Related Experiment Video
Updated: Jan 30, 2026

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
Mortality and Predictors of Death Poststroke: Data from a Multicenter Prospective Cohort of Lebanese Stroke Patients
Rachel Abdo1, Halim Abboud2, Pascale Salameh3
1Laboratory of Clinical and Epidemiology Research, Faculties of Pharmacy and of Public Health, Lebanese University, Beirut, Lebanon; Doctoral School of Life and Health Sciences, Paris-Est University, Creteil, France; INSPECT-LB (Institut National de Santé Publique, d'Epidémiologie Clinique et Toxicologie-Liban), Faculty of Public Health, Fanar, Lebanon.
Insights
Over 1 in 5 stroke patients in Lebanon died within one year. Stroke severity and complications were key predictors of mortality, alongside socioeconomic status and comorbidities. Public awareness campaigns are crucial for stroke prevention.
Area of Science:
- Neurology
- Public Health
- Epidemiology
Background:
- Stroke remains a leading cause of death in Lebanon.
- Understanding stroke risk factors and mortality is crucial for public health initiatives.
- This study investigates short-term and long-term mortality predictors following acute stroke.
Purpose of the Study:
- To determine 1-month and 1-year mortality rates after acute stroke in Lebanon.
- To identify key predictors of short-term (1-month) and long-term (1-year) mortality.
- To inform public health strategies for stroke prevention and management.
Main Methods:
- Prospective data collection from 191 hospitalized stroke patients across 8 Beirut hospitals over 1 year.
- 1-year follow-up or until death to assess survival.
- Cox proportional hazard models used to evaluate mortality predictors.
Main Results:
- Cumulative mortality rates were 14.1% at 1 month and 22% at 1 year.
- Multivariate analysis identified stroke severity and complications as predictors for both 1-month and 1-year mortality.
- Low socioeconomic status, dependency, and comorbidities predicted 1-year mortality.
Conclusions:
- Nearly one-fifth of stroke patients in Lebanon do not survive the first year.
- Public awareness campaigns are essential to improve stroke knowledge, recognition, and prevention.
- Targeting modifiable risk factors and providing better post-stroke care can reduce mortality rates.
Background:
Despite efforts to reduce stroke mortality rates, the disease remains a leading cause of death in Lebanon highlighting the importance of understanding risk factors and subsequent mortality. We examined mortality rates during the first year after acute stroke and the major short-term (1-month) and long-term (1-year) mortality predictors.
Methods:
Data were collected prospectively on hospitalized stroke patients from 8 hospitals in Beirut during a 1-year period. Patients were followed up for 1-year or until death. Mortality rates were assessed at 1-month and at 1-year poststroke and predictors of death were evaluated using Cox proportional hazard model.
Results:
A total of 191 stroke patients were included. Survival data were completed for over 97% of patients. Cumulative mortality rates were 14.1% at 1-month and 22% at 1-year. Predictors of short-term and long-term mortality in univariate analysis were low socioeconomic status, intensive care unit admission, decreased level of consciousness, stroke severity, and presence of complications. Marital status also predicted short-term mortality, while age greater than 64 years, atrial fibrillation, coronary heart disease, hypertension, Bamford and TOAST classifications and surgery need were also long-term mortality predictors. In multivariate analysis, stroke severity and presence of complications were predictors of death at 1-month and at 1-year. Low socioeconomic status, dependency in daily living activities, and the presence of comorbidities were additional predictors of 1-year mortality.
Conclusions:
Approximately 1 over 5 of patients did not survive 1-year after stroke. There is a need for public awareness campaigns to improve stroke knowledge, warning, and prevention which may reduce this high stroke mortality rate in Lebanon.
Related Concept Videos
Data Reporting and Recording
Autophagic Cell Death
Autophagy and Apoptosis
Autophagy can activate apoptosis. In normal conditions, the autophagy activating protein Beclin-1 and...
Overview of Cell Death
Cell death was observed in the early 19th century, but there was no experimental evidence to prove it. In 1842, Carl Vogt first discovered cell death in a metamorphic toad; however, it was not termed ‘cell death.’ Scientists discovered different cell death pathways only in the...
How Data are Classified: Categorical Data
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
How Data are Classified: Numerical Data
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical...
Regulation of Stroke Volume
Preload refers to the degree of stretch on the heart before it contracts. It's analogous to the stretching of a rubber band; the more it's stretched, the more forcefully it snaps back. This concept is encapsulated in the Frank-Starling law of the...

