12 research outputs found

    Data_Sheet_2_The Impact of Nontuberculous Mycobacteria Species on Mortality in Patients With Nontuberculous Mycobacterial Lung Disease.docx

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    Patients with nontuberculous mycobacterial lung disease (NTM-LD) have increased mortality. The impact of NTM species on the risk of mortality remains unclear, especially that of death by non-cancer causes. We conducted a retrospective cohort study from 2006 to 2018 in a tertiary-care hospital in Taiwan. We enrolled patients who fulfilled the microbiological diagnostic criteria of NTM-LD. The mortality causes within 8 years after diagnosis were identified, and the Cox proportional hazard regression was performed for risk factors of mortality. A total of 1,652 subjects with NTM-LD were included. Among them, 723 (43.8%) were infected by Mycobacterium avium complex (MAC), 408 (24.7%) by M. abscessus complex (MABC), 120 (7.3%) by Mycobacterium kansasii (MK), 304 (18.4%) by other rapid-growing mycobacteria (RGM), and 97 (5.9%) by other slow-growing mycobacteria (SGM) groups. The 8-year all-cause mortality was 45.2% for all and the highest in the MK-LD group (59.2%), followed by the MABC-LD and MAC-LD groups. The adjusted hazard ratios were 2.20 (95% confidence interval: 1.40–3.46) in the MK-LD, 1.85 (1.54–2.22) in the MABC-LD, and 1.65 (1.12–2.41) in the MAC-LD groups for all-cause mortality, compared with the SGM group. Kaplan–Meier survival curves showed that all-cause mortality, non-cancer mortality, and mortality due to chronic airway diseases were significantly correlated with NTM species (log-rank p = 0.0031, < 0.001, and 0.001, respectively). High 8-year mortality rates were found in patients with NTM-LDs according to different NTM species. Notably, the difference was significant in non-cancer mortality causes, especially in chronic airway diseases.</p

    Additional file 1 of Comparative cardiovascular safety of LABA/LAMA FDC versus LABA/ICS FDC in patients with chronic obstructive pulmonary disease: a population-based cohort study with a target trial emulation framework

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    Additional file 1: Table S1. Specification and emulation of a target trial of LABA/LAMA FDC versus LABAICS FDC among patients with COPD using real-world data from Taiwan NHIRD. Table S2. International Classification of Diseases, 9th or 10th Revision, Clinical Modification diagnosis codes used to identify patients with COPD. Table S3. Anatomical Therapeutic Chemical classification system codes used to identify use of LABA/LAMA FDC or LABA/ICS FDC. Table S4. International Classification of Diseases, 9th or 10th Revision, Clinical Modification diagnosis codes used to identify outcomes of interest and the positive control outcome. Table S5. International Classification of Diseases, 9th or 10th Revision, Clinical Modification diagnosis or procedure codes or Taiwan health insurance service claims codes used to identify comorbidities and measures of healthcare services at baseline. Table S6. Anatomical Therapeutic Chemical classification system codes used to identify medication use at baseline. Table S7. Measurement of the 11 clinical parameters at baseline. Table S8. Summary of subgroup analyses. Table S9. Patient characteristics of the eligible cohort before and after PS matching. Table S10. Number of patients and events, follow-up duration, incidence rate, and risk of pneumonia comparing LABA/LAMA FDC with LABA/ICS FDC before and after PS matching. Table S11. Number of patients and events, follow-up duration, incidence rate, and risk of composite cardiovascular events comparing LABA/LAMA FDC with LABA/ICS FDC before and after PS matching, by intention-to-treat approach. Table S12. Availability of the clinical parameters at baseline in the eligible cohort. Table S13. Clinical parameters of the imputed cohort before and after PS matching. Table S14. Number of patients, number of events, and risk of composite cardiovascular events comparing LABA/LAMA FDC versus LABA/ICS FDC before and after PS matching, by patient characteristic. Table S15. Number of patients, number of events, and risk of composite cardiovascular events comparing LABA/LAMA FDC versus LABA/ICS FDC before and after PS score matching, by individual LABA/LAMA FDC and LABA/ICS FDC. Table S16. Number of patients, number of events, and risk of composite cardiovascular events comparing LABA/LAMA FDC versus LABA/ICS FDC before and after PS matching, by treatment duration. Table S17. Selected patient characteristics at baseline and cardiovascular outcomes during follow-up of three substantial efficacy trials and our study. Figure S1. Study cohort assembly. Figure S2. Distributions of propensity score by study drug before and after PS matching. Figure S3. Cumulative incidence plots of composite cardiovascular events by study FDC treatment before and after PS matching derived from complement of the Kaplan-Meier survival function. Figure S4. Cumulative incidence plots of composite cardiovascular events by study FDC treatment before and after PS matching accounting for the influence of competing risk from overall death

    Study flowchart.

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    Abbreviation: FEV1, forced expiratory volume in one second; FVC, forced vital capacity.</p

    Independent factors associate with hospital mortality in patients with acute exacerbation of chronic obstructive pulmonary disease requiring intensive care unit admission: Focusing on the eosinophil-to-neutrophil ratio - Fig 3

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    (a) The synergistic impact of initial CRP and peak ENR on days 8–14 of treatment on the risk of hospital mortality. The adjusted odds ratios (AOR) with 95% confidence intervals (95% CIs) for mortality are shown. (b) Kaplan–Meier curves for 28-day mortality in each group.</p

    Univariate and multivariate logistic regression analysis of risk factors for hospital mortality in the study patients (n = 146).

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    Univariate and multivariate logistic regression analysis of risk factors for hospital mortality in the study patients (n = 146).</p

    The percentage and count of blood eosinophil and neutrophil prior to ER visit and during admission in the study patients.

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    The percentage and count of blood eosinophil and neutrophil prior to ER visit and during admission in the study patients.</p
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