Glaucoma Risk of Serotonin-norepinephrine Reuptake Inhibitors (SNRIs) and Gabapentinoids in Fibromyalgia Patients

Glaucoma Risk of Serotonin-norepinephrine Reuptake Inhibitors (SNRIs) and Gabapentinoids in Fibromyalgia Patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Glaucoma Risk of Serotonin-norepinephrine Reuptake Inhibitors (SNRIs) and Gabapentinoids in Fibromyalgia Patients Yang-Chi Lin, Ching-Chieh Lin, Ping-Hao Chiang, Jing-Yang Huang, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7502316/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objectives To evaluate the association between glaucoma risk and the use of serotonin-norepinephrine reuptake inhibitors (SNRIs) and gabapentinoids in patients with fibromyalgia (FM). Methods We conducted this retrospective cohort study by utilizing the US Collaborative Network from TriNetX database, and included newly diagnosed FM patients, categorizing them into four groups based on SNRI and gabapentinoid prescriptions. Glaucoma was set as the primary outcome, with angle-closure and open-angle subtypes being secondary outcomes in 3-year follow-up. Kaplan-Meier analyses with Cox proportional hazard model and 1:1 propensity-score matching were performed for risk comparisons. Results After propensity-score matching, we identified 37354 and 47308 patients respectively in each SNRI-related and gabapentinoid-related cohort, most of whom were White females. There was an association between the use of SNRIs [hazard ratio (HR) = 1.458, 95% confidence interval (CI): 1.184 – 1.796] and gabapentinoids (HR = 1.579, 95% CI: 1.318 – 1.892), and increased glaucoma risk compared to non-users. Additionally, SNRI users exhibited a higher glaucoma risk than gabapentinoid users (HR = 1.354, 95% CI: 1.031 – 1.777). Conclusion SNRIs and gabapentinoids increase the glaucoma risk in FM patients, with SNRI users exhibiting higher glaucoma risk than the gabapentinoid users. Health sciences/Diseases Health sciences/Medical research Health sciences/Risk factors Glaucoma Fibromyalgia Serotonin-norepinephrine reuptake inhibitors Gabapentinoids Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Fibromyalgia (FM) is a chronic pain disorder characterized by widespread musculoskeletal pain, fatigue, sleep disturbances, and depressive disorders, affecting 2% to 8% of the global population 1,2 . Management of chronic pain and associated sleep issues presents significant challenges 3 . Multidisciplinary treatment approaches for FM typically require both nonpharmacological methods, such as aerobic exercise and hypnosis, as well as pharmacological interventions, including antidepressants and anticonvulsants. The antidepressants used may include tricyclics, selective serotonin reuptake inhibitors (SSRIs) like fluoxetine and paroxetine, and norepinephrine reuptake inhibitors (SNRIs) such as duloxetine and milnacipran. Anticonvulsants frequently prescribed for FM, known as gabapentinoids, encompass pregabalin and gabapentin 1,4 . SNRIs and gabapentinoids play a role in neuropathic pain modulator in FM patients, among which duloxetine, milnacipran, and pregabalin were US Food and Drug Administration (FDA)-approved treatments. Despite their benefits in symptom relief, treatment with SNRIs and gabapentinoids is often associated with adverse effects such as nausea, headache, and dizziness 5-7 . Ocular side effects including blurred vision and amblyopia have also been documented in clinical trials involving patients on pregabalin or gabapentin 6 , 7 . Additionally, it has been demonstrated that SNRIs can precipitate acute angle-closure events by raising intraocular pressure (IOP) and inducing mydriasis 8 . Further, gabapentin usage has been associated with a 1.42-fold increased risk of acute angle-closure glaucoma (AAG) in a case-control study, and there are reports of bilateral AAG following the administration of duloxetine 9-11 . The quality of life for individuals with FM may be significantly impacted by ocular diseases 12 . Besides, research indicates that 84.1% of FM patients require more than one medication 13 . Given that glaucoma remains a leading cause of blindness worldwide, the association between FM medications and glaucoma warrants considerable attention 14 . Although some previous research has suggested a possible link between the usage of SNRIs and gabapentinoids and increased glaucoma risk, the results, when considered alongside other study findings, were conflicting, and most studies used a case-control design. Hence, we carried out this retrospective cohort study involving diverse cohorts from the United States by utilizing the US Collaborative Network from the TriNetX database, aiming to elucidate the association between the use of SNRIs and gabapentinoids and new-onset glaucoma diagnosis when compared to non-users in FM patients. Risk of glaucoma was also compared between users of SNRIs and gabapentinoids. Materials and Methods Data source The US Collaborative Network from the TriNetX database, including electronic medical records of approximately 118 million patients from over 68 healthcare organizations (HCOs), was employed for this retrospective cohort study. The de-identified data in this database adhered to Section §164.514(a) of the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule, under which the requirement to obtain informed consent is not applicable. 15 The use of this database was reviewed and granted by Chung Shan Medical University Hospital's Institutional Review Board (IRB). All methods were carried out in accordance with relevant guidelines and regulations. We extracted patient data spanned from January 1, 2016, to November 27, 2021. The coding systems used in this study included the International Classification of Diseases (ICD), the Veterans Affairs (VA) Drug Classification System, the Anatomical Therapeutic Chemical (ATC) Classification System, and the Current Procedural Terminology (CPT) code system. The TriNetX platform has performed data harmonization process, including converging VA or ATC codes to RxNorm system 16 . Details of codes run in this study are provided in Supplementary Material – Appendix 1. Population and study design Aiming to evaluate the risk of glaucoma development in FM patients associated with the use of SNRIs and gabapentinoids, this study involved three distinct 1:1 propensity-score-matched comparisons: one between patients receiving SNRIs and those not receiving SNRIs, another between patients treated with gabapentinoids and those not treated with gabapentinoids, and the other between SNRI users and gabapentinoid users. We included patients aged 20 years and above with outpatient visit records. Among these patients, we further identified those with a newly documented fibromyalgia diagnosis (ICD-10-CM: M79.7). Subsequently, we narrowed down the selection to those with long-term use, defined as having at least one prescription recorded between 6 and 12 months after the initial prescription, of SNRIs (venlafaxine, desvenlafaxine, duloxetine, milnacipran, and levomilnacipran based on RxNorm codes) and gabapentinoids (ATC: N02BF), as well as those without any prescription records. The first prescription date of SNRIs and gabapentinoids for the medication users, and the initial diagnostic date of FM among patients without medication use, were defined as the index date. Patients with prior glaucoma-related diagnoses (ICD-10-CM: H40.1-H40.9 and H42) and procedures (based on various CPT code records, detailed in Supplementary Material, Appendix 1) on or before the index date were excluded. The detailed cohort construction process is presented in Figure 1, and it should be noted that when exploring the differences in glaucoma risk between SNRI and gabapentinoid users, patients with previous gabapentinoid prescription records in the SNRI cohort and vice versa were excluded before the analysis. Glaucoma (ICD-10-CM: H40.1, H40.2, H40.6, and H40.9) was set as our primary outcome, with open-angle glaucoma (ICD-10-CM: H40.1) and angle-closure glaucoma (ICD-10-CM: H40.2) as secondary outcomes. A 3-year follow-up period was applied in this study. To incorporate into the long-term medication usage setting and reduce possible immortal time bias, patients with outcome events occurring within the first year of follow-up were excluded from the analyses. Data extraction was done on January 7, 2025, with all analyses conducted on the same day. Propensity-score matching (PSM) The analyses were conducted both before and after 1:1 propensity-score matching (b-PSM, a-PSM). Cohorts were matched based on variables extracted from the year preceding the index date. This matching process comprised a range of attributes, including demographics, healthcare utilizations, comorbidities, and medication records, with a focused consideration of potential and relatively common confounders linked to glaucoma development 17 . Demographic matching criteria included age, sex, and ethnic backgrounds such as White, Black or African American, and Asian. Matched records of healthcare utilization patterns consisted of inpatient, outpatient, and emergency visits. Comorbidities considered for matching comprised primary hypertension, diabetes mellitus, dyslipidemia, overweight and obesity, migraine, obstructive sleep disorder, rheumatoid arthritis, systemic lupus erythematosus, insomnia, arterial and capillary diseases, chronic kidney diseases. Medications for matching involved corticosteroids, antihistamines, anticholinergics, SSRIs, and tricyclic antidepressants. Additionally, blood pressure records were also included in the matching. The codes used for the aforementioned characteristics are detailed in Supplementary Material – Appendix 1. This study was carried out adhering to Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline. Primary analysis The primary analysis investigated whether SNRIs, and gabapentinoids, respectively increase glaucoma risk in FM patients, compared to non-users, and explored whether SNRI and gabapentinoid users exhibit a different risk of glaucoma and its subtypes. The outcome measurements were carried out both b-PSM and a-PSM. Subgroup analysis In subgroup analysis, we aimed to explore whether several relatively common comorbidities and important covariates in glaucoma development affect glaucoma risk difference between SNRI and gabapentinoid users. For demographic data, sex (female or male), age (20–39, 40–59, and >59 years), and ethnicity (White, Black or African American, and others) were stratified and adjusted. Concerning the comorbidities, subgroups with primary hypertension, diabetes mellitus, and dyslipidemia were examined based on records in the year prior to the index date, and analyses were adjusted accordingly. Regarding medication use, adjusted groups were established according to prescription records of corticosteroids, antihistamines, or SSRIs, and analyses were adjusted accordingly. All analyses of outcomes were performed after PSM with associated heterogeneity assessments. Sensitivity analysis The sensitivity analysis was performed to further compare the glaucoma risk between SNRI and gabapentinoid users by applying two analytic strategies with different prescription methodologies, which were the modified per-protocol (MPP) and time-restricted treatment (TRT) strategies. The former consisted of patients without drug switching records between SNRI and gabapentinoids, and the latter comprised patients with corresponding prescription records limited to a maximum duration of 2 years. The analyses were conducted both b-PSM and a-PSM. Statistical analysis We performed 1:1 propensity score matching using a greedy nearest-neighbor algorithm with a caliper of 0.1 standard deviations of the pooled logit of the propensity score. The baseline characteristics between the two matched cohorts were assessed for comparability using the standardized mean difference (SMD). An SMD below 0.1 indicated comparable groups 18 . To evaluate the 3-year risk of glaucoma-related diagnosis, Kaplan-Meier analyses were conducted, with results expressed as cumulative probabilities and presented as hazard ratios (HRs) and 95% confidence intervals (95% CI) within the Cox proportional hazard model. The statistical significance of the Kaplan-Meier survival curves was determined using log-rank tests, with a significance threshold set at a p-value of 0.05. Cochran’s Q tests were performed for heterogeneity assessments of the outcome measurement results in subgroup analysis, with the significance threshold for the p-values consistently set at 0.05 to maintain uniformity in statistical evaluation. Results Baseline characteristics The SSRI, non-SSRI, gabapentinoid, and non-gabapentinoid cohorts respectively encompassed 39954, 249254, 61163 and 209453 patients. The majority of patients in each cohort were female [(users vs. non-users) SNRIs: 85.2% vs. 72.9%; gabapentinoids: 80.7% vs. 72.6%], and the mean ages at index were around their fifties (SNRIs: 51.8 ± 13.7 vs. 52.2 ± 15; gabapentinoids: 52.8 ± 13.6 vs. 51.4 ± 15.1). The most prevalent comorbidity was primary hypertension, followed by dyslipidemia, diabetes mellitus, and overweight and obesity. Most frequently used medications conceivably linked to glaucoma risk were corticosteroids and antihistamines, followed by SSRIs. After PSM, SNRI-related cohorts each comprised 37354 patients and gabapentinoid-related cohorts each consisted of 47308 patients, with all characteristics comparable as all SMDs fell below 0.1 a-PSM. Details of characteristics both b-PSM and a-PSM in the primary analysis are provided in Table 1. It should be noted that small proportion of patient data may be incomplete during processing, while it was not incorporated into the analyses and the actual number of analyzed patients are showed in the figures. Primary analysis The outcome measurement results in the primary analysis respectively revealed an association between increased glaucoma and open-angle glaucoma risk, and the use of SNRIs, and gabapentinoids. When comparing the glaucoma risk in SNRI users with their non-users, there were respectively 240 and 907 patients developing glaucoma during the follow-up period. The HRs were 1.409 (95% CI: 1.222-1.624) b-PSM and 1.458 (95% CI: 1.184-1.796) a-PSM. Concerning that of gabapentinoid users compared with the non-users, there were 378 and 610 patients developing glaucoma. The HRs were 1.759 (95% CI: 1.548-2) b-PSM and 1.579 (95% CI: 1.318-1.892) a-PSM. As for comparing risk of angle-closure glaucoma in medication-users versus with non-users, SNRI-associated comparison revealed HR of 1.335 (95% CI: 0.758-2.351) b-PSM and 2.135 (95% CI: 0.828-5.502) a-PSM, and that gabapentinoid-associated comparison showed HR of 1.283 (95% CI: 0.746-2.206) b-PSM and 0.752 (0.384-1.475) a-PSM. Regarding risk of open-angle glaucoma, the use of SNRIs and gabapentinoids also respectively increased the risk with significance [(SNRI: b-PSM) HR = 1.291, 95% CI: 1.035-1.610; (SNRI: a-PSM) HR = 1.458, 95% CI: 1.052-2.02; (gabapentinoid: b-PSM) HR = 1.458, 95% CI: 1.193-1.781; (gabapentinoid: a-PSM) HR = 1.401, 95% CI: 1.061-1.848]. It should be noted that outcome events for glaucoma subtypes were limited by relatively small sample sizes, resulting in wide 95% CIs; therefore, these findings should be interpreted with caution. Concerning the comparisons between SNRI and gabapentinoid users, no significant differences in glaucoma-related risk was observed b-PSM, upon which the HRs of glaucoma and its angle-closure and open-angle subtypes were 0.948 (95% CI: 0.765-1.174), 1.092 (95% CI: 0.487-2.449), and 1.083 (95% CI: 0.774-1.515). Conversely after propensity-score matching, there were associations between the use of SNRIs and increased risk of glaucoma (HR = 1.354, 95% CI: 1.031-1.777) and open-angle subtypes (HR = 1.732, 95% CI: 1.105-2.715), when compared to gabapentinoid usages. Similarly, relatively small sample sizes with wide 95% CIs were observed in outcome events of glaucoma subtypes. The outcome measures for glaucoma are presented in Figure 2, while those for its subtypes are provided in Supplemenatry Material – Appendix 2. Additionally, the cumulative probability curves for glaucoma are shown in Figure 3. Subgroup analysis Among all outcome measurement results, consistent findings with the primary analysis were observed only in subgroup adjustments involving females, individuals aged 40–59 years, and ethnicity of White, and Black or African American, and patients without hypertension, diabetes mellitus, or dyslipidemia, as well as those receiving corticosteroids, SSRIs, and either with or without antihistamine treatments. Conversely, the subgroups of patients with hypertension or diabetes mellitus demonstrated findings that were markedly divergent from the primary analysis, revealing benefits from SNRIs [(hypertension) HR = 0.565, 95% CI: 0.361-0.884; (diabetes mellitus) HR = 0.544, 95% CI: 0.277-1.068] along with significant heterogeneity [(Cochran’s Q-test p-value) hypertension: 0.002; diabetes mellitus: 0.046]. The outcome measurement results are displayed in Figure 4, with detailed Cochran’s Q-test results for heterogeneity assessments provided in Supplementary Material – Appendix 3. Sensitivity analysis Concerning MPP analytic strategy, the SNRI cohort included 7948 and the gabapentinoid cohort consisted of 20243 patients b-PSM. 7946 patients were identified in both cohorts a-PSM. No significant findings were observed both b-PSM [(glaucoma) HR = 0.894, 95% CI: 0.660-1.209; (angle-closure glaucoma) HR = 1.078, 95% CI: 0.279-4.170; (open-angle glaucoma) HR = 1.066, 95% CI: 0.668-1.702] and a-PSM [(glaucoma) HR = 1.079, 95% CI: 0.709-1.643; (angle-closure glaucoma) HR = 2.013, 95% CI: 0.182-22.195; (open-angle glaucoma) HR = 1.821, 95% CI: 0.841-3.945]. The findings were only partially consistent with those in the primary analysis, coupled with wide 95% CIs resulted from relatively small patient sizes, caution should be taken when interpreting the results. Regarding TRT analytic strategy, the SNRI cohort encompassed 6648 and the gabapentinoid cohort consisted of 11744 patients b-PSM. 6612 patients were identified in both cohorts a-PSM. There were also no significant findings observed both b-PSM [(glaucoma) HR = 1.343, 95% CI: 0.885-2.040; (angle-closure glaucoma) HR = 0.552, 95% CI: 0.111-2.735; (open-angle glaucoma) HR = 1.090, 95% CI: 0.579-2.052] and a-PSM [(glaucoma) HR = 1.198, 95% CI: 0.742-1.943; (angle-closure glaucoma) HR = 0.160, 95% CI: 0.019-1.326; (open-angle glaucoma) HR = 1.003, 95% CI: 0.496-2.029]. Likewise, the results were not completely consistent with those in the primary analysis. The outcome measures for glaucoma are presented in Figure 5, while those for its subtypes are provided in Supplemenatry Material – Appendix 4. Discussion Association between neuropathic pain modulators and glaucoma risk This retrospective cohort study suggests a possible link between the use of SNRIs and gabapentinoids and an increased risk of glaucoma and its subtypes in FM patients. Besides, the users of SNRIs may exhibit higher glaucoma risk than the gabapentinoid users. However, results in the subgroup analysis and sensitivity analysis showed limited consistency, suggesting that the observed higher glaucoma risk among SNRI users should be interpreted with caution. In addition, when assessing the risk of glaucoma subtypes, we observed small sample sizes and wide 95% CIs, particularly for angle-closure glaucoma. This may partly explain the limited consistency observed in the results. Mechanistic insights into SNRI-associated glaucoma risk SNRIs theoretically have the potential to increase the risk of glaucoma by affecting the concentration of serotonin, norepinephrine, and dopamine. These medications exert serotonergic effects on 5HT7 receptors, leading to pupil dilation and increased aqueous humor production 8,19 , adrenergic effects on α1 receptors, resulting in mydriasis and eyelid retraction, as well as effects on α2 receptors that enhance aqueous humor outflow capacity 20 . Additionally, dopaminergic effects on vascular dopamine (DA1) receptors have been identified in ocular structures like the sclera, choroid, ciliary process, and trabecular meshwork, which are suggested to be associated with and AAG 21 . There have been several case reports of AAG in individuals using duloxetine and venlafaxine 10,11,22-24 , and a meta-analysis that included six case-control studies and one cohort study suggested that SSRIs were not linked to an increased risk of glaucoma (k=7, pooled adjusted odds ratio (pAOR)=0.956, 95% CI: 0.807-1.133, p = 0.604) 25 . Furthermore, patients exposed to both SSRIs and SNRIs even exhibited lower IOP (k=4, Hedges' g = -0.519, 95% CI: -0.743 to -0.296, p < 0.001). However, it is essential to note that there was considerable heterogeneity among the studies included in this analysis. Mechanistic insights into SNRI-associated glaucoma risk Conversely, the mechanisms underlying glaucoma development associated with gabapentinoids have received limited attention. Browne MJ et al.'s case-control study findings suggested an increased risk of AAG with gabapentin use, whereas pregabalin use did not show a similar association 26 . Although there have been studies demonstrating GABAergic influences on AAG development 27-30 , these findings could be only partially applicable to gabapentinoids. This is because gabapentinoids do not directly impact the concentration of GABAergic neurotransmitters but instead modulate calcium influx by binding to the α2δ-1 subunit of voltage-gated calcium channels 31 . Comparison with prior studies and population-specific considerations Our study indicated a potential association between the use of SNRIs and gabapentinoids, and an increased risk of glaucoma. Our findings regarding gabapentinoids are consistent with those of Browne MJ et al.'s study 26 . However, it is crucial to emphasize that our study specifically focuses on the FM population. Regarding our findings related to SNRIs and their association with increased glaucoma risk, they diverge from the results of Özer MA et al.'s study 32 . They indicated that duloxetine did not result in clinically significant changes in FM patients, despite observing statistically significant effects on anterior chamber parameters, including IOP, central corneal thickness (CCT), corneal endothelial cell density (CECD), and anterior chamber depth (ACD). One potential explanation for this discrepancy lies in our diagnosis criteria, which were not restrictive. It relied solely on records from healthcare organizations using glaucoma-related ICD codes, without considering the specific diagnostic tools and disease severity. Nevertheless, the findings in our study still hold some significance due to the inclusion of a relatively large population. As for the results regarding glaucoma subtypes, there were relatively few outcome events during the follow-up, especially angle closure subtypes. This may be explained by the limited sensitivity over the diagnosis codes, and that patients with a predisposition to angle-closure glaucoma, such as those with a family history or narrower anterior chamber angles, may be less likely to receive these medications initially, leading to possible selection bias when observing the relation between these medication usages and angle-closure glaucoma risk. Interpretation of the subgroup analysis In the subgroup analysis, we observed that SNRI users may exhibit a lower risk of glaucoma than gabapentinoid users among FM patients with primary hypertension. This finding may be coincidental due to the relatively small sample size. However, another potential explanation could be that in patients with hypertension, the blood pressure–raising effect of SNRIs is relatively attenuated, leading to a more neutral IOP or ocular perfusion. In contrast, in individuals without hypertension, SNRIs may elevate IOP by increasing aqueous humor production through blood pressure–induced filtration. Additionally, despite the statistical insignificance, we also observed the trend suggesting that SNRI users may exhibit lower risk of glaucoma compared to gabapentinoid users in FM patients with diabetes mellitus. This could be explained by the possible selection and detection biases due to the use of SNRIs in diabetic peripheral neuropathy (with duloxetine being FDA-approved for this indication) besides coincidence resulted from relatively small sample size. These patients may already undergo regular ophthalmologic monitoring, such as diabetic retinopathy screening, with further detection and management over glaucoma thereby reducing the risk. Moreover, our findings suggesting a linkage of SNRI usage to lower glaucoma risk when compared to gabapentinoids in FM patients with primary hypertension or diabetes mellitus, aligned with those in the case-control study conducted by Chen et al. evaluating the association between the use of SSRIs and glaucoma development in patients with major depressive disorders 9 . Their study indicated that SSRI users with hypertension did not exhibit significantly higher risk of glaucoma [odds ratio (OR) = 1.09, 95% CI: 0.95-1.25], and those with diabetes mellitus also did not (OR = 1.09, 95% CI: 0.87-1.34). They hypothesized that glaucoma developments in patients with such comorbidities may be more related to the health condition instead of the SSRI usage. Nevertheless, these hypotheses warrant further studies with prospective design to confirm the cause-and-effect relationship. Strengths Strengths of this retrospective cohort study include its focus on FM patients. The comparison between SNRIs and gabapentinoids provides a reference for clinicians when making treatment decisions regarding the initiation or selection of neuropathic pain relievers in this population—a topic that has been seldom explored in previous research. Furthermore, the scarcity of retrospective cohort studies addressing this specific topic enhances the significance of this research, and it also encompassed a relatively large population for analyzing the association between medication usage and glaucoma risk Limitations This study also has several limitations that should be acknowledged. First, the severity of fibromyalgia and the underlying neuropathic pain could not be assessed, which may have influenced the choice of medications to some extent. However, since that clinical prescribing practices often rely on diagnosis rather than quantified severity, the treatment patterns observed in this study may still reflect real-world decision-making. Second, the matching of our findings regarding the angle-closure glaucoma and open-angle glaucoma subtypes may not fully reflect the actual scenario. In a recent study researched by Tran et al. evaluating polygenic risk scores (PRSs) for primary open-angle glaucoma (POAG) using ICD codes versus manual record review in the Mount Sinai BioMe and Mass General Brigham (MGB) biobanks, ICD-based POAG diagnoses showed high sensitivity (97%) but low specificity (44% in BioMe, 53% in MGB) compared to cases confirmed by optical coherence tomography and visual field assessments 33 . Another recent study conducted by Lu et al. reported that in Chang Gung Research Database, which is the largest multi-institutional healthcare system in Taiwan comprising EMRs from 9 hospitals, POAG-related ICD-10 codes exhibited relatively lower sensitivity (57.4%) but higher specificity (97.4%), and that primary angle-closure glaucoma (PACG) related ICD-10 codes demonstrate sensitivity of 73.9% and specificity of 99.4%. Besides, ICD-10 codes regarding all both the glaucoma subtypes showed relatively high sensitivity (87.0%) and high specificity (92.8%) 34 . Even though these findings could not be entirely applied to the TriNetX database, they still provided valuable insights for our interpretations. Third, whether FM plays a role as a confounding factor of glaucoma is still questionable. A study conducted by Garcia-Martin E et al. revealed that FM could lead to subclinical axonal damage in the retinal nerve fiber layer (RNFL), which possibly increase the risk of glaucoma in this patient population 35 . However, the associated cause-and-effect relationship requires more studies for confirmation. Furthermore, FM patients are often within relatively complex medical history, and hence confounding bias might exist. We already took some common confounders into consideration when PSM to mitigate such bias, while some important factors such as genetics and IOPs were unavailable with our study design in this database, and that the used diagnostic tools were also unable to confirm. In addition, the study cannot guarantee that FM diagnoses were made based on specific diagnostic criteria, and information on parameters such as the widespread pain index (WPI), symptom severity (SS) scale score, or the duration of symptoms before diagnosis was not available. Besides, the findings of this study are based on a population with FM diagnoses, so the findings should be interpreted with caution when applying them to patients with different clinical backgrounds. Moreover, details of dosage and frequency of these drugs were not available, which may introduce bias due to dose-effect, and we were unable to ascertain whether the patients continued to use the medication until the end of the follow-up. Last but not least, the US Collaborative Network from TriNetX database does not encompass the entire population-based data of the US. Hence, the findings may not fully represent the actual conditions of the US patients. Conclusion In FM patients, the use of SNRIs and gabapentinoids was potentially associated with an increased risk of glaucoma. Among these, SNRI users may exhibit a higher risk than gabapentinoid users; however, this conclusion should be interpreted with caution in patients with hypertension. Declarations Contributorship: YCL: Conceptualization, Methodology, Data curation, Formal analysis, Writing – original draft CCL: Methodology, Investigation, Writing – original draft PHC: Validation, Visualization, Writing – review & editing JYH: Software, Supervision, Writing – review & editing CBY: Supervision, Writing – review & editing YJT: Supervision, Project administration, Writing – review & editing Funding: This research received no funding from any agency. Chung Shan Medical University Hospital’s institutional review board granted the ethical approval for using the TriNetX database in this study. Data availability statement: The analyzed data in this study was extracted from the TriNetX database, which accumulates electronic health records from healthcare organizations around the world. Due to licensing and confidentiality agreements, it cannot be publicly shared. The datasets used in this study can be requested from interested researchers by contacting TriNetX (https:// trinetx.com/) in accordance with their data usage policy. Ethical statements: All methods were carried out in accordance with relevant guidelines and regulations. The requirement to obtain informed consent was waived by the Institutional Review Board of Chung Shan Medical University Hospital because the de-identified data in this database adhered to Section §164.514(a) of the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule. Patient and Public Involvement: Patients were not involved in the design, conduct, reporting, or dissemination plans of our research. YCL, CCL, PHC, JYH, CBY, and YJT declare that they have no conflict of interest. Acknowledgments The authors would like to express their sincere gratitude to professor Chin-Wen Chi, for the valuable contributions to the manuscript. His insights and expertise were instrumental in the completion of this paper. References Schmidt-Wilcke, T. & Clauw, D. J. Fibromyalgia: from pathophysiology to therapy. Nat Rev Rheumatol 7 , 518-527, doi:10.1038/nrrheum.2011.98 (2011). Jones, G. T. et al. The prevalence of fibromyalgia in the general population: a comparison of the American College of Rheumatology 1990, 2010, and modified 2010 classification criteria. Arthritis Rheumatol 67 , 568-575, doi:10.1002/art.38905 (2015). Arnold, L. M. & Clauw, D. J. Challenges of implementing fibromyalgia treatment guidelines in current clinical practice. Postgrad Med 129 , 709-714, doi:10.1080/00325481.2017.1336417 (2017). Macfarlane, G. J. et al. EULAR revised recommendations for the management of fibromyalgia. 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Use of Diagnostic Codes for Primary Open-Angle Glaucoma Polygenic Risk Score Construction in Electronic Health Record-Linked Biobanks. Am J Ophthalmol 267 , 204-212, doi:10.1016/j.ajo.2024.06.007 (2024). Lu, P. T., Tsai, T. H., Lai, C. C., Chuang, L. H. & Shao, S. C. Validation of Diagnostic Codes to Identify Glaucoma in Taiwan's Claims Data: A Multi-Institutional Study. Clin Epidemiol 16 , 227-234, doi:10.2147/clep.S443872 (2024). Garcia-Martin, E. et al. Fibromyalgia Is Correlated with Retinal Nerve Fiber Layer Thinning. PLoS One 11 , e0161574, doi:10.1371/journal.pone.0161574 (2016). Tables Table 1A. Baseline characteristics before and after propensity-score matching (SNRI vs. non-SNRI) Variables Before propensity-score matching After propensity-score matching SNRI a (n = 37388) Non-SNRI (n = 237299) SMDs b SNRI (n = 37354) Non-SNRI (n = 37354) SMDs Age at index Mean ± SD c (years) 51.8 ± 13.7 52.2 ± 15 0.029 51.8 ± 13.7 52.2 ± 14.4 0.028 Sex, No. (%) Female 31859(85.2) 173108(72.9) 0.305 31825(85.2) 32249(86.3) 0.032 Male 3069(8.2) 31434(13.2) 0.163 3069(8.2) 2965(7.9) 0.01 Ethnicity, No. (%) White 27332(73.1) 151364(63.8) 0.202 27302(73.1) 27985(74.9) 0.042 Black or African American 3489(9.3) 23548(9.9) 0.02 3486(9.3) 3266(8.7) 0.021 Asian 349(0.9) 3706(1.6) 0.057 349(0.9) 328(0.9) 0.006 Healthcare utilization, No. (%) Inpatient 4991(13.3) 23839(10) 0.103 4977(13.3) 4701(12.6) 0.022 Outpatient 27341(73.1) 171174(72.1) 0.022 27307(73.1) 26998(72.3) 0.019 Emergency 7609(20.4) 39430(16.6) 0.096 7591(20.3) 7347(19.7) 0.016 Comorbidities, No. (%) Primary hypertension 10265(27.5) 48768(20.6) 0.162 10237(27.4) 9981(26.7) 0.015 Dyslipidemia 8046(21.5) 40348(17) 0.115 8025(21.5) 7721(20.7) <0.001 Overweight and obesity 5854(15.7) 21758(9.2) 0.198 5829(15.6) 5611(15) 0.016 Diabetes mellitus 5125(13.7) 22045(9.3) 0.139 5108(13.7) 4955(13.3) 0.012 Migraine 4286(11.5) 12939(5.5) 0.217 4254(11.4) 4042(10.8) 0.018 Insomnia 3018(8.1) 7353(3.1) 0.218 2987(8) 2790(7.5) 0.02 Obstructive sleep apnea 2994(8) 10570(4.5) 0.147 2971(8) 2854(7.6) 0.012 Diseases of arteries, arterioles and capillaries 1751(4.7) 9070(3.8) 0.043 1746(4.7) 1687(4.5) 0.008 Rheumatoid arthritis with rheumatoid factor (M05) 459(1.2) 2024(0.9) 0.037 457(1.2) 439(1.2) 0.004 Other rheumatoid arthritis (M06) 1800(4.8) 6354(2.7) 0.113 1790(4.8) 1708(4.6) 0.01 Systemic Lupus Erythematosus 969(2.6) 3608(1.5) 0.076 963(2.6) 961(2.6) <0.001 Chronic kidney disease, stage 3 (N18.3) 733(2) 3762(1.6) 0.028 732(2) 706(1.9) 0.005 Chronic kidney disease, stage 4 (N18.4) 115(0.3) 820(0.3) 0.007 115(0.3) 115(0.3) <0.001 Chronic kidney disease, stage 5 (N18.5) 39(0.1) 297(0.1) 0.006 39(0.1) 31(0.1) 0.007 End stage renal disease (N18.6) 115(0.3) 989(0.4) 0.018 115(0.3) 107(0.3) 0.004 Medications, No. (%) Corticalsteroids (dermatological preparations) 14135(37.8) 59369(25) 0.278 14103(37.8) 14188(38) 0.005 Corticalsteroids for systemic use 13788(36.9) 57345(24.2) 0.279 13756(36.8) 13934(37.3) 0.01 Antihistamines for systemic use 9107(24.4) 34767(14.7) 0.247 9078(24.3) 8848(23.7) 0.014 Antihistamines for topical use 5981(16) 22224(9.4) 0.2 5955(15.9) 5731(15.3) 0.017 Anticholinergics (inhalants) 2462(6.6) 8812(3.7) 0.13 2450(6.6) 2332(6.2) 0.013 Anticholinergics (ophthalmologicals) 1617(4.3) 6668(2.8) 0.082 1611(4.3) 1567(4.2) 0.006 Anticholinergic agents (oral) 507(1.4) 1250(0.5) 0.086 505(1.4) 426(1.1) 0.019 Selective serotonin reuptake inhibitors 6675(17.9) 22511(9.5) 0.245 6650(17.8) 6719(18) 0.005 Tricyclic antidepressants 3373(9) 8760(3.7) 0.22 3350(9) 3200(8.6) 0.014 Laboratory data, No. (%) Systolic blood pressure (mean ± SD mmHg) 125 ± 17.9 (47.2) 126 ± 18 (43.7) 0.082 125 ± 17.9 (47.2) 126 ± 18 (47) 0.052 Diastolic blood pressure (mean ± SD mmHg) 75.4 ± 11.7 (47.3) 75.6 ± 11.4 (43.7) 0.02 75.4 ± 11.7 (47.2) 75.5 ± 11.6 (47) 0.01 Table 1B. Baseline characteristics before and after propensity-score matching (Gabapentinoid vs. non-gabapentinoid) Variables Before propensity-score matching After propensity-score matching Gabapentinoid (n = 48484) Non-gabapentinoid (n = 181931) SMDs Gabapentinoid (n = 47308) Non-gabapentinoid (n = 47308) SMDs Age at index Mean ± SD (years) 52.8 ± 13.6 51.4 ± 15.1 0.1 52.8 ± 13.6 53.3 ± 14.6 0.032 Sex, No. (%) Female 39105(80.7) 132108(72.6) 0.191 38046(80.4) 38401(81.2) 0.019 Male 5615(11.6) 22264(12.2) 0.02 5513(11.7) 5592(11.8) 0.005 Ethnicity, No. (%) White 33516(69.1) 114812(63.1) 0.127 32739(69.2) 33466(70.7) 0.034 Black or African American 5866(12.1) 16347(9) 0.102 5567(11.8) 5362(11.3) 0.014 Asian 562(1.2) 2931(1.6) 0.039 554(1.2) 563(1.2) 0.002 Healthcare utilization, No. (%) Inpatient 7118(14.7) 14626(8) 0.21 6525(13.8) 6205(13.1) 0.02 Outpatient 36210(74.7) 126925(69.8) 0.11 35105(74.2) 34899(73.8) 0.01 Emergency 10039(20.7) 26701(14.7) 0.159 9458(20) 9375(19.8) 0.004 Comorbidities, No. (%) Primary hypertension 14474(29.9) 32722(18) 0.281 13587(28.7) 13311(28.1) 0.013 Dyslipidemia 11148(23) 28024(15.4) 0.194 10506(22.2) 10208(21.6) 0.015 Overweight and obesity 7415(15.3) 14649(8.1) 0.227 6808(14.4) 6552(13.9) 0.016 Diabetes mellitus 7736(16) 13497(7.4) 0.268 7075(15) 6922(14.6) 0.009 Migraine 4911(10.1) 9300(5.1) 0.19 4505(9.5) 4394(9.3) 0.008 Insomnia 3607(7.4) 4831(2.7) 0.22 3122(6.6) 2937(6.2) 0.016 Obstructive sleep apnea 3754(7.7) 6743(3.7) 0.174 3367(7.1) 3200(6.8) 0.014 Diseases of arteries, arterioles and capillaries 2554(5.3) 5779(3.2) 0.104 2384(5) 2314(4.9) 0.007 Rheumatoid arthritis with rheumatoid factor (M05) 609(1.3) 1369(0.8) 0.051 563(1.2) 583(1.2) 0.004 Other rheumatoid arthritis (M06) 2388(4.9) 4279(2.4) 0.138 2168(4.6) 2108(4.5) 0.006 Systemic Lupus Erythematosus 1276(2.6) 2402(1.3) 0.094 1155(2.4) 1089(2.3) 0.009 Chronic kidney disease, stage 3 (N18.3) 1112(2.3) 2152(1.2) 0.085 1003(2.1) 948(2) 0.008 Chronic kidney disease, stage 4 (N18.4) 227(0.5) 398(0.2) 0.043 201(0.4) 198(0.4) 0.001 Chronic kidney disease, stage 5 (N18.5) 81(0.2) 142(0.1) 0.025 68(0.1) 75(0.2) 0.004 End stage renal disease (N18.6) 277(0.6) 455(0.3) 0.05 245(0.5) 228(0.5) 0.005 Medications, No. (%) Corticalsteroids (dermatological preparations) 18272(37.7) 37128(20.4) 0.388 17201(36.4) 17403(36.8) 0.009 Corticalsteroids for systemic use 17846(36.8) 35778(19.7) 0.388 16783(35.5) 16955(35.8) 0.008 Antihistamines for systemic use 11225(23.2) 21177(11.6) 0.307 10375(21.9) 10311(21.8) 0.003 Antihistamines for topical use 7379(15.2) 12902(7.1) 0.26 6717(14.2) 6618(14) 0.006 Anticholinergics (inhalants) 3340(6.9) 4599(2.5) 0.207 2940(6.2) 2788(5.9) 0.013 Anticholinergics (ophthalmologicals) 1983(4.1) 3613(2) 0.123 1791(3.8) 1720(3.6) 0.008 Anticholinergic agents (oral) 540(1.1) 674(0.4) 0.087 458(1) 437(0.9) 0.005 Selective serotonin reuptake inhibitors 7443(15.4) 12500(6.9) 0.272 6793(14.4) 6769(14.3) 0.001 Tricyclic antidepressants 3665(7.6) 4741(2.6) 0.227 3203(6.8) 3143(6.6) 0.005 Laboratory data, No. (%) Systolic blood pressure (mean ± SD mmHg) 126 ± 18.3 (48) 126 ± 17.7 (41.5) 0.013 126 ± 18.2 (47.2) 127 ± 18.2 (48.6) 0.017 Diastolic blood pressure (mean ± SD mmHg) 75.6 ± 11.8 (48) 75.8 ± 11.1 (41.5) 0.017 75.7 ± 11.8 75.6 ± 11.7 0.006 Table 1C. Baseline characteristics before and after propensity-score matching (SNRI vs. gabapentinoid) a. Serotonin-norepinephrine reuptake inhibitor (SNRI) b. Standardized mean difference (SMD) c. Standard deviation (SD) All the characteristics were balanced and comparable after propensity-score matching. Variables Before propensity-score matching After propensity-score matching SNRI (n = 17933) Gabapentinoid (n = 36866) SMDs SNRI (n = 17913) Gabapentinoid (n = 17913) SMDs Age at index Mean ± SD (years) 51.5 ± 14 52.8 ± 13.9 0.096 51.5 ± 14 51.7 ± 14 0.015 Sex, No. (%) Female 15151(84.5) 29354(79.6) 0.127 15133(84.5) 15125(84.4) 0.001 Male 1234(6.9) 4561(12.4) 0.187 1234(6.9) 1293(7.2) 0.013 Ethnicity, No. (%) White 13116(73.1) 25300(68.6) 0.099 13098(73.1) 13166(73.5) 0.009 Black or African American 1307(7.3) 4336(11.8) 0.153 1307(7.3) 1302(7.3) 0.001 Asian 151(0.8) 440(1.2) 0.035 151(0.8) 143(0.8) 0.005 Healthcare utilization, No. (%) Inpatient 1563(8.7) 4910(13.3) 0.147 1563(8.7) 1529(8.5) 0.007 Outpatient 12483(69.6) 26675(72.4) 0.061 12463(69.6) 12237(68.3) 0.027 Emergency 2835(15.8) 7411(20.1) 0.112 2835(15.8) 2728(15.2) 0.016 Comorbidities, No. (%) Primary hypertension 4141(23.1) 10114(27.4) 0.1 4133(23.1) 3994(22.3) 0.019 Dyslipidemia 3381(18.9) 7740(21) 0.054 3367(18.8) 3287(18.4) 0.011 Overweight and obesity 2227(12.4) 4916(13.3) 0.027 2213(12.4) 2154(12) 0.01 Diabetes mellitus 1837(10.2) 5454(14.8) 0.138 1837(10.3) 1773(9.9) 0.012 Migraine 1719(9.6) 3249(8.8) 0.027 1709(9.5) 1667(9.3) 0.008 Insomnia 1177(6.6) 2250(6.1) 0.019 1166(6.5) 1112(6.2) 0.012 Obstructive sleep apnea 1070(6) 2496(6.8) 0.033 1064(5.9) 1007(5.6) 0.014 Diseases of arteries, arterioles and capillaries 628(3.5) 1852(5) 0.075 628(3.5) 631(3.5) 0.001 Rheumatoid arthritis with rheumatoid factor (M05) 187(1) 477(1.3) 0.023 187(1) 173(1) 0.008 Other rheumatoid arthritis (M06) 736(4.1) 1598(4.3) 0.011 734(4.1) 707(3.9) 0.008 Systemic Lupus Erythematosus 399(2.2) 922(2.5) 0.018 399(2.2) 373(2.1) 0.01 Chronic kidney disease, stage 3 (N18.3) 239(1.3) 837(2.3) 0.071 239(1.3) 237(1.3) 0.001 Chronic kidney disease, stage 4 (N18.4) 37(0.2) 192(0.5) 0.052 37(0.2) 32(0.2) 0.006 Chronic kidney disease, stage 5 (N18.5) 11(0.1) 69(0.2) 0.036 11(0.1) 10(0.1) 0.002 End stage renal disease (N18.6) 37(0.2) 229(0.6) 0.065 37(0.2) 39(0.2) 0.002 Medications, No. (%) Corticalsteroids (dermatological preparations) 5358(29.9) 13157(35.7) 0.124 5357(29.9) 5251(29.3) 0.013 Corticalsteroids for systemic use 5284(29.5) 12816(34.8) 0.114 5282(29.5) 5188(29) 0.012 Antihistamines for systemic use 3162(17.6) 7906(21.4) 0.096 3159(17.6) 3087(17.2) 0.011 Antihistamines for topical use 1997(11.1) 5287(14.3) 0.096 1995(11.1) 1906(10.6) 0.016 Anticholinergics (inhalants) 749(4.2) 2384(6.5) 0.102 749(4.2) 726(4.1) 0.006 Anticholinergics (ophthalmologicals) 518(2.9) 1424(3.9) 0.054 517(2.9) 502(2.8) 0.005 Anticholinergic agents (oral) 156(0.9) 442(1.2) 0.033 156(0.9) 148(0.8) 0.005 Selective serotonin reuptake inhibitors 2574(14.4) 6117(16.6) 0.062 2573(14.4) 2537(14.2) 0.006 Tricyclic antidepressants 1117(6.2) 2619(7.1) 0.035 1116(6.2) 1080(6) 0.008 Laboratory data, No. (%) Systolic blood pressure (mean ± SD mmHg) 125 ± 17.4 (43.8) 126 ± 18.7 (47.1) 0.078 125 ± 17.4 (43.7) 125 ± 17.5 (41.6) 0.033 Diastolic blood pressure (mean ± SD mmHg) 75.8 ± 11.3 (43.8) 75.4 ± 12.1 (47.1) 0.04 75.8 ± 11.3 (43.7) 75.8 ± 11.6 (41.6) <0.001 Additional Declarations No competing interests reported. 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The results suggested the use of serotonin-reuptake inhibitors (SNRIs) and gabapentinoids may respectively increase the risk of glaucoma. Outcome measures concerning the glaucoma subtypes are provided in Supplementary Material – Appendix 2.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7502316/v1/7202116e087db1682d9621f8.png"},{"id":92274909,"identity":"1e32b6e6-01c7-47c0-8509-5a9a1f27d285","added_by":"auto","created_at":"2025-09-26 15:27:44","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":13244221,"visible":true,"origin":"","legend":"\u003cp\u003eCumulative probability curves of glaucoma in the primary analysis (after 1:1 propensity-score matching).\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7502316/v1/ad09ad5ab41a6ee987f1dc8c.png"},{"id":92274700,"identity":"8aba823b-5a1e-4e65-aa67-dce450a2b255","added_by":"auto","created_at":"2025-09-26 15:27:32","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2720441,"visible":true,"origin":"","legend":"\u003cp\u003eOutcome measures of glaucoma in the subgroup analysis. Limited consistency with the findings in the primary analysis was observed. Cochran’s Q test p-values regarding primary hypertension and diabetes mellitus adjustments had reached significance. Details of the heterogeneity assessment results are provided in Supplementary Material – Appendix 3.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7502316/v1/89934a31130418d4b3cd095f.png"},{"id":92274908,"identity":"c968e2ea-0a63-4743-9821-45d8d63914e0","added_by":"auto","created_at":"2025-09-26 15:27:44","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":758581,"visible":true,"origin":"","legend":"\u003cp\u003eOutcome measures of glaucoma in the sensitivity analysis. The results showed partial consistency with those in the primary analysis by exhibiting generally lower hazard ratios. Outcome measures concerning glaucoma subtypes are demonstrated in Supplementary Material – Appendix 4.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7502316/v1/019653b49d372a0d46cef92f.png"},{"id":109219740,"identity":"a84b3f6b-98ab-4457-aa6b-bd15738e3191","added_by":"auto","created_at":"2026-05-13 20:01:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":38828852,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7502316/v1/beab5396-1fa9-46e7-95b8-41ceef29b210.pdf"},{"id":92274771,"identity":"d1a81dac-2934-45ac-8b9f-8fde120d80b8","added_by":"auto","created_at":"2025-09-26 15:27:37","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1233067,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-7502316/v1/32745ff02412d0e0a7151fa7.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Glaucoma Risk of Serotonin-norepinephrine Reuptake Inhibitors (SNRIs) and Gabapentinoids in Fibromyalgia Patients","fulltext":[{"header":"Introduction","content":"\u003cp\u003eFibromyalgia (FM) is a chronic pain disorder characterized by widespread musculoskeletal pain, fatigue, sleep disturbances, and depressive disorders, affecting 2% to 8% of the global population \u003csup\u003e1,2\u003c/sup\u003e. Management of chronic pain and associated sleep issues presents significant challenges \u003csup\u003e3\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eMultidisciplinary treatment approaches for FM typically require both nonpharmacological methods, such as aerobic exercise and hypnosis, as well as pharmacological interventions, including antidepressants and anticonvulsants. The antidepressants used may include tricyclics, selective serotonin reuptake inhibitors (SSRIs) like fluoxetine and paroxetine, and norepinephrine reuptake inhibitors (SNRIs) such as duloxetine and milnacipran. Anticonvulsants frequently prescribed for FM, known as gabapentinoids, encompass pregabalin and gabapentin \u003csup\u003e1,4\u003c/sup\u003e. SNRIs and gabapentinoids play a role in neuropathic pain modulator in FM patients, among which duloxetine, milnacipran, and pregabalin were US Food and Drug Administration (FDA)-approved treatments.\u003c/p\u003e\n\u003cp\u003eDespite their benefits in symptom relief, treatment with SNRIs and gabapentinoids is often associated with adverse effects such as nausea, headache, and dizziness \u003csup\u003e5-7\u003c/sup\u003e. Ocular side effects including blurred vision and amblyopia have also been documented in clinical trials involving patients on pregabalin or gabapentin \u003csup\u003e6\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e7\u003c/sup\u003e. Additionally, it has been demonstrated that SNRIs can precipitate acute angle-closure events by raising intraocular pressure (IOP) and inducing mydriasis \u003csup\u003e8\u003c/sup\u003e. Further, gabapentin usage has been associated with a 1.42-fold increased risk of acute angle-closure glaucoma (AAG) in a case-control study, and there are reports of bilateral AAG following the administration of duloxetine \u003csup\u003e9-11\u003c/sup\u003e. The quality of life for individuals with FM may be significantly impacted by ocular diseases \u003csup\u003e12\u003c/sup\u003e. Besides, research indicates that 84.1% of FM patients require more than one medication \u003csup\u003e13\u003c/sup\u003e. Given that glaucoma remains a leading cause of blindness worldwide, the association between FM medications and glaucoma warrants considerable attention \u003csup\u003e14\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eAlthough some previous research has suggested a possible link between the usage of SNRIs and gabapentinoids and increased glaucoma risk, the results, when considered alongside other study findings, were conflicting, and most studies used a case-control design. Hence, we carried out this retrospective cohort study involving diverse cohorts from the United States by utilizing the US Collaborative Network from the TriNetX database, aiming to elucidate the association between the use of SNRIs and gabapentinoids and new-onset glaucoma diagnosis when compared to non-users in FM patients. Risk of glaucoma was also compared between users of SNRIs and gabapentinoids.\u0026nbsp;\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003e\u003cu\u003eData source\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe US Collaborative Network from the TriNetX database, including electronic medical records of approximately 118 million patients from over 68 healthcare organizations (HCOs), was employed for this retrospective cohort study. The de-identified data in this database adhered to Section \u0026sect;164.514(a) of the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule, under which the requirement to obtain informed consent is not applicable.\u003csup\u003e15\u003c/sup\u003e The use of this database was reviewed and granted by Chung Shan Medical University Hospital\u0026apos;s Institutional Review Board (IRB). All methods were carried out in accordance with relevant guidelines and regulations. We extracted patient data spanned from January 1, 2016, to November 27, 2021. The coding systems used in this study included the International Classification of Diseases (ICD), the Veterans Affairs (VA) Drug Classification System, the Anatomical Therapeutic Chemical (ATC) Classification System, and the Current Procedural Terminology (CPT) code system. The TriNetX platform has performed data harmonization process, including converging VA or ATC codes to RxNorm system \u003csup\u003e16\u003c/sup\u003e. Details of codes run in this study are provided in Supplementary Material \u0026ndash; Appendix 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003ePopulation and study design\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAiming to evaluate the risk of glaucoma development in FM patients associated with the use of SNRIs and gabapentinoids, this study involved three distinct 1:1 propensity-score-matched comparisons: one between patients receiving SNRIs and those not receiving SNRIs, another between patients treated with gabapentinoids and those not treated with gabapentinoids, and the other between SNRI users and gabapentinoid users. We included patients aged 20 years and above with outpatient visit records. Among these patients, we further identified those with a newly documented fibromyalgia diagnosis (ICD-10-CM: M79.7). Subsequently, we narrowed down the selection to those with long-term use, defined as having at least one prescription recorded between 6 and 12 months after the initial prescription, of SNRIs (venlafaxine, desvenlafaxine, duloxetine, milnacipran, and levomilnacipran based on RxNorm codes) and gabapentinoids (ATC: N02BF), as well as those without any prescription records. The first prescription date of SNRIs and gabapentinoids for the medication users, and the initial diagnostic date of FM among patients without medication use, were defined as the index date. Patients with prior glaucoma-related diagnoses (ICD-10-CM: H40.1-H40.9 and H42) and procedures (based on various CPT code records, detailed in Supplementary Material, Appendix 1) on or before the index date were excluded. The detailed cohort construction process is presented in Figure 1, and it should be noted that when exploring the differences in glaucoma risk between SNRI and gabapentinoid users, patients with previous gabapentinoid prescription records in the SNRI cohort and vice versa were excluded before the analysis. Glaucoma (ICD-10-CM: H40.1, H40.2, H40.6, and H40.9) was set as our primary outcome, with open-angle glaucoma (ICD-10-CM: H40.1) and angle-closure glaucoma (ICD-10-CM: H40.2) as secondary outcomes. A 3-year follow-up period was applied in this study. To incorporate into the long-term medication usage setting and reduce possible immortal time bias, patients with outcome events occurring within the first year of follow-up were excluded from the analyses. Data extraction was done on January 7, 2025, with all analyses conducted on the same day.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003ePropensity-score matching (PSM)\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe analyses were conducted both before and after 1:1 propensity-score matching (b-PSM, a-PSM). Cohorts were matched based on variables extracted from the year preceding the index date. This matching process comprised a range of attributes, including demographics, healthcare utilizations, comorbidities, and medication records, with a focused consideration of potential and relatively common confounders linked to glaucoma development \u003csup\u003e17\u003c/sup\u003e. Demographic matching criteria included age, sex, and ethnic backgrounds such as White, Black or African American, and Asian. Matched records of healthcare utilization patterns consisted of inpatient, outpatient, and emergency visits. Comorbidities considered for matching comprised primary hypertension, diabetes mellitus, dyslipidemia, overweight and obesity, migraine, obstructive sleep disorder, rheumatoid arthritis, systemic lupus erythematosus, insomnia, arterial and capillary diseases, chronic kidney diseases. Medications for matching involved corticosteroids, antihistamines, anticholinergics, SSRIs, and tricyclic antidepressants. Additionally, blood pressure records were also included in the matching. The codes used for the aforementioned characteristics are detailed in Supplementary Material \u0026ndash; Appendix 1. This study was carried out adhering to Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003ePrimary analysis\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe primary analysis investigated whether SNRIs, and gabapentinoids, respectively increase glaucoma risk in FM patients, compared to non-users, and explored whether SNRI and gabapentinoid users exhibit a different risk of glaucoma and its subtypes. The outcome measurements were carried out both b-PSM and a-PSM. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eSubgroup analysis\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn subgroup analysis, we aimed to explore whether several relatively common comorbidities and important covariates in glaucoma development affect glaucoma risk difference between SNRI and gabapentinoid users. For demographic data, sex (female or male), age (20\u0026ndash;39, 40\u0026ndash;59, and \u0026gt;59 years), and ethnicity (White, Black or African American, and others) were stratified and adjusted. Concerning the comorbidities, subgroups with primary hypertension, diabetes mellitus, and dyslipidemia were examined based on records in the year prior to the index date, and analyses were adjusted accordingly. Regarding medication use, adjusted groups were established according to prescription records of corticosteroids, antihistamines, or SSRIs, and analyses were adjusted accordingly. All analyses of outcomes were performed after PSM with associated heterogeneity assessments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eSensitivity analysis\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sensitivity analysis was performed to further compare the glaucoma risk between SNRI and gabapentinoid users by applying two analytic strategies with different prescription methodologies, which were the modified per-protocol (MPP) and time-restricted treatment (TRT) strategies. The former consisted of patients without drug switching records between SNRI and gabapentinoids, and the latter comprised patients with corresponding prescription records limited to a maximum duration of 2 years. The analyses were conducted both b-PSM and a-PSM.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eStatistical analysis\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe performed 1:1 propensity score matching using a greedy nearest-neighbor algorithm with a caliper of 0.1 standard deviations of the pooled logit of the propensity score. The baseline characteristics between the two matched cohorts were assessed for comparability using the standardized mean difference (SMD). An SMD below 0.1 indicated comparable groups \u003csup\u003e18\u003c/sup\u003e. To evaluate the 3-year risk of glaucoma-related diagnosis, Kaplan-Meier analyses were conducted, with results expressed as cumulative probabilities and presented as hazard ratios (HRs) and 95% confidence intervals (95% CI) within the Cox proportional hazard model. The statistical significance of the Kaplan-Meier survival curves was determined using log-rank tests, with a significance threshold set at a p-value of 0.05. Cochran\u0026rsquo;s Q tests were performed for heterogeneity assessments of the outcome measurement results in subgroup analysis, with the significance threshold for the p-values consistently set at 0.05 to maintain uniformity in statistical evaluation.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e\u003cu\u003eBaseline characteristics\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe SSRI, non-SSRI, gabapentinoid, and non-gabapentinoid cohorts respectively encompassed 39954, 249254, 61163 and 209453 patients. The majority of patients in each cohort were female [(users vs. non-users) SNRIs: 85.2% vs. 72.9%; gabapentinoids: 80.7% vs. 72.6%], and the mean ages at index were around their fifties (SNRIs: 51.8 \u0026plusmn; 13.7 vs. 52.2 \u0026plusmn; 15; gabapentinoids: 52.8 \u0026plusmn; 13.6 vs. 51.4 \u0026plusmn; 15.1). The most prevalent comorbidity was primary hypertension, followed by dyslipidemia, diabetes mellitus, and overweight and obesity. Most frequently used medications conceivably linked to glaucoma risk were corticosteroids and antihistamines, followed by SSRIs. After PSM, SNRI-related cohorts each comprised 37354 patients and gabapentinoid-related cohorts each consisted of 47308 patients, with all characteristics comparable as all SMDs fell below 0.1 a-PSM. Details of characteristics both b-PSM and a-PSM in the primary analysis are provided in Table 1. It should be noted that small proportion of patient data may be incomplete during processing, while it was not incorporated into the analyses and the actual number of analyzed patients are showed in the figures.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003ePrimary analysis\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe outcome measurement results in the primary analysis respectively revealed an association between increased glaucoma and open-angle glaucoma risk, and the use of SNRIs, and gabapentinoids. When comparing the glaucoma risk in SNRI users with their non-users, there were respectively 240 and 907 patients developing glaucoma during the follow-up period. The HRs were 1.409 (95% CI: 1.222-1.624) b-PSM and 1.458 (95% CI: 1.184-1.796) a-PSM. Concerning that of gabapentinoid users compared with the non-users, there were 378 and 610 patients developing glaucoma. The HRs were 1.759 (95% CI: 1.548-2) b-PSM and 1.579 (95% CI: 1.318-1.892) a-PSM. As for comparing risk of angle-closure glaucoma in medication-users versus with non-users, SNRI-associated comparison revealed HR of 1.335 (95% CI: 0.758-2.351) b-PSM and 2.135 (95% CI: 0.828-5.502) a-PSM, and that gabapentinoid-associated comparison showed HR of 1.283 (95% CI: 0.746-2.206) b-PSM and 0.752 (0.384-1.475) a-PSM. Regarding risk of open-angle glaucoma, the use of SNRIs and gabapentinoids also respectively increased the risk with significance [(SNRI: b-PSM) HR = 1.291, 95% CI: 1.035-1.610; (SNRI: a-PSM) HR = 1.458, 95% CI: 1.052-2.02; (gabapentinoid: b-PSM) HR = 1.458, 95% CI: 1.193-1.781; (gabapentinoid: a-PSM) HR = 1.401, 95% CI: 1.061-1.848]. It should be noted that outcome events for glaucoma subtypes were limited by relatively small sample sizes, resulting in wide 95% CIs; therefore, these findings should be interpreted with caution. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConcerning the comparisons between SNRI and gabapentinoid users, no significant differences in glaucoma-related risk was observed b-PSM, upon which the HRs of glaucoma and its angle-closure and open-angle subtypes were 0.948 (95% CI: 0.765-1.174), 1.092 (95% CI: 0.487-2.449), and 1.083 (95% CI: 0.774-1.515). Conversely after propensity-score matching, there were associations between the use of SNRIs and increased risk of glaucoma (HR = 1.354, 95% CI: 1.031-1.777) and open-angle subtypes (HR = 1.732, 95% CI: 1.105-2.715), when compared to gabapentinoid usages. Similarly, relatively small sample sizes with wide 95% CIs were observed in outcome events of glaucoma subtypes. The outcome measures for glaucoma are presented in Figure 2, while those for its subtypes are provided in Supplemenatry Material \u0026ndash; Appendix 2. Additionally, the cumulative probability curves for glaucoma are shown in Figure 3.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eSubgroup analysis\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong all outcome measurement results, consistent findings with the primary analysis were observed only in subgroup adjustments involving females, individuals aged 40\u0026ndash;59 years, and ethnicity of White, and Black or African American, and patients without hypertension, diabetes mellitus, or dyslipidemia, as well as those receiving corticosteroids, SSRIs, and either with or without antihistamine treatments. Conversely, the subgroups of patients with hypertension or diabetes mellitus demonstrated findings that were markedly divergent from the primary analysis, revealing benefits from SNRIs [(hypertension) HR = 0.565, 95% CI: 0.361-0.884; (diabetes mellitus) HR = 0.544, 95% CI: 0.277-1.068] along with significant heterogeneity [(Cochran\u0026rsquo;s Q-test p-value) hypertension: 0.002; diabetes mellitus: 0.046]. The outcome measurement results are displayed in Figure 4, with detailed Cochran\u0026rsquo;s Q-test results for heterogeneity assessments provided in Supplementary Material \u0026ndash; Appendix 3.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eSensitivity analysis\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConcerning MPP analytic strategy, the SNRI cohort included 7948 and the gabapentinoid cohort consisted of 20243 patients b-PSM. 7946 patients were identified in both cohorts a-PSM. No significant findings were observed both b-PSM [(glaucoma) HR = 0.894, 95% CI: 0.660-1.209; (angle-closure glaucoma) HR = 1.078, 95% CI: 0.279-4.170; (open-angle glaucoma) HR = 1.066, 95% CI: 0.668-1.702] and a-PSM [(glaucoma) HR = 1.079, 95% CI: 0.709-1.643; (angle-closure glaucoma) HR = 2.013, 95% CI: 0.182-22.195; (open-angle glaucoma) HR = 1.821, 95% CI: 0.841-3.945]. The findings were only partially consistent with those in the primary analysis, coupled with wide 95% CIs resulted from relatively small patient sizes, caution should be taken when interpreting the results.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRegarding TRT analytic strategy, the SNRI cohort encompassed 6648 and the gabapentinoid cohort consisted of 11744 patients b-PSM. 6612 patients were identified in both cohorts a-PSM. There were also no significant findings observed both b-PSM [(glaucoma) HR = 1.343, 95% CI: 0.885-2.040; (angle-closure glaucoma) HR = 0.552, 95% CI: 0.111-2.735; (open-angle glaucoma) HR = 1.090, 95% CI: 0.579-2.052] and a-PSM [(glaucoma) HR = 1.198, 95% CI: 0.742-1.943; (angle-closure glaucoma) HR = 0.160, 95% CI: 0.019-1.326; (open-angle glaucoma) HR = 1.003, 95% CI: 0.496-2.029]. Likewise, the results were not completely consistent with those in the primary analysis. The outcome measures for glaucoma are presented in Figure 5, while those for its subtypes are provided in Supplemenatry Material \u0026ndash; Appendix 4.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cstrong\u003e\u003cu\u003eAssociation between neuropathic pain modulators and glaucoma risk\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis retrospective cohort study suggests a possible link between the use of SNRIs and gabapentinoids and an increased risk of glaucoma and its subtypes in FM patients. Besides, the users of SNRIs may exhibit higher glaucoma risk than the gabapentinoid users. However, results in the subgroup analysis and sensitivity analysis showed limited consistency, suggesting that the observed higher glaucoma risk among SNRI users should be interpreted with caution. In addition, when assessing the risk of glaucoma subtypes, we observed small sample sizes and wide 95% CIs, particularly for angle-closure glaucoma. This may partly explain the limited consistency observed in the results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eMechanistic insights into SNRI-associated glaucoma risk\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSNRIs theoretically have the potential to increase the risk of glaucoma by affecting the concentration of serotonin, norepinephrine, and dopamine. These medications exert serotonergic effects on 5HT7 receptors, leading to pupil dilation and increased aqueous humor production \u003csup\u003e8,19\u003c/sup\u003e, adrenergic effects on α1 receptors, resulting in mydriasis and eyelid retraction, as well as effects on α2 receptors that enhance aqueous humor outflow capacity \u003csup\u003e20\u003c/sup\u003e. Additionally, dopaminergic effects on vascular dopamine (DA1) receptors have been identified in ocular structures like the sclera, choroid, ciliary process, and trabecular meshwork, which are suggested to be associated with and AAG \u003csup\u003e21\u003c/sup\u003e. There have been several case reports of AAG in individuals using duloxetine and venlafaxine \u003csup\u003e10,11,22-24\u003c/sup\u003e, and a meta-analysis that included six case-control studies and one cohort study suggested that SSRIs were not linked to an increased risk of glaucoma (k=7, pooled adjusted odds ratio (pAOR)=0.956, 95% CI: 0.807-1.133, p = 0.604) \u003csup\u003e25\u003c/sup\u003e. Furthermore, patients exposed to both SSRIs and SNRIs even exhibited lower IOP (k=4, Hedges' g = -0.519, 95% CI: -0.743 to -0.296, p \u0026lt; 0.001). However, it is essential to note that there was considerable heterogeneity among the studies included in this analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eMechanistic insights into SNRI-associated glaucoma risk\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConversely, the mechanisms underlying glaucoma development associated with gabapentinoids have received limited attention. Browne MJ et al.'s case-control study findings suggested an increased risk of AAG with gabapentin use, whereas pregabalin use did not show a similar association \u003csup\u003e26\u003c/sup\u003e. Although there have been studies demonstrating GABAergic influences on AAG development \u003csup\u003e27-30\u003c/sup\u003e, these findings could be only partially applicable to gabapentinoids. This is because gabapentinoids do not directly impact the concentration of GABAergic neurotransmitters but instead modulate calcium influx by binding to the α2δ-1 subunit of voltage-gated calcium channels \u003csup\u003e31\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eComparison with prior studies and population-specific considerations\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur study indicated a potential association between the use of SNRIs and gabapentinoids, and an increased risk of glaucoma. Our findings regarding gabapentinoids are consistent with those of Browne MJ et al.'s study \u003csup\u003e26\u003c/sup\u003e. However, it is crucial to emphasize that our study specifically focuses on the FM population. Regarding our findings related to SNRIs and their association with increased glaucoma risk, they diverge from the results of Özer MA et al.'s study \u003csup\u003e32\u003c/sup\u003e. They indicated that duloxetine did not result in clinically significant changes in FM patients, despite observing statistically significant effects on anterior chamber parameters, including IOP, central corneal thickness (CCT), corneal endothelial cell density (CECD), and anterior chamber depth (ACD). One potential explanation for this discrepancy lies in our diagnosis criteria, which were not restrictive. It relied solely on records from healthcare organizations using glaucoma-related ICD codes, without considering the specific diagnostic tools and disease severity. Nevertheless, the findings in our study still hold some significance due to the inclusion of a relatively large population. As for the results regarding glaucoma subtypes, there were relatively few outcome events during the follow-up, especially angle closure subtypes. This may be explained by the limited sensitivity over the diagnosis codes, and that patients with a predisposition to angle-closure glaucoma, such as those with a family history or narrower anterior chamber angles, may be less likely to receive these medications initially, leading to possible selection bias when observing the relation between these medication usages and angle-closure glaucoma risk.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eInterpretation of the subgroup analysis\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the subgroup analysis, we observed that SNRI users may exhibit a lower risk of glaucoma than gabapentinoid users among FM patients with primary hypertension. This finding may be coincidental due to the relatively small sample size. However, another potential explanation could be that in patients with hypertension, the blood pressure–raising effect of SNRIs is relatively attenuated, leading to a more neutral IOP or ocular perfusion. In contrast, in individuals without hypertension, SNRIs may elevate IOP by increasing aqueous humor production through blood pressure–induced filtration. Additionally, despite the statistical insignificance, we also observed the trend suggesting that SNRI users may exhibit lower risk of glaucoma compared to gabapentinoid users in FM patients with diabetes mellitus. This could be explained by the possible selection and detection biases due to the use of SNRIs in diabetic peripheral neuropathy (with duloxetine being FDA-approved for this indication) besides coincidence resulted from relatively small sample size. These patients may already undergo regular ophthalmologic monitoring, such as diabetic retinopathy screening, with further detection and management over glaucoma thereby reducing the risk. Moreover, our findings suggesting a linkage of SNRI usage to lower glaucoma risk when compared to gabapentinoids in FM patients with primary hypertension or diabetes mellitus, aligned with those in the case-control study conducted by Chen et al. evaluating the association between the use of SSRIs and glaucoma development in patients with major depressive disorders \u003csup\u003e9\u003c/sup\u003e. Their study indicated that SSRI users with hypertension did not exhibit significantly higher risk of glaucoma [odds ratio (OR) = 1.09, 95% CI: 0.95-1.25], and those with diabetes mellitus also did not (OR = 1.09, 95% CI: 0.87-1.34). They hypothesized that glaucoma developments in patients with such comorbidities may be more related to the health condition instead of the SSRI usage. Nevertheless, these hypotheses warrant further studies with prospective design to confirm the cause-and-effect relationship.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eStrengths\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStrengths of this retrospective cohort study include its focus on FM patients. The comparison between SNRIs and gabapentinoids provides a reference for clinicians when making treatment decisions regarding the initiation or selection of neuropathic pain relievers in this population—a topic that has been seldom explored in previous research. Furthermore, the scarcity of retrospective cohort studies addressing this specific topic enhances the significance of this research, and it also encompassed a relatively large population for analyzing the association between medication usage and glaucoma risk\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eLimitations\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study also has several limitations that should be acknowledged. First, the severity of fibromyalgia and the underlying neuropathic pain could not be assessed, which may have influenced the choice of medications to some extent. However, since that clinical prescribing practices often rely on diagnosis rather than quantified severity, the treatment patterns observed in this study may still reflect real-world decision-making. Second, the matching of our findings regarding the angle-closure glaucoma and open-angle glaucoma subtypes may not fully reflect the actual scenario. In a recent study researched by Tran et al. evaluating polygenic risk scores (PRSs) for primary open-angle glaucoma (POAG) using ICD codes versus manual record review in the Mount Sinai BioMe and Mass General Brigham (MGB) biobanks, ICD-based POAG diagnoses showed high sensitivity (97%) but low specificity (44% in BioMe, 53% in MGB) compared to cases confirmed by optical coherence tomography and visual field assessments \u003csup\u003e33\u003c/sup\u003e. Another recent study conducted by Lu et al. reported that in Chang Gung Research Database, which is the largest multi-institutional healthcare system in Taiwan comprising EMRs from 9 hospitals, POAG-related ICD-10 codes exhibited relatively lower sensitivity (57.4%) but higher specificity (97.4%), and that primary angle-closure glaucoma (PACG) related ICD-10 codes demonstrate sensitivity of 73.9% and specificity of 99.4%. Besides, ICD-10 codes regarding all both the glaucoma subtypes showed relatively high sensitivity (87.0%) and high specificity (92.8%) \u003csup\u003e34\u003c/sup\u003e. Even though these findings could not be entirely applied to the TriNetX database, they still provided valuable insights for our interpretations. Third, whether FM plays a role as a confounding factor of glaucoma is still questionable. A study conducted by Garcia-Martin E et al. revealed that FM could lead to subclinical axonal damage in the retinal nerve fiber layer (RNFL), which possibly increase the risk of glaucoma in this patient population \u003csup\u003e35\u003c/sup\u003e. However, the associated cause-and-effect relationship requires more studies for confirmation. Furthermore, FM patients are often within relatively complex medical history, and hence confounding bias might exist. We already took some common confounders into consideration when PSM to mitigate such bias, while some important factors such as genetics and IOPs were unavailable with our study design in this database, and that the used diagnostic tools were also unable to confirm. In addition, the study cannot guarantee that FM diagnoses were made based on specific diagnostic criteria, and information on parameters such as the widespread pain index (WPI), symptom severity (SS) scale score, or the duration of symptoms before diagnosis was not available. Besides, the findings of this study are based on a population with FM diagnoses, so the findings should be interpreted with caution when applying them to patients with different clinical backgrounds. Moreover, details of dosage and frequency of these drugs were not available, which may introduce bias due to dose-effect, and we were unable to ascertain whether the patients continued to use the medication until the end of the follow-up. Last but not least, the US Collaborative Network from TriNetX database does not encompass the entire population-based data of the US. Hence, the findings may not fully represent the actual conditions of the US patients.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn FM patients, the use of SNRIs and gabapentinoids was potentially associated with an increased risk of glaucoma. Among these, SNRI users may exhibit a higher risk than gabapentinoid users; however, this conclusion should be interpreted with caution in patients with hypertension.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eContributorship:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eYCL: Conceptualization, Methodology, Data curation, Formal analysis, Writing – original draft\u003c/p\u003e\n\u003cp\u003eCCL: Methodology, Investigation, Writing – original draft\u003c/p\u003e\n\u003cp\u003ePHC: Validation, Visualization, Writing – review \u0026amp; editing\u003c/p\u003e\n\u003cp\u003eJYH: Software, Supervision, Writing – review \u0026amp; editing\u003c/p\u003e\n\u003cp\u003eCBY: Supervision, Writing – review \u0026amp; editing\u003c/p\u003e\n\u003cp\u003eYJT: Supervision, Project administration, Writing – review \u0026amp; editing\u003c/p\u003e\n\u003cp\u003eFunding: This research received no funding from any agency.\u003c/p\u003e\n\u003cp\u003eChung Shan Medical University Hospital’s institutional review board granted the ethical approval for using the TriNetX database in this study.\u003c/p\u003e\n\u003cp\u003eData availability statement: The analyzed data in this study was extracted\u003c/p\u003e\n\u003cp\u003efrom the TriNetX database, which accumulates electronic health\u003c/p\u003e\n\u003cp\u003erecords from healthcare organizations around the world. Due to licensing\u003c/p\u003e\n\u003cp\u003eand confidentiality agreements, it cannot be publicly shared. The\u003c/p\u003e\n\u003cp\u003edatasets used in this study can be requested from interested researchers\u003c/p\u003e\n\u003cp\u003eby contacting TriNetX (https:// trinetx.com/) in accordance with their\u003c/p\u003e\n\u003cp\u003edata usage policy.\u003c/p\u003e\n\u003cp\u003eEthical statements: All methods were carried out in accordance with relevant guidelines and regulations. The requirement to obtain informed consent was waived by the Institutional Review Board of Chung Shan Medical University Hospital because the de-identified data in this database adhered to Section §164.514(a) of the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule.\u003c/p\u003e\n\u003cp\u003ePatient and Public Involvement: Patients were not involved in the design, conduct, reporting, or dissemination plans of our research.\u003c/p\u003e\n\u003cp\u003eYCL, CCL, PHC, JYH, CBY, and YJT\u0026nbsp;declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003eAcknowledgments\u003c/p\u003e\n\u003cp\u003eThe authors would like to express their sincere gratitude to professor Chin-Wen Chi, for the valuable contributions to the manuscript. His insights and expertise were instrumental in the completion of this paper.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSchmidt-Wilcke, T. \u0026amp; Clauw, D. J. 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Mechanism of topiramate-induced acute-onset myopia and angle closure glaucoma. \u003cem\u003eAm J Ophthalmol\u003c/em\u003e\u003cstrong\u003e137\u003c/strong\u003e, 193-195, doi:10.1016/s0002-9394(03)00774-8 (2004).\u003c/li\u003e\n\u003cli\u003e Thambi, L.\u003cem\u003e et al.\u003c/em\u003e Topiramate-associated secondary angle-closure glaucoma: a case series. \u003cem\u003eArch Ophthalmol\u003c/em\u003e\u003cstrong\u003e120\u003c/strong\u003e, 1108, doi:10.1001/archopht.120.8.1108 (2002).\u003c/li\u003e\n\u003cli\u003e Banta, J. T., Hoffman, K., Budenz, D. L., Ceballos, E. \u0026amp; Greenfield, D. S. Presumed topiramate-induced bilateral acute angle-closure glaucoma. \u003cem\u003eAm J Ophthalmol\u003c/em\u003e\u003cstrong\u003e132\u003c/strong\u003e, 112-114, doi:10.1016/s0002-9394(01)01013-3 (2001).\u003c/li\u003e\n\u003cli\u003e Sills, G. J. The mechanisms of action of gabapentin and pregabalin. \u003cem\u003eCurr Opin Pharmacol\u003c/em\u003e\u003cstrong\u003e6\u003c/strong\u003e, 108-113, doi:10.1016/j.coph.2005.11.003 (2006).\u003c/li\u003e\n\u003cli\u003e \u0026Ouml;zer, M. A.\u003cem\u003e et al.\u003c/em\u003e Evaluation of the effects of duloxetine treatment on anterior segment parameters by optical coherence tomography. \u003cem\u003eInt Ophthalmol\u003c/em\u003e\u003cstrong\u003e43\u003c/strong\u003e, 141-146, doi:10.1007/s10792-022-02396-1 (2023).\u003c/li\u003e\n\u003cli\u003e Tran, J. H.\u003cem\u003e et al.\u003c/em\u003e Use of Diagnostic Codes for Primary Open-Angle Glaucoma Polygenic Risk Score Construction in Electronic Health Record-Linked Biobanks. \u003cem\u003eAm J Ophthalmol\u003c/em\u003e\u003cstrong\u003e267\u003c/strong\u003e, 204-212, doi:10.1016/j.ajo.2024.06.007 (2024).\u003c/li\u003e\n\u003cli\u003e Lu, P. T., Tsai, T. H., Lai, C. C., Chuang, L. H. \u0026amp; Shao, S. C. Validation of Diagnostic Codes to Identify Glaucoma in Taiwan's Claims Data: A Multi-Institutional Study. \u003cem\u003eClin Epidemiol\u003c/em\u003e\u003cstrong\u003e16\u003c/strong\u003e, 227-234, doi:10.2147/clep.S443872 (2024).\u003c/li\u003e\n\u003cli\u003e Garcia-Martin, E.\u003cem\u003e et al.\u003c/em\u003e Fibromyalgia Is Correlated with Retinal Nerve Fiber Layer Thinning. \u003cem\u003ePLoS One\u003c/em\u003e\u003cstrong\u003e11\u003c/strong\u003e, e0161574, doi:10.1371/journal.pone.0161574 (2016).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1A. Baseline characteristics before and after propensity-score matching (SNRI vs. non-SNRI)\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"1010\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 362px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 328px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBefore propensity-score matching\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 320px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAfter propensity-score matching\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSNRI\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 37388)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-SNRI\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 237299)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSMDs\u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSNRI\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 37354)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-SNRI\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 37354)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSMDs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"36\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd height=\"36\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd height=\"36\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge at index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003csup\u003ec\u003c/sup\u003e (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e51.8 \u0026plusmn; 13.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e52.2 \u0026plusmn; 15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e51.8 \u0026plusmn; 13.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e52.2 \u0026plusmn; 14.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex, No. (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e31859(85.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e173108(72.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e31825(85.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e32249(86.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e3069(8.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e31434(13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e3069(8.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e2965(7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity, No. (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e27332(73.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e151364(63.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e27302(73.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e27985(74.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003eBlack or African American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e3489(9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e23548(9.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e3486(9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e3266(8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Asian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e349(0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e3706(1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e349(0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e328(0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthcare utilization, No. (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Inpatient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e4991(13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e23839(10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e4977(13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e4701(12.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Outpatient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e27341(73.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e171174(72.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e27307(73.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e26998(72.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Emergency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e7609(20.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e39430(16.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e7591(20.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e7347(19.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidities, No. (%)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Primary hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e10265(27.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e48768(20.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.162\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e10237(27.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e9981(26.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Dyslipidemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e8046(21.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e40348(17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e8025(21.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e7721(20.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Overweight and obesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e5854(15.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e21758(9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e5829(15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e5611(15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Diabetes mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e5125(13.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e22045(9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e5108(13.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e4955(13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Migraine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e4286(11.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e12939(5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e4254(11.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e4042(10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Insomnia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e3018(8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e7353(3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e2987(8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e2790(7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Obstructive sleep apnea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e2994(8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e10570(4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e2971(8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e2854(7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Diseases of arteries, arterioles and capillaries\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e1751(4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e9070(3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e1746(4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e1687(4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Rheumatoid arthritis with rheumatoid factor (M05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e459(1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e2024(0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e457(1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e439(1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Other rheumatoid arthritis (M06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e1800(4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e6354(2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e1790(4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e1708(4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Systemic Lupus Erythematosus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e969(2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e3608(1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.076\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e963(2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e961(2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Chronic kidney disease, stage 3 (N18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e733(2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e3762(1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e732(2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e706(1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Chronic kidney disease, stage 4 (N18.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e115(0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e820(0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e115(0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e115(0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Chronic kidney disease, stage 5 (N18.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e39(0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e297(0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e39(0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e31(0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; End stage renal disease (N18.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e115(0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e989(0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e115(0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e107(0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedications, No. (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Corticalsteroids (dermatological preparations)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e14135(37.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e59369(25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e14103(37.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e14188(38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Corticalsteroids for systemic use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e13788(36.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e57345(24.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.279\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e13756(36.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e13934(37.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Antihistamines for systemic use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e9107(24.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e34767(14.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.247\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e9078(24.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e8848(23.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Antihistamines for topical use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e5981(16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e22224(9.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e5955(15.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e5731(15.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Anticholinergics (inhalants)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e2462(6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e8812(3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e2450(6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e2332(6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Anticholinergics (ophthalmologicals)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e1617(4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e6668(2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e1611(4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e1567(4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Anticholinergic agents (oral)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e507(1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e1250(0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e505(1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e426(1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Selective serotonin reuptake inhibitors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e6675(17.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e22511(9.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.245\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e6650(17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e6719(18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Tricyclic antidepressants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e3373(9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e8760(3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e3350(9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e3200(8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLaboratory data, No. (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Systolic blood pressure (mean \u0026plusmn; SD mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e125 \u0026plusmn; 17.9 (47.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e126 \u0026plusmn; 18 (43.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e125 \u0026plusmn; 17.9 (47.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e126 \u0026plusmn; 18 (47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 362px;\"\u003e\n \u003cp\u003e\u0026nbsp; Diastolic blood pressure (mean \u0026plusmn; SD mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e75.4 \u0026plusmn; 11.7 (47.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e75.6 \u0026plusmn; 11.4 (43.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e75.4 \u0026plusmn; 11.7 (47.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e75.5 \u0026plusmn; 11.6 (47)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eTable 1B. Baseline characteristics before and after propensity-score matching (Gabapentinoid vs. non-gabapentinoid)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"1010\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eBefore propensity-score matching\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 32.4661%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAfter propensity-score matching\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eGabapentinoid\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 48484)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-gabapentinoid\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 181931)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eSMDs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eGabapentinoid\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 47308)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-gabapentinoid\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 47308)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSMDs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"36\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd height=\"36\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd height=\"36\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAge at index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e52.8 \u0026plusmn; 13.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e51.4 \u0026plusmn; 15.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e52.8 \u0026plusmn; 13.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e53.3 \u0026plusmn; 14.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSex, No. (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39105(80.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e132108(72.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e38046(80.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e38401(81.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5615(11.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22264(12.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5513(11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5592(11.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity, No. (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e33516(69.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e114812(63.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e32739(69.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e33466(70.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eBlack or African American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5866(12.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16347(9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5567(11.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5362(11.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Asian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e562(1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2931(1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e554(1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e563(1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eHealthcare utilization, No. (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Inpatient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7118(14.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14626(8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6525(13.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6205(13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Outpatient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e36210(74.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e126925(69.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e35105(74.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e34899(73.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Emergency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10039(20.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e26701(14.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9458(20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9375(19.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidities, No. (%)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Primary hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14474(29.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e32722(18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13587(28.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13311(28.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Dyslipidemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11148(23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28024(15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10506(22.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10208(21.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Overweight and obesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7415(15.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14649(8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6808(14.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6552(13.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Diabetes mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7736(16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13497(7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.268\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7075(15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6922(14.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Migraine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4911(10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9300(5.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4505(9.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4394(9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Insomnia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3607(7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4831(2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3122(6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2937(6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Obstructive sleep apnea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3754(7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6743(3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.174\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3367(7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3200(6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Diseases of arteries, arterioles and capillaries\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2554(5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5779(3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2384(5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2314(4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Rheumatoid arthritis with rheumatoid factor (M05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e609(1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1369(0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e563(1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e583(1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Other rheumatoid arthritis (M06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2388(4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4279(2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2168(4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2108(4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Systemic Lupus Erythematosus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1276(2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2402(1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1155(2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1089(2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Chronic kidney disease, stage 3 (N18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1112(2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2152(1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1003(2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e948(2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Chronic kidney disease, stage 4 (N18.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e227(0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e398(0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e201(0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e198(0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Chronic kidney disease, stage 5 (N18.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e81(0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e142(0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e68(0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e75(0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; End stage renal disease (N18.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e277(0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e455(0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e245(0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e228(0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMedications, No. (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Corticalsteroids (dermatological preparations)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18272(37.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e37128(20.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.388\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17201(36.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17403(36.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Corticalsteroids for systemic use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17846(36.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e35778(19.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.388\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16783(35.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16955(35.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Antihistamines for systemic use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11225(23.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21177(11.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.307\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10375(21.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10311(21.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Antihistamines for topical use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7379(15.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12902(7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6717(14.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6618(14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Anticholinergics (inhalants)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3340(6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4599(2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2940(6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2788(5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Anticholinergics (ophthalmologicals)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1983(4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3613(2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1791(3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1720(3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Anticholinergic agents (oral)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e540(1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e674(0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e458(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e437(0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Selective serotonin reuptake inhibitors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7443(15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12500(6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.272\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6793(14.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6769(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Tricyclic antidepressants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3665(7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4741(2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3203(6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3143(6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eLaboratory data, No. (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Systolic blood pressure (mean \u0026plusmn; SD mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e126 \u0026plusmn; 18.3 (48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e126 \u0026plusmn; 17.7 (41.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e126 \u0026plusmn; 18.2 (47.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e127 \u0026plusmn; 18.2 (48.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Diastolic blood pressure (mean \u0026plusmn; SD mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e75.6 \u0026plusmn; 11.8 (48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e75.8 \u0026plusmn; 11.1 (41.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e75.7 \u0026plusmn; 11.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e75.6 \u0026plusmn; 11.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.8643%;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\" style=\"width: 0.6787%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eTable 1C. Baseline characteristics before and after propensity-score matching (SNRI vs. gabapentinoid)\u003c/p\u003e\n\u003cp\u003ea. Serotonin-norepinephrine reuptake inhibitor (SNRI)\u003c/p\u003e\n\u003cp\u003eb. Standardized mean difference (SMD)\u003c/p\u003e\n\u003cp\u003ec. Standard deviation (SD)\u003c/p\u003e\n\u003cp\u003eAll the characteristics were balanced and comparable after propensity-score matching.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"1010\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eBefore propensity-score matching\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eAfter propensity-score matching\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"31\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eSNRI\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 17933)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eGabapentinoid\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 36866)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eSMDs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eSNRI\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 17913)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eGabapentinoid\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n = 17913)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eSMDs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"36\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd height=\"36\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd height=\"36\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAge at index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd height=\"31\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e51.5 \u0026plusmn; 14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e52.8 \u0026plusmn; 13.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e51.5 \u0026plusmn; 14\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e51.7 \u0026plusmn; 14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSex, No. (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15151(84.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29354(79.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15133(84.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15125(84.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1234(6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4561(12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1234(6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1293(7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity, No. (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13116(73.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e25300(68.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13098(73.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13166(73.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eBlack or African American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1307(7.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4336(11.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1307(7.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1302(7.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Asian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e151(0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e440(1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e151(0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e143(0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eHealthcare utilization, No. (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Inpatient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1563(8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4910(13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1563(8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1529(8.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Outpatient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12483(69.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e26675(72.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12463(69.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12237(68.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Emergency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2835(15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7411(20.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2835(15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2728(15.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidities, No. (%)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Primary hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4141(23.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10114(27.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4133(23.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3994(22.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Dyslipidemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3381(18.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7740(21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3367(18.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3287(18.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Overweight and obesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2227(12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4916(13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2213(12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2154(12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Diabetes mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1837(10.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5454(14.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1837(10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1773(9.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Migraine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1719(9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3249(8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1709(9.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1667(9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Insomnia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1177(6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2250(6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1166(6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1112(6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Obstructive sleep apnea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1070(6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2496(6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1064(5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1007(5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Diseases of arteries, arterioles and capillaries\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e628(3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1852(5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e628(3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e631(3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Rheumatoid arthritis with rheumatoid factor (M05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e187(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e477(1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e187(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e173(1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Other rheumatoid arthritis (M06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e736(4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1598(4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e734(4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e707(3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Systemic Lupus Erythematosus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e399(2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e922(2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e399(2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e373(2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Chronic kidney disease, stage 3 (N18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e239(1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e837(2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e239(1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e237(1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Chronic kidney disease, stage 4 (N18.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e37(0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e192(0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e37(0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e32(0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Chronic kidney disease, stage 5 (N18.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11(0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e69(0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11(0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10(0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; End stage renal disease (N18.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e37(0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e229(0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e37(0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39(0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMedications, No. (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Corticalsteroids (dermatological preparations)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5358(29.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13157(35.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5357(29.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5251(29.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Corticalsteroids for systemic use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5284(29.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12816(34.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5282(29.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5188(29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Antihistamines for systemic use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3162(17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7906(21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3159(17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3087(17.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Antihistamines for topical use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1997(11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5287(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1995(11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1906(10.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Anticholinergics (inhalants)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e749(4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2384(6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e749(4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e726(4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Anticholinergics (ophthalmologicals)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e518(2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1424(3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e517(2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e502(2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Anticholinergic agents (oral)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e156(0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e442(1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e156(0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e148(0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Selective serotonin reuptake inhibitors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2574(14.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6117(16.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2573(14.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2537(14.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Tricyclic antidepressants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1117(6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2619(7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1116(6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1080(6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eLaboratory data, No. (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Systolic blood pressure (mean \u0026plusmn; SD mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e125 \u0026plusmn; 17.4 (43.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e126 \u0026plusmn; 18.7 (47.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e125 \u0026plusmn; 17.4 (43.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e125 \u0026plusmn; 17.5 (41.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp; Diastolic blood pressure (mean \u0026plusmn; SD mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e75.8 \u0026plusmn; 11.3 (43.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e75.4 \u0026plusmn; 12.1 (47.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e75.8 \u0026plusmn; 11.3 (43.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e75.8 \u0026plusmn; 11.6 (41.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"34\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Glaucoma, Fibromyalgia, Serotonin-norepinephrine reuptake inhibitors, Gabapentinoids","lastPublishedDoi":"10.21203/rs.3.rs-7502316/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7502316/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjectives\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo evaluate the association between glaucoma risk and the use of serotonin-norepinephrine reuptake inhibitors (SNRIs) and gabapentinoids in patients with fibromyalgia (FM).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted this retrospective cohort study by utilizing the US Collaborative Network from TriNetX database, and included newly diagnosed FM patients, categorizing them into four groups based on SNRI and gabapentinoid prescriptions. Glaucoma was set as the primary outcome, with angle-closure and open-angle subtypes being secondary outcomes in 3-year follow-up. Kaplan-Meier analyses with Cox proportional hazard model and 1:1 propensity-score matching were performed for risk comparisons.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter propensity-score matching, we identified 37354 and 47308 patients respectively in each SNRI-related and gabapentinoid-related cohort, most of whom were White females. There was an association between the use of SNRIs [hazard ratio (HR) = 1.458, 95% confidence interval (CI): 1.184 – 1.796] and gabapentinoids (HR = 1.579, 95% CI: 1.318 – 1.892), and increased glaucoma risk compared to non-users. Additionally, SNRI users exhibited a higher glaucoma risk than gabapentinoid users (HR = 1.354, 95% CI: 1.031 – 1.777).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSNRIs and gabapentinoids increase the glaucoma risk in FM patients, with SNRI users exhibiting higher glaucoma risk than the gabapentinoid users.\u003c/p\u003e","manuscriptTitle":"Glaucoma Risk of Serotonin-norepinephrine Reuptake Inhibitors (SNRIs) and Gabapentinoids in Fibromyalgia Patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-26 15:04:07","doi":"10.21203/rs.3.rs-7502316/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6b7d4b63-50c8-4a62-849e-49a1c8746cfd","owner":[],"postedDate":"September 26th, 2025","published":true,"recentEditorialEvents":[{"type":"decision","content":"Rejected","date":"2026-05-13T06:57:00+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":55127677,"name":"Health sciences/Diseases"},{"id":55127678,"name":"Health sciences/Medical research"},{"id":55127679,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2026-05-13T07:13:34+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-26 15:04:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7502316","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7502316","identity":"rs-7502316","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}