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The reported regressions are the result of a backward selection model technique applied on a model including all variables that were significant at p ≤ 0.20 in univariate analysis except for symptom severity indicators (first model) or hypoglycemic symptoms indicator (second model).
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This trial will contribute to the research question, whether structured, longitudinal monitoring of patients' multidimensional symptoms, indicators for symptom management, and clinical benefit outcomes can influence patients' quality of life and symptom distress, in a setting of routine oncology practice.
The InterVA model is an expert opinion based algorithm founded on Bayes' theorem, which defines the probability of a cause of death given the presence of a particular symptom or set of symptoms (indicators).
The resultant quality measure involving critical symptom indicators is a count of critical symptom indicator questions asked by the triagist compared to the number in the ideal set.
Actors simulating real calls and using scripted symptom scenarios showed that triagists frequently do not ask important symptom indicator questions [ 10, 11].
In most algorithms there are critical symptom indicator questions at the start of the structured dialog that will rapidly lead to an emergency recommendation or very urgent disposition.
Participants completed a survey encompassing demographic, geographic, and symptom indicators.
The 4 factor analytically derived symptom indicators were then used in these taxometric analyses.
However, they used the mean number of DSM-IV diagnostic criteria of SPD as symptom indicators.
Using CDS, there were also fewer omissions of critical symptom indicators in the triage documents.
Triage notes were assessed for the presence of critical symptom indicators using established lists in the literature [ 14].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com