Dataset Information

Cystatin C is a useful predictor of early neurological deterioration following ischaemic stroke in elderly patients with normal renal function.

ABSTRACT:

Introduction

Cystatin C has been suggested as a sensitive marker of renal function. A high level of cystatin C is related to cardiovascular disease and stroke in elderly patients. We investigated the relationship between levels of cystatin C and early neurological deterioration with acute ischaemic stroke in elderly patients without chronic kidney disease.

Patients and methods

We evaluated a total of 771 elderly patients (mean age, 72.2; male, 59.0%) without chronic kidney disease who were admitted following acute ischaemic stroke between March 2010 and January 2015. The patients were divided into four groups based on the quartiles of serum cystatin C values. Early neurological deterioration was defined as an increase of ?2 points from the baseline National Institutes of Health Stroke Scale score during the 7 days following onset. We compared the clinical characteristics and cystatin C concentrations between patients with and without early neurological deterioration.

Results

Eighty-six patients (11.2%) experienced early neurological deterioration. The percentage values of the higher (third and fourth) quartiles were significantly higher in the early neurological deterioration group (30.2% vs. 24.4% and 34.9% vs. 23.8%, P?=?0.002). After adjustment for covariates, higher cystatin C levels were independently associated with a higher risk of early neurological deterioration: odds ratio (95% confidence interval) for second quartile 1.59 (0.70-3.58), third quartile 2.75 (1.25-6.04), fourth quartile 3.12 (1.36-7.16); P for trend 0.026.

Discussion and conclusions

This study demonstrated that cystatin C concentrations in elderly patients without chronic kidney disease were associated with early neurological deterioration following acute stroke. This suggests that cystatin C level could be a useful predictor for early neurological deterioration following acute stroke.

SUBMITTER: Kim TJ

PROVIDER: S-EPMC6453184 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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Publications

Cystatin C is a useful predictor of early neurological deterioration following ischaemic stroke in elderly patients with normal renal function.

Kim Tae Jung TJ Kang Min Kyoung MK Jeong Han-Gil HG Kim Chi Kyung CK Kim Yerim Y Nam Ki-Woong KW Mo Heejung H An Sang Joon SJ Ko Sang-Bae SB Yoon Byung-Woo BW

European stroke journal 20161026 1

<h4>Introduction</h4>Cystatin C has been suggested as a sensitive marker of renal function. A high level of cystatin C is related to cardiovascular disease and stroke in elderly patients. We investigated the relationship between levels of cystatin C and early neurological deterioration with acute ischaemic stroke in elderly patients without chronic kidney disease.<h4>Patients and methods</h4>We evaluated a total of 771 elderly patients (mean age, 72.2; male, 59.0%) without chronic kidney disease ...[more]

PMID: 31008299

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Project description:For many years, researchers have sought to understand whether and when stroke survivors with acquired language impairment (aphasia) will recover. There is broad agreement that lesion location information should play some role in these predictions, but still no consensus on the best or right way to encode that information. Here, we address the emerging emphasis on the structural connectome in this work - specifically the claim that disrupted white matter connectivity conveys important, unique prognostic information for stroke survivors with aphasia. Our sample included 818 stroke patients extracted from the PLORAS database, which associates structural MRI from stroke patients with language assessment scores from the Comprehensive Aphasia Test (CAT) and basic demographic. Patients were excluded when their lesions were too diffuse or small (<1?cm3) to be detected by the Automatic Lesion Identification toolbox, which we used to encode patients' lesions as binary lesion images in standard space. Lesions were encoded using the 116 regions defined by the Automatic Anatomical Labelling atlas. We examined prognostic models driven by both "lesion load" in these regions (i.e. the proportion of each region destroyed by each patient's lesion), and by the disconnection of the white matter connections between them which was calculated via the Network Modification toolbox. Using these data, we build a series of prognostic models to predict first one ("naming"), and then all of the language scores defined by the CAT. We found no consistent evidence that connectivity disruption data in these models improved our ability to predict any language score. This may be because the connectivity disruption variables are strongly correlated with the lesion load variables: correlations which we measure both between pairs of variables in their original form, and between principal components of both datasets. Our conclusion is that, while both types of structural brain data do convey useful, prognostic information in this domain, they also appear to convey largely the same variance. We conclude that connectivity disruption variables do not help us to predict patients' language skills more accurately than lesion location (load) data alone.

Dataset Information

Cystatin C is a useful predictor of early neurological deterioration following ischaemic stroke in elderly patients with normal renal function.

Introduction

Patients and methods

Results

Discussion and conclusions

Publications

Cystatin C is a useful predictor of early neurological deterioration following ischaemic stroke in elderly patients with normal renal function.

Similar Datasets

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