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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
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1 to 2 of 2 Research Studies DisplayedMartinez DA, Levin SR, Klein EY
Early prediction of acute kidney injury in the emergency department with machine-learning methods applied to electronic health record data.
Researchers analyzed routinely collected emergency department (ED) data and developed prediction models with capacity for early identification of ED patients at high risk for acute kidney injury. They found that machine learning applied to routinely-collected ED data identified ED patients at high risk for acute kidney injury up to 72 hours before they met diagnostic criteria. They recommended further prospective evaluation.
AHRQ-funded; HS027793.
Citation: Martinez DA, Levin SR, Klein EY .
Early prediction of acute kidney injury in the emergency department with machine-learning methods applied to electronic health record data.
Ann Emerg Med 2020 Oct;76(4):501-14. doi: 10.1016/j.annemergmed.2020.05.026..
Keywords: Kidney Disease and Health, Emergency Department, Electronic Health Records (EHRs), Health Information Technology (HIT)
Daniels B, Gross CP, Molinaro A
STONE PLUS: evaluation of emergency department patients with suspected renal colic, using a clinical prediction tool combined with point-of-care limited ultrasonography.
This study sought to determine whether renal point-of-care limited ultrasonography (PLUS) used in conjunction with the Sex, Timing, Origin, Nausea, Erythrocytes (STONE) clinical prediction score can aid identification of emergency department (ED) patients with uncomplicated ureteral stone or need for urologic intervention. It concluded that hydronephrosis on renal PLUS modestly improved risk stratification in low- and moderate-risk STONE score patients.
AHRQ-funded; HS018322.
Citation: Daniels B, Gross CP, Molinaro A .
STONE PLUS: evaluation of emergency department patients with suspected renal colic, using a clinical prediction tool combined with point-of-care limited ultrasonography.
Ann Emerg Med 2016 Apr;67(4):439-48. doi: 10.1016/j.annemergmed.2015.10.020.
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Keywords: Shared Decision Making, Emergency Department, Imaging, Kidney Disease and Health