Dataset Information

Location of intracerebral haemorrhage predicts haematoma expansion.

ABSTRACT:

Introduction

The role of intracerebral haemorrhage location in haematoma expansion remains unclear. Our objective was to assess the effect of lobar versus non-lobar haemorrhage on haematoma expansion and clinical outcome.

Patients and methods

We analysed data from the prospective PREDICT study where patients with intracerebral haemorrhage presenting to hospital under 6 h of symptom onset received baseline computed tomography (CT), CT angiogram, 24 h follow-up CT, and 90-day mRS. Intracerebral haemorrhage location was categorised as lobar versus non-lobar, and primary outcomes were significant haematoma expansion (>6 ml) and poor clinical outcome (mRS > 3). Multivariable regression was used to adjust for relevant covariates. The primary analysis population was divided by spot sign status and the effect of haemorrhage location was compared to haematoma expansion in exploratory post hoc analysis.

Results

Among 302 patients meeting the inclusion criteria, lobar haemorrhage was associated with increased haematoma expansion >6 ml (p = 0.003), poor clinical outcome (p = 0.011) and mortality (p = 0.017). When adjusted for covariates, lobar haemorrhage independently predicted significant haematoma expansion (aOR 2.2 (95% CI: 1.1-4.3), p = 0.021) and poor clinical outcome (aOR 2.6 (95% CI: 1.2-5.6), p = 0.019). Post hoc analysis showed that patients who were spot sign negative had a higher degree of haematoma expansion with baseline lobar haemorrhage (lobar 26% versus deep 11%; p = 0.01). No significant associations were observed in spot-positive patients (lobar 52% versus deep 47%; p = 0.69).

Discussion and conclusion

Haematoma expansion is more likely to occur with lobar intracerebral haemorrhage and haemorrhage location is associated with poor clinical outcome. As expansion is a promising therapeutic target, hemorrhage location may be helpful for prognostication and as a selection tool in future ICH clinical trials.

SUBMITTER: Yogendrakumar V

PROVIDER: S-EPMC6454825 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Publications

Location of intracerebral haemorrhage predicts haematoma expansion.

Yogendrakumar Vignan V Demchuk Andrew M AM Aviv Richard I RI Rodriguez-Luna David D Molina Carlos A CA Blas Yolanda S YS Dzialowski Imanuel I Kobayashi Adam A Boulanger Jean-Martin JM Lum Cheemun C Gubitz Gord G Padma Vasantha V Roy Jayanta J Kase Carlos S CS Bhatia Rohit R Hill Michael D MD Dowlatshahi Dar D

European stroke journal 20170615 3

<h4>Introduction</h4>The role of intracerebral haemorrhage location in haematoma expansion remains unclear. Our objective was to assess the effect of lobar versus non-lobar haemorrhage on haematoma expansion and clinical outcome.<h4>Patients and methods</h4>We analysed data from the prospective PREDICT study where patients with intracerebral haemorrhage presenting to hospital under 6 h of symptom onset received baseline computed tomography (CT), CT angiogram, 24 h follow-up CT, and 90-day mRS. I ...[more]

PMID: 31008319

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Project description:ObjectiveTo obtain precise estimates of age, haematoma volume, secondary haematoma expansion (HE) and mortality for patients with intracerebral haemorrhage (ICH) taking oral anticoagulants [Vitamin K antagonists (VKA-ICH) or non-Vitamin K antagonist oral anticoagulants (NOAC-ICH)] and those not taking oral anticoagulants (non-OAC ICH) at ICH symptom onset.MethodsWe conducted a systematic review and meta-analysis of studies comparing VKA-ICH or NOAC-ICH or both with non-OAC ICH. Primary outcomes were haematoma volume (in ml), HE, and mortality (in-hospital and 3-month). We calculated odds ratios (ORs) using the Mantel-Haenszel random-effects method and corresponding 95% confidence intervals (95%CI) and determined the mean ICH volume difference.ResultsWe identified 19 studies including data from 16,546 patients with VKA-ICH and 128,561 patients with non-OAC ICH. Only 2 studies reported data on 4943 patients with NOAC-ICH. Patients with VKA-ICH were significantly older than patients with non-OAC ICH (mean age difference: 5.55 years, 95%CI 4.03-7.07, p < 0.0001, I2 = 92%, p < 0.001). Haematoma volume was significantly larger in VKA-ICH with a mean difference of 9.66 ml (95%CI 6.24-13.07 ml, p < 0.00001; I2 = 42%, p = 0.05). HE occurred significantly more often in VKA-ICH (OR 2.96, 95%CI 1.74-4.97, p < 0.00001; I2 = 65%). VKA-ICH was associated with significantly higher in-hospital mortality (VKA-ICH: 32.8% vs. non-OAC ICH: 22.4%; OR 1.83, 95%CI 1.61-2.07, p < 0.00001, I2 = 20%, p = 0.27) and 3-month mortality (VKA-ICH: 47.1% vs. non-OAC ICH: 25.5%; OR 2.24, 95%CI 1.52-3.31, p < 0.00001, I2 = 71%, p = 0.001). We did not find sufficient data for a meta-analysis comparing NOAC-ICH and non-OAC-ICH.ConclusionThis meta-analysis confirms, refines and expands findings from prior studies. We provide precise estimates of key prognostic factors and outcomes for VKA-ICH, which has larger haematoma volume, increased rate of HE and higher mortality compared to non-OAC ICH. There are insufficient data on NOACs.

Project description:ObjectivesTo test radiomics-based features extracted from noncontrast CT of patients with spontaneous intracerebral haemorrhage for prediction of haematoma expansion and poor functional outcome and compare them with radiological signs and clinical factors.Materials and methodsSeven hundred fifty-four radiomics-based features were extracted from 1732 scans derived from the TICH-2 multicentre clinical trial. Features were harmonised and a correlation-based feature selection was applied. Different elastic-net parameterisations were tested to assess the predictive performance of the selected radiomics-based features using grid optimisation. For comparison, the same procedure was run using radiological signs and clinical factors separately. Models trained with radiomics-based features combined with radiological signs or clinical factors were tested. Predictive performance was evaluated using the area under the receiver operating characteristic curve (AUC) score.ResultsThe optimal radiomics-based model showed an AUC of 0.693 for haematoma expansion and an AUC of 0.783 for poor functional outcome. Models with radiological signs alone yielded substantial reductions in sensitivity. Combining radiomics-based features and radiological signs did not provide any improvement over radiomics-based features alone. Models with clinical factors had similar performance compared to using radiomics-based features, albeit with low sensitivity for haematoma expansion. Performance of radiomics-based features was boosted by incorporating clinical factors, with time from onset to scan and age being the most important contributors for haematoma expansion and poor functional outcome prediction, respectively.ConclusionRadiomics-based features perform better than radiological signs and similarly to clinical factors on the prediction of haematoma expansion and poor functional outcome. Moreover, combining radiomics-based features with clinical factors improves their performance.Key points• Linear models based on CT radiomics-based features perform better than radiological signs on the prediction of haematoma expansion and poor functional outcome in the context of intracerebral haemorrhage. • Linear models based on CT radiomics-based features perform similarly to clinical factors known to be good predictors. However, combining these clinical factors with radiomics-based features increases their predictive performance.

Dataset Information

Location of intracerebral haemorrhage predicts haematoma expansion.

Introduction

Patients and methods

Results

Discussion and conclusion

Publications

Location of intracerebral haemorrhage predicts haematoma expansion.

Similar Datasets

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