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Diastolic blood pressure cut-off predicts major cerebrovascular events after minor ischaemic stroke: a post-hoc modelling study

Diastolic blood pressure cut-off predicts major cerebrovascular events after minor ischaemic stroke: a post-hoc modelling study
Diastolic blood pressure cut-off predicts major cerebrovascular events after minor ischaemic stroke: a post-hoc modelling study
Only few follow-up studies have studied in detail the role of most important risk factors, but no reports were found on critical values (cut-offs) for such factors in prospectively predicting cerebrovascular events (CVE) in patients with minor ischaemic stroke (MIS). Estimates of predictive importance of such cut-offs may better inform and contribute to optimize treatment. This was a post-hoc modelling study with unique data from Bulgaria on 54 consecutive patients with MIS, aged ? 40, followed for 12 months for nonfatal or fatal CV events. A set of routine clinical demographic and known risk factors (SBP, DBP, HDL cholesterol, etc.) were explored using univariate statistics and multivariate regression models to identify the most important independent predictors of secondary CVE. An artificial neural network (ANN) model, irrespective of usual statistical constraints, also confirmed the specific role and importance of identified predictors. A receiver operating characteristics (ROC) curve and stratified survival analyses were used to define the best cut-off of most important predictors and validate the final model. During follow-up period of 11.1±2.4 months, 8 secondary CV events (14.8%) were observed only in males with MIS at the 5.8±2.7 months mark. No difference in age of patients with CV event (61.1±12.6 years) vs. those without (62.1±9.6 years) was found (p>0.05). The one-year risk for CVE was.15% (95%CI 7.1, 27.7%). The two most important risk factors in patients with versus without CV events were acute MIS onset (62.5 vs. 13.0%) and mean DBP at day 30 post-MIS (101.3±9.9 vs. 92.3±10.8 mmHg), with a relative importance by ANN of 20.92 versus 15.9 points, respectively. At multivariate logistic analysis only MIS onset and DBP were independently associated with the risk for secondary CVE (79.6% model accuracy, p model=0.0015). An increase of DBP with 1 mmHg was associated with 8% higher risk of CVE [adjusted OR=1.08 (95%Cl 1.004, 1.158)]. With this method, a novel cut-off predictive DBP value of 95 mmHg (ROCAUC=0.79, 95%Cl 0.60, 0.99, p=0.009) for CV events in patients with MIS has been found. In conclusions the new DBP cut-off (sensitivity >87%, specificity >69%) clearly discriminated between absence and presence of secondary CVE as also confirmed by stratified survival analysis (7 vs. 1 events, plog-rank =0.0103). This cut-off may be applied to better precisely evaluate and define, as earlier as possible, MIS patients at increased risk of secondary CV events
minor ischemic stroke, cerebrovascular events, artificial neural networks, outcome modelling, bulgaria
1895-1058
430-437
Atanassova, P.A.
0a35e6ad-0564-4057-b998-967ec0d8bef6
Chalakova, N.T.
10d1fae5-ee15-4f8b-abde-e41659d8bad3
Dimitrov, B.D.
366d715f-ffd9-45a1-8415-65de5488472f
Atanassova, P.A.
0a35e6ad-0564-4057-b998-967ec0d8bef6
Chalakova, N.T.
10d1fae5-ee15-4f8b-abde-e41659d8bad3
Dimitrov, B.D.
366d715f-ffd9-45a1-8415-65de5488472f

Atanassova, P.A., Chalakova, N.T. and Dimitrov, B.D. (2008) Diastolic blood pressure cut-off predicts major cerebrovascular events after minor ischaemic stroke: a post-hoc modelling study. Central European Journal of Medicine, 3 (4), 430-437. (doi:10.2478/s11536-008-0064-4).

Record type: Article

Abstract

Only few follow-up studies have studied in detail the role of most important risk factors, but no reports were found on critical values (cut-offs) for such factors in prospectively predicting cerebrovascular events (CVE) in patients with minor ischaemic stroke (MIS). Estimates of predictive importance of such cut-offs may better inform and contribute to optimize treatment. This was a post-hoc modelling study with unique data from Bulgaria on 54 consecutive patients with MIS, aged ? 40, followed for 12 months for nonfatal or fatal CV events. A set of routine clinical demographic and known risk factors (SBP, DBP, HDL cholesterol, etc.) were explored using univariate statistics and multivariate regression models to identify the most important independent predictors of secondary CVE. An artificial neural network (ANN) model, irrespective of usual statistical constraints, also confirmed the specific role and importance of identified predictors. A receiver operating characteristics (ROC) curve and stratified survival analyses were used to define the best cut-off of most important predictors and validate the final model. During follow-up period of 11.1±2.4 months, 8 secondary CV events (14.8%) were observed only in males with MIS at the 5.8±2.7 months mark. No difference in age of patients with CV event (61.1±12.6 years) vs. those without (62.1±9.6 years) was found (p>0.05). The one-year risk for CVE was.15% (95%CI 7.1, 27.7%). The two most important risk factors in patients with versus without CV events were acute MIS onset (62.5 vs. 13.0%) and mean DBP at day 30 post-MIS (101.3±9.9 vs. 92.3±10.8 mmHg), with a relative importance by ANN of 20.92 versus 15.9 points, respectively. At multivariate logistic analysis only MIS onset and DBP were independently associated with the risk for secondary CVE (79.6% model accuracy, p model=0.0015). An increase of DBP with 1 mmHg was associated with 8% higher risk of CVE [adjusted OR=1.08 (95%Cl 1.004, 1.158)]. With this method, a novel cut-off predictive DBP value of 95 mmHg (ROCAUC=0.79, 95%Cl 0.60, 0.99, p=0.009) for CV events in patients with MIS has been found. In conclusions the new DBP cut-off (sensitivity >87%, specificity >69%) clearly discriminated between absence and presence of secondary CVE as also confirmed by stratified survival analysis (7 vs. 1 events, plog-rank =0.0103). This cut-off may be applied to better precisely evaluate and define, as earlier as possible, MIS patients at increased risk of secondary CV events

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Published date: 2008
Keywords: minor ischemic stroke, cerebrovascular events, artificial neural networks, outcome modelling, bulgaria
Organisations: Primary Care & Population Sciences

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Local EPrints ID: 365794
URI: https://eprints.soton.ac.uk/id/eprint/365794
ISSN: 1895-1058
PURE UUID: 311d761f-5c3f-449e-b82d-68f38922d486

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Date deposited: 16 Jun 2014 11:51
Last modified: 16 Jul 2019 21:03

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