Abstract
Background and Objectives
Hypothyroidism affects 4.6% of the US population, with incidence increasing in recent years. Systemic effects of hypothyroidism include increased serum cholesterol, endothelial dysfunction, and hypertension, which are widely recognized risk factors for stroke. To better understand the prognostic value of thyroid hormone levels in acute ischemic stroke (AIS), this population-based, cross-sectional study aims to examine the clinical outcomes of patients with AIS with hypothyroidism.
Methods
The National (Nationwide) Inpatient Sample was queried from 2016 to 2020 for patients with AIS with a diagnosis of hypothyroidism using International Classification of Disease Ninth and Tenth Revision diagnostic codes. patients with AIS with and without hypothyroidism were assessed for baseline clinical characteristics, interventions, complications, and clinical outcomes. Propensity score matched analysis (1:1) was conducted to control for possible confounding variables.
Results
Of 2,946,195 patients with AIS identified, 388,235 (13.2%) had a concurrent diagnosis of hypothyroidism. After propensity-score matching, hypothyroidism patients were more likely to experience discharge home (odds ratio (OR) = 0.70; p < 0.01), shorter length of stay (LOS) (4.93 vs. 5.19 days; p < 0.01), and lower rates of inpatient death (OR = 0.80; 95% CI: 0.76–0.84; p < 0.01), compared to patients without hypothyroidism.
Conclusions
This retrospective analysis found that patients with hypothyroidism had shorter inpatient LOS, improved discharge disposition, and lower rates of mortality, suggesting that low thyroid hormone levels may be protective in outcomes of AIS. With the rising prevalence of hypothyroidism in the US population, it is increasingly important to investigate its potential effects on patients with cerebrovascular disease.
Keywords: Acute ischemic stroke, hypothyroidism, stroke outcomes, thyroid hormone
Introduction
Hypothyroidism affects approximately 4.6% of the US population and is more common in women of advanced age.1,2 In recent years, the number of patients diagnosed with hypothyroidism has been steadily rising. 3 Symptoms are generally nonspecific and include fatigue, weakness, and cold intolerance. 1 Systemic effects of hypothyroidism include increased serum lipids, specifically low-density lipoprotein (LDL), as well as endothelial dysfunction, hypercoagulability, inflammation, and hypertension. 4 Critically, these physiological changes are well-established risk factors for atherosclerotic disease and stroke.5,6 Despite the reported elevated risk, the connection between hypothyroidism and the development of cerebrovascular disease remains unclear.
Several retrospective and prospective studies have suggested an association between abnormal thyroid hormone levels and acute ischemic stroke (AIS) severity, but with varying results. A previous prospective study found that lower fT3 levels were associated with greater neurological impairment and higher mortality. 7 Other retrospective observational studies have also determined that lower T3 levels at admission were significantly and independently associated with higher risk of poor functional outcomes after ischemic stroke.8,9 On the contrary, some studies suggest a protective effect of hypothyroidism in patients experiencing AIS. A previous meta-analysis found that patients with subclinical hypothyroidism had lower Modified Rankin Scores after AIS, while patients with low initial fT3 had worse outcomes at discharge. 10 A large-cohort retrospective study found that patients with AIS with hypothyroidism had higher Glasgow Coma Scale scores, and better outcomes at 1-year follow up. 11
Given the high prevalence of thyroid disorders in the general population and the conflicting evidence in the literature regarding the link between thyroid hormone levels and stroke prognosis, it is imperative for the medical community to develop a robust understanding of the associations between hypothyroidism and AIS. This population-based, cross-sectional study aims to examine the clinical outcomes of patients with AIS with hypothyroidism.
Methods
Data source
Data was obtained from the National (Nationwide) Inpatient Sample (NIS), which contains information from nonfederal hospital admissions. This database is part of the Healthcare Cost and Utilization Cost Project (HCUP) and includes approximately 7 million hospital visits per year. It allows for consistent reproduction of national estimates on many different parameters, including patient demographics, diagnoses, hospital information, procedures, outcomes, and discharge disposition of patients.
Standard protocol approvals, registrations, and patient consents
The NIS is an HCUP database which conforms to the definition of a limited dataset. A limited dataset is healthcare data in which 16 direct identifiers, specified in the Privacy Rule, have been removed. Under the Health Insurance Portability and Accountability Act, review by an institutional review board is not required for use of limited datasets. All data abstractors included on this project signed an HCUP Data Use agreement, which outlines the proper use of datasets, in order to maintain the privacy rights of the individuals and institutions featured in the data. This retrospective study was reported in accordance with the STROBE guidelines for observational research.
Patient selection and cohort development
The study sample was identified using the International Classification of Diseases Ninth (ICD-9-CM) and Tenth (ICD-10-CM) Revision diagnostic and procedural codes during the period between 2016 and 2020. Patients who experienced an AIS were identified using ICD-9-CM 433 and 434, and ICD-10-CM I63. Subgroup analysis was conducted for patients with a definitive hypothyroidism diagnosis (ICD E03).
Baseline demographic, clinical characteristics, and clinical endpoints
Baseline characteristics included patient age, gender, race, hypertension, obesity status, hyperlipidemia, long-term anticoagulant use, diabetes, atrial fibrillation, smoking, anticoagulant use, and long-term steroid use. Patient symptoms that were examined included aphasia, hemiplegia, mechanical ventilation, cerebral edema, and cerebral herniation. AIS severity score was determined using the National Institute of Health Stroke Scale (NIHSS) as a template. Interventions that were analyzed included tissue plasminogen activator (tPA), endovascular therapy, and both tPA and endovascular therapy.
The clinical endpoints of this study included in-hospital death, length of stay (LOS), and functional outcome. Good functional outcome was defined as routine discharge or discharge to a short-term facility. Poor functional outcome, a surrogate measure of moderate to severe neurological disability, was defined as all other discharge dispositions.
Statistical analyses
Data management and statistical analyses were performed using Statistical Package for the Social Sciences (SPSS) (IBM SPSS Statistics 27; Armonk, NY). Statistical significance was set at alpha < .05. Dichotomous variables were assessed for significance and descriptive data were analyzed for comparison using Pearson's chi-squared test. Continuous variables were computed using independent samples t-test. Binary logistic regression models were created to investigate the adjusted, independent association baseline patient characteristics and clinical outcomes from the univariate analysis. In the first branch of this analysis, patients with hypothyroid AIS were compared to patients with nonhypothyroid AIS. In the second branch of the analysis, 1:1 propensity score-matched cohorts were created to control for possible confounding variables, including age, gender, race, insurance status, income status, comorbidities (hypertension, obesity, hyperlipidemia, diabetes mellitus, atrial fibrillation, smoking status, anticoagulant/antiplatelet use, long-term steroid use), and NIHSS score.
Data availability statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Results
Baseline demographics and comorbidities
Between 2016 and 2020, 2,946,195 patients were diagnosed with AIS, of which 388,235 (13.20%) had a concurrent diagnosis of hypothyroidism. Patients with AIS with hypothyroidism were older (75.95 years old vs. 68.95 years old; p < 0.01), more likely to be female (odds ratio (OR) = 2.94; p < 0.01), and Caucasian (OR = 2.16; p < 0.01), compared to their nonhypothyroid AIS counterparts. Hypothyroid patients were more likely to have hyperlipidemia (OR = 1.23; p < 0.01) and atrial fibrillation (OR = 1.53; p < 0.01), but less likely to have hypertension (OR = 0.91; p < 0.01), obesity (OR = 0.94; p < 0.01), and diabetes (OR = 0.94; p < 0.01). They were also more likely to be on anticoagulants (OR = 1.18; p < 0.01) and long-term steroid therapy (OR = 1.45; p < 0.01; Table 1).
Table 1.
Baseline clinical characteristics, symptoms and severity, interventions, and outcomes of patients with AIS stratified by thyroid status.
| No hypothyroidism N = 2,557,960 (86.8%) |
Hypothyroidism N = 388,235 (13.2%) |
OR | p-Value | |
|---|---|---|---|---|
| Baseline demographic and clinical characteristics | ||||
| Age (mean years) | 68.95 ± 14.35 | 75.95 ± 12.28 | <0.01 | |
| Age > 65 | 1,572,985 (61.5%) | 314,600 (81.0%) | 2.68 (2.65–2.70) | <0.01 |
| Female | 1,189,700 (46.5%) | 279,070 (71.9%) | 2.94 (2.92–2.96) | <0.01 |
| Caucasian | 1,641,350 (64.2%) | 308,420 (79.4%) | 2.16 (2.14–2.18) | <0.01 |
| Hypertension | 1,437,735 (56.2%) | 209,375 (53.9%) | 0.91 (0.91–0.92) | <0.01 |
| Obesity | 214,470 (8.4%) | 30,775 (7.9%) | 0.94 (0.93–0.95) | <0.01 |
| Hyperlipidemia | 1,252,575 (49.0%) | 209,825 (54.%) | 1.23 (1.22–1.23) | <0.01 |
| Diabetes mellitus | 966,120 (37.8%) | 140,650 (36.2%) | 0.94 (0.93–0.94) | <0.01 |
| Atrial fibrillation | 601,370 (23.5%) | 124,090 (32.0%) | 1.53 (1.52–1.54) | <0.01 |
| Smoking | 521,145 (20.4%) | 39,105 (10.1%) | 0.44 (0.43–0.44) | <0.01 |
| Anticoagulation/antiplatelet | 853,925 (33.4%) | 144,545 (37.2%) | 1.18 (1.18–1.19) | <0.01 |
| Long-term steroid therapy | 19,755 (0.8%) | 4340 (1.1%) | 1.45 (1.41–1.50) | <0.01 |
| Symptoms and severity | ||||
| Aphasia | 522,190 (20.4%) | 84,185 (21.7%) | 1.08 (1.07–1.09) | <0.01 |
| Hemiplegia | 1,064,210 (41.6%) | 154,535 (39.8%) | 0.93 (0.92–0.94) | <0.01 |
| Mechanical ventilation | 93,515 (3.7%) | 9150 (2.4%) | 0.65 (0.62–0.65) | <0.01 |
| Cerebral edema/herniation | 148,500 (5.8%) | 15,925 (4.1%) | 0.69 (0.68–0.71) | <0.01 |
| NIHSS > 15 (moderate to severe stroke) | 100,160 (3.9%) | 15,440 (4.%) | 1.02 (1.00–1.03) | 0.03 |
| Interventions | ||||
| tPA | 285,095 (11.1%) | 42,215 (10.9%) | 0.97 (0.96–0.98) | <0.01 |
| Endovascular therapy | 148,405 (5.8%) | 20,195 (5.2%) | 0.89 (0.88–0.90) | <0.01 |
| tPA and endovascular therapy | 41,390 (1.6%) | 5535 (1.4%) | 0.88 (0.86–0.91) | <0.01 |
| Clinical Outcomes | ||||
| Discharge home | 915,705 (35.8%) | 109,450 (28.3%) | 0.70 (0.70–0.71) | <0.01 |
| Inpatient death | 118,095 (4.6%) | 16,390 (4.2%) | 0.91 (0.90–093) | <0.01 |
| LOS | 5.53 ± 7.91 | 4.93 ± 5.54 | <0.01 | |
LOS: length of stay; OR: odds ratio; tPA: plasminogen activator.
Severity, complications, and interventions
Patients with hypothyroid AIS were more likely to experience aphasia (OR = 1.08; p < 0.01), but less likely to have hemiplegia (OR = 0.93; p < 0.01), and cerebral edema (OR = 0.69; p < 0.01). They were also less likely to require mechanical ventilation (OR = 0.65; p < 0.01). Further examination of interventions demonstrated that patients with hypothyroid AIS were less likely to receive tPA (OR = 0.97; p < 0.01), endovascular therapy (OR = 0.89; p < 0.01), or a combination of both (OR = 0.88; p < 0.01).
Clinical outcomes
Patients with AIS-hypothyroidism had worse rates of discharge home (OR = 0.70; p < 0.01), but lower rates of inpatient death (OR = 0.91; p < 0.01), and shorter LOS (4.93 vs. 5.53 days; p < 0.01). However, after propensity-score matching, patients with AIS-hypothyroidism were more likely to experience routine discharge home (OR = 1.03; p < 0.01), lower rates of inpatient death (OR = 0.80; 95% CI: 0.76–0.84; p < 0.01), and shorter LOS (4.93 vs. 5.19 days; p < 0.01; Table 2).
Table 2.
Clinical outcomes of AIS in hypothyroidism after propensity score matching.
| No hypothyroidism N = 77,646 |
Hypothyroidism N = 77,646 |
OR | p-Value | |
|---|---|---|---|---|
| Discharge home | 21,422 (27.6%) | 21,890 (28.2%) | 1.03 (1.01–1.05) | <0.01 |
| Discharge to rehabilitation facility | 38,340 (49.4%) | 38,181 (49.2%) | 0.99 (0.97–1.01) | 0.21 |
| Inpatient death | 4060 (5.2%) | 3278 (4.2%) | 0.80 (0.76–0.84) | <0.01 |
| LOS | 5.19 ± 6.31 | 4.93 ± 5.54 | <0.01 |
*Propensity Score Match controlled for: age, female, Caucasian, Medicaid, Q1 median income, hypertension, obesity, hyperlipidemia, diabetes mellitus, atrial fibrillation, smoking, AC/AP, long-term steroid use, NIHSS > 15.
AIS: acute ischemic stroke; LOS: length of stay; OR: odds ratio.
Discussion
This retrospective study of 388,235 patients with AIS with hypothyroidism demonstrated that patients with AIS with hypothyroidism experienced a decreased likelihood of poor functional outcomes, compared to their nonhypothyroid counterparts (after propensity score matching). With baseline demographics, hypothyroidism was strongly associated with female sex, older age, and Caucasian race. This is consistent with the epidemiology of hypothyroidism, which predominantly affects females and older patients. 1 These demographic factors may explain the variation in outcome differences. Although older patients typically experience worse stroke outcomes, AIS-hypothyroid patients’ decreased complication rates suggest a more complex interaction of factors beyond age alone. 12
Thyroid dysfunction worsens multiple conditions, including cardiovascular, cerebral, and endocrine abnormalities. 6 Research has shown that this is linked to an increased inflammatory state and oxidative stress associated with thyroid hormonal changes, which aggravate chronic conditions. 13 Elevated inflammation and endothelial damage compromise blood vessel integrity, further worsening these conditions. 4 Hypothyroidism has been associated with elevated levels of total cholesterol, LDL, and triglycerides, contributing to an increased risk of metabolic disorders in this population.14,15 Consistent with previous literature, this study found that hypothyroid patients had a higher prevalence of hyperlipidemia.4,16 However, this study also found that patients with AIS with hypothyroidism experienced fewer adverse outcomes. These patients may be on lipid-lowering agents, which could reduce the number of adverse events. Patients with hypothyroidism have reduced sensitivity to adrenergic stimulation, which may display a protective mechanism in stroke outcomes due to neuronal resilience and a decreased response to acute stress. 17 Thus, while patients with hypothyroid AIS may be at a higher risk of stroke due to their cardiovascular profile, certain protective factors may lead to better clinical outcomes for these patients.
Hypothyroidism is suggested to be associated with an increased coagulable state due to altered homeostasis, which may result in an increased risk for thromboembolic events. 18 However, our cohort of patients with hypothyroid AIS demonstrated a higher percentage of aphasia but fewer complications of cerebral edema and hemiplegia. This may be partly attributed to our finding that patients with AIS with hypothyroidism were more likely to be on anticoagulants, which supports the notion that anticoagulants have the potential to partially mitigate the severity of AIS.
The difference in baseline characteristics of the AIS-hypothyroidism cohort suggests a different metabolic profile and that these older, patients with hypothyroid AIS do not share all of the traditional stroke risk factors. Our study's patients with AIS with hypothyroidism were more likely to have atrial fibrillation and hyperlipidemia, both of which are known risk factors for stroke and are conditions that may amplify the risk of AIS in hypothyroid patients, complicating management strategies. 19 However, patients with hypothyroid AIS were less likely to have hypertension, obesity, and diabetes, which are strong predictors of poor outcomes in stroke patients. 19 The management of comorbidities may also be contributing to the differences in outcomes.
The primary limitation of this study is its cross-sectional design, which does not allow for surveillance of longitudinal outcomes occurring after hospitalization. Additionally, patients with hypothyroid AIS had differing comorbidities from patients with nonhypothyroid AIS. Although age was controlled for in the analysis, the impact of hypothyroidism on AIS in various age groups should be further analyzed. Furthermore, due to the nature of the NIS database, a hypothyroid diagnosis code does not allow for distinguishing of patients being treated with levothyroxine, what T4 levels patients have, and if the hypothyroidism is related to treatment of hyperthyroidism. Despite these limitations, this study highlights a clinically significant relationship between hypothyroidism, AIS severity, and clinical outcomes that is important for physicians to consider in their clinical care and management of patients with hypothyroid AIS.
Conclusions
This population-based analysis highlights significant differences in baseline characteristics, clinical severity, interventions, and outcomes between patients with AIS with and without concurrent hypothyroidism. The findings reveal that patients with AIS with hypothyroidism, despite being older and more likely to have certain comorbid conditions, experience fewer severe stroke complications. Moreover, these patients are less likely to receive standard reperfusion therapies, yet they exhibit better functional outcomes, including shorter LOS, decreased inpatient mortality, and increased discharge home. Hypothyroidism in patients with AIS presents a unique set of risks and paradoxical protective effects that influence stroke presentation, treatment, and recovery, necessitating thorough and comprehensive management to optimize patient outcomes.
Footnotes
Data availability statement: This study data can be requested from the corresponding author after completing the required procedures outlined by the Healthcare Cost and Utilization Project.
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.
ORCID iDs: Yael Weitzner https://orcid.org/0000-0002-2429-9268
Patricia Xu https://orcid.org/0000-0003-0016-6599
Ankita Jain https://orcid.org/0009-0002-4761-7828
Ariel Sacknovitz https://orcid.org/0009-0008-6236-1190
Ruaa Alsaeed https://orcid.org/0009-0007-5219-4475
Pankajavalli Ramakrishnan https://orcid.org/0000-0003-1576-2772
Chirag D Gandhi https://orcid.org/0000-0002-8423-0414
Fawaz Al-Mufti https://orcid.org/0000-0003-4461-7005
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.