Healthcare is awash with numbers, and figuring out what knowledge these numbers might hold is worthwhile in order to improve patient care. Numbers allow for objective mathematical analysis of the information at hand, but while mathematics is objective by design, our choice of mathematical approach in a given situation is not. In prehospital and critical care, numbers stem from a wide range of different sources and situations, be it experimental setups, observational data or data registries, and what constitutes a "good" statistical analysis can be unclear. A well-crafted statistical analysis can help us see things our eyes cannot, and find patterns where our brains come short, ultimately contributing to changing clinical practice and improving patient outcome. With increasingly more advanced research questions and research designs, traditional statistical approaches are often inadequate, and being able to properly merge statistical competence with clinical knowhow is essential in order to arrive at not only correct, but also valuable and usable research results. By marrying clinical knowhow with rigorous statistical analysis we can accelerate the field of prehospital and critical care.
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http://dx.doi.org/10.1186/s13049-024-01256-4 | DOI Listing |
Nutr Metab Cardiovasc Dis
September 2022
Department of Clinical and Experimental Medicine, University of Messina, Messina, Italy.
Background And Aims: Data on second generation basal insulin (2BI) in people with type 2 diabetes (T2D) generated by clinical trials still need confirmation in real-world clinical settings. This study aimed at assessing the comparative effectiveness of 2BI [Glargine 300 U/mL (Gla-300) vs. Degludec 100 U/mL (Deg-100)] in T2D Italian patients switching from first generation basal insulins (1BI).
View Article and Find Full Text PDFJ Gerontol A Biol Sci Med Sci
October 2021
Gerontopole of Toulouse, Institute of Ageing, Toulouse University Hospital (CHU Toulouse), France.
Background: This study aims to investigate the predictive value of biological and neuroimaging markers to determine incident frailty among older people for a period of 5 years.
Methods: We included 1394 adults aged 70 years and older from the Multidomain Alzheimer Preventive Trial, who were not frail at baseline (according to Fried's criteria) and who had at least 1 post-baseline measurement of frailty. Participants who progressed to frailty during the 5-year follow-up were categorized as "incident frailty" and those who remained non-frail were categorized as "without frailty.
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