Skip to main content

Main menu

  • Home
  • Content
    • Latest
    • Archive
    • home
  • Info for
    • Authors
    • Reviewers
    • Subscribers
    • Institutions
    • Advertisers
    • Join SMJ
  • About Us
    • About Us
    • Editorial Office
    • Editorial Board
  • More
    • Advertising
    • Alerts
    • Feedback
    • Folders
    • Help
  • Other Publications
    • NeuroSciences Journal

User menu

  • My alerts
  • Log in

Search

  • Advanced search
Saudi Medical Journal
  • Other Publications
    • NeuroSciences Journal
  • My alerts
  • Log in
Saudi Medical Journal

Advanced Search

  • Home
  • Content
    • Latest
    • Archive
    • home
  • Info for
    • Authors
    • Reviewers
    • Subscribers
    • Institutions
    • Advertisers
    • Join SMJ
  • About Us
    • About Us
    • Editorial Office
    • Editorial Board
  • More
    • Advertising
    • Alerts
    • Feedback
    • Folders
    • Help
  • Follow psmmc on Twitter
  • Visit psmmc on Facebook
  • RSS
Research ArticleOriginal Article
Open Access

Identifying individuals at risk of post-stroke depression

Development and validation of a predictive model

Saeed A. Alqahtani
Saudi Medical Journal May 2025, 46 (5) 497-506; DOI: https://doi.org/10.15537/smj.2025.46.5.20250080
Saeed A. Alqahtani
From the Department of Basic Medical Sciences, Taibah University, Al-Madinah Al-Munawarah, Kingdom of Saudi Arabia.
MD, PhD
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Saeed A. Alqahtani
  • For correspondence: [email protected]
  • Article
  • Figures & Data
  • eLetters
  • Info & Metrics
  • References
  • PDF
Loading

Article Figures & Data

Figures

  • Tables
  • Figure 1
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 1

    - Mutual information of the features.

  • Figure 2
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 2

    - Adjusted mutual information of the features.

Tables

  • Figures
    • View popup
    Table 1

    - Descriptive analysis of the variables.

    Variablesn (%)
    Depression stroke
    No12231 (0.1)
    Yes5229 (29.9)
    Gender
    Female220428 (52.5)
    Male199048 (47.5)
    Marital status
    Not married200055 (48.2)
    Married215236 (51.8)
    Alcohol status
    Do not drink184234 (43.9)
    Yes235242 (56.1)
    Physical activity
    No physical activity or exercise in last 30 days102760 (24.6)
    Had physical activity or exercise315502 (75.4)
    Smoking status
    No353604 (89.1)
    Yes43441 (10.9)
    Diabetes status
    Not diabetic358706 (85.7)
    Diabetic59786 (14.3)
    Hypertension status
    No hypertension248435 (59.5)
    Have hypertension169195 (40.5)
    Cholesterol status
    Normal213522 (58.4)
    High152114 (41.6)
    Stroke status
    No400461 (95.8)
    Yes17609 (4.2)
    Depressive disorder
    No332667 (79.8)
    Yes84333 (20.2)
    Age groups (years)
    65-6944491 (10.6)
    70-7442049 (10.0)
    60-6440438 (9.6)
    80-older37723 (9.0)
    75-7933407 (8.0)
    55-5932968 (7.9)
    50-5430131 (7.2)
    40-4427445 (6.5)
    35-3926188 (6.2)
    45-4926172 (6.2)
    18-2425962 (6.2)
    30-3424101 (5.7)
    25-2920804 (5.0)
    Education level
    Graduated from college or technical school179801 (42.9)
    Attended college or technical school110398 (26.3)
    Graduated high school103086 (24.6)
    Did not graduate high school23920 (5.7)
    Income category
    $50,000 to <$100,000103861 (30.9)
    $100,000 to <$200,00074632 (22.2)
    $35,000 to <$50,00045827 (13.7)
    $25,000 to <$35,00037045 (11.0)
    $15,000 to <$25,00029749 (8.9)
    $200,000 or more26223 (7.8)
    Less than $15,00018270 (5.4)
    BMI category
    Overweight135644 (35.7)
    Obese123934 (32.6)
    Normal weight114035 (30.0)
    Underweight6638 (1.7)

    Values are presented as numbers and percentages (%). BMI: body mass index

      • View popup
      Table 2

      - Logistic regression analysis.

      VariablesOdds ratio95% CIP-values
      Intercept1.861.21-2.85<0.05
      BMI
      Obese1.331.21-1.46<0.05
      Overweight1.060.97-1.160.23
      Underweight1.160.90-1.490.25
      Gender0.570.53-0.61<0.05
      Marital status0.860.80-0.93<0.05
      Physical activity0.770.72-0.83<0.05
      Smoking status1.51.37-1.65<0.05
      Diabetes status1.221.13-1.31<0.05
      Hypertension status0.960.88-1.040.3
      Cholesterol status1.41.30-1.51<0.05
      Alcohol status0.970.90-1.050.43
      Age (years)
      25-291.020.59-1.780.94
      30-340.740.45-1.240.25
      35-390.940.59-1.510.81
      40-440.780.50-1.220.28
      45-490.840.55-1.300.44
      50-540.580.38-0.89<0.05
      55-590.580.38-0.88<0.05
      60-640.510.34-0.76<0.05
      65-690.360.24-0.54<0.05
      70-740.320.21-0.47<0.05
      75-790.270.18-0.41<0.05
      80 or older0.160.11-0.24<0.05
      Education level
      Graduated high school0.90.80-1.020.11
      Attended college or technical school1.060.94-1.200.35
      Graduated from college or technical school1.130.99-1.290.08
      Income category
      $15,000 to <$25,0000.730.64-0.84<0.05
      $25,000 to <$35,0000.650.57-0.75<0.05
      $35,000 to <$50,0000.60.53-0.68<0.05
      $50,000 to <$100,0000.570.49-0.66<0.05
      $100,000 to <$200,0000.460.38-0.55<0.05
      $200,000 or more0.40.30-0.54<0.05

      CI: confidence interval, BMI: body mass index, $: US dollar

        • View popup
        Table 3

        - Models evaluation metrics.

        ModelsAccuracyPrecisionRecallF1-scoreAUC-ROC
        Random forest0.730.710.770.740.81
        Decision tree0.700.690.730.710.73
        Gradient boosting0.650.660.640.650.72
        Logistic regression0.650.650.620.640.70

        F1-score: harmonic mean of precision and recall, AUC: area under the curve, ROC: receiver-operating characteristic curve

        PreviousNext
        Back to top

        In this issue

        Saudi Medical Journal: 46 (5)
        Saudi Medical Journal
        Vol. 46, Issue 5
        1 May 2025
        • Table of Contents
        • Cover (PDF)
        • Index by author
        Print
        Download PDF
        Email Article

        Thank you for your interest in spreading the word on Saudi Medical Journal.

        NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

        Enter multiple addresses on separate lines or separate them with commas.
        Identifying individuals at risk of post-stroke depression
        (Your Name) has sent you a message from Saudi Medical Journal
        (Your Name) thought you would like to see the Saudi Medical Journal web site.
        Citation Tools
        Identifying individuals at risk of post-stroke depression
        Saeed A. Alqahtani
        Saudi Medical Journal May 2025, 46 (5) 497-506; DOI: 10.15537/smj.2025.46.5.20250080

        Citation Manager Formats

        • BibTeX
        • Bookends
        • EasyBib
        • EndNote (tagged)
        • EndNote 8 (xml)
        • Medlars
        • Mendeley
        • Papers
        • RefWorks Tagged
        • Ref Manager
        • RIS
        • Zotero
        Share
        Identifying individuals at risk of post-stroke depression
        Saeed A. Alqahtani
        Saudi Medical Journal May 2025, 46 (5) 497-506; DOI: 10.15537/smj.2025.46.5.20250080
        Twitter logo Facebook logo Mendeley logo
        • Tweet Widget
        • Facebook Like
        • Google Plus One
        Bookmark this article

        Jump to section

        • Article
          • ABSTRACT
          • Methods
          • Results
          • Discussion
          • Acknowledgment
          • Footnotes
          • References
        • Figures & Data
        • eLetters
        • References
        • Info & Metrics
        • PDF

        Related Articles

        • No related articles found.
        • PubMed
        • Google Scholar

        Cited By...

        • No citing articles found.
        • Google Scholar

        More in this TOC Section

        • Hematological parameters in recent and past dengue infections in Jazan Province, Saudi Arabia
        • Longitudinal analysis of foodborne disease outbreaks in Saudi Arabia
        Show more Original Article

        Similar Articles

        Keywords

        • post-stroke depression
        • risk factors
        • machine learning
        • mutual information
        • logistic regression

        CONTENT

        • home

        JOURNAL

        • home

        AUTHORS

        • home
        Saudi Medical Journal

        © 2025 Saudi Medical Journal Saudi Medical Journal is copyright under the Berne Convention and the International Copyright Convention.  Saudi Medical Journal is an Open Access journal and articles published are distributed under the terms of the Creative Commons Attribution-NonCommercial License (CC BY-NC). Readers may copy, distribute, and display the work for non-commercial purposes with the proper citation of the original work. Electronic ISSN 1658-3175. Print ISSN 0379-5284.

        Powered by HighWire