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Added Value of Frequency of Imaging Markers for Prediction of Outcome After Intracerebral Hemorrhage: A Secondary Analysis of Existing Data

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Abstract

Background

Frequency of imaging markers (FIM) has been identified as an independent predictor of hematoma expansion in patients with intracerebral hemorrhage (ICH), but its impact on clinical outcome of ICH is yet to be determined. The aim of the present study was to investigate this association.

Methods

This study was a secondary analysis of our prior research. The data for this study were derived from six retrospective cohorts of ICH from January 2018 to August 2022. All consecutive study participants were examined within 6 h of stroke onset on neuroimaging. FIM was defined as the ratio of the number of imaging markers on noncontrast head tomography (i.e., hypodensities, blend sign, and island sign) to onset-to-neuroimaging time. The primary poor outcome was defined as a modified Rankin Scale score of 3–6 at 3 months.

Results

A total of 1253 patients with ICH were included for final analysis. Among those with available follow-up results, 713 (56.90%) exhibited a poor neurologic outcome at 3 months. In a univariate analysis, FIM was associated with poor prognosis (odds ratio 4.36; 95% confidence interval 3.31–5.74; p < 0.001). After adjustment for age, Glasgow Coma Scale score, systolic blood pressure, hematoma volume, and intraventricular hemorrhage, FIM was still an independent predictor of worse prognosis (odds ratio 3.26; 95% confidence interval 2.37–4.48; p < 0.001). Based on receiver operating characteristic curve analysis, a cutoff value of 0.28 for FIM was associated with 0.69 sensitivity, 0.66 specificity, 0.73 positive predictive value, 0.62 negative predictive value, and 0.71 area under the curve for the diagnosis of poor outcome.

Conclusions

The metric of FIM is associated with 3-month poor outcome after ICH. The novel indicator that helps identify patients who are likely within the 6-h time window at risk for worse outcome would be a valuable addition to the clinical management of ICH.

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References

  1. Thrift AG, Thayabaranathan T, Howard G, et al. Global stroke statistics. Int J Stroke. 2017;12(1):13–32.

    Article  PubMed  Google Scholar 

  2. Morotti A, Boulouis G, Dowlatshahi D, et al. Intracerebral haemorrhage expansion: definitions, predictors, and prevention. Lancet Neurol. 2023;22(2):159–71.

    Article  PubMed  Google Scholar 

  3. Phan TG, Krishnadas N, Lai V, et al. Meta-analysis of accuracy of the spot sign for predicting hematoma growth and clinical outcomes. Stroke. 2019;50(8):2030–6.

    Article  PubMed  Google Scholar 

  4. Greenberg SM, Ziai WC, Cordonnier C, et al. 2022 Guideline for the management of patients with spontaneous intracerebral hemorrhage: a guideline from the American Heart Association/American Stroke Association. Stroke. 2022;53(7):e282–361.

    Article  CAS  PubMed  Google Scholar 

  5. Shoamanesh A, Patrice Lindsay M, Castellucci LA, et al. Canadian stroke best practice recommendations: management of spontaneous intracerebral hemorrhage, 7th edition update 2020. Int J Stroke. 2021;16(3):321–41.

    Article  PubMed  Google Scholar 

  6. Morotti A, Boulouis G, Dowlatshahi D, et al. Standards for detecting, interpreting, and reporting noncontrast computed tomographic markers of intracerebral hemorrhage expansion. Ann Neurol. 2019;86(4):480–92.

    Article  PubMed  Google Scholar 

  7. Song L, Cheng J, Zhang C, et al. The frequency of imaging markers adjusted for time since symptom onset in intracerebral hemorrhage: a novel predictor for hematoma expansion. Int J Stroke. 2024;19(2):226–34.

    Article  PubMed  Google Scholar 

  8. Magid-Bernstein J, Girard R, Polster S, et al. Cerebral Hemorrhage: pathophysiology, treatment, and future directions. Circ Res. 2022;130(8):1204–29.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Boulouis G, Morotti A, Brouwers HB, et al. Association between hypodensities detected by computed tomography and hematoma expansion in patients with intracerebral hemorrhage. JAMA Neurol. 2016;73(8):961–8.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Li Q, Zhang G, Huang YJ, et al. Blend sign on computed tomography: novel and reliable predictor for early hematoma growth in patients with intracerebral hemorrhage. Stroke. 2015;46(8):2119–23.

    Article  PubMed  Google Scholar 

  11. Li Q, Liu QJ, Yang WS, et al. Island sign: an imaging predictor for early hematoma expansion and poor outcome in patients with intracerebral hemorrhage. Stroke. 2017;48(11):3019–25.

    Article  PubMed  Google Scholar 

  12. Hanley DF, Lane K, McBee N, et al. Thrombolytic removal of intraventricular haemorrhage in treatment of severe stroke: results of the randomised, multicentre, multiregion, placebo-controlled CLEAR III trial. Lancet. 2017;389(10069):603–11.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Law ZK, Dineen R, England TJ, et al. Predictors and outcomes of neurological deterioration in intracerebral hemorrhage: results from the TICH-2 randomized controlled trial. Transl Stroke Res. 2021;12(2):275–83.

    Article  CAS  PubMed  Google Scholar 

  14. Okazaki S, Yamamoto H, Foster LD, et al. Late neurological deterioration after acute intracerebral hemorrhage: a post hoc analysis of the ATACH-2 trial. Cerebrovasc Dis. 2020;49(1):26–31.

    Article  PubMed  Google Scholar 

  15. You S, Zheng D, Delcourt C, et al. Determinants of early versus delayed neurological deterioration in intracerebral hemorrhage. Stroke. 2019;50(6):1409–14.

    Article  PubMed  Google Scholar 

  16. Ovesen C, Christensen AF, Havsteen I, et al. Prediction and prognostication of neurological deterioration in patients with acute ICH: a hospital-based cohort study. BMJ Open. 2015;5(7):e008563.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Sheth KN. Spontaneous intracerebral hemorrhage. N Engl J Med. 2022;387(17):1589–96.

    Article  CAS  PubMed  Google Scholar 

  18. Boulouis G, Morotti A, Brouwers HB, et al. Noncontrast computed tomography hypodensities predict poor outcome in intracerebral hemorrhage patients. Stroke. 2016;47(10):2511–6.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Li Q, Yang WS, Wang XC, et al. Blend sign predicts poor outcome in patients with intracerebral hemorrhage. PLoS ONE. 2017;12(8):e0183082.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Al-Shahi Salman R, Frantzias J, Lee RJ, et al. Absolute risk and predictors of the growth of acute spontaneous intracerebral haemorrhage: a systematic review and meta-analysis of individual patient data. Lancet Neurol. 2018;17(10):885–94.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Bowry R, Parker SA, Bratina P, et al. Hemorrhage enlargement is more frequent in the first 2 h: a prehospital mobile stroke unit study. Stroke. 2022;53(7):2352–60.

    Article  PubMed  Google Scholar 

  22. Zhang F, Li H, Qian J, et al. Island sign predicts long-term poor outcome and mortality in patients with intracerebral hemorrhage. World Neurosurg. 2018;120:e304–12.

    Article  PubMed  Google Scholar 

  23. Quintas-Neves M, Marques L, Silva L, Amorim JM, Ferreira C, Pinho J. Noncontrast computed tomography markers of outcome in intracerebral hemorrhage patients. Neurol Res. 2019;41(12):1083–9.

    Article  PubMed  Google Scholar 

  24. Shah VA, Thompson RE, Yenokyan G, et al. One-year outcome trajectories and factors associated with functional recovery among survivors of intracerebral and intraventricular hemorrhage with initial severe disability. JAMA Neurol. 2022;79(9):856–68.

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

Thanks to all the coworkers who made a contribution to this research and to all the patients who made this research possible.

Funding

This study was supported by the Hubei Provincial Natural Science Foundation Innovation and Development Joint Fund (Grant No. 2023AFD016).

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Authors and Affiliations

Authors

Contributions

LK and SF: manuscript writing and interpretation of data; HZ, WG, Y. Ye, RW, JZ, HX, DT, LZ: data collection; Y. Yu and XQ: study design, manuscript review; JC, LH, and CG: data analysis; LS: study design and supervision.

Corresponding author

Correspondence to Lei Song.

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The authors declare that they have no conflicts of interest.

Clinical trial registration

Clinical registration Retrospectively registered upon approval of the local Institutional Review Board.

Human and Animal Rights

All included human research has been approved by the appropriate institutional review boards and/or ethics committees as appropriate.

Ethical Approval/Informed Consent

Because of the absence of any individually identifying information in the data set, the local institutional review board granted an exemption to informed consent (IRB no. 2022-22, 2021-036, XYYYE20220081, PJ2022-09-30, YX2023-134, and GRYY-LL-KJ2022-K820).

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Kuang, L., Fei, S., Zhou, H. et al. Added Value of Frequency of Imaging Markers for Prediction of Outcome After Intracerebral Hemorrhage: A Secondary Analysis of Existing Data. Neurocrit Care (2024). https://doi.org/10.1007/s12028-024-01963-x

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  • DOI: https://doi.org/10.1007/s12028-024-01963-x

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