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Showing 4,321 - 4,340 results of 4,766 for search 'i ((values decrease) OR (largest decrease))', query time: 0.38s Refine Results
  1. 4321

    Table 4_The hemoglobin, albumin, lymphocyte, and platelet score as a useful predictor for mortality in older patients with hip fracture.docx by Zhicong Wang (810566)

    Published 2025
    “…For each unit increase in the HALP score, there was a significant decrease in 90-day mortality by 1.1% and in overall mortality by 1.0% (all p < 0.05). …”
  2. 4322

    Image 2_The hemoglobin, albumin, lymphocyte, and platelet score as a useful predictor for mortality in older patients with hip fracture.jpeg by Zhicong Wang (810566)

    Published 2025
    “…For each unit increase in the HALP score, there was a significant decrease in 90-day mortality by 1.1% and in overall mortality by 1.0% (all p < 0.05). …”
  3. 4323

    Image 7_Systemic immune inflammatory index and mortality in chronic kidney disease.tif by Yanshuang Ma (22176478)

    Published 2025
    “…The evaluation of threshold impacts identified important levels starting at 6.06 and 6.25, which corresponded to the lowest observed mortality risk when evaluated through the SII.log values. The likelihood of mortality from all causes escalated once these limits were surpassed (HR 0.75, 95% CI 0.64-0.88; HR 1.74, 95% CI 1.55-1.95). …”
  4. 4324

    Image 2_Systemic immune inflammatory index and mortality in chronic kidney disease.tif by Yanshuang Ma (22176478)

    Published 2025
    “…The evaluation of threshold impacts identified important levels starting at 6.06 and 6.25, which corresponded to the lowest observed mortality risk when evaluated through the SII.log values. The likelihood of mortality from all causes escalated once these limits were surpassed (HR 0.75, 95% CI 0.64-0.88; HR 1.74, 95% CI 1.55-1.95). …”
  5. 4325

    Image 3_Systemic immune inflammatory index and mortality in chronic kidney disease.tif by Yanshuang Ma (22176478)

    Published 2025
    “…The evaluation of threshold impacts identified important levels starting at 6.06 and 6.25, which corresponded to the lowest observed mortality risk when evaluated through the SII.log values. The likelihood of mortality from all causes escalated once these limits were surpassed (HR 0.75, 95% CI 0.64-0.88; HR 1.74, 95% CI 1.55-1.95). …”
  6. 4326

    Image 4_Systemic immune inflammatory index and mortality in chronic kidney disease.tif by Yanshuang Ma (22176478)

    Published 2025
    “…The evaluation of threshold impacts identified important levels starting at 6.06 and 6.25, which corresponded to the lowest observed mortality risk when evaluated through the SII.log values. The likelihood of mortality from all causes escalated once these limits were surpassed (HR 0.75, 95% CI 0.64-0.88; HR 1.74, 95% CI 1.55-1.95). …”
  7. 4327

    Image 5_Systemic immune inflammatory index and mortality in chronic kidney disease.tif by Yanshuang Ma (22176478)

    Published 2025
    “…The evaluation of threshold impacts identified important levels starting at 6.06 and 6.25, which corresponded to the lowest observed mortality risk when evaluated through the SII.log values. The likelihood of mortality from all causes escalated once these limits were surpassed (HR 0.75, 95% CI 0.64-0.88; HR 1.74, 95% CI 1.55-1.95). …”
  8. 4328

    Image 6_Systemic immune inflammatory index and mortality in chronic kidney disease.tif by Yanshuang Ma (22176478)

    Published 2025
    “…The evaluation of threshold impacts identified important levels starting at 6.06 and 6.25, which corresponded to the lowest observed mortality risk when evaluated through the SII.log values. The likelihood of mortality from all causes escalated once these limits were surpassed (HR 0.75, 95% CI 0.64-0.88; HR 1.74, 95% CI 1.55-1.95). …”
  9. 4329

    Octβ2R and cAMP underlie the Brp compartmental heterogeneity. by Hongyang Wu (8856740)

    Published 2025
    “…Pseudo color range: −1.2 to 1.2. Mann–Whitney <i>U</i>-test. Ctrl (<i>n</i> = 10 brains) vs. …”
  10. 4330

    Table 2_Genomic characterization and antibiotic susceptibility of biofilm-forming Borrelia afzelii and Borrelia garinii from patients with erythema migrans.pdf by Giorgia Fabrizio (19022288)

    Published 2025
    “…Core genome analysis showed 38.9% of genes were shared between B. afzelii and B. garinii, decreasing to 26.1% with B. burgdorferi. The cloud genome expanded from 34.4% to 53.4% with the addition of B. burgdorferi. …”
  11. 4331

    Image 8_Can posttreatment blood inflammatory markers predict poor survival in gynecologic cancer?: a systematic review and meta-analysis.tiff by Minyong Choi (22465405)

    Published 2025
    “…A systematic review and meta-analysis were conducted to identify the prognostic value of posttreatment PBIMs and their dynamic changes from baseline in gynecologic cancers. …”
  12. 4332

    Image 7_Can posttreatment blood inflammatory markers predict poor survival in gynecologic cancer?: a systematic review and meta-analysis.tiff by Minyong Choi (22465405)

    Published 2025
    “…A systematic review and meta-analysis were conducted to identify the prognostic value of posttreatment PBIMs and their dynamic changes from baseline in gynecologic cancers. …”
  13. 4333

    Data Sheet 2_Can posttreatment blood inflammatory markers predict poor survival in gynecologic cancer?: a systematic review and meta-analysis.zip by Minyong Choi (22465405)

    Published 2025
    “…A systematic review and meta-analysis were conducted to identify the prognostic value of posttreatment PBIMs and their dynamic changes from baseline in gynecologic cancers. …”
  14. 4334

    Image 4_Can posttreatment blood inflammatory markers predict poor survival in gynecologic cancer?: a systematic review and meta-analysis.tiff by Minyong Choi (22465405)

    Published 2025
    “…A systematic review and meta-analysis were conducted to identify the prognostic value of posttreatment PBIMs and their dynamic changes from baseline in gynecologic cancers. …”
  15. 4335

    Image 3_Can posttreatment blood inflammatory markers predict poor survival in gynecologic cancer?: a systematic review and meta-analysis.tiff by Minyong Choi (22465405)

    Published 2025
    “…A systematic review and meta-analysis were conducted to identify the prognostic value of posttreatment PBIMs and their dynamic changes from baseline in gynecologic cancers. …”
  16. 4336

    Image 2_Can posttreatment blood inflammatory markers predict poor survival in gynecologic cancer?: a systematic review and meta-analysis.tiff by Minyong Choi (22465405)

    Published 2025
    “…A systematic review and meta-analysis were conducted to identify the prognostic value of posttreatment PBIMs and their dynamic changes from baseline in gynecologic cancers. …”
  17. 4337

    Image 5_Can posttreatment blood inflammatory markers predict poor survival in gynecologic cancer?: a systematic review and meta-analysis.tiff by Minyong Choi (22465405)

    Published 2025
    “…A systematic review and meta-analysis were conducted to identify the prognostic value of posttreatment PBIMs and their dynamic changes from baseline in gynecologic cancers. …”
  18. 4338

    Image 6_Can posttreatment blood inflammatory markers predict poor survival in gynecologic cancer?: a systematic review and meta-analysis.tif by Minyong Choi (22465405)

    Published 2025
    “…A systematic review and meta-analysis were conducted to identify the prognostic value of posttreatment PBIMs and their dynamic changes from baseline in gynecologic cancers. …”
  19. 4339

    Internal states adjust the Brp compartmental heterogeneity through octopamine. by Hongyang Wu (8856740)

    Published 2025
    “…GFP<sub>1−10</sub> was expressed in KCs using <i>R13F02-GAL4</i> in control, or <i>T</i>β<i>h</i><sup><i>SK2-4</i></sup> background flies. 1−2 weeks old flies were used. …”
  20. 4340

    CRISPR/Cas9-mediated editing of barley lipoxygenase genes promotes grain fatty acid accumulation and storability by Zhanghui Zeng (3571331)

    Published 2025
    “…Notably, the total LOX activity in mature grains decreased by 36–42% in <i>loxC1</i> mutants and by 94% in <i>loxAloxC1</i> mutants, with no significant change observed in <i>loxB</i> mutants. …”