RT Journal Article
T1 Predictive Model and Mortality Risk Score during Admission for Ischaemic Stroke with Conservative Treatment.
A1 Lea-Pereira, Maria Carmen
A1 Amaya-Pascasio, Laura
A1 Martinez-Sanchez, Patricia
A1 Rodriguez Salvador, Maria Del Mar
A1 Galvan-Espinosa, Jose
A1 Tellez-Ramirez, Luis
A1 Reche-Lorite, Fernando
A1 Sanchez-Perez, Maria-Jose
A1 Garcia-Torrecillas, Juan Manuel
K1 mortality
K1 predictive model
K1 risk score
K1 stroke
K1 vascular neurology
AB Stroke is the second cause of mortality worldwide and the first in women. The aim of this study is to develop a predictive model to estimate the risk of mortality in the admission of patients who have not received reperfusion treatment. A retrospective cohort study was conducted of a clinical-administrative database, reflecting all cases of non-reperfused ischaemic stroke admitted to Spanish hospitals during the period 2008-2012. A predictive model based on logistic regression was developed on a training cohort and later validated by the "hold-out" method. Complementary machine learning techniques were also explored. The resulting model had the following nine variables, all readily obtainable during initial care. Age (OR 1.069), female sex (OR 1.202), readmission (OR 2.008), hypertension (OR 0.726), diabetes (OR 1.105), atrial fibrillation (OR 1.537), dyslipidaemia (0.638), heart failure (OR 1.518) and neurological symptoms suggestive of posterior fossa involvement (OR 2.639). The predictability was moderate (AUC 0.742, 95% CI: 0.737-0.747), with good visual calibration; Pearson's chi-square test revealed non-significant calibration. An easily consulted risk score was prepared. It is possible to create a predictive model of mortality for patients with ischaemic stroke from which important advances can be made towards optimising the quality and efficiency of care. The model results are available within a few minutes of admission and would provide a valuable complementary resource for the neurologist.
PB MDPI AG
YR 2022
FD 2022-03-04
LK http://hdl.handle.net/10668/21043
UL http://hdl.handle.net/10668/21043
LA en
NO Lea-Pereira MC, Amaya-Pascasio L, Martínez-Sánchez P, Rodríguez Salvador MDM, Galván-Espinosa J, Téllez-Ramírez L, et al. Predictive Model and Mortality Risk Score during Admission for Ischaemic Stroke with Conservative Treatment. Int J Environ Res Public Health. 2022 Mar 8;19(6):3182.
NO This work was supported by the “Fundación Progreso y Salud”, in the context of FPS 2020—R&I projects in Primary Care, Regional hospitals and CHARES. Grant number AP-0013-2020-C1-F1and the APC was funded by the same.
DS RISalud
RD Apr 6, 2025