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Neurological Sciences

, Volume 30, Issue 4, pp 275–280 | Cite as

Can demographic and admission laboratory variables be useful to identify long-stay patients with acute ischemic stroke? A hospital-based cohort study in Singapore

  • Raymond C. S. SeetEmail author
  • Erle C. H. Lim
  • Y. H. Chan
  • Bernard P. L. Chan
  • Amy M. L. Quek
  • Benjamin K. C. Ong
Original Article

Abstract

The demographic and laboratory predictors of long-stay patients with ischemic stroke were sought in this retrospective hospital-based study. In the univariate and multivariate analysis, advanced age, male gender, leukocytosis, elevated creatinine, low-serum albumin, elevated alkaline transaminases, and lactate dehydrogenase were identified as independent predictors of “long” stayers. At an optimal probability cut-offs, the receiver operating curve incorporating these variables was 0.70, sensitivity 68%, specificity 80%, positive-predictive value 39% and negative-predictive value 95%. Application of this information may assist physicians to triage patients at risk of severe stroke for early therapy and care.

Keywords

Demographic characteristics Laboratory features Length of stay Ischemic stroke Prediction model Singapore 

Notes

Acknowledgments

We thank staff from the Division of Neurology, National University Hospital, Singapore, for their clinical contribution and Hendry Wangsa for electronic retrieval of information used in this study. We declare that we do not have any financial interest that may arise from this publication, which was prepared without any external sources of funding.

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Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Raymond C. S. Seet
    • 1
    • 2
    Email author
  • Erle C. H. Lim
    • 1
    • 2
  • Y. H. Chan
    • 3
  • Bernard P. L. Chan
    • 2
  • Amy M. L. Quek
    • 2
  • Benjamin K. C. Ong
    • 1
    • 2
  1. 1.Department of Medicine, Yong Loo Lin School of MedicineNational University of SingaporeSingaporeSingapore
  2. 2.Division of NeurologyNational University HospitalSingaporeSingapore
  3. 3.Biostatistics Unit, Yong Loo Lin School of MedicineNational University SingaporeSingaporeSingapore

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