Optimizing identification of resistant hypertension: Computable phenotype development and validation.
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| Title: | Optimizing identification of resistant hypertension: Computable phenotype development and validation. |
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| Authors: | McDonough CW; Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, Florida, USA., Babcock K; Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, Florida, USA., Chucri K; Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, Florida, USA., Crawford DC; Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio, USA., Bian J; Department of Health Outcomes & Biomedical Informatics, College of Medicine, University of Florida, Gainesville, Florida, USA., Modave F; Department of Health Outcomes & Biomedical Informatics, College of Medicine, University of Florida, Gainesville, Florida, USA., Cooper-DeHoff RM; Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, Florida, USA.; Division of Cardiovascular Medicine, Department of Medicine, College of Medicine, University of Florida, Gainesville, Florida, USA., Hogan WR; Department of Health Outcomes & Biomedical Informatics, College of Medicine, University of Florida, Gainesville, Florida, USA. |
| Source: | Pharmacoepidemiology and drug safety [Pharmacoepidemiol Drug Saf] 2020 Nov; Vol. 29 (11), pp. 1393-1401. Date of Electronic Publication: 2020 Aug 26. |
| Publication Type: | Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Wiley Country of Publication: England NLM ID: 9208369 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1099-1557 (Electronic) Linking ISSN: 10538569 NLM ISO Abbreviation: Pharmacoepidemiol Drug Saf Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1099-1557 |
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| DOI: | 10.1002/pds.5095 |
