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MB clade 7 viruses accounted for 34 viral sequences in our data set, and 52.9% (18/34) required hospitalization, peaking in November during wave 2. Such intensified regional sampling may have introduced confounding bias in our severity analysis.
These findings corroborate our severity ranking.
A number of findings support the validity of our severity ranking.
The foregoing findings support the validity of our diagnostic categories and our severity ranking.
This would not have affected our severity analysis that was based on information over the whole course of the illness.
Our severity ranking showed a monotonic relationship to hospital length of stay, amputation rate, transition to long-term care, and mortality.
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Analysts and policy-makers should therefore exercise caution when using predicted scores from our severity-specific Barthel to AQoL algorithms in samples that include low severity patients.
Whatever the reason, our findings suggest that the predictive validity of our severity-specific item-based and subscale-based SF-36 to AQoL algorithms is more than adequate for evaluating the relative effectiveness and cost-effectiveness of stroke interventions.
12 We and others have found worse agreement for auscultatory findings in infants, 21, 31 but that overall the reliability of our severity-of-illness tool (κ = 0.68) was sufficient to permit its use.
Although an association between age and phenotype was not apparent and our severity-based characterization of phenotype was imperfect, further consideration of the relationship among phenotype, age, and severity is warranted.
It should also be emphasised that use of our severity-specific algorithms requires some means of distinguishing 'low severity' patients (whose AQoL scores are most appropriately estimated using the 'low severity' algorithms) from 'moderate to high' severity patients (whose AQoL scores are most appropriately estimated using the 'moderate to severe' algorithms).
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