Literature DB >> 32502654

The effect of age and injury severity on clinical prediction rules for ambulation among individuals with spinal cord injury.

Einat Engel-Haber1, Gabi Zeilig2, Simi Haber3, Lynn Worobey4, Steven Kirshblum5.   

Abstract

BACKGROUND CONTEXT: While several models for predicting independent ambulation early after traumatic spinal cord injury (SCI) based upon age and specific motor and sensory level findings have been published and validated, their accuracy, especially in individual American Spinal Injury Association [ASIA] Impairment Scale (AIS) classifications, has been questioned. Further, although age is widely used in prediction rules, its role and possible modifications have not been adequately evaluated until now.
PURPOSE: To evaluate the predictive accuracy of existing clinical prediction rules for independent ambulation among individuals at spinal cord injury model systems (SCIMS) Centers as well as the effect of modifying the age parameter from a cutoff of 65 years to 50 years. STUDY
DESIGN: Retrospective analysis of a longitudinal database. PATIENT SAMPLE: Adult individuals with traumatic SCI. OUTCOME MEASURES: The FIM locomotor score was used to assess independent walking ability at the 1-year follow-up.
METHODS: In all, 639 patients were enrolled in the SCIMS database between 2011 and 2015, with complete neurological examination data within 15 days following the injury and a follow-up assessment with functional independence measure (FIM) at 1-year post injury. Two previously validated logistic regression models were evaluated for their ability to predict independent walking at 1-year post injury with participants in the SCIMS database. Area under the receiver operating curve (AUC) was calculated for the individual AIS categories and for different age groups. Prediction accuracy was also calculated for a new modified LR model (with cut-off age of 50).
RESULTS: Overall AUC for each of the previous prediction models was found to be consistent with previous reports (0.919 and 0.904). AUCs for grouped AIS levels (A+D, B+C) were consistent with prior reports, moreover, prediction for individual AIS grades continued to reveal lower values. AUCs by different age categories showed a decline in prognostication accuracy with an increase in age, with statistically significant improvement of AUC when age-cut off was reduced to 50.
CONCLUSIONS: We confirmed previous results that former prediction models achieve strong prognostic accuracy by combining AIS subgroups, yet prognostication of the separate AIS groups is less accurate. Further, prognostication of persons with AIS B+C, for whom a clinical prediction model has arguably greater clinical utility, is less accurate than those with AIS A+D. Our findings emphasize that age is an important factor in prognosticating ambulation following SCI. Prediction accuracy declines for older individuals compared with younger ones. To improve prediction of independent ambulation, the age of 50 years may be a better cutoff instead of age of 65.
Copyright © 2020 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Aging; Functional outcomes; Injury severity; Logistic regression; Prediction; Prognosis; Traumatic spinal cord injury; Walking recovery

Mesh:

Year:  2020        PMID: 32502654     DOI: 10.1016/j.spinee.2020.05.551

Source DB:  PubMed          Journal:  Spine J        ISSN: 1529-9430            Impact factor:   4.166


  5 in total

1.  Toward Improving the Prediction of Functional Ambulation After Spinal Cord Injury Through the Inclusion of Limb Accelerations During Sleep and Personal Factors.

Authors:  Stephanie K Rigot; Michael L Boninger; Dan Ding; Gina McKernan; Edelle C Field-Fote; Jeanne Hoffman; Rachel Hibbs; Lynn A Worobey
Journal:  Arch Phys Med Rehabil       Date:  2021-04-08       Impact factor: 3.966

2.  MRI metrics at the epicenter of spinal cord injury are correlated with the stepping process in rhesus monkeys.

Authors:  Jia-Sheng Rao; Can Zhao; Shu-Sheng Bao; Ting Feng; Meng Xu
Journal:  Exp Anim       Date:  2021-11-16

3.  A functional outcome prediction model of acute traumatic spinal cord injury based on extreme gradient boost.

Authors:  Zhan Sizheng; Huang Boxuan; Xue Feng; Zhang Dianying
Journal:  J Orthop Surg Res       Date:  2022-10-12       Impact factor: 2.677

4.  Differences in clinical characteristics of cervical spine injuries in older adults by external causes: a multicenter study of 1512 cases.

Authors:  Noriaki Yokogawa; Satoshi Kato; Takeshi Sasagawa; Hiroyuki Hayashi; Hiroyuki Tsuchiya; Kei Ando; Hiroaki Nakashima; Naoki Segi; Toru Funayama; Fumihiko Eto; Akihiro Yamaji; Satoshi Nori; Junichi Yamane; Takeo Furuya; Atsushi Yunde; Hideaki Nakajima; Tomohiro Yamada; Tomohiko Hasegawa; Yoshinori Terashima; Ryosuke Hirota; Hidenori Suzuki; Yasuaki Imajo; Shota Ikegami; Masashi Uehara; Hitoshi Tonomura; Munehiro Sakata; Ko Hashimoto; Yoshito Onoda; Kenichi Kawaguchi; Yohei Haruta; Nobuyuki Suzuki; Kenji Kato; Hiroshi Uei; Hirokatsu Sawada; Kazuo Nakanishi; Kosuke Misaki; Hidetomi Terai; Koji Tamai; Eiki Shirasawa; Gen Inoue; Kenichiro Kakutani; Yuji Kakiuchi; Katsuhito Kiyasu; Hiroyuki Tominaga; Hiroto Tokumoto; Yoichi Iizuka; Eiji Takasawa; Koji Akeda; Norihiko Takegami; Haruki Funao; Yasushi Oshima; Takashi Kaito; Daisuke Sakai; Toshitaka Yoshii; Tetsuro Ohba; Bungo Otsuki; Shoji Seki; Masashi Miyazaki; Masayuki Ishihara; Seiji Okada; Shiro Imagama; Kota Watanabe
Journal:  Sci Rep       Date:  2022-09-23       Impact factor: 4.996

Review 5.  Improving Diagnostic Workup Following Traumatic Spinal Cord Injury: Advances in Biomarkers.

Authors:  Simon Schading; Tim M Emmenegger; Patrick Freund
Journal:  Curr Neurol Neurosci Rep       Date:  2021-07-16       Impact factor: 5.081

  5 in total

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