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Preoperative Heart Rate Variability as Predictors of Vagus Nerve Stimulation Outcome in Patients with Drug-resistant Epilepsy

Liu, Hong-Yun ; Yang, Zhao ; Meng, Fan-Gang ; [et al.]

Springer Science and Business Media LLC ; 2018

In: Scientific Reports Vol. 8, No. 1 ( 2018-03-01)

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In: Scientific Reports, Springer Science and Business Media LLC, Vol. 8, No. 1 ( 2018-03-01)

Abstract: Vagus nerve stimulation (VNS) is an adjunctive treatment for drug-resistant epilepsy (DRE). However, it is still difficult to predict which patients will respond to VNS treatment and to what extent. We aim to explore the relationship between preoperative heart rate variability (HRV) and VNS outcome. 50 healthy control subjects and 63 DRE patients who had received VNS implants and had at least one year of follow up were included. The preoperative HRV were analyzed by traditional linear methods and heart rhythm complexity analyses with multiscale entropy (MSE). DRE patients had significantly lower complexity indices (CI) as well as traditional linear HRV measurements than healthy controls. We also found that non-responders 0 had significantly lower preoperative CI including Area 1–5, Area 6–15 and Area 6–20 than those in the responders 0 while those of the non-responders 50 had significantly lower RMSSD, pNN50, VLF, LF, HF, TP and LF/HF than the responders 50 . In receiver operating characteristic (ROC) curve analysis, Area 6–20 and RMSSD had the greatest discriminatory power for the responders 0 and non-responders 0 , responders 50 and non-responders 50 , respectively. Our results suggest that preoperative assessment of HRV by linear and MSE analysis can help in predicting VNS outcomes in patients with DRE.

Type of Medium: Online Resource

ISSN: 2045-2322

URL: Article

DOI: 10.1038/s41598-018-21669-3

Language: English

Publisher: Springer Science and Business Media LLC

Publication Date: 2018

detail.hit.zdb_id: 2615211-3

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Comparison of the real‐world effectiveness of vertical versus lateral functional hemispherotomy techniques for pediatric drug‐resistant epilepsy: A post hoc analysis of the HOPS study

Fallah, Aria ; Lewis, Evan ; Ibrahim, George M. ; [et al.]

Wiley ; 2021

In: Epilepsia Vol. 62, No. 11 ( 2021-11), p. 2707-2718

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In: Epilepsia, Wiley, Vol. 62, No. 11 ( 2021-11), p. 2707-2718

Abstract: This study was undertaken to determine whether the vertical parasagittal approach or the lateral peri‐insular/peri‐Sylvian approach to hemispheric surgery is the superior technique in achieving long‐term seizure freedom. Methods We conducted a post hoc subgroup analysis of the HOPS (Hemispheric Surgery Outcome Prediction Scale) study, an international, multicenter, retrospective cohort study that identified predictors of seizure freedom through logistic regression modeling. Only patients undergoing vertical parasagittal, lateral peri‐insular/peri‐Sylvian, or lateral trans‐Sylvian hemispherotomy were included in this post hoc analysis. Differences in seizure freedom rates were assessed using a time‐to‐event method and calculated using the Kaplan–Meier survival method. Results Data for 672 participants across 23 centers were collected on the specific hemispherotomy approach. Of these, 72 (10.7%) underwent vertical parasagittal hemispherotomy and 600 (89.3%) underwent lateral peri‐insular/peri‐Sylvian or trans‐Sylvian hemispherotomy. Seizure freedom was obtained in 62.4% (95% confidence interval [CI] = 53.5%–70.2%) of the entire cohort at 10‐year follow‐up. Seizure freedom was 88.8% (95% CI = 78.9%–94.3%) at 1‐year follow‐up and persisted at 85.5% (95% CI = 74.7%–92.0%) across 5‐ and 10‐year follow‐up in the vertical subgroup. In contrast, seizure freedom decreased from 89.2% (95% CI = 86.3%–91.5%) at 1‐year to 72.1% (95% CI = 66.9%–76.7%) at 5‐year to 57.2% (95% CI = 46.6%–66.4%) at 10‐year follow‐up for the lateral subgroup. Log‐rank test found that vertical hemispherotomy was associated with durable seizure‐free progression compared to the lateral approach ( p = .01). Patients undergoing the lateral hemispherotomy technique had a shorter time‐to‐seizure recurrence (hazard ratio = 2.56, 95% CI = 1.08–6.04, p = .03) and increased seizure recurrence odds (odds ratio = 3.67, 95% CI = 1.05–12.86, p = .04) compared to those undergoing the vertical hemispherotomy technique. Significance This pilot study demonstrated more durable seizure freedom of the vertical technique compared to lateral hemispherotomy techniques. Further studies, such as prospective expertise‐based observational studies or a randomized clinical trial, are required to determine whether a vertical approach to hemispheric surgery provides superior long‐term seizure outcomes.

Type of Medium: Online Resource

ISSN: 0013-9580 , 1528-1167

URL: Issue

URL: Article

DOI: 10.1111/epi.v62.11

DOI: 10.1111/epi.17021

RVK:

XA 10000

Language: English

Publisher: Wiley

Publication Date: 2021

detail.hit.zdb_id: 2002194-X

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Hemispherectomy Outcome Prediction Scale: Development and validation of a seizure freedom prediction tool

Weil, Alexander G. ; Lewis, Evan C. ; Ibrahim, George M. ; [et al.]

Wiley ; 2021

In: Epilepsia Vol. 62, No. 5 ( 2021-05), p. 1064-1073

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In: Epilepsia, Wiley, Vol. 62, No. 5 ( 2021-05), p. 1064-1073

Abstract: To develop and validate a model to predict seizure freedom in children undergoing cerebral hemispheric surgery for the treatment of drug‐resistant epilepsy. Methods We analyzed 1267 hemispheric surgeries performed in pediatric participants across 32 centers and 12 countries to identify predictors of seizure freedom at 3 months after surgery. A multivariate logistic regression model was developed based on 70% of the dataset (training set) and validated on 30% of the dataset (validation set). Missing data were handled using multiple imputation techniques. Results Overall, 817 of 1237 (66%) hemispheric surgeries led to seizure freedom (median follow‐up = 24 months), and 1050 of 1237 (85%) were seizure‐free at 12 months after surgery. A simple regression model containing age at seizure onset, presence of generalized seizure semiology, presence of contralateral 18‐fluoro‐2‐deoxyglucose–positron emission tomography hypometabolism, etiologic substrate, and previous nonhemispheric resective surgery is predictive of seizure freedom (area under the curve = .72). A Hemispheric Surgery Outcome Prediction Scale (HOPS) score was devised that can be used to predict seizure freedom. Significance Children most likely to benefit from hemispheric surgery can be selected and counseled through the implementation of a scale derived from a multiple regression model. Importantly, children who are unlikely to experience seizure control can be spared from the complications and deficits associated with this surgery. The HOPS score is likely to help physicians in clinical decision‐making.

Type of Medium: Online Resource

ISSN: 0013-9580 , 1528-1167

URL: Issue

URL: Article

DOI: 10.1111/epi.v62.5

DOI: 10.1111/epi.16861

RVK:

XA 10000

Language: English

Publisher: Wiley

Publication Date: 2021

detail.hit.zdb_id: 2002194-X

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Development of an online calculator for the prediction of seizure freedom following pediatric hemispherectomy using HOPS

Weil, Alexander G. ; Dimentberg, Evan ; Lewis, Evan ; [et al.]

Wiley ; 2023

In: Epilepsia

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In: Epilepsia, Wiley

Abstract: Although hemispheric surgeries are among the most effective procedures for drug‐resistant epilepsy (DRE) in the pediatric population, a large variability in outcomes remains. Identifying ideal hemispherectomy candidates is imperative to maximize the potential for seizure freedom. The objective was to develop an online, freely‐accesible tool that accurately predicts the probability of seizure freedom for any patient at 1‐, 2‐, and 5‐years post‐hemispherectomy to provide clinicians accessible and reliable prognostic information to complement clinical judgement. Methods Retrospective data of all pediatric patients with DRE and seizure outcome data from the original Hemispherectomy Outcome Prediction Scale (HOPS) study were included. The primary outcome of interest was time‐to‐seizure recurrence. A multivariate Cox proportional‐hazards regression model was developed to predict the likelihood of post‐hemispheric surgery seizure freedom duration based on a combination of variables identified by clinical judgement and inferential statistics as predictive of the primary outcome. The final model from this study was encoded in a publicly accessible online calculator on the (iNEST) website . Results The selected variables for inclusion in the final model included the 5 original HOPS variables (age at seizure onset, etiologic substrate, seizure semiology, prior non‐hemispheric resective surgery, and contralateral FDG‐PET hypometabolism) and 3 additional variables (age at surgery, history of infantile spasms, and magnetic resonance (MR) imaging lesion). Predictors of shorter time‐to‐seizure recurrence included younger age at seizure onset, older age at surgery, prior resective surgery, generalized seizure semiology, FDG‐PET hypometabolism contralateral to side of surgery, contralateral MR imaging lesion, non‐lesional MR imaging, non‐stroke etiologies, and history of infantile spasms. The area under the curve (AUC) of the final model was 73.0%. Significance Online calculators are efficient, cost‐free tools that can facilitate physicians in risk‐estimation and inform joint decision‐making with families, potentially leading to greater satisfaction. Although the HOPS data was previously validated in the first analysis, the authors encourage prospective external validation of this new tool.

Type of Medium: Online Resource

ISSN: 0013-9580 , 1528-1167

URL: Article

DOI: 10.1111/epi.17689

RVK:

XA 10000

Language: English

Publisher: Wiley

Publication Date: 2023

detail.hit.zdb_id: 2002194-X

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Hemispheric Surgery Outcome Prediction Scale: Development and Validation of a Seizure Freedom Prediction Tool

Fallah, Aria ; Weil, Alexander G. ; Lewis, Evan C. ; [et al.]

Elsevier BV ; 2020

In: SSRN Electronic Journal

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In: SSRN Electronic Journal, Elsevier BV

Type of Medium: Online Resource

ISSN: 1556-5068

URL: Article

DOI: 10.2139/ssrn.3514748

Language: English

Publisher: Elsevier BV

Publication Date: 2020

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Data_Sheet_1.PDF

Fang, Xi ; Liu, Hong-Yun ; Wang, Zhi-Yan ; [et al.]

Frontiers Media SA ; 2021

In: Frontiers in Neurology Vol. 12 ( 2021-7-7)

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In: Frontiers in Neurology, Frontiers Media SA, Vol. 12 ( 2021-7-7)

Abstract: Objective: Vagus nerve stimulation (VNS) is an adjunctive and well-established treatment for patients with drug-resistant epilepsy (DRE). However, it is still difficult to identify patients who may benefit from VNS surgery. Our study aims to propose a VNS outcome prediction model based on machine learning with multidimensional preoperative heart rate variability (HRV) indices. Methods: The preoperative electrocardiography (ECG) of 59 patients with DRE and of 50 healthy controls were analyzed. Responders were defined as having at least 50% average monthly seizure frequency reduction at 1-year follow-up. Time domain, frequency domain, and non-linear indices of HRV were compared between 30 responders and 29 non-responders in awake and sleep states, respectively. For feature selection, univariate filter and recursive feature elimination (RFE) algorithms were performed to assess the importance of different HRV indices to VNS outcome prediction and improve the classification performance. Random forest (RF) was used to train the classifier, and leave-one-out (LOO) cross-validation was performed to evaluate the prediction model. Results: Among 52 HRV indices, 49 showed significant differences between DRE patients and healthy controls. In sleep state, 35 HRV indices of responders were significantly higher than those of non-responders, while 16 of them showed the same differences in awake state. Low-frequency power (LF) ranked first in the importance ranking results by univariate filter and RFE methods, respectively. With HRV indices in sleep state, our model achieved 74.6% accuracy, 80% precision, 70.6% recall, and 75% F1 for VNS outcome prediction, which was better than the optimal performance in awake state (65.3% accuracy, 66.4% precision, 70.5% recall, and 68.4% F1). Significance: With the ECG during sleep state and machine learning techniques, the statistical model based on preoperative HRV could achieve a better performance of VNS outcome prediction and, therefore, help patients who are not suitable for VNS to avoid the high cost of surgery and possible risks of long-term stimulation.

Type of Medium: Online Resource

ISSN: 1664-2295

URL: Article

DOI: 10.3389/fneur.2021.691328

DOI: 10.3389/fneur.2021.691328.s001

Language: Unknown

Publisher: Frontiers Media SA

Publication Date: 2021

detail.hit.zdb_id: 2564214-5

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Haemodynamics-Driven Developmental Pruning of Brain Vasculature in Zebrafish

Chen, Qi ; Jiang, Luan ; Li, Chun ; [et al.]

Public Library of Science (PLoS) ; 2012

In: PLoS Biology Vol. 10, No. 8 ( 2012-8-14), p. e1001374-

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In: PLoS Biology, Public Library of Science (PLoS), Vol. 10, No. 8 ( 2012-8-14), p. e1001374-

Type of Medium: Online Resource

ISSN: 1545-7885

URL: Article

DOI: 10.1371/journal.pbio.1001374

DOI: 10.1371/journal.pbio.1001374.s001

DOI: 10.1371/journal.pbio.1001374.s002

DOI: 10.1371/journal.pbio.1001374.s003

DOI: 10.1371/journal.pbio.1001374.s004

DOI: 10.1371/journal.pbio.1001374.s005

DOI: 10.1371/journal.pbio.1001374.s006

DOI: 10.1371/journal.pbio.1001374.s007

DOI: 10.1371/journal.pbio.1001374.s008

DOI: 10.1371/journal.pbio.1001374.s009

DOI: 10.1371/journal.pbio.1001374.s010

DOI: 10.1371/journal.pbio.1001374.s011

DOI: 10.1371/journal.pbio.1001374.s012

DOI: 10.1371/journal.pbio.1001374.s013

DOI: 10.1371/journal.pbio.1001374.s014

DOI: 10.1371/journal.pbio.1001374.s015

DOI: 10.1371/journal.pbio.1001374.s016

DOI: 10.1371/journal.pbio.1001374.s017

DOI: 10.1371/journal.pbio.1001374.s018

DOI: 10.1371/journal.pbio.1001374.s019

DOI: 10.1371/journal.pbio.1001374.s020

DOI: 10.1371/journal.pbio.1001374.s021

DOI: 10.1371/journal.pbio.1001374.s022

DOI: 10.1371/journal.pbio.1001374.s023

DOI: 10.1371/journal.pbio.1001374.s024

DOI: 10.1371/journal.pbio.1001374.s025

Language: English

Publisher: Public Library of Science (PLoS)

Publication Date: 2012

detail.hit.zdb_id: 2126773-X

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A series of bis-pyridyl-bis-amide-modulated metal–organic frameworks: formation, transformation and selectivity for the efficient detection of multiple analytes

Zhang, Xiao-Sa ; Liu, Yan ; Liu, Yu ; [et al.]

Royal Society of Chemistry (RSC) ; 2022

In: CrystEngComm Vol. 24, No. 32 ( 2022), p. 5767-5782

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In: CrystEngComm, Royal Society of Chemistry (RSC), Vol. 24, No. 32 ( 2022), p. 5767-5782

Abstract: The designing of luminescent metal–organic frameworks (LMOFs) as sensors for the detection of molecules and ions constitutes an active area of research. Four different three-dimensional (3D) unusual LMOFs, namely, {[Zn(3-pda)(TA)]·H 2 O} n (1), {[Zn(4-pda)(TA)]·2H 2 O} n (2), [Cd(3-pda)(TA)] n (3), and {[Cd 2 (4-pda) 2 (TA) 2 ]·(4-fpia)·H 2 O} n (4) (3-pda = 1,4-bis(3-pyridylcarboxylamide)benzene, 4-pda = 1,4-bis(4-pyridylcarboxylamide)benzene, 4-fpia = N -(4-formylamino-phenyl)-isonicotinamide, and TA = terephthalic acid) were successfully synthesized by a hydrothermal method and characterized by single-crystal X-ray diffraction. Under solvothermal conditions, a structurally transformational 3D 3-fold interpenetrated porous MOF, [Cd 2 (4-pda) 2 (TA) 2 (DMF)] n (4a), was obtained, which could be further transformed to isostructural [Cu 2 (4-pda) 2 (TA) 2 (DMF)] n (4b) by single-crystal to single-crystal (SCSC) transformation. The effect of N-donor ligands, metal ions and solvents on the structure of MOFs is discussed in detail. A series of luminescence recognition tests proved that complexes 1–4 can be used as luminescent sensors for detecting certain metal cations, oxyanions, and toxic organic solvents in an aqueous environment. Furthermore, the luminescence quenching mechanism and structure–function relationship were studied systematically.

Type of Medium: Online Resource

ISSN: 1466-8033

URL: Article

DOI: 10.1039/D2CE00915C

Language: English

Publisher: Royal Society of Chemistry (RSC)

Publication Date: 2022

detail.hit.zdb_id: 2025075-7

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