Dataset Information

Cerebral autoregulation after subarachnoid hemorrhage: comparison of three methods.

ABSTRACT: In patients after subarachnoid hemorrhage (SAH) failure of cerebral autoregulation is associated with delayed cerebral ischemia (DCI). Various methods of assessing autoregulation are available, but their predictive values remain unknown. We characterize the relationship between different indices of autoregulation. Patients with SAH within 5 days were included in a prospective study. The relationship between three indices of autoregulation was analyzed: two indices calculated using spontaneous blood pressure fluctuations, Sxa (based on transcranial Doppler) and TOxa (based on near-infrared spectroscopy); and transient hyperemic response test (THRT) where a brief compression of the common carotid artery is used. The predictive value of indices was assessed using data from the first 5 days. Overall there was only moderate correlation between indices. However, both Sxa and TOxa showed good accuracy in predicting impaired autoregulation evidenced by a negative THRT (area under the curve (AUC): 0.788, 95% CI: 0.723 to 0.854 and AUC: 0.827, 95% CI: 0.769 to 0.885, respectively). All indices proved accurate in predicting DCI when 0- to 5-day data were used (AUC: 0.801, 95% CI: 0.660 to 0.942; AUC: 0.857, 95% CI: 0.731 to 0.984, AUC: 0.796, 95% CI: 0.658 to 0.934 for THRT, Sxa, and TOxa, respectively). Combining all three indices had 100% specificity for predicting DCI. While multiple colinearities exist between the assessed methods, multimodal monitoring of cerebral autoregulation can aid in predicting DCI.

SUBMITTER: Budohoski KP

PROVIDER: S-EPMC3587818 | biostudies-other | 2013 Mar

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Cerebral autoregulation after subarachnoid hemorrhage: comparison of three methods.

Budohoski Karol P KP Czosnyka Marek M Smielewski Peter P Varsos Georgios V GV Kasprowicz Magdalena M Brady Ken M KM Pickard John D JD Kirkpatrick Peter J PJ

Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism 20121212 3

In patients after subarachnoid hemorrhage (SAH) failure of cerebral autoregulation is associated with delayed cerebral ischemia (DCI). Various methods of assessing autoregulation are available, but their predictive values remain unknown. We characterize the relationship between different indices of autoregulation. Patients with SAH within 5 days were included in a prospective study. The relationship between three indices of autoregulation was analyzed: two indices calculated using spontaneous bl ...[more]

PMID: 23232948

Similar Datasets

Project description:Subarachnoid hemorrhage (SAH) is a common form of hemorrhagic stroke associated with high rates of mortality and severe disability. SAH patients often develop severe neurological deficits days after ictus, events attributed to a phenomenon referred to as delayed cerebral ischemia (DCI). Recent studies indicate that SAH-induced DCI results from a multitude of cerebral circulatory disturbances including cerebral autoregulation malfunction. Cerebral autoregulation incorporates the influence of blood pressure (BP) on arterial diameter in the homeostatic regulation of cerebral blood flow (CBF), which is necessary for maintaining constant brain perfusion during physiological swings in systemic BP. In this study, we quantitatively examined the impact of SAH on cerebral autoregulation using a mouse endovascular perforation model and a newly developed approach combining absolute and relative CBF measurements. This method enables a direct quantitative comparison of cerebral autoregulation between individual animals (e.g., SAH vs. control or sham-operated mice), which cannot be done solely using relative CBF changes by laser Doppler flowmetry. Here, absolute CBF was measured via injection of fluorescent microspheres at a baseline BP. In separate groups of animals, in vivo laser Doppler flowmetry was used to measure relative CBF changes over a range of BP using phlebotomy and the pressor phenylephrine to lower and raise BP, respectively. Absolute CBF measurements from microspheres were then used to calibrate laser Doppler measurements to calculate the relationship between CBF and BP, i.e., "cerebral autoregulation curves." Un-operated and sham-operated groups exhibited similar cerebral autoregulatory curves, showing comparable levels of relatively constant CBF over a range of BP from ~80 mmHg to ~130 mmHg. In contrast, SAH animals exhibited a narrower autoregulatory range of BP, which was primarily due to a decrease in the upper limit of BP whereby cerebral autoregulation was maintained. Importantly, SAH animals also exhibited a marked decrease in CBF throughout the entire range of BP. In sum, this study provides evidence of the dramatic reduction in cortical CBF and the diminished range of autoregulation after SAH. Furthermore, this novel methodology should pave the way for future studies examining pathological mechanisms and/or therapeutic strategies targeting impaired cerebral autoregulation, a pathology common to many cardiovascular and cerebrovascular disorders.

Project description:The diagnosis of cerebral vasospasm after Subarachnoid-Hemorrhage is currently very difficult, additional tools such as blood biomarkers are necessary. We tested the ability of gene expression profiles of blood cells to predict vasospasm. 32 patients suffering subarachnoid-hemorrhage were included in this prospective monocentre study. They were grouped according to have a complicated cerebral vasospasm (Vasospasm) or not (Control) and Paired according to age (+/- 10 years), sex, Fisher grade (+/- 1), location, smoking (at least 3 first parameters). Gene expression profiles of blood cells were determined using 25,000~gene microarray. Blood sample: 2.5 mL harvested in PAXgene® Blood RNA tubes (PreAnalytix) RNA extraction: PAXgene® Blood RNA kit (Qiagen). We used a Universel Reference RNA (Stratagene). RNA amplification and labelling: kit Amino Allyl MessageAmp II (Ambion). We hybridized 4 microarrays per patient using pangenomic microarrays from the "Réseau National des Génopôles" (Illkirch, France). 2 slides were hybridized with reference RNA labelled Cy3 and patient RNA labelled Cy5, and 2 slides were hybridized with reference RNA labelled Cy5 and patient RNA labelled Cy3. Hybridation : Agilent protocol with few modifications : 750 ng of each labelled RNA were hubriddized at 60°C during 17 hours in an Aglient hybridization oven. After washings, Slides were scanned with a GenePix 4000B scanner (Molecular Devices). Image intensity data were extracted with GenePix Pro 6.0 analysis software. Quantification of Cy3 and Cy5 and selection of good spots were performed using the MAIA software (Novikov E and Barillot E. Software package for automatic microarray image analysis (MAIA). The ACUITY software was then used to normalize log ratios Cy3/Cy5 with Lowess non linear normalization, to filter out genes not present in at least 3 slides out of 4, to evaluate the reproducibility of the 4 microarrays of each patient (hierarchical clustering, Self Organizing Maps). Statistical analyses to insure reproducibility was performed using Excel (correlation coefficients, ANOVA). Only slides that passed all reprocubility tests were validated.

Project description:BackgroundTimely and accurate prediction of delayed cerebral ischemia is critical for improving the prognosis of patients with aneurysmal subarachnoid hemorrhage. Machine learning (ML) algorithms are increasingly regarded as having a higher prediction power than conventional logistic regression (LR). This study aims to construct LR and ML models and compare their prediction power on delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage (aSAH).MethodsThis was a multicenter, retrospective, observational cohort study that enrolled patients with aneurysmal subarachnoid hemorrhage from five hospitals in China. A total of 404 aSAH patients were prospectively enrolled. We randomly divided the patients into training (N = 303) and validation cohorts (N = 101) according to a ratio of 75-25%. One LR and six popular ML algorithms were used to construct models. The area under the receiver operating characteristic curve (AUC), accuracy, balanced accuracy, confusion matrix, sensitivity, specificity, calibration curve, and Hosmer-Lemeshow test were used to assess and compare the model performance. Finally, we calculated each feature of importance.ResultsA total of 112 (27.7%) patients developed DCI. Our results showed that conventional LR with an AUC value of 0.824 (95%CI: 0.73-0.91) in the validation cohort outperformed k-nearest neighbor, decision tree, support vector machine, and extreme gradient boosting model with the AUCs of 0.792 (95%CI: 0.68-0.9, P = 0.46), 0.675 (95%CI: 0.56-0.79, P < 0.01), 0.677 (95%CI: 0.57-0.77, P < 0.01), and 0.78 (95%CI: 0.68-0.87, P = 0.50). However, random forest (RF) and artificial neural network model with the same AUC (0.858, 95%CI: 0.78-0.93, P = 0.26) were better than the LR. The accuracy and the balanced accuracy of the RF were 20.8% and 11% higher than the latter, and the RF also showed good calibration in the validation cohort (Hosmer-Lemeshow: P = 0.203). We found that the CT value of subarachnoid hemorrhage, WBC count, neutrophil count, CT value of cerebral edema, and monocyte count were the five most important features for DCI prediction in the RF model. We then developed an online prediction tool (https://dynamic-nomogram.shinyapps.io/DynNomapp-DCI/) based on important features to calculate DCI risk precisely.ConclusionsIn this multicenter study, we found that several ML methods, particularly RF, outperformed conventional LR. Furthermore, an online prediction tool based on the RF model was developed to identify patients at high risk for DCI after SAH and facilitate timely interventions.Clinical trial registrationhttp://www.chictr.org.cn, Unique identifier: ChiCTR2100044448.

Dataset Information

Cerebral autoregulation after subarachnoid hemorrhage: comparison of three methods.

Publications

Cerebral autoregulation after subarachnoid hemorrhage: comparison of three methods.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets