FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2981937324> ?p ?o ?g. }

• W2981937324 endingPage "e0226518" @default.
• W2981937324 startingPage "e0226518" @default.
• W2981937324 abstract "The triage of patients in prehospital care is a difficult task, and improved risk assessment tools are needed both at the dispatch center and on the ambulance to differentiate between low- and high-risk patients. This study validates a machine learning-based approach to generating risk scores based on hospital outcomes using routinely collected prehospital data.Dispatch, ambulance, and hospital data were collected in one Swedish region from 2016-2017. Dispatch center and ambulance records were used to develop gradient boosting models predicting hospital admission, critical care (defined as admission to an intensive care unit or in-hospital mortality), and two-day mortality. Composite risk scores were generated based on the models and compared to National Early Warning Scores (NEWS) and actual dispatched priorities in a prospectively gathered dataset from 2018.A total of 38203 patients were included from 2016-2018. Concordance indexes (or areas under the receiver operating characteristics curve) for dispatched priorities ranged from 0.51-0.66, while those for NEWS ranged from 0.66-0.85. Concordance ranged from 0.70-0.79 for risk scores based only on dispatch data, and 0.79-0.89 for risk scores including ambulance data. Dispatch data-based risk scores consistently outperformed dispatched priorities in predicting hospital outcomes, while models including ambulance data also consistently outperformed NEWS. Model performance in the prospective test dataset was similar to that found using cross-validation, and calibration was comparable to that of NEWS.Machine learning-based risk scores outperformed a widely-used rule-based triage algorithm and human prioritization decisions in predicting hospital outcomes. Performance was robust in a prospectively gathered dataset, and scores demonstrated adequate calibration. Future research should explore the robustness of these methods when applied to other settings, establish appropriate outcome measures for use in determining the need for prehospital care, and investigate the clinical impact of interventions based on these methods." @default.
• W2981937324 created "2019-11-01" @default.
• W2981937324 creator A5009497973 @default.
• W2981937324 creator A5011381332 @default.
• W2981937324 creator A5065983774 @default.
• W2981937324 creator A5070317638 @default.
• W2981937324 date "2019-12-13" @default.
• W2981937324 modified "2023-10-14" @default.
• W2981937324 title "A validation of machine learning-based risk scores in the prehospital setting" @default.
• W2981937324 cites W1869193869 @default.
• W2981937324 cites W1973165025 @default.
• W2981937324 cites W1979646028 @default.
• W2981937324 cites W1986147098 @default.
• W2981937324 cites W1991991793 @default.
• W2981937324 cites W1998536898 @default.
• W2981937324 cites W2003613567 @default.
• W2981937324 cites W2008274261 @default.
• W2981937324 cites W2010369956 @default.
• W2981937324 cites W2022147694 @default.
• W2981937324 cites W2024784120 @default.
• W2981937324 cites W2027360550 @default.
• W2981937324 cites W2039770044 @default.
• W2981937324 cites W2044483834 @default.
• W2981937324 cites W2045352610 @default.
• W2981937324 cites W2052945001 @default.
• W2981937324 cites W2056573627 @default.
• W2981937324 cites W2071731535 @default.
• W2981937324 cites W2078271269 @default.
• W2981937324 cites W2082780796 @default.
• W2981937324 cites W2104436528 @default.
• W2981937324 cites W2116971285 @default.
• W2981937324 cites W2135004706 @default.
• W2981937324 cites W2144497181 @default.
• W2981937324 cites W2153630089 @default.
• W2981937324 cites W2174265856 @default.
• W2981937324 cites W2178634243 @default.
• W2981937324 cites W2290507636 @default.
• W2981937324 cites W2345073978 @default.
• W2981937324 cites W2346292157 @default.
• W2981937324 cites W2474618558 @default.
• W2981937324 cites W2752349109 @default.
• W2981937324 cites W2770001088 @default.
• W2981937324 cites W2785330135 @default.
• W2981937324 cites W2807025383 @default.
• W2981937324 cites W2810708119 @default.
• W2981937324 cites W2883629144 @default.
• W2981937324 cites W2884597820 @default.
• W2981937324 cites W2888109941 @default.
• W2981937324 cites W2888830143 @default.
• W2981937324 cites W2898595620 @default.
• W2981937324 cites W2903513497 @default.
• W2981937324 cites W2910432161 @default.
• W2981937324 cites W2910885668 @default.
• W2981937324 cites W2913423234 @default.
• W2981937324 cites W2929110666 @default.
• W2981937324 cites W2950373907 @default.
• W2981937324 cites W2952047734 @default.
• W2981937324 cites W3098949126 @default.
• W2981937324 cites W3102476541 @default.
• W2981937324 cites W3124151764 @default.
• W2981937324 cites W4229771528 @default.
• W2981937324 cites W4298872162 @default.
• W2981937324 doi "https://doi.org/10.1371/journal.pone.0226518" @default.
• W2981937324 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6910679" @default.
• W2981937324 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31834920" @default.
• W2981937324 hasPublicationYear "2019" @default.
• W2981937324 type Work @default.
• W2981937324 sameAs 2981937324 @default.
• W2981937324 citedByCount "32" @default.
• W2981937324 countsByYear W29819373242020 @default.
• W2981937324 countsByYear W29819373242021 @default.
• W2981937324 countsByYear W29819373242022 @default.
• W2981937324 countsByYear W29819373242023 @default.
• W2981937324 crossrefType "journal-article" @default.
• W2981937324 hasAuthorship W2981937324A5009497973 @default.
• W2981937324 hasAuthorship W2981937324A5011381332 @default.
• W2981937324 hasAuthorship W2981937324A5065983774 @default.
• W2981937324 hasAuthorship W2981937324A5070317638 @default.
• W2981937324 hasBestOaLocation W29819373241 @default.
• W2981937324 hasConcept C11783203 @default.
• W2981937324 hasConcept C119857082 @default.
• W2981937324 hasConcept C12174686 @default.
• W2981937324 hasConcept C126322002 @default.
• W2981937324 hasConcept C142724271 @default.
• W2981937324 hasConcept C160798450 @default.
• W2981937324 hasConcept C177713679 @default.
• W2981937324 hasConcept C194828623 @default.
• W2981937324 hasConcept C2776376669 @default.
• W2981937324 hasConcept C2777120189 @default.
• W2981937324 hasConcept C2777671062 @default.
• W2981937324 hasConcept C2779134260 @default.
• W2981937324 hasConcept C38652104 @default.
• W2981937324 hasConcept C41008148 @default.
• W2981937324 hasConcept C545542383 @default.
• W2981937324 hasConcept C58471807 @default.
• W2981937324 hasConcept C71924100 @default.
• W2981937324 hasConceptScore W2981937324C11783203 @default.
• W2981937324 hasConceptScore W2981937324C119857082 @default.

• next