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. 2021 Dec 7;22(1):41-42.
doi: 10.1177/15357597211058270. eCollection 2022 Jan-Feb.

What's in Your Nomogram? Personalized Prognostication of Verbal Memory Decline after Temporal Lobe Resection in Adults With Epilepsy

Affiliations

What's in Your Nomogram? Personalized Prognostication of Verbal Memory Decline after Temporal Lobe Resection in Adults With Epilepsy

Tracey A Milligan. Epilepsy Curr. .

Erratum in

  • Erratum 22(1), 22(2), 22(3) and 22(4).
    [No authors listed] [No authors listed] Epilepsy Curr. 2022 Dec 1;23(1):61-62. doi: 10.1177/15357597221144381. eCollection 2023 Jan-Feb. Epilepsy Curr. 2022. PMID: 36923327 Free PMC article.

Abstract

Objective: This study aims to develop and externally validate models to predict the probability of postoperative verbal memory decline in adults following temporal lobe resection (TLR) for epilepsy using easily accessible preoperative clinical predictors.

Methods: Multivariable models were developed to predict delayed verbal memory outcome on 3 commonly used measures: Rey Auditory Verbal Learning Test (RAVLT), and Logical Memory (LM), and Verbal Paired Associates (VPA) subtests from Wechsler Memory Scale-Third Edition. Using Harrell's step-down procedure for variable selection, models were developed in 359 adults who underwent TLR at Cleveland Clinic and validated in 290 adults at 1 of 5 epilepsy surgery centers in the United States or Canada.

Results: Twenty-nine percent of the development cohort and 26% of the validation cohort demonstrated significant decline on at least 1 verbal memory measure. Initial models had good-to-excellent predictive accuracy (calibration (c) statistic range = .77-.80) in identifying patients with memory decline; however, models slightly underestimated decline in the validation cohort. Model coefficients were updated using data from both cohorts to improve stability. The model for RAVLT included surgery side, baseline memory score, and hippocampal resection. The models for LM and VPA included surgery side, baseline score, and education. Updated model performance was good to excellent (RAVLT c = .81, LM c = .76, VPA c = .78). Model calibration was very good, indicating no systematic over- or under-estimation of risk.

Conclusions: Nomograms are provided in 2 easy-to-use formats to assist clinicians in estimating the probability of verbal memory decline in adults considering TLR for treatment of epilepsy.

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Conflict of interest statement

Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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