One-year survival and prognostic factors for survival among stroke patients: The PROVE-stroke study

Mahshid Givi1, Negin Badihian2, Marzieh Taheri3

  • 1Nursing and Midwifery Care Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.

Insights

Stroke survival rates in Iran show that 72.1% of patients lived one year post-stroke. Key predictors included age, diabetes, prior stroke, and hospital complications like hemorrhage and sepsis.

Area of Science:

  • Neurology
  • Public Health
  • Epidemiology

Background:

  • Stroke incidence and outcomes vary globally, with limited data from the Middle East.
  • Understanding regional stroke patterns is crucial for targeted public health interventions.

Purpose of the Study:

  • To determine 1-year survival rates among stroke patients in Central Iran.
  • To identify prognostic factors influencing stroke survival in this specific population.

Main Methods:

  • An observational analytical study using the PROVE-Stroke database.
  • Reviewed records of 1703 patients admitted for stroke in Isfahan, Iran, between 2015-2016.
  • Collected data on demographics, clinical details, comorbidities, and 1-year survival status.

Main Results:

  • Out of 1345 patients, 970 (72.1%) survived one year, with a mean survival time of 277.33 days.
  • Ischemic stroke (84.8%) was more common than hemorrhagic stroke (15.0%).
  • Significant predictors of mortality included advanced age, diabetes, history of stroke/TIA, warfarin use, hospital-acquired hemorrhage, sepsis, hydrocephalus, and a modified Rankin Scale score of ≥3 at discharge.

Conclusions:

  • Identified both unmodifiable (age, diabetes, prior stroke, mRS) and modifiable (hospital complications) predictors of 1-year stroke survival.
  • Highlights the importance of managing hospital-acquired complications to reduce stroke mortality.
Abstract

Related Concept Videos

Actuarial Approach01:20

Actuarial Approach

The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
108
Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
411
Atherosclerosis IV: Nursing Management01:23

Atherosclerosis IV: Nursing Management

Nursing management for a patient with arteriosclerosis involves a comprehensive approach focusing on lifestyle modification, disease monitoring, education, and symptomatic care. Here is an overview of effective nursing strategies:Assessment and Monitoring: Initial and ongoing assessments are crucial. Nurses must document the patient's medical history, including any hypertension, diabetes, hyperlipidemia, and other cardiovascular diseases. Assessments also cover family history and lifestyle...
35
Assumptions of Survival Analysis01:15

Assumptions of Survival Analysis

Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
172