Literature DB >> 29900414

Development and validation of the Dutch Stroke Score for predicting disability and functional outcome after ischemic stroke: A tool to support efficient discharge planning.

Inger R de Ridder1, Simone A Dijkland2, Maaike Scheele1, Heleen M den Hertog3, Maaike Dirks1,4, Willeke F Westendorp5, Paul J Nederkoorn5, Diederik van de Beek5, Gerard M Ribbers6, Ewout W Steyerberg2,7, Hester F Lingsma2, Diederik Wj Dippel1.   

Abstract

INTRODUCTION: We aimed to develop and validate a prognostic score for disability at discharge and functional outcome at three months in patients with acute ischemic stroke based on clinical information available on admission. PATIENTS AND METHODS: The Dutch Stroke Score (DSS) was developed in 1227 patients with ischemic stroke included in the Paracetamol (Acetaminophen) In Stroke study. Predictors for Barthel Index (BI) at discharge ('DSS-discharge') and modified Rankin Scale (mRS) at three months ('DSS-3 months') were identified in multivariable ordinal regression. The models were internally validated with bootstrapping techniques. The DSS-3 months was externally validated in the PRomoting ACute Thrombolysis in Ischemic StrokE study (1589 patients) and the Preventive Antibiotics in Stroke Study (2107 patients). Model performance was assessed in terms of discrimination, expressed by the area under the receiver operating characteristic curve (AUC), and calibration.
RESULTS: At model development, the strongest predictors of Barthel Index at discharge were age per decade over 60 (odds ratio = 1.55, 95% confidence interval (CI) 1.41-1.68), National Institutes of Health Stroke Scale (odds ratio = 1.24 per point, 95% CI 1.22-1.26) and diabetes (odds ratio = 1.62, 95% CI 1.32-1.91). The internally validated AUC was 0.76 (95% CI 0.75-0.79). The DSS-3 months, additionally consisting of previous stroke and atrial fibrillation, performed similarly at internal (AUC 0.75, 95% CI 0.74-0.77) and external validation (AUC 0.74 in PRomoting ACute Thrombolysis in Ischemic StrokE (95% CI 0.72-0.76) and 0.69 in Preventive Antibiotics in Stroke Study (95% CI 0.69-0.72)). Observed outcome was slightly better than predicted.Discussion: The DSS had satisfactory performance in predicting BI at discharge and mRS at three months in ischemic stroke patients.
CONCLUSION: If further validated, the DSS may contribute to efficient stroke unit discharge planning alongside patients' contextual factors and therapeutic needs.

Entities:  

Keywords:  Stroke; clinical prediction model; discharge planning; hospital discharge; prognosis; rehabilitation

Year:  2018        PMID: 29900414      PMCID: PMC5992735          DOI: 10.1177/2396987318754591

Source DB:  PubMed          Journal:  Eur Stroke J        ISSN: 2396-9873


  30 in total

Review 1.  Systematic review of prognostic models in patients with acute stroke.

Authors:  C Counsell; M Dennis
Journal:  Cerebrovasc Dis       Date:  2001       Impact factor: 2.762

2.  Risk score for in-hospital ischemic stroke mortality derived and validated within the Get With the Guidelines-Stroke Program.

Authors:  Eric E Smith; Nandavar Shobha; David Dai; Daiwai M Olson; Mathew J Reeves; Jeffrey L Saver; Adrian F Hernandez; Eric D Peterson; Gregg C Fonarow; Lee H Schwamm
Journal:  Circulation       Date:  2010-09-27       Impact factor: 29.690

3.  Interobserver agreement for the assessment of handicap in stroke patients.

Authors:  J C van Swieten; P J Koudstaal; M C Visser; H J Schouten; J van Gijn
Journal:  Stroke       Date:  1988-05       Impact factor: 7.914

4.  The Stroke Unit Discharge Guideline, a prognostic framework for the discharge outcome from the hospital stroke unit. A prospective cohort study.

Authors:  R Meijer; J van Limbeek; G Peusens; M Rulkens; K Dankoor; M Vermeulen; R J de Haan
Journal:  Clin Rehabil       Date:  2005-10       Impact factor: 3.477

5.  Endovascular thrombectomy after large-vessel ischaemic stroke: a meta-analysis of individual patient data from five randomised trials.

Authors:  Mayank Goyal; Bijoy K Menon; Wim H van Zwam; Diederik W J Dippel; Peter J Mitchell; Andrew M Demchuk; Antoni Dávalos; Charles B L M Majoie; Aad van der Lugt; Maria A de Miquel; Geoffrey A Donnan; Yvo B W E M Roos; Alain Bonafe; Reza Jahan; Hans-Christoph Diener; Lucie A van den Berg; Elad I Levy; Olvert A Berkhemer; Vitor M Pereira; Jeremy Rempel; Mònica Millán; Stephen M Davis; Daniel Roy; John Thornton; Luis San Román; Marc Ribó; Debbie Beumer; Bruce Stouch; Scott Brown; Bruce C V Campbell; Robert J van Oostenbrugge; Jeffrey L Saver; Michael D Hill; Tudor G Jovin
Journal:  Lancet       Date:  2016-02-18       Impact factor: 79.321

Review 6.  Predicting disability in stroke--a critical review of the literature.

Authors:  G Kwakkel; R C Wagenaar; B J Kollen; G J Lankhorst
Journal:  Age Ageing       Date:  1996-11       Impact factor: 10.668

7.  New considerations in the design of clinical trials for traumatic brain injury.

Authors:  Bob Roozenbeek; Hester F Lingsma; Andrew Ir Maas
Journal:  Clin Investig (Lond)       Date:  2012-02

8.  Predicting outcome after acute and subacute stroke: development and validation of new prognostic models.

Authors:  Carl Counsell; Martin Dennis; Michael McDowall; Charles Warlow
Journal:  Stroke       Date:  2002-04       Impact factor: 7.914

9.  The Preventive Antibiotics in Stroke Study (PASS): a pragmatic randomised open-label masked endpoint clinical trial.

Authors:  Willeke F Westendorp; Jan-Dirk Vermeij; Elles Zock; Imke J Hooijenga; Nyika D Kruyt; Hans J L W Bosboom; Vincent I H Kwa; Martijn Weisfelt; Michel J M Remmers; Robert ten Houten; A H C M Tobien Schreuder; Sarah E Vermeer; Ewout J van Dijk; Diederik W J Dippel; Marcel G W Dijkgraaf; Lodewijk Spanjaard; Marinus Vermeulen; Tom van der Poll; Jan M Prins; Frederique H Vermeij; Yvo B W E M Roos; Ruud P Kleyweg; Henk Kerkhoff; Matthijs C Brouwer; Aeilko H Zwinderman; Diederik van de Beek; Paul J Nederkoorn
Journal:  Lancet       Date:  2015-01-20       Impact factor: 79.321

10.  The Paracetamol (Acetaminophen) In Stroke (PAIS) trial: a multicentre, randomised, placebo-controlled, phase III trial.

Authors:  Heleen M den Hertog; H Bart van der Worp; H Maarten A van Gemert; Ale Algra; L Jaap Kappelle; Jan van Gijn; Peter J Koudstaal; Diederik W J Dippel
Journal:  Lancet Neurol       Date:  2009-03-16       Impact factor: 44.182

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1.  Outcome in Stroke Patients Is Associated with Age and Fractional Anisotropy in the Cerebral Peduncles: A Multivariate Regression Study.

Authors:  Tetsuo Koyama; Yuki Uchiyama; Kazuhisa Domen
Journal:  Prog Rehabil Med       Date:  2020-04-03

Review 2.  Machine learning methods for functional recovery prediction and prognosis in post-stroke rehabilitation: a systematic review.

Authors:  Silvia Campagnini; Chiara Arienti; Michele Patrini; Piergiuseppe Liuzzi; Andrea Mannini; Maria Chiara Carrozza
Journal:  J Neuroeng Rehabil       Date:  2022-06-03       Impact factor: 5.208

3.  Cross-validation of predictive models for functional recovery after post-stroke rehabilitation.

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4.  Repeated Measures of Modified Rankin Scale Scores to Assess Functional Recovery From Stroke: AFFINITY Study Findings.

Authors:  Alexander Chye; Maree L Hackett; Graeme J Hankey; Erik Lundström; Osvaldo P Almeida; John Gommans; Martin Dennis; Stephen Jan; Gillian E Mead; Andrew H Ford; Christopher Etherton Beer; Leon Flicker; Candice Delcourt; Laurent Billot; Craig S Anderson; Katharina Stibrant Sunnerhagen; Qilong Yi; Severine Bompoint; Thang Huy Nguyen; Thomas Lung
Journal:  J Am Heart Assoc       Date:  2022-08-05       Impact factor: 6.106

5.  Protocol for the development of a clinical practice guideline for discharge planning of stroke patients.

Authors:  Cong Wang; Ting Yu; Xufei Luo; Chunfen Zhou; Chao You; Lijuan Duan; Shanshan Liu; Yaolong Chen; Yan Jiang; Hong Zhu
Journal:  Ann Transl Med       Date:  2022-09
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