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Comment
. 2024 Apr 1;52(4):e216-e217.
doi: 10.1097/CCM.0000000000006183. Epub 2024 Mar 14.

Case-Mix and the Limitations of Standardized Mortality Ratios for ICU Performance and Benchmarking

Filipe Amado  1   2 , Amanda Quintairos  1   3 , Jorge I F Salluh  1   4
Affiliations
Comment

Case-Mix and the Limitations of Standardized Mortality Ratios for ICU Performance and Benchmarking

Filipe Amado et al. Crit Care Med. .
No abstract available

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Conflict of interest statement

Dr. Salluh is supported, in part, by individual research grants from Conselho Nacional de Desenvolvimento Científico e Tecnológico and Fundação Carlos Chagas Filho de Amparo à Pesquisa do Rio de Janeiro. The remaining authors have disclosed that they do not have any potential conflicts of interest.

Comment in

  • The authors reply.
    Pölkki A, Moser A, Raj R, Takala J, Bendel S, Jakob SM, Reinikainen M. Pölkki A, et al. Crit Care Med. 2024 Apr 1;52(4):e217-e218. doi: 10.1097/CCM.0000000000006205. Epub 2024 Mar 14. Crit Care Med. 2024. PMID: 38483239 No abstract available.

Comment on

References

    1. Pölkki A, Moser A, Raj R, et al.: The influence of potential organ donors on standardized mortality ratios and ICU benchmarking. Crit Care Med 2023 Nov 10. [online ahead of print]
    1. Beane A, Dongelmans DA, Fernandez AL, et al.; Linking of Global Intensive Care Collaboration (LOGIC): Time to revisit treatment limitations in critical care benchmarking. Crit Care Med 2021; 49:e472–e473
    1. Quintairos A, Pilcher D, Salluh JIF: ICU scoring systems. Intensive Care Med 2023; 49:223–225
    1. Raj R, Moser A, Starkopf J, et al.: Variation in severity-adjusted resource use and outcome for neurosurgical emergencies in the intensive care unit. Neurocrit Care 2023 Apr 26. [online ahead of print]
    1. Vranas KC, Jopling JK, Sweeney TE, et al.: Identifying distinct subgroups of ICU patients: A machine learning approach. Crit Care Med 2017; 45:1607–1615

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