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In accordance with the authors of the qualitative review we grouped the recommendations by the WHO classification of risk factors influencing adherence to long-term therapy [ 21].
We used the WHO classification of risk factors influencing adherence to long-term therapy [ 21] as a framework to group the links found between the interventions and the recommendations.
Regarding the classification of risk factors, parity was considered a non-modifiable factor in the work of Barnes et al., but was assessed as a modifiable factor in this study.
To help distinguish the type of recommendations they were grouped by WHO classification of risk factors influencing adherence to long-term therapies, namely relating to therapy, disease status i.e. having HIV-1, patient factors such as motivation to take therapy, healthcare team and system, and socio-economic circumstances [ 21].
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In all classifications, three prognostic groups were identified using the estimated 5-year survival by sum score (classification 5R), combination of risk factors (5Ri) or binary tree (5T).
Figure 3 presents the classification of patients according to the number of risk factors on target.
This was observed using two different risk functions (SCORE and the FCRS) and a classification of patients according to the number of risk factors that were on target, including self-reported parameters of lifestyle.
For analysis of risk factors, beside univariate analysis, multivariate classification tree analysis statistical method was used.
Our classification of children according to the number and type of risk factors provides some insights into providers' possible perceived urgency of a referral.
Body mass index (BMI) commonly is used in obesity classification as a surrogate measure, and obesity is associated with a cluster of risk factors for cardiovascular disease.
Following symptom classification, travellers are assigned to one of four detectability classes: fever present with symptom onset, aware of risk factors, neither or both.
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