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Predictors of quality of life 1 year after minor stroke or TIA: a prospective single-centre cohort study.

ABSTRACT: OBJECTIVES:In patients after a transient ischaemic attack (TIA) or minor stroke, dysfunction is often underestimated by clinical measures due to invisible symptoms, including cognitive and emotional problems. Many of these patients need stroke care programme, but others do not. In this study, we aim to identify potential predictors of quality of life (QoL) in patients with TIA or minor stroke 1 year poststroke to be able to select which of these patients will need aftercare. DESIGN:Prospective observational cohort study. SETTING:Single-centre hospital in the Netherlands. PARTICIPANTS:120 patients, diagnosed with TIA or minor stroke and discharged without rehabilitation treatment, completed the study. PRIMARY AND SECONDARY OUTCOME MEASURES:QoL (RAND-36), anxiety and depressive symptoms (Hospital Anxiety and Depression scale), the degree of disability or functional dependence after stroke (modified Rankin Scale (mRS)) and symptoms of anxiety and depression specific to stroke (SSADQ) were assessed at baseline (2-6 weeks poststroke) and compared with follow-up at 1 year poststroke. RESULTS:Depression (B=-1.35, p<0.001) and anxiety (B=-0.57, p=0.041) at baseline predicted a worse mental component of QoL after 1 year. Depression (B=-1.100, p<0.001) at baseline, but also age (B=-0.261, p=0.002) and female sex (B=4.101, p=0.034) predicted a worse physical component of QoL after 1 year. CONCLUSION:With the identification of these predictors, we might be able to select more efficiently and timely the patients with TIA or minor stroke who need stroke aftercare.

SUBMITTER: Lam KH

PROVIDER: S-EPMC6830651 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Predictors of quality of life 1 year after minor stroke or TIA: a prospective single-centre cohort study.

Lam Ka-Hoo KH Blom Emma E Kwa Vincent I H VIH

BMJ open 20191102 11

<h4>Objectives</h4>In patients after a transient ischaemic attack (TIA) or minor stroke, dysfunction is often underestimated by clinical measures due to invisible symptoms, including cognitive and emotional problems. Many of these patients need stroke care programme, but others do not. In this study, we aim to identify potential predictors of quality of life (QoL) in patients with TIA or minor stroke 1 year poststroke to be able to select which of these patients will need aftercare.<h4>Design</h ...[more]

PMID: 31678939

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Project description:BackgroundClinical prediction models/scores help clinicians make optimal evidence-based decisions when caring for their patients. To critically appraise such prediction models for use in a clinical setting, essential information on the derivation and validation of the models needs to be transparently reported. In this systematic review, we assessed the quality of reporting of derivation and validation studies of prediction models for the prognosis of recurrent stroke in patients with transient ischemic attack or minor stroke.MethodsMEDLINE and EMBASE databases were searched up to February 04, 2020. Studies reporting development or validation of multivariable prognostic models predicting recurrent stroke within 90 days in patients with TIA or minor stroke were included. Included studies were appraised for reporting quality and conduct using a select list of items from the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) Statement.ResultsAfter screening 7026 articles, 60 eligible articles were retained, consisting of 100 derivation and validation studies of 27 unique prediction models. Four models were newly derived while 23 were developed by validating and updating existing models. Of the 60 articles, 15 (25%) reported an informative title. Among the 100 derivation and validation studies, few reported whether assessment of the outcome (24%) and predictors (12%) was blinded. Similarly, sample size justifications (49%), description of methods for handling missing data (16.1%), and model calibration (5%) were seldom reported. Among the 96 validation studies, 17 (17.7%) clearly reported on similarity (in terms of setting, eligibility criteria, predictors, and outcomes) between the validation and the derivation datasets. Items with the highest prevalence of adherence were the source of data (99%), eligibility criteria (93%), measures of discrimination (81%) and study setting (65%).ConclusionsThe majority of derivation and validation studies for the prognosis of recurrent stroke in TIA and minor stroke patients suffer from poor reporting quality. We recommend that all prediction model derivation and validation studies follow the TRIPOD statement to improve transparency and promote uptake of more reliable prediction models in practice.Trial registrationThe protocol for this review was registered with PROSPERO (Registration number CRD42020201130 ).

Project description:Background and Purpose: The risk of recurrent stroke following a transient ischemic attack (TIA) or minor stroke is high, despite of a significant reduction in the past decade. In this study, we investigated the feasibility of using artificial neural network (ANN) for risk stratification of TIA or minor stroke patients. Methods: Consecutive patients with acute TIA or minor ischemic stroke presenting at a tertiary hospital during a 2-year period were recruited. We collected demographics, clinical and imaging data at baseline. The primary outcome was recurrent ischemic stroke within 1 year. We developed ANN models to predict the primary outcome. We randomly down-sampled patients without a primary outcome to 1:1 match with those with a primary outcome to mitigate data imbalance. We used a 5-fold cross-validation approach to train and test the ANN models to avoid overfitting. We employed 19 independent variables at baseline as the input neurons in the ANN models, using a learning algorithm based on backpropagation to minimize the loss function. We obtained the sensitivity, specificity, accuracy and the c statistic of each ANN model from the 5 rounds of cross-validation and compared that of support vector machine (SVM) and Naïve Bayes classifier in risk stratification of the patients. Results: A total of 451 acute TIA or minor stroke patients were enrolled. Forty (8.9%) patients had a recurrent ischemic stroke within 1 year. Another 40 patients were randomly selected from those with no recurrent stroke, so that data from 80 patients in total were used for 5 rounds of training and testing of ANN models. The median sensitivity, specificity, accuracy and c statistic of the ANN models to predict recurrent stroke at 1 year was 75%, 75%, 75%, and 0.77, respectively. ANN model outperformed SVM and Naïve Bayes classifier in our dataset for predicting relapse after TIA or minor stroke. Conclusion: This pilot study indicated that ANN may yield a novel and effective method in risk stratification of TIA and minor stroke. Further studies are warranted for verification and improvement of the current ANN model.

Project description:ObjectiveWe report on: (1) the proportion of patients with known atrial fibrillation (AF); and (2) demographic, clinical or radiological differences between patients with known AF (and not treated) and patients with newly diagnosed AF, in a cohort of patients who presented with ischaemic stroke or transient ischaemic attack (TIA) not previously treated with anticoagulation.DesignWe reviewed cross-sectional baseline demographic and clinical data from a prospective observational cohort study, (CROMIS-2).SettingPatients were recruited from 79 hospital stroke centres throughout the UK and one centre in the Netherlands.ParticipantsPatients were eligible if they were adults who presented with ischaemic stroke or TIA and AF and had not been previously treated with oral anticoagulation.Main outcome measuresProportion of patients with known AF before index ischaemic stroke or TIA from a cohort of patients who have not been previously treated with oral anticoagulation. Secondary analysis includes the comparison of CHA2DS2-VASc and HAS-BLED scores and other demographics and risk factors between those with newly diagnosed AF and those with previously known AF.ResultsOf 1470 patients included in the analysis (mean age 76 years (SD 10)), 622 (42%) were female; 999 (68%) patients had newly diagnosed AF and 471 (32%) patients had known AF. Of the 471 patients with known AF, 68% had a strong indication for anticoagulation and 89% should have been considered for anticoagulation based upon CHA2DS2-VASc score. Patients with known AF were more likely to have a prior history of dementia (4% vs 2%, p=0.02) and had higher HAS-BLED scores (median 3 vs 2). CHA2DS2-VASc, other risk factors and demographics were similar.ConclusionsAbout 1/3 of patients who present with stroke and have AF who have not been treated with oral anticoagulation have previously known AF. Of these patients, at least 68% were not adequately treated with oral anticoagulation.Trial registration numberNCT02513316.

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Predictors of quality of life 1 year after minor stroke or TIA: a prospective single-centre cohort study.

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Predictors of quality of life 1 year after minor stroke or TIA: a prospective single-centre cohort study.

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