ABSTRACT
BACKGROUND: Pooled testing for Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) may be a cost-saving solution to increase screening by simplifying testing procedures and reducing resource burdens. We conducted a systematic review and meta-analysis to examine the performance of pooled 3-anatomic-site testing (pharyngeal, rectal, and urogenital sites) for CT and NG in comparison with single-anatomic-site testing. METHODS: We conducted a systematic literature search in PubMed, Embase, and Web of Science to identify original evaluation studies of the performance of pooled testing for CT and NG infections and identified 14 studies for inclusion. Each study was systematically evaluated for bias. We conducted bivariate fixed-effects and random-effects meta-analyses using a full Bayesian method of the positive percent agreement and negative percent agreement. RESULTS: The combined positive percent agreement for CT was 93.11% (95% confidence interval [CI], 91.51%-94.55%), and the negative percent agreement was 99.44% (95% CI, 99.18%-99.65%). For NG, the combined positive percent agreement was 93.80% (95% CI, 90.26%-96.61%), and the negative percent agreement was 99.73% (95% CI, 99.30%-99.97%). CONCLUSIONS: We found that pooled 3-anatomic-site tests performed similarly to single-anatomic-site tests for the detection of CT and NG. The pooled 3-anatomic-site tests have the added potential benefit of reduced cost and resource requirement, which could lead to improved testing access and screening uptake.
Subject(s)
Chlamydia Infections , Gonorrhea , Bayes Theorem , Chlamydia Infections/diagnosis , Chlamydia trachomatis , Gonorrhea/diagnosis , Humans , Neisseria gonorrhoeaeABSTRACT
When people use samples of evidence to make inferences, they consider both the sample contents and how the sample was generated ("sampling assumptions"). The current studies examined whether people can update their sampling assumptions - whether they can revise a belief about sample generation that is discovered to be incorrect, and reinterpret old data in light of the new belief. We used a property induction task where learners saw a sample of instances that shared a novel property and then inferred whether it generalized to other items. Assumptions about how the sample was selected were manipulated between conditions: in the property sampling frame condition, items were selected because they shared a property, while in the category sampling frame condition, items were selected because they belonged to a particular category. Experiment 1 found that these frames affected patterns of property generalization regardless of whether they were presented before or after the sample data was observed: in both cases, generalization was narrower under a property than a category frame. In Experiments 2 and 3, an initial category or property frame was presented before the sample, and was later retracted and replaced with the complementary frame. Learners were able to update their beliefs about sample generation, basing their property generalization on the more recent correct frame. These results show that learners can revise incorrect beliefs about data selection and adjust their inductive inferences accordingly.
Subject(s)
Generalization, Psychological , HumansABSTRACT
OBJECTIVE: To identify the disease-causing mutation in a large 3 generation pedigree of X-linked congenital nystagmus. METHODS: Twenty-three members of a single pedigree, including 7 affected males, 2 affected females, 5 obligate carriers, and 9 unaffected family members were tested for mutations in the FRMD7 gene using PCR-based DNA sequencing assays and multiplex PCR assays for deletions. RESULTS: A hemizygous deletion of exons 2, 3, and 4 of FRMD7 was detected in all affected males in the family and was absent from 40 control subjects. CONCLUSIONS: A range of missense, nonsense, frameshift, and splicing mutations in FRMD7 have been shown to cause X-linked congenital nystagmus. Here we show for the first time that large intragenic deletions of FRMD7 can also cause this form of nystagmus.