2 datasets found
  1. m

    Supplemental Methods Final PPI Fungal

    • data.mendeley.com
    Updated Mar 25, 2025
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    Rahib Islam (2025). Supplemental Methods Final PPI Fungal [Dataset]. http://doi.org/10.17632/h5y9wktcrz.1
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    Dataset updated
    Mar 25, 2025
    Authors
    Rahib Islam
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    A retrospective cohort study was conducted using the TriNetX Global Collaborative Network, a federated database comprising de-identified electronic health records from 142 healthcare organizations (HCOs). The database was queried on March 13, 2025, to identify patients diagnosed with gastroesophageal reflux disease (GERD). Patients were stratified into two cohorts based on proton pump inhibitor (PPI) exposure. The GERD+PPI cohort included patients with a diagnosis of GERD (ICD-10: K21) who had ≥2 prescriptions for a PPI (omeprazole, esomeprazole, pantoprazole, lansoprazole, dexlansoprazole, or rabeprazole) within 5 years prior to the index date. The GERD control cohort included GERD patients with no history of PPI use, defined as no recorded prescriptions for any listed PPIs at any time. Patients were excluded in the risk analysis if they had a history of cutaneous fungal infections, including onychomycosis, tinea corporis, tinea pedis, tinea cruris, or cutaneous candidiasis. Additional exclusions included a history of systemic antifungal use (fluconazole, terbinafine, itraconazole) within 1 day prior to the index date or a history of immunodeficiency conditions, including HIV (ICD-10: B20), solid organ transplantation, or primary immunodeficiency disorders (ICD-10: D80-D84). Cohorts were propensity score-matched (1:1) to minimize confounding, using variables including age, sex, race/ethnicity, diabetes, obesity, immunosuppression, and concurrent medication use. Standardized mean differences (SMDs) were used to assess balance between matched cohorts. The primary outcome was the incidence of cutaneous fungal infections following PPI use. Risk ratios (RR) with 95% confidence intervals (CIs) were calculated using logistic regression. A p-value <0.05 was considered statistically significant. All statistical analyses were conducted within the TriNetX platform.

  2. f

    Table 1_Insomnia increases the risk for specific autoimmune diseases: a...

    • frontiersin.figshare.com
    docx
    Updated Apr 10, 2025
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    Sarah Stenger; Artem Vorobyev; Katja Bieber; Tanja Lange; Ralf J. Ludwig; Jennifer E. Hundt (2025). Table 1_Insomnia increases the risk for specific autoimmune diseases: a large-scale retrospective cohort study.docx [Dataset]. http://doi.org/10.3389/fnetp.2025.1499297.s001
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    docxAvailable download formats
    Dataset updated
    Apr 10, 2025
    Dataset provided by
    Frontiers
    Authors
    Sarah Stenger; Artem Vorobyev; Katja Bieber; Tanja Lange; Ralf J. Ludwig; Jennifer E. Hundt
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    ObjectiveThe global rise of autoimmune diseases presents a significant medical challenge, with inadequate treatment options, high morbidity risks, and escalating healthcare costs. While the underlying mechanisms of autoimmune disease development are not fully understood, both genetic predispositions and lifestyle factors, particularly sleep, play critical roles. Insomnia and circadian rhythm sleep disorders not only impair sleep but also disrupt multi-organ interactions by dysregulating sympathetic nervous system activity, altering immune responses, and influencing neuroendocrine function. These disruptions can contribute to immune system dysregulation, increasing the risk of autoimmune disease development.MethodsTo assess the impact of impaired sleep on the risk of developing autoimmune diseases, a global population-based retrospective cohort study was conducted using electronic health records from the TriNetX US Global Collaborative Network, including 351,366 subjects in each propensity score matched group. Twenty autoimmune diseases were examined, and propensity score matching was employed to reduce bias. Three sensitivity analyses were conducted to test the robustness of the results.ResultsThe study identified significantly increased risks for several autoimmune diseases associated with impaired sleep, likely mediated by dysregulated neuroimmune and autonomic interactions. Specifically, cutaneous lupus erythematosus [hazard ratio (HR) = 2.119; confidence interval (CI) 1.674–2.682; p < 0.0001], rheumatoid arthritis (HR = 1.404; CI 1.313–1.501; p < 0.0001), Sjögren syndrome (HR = 1.84; CI 1.64–2.066; p < 0.0001), and autoimmune thyroiditis (HR = 1.348; CI 1.246–1.458; p < 0.0001) showed significantly increased risks. No diseases demonstrated reduced risks, and 4 out of 20 tested diseases did not show significant HR increases in any analysis.ConclusionThis study highlights the integral role of sleep in maintaining immune homeostasis through multi-organ interactions involving the autonomic nervous system, immune signalling pathways, and endocrine regulation. Disruptions in these systems due to chronic sleep impairment may predispose individuals to autoimmune diseases by altering inflammatory responses and immune tolerance. These findings underscore the necessity of recognizing and treating sleep disorders not only for general wellbeing but also as a potential strategy to mitigate the long-term risk of autoimmune disease development.

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Rahib Islam (2025). Supplemental Methods Final PPI Fungal [Dataset]. http://doi.org/10.17632/h5y9wktcrz.1

Supplemental Methods Final PPI Fungal

Explore at:
Dataset updated
Mar 25, 2025
Authors
Rahib Islam
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

A retrospective cohort study was conducted using the TriNetX Global Collaborative Network, a federated database comprising de-identified electronic health records from 142 healthcare organizations (HCOs). The database was queried on March 13, 2025, to identify patients diagnosed with gastroesophageal reflux disease (GERD). Patients were stratified into two cohorts based on proton pump inhibitor (PPI) exposure. The GERD+PPI cohort included patients with a diagnosis of GERD (ICD-10: K21) who had ≥2 prescriptions for a PPI (omeprazole, esomeprazole, pantoprazole, lansoprazole, dexlansoprazole, or rabeprazole) within 5 years prior to the index date. The GERD control cohort included GERD patients with no history of PPI use, defined as no recorded prescriptions for any listed PPIs at any time. Patients were excluded in the risk analysis if they had a history of cutaneous fungal infections, including onychomycosis, tinea corporis, tinea pedis, tinea cruris, or cutaneous candidiasis. Additional exclusions included a history of systemic antifungal use (fluconazole, terbinafine, itraconazole) within 1 day prior to the index date or a history of immunodeficiency conditions, including HIV (ICD-10: B20), solid organ transplantation, or primary immunodeficiency disorders (ICD-10: D80-D84). Cohorts were propensity score-matched (1:1) to minimize confounding, using variables including age, sex, race/ethnicity, diabetes, obesity, immunosuppression, and concurrent medication use. Standardized mean differences (SMDs) were used to assess balance between matched cohorts. The primary outcome was the incidence of cutaneous fungal infections following PPI use. Risk ratios (RR) with 95% confidence intervals (CIs) were calculated using logistic regression. A p-value <0.05 was considered statistically significant. All statistical analyses were conducted within the TriNetX platform.

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