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Neurocritical Care

, Volume 30, Issue 2, pp 394–404 | Cite as

External Validation of Hematoma Expansion Scores in Spontaneous Intracerebral Hemorrhage in an Asian Patient Cohort

  • Jia Xu Lim
  • Julian Xinguang Han
  • Angela An Qi See
  • Voon Hao Lew
  • Wan Ting Chock
  • Vin Fei Ban
  • Sohil Pothiawala
  • Winston Eng Hoe Lim
  • Louis Elliot McAdory
  • Michael Lucas James
  • Nicolas Kon Kam KingEmail author
Original Article

Abstract

Background

Hematoma expansion (HE) occurs in approximately one-third of patients with intracerebral hemorrhage (ICH) and is known to be a strong predictor of neurological deterioration as well as poor functional outcome. This study aims to externally validate three risk prediction models of HE (PREDICT, 9-point, and BRAIN scores) in an Asian population.

Methods

A prospective cohort of 123 spontaneous ICH patients admitted to a tertiary hospital (certified stroke center) in Singapore was recruited. Logistic recalibrations were performed to obtain updated calibration slopes and intercepts for all models. The discrimination (c-statistic), calibration (Hosmer–Lemeshow test, le Cessie–van Houwelingen–Copas–Hosmer test, Akaike information criterion), overall performance (Brier score, R2), and clinical usefulness (decision curve analysis) of the risk prediction models were examined.

Results

Overall, the recalibrated PREDICT performed best among the three models in our study cohort based on the novel matrix comprising of Akaike information criterion and c-statistic. The PREDICT model had the highest R2 (0.26) and lowest Brier score (0.14). Decision curve analyses showed that recalibrated PREDICT was more clinically useful than 9-point and BRAIN models over the greatest range of threshold probabilities. The two scores (PREDICT and 9-point) which incorporated computed tomography (CT) angiography spot sign outperformed the one without (BRAIN).

Conclusions

To our knowledge, this is the first study to validate HE scores, namely PREDICT, 9-Point and BRAIN, in a multi-ethnic Asian ICH patient population. The PREDICT score was the best performing model in our study cohort, based on the performance metrics employed in this study. Our findings also showed support for CT angiography spot sign as a predictor of outcome after ICH. Although the models assessed are sufficient for risk stratification, the discrimination and calibration are at best moderate and could be improved.

Keywords

Intracerebral hemorrhage Hematoma expansion External validation Risk prediction 

Notes

Authors Contribution

JXL contributed to protocol development, data collection and management, and manuscript writing and editing. JH contributed to protocol development, data analysis, and manuscript writing and editing. AAQS contributed to protocol development, data analysis, and manuscript writing and editing. VHL, WTC, and VFB contributed to data collection and management and manuscript approval. SP, LEM, and WEHL contributed to protocol development, data collection, and manuscript approval. MLJ contributed to protocol development and manuscript writing and editing. NKKK contributed to protocol development, data analysis, and manuscript writing and editing. MLJ is the Basic Science Editor for Neurocritical Care.

Sources of support

None.

Compliance with Ethical Standards

Conflict of interest

Michael James is the Basic Science Editor for Neurocritical Care. The other authors declare that they have no conflict of interest.

Human and Animal Rights

This is a prospective study, needs statement of ethics approval and consent.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature and Neurocritical Care Society 2018

Authors and Affiliations

  • Jia Xu Lim
    • 1
    • 2
  • Julian Xinguang Han
    • 1
    • 2
  • Angela An Qi See
    • 1
    • 2
  • Voon Hao Lew
    • 1
  • Wan Ting Chock
    • 2
  • Vin Fei Ban
    • 2
  • Sohil Pothiawala
    • 3
  • Winston Eng Hoe Lim
    • 4
  • Louis Elliot McAdory
    • 4
  • Michael Lucas James
    • 5
    • 6
  • Nicolas Kon Kam King
    • 1
    • 2
    • 7
    Email author
  1. 1.Department of NeurosurgeryNational Neuroscience InstituteSingaporeSingapore
  2. 2.Department of NeurosurgerySingapore General HospitalSingaporeSingapore
  3. 3.Department of Emergency MedicineSingapore General HospitalSingaporeSingapore
  4. 4.Department of Diagnostic RadiologySingapore General HospitalSingaporeSingapore
  5. 5.Departments of AnesthesiologyBrain Injury Translational Research Center, Duke UniversityDurhamUSA
  6. 6.Departments of NeurologyBrain Injury Translational Research Center, Duke UniversityDurhamUSA
  7. 7.Duke-NUS Medical SchoolSingaporeSingapore

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