.0001* | 0.6790 | 4.9357 (6 groups) | 0.2940 |
| SITS-SICH | 1.406 (1.239–1.595) | < 0.0001* | 0.6888 | 7.4850 (7 groups) | 0.1870 |
| Cucchiara | 1.800 (1.357–2.388) | < 0.0001* | 0.6599 | 3.1769 (5 groups) | 0.2042 |
| SEDAN | 1.735 (1.415–2.126) | < 0.0001* | 0.7169 | 1.4369 (5 groups) | 0.6969 |
| SPAN-100 | 1.581 (1.411–2.190) | 0.0059* | 0.6015 | 1.2868 (4 groups) | 0.5255 |
| GRASPS | 1.087 (1.051–1.124) | < 0.0001* | 0.6963 | 5.5266 (10 groups) | 0.7001 |
| THRIVE | 1.290 (1.132–1.470) | < 0.0001* | 0.6571 | 9.7999 (7 groups) | 0.0811 |
| New models with LDL-C risk scores by SITS-MOST criteria | |||||
| HAT | 2.505 (1.748–3.590) | < 0.0001* | 0.7776 | 2.8237 (5 groups) | 0.4196 |
| SITS-SICH | 1.464 (1.222–1.754) | < 0.0001* | 0.7301 | 5.3503 (4 groups) | 0.3746 |
| Cucchiara | 2.277 (1.498–3.461) | < 0.0001* | 0.7234 | 13.1442 (4 groups) | 0.0014* |
| SEDAN | 1.972 (1.476–2.635) | < 0.0001* | 0.7596 | 1.6954 (5 groups) | 0.6380 |
| SPAN-100 | 2.039 (1.243–2.342) | 0.0047* | 0.6492 | 1.6072 (4 groups) | 0.4477 |
| GRASPS | 1.097 (1.046–1.152) | 0.0002* | 0.7140 | 3.8193 (10 groups) | 0.8730 |
| THRIVE | 1.421 (1.175–1.719) | < 0.0001* | 0.7035 | 7.3688 (7 groups) | 0.1946 |
ECASS II, the European Cooperative Acute Stroke Study II; GRASPS, Glucose Race Age Sex Pressure Stroke Severity; HAT, Hemorrhage After Thrombolysis; LDL-C, Low density lipoprotein-cholesterol; NINDS, National Institute of Neurological Disorders and Stroke; ROC, receiver operating characteristic; SICH, symptomatic intracerebral hemorrhage; SPAN-100, Stroke Prognostication using Age and National Institutes of Health Stroke Scaleand-100.
Fig. 3.
Validation study with adding discrete LDL-C scores as the new model. All of the new models (gray bar) were more accurate in predicting SICH by the NINDS standard.
Supplemental Fig. 1.
Validation Study with adding discrete LDL-C scores as the new model. All of the new models (gray bar) were more accurate in predicting SICH by the ECASS II standard.
Supplemental Fig. 2.
Validation Study with adding discrete LDL-C scores as the new model. All of the new models (gray bar) were more accurate in predicting SICH by the SITS-MOST standard.
Discussion
In this investigation, hyperlipidemia had a robust protective effect on the development of SICH among patients with acute ischemic stroke treated with IV thrombolysis, but not for the favorable functional outcomes at 30 and 90 days. The study confirmed that the association between the lipid profile and SICH was mostly attributable to LDL-C, and a level of LDL-C < 130 mg/dL had the greatest significant association with increased SICH.
In our cohorts, the ICH and SICH rates varied according to the NINDS, ECASS II, and SITS-MOST. Because the SITS-MOST standard had the most conservative definition, the SICH rates were markedly reduced in the hyperlipidemia and non-hyperlipidemia groups (0.27% and 1.46%, respectively). This was comparable to previous literature13, 14) and also reflected real-world data among Asian population. Moreover, our cohorts had high follow-up rates in both groups (92.2% and 90.4%, respectively, at 30 days; 86.1% and 87.7%, respectively, at 90 days). These high follow-up rates should strengthen our research by avoiding the selection bias.
In the validation section, we confirmed LDL-C had high diagnostic ability in predicting hemorrhagic transformation. Each of the modified risk scoring model implementing LDL-C variable had higher ROC statistics (the area under curve) in predicting SICH and maintained stable goodness of fit. The modified models in a way of LDL-C discrete points also exempted from the doubt of increasing diagnostic ability by adding another variable. For an example, the discrete points models of HAT score synthesized all scoring variables (including the LDL-C) into single value in a range from 0, 1, 2, ≥ 3 which called as total score. Only the total score was used as the independent variable in these modified models. These modified models verified our judgment and raised the practical ability (Fig. 3, Supplemental Figs. 1 and 2).
From earlier studies such as the INTERSTROKE study, we recognized that non-HDL-C was possibly connected with spontaneous ICH occurrence. Our study showed that increased TG may be protective, but it was only significant in the SITS-MOST standard. Referred to the previous literature of TG, which showed inconsistent results28–32), we supposed TG was not a reliable marker for hemorrhagic transformation. For increased HDL-C level, our results showed a paradoxically raised risk of hemorrhagic transformation despite only significant in the ECASS II standard. The relevant studies showed a similar trend for HDL-C29, 30, 33, 34), but most of their results were not significant like our study results. Regarding LDL-C, a recent study proposed that admission ICH volume in cube root was inversely proportional to admission LDL-C levels35). We considered that low LDL-C may modify the SICH through increasing ICH volume expansion, but all lipid profiles did not effectively alter the long-term outcomes. This warrants further studies.
The distinctive strengths of our study are (1) a longitudinal cohort study design with a large sample size of patients treated with a thrombolytic agent in comparison to previous studies, (2) determination of how much a lower level of LDL-C contributed to increase hemorrhagic transformation of SICH, (3) a solid definition of SICH by the NINDS, ECASS II, and SITS-MOST standards, (4) a validation study to substantiate our findings, and (5) a proper statistical estimation. We adopted the Poisson regression instead of logistic regression model because the former produces a more unbiased estimate when adjusting for confounders36, 37) and our prime data fulfilled the assumption of the Poisson regression (the count of SICH events was rare and the sample size of enrolled patients was large).
This study has some limitations. First, the TTT-AIS registry13, 14) has no exact information on whether patients treated with a thrombolytic agent took statins. However, we may identify the patients who were possibly statin-naive because the TNHI system had strict payment rule for statin and covered all residents in Taiwan. Although we cannot thoroughly discuss the interaction with statins, we found that these possibly statin-naive patients still had an increased association between low LDL-C and SICH (Supplemental Fig. 3 and Supplemental Table 4). Second, the TTT-AIS registry13, 14) had not enrolled patients treated with intra-arterial thrombectomy. The TTT-AIS was launched in 2004 at that time the intra-arterial thrombectomy technique had not been introduced in Taiwan. Third, the TTT-AIS registry had no nutrient-related information. Nonetheless, our results should stay free from the doubt of malnutrition influence. Compared to the neighboring Asian countries, the National Health and Nutrition Examination Survey (NHANES)38) in Taiwan reported that our population had the highest average number of body mass index and metabolic syndrome, and the prevalence of obesity was also proportional to increasing age. These also highlight the importance of this research investigating the association between thrombolytic outcomes and lipid profiles.
In conclusion, this study supports an association between reduced lipid profiles and increased SICH among patients with acute ischemic stroke treated with IV thrombolysis. LDL-C level of < 130 mg/dL is a candidate marker indicating increased SICH after IV thrombolysis.
Acknowledgments
Each author contributed to the conception and design of the study, acquisition, analysis, and interpretation of data. S.F.L wrote the first draft of the article.
Funding
This study was supported by grants from Ministry of Science and Technology (MOST) 104-2314-B-037-029- and KMUH 104-4R53.
Conflicts of Interests
The authors have no conflicts of interests to declare.
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