Long‐term intellectual and developmental outcomes after pediatric epilepsy surgery: A systematic review and meta‐analysis

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

In addition to the primary aim of seizure freedom, a key secondary aim of pediatric epilepsy surgery is to stabilize and, potentially, optimize cognitive development. Although the efficacy of surgical treatment for seizure control has been established, the long‐term intellectual and developmental trajectories are yet to be delineated. We conducted a systematic review and meta‐analysis of studies reporting pre‐ and postsurgical intelligence or developmental quotients (IQ/DQ) of children with focal lesional epilepsy aged ≤18 years at epilepsy surgery and assessed at >2 years after surgery. We determined the IQ/DQ change and conducted a random‐effects meta‐analysis and meta‐regression to assess its determinants. We included 15 studies reporting on 341 patients. The weighted mean age at surgery was 7.1 years (range = .3–13.8). The weighted mean postsurgical follow‐up duration was 5.6 years (range = 2.7–12.8). The overall estimate of the mean presurgical IQ/DQ was 60 (95% confidence interval [CI] = 47–73), the postsurgical IQ/DQ was 61 (95% CI = 48–73), and the change was +.94 IQ/DQ (95% CI = −1.70 to 3.58, p = .486). Children with presurgical IQ/DQ ≥ 70 showed a tendency for higher gains than those with presurgical IQ/DQ < 70 ( p = .059). Higher gains were determined by cessation of antiseizure medication (ASM; p = .041), not just seizure freedom. Our findings indicate, on average, stabilization of intellectual and developmental functioning at long‐term follow‐up after epilepsy surgery. Once seizure freedom has been achieved, ASM cessation enables the optimization of intellectual and developmental trajectories in affected children.

Related collections

Most cited references 62

Record: found
Abstract: not found
Article: not found

Bias in meta-analysis detected by a simple, graphical test

Jos I. M. Egger, G D Smith, M. Schneider … (1997)

0 comments Cited 6634 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

Interrater reliability: the kappa statistic

Mary L McHugh (2012)

The kappa statistic is frequently used to test interrater reliability. The importance of rater reliability lies in the fact that it represents the extent to which the data collected in the study are correct representations of the variables measured. Measurement of the extent to which data collectors (raters) assign the same score to the same variable is called interrater reliability. While there have been a variety of methods to measure interrater reliability, traditionally it was measured as percent agreement, calculated as the number of agreement scores divided by the total number of scores. In 1960, Jacob Cohen critiqued use of percent agreement due to its inability to account for chance agreement. He introduced the Cohen’s kappa, developed to account for the possibility that raters actually guess on at least some variables due to uncertainty. Like most correlation statistics, the kappa can range from −1 to +1. While the kappa is one of the most commonly used statistics to test interrater reliability, it has limitations. Judgments about what level of kappa should be acceptable for health research are questioned. Cohen’s suggested interpretation may be too lenient for health related studies because it implies that a score as low as 0.41 might be acceptable. Kappa and percent agreement are compared, and levels for both kappa and percent agreement that should be demanded in healthcare studies are suggested.

0 comments Cited 3037 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range

Xiang Wan, Wenqian Wang, Jiming Liu … (2014)

Background In systematic reviews and meta-analysis, researchers often pool the results of the sample mean and standard deviation from a set of similar clinical trials. A number of the trials, however, reported the study using the median, the minimum and maximum values, and/or the first and third quartiles. Hence, in order to combine results, one may have to estimate the sample mean and standard deviation for such trials. Methods In this paper, we propose to improve the existing literature in several directions. First, we show that the sample standard deviation estimation in Hozo et al.’s method (BMC Med Res Methodol 5:13, 2005) has some serious limitations and is always less satisfactory in practice. Inspired by this, we propose a new estimation method by incorporating the sample size. Second, we systematically study the sample mean and standard deviation estimation problem under several other interesting settings where the interquartile range is also available for the trials. Results We demonstrate the performance of the proposed methods through simulation studies for the three frequently encountered scenarios, respectively. For the first two scenarios, our method greatly improves existing methods and provides a nearly unbiased estimate of the true sample standard deviation for normal data and a slightly biased estimate for skewed data. For the third scenario, our method still performs very well for both normal data and skewed data. Furthermore, we compare the estimators of the sample mean and standard deviation under all three scenarios and present some suggestions on which scenario is preferred in real-world applications. Conclusions In this paper, we discuss different approximation methods in the estimation of the sample mean and standard deviation and propose some new estimation methods to improve the existing literature. We conclude our work with a summary table (an Excel spread sheet including all formulas) that serves as a comprehensive guidance for performing meta-analysis in different situations. Electronic supplementary material The online version of this article (doi:10.1186/1471-2288-14-135) contains supplementary material, which is available to authorized users.

0 comments Cited 2382 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Ilona Stefanos‐Yakoub: (View ORCID Profile)

Kevin Wingeier: (View ORCID Profile)

Ulrike Held: (View ORCID Profile)

Beatrice Latal: (View ORCID Profile)

Elaine Wirrell: (View ORCID Profile)

Mary Lou Smith: (View ORCID Profile)

Georgia Ramantani: (View ORCID Profile)

Journal

Title: Epilepsia

Abbreviated Title: Epilepsia

Publisher: Wiley

ISSN (Print): 0013-9580

ISSN (Electronic): 1528-1167

Publication date Created: February 2024

Publication date (Electronic): December 09 2023

Publication date (Print): February 2024

Volume: 65

Issue: 2

Pages: 251-265

Affiliations

[1 ] Department of Neuropediatrics University Children's Hospital Zurich Zurich Switzerland

[2 ] Department of Psychosomatics and Psychiatry University Children's Hospital Zurich Zurich Switzerland

[3 ] Department of Biostatistics at Epidemiology, Biostatistics, and Prevention Institute University of Zurich Zurich Switzerland

[4 ] Child Development Center University Children's Hospital Zurich Zurich Switzerland

[5 ] Children's Research Center University Children's Hospital Zurich Zurich Switzerland

[6 ] University of Zurich Zurich Switzerland

[7 ] Divisions of Child and Adolescent Neurology and Epilepsy, Department of Neurology Mayo Clinic Rochester Minnesota USA

[8 ] Department of Psychology University of Toronto Mississauga; Neurosciences and Mental Health Program, Hospital for Sick Children Toronto Ontario Canada