Morbidity After Symptomatic Hemorrhage of Cerebral Cavernous Malformation

 Well congratulations, you described a problem BUT DID NOTHING TO SOLVE IT. You all need to be fired.

Morbidity After Symptomatic Hemorrhage of Cerebral Cavernous Malformation

A Nomogram Approach to Risk Assessment

Li Ma

,

Shuo Zhang

,

Zongze Li

,

Chun-Xue Wu

,

Zhaozhao Wang

,

Lei Zhan

,

Qiang Hao

,

Hao Wang

,

Xun Ye

,

Xiaolin Chen

,

Ya-Ou Liu

,

Shuo Wang

,

Yuan-Li Zhao

Originally published21 Sep 2020https://doi.org/10.1161/STROKEAHA.120.029942Stroke. ;0

Abstract

Background and Purpose:

Symptomatic hemorrhage contributes to an increased risk of repeated bleeding and morbidity in cerebral cavernous malformation (CCM). A better understanding of morbidity after CCM hemorrhage would be helpful to identify patients of higher risk for unfavorable outcome and tailor individualized management.

Methods:

We identified 282 consecutive patients who referred to our institute from 2014 to 2018 for CCM with symptomatic hemorrhage and had an untreated follow-up period over 6 months after the first hemorrhage. The morbidity after hemorrhage was described in CCM of different features. Nomogram to predict morbidity was formulated based on the multivariable model of risk factors. The predictive accuracy and discriminative ability of nomogram were determined with concordance index (C-index) and calibration curve, and further validated in an independent CCM cohort of a prospective multicenter study from 2019 to 2020.

Results:

The overall morbidity of CCM was 26.2% after a mean follow-up of 1.9 years (range 0.5–3.5 years) since the first hemorrhage. The morbidity during untreated follow-up was associated with hemorrhage ictus (adjusted odds ratio per ictus increase, 4.17 [95%CI, 1.86–9.33]), modified Rankin Scale score at initial hemorrhage (adjusted odds ratio per point increase, 2.57 [95%CI, 1.82–3.63]), brainstem location (adjusted odds ratio, 2.93 [95%CI, 1.28–6.68]), and associated developmental venous anomaly (adjusted odds ratio, 2.21 [95%CI, 1.01–4.83]). Subgroup analysis revealed similar findings in brainstem and non-brainstem CCM. Nomogram was contracted based on these features. The calibration curve showed good agreement between nomogram prediction and actual observation. The C-index of nomogram predicting morbidity was 0.83 (95% CI, 0.77–0.88). In validation cohort, the nomogram maintained the discriminative ability (C-index, 0.87 [95% CI, 0.78–0.96]).

Conclusions:

Multiple symptomatic hemorrhages, initial neurological function after hemorrhage, brainstem location, and associated developmental venous anomaly were associated with morbidity of CCM hemorrhage. The nomogram represented a practical approach to provide individualized risk assessment for CCM patients.(Useless, don't you think patients might want solutions to prevent that risk?)

REGISTRATION:

URL: https://www.clinicaltrials.gov. Unique identifier: NCT04076449.

 

Quantitative Lesion Water Uptake in Acute Stroke Computed Tomography Is a Predictor of Malignant Infarction

I had never heard of this problem before. I would expect a public database of all sequelae from stroke and the protocols necessary to treat them. This hiding of stroke interventions needs to stop. We should know the exact percentage of cases that have this and the morbidity rate from them. Only by quantifying the problem will anyone ever try to solve it.

Quantitative Lesion Water Uptake in Acute Stroke Computed Tomography Is a Predictor of Malignant Infarction

Gabriel Broocks, Fabian Flottmann, Alexandra Scheibel, Annette Aigner, Tobias D. Faizy, Uta Hanning, Hannes Leischner, Sabine I. Broocks, Jens Fiehler, Susanne Gellissen, Andre Kemmling

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https://doi.org/10.1161/STROKEAHA.118.020507

Stroke. 2018;STROKEAHA.118.020507

Originally published July 5, 2018

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Abstract

Background and Purpose—Early selection of patients with acute middle cerebral artery infarction at risk for malignant edema is critical to initiate timely decompressive surgery. Net water uptake (NWU) per brain volume is a quantitative imaging biomarker of space-occupying ischemic edema which can be measured in computed tomography. We hypothesize that NWU in early infarct lesions can predict development of malignant edema. The aim was to compare NWU in acute brain infarct against other common predictors of malignant edema.

Methods—After consecutive screening of single-center registry data, 153 patients with acute proximal middle cerebral artery occlusion fulfilled the inclusion criteria. A total of 29 (18.2%) patients developed malignant edema defined as end point in follow-up imaging leading to decompressive surgery and death as a direct implication of mass effect. Early infarct lesion volume and NWU were quantified in multimodal admission computed tomography; time from symptom onset to admission imaging was recorded.

Results—Mean time from onset to admission imaging was equivalent between patients with and without malignant infarcts (mean±SD: 3.3±1.4 hours and 3.3±1.7 hours, respectively). Edematous tissue expansion by NWU within infarct lesions occurred across all patients in this cohort (NWU: 9.1%±6.8%; median, 7.9%; interquartile range, 8.8%; range, 0.1%–35.6%); 7.0% (±5.2) in nonmalignant and 18.0% (±5.7) in malignant infarcts. Based on univariate receiver operating characteristic curve analysis, NWU >12.7% or an edema rate >3.7% NWU/h identified malignant infarcts with high discriminative power (area under curve, 0.93±0.02). In multivariate binary logistic regression, the probability of malignant infarct was significantly associated with early infarct volume and NWU.

Conclusions—Computed tomography–based quantitative NWU in early infarct lesions is an important surrogate marker for developing malignant edema. Besides volume of early infarct, the measurements of lesion water uptake may further support identifying patients at risk for malignant infarction.