Assessing Sex Differences in Patients With Stroke or Transient Ischemic AttackWhen Treated With Dual Antiplatelet Therapy

PRESLEY WHETMAN
PRESLEY WHETMAN

Abstract

Purpose

Our study aims to identify sex-associated differences in stroke and major bleed rates for patients with intracranial atherosclerosis (IA) and transient ischemic attack (TIA) when treated with dual antiplatelet therapy (DAPT) for secondary stroke prevention. The potential impact of our study could support change for treatment guidelines for secondary stroke prevention in men and women with IA treated with DAPT. It is reasonable to suggest that sex differences influence pathophysiology of intracranial atherosclerosis, IA-associated adverse events, and outcomes of patients with IA in response to DAPT.

Methods

In this retrospective observational case-control study, we used electronic medical records provided by the University of Utah Health to gather data. We performed a retrospective chart review of approximately 375 patients, of those and identified 89 patients. We extracted data documenting sex, age, follow-up appointments for their DAPT initiation (no longer than six months from DAPT start date) and if patients had a recurrent stroke or major bleed. For raw demographic data, including age and sex, we will use descriptive statistics in the form of means, standard deviations, and percentages.

Results

Overall, a difference in the number of outcomes between men and women was detected. Although we had a low frequency of outcomes, we did see that more women had recurrent stroke whereas men have more major bleeding events. Men, making up (n=50) 56% of the total patients, had six major bleeding events and four recurrent stroke or TIA. Women (n=39), when compared to men, had more recurrent strokes (n=6) and fewer major bleeding events (n=4).

Conclusion

We expected a difference in major bleed and stroke rates between men and women with intracranial atherosclerosis and treated with dual antiplatelet therapy for secondary stroke prevention. While we see a difference in raw data, we are unable to say if an actual difference. Our study highlights the need for more data in this area of DAPT in IA.

Recommend0 recommendationsPublished in College of Pharmacy, Virtual Poster Session Spring 2021

Responses

  1. Nice work, Pressley. Sorry you didn’t have more data to analyze. What was the most important lesson about doing observational research like this? What would you do differently next time?

    1. I learned two valuable lessons here, the first being to allow yourself for a lot more time than you think you will need for chart reviews and data analysis. The second being to be critical of your initial data pool provided. We ended up with a very small dataset because I believe our initial pool may not have been pulled correctly in epic to maximize the number of eligible patients. Great question! Thanks for stopping by and all your help up to this point with my project!

  2. Presley – I am not familiar with stroke/TIA much and wonder if you can help me understand the reason behind the hypothesis that you expect on the differences based on sex. Look forward to hearing more on that. Thanks.

    1. Thanks for stopping by and an excellent question! Numerous studies demonstrate sex differences in various disease states, including those that directly impact IA and its pathogenesis. To sum it up we know some cardiovascular risk factors differ by gender. The risk of stroke increases with age, and at younger ages, men are more likely than women to have strokes. We know that women who smoke are more likely to have a heart attack than male smokers. Ischemic heart disease (IHD) develops at a later age for women compared to men; however, rates of IHD have been increasing among younger women. For other risk factors like hypertension and dyslipidemia, rates are higher in premenopausal women than in men. These are only a few that we know of but DAPT efficacy and safety have never been evaluated on a sex/gender basis.

  3. I love this topic! I wish I would have known this was your topic – the poster would be a great submission for the conference on sex and gender in health that is coming up virtually at the U – if you are interested – we may be able to get the organizers to let you submit!!! just contact me if you want. I dont’ think it would be too much work.

    1. Wow really?! I would love that. Are you able to email the details, and I will see if this is doable? Also, thanks for taking the time to check out my poster.

      1. I sent the announcement to your email. Leanne has been very nice about flexing the due date 🙂

  4. Presley, nicely done. While your data-set is limited and the results, therefore, preliminary, the findings are provocative and provide a basis for moving the research forward to determine whether the differences hold up. You findings also lay important ground work for completing necessary power analyses to be able to design the experiment to really address the question. I’m curious what you see as the biggest limitation to increasing sample size/being able to complete a fully powered study?

    1. I believe the biggest limitation was not being critical or general enough at the initial stage of working with the data warehouse for EPIC to get our initial pool of applicants. Our data may not have been pulled correctly in epic to maximize the number of eligible patients. I also realize that many patients with IA (and same underlying risk factors) have also undergone other major stenting or CV events requiring DAPT that skewed our data.

    2. Also, thank you for your help throughout this process and all your support! I appreciate the time you take with us and developing our ideas!

  5. Presley – Congratulations on an interesting poster!! What are two things you learned in doing this project? Any potential future work that you would suggest in terms of looking at minority individuals?

    1. I learned two valuable lessons here, the first being to allow yourself for a lot more time than you think you will need for chart reviews and data analysis. The second being to be critical of your initial data pool provided. We ended up with a very small dataset because I believe our initial pool may not have been pulled correctly in epic to maximize the number of eligible patients. I have not seen (or heard of any potential studies looking at minority groups) but when you take into account the risk factors impacting these groups it poses an interesting question. Thank you for taking the time to look at my work, it means a lot that you stopped by (virtually). I hope you are well and say hi to Jerry for me!

  6. Presley, thank you for sharing your work on this important topic. There are so many variables to consider here -including drug interactions, smoking and adherence – which you considered. Any additional thoughts about duration of therapy and risk for bleeding? Thank you so much for this excellent poster!

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