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The purpose of this study was to determine the most sensitive strategy for the detection of Staphylococcus aureus among pregnant women and newborn infants.
Though stereovision is probably the most immediate, and certainly the most sensitive strategy that the brain has for acquiring information about depth, there are other cues that Bridgeman came to rely on heavily,like shading, perspective and occlusion (if you look at a forest while moving your head, the trees that are farthest away will blink in and out of view behind the ones that are closest).
In other words, compared to the reference strategy, the most sensitive strategy prompted 638 more colonoscopies and detected 12 more cancers and 143 more advanced adenomas.
Considering the false positive causes related to the most sensitive strategy, all datasets shared a very common cause; cases considered "incident cases" by the algorithm that actually were "prevalent cases" (data ranged form 61.1% in MD to 82.3% in GD).
S: sensitivity, PPV: Positive Predictive Value; CI95%: Confidence Interval assuming a type I error of 5% The most sensitive strategy (algorithm 2) was that which used diagnostic codes from position 1 to 5; whereas the most predictive (algorithm 4) (i.e. the highest PPV) was that which considered concurrent diagnoses and procedures from positions 1 to 5 (Table 2).
Identifying the optimal strategy was not the aim of this study; however, although based on a limited sample size, our data suggest that minimising PR (by adopting the most specific strategy) is associated to a substantial loss in the DR, whereas, on the other hand, maximising the DR (by adopting the most sensitive strategy) is associated to hardly acceptable recall rate.
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Those using only diagnostic codes were the most sensitive strategies although sensitivity scored around 25%; those using concurrent information about procedures were the most predictive, although positive predictive value scored close to 50%.
These search terms, in addition to the terms used in our search strategies, were tested to identify the most sensitive search strategy possible.
The most sensitive search strategy used 'floating' subheadings (table 1).
In CDSR the most sensitive search strategy used the 'floating' subheading 'adverse effects' combined with searching for 'adverse near/20 objectives' in the abstract.
The most sensitive search strategy in DARE, with the terms tested here, used a combination of text words in the title and abstract, a MeSH term and 'floating' subheadings (see figure 4).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com