Prognostic association of routinely measured biomarkers in patients admitted to critical care: a systematic review. (2nd January 2021)

• Record Type: Journal Article
• Authors: Wan, Yize I.; Brayne, Adam B.; Haines, Ryan W.; Puthucheary, Zudin A.; Prowle, John R.
• Is Part Of: Biomarkers. Volume 26:Number 1(2021)
• Page Start: 1
• Page End: 12
• Publication Date: 2021-01-02
• Subjects: Systematic reviews -- intensive care -- biomarker -- mortality -- length of stay; Biochemical markers -- Periodicals; 610.28
• DOI: 10.1080/1354750X.2020.1842498
• Languages: English
• ISSNs: 1354-750X

Abstract

Abstract: Purpose: To examine reported prognostic associations of routine blood measurements in the intensive care unit. Materials and methods: We searched PubMed, EMBASE through 28 th May 2020 to identify all studies in adult critical care investigating associations between parameters measured routinely in whole blood, plasma or serum, and length of stay or mortality. Registration: PROSPERO; CRD42019122058. Results: A total of 128 studies, reporting 28 different putative prognostic biomarkers, met eligibility criteria. Those most frequently examined were red cell distribution width, neutrophil-to-lymphocyte ratio, C-reactive protein, and platelet count. A higher red cell distribution width, a lower platelet count, and a higher neutrophil-to-lymphocyte ratio were consistently associated with both increased mortality and length of stay. A lower level of albumin was consistently associated with greater mortality. C-reactive protein was inconsistent. Most studies (n = 110) used regression modelling with wide variation in variable selection and covariate-adjustment; none externally validated the proposed predictive models. Conclusions: Simple regression models have so far proved inadequate for the complexity of data available from routine blood sampling in critical care. Adoption of a direct causal framework may help better assess mechanistic processes, aid design of future studies, and guide clinical decision making using routine data.