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Prehospital factors determining regional variation in thrombolytic therapy in acute ischemic stroke

Authors

  • Maarten M. H. Lahr,

    Corresponding author
    1. Department of Neurology, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands
    • Correspondence: Maarten M.H. Lahr, Hanzeplein 1, P.O. Box 30001, 9700 RB Groningen, The Netherlands.

      E-mail: m.m.h.lahr@umcg.nl

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  • Patrick C. A. J. Vroomen,

    1. Department of Neurology, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands
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  • Gert-Jan Luijckx,

    1. Department of Neurology, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands
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  • Durk-Jouke van der Zee,

    1. Department of Operations, Faculty of Economics and Business, University of Groningen, Groningen, The Netherlands
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  • Ronald de Vos,

    1. Regional Ambulance Services Groningen, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands
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  • Erik Buskens

    1. Health Technology Assessment, Department of Epidemiology, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands
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  • Conflict of interest: None declared.

Abstract

Background

Treatment rates with intravenous tissue plasminogen activator vary by region, which can be partially explained by organizational models of stroke care. A recent study demonstrated that prehospital factors determine a higher thrombolysis rate in a centralized vs. decentralized model in the north of the Netherlands.

Aim

To investigate prehospital factors that may explain variation in thrombolytic therapy between a centralized and a decentralized model.

Methods

A consecutive case observational study was conducted in the north of the Netherlands comparing patients arriving within 4·5 h in a centralized vs. decentralized stroke care model. Factors investigated were transportation mode, prehospital diagnostic accuracy, and preferential referral of thrombolysis candidates. Potential confounders were adjusted using logistic regression analysis.

Results

A total of 172 and 299 arriving within 4·5 h were enrolled in centralized and decentralized settings, respectively. The rate of transportation by emergency medical services was greater in the centralized model (adjusted odds ratio 3·11; 95% confidence interval, 1·59–6·06). Also, more misdiagnoses of stroke occurred in the central model (P = 0·05). In postal code areas with and without potential preferential referral of thrombolysis candidates due to overlapping catchment areas, the odds of hospital arrival within 4·5 h in the central vs. decentral model were 2·15 (95% confidence interval, 1·39–3·32) and 1·44 (95% confidence interval, 1·04–2·00), respectively.

Conclusions

These results suggest that the larger proportion of patients arriving within 4·5 h in the centralized model might be related to a lower threshold to use emergency services to transport stroke patients and partly to preferential referral of thrombolysis candidates.

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