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However, we consider the study to be at best uninformative.
We judged one study to be at an unclear risk for other potential sources of bias [40]; the other study [37] was judged to be at high risk of bias due to likely imbalance of patient characteristics, imbalanced distribution of co-treatment, and other methodological study flaws (Figs. 3 and 4).
We judged one study to be at high risk for attrition bias related to incomplete outcome data; the loss to follow-up in this study of 33%% (20 out of 60 enrolled women) is sufficiently high and thus very likely to cause substantial attrition bias [37].
However, we found only 27% of HCV-1a and 20% of HCV-3a infected individuals in our study to be at risk of exposure by IDU, and a similar proportion, albeit with lower numbers, of NIDU (Table 1).
The prevalence of preschool mental health disorders was estimated in a clinic-based study to be at 7% [ 6].
Women with fasting hyperglycaemia, shown in this study to be at risk of adverse outcomes, would not have been readily identified using a GCT, which relies on a 1 h post-load test only.
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We judged three studies to be at low risk for other potential sources of bias [36, 38, 39].
We judged 67 of 72 studies to be at unclear risk of bias in this domain.
We judged the remaining 62 studies to be at low risk of bias.
We judged eight studies to be at low risk of bias, 41 to be at medium risk, and 24 studies to be at high risk of bias (eTable 1).
We judged two other studies to be at unclear risk of bias due to insufficient information (Jeffery 2007; Stroebele 2009).
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