ArticleProceedings. IEEE International Conference on Bioinformatics and Biomedicine2019
Using Machine Learning to Predict Hyperchloremia in Critically Ill Patients.
Article in Proceedings. IEEE International Conference on Bioinformatics and Biomedicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed, 3 citations in OpenAlex.
- Hyperchloremia in critically ill patients: association with outcomes and prediction using electronic health record data.BMC medical informatics and decision making · 2020Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Elevated serum chloride levels (hyperchloremia) and the administration of intravenous (IV) fluids with high chloride content have both been associated with increased morbidity and mortality in certain subgroups of critically ill patients, such as those with sepsis. Here, we demonstrate this association in a general intensive care unit (ICU) population using data from the Medical Information Mart for Intensive Care III (MIMIC-III) database and propose the use of supervised learning to predict hyperchloremia in critically ill patients. Clinical variables from records of the first 24h of adult ICU stays were represented as features for four predictive supervised learning classifiers. The best performing model was able to predict second-day hyperchloremia with an AUC of 0.80 and a ratio of 5 false alerts for every true alert, which is a clinically-actionable rate. Our results suggest that clinicians can be effectively alerted to patients at risk of developing hyperchloremia, providing an opportunity to mitigate this risk and potentially improve outcomes.
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Registered trials
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