Ale Algra

Hemicraniectomy after middle cerebral artery infarction with life-threatening Edema trial (HAMLET). Protocol for a randomised controlled trial of decompressive surgery in space-occupying hemispheric infarction

BackgroundPatients with a hemispheric infarct and massive space-occupying brain oedema have a poor prognosis. Despite maximal conservative treatment, the case fatality rate may be as high as 80%, and most survivors are left severely disabled. Non-randomised studies suggest that decompressive surgery reduces mortality substantially and improves functional outcome of survivors. This study is designed to compare the efficacy of decompressive surgery to improve functional outcome with that of conservative treatment in patients with space-occupying supratentorial infarctionMethodsThe study design is that of a multi-centre, randomised clinical trial, which will include 112 patients aged between 18 and 60 years with a large hemispheric infarct with space-occupying oedema that leads to a decrease in consciousness. Patients will be randomised to receive either decompressive surgery in combination with medical treatment or best medical treatment alone. Randomisation will be stratified for the intended mode of conservative treatment (intensive care or stroke unit care). The primary outcome measure will be functional outcome, as determined by the score on the modified Rankin Scale, at one year.

Prediction models for clinical outcome after a carotid revascularisation procedure: A systematic review:

Introduction Prediction models for clinical outcome after carotid artery stenting or carotid endarterectomy could aid physicians in estimating peri- and postprocedural risks in individual patients. We aimed to identify existing prediction models for short- and long-term outcome after carotid artery stenting or carotid endarterectomy in patients with symptomatic or asymptomatic carotid stenosis, and to summarise their most important predictors and predictive performance. Patients and methods We performed a systematic literature search for studies that developed a prediction model or risk score published until 22 December 2016. Eligible prediction models had to predict the risk of vascular events with at least one patient characteristic. Results We identified 37 studies that developed 46 prediction models. Thirty-four (74%) models were developed in carotid endarterectomy patients; 27 of these (59%) predicted short-term (in-hospital or within 30 days) risk. Most commonly predicted outcome was stroke or death (n = 12; 26%). Age (n = 31; 67%), diabetes mellitus (n = 21; 46%), heart failure (n = 16; 35%), and contralateral carotid stenosis ≥50% or occlusion (n = 16; 35%) were most commonly used as predictors. For 25 models (54%), it was unclear how missing data were handled; a complete case analysis was performed in 15 (33%) of the remaining 21 models. Twenty-eight (61%) models reported the full regression formula or risk score with risk classification. Twenty-one (46%) models were validated internally and 12 (26%) externally. Discriminative performance (c-statistic) ranged from 0.66 to 0.94 for models after carotid artery stenting and from 0.58 to 0.74 for models after carotid endarterectomy. The c-statistic ranged from 0.55 to 0.72 for the external validations. Discussion Age, diabetes mellitus, heart failure, and contralateral carotid stenosis ≥50% or occlusion were most often used as predictors in all models. Discriminative performance (c-statistic) was higher for prediction models after carotid artery stenting than after carotid endarterectomy. Conclusion The clinical usefulness of most prediction models for short- or long-term outcome after carotid artery stenting or carotid endarterectomy remains unclear because of incomplete reporting, methodological limitations, and lack of external validation.