ArticleJournal of Korean medical science2015
Real-time Data Display System of the Korean Neonatal Network.
Article in Journal of Korean medical science, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Improvement in the Survival Rates of Very Low Birth Weight Infants after the Establishment of the Korean Neonatal Network: Comparison between the 2000s and 2010s.Journal of Korean medical science · 2017Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Real-time data reporting in clinical research networks can provide network members through interim analyses of the registered data, which can facilitate further studies and quality improvement activities. The aim of this report was to describe the building process of the data display system (DDS) of the Korean Neonatal Network (KNN) and its basic structure. After member verification at the KNN member's site, users can choose a variable of interest that is listed in the in-hospital data statistics (for 90 variables) or in the follow-up data statistics (for 54 variables). The statistical results of the outcome variables are displayed on the HyperText Markup Language 5-based chart graphs and tables. Participating hospitals can compare their performance to those of KNN as a whole and identify the trends over time. Ranking of each participating hospital is also displayed in terms of key outcome variables such as mortality and major neonatal morbidities with the names of other centers blinded. The most powerful function of the DDS is the ability to perform 'conditional filtering' which allows users to exclusively review the records of interest. Further collaboration is needed to upgrade the DDS to a more sophisticated analytical system and to provide a more user-friendly interface.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.