Why are you predicting failure to recover rather THAN DELIVERING EXACT PROTOCOLS THAT WILL RECOVER YOUR PATIENT? You're that fucking stupid you don't know that survivors want recovery rather than predicting failure to recover! WOW! That's absolute stupidity!
SDNN predicts 90-day disability after intravenous thrombolysis: autonomic dysfunction as a novel predictors in acute ischemic stroke
Xiaoyan Wu†
Jianjun Guo- Department of Neurology, The Fourth Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
Background: Recent studies have clarified the relationship between autonomic dysfunction and ischemic stroke location, etiology, and neurological outcomes. However, few studies have evaluated autonomic nervous system (ANS) function via heart rate variability (HRV) in patients undergoing intravenous thrombolysis. Moreover no HRV parameter has been conclusively established as an independent predictor of unfavorable prognosis in this clinical population.
Methods: We retrospectively analyzed data from acute ischemic stroke (AIS) patients treated with intravenous thrombolysis (IVT) between January 2021 and December 2023. HRV measurements were obtained within 7 days post-stroke to evaluate ANS function. Of the 150 patients included, a unfavorable outcome was defined as a modified Rankin Scale score >2 at 90-days. Multivariate logistic regression adjusted for potential confounders, was used to evaluate associations between HRV parameters and functional outcomes.
Results: Linear regression analyses revealed consistent associations between favorable functional outcomes and HRV parameters reflectiving both sympathetic and parasympathetic activity, assessed at 7- and 90-days post-stroke (all p < 0.05). In multivariable logistic regression model, a lower standard deviation of normal-to-normal intervals was identified as an independent Influencing factor of worse modified Rankin Scale scores after adjustment for potential confounders.
Conclusion: Impaired autonomic nervous system function in the acute phase of ischemic stroke may exert a sustained influence on recovery, extending to 90 days post-onset. Standard deviation of normal-to-normal intervals emerged as an independent risk factor for unfavorable prognosis in acute ischemic stroke patients treated with intravenous thrombolysis.
1 Introduction
Stroke continues to be a significant global public-health challenge and presents a severe threat to human health. Based on disability—adjusted life years (DALYs), it remains the second leading cause of death globally and the third leading cause of combined mortality and disability (1). In China, ischemic stroke is the predominant subtype, representing 65.3% of all stroke cases (2). Intravenous thrombolysis (IVT), as a standard treatment for acute ischemic stroke (AIS), has been shown to effectively reduce stroke-related disability by facilitating vascular recanalization (3, 4). Although intravenous IVT is a well-established treatment for AIS, post-thrombolysis neurological deterioration remains a substantial clinical issue in a considerable number of patients (5). Therefore, identifying and intervening factors that can affect the efficacy of IVT and is crucial for improving patient outcomes. Currently, most predictive markers focus on the hyperacute phase or short-term outcomes. There is still a gap in identifying transversal prognostic markers that persist from the acute phase into later recovery and can help explain functional outcomes.
A profound pathophysiological association exists between the dysfunction of the autonomic nervous system (ANS) and ischemic stroke. The regulation of the ANS in the brain is not achieved by a single “center” but relies on a widely distributed “central autonomic neural network”. This network primarily encompasses the insula, anterior cingulate cortex, prefrontal cortex, amygdala, hypothalamus, and brain stem (6). These regions collaborate through intricate connections to implement “top–down” regulation of the heart. When a stroke damages these network nodes or disrupts their connectivity, it leads to ANS abnormalities. There is evidence suggesting that there may be right - sided dominance of neural structures that control heart rate and heart rate variability (HRV) (7). This observation elucidates the pronounced disruption of HRV associated with damage to the right hemisphere, particularly regions integral to the limbic system and the salience network. Emerging evidence further indicates that post-stroke alterations in HRV may stem from impaired functional connectivity within resting-state brain networks (8).
While the pathophysiological mechanisms of the autonomic nervous system (ANS) in ischemic stroke are well-characterized, its clinical utility warrants further investigation. HRV, a non-invasive and quantifiable biomarker of ANS function, demonstrates significant clinical potential in this context. It provides an objective measure of the often-underestimated autonomic dysfunction following stroke: diminished HRV correlates with more severe neurological impairment, as indicated by higher NIHSS scores, and reflects both injury to autonomic regulatory centers and the magnitude of systemic stress mediated by the brain-heart axis (9). Furthermore, dynamic alterations in HRV serve as a robust predictor for the risk of major post-stroke complications, including malignant arrhythmias, cardiac injury, and infections (10), thereby providing a powerful tool for risk stratification in the acute phase—for instance, by identifying high-risk patients during the hyperacute stage. Additionally, the recovery trajectory of HRV demonstrates a significant association with long-term functional outcomes, maintaining substantial prognostic value even throughout the chronic rehabilitation period (11). In summary, the integration of multidimensional information-encompassing stroke severity, complication risk, and neural repair potential-enables HRV to serve as an objective and multifaceted quantitative tool across the full clinical management continuum, from acute-phase early warning to long-term outcome evaluation. Consequently, HRV has emerged not merely as an indicator of autonomic function, but as an independent prognostic biomarker that reflects the integrative capacity of higher-order neural networks, with direct implications for adverse neurological outcomes and elevated complication risk.
Building upon this foundation, the present study not only seeks to corroborate the association between HRV and stroke but places greater emphasis on its translation into a clinical tool possessing distinct and independent prognostic value for IVT-treated patients. We further introduce the novel concept that autonomic function exerts a continuous influence across the entire continuum of stroke recovery. This perspective offers a new theoretical framework and an evaluative target for subsequent investigations into neuroprotective or neuromodulatory interventions.
2 Materials and methods
2.1 Study population
This retrospective analysis included patients with AIS who were admitted to the Department of Neurology at The Fourth Affiliated Hospital of Guangzhou Medical University from January 2021 to December 2023. Eligible participants were those who received IVT within 4.5 h of symptom onset. Inclusion criteria comprised: (1) performance of 24-h Holter monitoring within 24 h post-thrombolysis and within 7 days of symptom onset; and (2) fulfillment of IVT eligibility according to the 2018 Chinese AIS Guidelines (11). Exclusion criteria were: (1) contraindications to IVT as specified in the aforementioned guidelines; (2) pre-existing cardiac disorders known to influence heart rate variability (HRV) parameters, including dilated cardiomyopathy, hypertrophic cardiomyopathy, acute coronary syndrome, heart failure, arrhythmias, or atrial fibrillation; (3) a medical history of hyperthyroidism, epilepsy, Parkinson’s disease, multiple sclerosis, anemia, or other conditions potentially affecting HRV; and (4) use of medications impacting the cardiac autonomic nervous system (e.g., digoxin, levodopa, β-blockers) prior to admission; (5) exclusion of participants from whom reliable HRV analysis could not be derived from 24-h electrocardiogram recordings owing to substantial signal interference; (6) presence of unstable clinical conditions, such as systemic inflammatory states, renal or hepatic failure, intracranial neoplasms, or active infectious diseases; (7) exclusion of cases identified as cardioembolic stroke based on the TOAST classification, to ensure that the observed HRV alterations more accurately reflect the specific impact of the acute stroke event on autonomic nervous system function. Written informed consent was obtained from all participants or their legally authorized representatives. The study protocol received approval from the Ethics Committee of The Fourth Affiliated Hospital of Guangzhou Medical University, and all procedures were conducted in accordance with the principles of the World Medical Association Declaration of Helsinki. The research flowchart is shown in Figure 1.
Figure 1. Algorithm for inclusion/exclusion of patients.
2.2 Clinical assessments
All patients were administered recombinant tissue plasminogen activator (rt-PA; alteplase, Boehringer Ingelheim, batch 202010) at a dose of 0.9 mg/kg (maximum 90 mg). Clinical evaluations were performed within 24 h of hospital admission. Collected data encompassed demographic characteristics, vascular risk factors (including hypertension, diabetes, smoking history, prior stroke, coronary artery disease, and medication use), NIHSS scores before and after thrombolysis, and stroke subtypes classified according to the TOAST criteria. Functional outcomes were assessed using the modified Rankin Scale (mRS) at 90 days, with a score >2 defined as an unfavorable outcome. Currently, there is no universally accepted definition for DNI. In the present study, favorable outcomes at 7 days post-treatment were defined as follows (12, 13): (1) an improvement of ≥4 points in NIHSS score from baseline; or (2) an improvement of ≥20% in NIHSS score from baseline. The NIHSS was assessed at admission in the emergency department by a certified neurologist prior to thrombolysis. At 90 days post-stroke, the mRS score was obtained via a standardized telephone interview conducted by a trained research coordinator, who was blinded to all baseline clinical information and HRV data.
2.3 Heart rate variability
HRV parameters were derived from 24-h Holter monitoring (B19900, Shenzhen Boying Dynamic ECG Analysis System), conducted within a post-onset window of 24 h to 7 days. Standard 12-lead ECG signals (I, II, III, aVF, aVL, aVR, V1–V6) were acquired to enable comprehensive cardiac cycle analysis. All assessments were carried out in a quiet examination room. To reduce potential confounding effects of circadian rhythm on heart rate variability, measurements were scheduled between 9:00 a.m. and 10:00 a.m., with ambient temperature maintained at 20 °C–24 °C. Prior to testing, patients rested in a supine position for 10 min. Beat-to-beat recordings were analyzed using specialized software to generate cardiac cycle patterns. For the purposes of this study, the wake phase was defined as 08:00 to 22:00, and the sleep phase as 22:00 to 08:00 the following day.
ECG monitoring was performed under naturalistic conditions (encompassing both active and resting states) at a sampling frequency of 250 Hz. Heart rate variability (HRV) was assessed across two primary domains: time-domain indices, which comprised (1) the standard deviation of normal-to-normal R-R intervals (SDNN), reflecting the overall variability in sinus rhythm, and (2) the root mean square of successive differences between adjacent R-R intervals (RMSSD), representing beat-to-beat variance in heart rate. The frequency-domain parameters assessed were: (1) Low Frequency (LF), corresponding to the spectral power between 0.04 and 0.15 Hz; (2) High Frequency (HF), representing the spectral power from 0.15 to 0.40 Hz; (3) Very Low Frequency (VLF), denoting the spectral power below 0.04 Hz; and (4) the ratio of low-frequency to high-frequency power (LF/HF). Additionally, a geometric approach based on R-R interval histogram distributions was applied-specifically, the Heart Rate Variability Triangular Index. This index is derived as the quotient of the total number of normal R-R intervals divided by the maximum bin height of the histogram, providing a geometric assessment of overall heart rate variability.
2.4 Statistical analysis
All statistical analyses were conducted using SPSS (version 26.0) and R (version 4.4.1). Normality of variable distributions was evaluated with the Kolmogorov–Smirnov test. Normally distributed continuous variables are presented as mean ± standard deviation and compared between independent groups using Student’s t-test. Non-normally distributed continuous variables are summarized as median (interquartile range) and compared using the Mann–Whitney U test. Categorical variables are reported as frequencies and percentages, with between-group differences assessed using the chi-square test or Fisher’s exact test, as appropriate.
To assess the association between HRV and 7-day or 3-month clinical outcomes in patients receiving IVT, multivariable logistic regression models were employed. Sensitivity analyses were conducted using four distinct models: (1) unadjusted; (2) adjusted for age and sex; (3) additionally adjusted for vascular risk factors (including smoking, alcohol consumption, hypertension, diabetes, dyslipidemia, and prior ischemic stroke); and (4) further adjusted for clinical parameters (including admission systolic and diastolic blood pressure, heart rate, fasting glucose, NIHSS score, onset-to-admission time, TOAST classification, and antihypertensive medication). All statistical tests were two-sided, with significance defined as p < 0.05.
3 Result
3.1 Baseline characteristics of AIS patients treated with intravenous alteplase
At the 7-day follow-up, unfavorable outcomes were recorded in 43 patients (28.7%), a proportion that decreased to 40 patients (26.7%) at 90 days. Baseline characteristics, stratified according to 90-day clinical outcomes, are summarized in Table 1. Patients with unfavorable outcomes were significantly older than those with favorable outcomes (mean age 69.33 vs. 62.68 years). A history of ischemic stroke was significantly more prevalent in the unfavorable outcome group (35.0% vs. 14.7%; p = 0.002). Several key clinical parameters-including fasting glucose (6.02 vs. 5.19 mmol/L, p = 0.043), systolic blood pressure (162.15 vs. 153.04 mmHg, p = 0.038), and admission NIHSS scores (median 9 vs. 4; p < 0.001)—differed significantly between groups, with more favorable values observed among patients with positive outcomes. In addition, the distribution of TOAST etiological subtypes differed significantly between the two outcome groups (p = 0.001).
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