Individual Patient Data Meta-Analysis of Dynamic Cerebral Autoregulation and Functional Outcome After Ischemic Stroke

Author:

Beishon Lucy12ORCID,Vasilopoulos Terrie3ORCID,Salinet Angela S.M.4ORCID,Levis Brooke56,Barnes Samuel17ORCID,Hills Eleanor1,Ramesh Pranav1ORCID,Gkargkoula Panagoula7,Minhas Jatinder S.12ORCID,Castro Pedro8ORCID,Brassard Patrice9,Goettel Nicolai10ORCID,Gommer Erik D.11ORCID,Jara Jose Luis12ORCID,Liu Jia13ORCID,Mueller Martin14,Nasr Nathalie15,Payne Stephen16ORCID,Robertson Andrew D.17ORCID,Simpson David18ORCID,Robinson Thompson G.12ORCID,Panerai Ronney B.12,Nogueira Ricardo C.4ORCID

Affiliation:

1. Department of Cardiovascular Sciences, University of Leicester, United Kingdom (L.B., S.B., E.H., P.R., J.S.M., T.G.R., R.B.P.).

2. NIHR Leicester Biomedical Research Centre, British Heart Foundation Cardiovascular Research Centre, Glenfield Hospital, United Kingdom (L.B., J.S.M., T.G.R., R.B.P.).

3. Department of Anesthesiology, University of Florida College of Medicine, Gainesville (T.V.).

4. Neurology Department, Hospital das Clinicas, School of Medicine, University of Sao Paulo, Brazil (A.S.M.S., R.C.N.).

5. Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada (B.L.).

6. Centre for Prognosis Research, School of Medicine, Keele University, Staffordshire, United Kingdom (B.L.).

7. Department of Stroke Medicine, University Hospitals of Leicester NHS Trust, Leicester, United Kingdom (S.B., P.G.).

8. Department of Neurology, Centro Hospitalar Universitário de São João, Faculty of Medicine, University of Porto (P.C.).

9. Département de Kinésiologie, Faculté de Médecine, Institut Universitaire de Cardiologie et de pneumologie de Québec (P.B.).

10. Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA (N.G.).

11. Department of Clinical Neurophysiology, Maastricht University Medical Centre, the Netherlands (E.D.G.).

12. Departamento de Ingeniería Informática, Universidad de Santiago de Chile (J.L.J.).

13. Shenzhen Institutes of Advanced Technology at the Chinese Academy of Sciences in Shenzhen, China (J.L.).

14. Department of Neurology and Neurorehabilitation, Spitalstrasse, CH 6000 Lucerne (M.M.).

15. Department of Neurology, Poitiers University Hospital, Laboratoire de Neurosciences Expérimentales et Cliniques, University of Poitiers, France (N.N.).

16. Institute of Applied Mechanics, National Taiwan University, Taipei (S.P.).

17. Schlegel-UW Research Institute for Aging, University of Waterloo, ON, CA (A.D.R.).

18. Faculty of Engineering and Physical Sciences, University of Southampton (D.S.).

Abstract

BACKGROUND: The relationship between dynamic cerebral autoregulation (dCA) and functional outcome after acute ischemic stroke (AIS) is unclear. Previous studies are limited by small sample sizes and heterogeneity. METHODS: We performed a 1-stage individual patient data meta-analysis to investigate associations between dCA and functional outcome after AIS. Participating centers were identified through a systematic search of the literature and direct invitation. We included centers with dCA data within 1 year of AIS in adults aged over 18 years, excluding intracerebral or subarachnoid hemorrhage. Data were obtained on phase, gain, coherence, and autoregulation index derived from transfer function analysis at low-frequency and very low-frequency bands. Cerebral blood velocity, arterial pressure, end-tidal carbon dioxide, heart rate, stroke severity and sub-type, and comorbidities were collected where available. Data were grouped into 4 time points after AIS: <24 hours, 24 to 72 hours, 4 to 7 days, and >3 months. The modified Rankin Scale assessed functional outcome at 3 months. Modified Rankin Scale was analyzed as both dichotomized (0 to 2 versus 3 to 6) and ordinal (modified Rankin Scale scores, 0–6) outcomes. Univariable and multivariable analyses were conducted to identify significant relationships between dCA parameters, comorbidities, and outcomes, for each time point using generalized linear (dichotomized outcome), or cumulative link (ordinal outcome) mixed models. The participating center was modeled as a random intercept to generate odds ratios with 95% CIs. RESULTS: The sample included 384 individuals (35% women) from 7 centers, aged 66.3±13.7 years, with predominantly nonlacunar stroke (n=348, 69%). In the affected hemisphere, higher phase at very low-frequency predicted better outcome (dichotomized modified Rankin Scale) at <24 (crude odds ratios, 2.17 [95% CI, 1.47–3.19]; P <0.001) hours, 24–72 (crude odds ratios, 1.95 [95% CI, 1.21–3.13]; P =0.006) hours, and phase at low-frequency predicted outcome at 3 (crude odds ratios, 3.03 [95% CI, 1.10–8.33]; P =0.032) months. These results remained after covariate adjustment. CONCLUSIONS: Greater transfer function analysis-derived phase was associated with improved functional outcome at 3 months after AIS. dCA parameters in the early phase of AIS may help to predict functional outcome.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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