Indian Journal of Critical Care Medicine

Register      Login

SEARCH WITHIN CONTENT

FIND ARTICLE

Volume / Issue

Online First

Archive
Related articles

VOLUME 25 , ISSUE 7 ( July, 2021 ) > List of Articles

EDITORIAL

Data Analysis will not Result in Knowledge Production about Sepsis

Sriram Sampath

Keywords : Data analysis, Fragility index, Knowledge, Scientific method, Sepsis

Citation Information : Sampath S. Data Analysis will not Result in Knowledge Production about Sepsis. Indian J Crit Care Med 2021; 25 (7):750-751.

DOI: 10.5005/jp-journals-10071-23887

License: CC BY-NC 4.0

Published Online: 07-07-2021

Copyright Statement:  Copyright © 2021; Jaypee Brothers Medical Publishers (P) Ltd.


Abstract


PDF Share
  1. Marik PE, Farkas JD, Spiegel R, Weingart S, Aberegg S, Beck-Esmay J, et al. POINT: should the surviving sepsis campaign guidelines be retired? Yes. Chest 2019;155(1):12–14. DOI: 10.1016/j.chest.2018.10.008.
  2. Choupoo NS, Das SK, Saikia P, Dey S, Ray S. How Robust are the Evidences that formulate Surviving Sepsis Guidelines? An Analysis of Fragility and Reverse Fragility of Randomized Controlled Trials that were referred in these Guidelines. Indian J Crit Care Med 2021;25(7):773-779.
  3. Levy MM, Rhodes A, Evans LE, Antonelli M, Bailey H, Kesecioglu J, et al. COUNTERPOINT: should the surviving sepsis campaign guidelines be retired? No. Chest 2019;155(1):14–17. DOI: 10.1016/j.chest.2018.10.012.
  4. Laffey JG, Kavanagh BP. Negative trials in critical care: why most research is probably wrong. Lancet Respir Med 2018;6(9):659–660. DOI: 10.1016/S2213-2600(18)30279-0.
  5. Seligman H, Teixeira-Pinto A, Nowbar A, Francis D. Fragility of the bond between cardiovascular investigators and their readers. Circ Cardiovasc Qual Outcomes 2019;12:e006271. DOI: 10.1161/CIRCOUTCOMES.119.006271.
  6. Coveney PV, Dougherty ER, Highfield RR. 2016 Big data need big theory too. Philos Trans R Soc A 374:20160153. DOI: 10.1098/rsta.2016.0153.
  7. Shappell CN, Klompas M, Rhee C. Surveillance strategies for tracking sepsis incidence and outcomes. J Infect Dis 2020;222(Supplement_2):S74–S78. DOI: 10.1093/infdis/jiaa102.
  8. Carra G, Salluh JI, da Silva Ramos FJ, Meyfroidt G. Data-driven ICU management: using big data and algorithms to improve outcomes. J Crit Care 2020;60:300–304. DOI: 10.1016/j.jcrc.2020.09.002.
  9. Succi S, Coveney PV. Big data: the end of the scientific method? Philos Trans Roy Soc A 2019;377(2142):20180145. DOI: 10.1098/rsta.2018.0145.
  10. Pearl J. Theoretical impediments to machine learning with seven sparks from the causal revolution. arXiv preprint arXiv:1801.04016. 2018.
  11. Hernán MA, Clayton D, Keiding N. The Simpson's paradox unraveled. Int J Epidemiol 2011;40(3):780–785. DOI: 10.1093/ije/dyr041.
  12. Van Wyngene L, Vandewalle J, Libert C. Reprogramming of basic metabolic pathways in microbial sepsis: therapeutic targets at last? EMBO Mol Med 2018;10(8):e8712. DOI: 10.15252/emmm.201708712.
  13. Hattori Y, Hattori K, Suzuki T, Matsuda N. Recent advances in the pathophysiology and molecular basis of sepsis-associated organ dysfunction: novel therapeutic implications and challenges. Pharmacol Ther 2017;177:56–66. DOI: 10.1016/j.pharmthera.2017.02.040.
  14. Chousterman BG, Swirski FK, Weber GF. Cytokine storm and sepsis disease pathogenesis. Semin Immunopathol 2017;39(5):517–528. DOI: 10.1007/s00281-017-0639-8.
PDF Share
PDF Share

© Jaypee Brothers Medical Publishers (P) LTD.