Showing 781 - 800 results of 14,107 for search '(( significant decrease decrease ) OR ( significantly ((i decrease) OR (a decrease)) ))~', query time: 0.46s Refine Results
  1. 781

    Annual number of outpatient visits in all eyes. by Yasuyuki Sotani (20114144)

    Published 2025
    “…<p>Mean visit frequency (mean ± standard deviation) significantly decreased from 11.5 ± 4.3 preoperatively to 8.8 ± 4.1, 5.0 ± 3.4, and 4.4 ± 3.2 visits in the first, second, and third postoperative years, respectively (Kruskal–Wallis test, P < 0.001; Dunn’s test, **P < 0.01). …”
  2. 782

    Annual treatment frequencies in all eyes. by Yasuyuki Sotani (20114144)

    Published 2025
    “…<p>The number of anti-VEGF treatments, STTA, MA-PC, PPV, and total treatments (mean ± SD) significantly decreased from 2.6 ± 1.6, 0.3 ± 0.8, 0.6 ± 0.8, 0.1 ± 0.3, and 3.7 ± 1.7 preoperatively to 0.8 ± 1.9, 0.0 ± 0.2, 0.3 ± 1.0, 0.0, and 1.2 ± 2.2; at year 2 to 0.7 ± 2.0, 0.1 ± 0.6, 0.0 ± 0.2, 0.0 ± 0.2, and 1.0 ± 2.1; and at year 3 to 0.9 ± 2.2, 0.0, 0.2 ± 1.0, 0.0 ± 0.2, and 1.1 ± 3.1 (Kruskal–Wallis test, P < 0.001; Dunn’s test, **P < 0.01). …”
  3. 783

    Time course of central retinal thickness (CRT) in recurrence and non-recurrence groups. by Yasuyuki Sotani (20114144)

    Published 2025
    “…These values significantly decreased in the first postoperative year to 2.3 ± 2.6, 0.1 ± 0.3, 0.8 ± 1.6, 0, and 3.1 ± 2.8; in the second year to 2.1 ± 2.8, 0.4 ± 1.0, 0.0, 0.1 ± 0.3, and 2.6 ± 2.8; and in the third year to 2.0 ± 2.2, 0, 0.6 ± 1.7, 0.1 ± 0.3, and 2.8 ± 3.5 (Kruskal–Wallis test, p < 0.001; <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0332941#pone.0332941.g007" target="_blank">Fig 7</a>). …”
  4. 784

    Time course of best-corrected visual acuity (BCVA) in recurrence and non-recurrence groups. by Yasuyuki Sotani (20114144)

    Published 2025
    “…CRT in the recurrence group significantly decreased from 546.1 ± 117.0 μm preoperatively to 317.1 ± 46.9, 317.8 ± 55.6, 290.8 ± 33.5, 342.9 ± 82.2, 333.0 ± 84.2, and 349.8 ± 76.9 μm at 1, 3, 6, 12, 24, and 36 months postoperatively, respectively (Kruskal-Wallis test, p < 0.001). …”
  5. 785
  6. 786
  7. 787
  8. 788

    Sociodemographic characteristics. by Hea Ree Park (10769827)

    Published 2024
    “…Increased circadian preference for eveningness and social jet lag were noted. A significant decrease in sleep duration and sleep efficiency, along with an increased prevalence of insomnia and daytime sleepiness, was noted with age- and sex-specific variations.…”
  9. 789

    Study flow chart. by Hea Ree Park (10769827)

    Published 2024
    “…Increased circadian preference for eveningness and social jet lag were noted. A significant decrease in sleep duration and sleep efficiency, along with an increased prevalence of insomnia and daytime sleepiness, was noted with age- and sex-specific variations.…”
  10. 790
  11. 791
  12. 792

    Participant retention flowchart. by Carolin Oetzmann (11397968)

    Published 2025
    “…We used latent class and latent transition analysis to identify subtypes at baseline, determined their consistency at 6- and 12-month follow-ups, and examined transitions over time. We identified a 4-class solution: (1) severe with appetite decrease, (2) severe with appetite increase, (3) moderate severity and (4) low severity. …”
  13. 793
  14. 794
  15. 795

    S1 Data - by Francois Kiemde (5369657)

    Published 2024
    “…However, when cortisol increases with one unit, the average concentration of prolactin decreases by 1.16 ng/ml (p = 0.013).…”
  16. 796
  17. 797
  18. 798
  19. 799

    Overview of the parameters used in the model. by Albertus Constantijn Sloof (20405090)

    Published 2024
    “…<div><p>Background</p><p>Chikungunya virus (CHIKV) outbreaks, driven by the expanding habitat of the <i>Aedes albopictus</i> mosquito and global climate change, pose a significant threat to public health. …”
  20. 800

    Mortality rates per lifecycle stage [28]. by Albertus Constantijn Sloof (20405090)

    Published 2024
    “…<div><p>Background</p><p>Chikungunya virus (CHIKV) outbreaks, driven by the expanding habitat of the <i>Aedes albopictus</i> mosquito and global climate change, pose a significant threat to public health. …”