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significant gender » significant concern (Expand Search), significant burden (Expand Search)
gender decrease » greater decrease (Expand Search)
side decrease » sizes decrease (Expand Search), fid decreased (Expand Search), step decrease (Expand Search)
teer decrease » mean decrease (Expand Search), greater decrease (Expand Search)
Showing 61 - 80 results of 1,032 for search '(( significant gender decrease ) OR ( significant ((side decrease) OR (teer decrease)) ))', query time: 0.48s Refine Results
  1. 61
    Alcohol-related monthly crude rates for ages 15 and older between 2018 and 2024, stratified by gender and race.

    Alcohol-related monthly crude rates for ages 15 and older between 2018 and 2024, stratified by gender and race. by Tony Wong (779773)

    Published 2025
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  2. 62
    Comparative Analysis of Chills Experience Across Three Groups: This table presents a detailed comparison of three groups (A, B, and C) in terms of their experiences with chills. It includes the number of participants in each group, frequency, intensity, and duration of chills, along with demographics such as gender, age, race, education level, and income. Statistical significance (p-value) is also provided for each category.

    Comparative Analysis of Chills Experience Across Three Groups: This table presents a detailed comparison of three groups (A, B, and C) in terms of their experiences with chills. It... by Felix Alexandre Schoeller (20988295)

    Published 2025
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  3. 63
    Relative change in cardiovascular diseases DALYs rates from 1990-1994 to 2017-2021 in Chile, for both genders.

    Relative change in cardiovascular diseases DALYs rates from 1990-1994 to 2017-2021 in Chile, for both genders. by Camilo Briones-Valdivieso (21567535)

    Published 2025
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  4. 64
    The results of the subgroup and meta-regression analyses, stratified by follow-up duration, age, gender, study design, and study setting.

    The results of the subgroup and meta-regression analyses, stratified by follow-up duration, age, gender, study design, and study setting. by Razieh Bidhendi-Yarandi (7139387)

    Published 2025
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  5. 65
    Shares of antibiotic substances on total prescription in UTI treatment (N39.0, N30.0) by sex and age group in 2019 (female: n = 238.670 prescriptions; male: n = 40.641 prescriptions).

    Shares of antibiotic substances on total prescription in UTI treatment (N39.0, N30.0) by sex and age group in 2019 (female: n = 238.670 prescriptions; male: n = 40.641 prescription... by Thomas Hanslmeier (19949694)

    Published 2024
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  6. 66
    Shares of antibiotic substances on total prescription by quarter from 2013 to 2019 for female and male patients with UTI (N39.0, N30.0)(female: n = 1.681.255 prescriptions; male: n = 269.151prescriptions).

    Shares of antibiotic substances on total prescription by quarter from 2013 to 2019 for female and male patients with UTI (N39.0, N30.0)(female: n = 1.681.255 prescriptions; male: n... by Thomas Hanslmeier (19949694)

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  7. 67
    Shares of specialist groups prescribing 1<sup>st</sup>, 2<sup>nd</sup>, and 3<sup>rd</sup> antibiotic prescriptions in UTI treatment of females (N39.0, N30.0) in 2018 and 2019.

    Shares of specialist groups prescribing 1<sup>st</sup>, 2<sup>nd</sup>, and 3<sup>rd</sup> antibiotic prescriptions in UTI treatment of females (N39.0, N30.0) in 2018 and 2019. by Thomas Hanslmeier (19949694)

    Published 2024
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  8. 68
    Number of antibiotic prescriptions in female and male patients with UTI (N30.0 and/or N39.0).

    Number of antibiotic prescriptions in female and male patients with UTI (N30.0 and/or N39.0). by Thomas Hanslmeier (19949694)

    Published 2024
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  9. 69
    Shares of antibiotic substances on total prescription in female patients with UTI (N39.0, N30.0) by physician specialties (GPs: n = 1.299.641 prescriptions; gynecologists n = 141.814 prescriptions; urologists n = 182.100 prescriptions).

    Shares of antibiotic substances on total prescription in female patients with UTI (N39.0, N30.0) by physician specialties (GPs: n = 1.299.641 prescriptions; gynecologists n = 141.8... by Thomas Hanslmeier (19949694)

    Published 2024
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  10. 70
    Comparison of 1<sup>st</sup>, 2<sup>nd</sup>, and 3<sup>rd</sup> antibiotic prescription.

    Comparison of 1<sup>st</sup>, 2<sup>nd</sup>, and 3<sup>rd</sup> antibiotic prescription. by Thomas Hanslmeier (19949694)

    Published 2024
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  11. 71
    UTI diagnoses by sex and physician specialty (2013–2019).

    UTI diagnoses by sex and physician specialty (2013–2019). by Thomas Hanslmeier (19949694)

    Published 2024
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  12. 72
    The ASDR of hypertension-related AA stratified by gender in different SDI from 1990 to 2021.

    The ASDR of hypertension-related AA stratified by gender in different SDI from 1990 to 2021. by Guanghui Yu (423945)

    Published 2025
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  13. 73
    Forest plot showing the ratio of odds of acute side effects: nausea (a) and vomiting (b) (=events) among pediatric patients with brain tumors treated with PT or XRT.

    Forest plot showing the ratio of odds of acute side effects: nausea (a) and vomiting (b) (=events) among pediatric patients with brain tumors treated with PT or XRT. by Renáta Kiss-Miki (20760127)

    Published 2025
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  14. 74
    (A) Side image of epoxy resin-made abutment-analog base and prosthesis; (B) Front image of epoxy resin-made abutment-analog base and prosthesis.

    (A) Side image of epoxy resin-made abutment-analog base and prosthesis; (B) Front image of epoxy resin-made abutment-analog base and prosthesis. by Long Li (6555)

    Published 2025
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  15. 75
    Everolimus decreased CD89 deposits in α1<sup>KI</sup>CD89<sup>Tg</sup> mice.

    Everolimus decreased CD89 deposits in α1<sup>KI</sup>CD89<sup>Tg</sup> mice. by Alexandra Cambier (22307216)

    Published 2025
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  16. 76
    Results of negative binomial regression on hours use computer past 30 days (PAQ715).

    Results of negative binomial regression on hours use computer past 30 days (PAQ715). by Mi Zhou (9884)

    Published 2025
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  17. 77
    R code for data analysis.

    R code for data analysis. by Mi Zhou (9884)

    Published 2025
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  18. 78
    Results of negative binomial regression on hours watch TV or videos past 30 days (PAQ710).

    Results of negative binomial regression on hours watch TV or videos past 30 days (PAQ710). by Mi Zhou (9884)

    Published 2025
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  19. 79
    Negative binomial regression results of days physically active at least 60 min (PAQ706).

    Negative binomial regression results of days physically active at least 60 min (PAQ706). by Mi Zhou (9884)

    Published 2025
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  20. 80
    Correlation among demographics, PA, and screen time.

    Correlation among demographics, PA, and screen time. by Mi Zhou (9884)

    Published 2025
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