Volume 9, Issue 7 e70227
ORIGINAL ARTICLE
Open Access

Gastroparesis and Systemic Lupus Erythematosus: A Propensity Score-Matched Study of US National Database Analysis

Noppachai Siranart

Noppachai Siranart

Division of Gastroenterology, Hepatology and Endoscopy, Brigham and Women's Hospital, Boston, Massachusetts, USA

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Pannathorn Nakaphan

Pannathorn Nakaphan

Department of Internal Medicine, Weiss Memorial Hospital, Chicago, Illinois, USA

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Thanathip Suenghataiphorn

Thanathip Suenghataiphorn

Department of Medicine, Griffin Hospital, Derby, Connecticut, USA

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Panisara Fangsaard

Panisara Fangsaard

Department of Internal Medicine, Bassett Medical Center, Cooperstown, New York, USA

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Tanattida Phanthong

Tanattida Phanthong

Faculty of Medicine, King Chulalongkorn Memorial Hospital, Bangkok, Thailand

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Patavee Pajareya

Patavee Pajareya

Faculty of Medicine, King Chulalongkorn Memorial Hospital, Bangkok, Thailand

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Somkiat Phutinart

Somkiat Phutinart

Faculty of Medicine, King Chulalongkorn Memorial Hospital, Bangkok, Thailand

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Pawaris Tirakunwichcha

Pawaris Tirakunwichcha

Faculty of Medicine, King Chulalongkorn Memorial Hospital, Bangkok, Thailand

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Suwit Paksin

Suwit Paksin

Faculty of Medicine, King Chulalongkorn Memorial Hospital, Bangkok, Thailand

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Pornnicha Sowalertrat

Pornnicha Sowalertrat

Faculty of Medicine, Srinakharinwirot University, Bangkok, Thailand

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Sakkarin Chirapongsathorn

Sakkarin Chirapongsathorn

Division of Gastroenterology and Hepatology, Department of Medicine, Phramongkutklao Hospital and College of Medicine, Bangkok, Thailand

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Kittithat Tantitanawat

Corresponding Author

Kittithat Tantitanawat

Division of Gastroenterology and Hepatology, Department of Medicine, Phramongkutklao Hospital and College of Medicine, Bangkok, Thailand

Correspondence:

Kittithat Tantitanawat ([email protected])

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First published: 11 July 2025

Funding: The authors received no specific funding for this work.

Pannathorn Nakaphan is the co-first author.

ABSTRACT

Introduction

While gastrointestinal involvement is a common manifestation of systemic lupus erythematosus (SLE), the association between gastroparesis and SLE remains unclear.

Methods

We analyzed data from the National Inpatient Sample (NIS) database from 2016 to 2021. Patients with gastroparesis were categorized into SLE and non-SLE groups. Similarly, patients with SLE were categorized into gastroparesis and nongastroparesis groups. Clinical characteristics, comorbidities, hospitalization data, and outcomes were compared. The primary outcome was the association between SLE and primary gastroparesis. Secondary outcomes were clinical impacts of gastroparesis in patients with or without SLE.

Results

A total of 12 538 228 patients were included from the NIS database. Of these, 1 165 925 patients (9.3%) were diagnosed with gastroparesis during hospitalization, while 11 372 303 patients (90.7%) did not have gastroparesis. SLE was significantly more common in patients with gastroparesis compared to those without (1.6% vs. 0.7%, p < 0.001; aOR 1.87 [95% CI: 1.80–1.95]). Among patients hospitalized with gastroparesis, those with SLE had a longer length of stay, with a β-coefficient of 0.31 (95% CI: 0.07–0.55, p = 0.009), lower hospitalization charges, with mean differences of $4761 (95% CI: 442–9080, p = 0.031), and a higher rate of intervention needs, with odds ratios of 1.31 (95% CI: 1.09–1.56, p = 0.003). After propensity-score matching (1:1), SLE patients aged ≥ 65 had higher hospital charges, with mean differences of $7287 (95% CI: 2928–11 646, p = 0.01), compared to non-SLE patients.

Conclusion

Gastroparesis is associated with SLE, contributing to longer hospitalizations, higher costs, and increased need for invasive interventions. These findings underscore the importance of evaluating gastroparesis in SLE patients to enable early management and reduce potential complications.

Abbreviations

  • aORs
  • adjusted odds ratios
  • HCUP
  • Health Care Utilization Project
  • ICD-10-CM
  • International classification of diseases, Tenth revision, clinical modification
  • IRB
  • Institutional Review Board
  • MD
  • mean difference
  • NIS
  • National Inpatient Sample
  • SD
  • standard deviation
  • SLE
  • systemic lupus erythematosus
  • TPN
  • total parenteral nutrition
  • 1 Introduction

    Gastroparesis is a disorder of upper gastrointestinal motility characterized by symptoms suggestive of, and objective evidence of delayed gastric emptying. It is typically associated with symptoms such as nausea, vomiting, upper abdominal pain, early satiety, fullness, or bloating, occurring in the absence of any mechanical obstruction of the stomach or duodenum [1-3]. To date, we categorize the causes of gastroparesis into three domains: diabetic gastroparesis, iatrogenic gastroparesis (resulting from upper gastrointestinal surgery or medications), and idiopathic gastroparesis [4]. However, in the largest group of patients, no identifiable underlying cause is found, and these cases are categorized as idiopathic gastroparesis [5, 6].

    Systemic lupus erythematosus (SLE) is a systemic autoimmune disease characterized by immune-mediated injury and chronic inflammation affecting multiple organ systems [7, 8]. Gastrointestinal involvement in patients with SLE is reported in up to 50% of cases [9]. Among the most common manifestations are nausea, anorexia, and vomiting [9]. Regarding clinical manifestations, abdominal pain and weight loss are reported in up to two-thirds of cases. Gastroparesis associated with substantial health care costs thus, prompt diagnosis of gastroparesis in SLE patients is crucial to improve long-term outcomes and quality of life. However, gastroparesis is often underdiagnosed due to the limited availability of the gold standard diagnostic tool, gastric emptying scintigraphy [10, 11].

    While gastrointestinal involvement is a common manifestation of SLE, association between gastroparesis and SLE remains unclear. The majority of the data utilized were derived from a small cohort of patients treated at a single center [6]. While these findings provide valuable insights, the limited sample size and single-center nature of the study may affect the generalizability of the results to broader populations. To address these evidence gaps, the current study aimed to estimate the prevalence of gastroparesis in adults, describe patient demographics, explore disease etiology and treatments received following diagnosis, and treatment outcomes in a large, national administrative insurance claims database.

    2 Methods

    2.1 Data Source

    This study utilized data from the 2021 Health Care Utilization Project National Inpatient Sample (HCUP-NIS), the largest publicly accessible all-payer inpatient database in the United States, sponsored by the Agency for Healthcare Research and Quality. The HCUP-NIS uses a multilevel survey design to sample approximately 20% of hospital admissions and discharges nationwide. This approach allows for generating national estimates on patient demographics, diagnoses, and hospital-based procedures performed in acute-care hospitals across the United States. All sampled hospital discharges are recorded and weighted to ensure an accurate representation of the national inpatient care landscape.

    2.2 Study Cohort

    This study focused on individuals aged 18 and older who were hospitalized with any diagnosis of gastroparesis episodes and SLE from 2016 to 2021. Eligible discharge records were identified using the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) coding system. As the NIS database does not include clinical testing data, diagnoses were based solely on ICD-10-CM codes, without confirmation through objective measures such as gastric emptying studies. Records categorized as elective hospitalizations were excluded from the analysis. Data S1 provided a detailed list of the ICD-10 codes used to identify eligible patients and assess associated risks and procedures.

    We employed propensity score matching (1:1) to balance and minimize differences in baseline characteristics in this study. Each variable was matched to generate a propensity-matched cohort. A combination of balancing, matching, weight readjustment, and interpretation strategies was applied to ensure comparability between the cohorts. A standardized difference of less than 10% among the measured covariates indicated adequate matching between the two groups, thereby reducing potential bias.

    2.3 Outcomes

    The primary outcome was to evaluate the relationship between gastroparesis and SLE. The secondary outcomes focused on analyzing patient characteristics and identifying comorbidities associated with gastroparesis in individuals with SLE. Additionally, hospitalization outcomes, including length of hospital stay, hospitalization charges, the need for invasive interventions including insertion of feeding devices into stomach or jejunum, total parenteral nutrition (TPN), and pyloroplasty and all-cause mortality, were compared between gastroparesis patients with and without SLE.

    2.4 Statistical Analysis

    Data analyses were conducted using StataBE 17.0 software (StataCorp, College Station, TX). Weighted sampling techniques were applied in accordance with HCUP-NIS guidelines to generate nationally representative estimates. Descriptive statistics for continuous variables were presented as mean ± standard deviation (SD), while categorical variables were expressed as percentages. Proportions were compared using Fisher's exact test for categorical variables and the Student's t test for continuous variables. Covariates included in the analysis were selected based on a thorough literature review, prior research findings, and established confounding factors.

    Multivariate logistic regression models were used to calculate adjusted odds ratios (aORs) for primary and secondary outcomes. For continuous outcomes, multivariable linear regression analyses were performed. These models were adjusted for a comprehensive set of patient- and hospital-level confounders, including age, sex, race, median income, hospital size, hospital location, teaching status, insurance type, and comorbidities, to improve the robustness of the findings. A p < 0.05 was considered statistically significant.

    Additionally, a prespecified subgroup analysis was conducted stratifying patients by age (< 65 vs. ≥ 65 years), in which individuals aged 65 and older were classified as elderly, following the definition commonly used in general guidelines.

    3 Results

    A total of 12 538 228 patients were included from the NIS database. Of these, 1 165 925 patients (9.3%) were diagnosed with gastroparesis during intrahospitalization, and 11 372 303 patients (90.7%) did not have gastroparesis. In the gastroparesis group, 18 765 (1.6%) patients were SLE patients while 1 147 160 (98.4%) patients were non-SLE patients. In the nongastroparesis group, 0.7% of patients had SLE, while the remaining 99.3% did not have SLE.

    3.1 Gastroparesis and SLE

    A significant association was found between the presence of gastroparesis and SLE patients (p < 0.001). In univariable analysis, SLE was associated with an OR of 2.50 (95% CI: 2.41–2.59, p < 0.001) compared to non-SLE. In multivariable analysis, adjusted for age, sex, and ethnicity, SLE remained an associated factor with an OR of 1.87 (95% CI: 1.80–1.95, p < 0.001).

    3.2 Before Propensity-Score Matching

    Gastroparesis patients with SLE were younger (51.6 ± 0.05 vs. 48.02 ± 0.24, p < 0.001) and had a higher proportion of females (95.7% vs. 65.3%, p < 0.001) compared to patients without SLE. Demographics and comorbidities differed between the two groups. In terms of gastroparesis symptoms, SLE patients exhibited comparable frequencies of nausea and vomiting, loss of appetite, early satiety, and abdominal pain. However, weight loss was significantly more prevalent in the SLE group (p = 0.014). Baseline characteristics were shown in Table 1.

    TABLE 1. Baseline characteristics of patients with gastroparesis, stratified by the presence of systematic lupus erythematous.
    Outcomes Before propensity score matching After propensity score matching
    SLE− (N = 1 147 160) SLE+ (N = 18 765) p SLE− (N = 18 300) SLE+ (N = 18 300) p
    Age (years, mean ± SD) 51.58 ± 0.05 48.02 ± 0.24 < 0.001 49.26 ± 0.28 48.15 ± 0.26 0.004
    Female (%) 65.34 95.74 < 0.001 95.82 95.74 0.874
    Race (%)
    Caucasians 57.21 53.1 < 0.001 56.48 53.28 0.112
    African Americans 26.33 31.84 29.54 31.67
    Hispanics 11.95 11.93 11.15 11.89
    Asians 1.47 0.73 0.49 0.74
    Natives 0.8 0.38 0.22 0.38
    Others 2.24 2.03 2.13 2.05
    Symptoms during hospitalization (%)
    Nausea and vomiting 4.6 4.32 0.42 4.26 4.29 0.957
    Loss of appetite 0.66 0.75 0.507 0.57 0.71 0.49
    Early satiety 0.25 0.27 0.811 0.19 0.27 0.491
    Abdominal pain 3.6 4.05 0.157 4.04 4.13 0.871
    Weight loss 0.9 1.28 0.014 1.17 1.31 0.617
    Hospital region (%)
    Northeast 15.42 13.35 0.001 13.63 13.58 0.247
    Midwest 21.32 18.6 17.43 18.22
    South 45.1 51.93 54.23 51.97
    West 18.16 16.12 14.7 16.23
    Insurance status (%)
    Medicare 48.92 53.27 0.001 54.92 53.33 0.37
    Medicaid 24.03 20.26 18.8 20.08
    Private insurance 20.35 21.86 22.32 21.94
    Self-payment 6.7 4.61 3.96 4.65
    Patient location (%)
    Central metro area 30.36 33.35 0.001 32.6 33.55 0.938
    Suburban metro area 23.62 25.5 26.83 25.74
    250 K–1 M area 22.65 23.36 22.87 22.92
    50 K–250 K area 9.96 7.72 7.73 7.76
    Micropolitan area 8.07 5.95 6.07 5.93
    Others 5.35 4.11 3.91 4.1
    Comorbidities (%)
    Hypertension 30.59 29.31 0.109 29.89 29.32 0.621
    Diabetes mellitus type 1 23.29 10.21 < 0.001 17.38 10.14 < 0.001
    Diabetes mellitus type 2 52.09 37.62 35.33 37.98
    Ischemic heart disease 23.96 19.4 < 0.001 19.78 19.62 0.872
    Dyslipidemia 40.76 30.38 < 0.001 31.67 30.74 0.432
    Obesity 18.9 21.32 < 0.001 21.91 21.45 0.658
    Liver diseases 8.83 9.78 0.053 9.51 9.75 0.742
    Chronic kidney disease 15.8 14.68 0.085 12.79 14.54 0.047
    Known pyloric stenosis 1.12 0.85 0.119 0.93 0.87 0.815
    Other rheumatic diseases 0.29 2.98 < 0.001 2.35 2.49 0.724
    Elixhauser co-morbidity index (mean ± SD) 4.83 ± 0.01 5.67 ± 0.03 < 0.001 4.51 ± 0.03 5.68 ± 0.04 < 0.001
    Lifestyle (%)
    Smoking/tobacco use 36.17 27.12 < 0.001 26.64 26.94 0.788
    Alcohol usage 3.41 1.47 < 0.001 1.31 1.5 0.527
    Medications (%)
    Steroids, initial usage 0.93 2.13 < 0.001 0.24 2.08 0.338
    Steroids, long-term 1.91 12.18 12.43 11.5
    • * Statistical significance; p < 0.05.

    In a univariable logistic and linear regression analysis, SLE patients were associated with a longer hospital stay, as indicated by a β-coefficient of 0.31 (95% CI: 0.07–0.55, p = 0.009). However, they incurred lower intrahospitalization charges, with a mean difference (MD) of $4761 (95% CI: $442–$9080, p = 0.031), compared to non-SLE patients. Notably, SLE patients under the age of 65 had significantly lower charges (MD = $7705, 95% CI: $2885–$12 524, p = 0.002), while those aged 65 and older had comparable charges (MD = −$5180, 95% CI: –$13 807 to $3447, p = 0.239).

    Regarding interventions during hospitalization, SLE patients required more invasive procedures compared to non-SLE patients (OR = 1.31, 95% CI: 1.09–1.56, p = 0.003). Specifically, patients under 65 years of age were more likely to require interventions (OR = 1.49, 95% CI: 1.24–1.79, p < 0.001), while those aged 65 and older had comparable intervention rates (OR = 0.78, 95% CI: 0.43–1.38, p = 0.398). Among invasive interventions, TPN was more frequently administered to SLE patients (OR = 1.47, 95% CI: 1.17–1.84, p < 0.001). However, rates of feeding device insertion (OR = 1.18, 95% CI: 0.91–1.53, p = 0.199) and pyloroplasty (OR = 0.88, 95% CI: 0.12–6.39, p = 0.904) were similar between groups.

    In terms of intrahospital mortality, no significant difference was observed between SLE and non-SLE patients (OR = 0.85, 95% CI: 0.61–1.13, p = 0.282).

    Multivariable logistic and linear regression models were adjusted for key demographic and hospital-level covariates to control for potential confounding. These analyses yielded results consistent with the univariable models. SLE patients showed a longer length of stay with β-coefficient of 0.45 (95% CI: 0.21–0.69, p < 0.001), higher hospitalization charges with MDs of $7287 (95% CI: 2928–11 646, p = 0.01), and a higher rate of invasive intervention needs with ORs of 1.28 (95% CI: 1.09–1.53, p = 0.007) specifically, the needs of TPN with ORs of 1.33 (95% CI: 1.05–1.67, p = 0.015) (Table 2).

    TABLE 2. SLE+ versus SLE− in terms of gastroparesis outcomes during hospitalization.
    Outcomes Before propensity-score matching After propensity-score matching
    OR (95% CI) p aOR (95% CI) p OR (95% CI) p
    Need any interventions 1.31 (1.09, 1.56) 0.003 1.28 (1.06, 1.53) 0.007 0.97 (0.75, 1.26) 0.869
    Age < 65 1.49 (1.24, 1.79) < 0.001 1.35 (1.12, 1.63) 0.001 1.06 (0.80, 1.39) 0.661
    Age > = 65 0.78 (0.43, 1.38) 0.398 0.63 (0.28, 1.45) 0.287
    Insertion of feeding device into stomach/jejunum 1.18 (0.91, 1.53) 0.199 1.04 (0.71, 1.52) 0.81
    TPN 1.47 (1.17, 1.84) < 0.001 1.33 (1.05, 1.67) 0.015 0.97 (0.69, 1.36) 0.884
    Pyloroplasty 0.88 (0.12, 6.39) 0.904 1.00 (0.05, 18.95) 1
    Mortality 0.85 (0.61, 1.13) 0.282 1.28 (0.80, 2.06) 0.288
    β-coefficient (95% CI) p β-coefficient (95% CI) p β-coefficient (95% CI) p
    Length of stay 0.31 (0.07, 0.55) 0.009 0.45 (0.21, 0.69) < 0.001 0.00 (−0.38, 0.37) 0.974
    Mean differences (95% CI) p Mean differences (95% CI) p Mean differences (95% CI) p
    Hospitalization charges 4761 (442, 9080) 0.031 7287 (2928, 11 646) 0.001 3848 (−2326, 10 022) 0.222
    Age < 65 7705 (2885, 12.524) 0.002 8005 (3117, 12 893) 0.001 7088 (362, 13 815) 0.039
    Age > = 65 −5180 (−13 807, 3447) 0.239 −9790 (−26 248, 6668) 0.243
    • a Adjusted by age, sex, race, hospital region, insurance, patient location, smoking, and alcohol.
    • * Statistical significance: p < 0.05.

    3.3 After Propensity-Score Matching

    Propensity score matching (1:1) was matched by age, sex, and patients' demographic data, resulting in 18 300 matched pairs for comparisons between the SLE and non-SLE groups (Table 1). Younger age (p = 0.004), distinct diabetes profiles (p < 0.001), a higher prevalence of chronic kidney disease (p = 0.047), and a higher Elixhauser comorbidity index (p < 0.001) were observed in SLE patients compared to non-SLE patients.

    In a univariable logistic and linear regression model, they showed similar outcomes in terms of length of stay with β-coefficient of 0.00 (95% CI: −0.38 to 0.37, p = 0.974), hospital charges with MDs of $3848 (95% CI: −2326 to 10 022, p = 0.222), needs of any invasive interventions with ORs of 0.97 (95% CI: 0.75–1.26, p = 0.869). In subgroup analysis, SLE patients with age < 65 showed higher charges compared to age ≤ 65 with MDs of $7088 (95% CI: 362–13 815, p = 0.039) (Table 2).

    4 Discussion

    Our study is the first to utilize a large database to demonstrate that gastroparesis is associated with SLE. It also demonstrated a marked difference in clinical characteristics of patients with SLE who develop gastroparesis compared to the general gastroparesis patient population.

    It is unsurprising that patients with SLE in our study had higher steroid usage and a greater prevalence of chronic kidney disease, as these are inherent to the disease's natural course. One might assume that SLE is linked to steroid use, which in turn leads to diabetes and eventually gastroparesis. However, our findings suggest otherwise, as SLE patients in our cohort had a lower prevalence of diabetes—a well-established major risk factor for gastroparesis. Additionally, SLE patients were younger and had lower smoking rates, both of which are also recognized risk factors. Although causality cannot be inferred due to the observational nature of our study, a more plausible explanation is that SLE itself, as a distinct disease entity, may contribute to the pathophysiology of gastroparesis. This hypothesis is further supported by a previous study demonstrating that SLE is associated with gastroparesis even in a nondiabetic population [12].

    The mechanisms underlying the development of gastroparesis in SLE remain poorly understood. However, autonomic dysfunction is well-documented in SLE patients [13]. Autonomic neuropathy secondary to SLE, particularly its impact on the regulation of the enteric nervous system, may play a significant role. Additionally, intrinsic smooth muscle dysmotility due to immune complex deposition or vasculitis-related chronic ischemia, as observed in SLE patients with intestinal pseudo-obstruction, could also play a role [14].

    In our study, patients with SLE and gastroparesis had significantly longer hospital stays and higher hospital costs, which may reflect that gastroparesis in the context of SLE is more difficult to manage and potentially associated with worse clinical outcomes. This may be due to the complex interplay between autoimmunity, autonomic dysfunction, and gastrointestinal dysmotility, making treatment less straightforward compared to idiopathic gastroparesis. Nutritional management is a key consideration in these patients, as malnutrition can exacerbate disease severity and increase hospitalization risks. The choice of nutrition depends on the severity of gastroparesis, with enteral nutrition generally preferred to maintain gut integrity, while parenteral nutrition is reserved for severe cases where enteral feeding is not tolerated [6]. Notably, patients with SLE in our study were more likely to receive TPN, and weight loss was more pronounced in this group, underscoring the critical role of early nutritional assessment and intervention. Although our study assessed the odds of SLE patients receiving gastric or jejunal feeding device placement, the association was not statistically significant. However, there was a significant increase in the likelihood of overall interventions, which likely contributed to the higher costs and longer hospital stays observed. This suggests that while gastroparesis in SLE may not always necessitate invasive nutritional support, the overall burden of disease often requires aggressive inpatient management.

    Previous studies have shown that improving SLE disease control can lead to symptom relief in gastroparesis [10]. Given the potential for immune-mediated damage to the autonomic nervous system and smooth muscle, optimizing SLE management may be crucial not only for controlling systemic inflammation but also for improving gastrointestinal motility. A multidisciplinary approach involving rheumatologists, gastroenterologists, and nutritionists may be essential in reducing the need for interventions, ultimately leading to shorter hospital stays, lower healthcare costs, and improved patient outcomes.

    This study has a few limitations. The administrative and cross-sectional nature of the NIS database restricted access to detailed patient-level data, such as clinical characteristics, endoscopic findings, gastric emptying study results, and laboratory values, which are critical for stratifying disease severity and accurately characterizing gastroparesis in SLE patients. Misclassification bias may be present, as the identification of gastroparesis was based solely on ICD-10-CM coding without confirmation through objective diagnostic testing. Additionally, the database lacks information on medication use, including specific prokinetics, immunosuppressive therapies, opioids, or steroid regimens, as well as SLE disease activity and duration, which could provide insights into treatment effects and potential confounding factors. The absence of data on the duration, frequency, and severity of symptoms such as nausea, vomiting, and weight loss limits our ability to assess the clinical burden of gastroparesis in this population. Furthermore, the database focuses exclusively on in-hospital occurrences, potentially overlooking significant postdischarge outcomes such as long-term nutritional status, quality of life, and subsequent hospital readmissions. It also may not fully represent the broader SLE population affected by gastroparesis, as a significant proportion of SLE patients are managed in the outpatient setting and were therefore not included in our analysis. Finally, the observational nature of this study precludes the establishment of definitive causal relationships between SLE and gastroparesis. Moreover, while we conducted multivariable analyses and age-stratified subgroup analysis to address confounding and assess robustness, we did not perform additional subgroup or sensitivity analyses (e.g., stratified by comorbidity burden) due to limitations in dataset granularity and statistical power. Future studies may explore these subgroup effects in more targeted cohorts or with prospectively collected data. While our findings suggest an association, further prospective studies are needed to confirm these relationships and explore underlying mechanisms. Despite these limitations, our study is the first to utilize a large database population to provide important insights into the prevalence, clinical impact, and treatment outcomes of gastroparesis in SLE patients. These findings underscore the need for heightened clinical awareness and further research to improve diagnosis, management, and outcomes in the SLE population.

    In conclusion, gastroparesis is increasingly recognized as a significant gastrointestinal manifestation in SLE, with its presence contributing to longer hospital stays, higher healthcare costs, and an increased requirement for invasive interventions. These findings highlight the critical need for early identification and management of gastroparesis in SLE patients to mitigate its impact on morbidity, improve patient outcomes, and reduce healthcare burdens. The observed association emphasizes the importance of routine evaluation for gastrointestinal symptoms in SLE patients, particularly in those with risk factors for gastroparesis. Future research should prioritize elucidating the complex pathophysiological mechanisms linking SLE to gastroparesis, including the roles of autoimmunity, neural dysfunction, and comorbid conditions. Additionally, validating these findings in diverse populations and through well-designed prospective cohort studies will be essential to better understand this relationship and inform tailored therapeutic strategies.

    Ethics Statement

    As the NIS database does not include patient or hospital-specific identifiers, Institutional Review Board (IRB) approval was not required for this study. Nevertheless, we ensured compliance with ethical standards for research involving human subjects.

    Conflicts of Interest

    The authors declare no conflicts of interest.

    Data Availability Statement

    The data that support the findings of this study are available from the corresponding author upon reasonable request.

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