A web-based tool to predict acute kidney injury in patients with ST-elevation myocardial infarction: Development, internal validation and comparison

Autor: Inyong Hwang, Rami N. Khouzam, Darshan Naik, Mason Chumpia, Guy L. Reed, Fridtjof Thomas, Robert T. Ellis, Uzoma N. Ibebuogu, Benjamin R. Zambetti, Allen C. Brown
Rok vydání: 2017
Předmět:
Male
Medical Doctors
medicine.medical_treatment
Health Care Providers
lcsh:Medicine
030204 cardiovascular system & hematology
Cardiovascular Medicine
urologic and male genital diseases
Severity of Illness Index
Biochemistry
Diagnostic Radiology
0302 clinical medicine
Medicine and Health Sciences
030212 general & internal medicine
Myocardial infarction
Diagnosis
Computer-Assisted
Cardiovascular Imaging
lcsh:Science
Multidisciplinary
Radiology and Imaging
Acute kidney injury
Area under the curve
Angiography
Acute Kidney Injury
Middle Aged
female genital diseases and pregnancy complications
Hospitals
Professions
Treatment Outcome
Area Under Curve
Creatinine
Cohort
Cardiology
Female
Anatomy
Algorithms
Research Article
Risk
medicine.medical_specialty
Systole
Imaging Techniques
Death Rates
Research and Analysis Methods
Sensitivity and Specificity
03 medical and health sciences
Percutaneous Coronary Intervention
Diagnostic Medicine
Internal medicine
Physicians
Severity of illness
medicine
Humans
Aged
Retrospective Studies
Demography
Internet
business.industry
urogenital system
lcsh:R
Percutaneous coronary intervention
Reproducibility of Results
Biology and Life Sciences
Retrospective cohort study
Kidneys
Renal System
medicine.disease
Health Care
Health Care Facilities
People and Places
ST Elevation Myocardial Infarction
lcsh:Q
Population Groupings
Health Statistics
Morbidity
business
Biomarkers
Zdroj: PLoS ONE
PLoS ONE, Vol 12, Iss 7, p e0181658 (2017)
ISSN: 1932-6203
Popis: Background In ST-elevation myocardial infarction (STEMI), acute kidney injury (AKI) may increase subsequent morbidity and mortality. Still, it remains difficult to predict AKI risk in these patients. We sought to 1) determine the frequency and clinical outcomes of AKI and, 2) develop, validate and compare a web-based tool for predicting AKI. Methods & findings In a racially diverse series of 1144 consecutive STEMI patients, Stage 1 or greater AKI occurred in 12.9% and was severe (Stage 2-3) in 2.9%. AKI was associated with increased mortality (5.7-fold, unadjusted) and hospital stay (2.5-fold). AKI was associated with systolic dysfunction, increased left ventricular end-diastolic pressures, hypotension and intra-aortic balloon counterpulsation. A computational algorithm (UT-AKI) was derived and internally validated. It showed higher sensitivity and improved overall prediction for AKI (area under the curve 0.76) vs. other published indices. Higher UT-AKI scores were associated with more severe AKI, longer hospital stay and greater hospital mortality. Conclusions In a large, racially diverse cohort of STEMI patients, Stage 1 or greater AKI was relatively common and was associated with significant morbidity and mortality. A web-accessible, internally validated tool was developed with improved overall value for predicting AKI. By identifying patients at increased risk, this tool may help physicians tailor post-procedural diagnostic and therapeutic strategies after STEMI to reduce AKI and its associated morbidity and mortality.
Databáze: OpenAIRE
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