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The implication of this variation is serious: If readings are erroneous, some patients will undergo revascularization procedures unnecessarily and others will be denied an essential treatment.
Here, we review the evidence that month of birth varies significantly with geographical location 6– 8 and over time 8– 11 in the normal population and consider the implication of this variation for case control studies considering month of birth as a risk factor for the development of multiple sclerosis.
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We show how widely these elements vary across five different assessments and discuss the implications of this variation.
We also explore the implications of this variation in light of particular interdisciplinary learning objectives.
We then explore the implications of this variation for student learning and interdisciplinary education more broadly.
Nor is there sufficient knowledge on the implications of these variations for the health of the environment and its ecosystems.
What are the implications of these variations for population exposure?
In section 4.4.5 we discuss the implications of the variations based on loop-directed mutagenesis results.
However, there is only anecdotal information about variation in transmission rate by age/stage structure in wild animals or the implication of such variation on disease dynamics in zoonotic reservoirs [5] and only limited information in the case of domestic animals (see e.g., [6]).
We further calculated the additive genetic coefficient of variation (CVA) as the square root of divided by the average PDS to assess the implication of genetic variation for adaptive potential (Houle 1992).
The clinical implications of this variation in collaborative decision making on patient outcomes such as the duration of ventilation and weaning is unclear.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com