scholarly journals Prediction Models for Assessing Long-Term Outcome in Alzheimer’s Disease

2013 ◽  
Vol 28 (5) ◽  
pp. 440-449 ◽  
Author(s):  
Carina Wattmo
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Prediction Models ◽  
Term Outcome ◽  
Long Term Outcome

scholarly journals Assessment of the Subarachnoid Hemorrhage International Trialists (SAHIT) Models for Dichotomized Long-Term Functional Outcome Prediction After Aneurysmal Subarachnoid Hemorrhage in a United Kingdom Multicenter Cohort Study

Neurosurgery ◽  
2020 ◽  
Author(s):  
Isabel C Hostettler ◽  
Menelaos Pavlou ◽  
Gareth Ambler ◽  
Varinder S Alg ◽  
Stephen Bonner ◽  
...  
Keyword(s):  
Subarachnoid Hemorrhage ◽  
Functional Outcome ◽  
Outcome Prediction ◽  
Prediction Models ◽  
Aneurysmal Subarachnoid Hemorrhage ◽  
Predictive Performance ◽  
Term Outcome ◽  
Long Term Outcome ◽  
Fisher Grade

Abstract BACKGROUND Long-term outcome after subarachnoid hemorrhage, beyond the first few months, is difficult to predict, but has critical relevance to patients, their families, and carers. OBJECTIVE To assess the performance of the Subarachnoid Hemorrhage International Trialists (SAHIT) prediction models, which were initially designed to predict short-term (90 d) outcome, as predictors of long-term (2 yr) functional outcome after aneurysmal subarachnoid hemorrhage (aSAH). METHODS We included 1545 patients with angiographically-proven aSAH from the Genetic and Observational Subarachnoid Haemorrhage (GOSH) study recruited at 22 hospitals between 2011 and 2014. We collected data on age, WNFS grade on admission, history of hypertension, Fisher grade, aneurysm size and location, as well as treatment modality. Functional outcome was measured by the Glasgow Outcome Scale (GOS) with GOS 1 to 3 corresponding to unfavorable and 4 to 5 to favorable functional outcome, according to the SAHIT models. The SAHIT models were assessed for long-term outcome prediction by estimating measures of calibration (calibration slope) and discrimination (area under the receiver-operating characteristic curve [AUC]) in relation to poor clinical outcome. RESULTS Follow-up was standardized to 2 yr using imputation methods. All 3 SAHIT models demonstrated acceptable predictive performance for long-term functional outcome. The estimated AUC was 0.71 (95% CI: 0.65-0.76), 0.73 (95% CI: 0.68-0.77), and 0.74 (95% CI: 0.69-0.79) for the core, neuroimaging, and full models, respectively; the calibration slopes were 0.86, 0.84, and 0.89, indicating good calibration. CONCLUSION The SAHIT prediction models, incorporating simple factors available on hospital admission, show good predictive performance for long-term functional outcome after aSAH.

The association of traumatic brain injury with rate of progression of cognitive and functional impairment in a population-based cohort of Alzheimer's disease: the Cache County dementia progression study by Gilbertet al. Late effects of traumatic brain injury on dementia progression

2014 ◽  
Vol 26 (10) ◽  
pp. 1591-1592 ◽  
Author(s):  
David J. Sharp
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Road Traffic ◽  
Population Based ◽  
Term Outcome ◽  
Long Term Outcome ◽  
History Of ◽  
First Time

There is compelling evidence that traumatic brain injury (TBI) can trigger neurodegeneration, and that this is a major determinant of long-term outcome (Smithet al., 2013). A single significant injury such as a road traffic accident or exposure to a bomb blast can predispose an individual to Alzheimer's disease (AD), and here Gilbert and colleagues show for the first time that a history of TBI also alters the progression the disease.

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

2017 ◽  
Vol 3 (1) ◽  
pp. 57-65 ◽  
Author(s):  
Eline J Volkers ◽  
Ale Algra ◽  
L Jaap Kappelle ◽  
Jacoba P Greving
Keyword(s):  
Carotid Artery ◽  
Carotid Endarterectomy ◽  
Carotid Stenosis ◽  
Carotid Artery Stenting ◽  
Prediction Models ◽  
Term Outcome ◽  
Discriminative Performance ◽  
Long Term Outcome ◽  
C Statistic

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.

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