Analyzing Pain Patterns in Stroke Survivors in Outpatient Clinics: A Retrospective, Cross-Sectional, Observational Study
Deniz Dishman, Catherine Gonzalez, Tia S Thomas,* Hari Kishan Indupuru,* Seokhun Kim, Charles Green,* Anjail Sharrief, Sean I Savitz* Institute for Stroke and Cerebrovascular Disease, University of Texas Health Science Center at Houston, Houston, TX, U...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Dove Medical Press
2025-07-01
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| Series: | Journal of Pain Research |
| Subjects: | |
| Online Access: | https://www.dovepress.com/analyzing-pain-patterns-in-stroke-survivors-in-outpatient-clinics-a-re-peer-reviewed-fulltext-article-JPR |
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| Summary: | Deniz Dishman, Catherine Gonzalez, Tia S Thomas,* Hari Kishan Indupuru,* Seokhun Kim, Charles Green,* Anjail Sharrief, Sean I Savitz* Institute for Stroke and Cerebrovascular Disease, University of Texas Health Science Center at Houston, Houston, TX, USA*These authors contributed equally to this workCorrespondence: Deniz Dishman, Department of Research, Cizik School of Nursing, Institute for Stroke and Cerebrovascular Disease, University of Texas Health Science Center Houston, 6901 Bertner Avenue, 580C, Houston, TX, 77030, USA, Tel +1 713-500-9940, Email Deniz.N.Dishman@uth.tmc.eduBackground: Pain is one of the most common sequelae after a stroke. Yet it is under-recognized, under-treated, and under-investigated, with no standard care guidelines for management during post-stroke recovery.Purpose: The primary objective of this study was to capture the prevalence of pain and different pain types in stroke survivors.Patients and Methods: The study included stroke survivors who completed a pre-visit telehealth review of systems instrument between March 1, 2020, and February 28, 2022. 442 out-patient subjects were identified and matched to their respective electronic health record from the incident stroke. Subjects were divided into pain and no-pain groups based on self-report of post-stroke pain. Bivariate analyses were performed to test the association between the patient’s demographic and clinical characteristics and pain using t-tests or Wilcoxon rank sum tests for continuous variables and chi-square tests for categorical variables. Random forest imputation was used to address missing values. Multivariable analysis was performed using the logistic regression method.Results: Of the 442 subjects, 58% (N=258) reported pain, with 56% experiencing multiple pain types. Musculoskeletal pain (36%), Neuropathic pain (22%), and Headaches (17%) were the most common pain types. Only 20% of patients reporting pain used analgesics, with gabapentin (43%) and opioids (11%) being the most common prescriptions. Obstructive sleep apnea (OSA), history of recreational drug use, and gender showed a significant relationship with pain in univariate analysis. In the final logistic regression model, OSA (OR: 3.37, 95% CI: 1.34– 9.80, p: 0.015) and history of recreational drug use (OR: 2.05, 95% CI: 1.16– 3.83, p: 0.018) remained significant. The model achieved moderate discrimination with an AUC of 0.62.Conclusion: Over half of stroke survivors experienced pain, with 30% reporting multiple pain types. The low rate of analgesic use (20%) and significant proportion of patients experiencing pain highlight the critical need for evidence-based pain management guidelines in post-stroke care.Keywords: stroke, post-stroke pain, neuropathic pain, musculoskeletal pain |
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| ISSN: | 1178-7090 |