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Skrupky LP, Stevens RW, Virk A, Tande AJ, Oyen LJ, Cook DA. Personalisation and embodiment in e-Learning for health professionals: A randomised controlled trial. Med Educ 2024; 58:566-574. [PMID: 37655515 DOI: 10.1111/medu.15198] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 07/30/2023] [Accepted: 08/14/2023] [Indexed: 09/02/2023]
Abstract
PURPOSE Mayer's theory of multimedia learning proposes that personalisation and embodiment (P/E) can improve outcomes in e-Learning. The authors hypothesised that an e-Learning module enhanced by P/E principles would lead to higher knowledge, perceived P/E and motivation among health care professionals, compared with an unenhanced module. METHODS The authors conducted a randomised trial comparing two versions of a 30-minute multimedia e-Learning module addressing the antibiotic management of pneumonia. The unenhanced format used slides with voiceover (human voice but no visible speaker), formal language and no specific P/E strategies. The enhanced format additionally implemented P/E strategies including conversational style, polite language, visible author, social congruence, human-like presence and professional presence by subtly changing the script and substituting several short videos of subject matter experts. Participants included pharmacists, physicians and advanced practice providers from three academic and several community hospitals. Outcomes included knowledge, perceived P/E (assessed by the Congruence Personalisation Questionnaire, CPQ), motivation (assessed via the Instructional Materials Motivation Survey [IMMS] and Motivated Strategies for Learning Questionnaire [MSLQ]) and course satisfaction. RESULTS There were 406 participants including 225 pharmacists, 109 physicians and 72 advanced practice providers. Post-module knowledge was slightly higher for the enhanced versus the unenhanced format, but the difference did not reach statistical significance (adjusted mean difference, 0.04 of 10 possible, [95% CI -0.26, 0.34], p = 0.78; Cohen d 0.02). Participant perceptions of P/E (measured via CPQ) were significantly greater for the enhanced format (difference 0.46 of 5 possible [0.35, 0.56], p < 0.001; Cohen d 0.85), as were motivational features of the e-Learning course (measured via IMMS) (difference 0.14 of 5 possible [0.02, 0.26], p = 0.02; Cohen d 0.24). Participants' overall motivational orientation (measured via MSLQ) and course satisfaction were not significantly different between the two formats (p > 0.05). CONCLUSION Application of P/E principles to an e-Learning module led to greater perceived P/E and motivational features but did not influence knowledge.
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Affiliation(s)
- Lee P Skrupky
- Center for Clinical Knowledge Management, University of Wisconsin Health, Madison, Wisconsin, USA
| | - Ryan W Stevens
- Department of Pharmacy, Mayo Clinic, Rochester, Minnesota, USA
| | - Abinash Virk
- Division of Public Health, Infectious Diseases and Occupational Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Aaron J Tande
- Division of Public Health, Infectious Diseases and Occupational Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Lance J Oyen
- Department of Pharmacy, Mayo Clinic, Rochester, Minnesota, USA
| | - David A Cook
- Office of Applied Scholarship and Education Science, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA
- Division of General Internal Medicine, Mayo Clinic, Rochester, Minnesota, USA
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2
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Nuttall GA, Reed AM, Pham Louis KD, Oyen LJ, Marsland SP, Ackerman MJ. The Incidence of Torsades de Pointes With Perioperative Triple Antiemetic Administration. Ann Pharmacother 2023:10600280231215786. [PMID: 38053391 DOI: 10.1177/10600280231215786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/07/2023] Open
Abstract
BACKGROUND The safety of triple antiemetic therapy consisting of ondansetron, haloperidol, and a steroid, to surgical patients is unknown. OBJECTIVE To determine the incidence of torsade de pointes (TdP) or death following perioperative administration of triple antiemetic therapy. METHODS A retrospective cohort study identified 19,874 patients who received 22,202 doses of triple antiemetics during the 2.5-year time frame from March 4, 2020 to September 7, 2022 for surgical nausea prophylaxis or treatment of nausea. These patients above were cross-matched with an electrocardiogram and adverse outcome database; this identified 226 patients with documentation of a QTc > 450 ms, all ventricular tachycardias including TdP within 48 hours of receiving triple antiemetic therapy, or death within 7 days of receiving ondansetron. RESULTS There were 3 patients who had documented VT (n = 3), but there were no documented incidents of TdP (n = 0). There were 9 codes called on patients within 48 hours of medication administration, and none of them were due to ventricular arrythmias (n = 0). A total of 11 patients died within 7 days of triple antiemetic therapy. Ten of the 11 deaths were determined to not be from the triple antiemetic. One patient died at home within 24 hours of the procedure of an unknown cause (n = 1). CONCLUSIONS AND RELEVANCE No episodes of TdP were identified in patients receiving triple antiemetic therapy perioperatively, though the cause of death in 1 patient could not be determined. This suggest that low-dose triple antiemetic therapy is low risk for the development of TdP.
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Affiliation(s)
- Gregory A Nuttall
- Department of Anesthesiology, Mayo Clinic College of Medicine and Science, Mayo Foundation, Rochester, MN, USA
| | - Alyssa M Reed
- Mayo School of Health Sciences, Mayo Foundation, Rochester, MN, USA
| | | | - Lance J Oyen
- Mayo Clinic College of Medicine and Science, Mayo Foundation, Rochester, MN, USA
| | | | - Michael J Ackerman
- Mayo Clinic College of Medicine and Science, Mayo Foundation, Rochester, MN, USA
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3
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Wang L, Scherer SE, Bielinski SJ, Muzny DM, Jones LA, Black JL, Moyer AM, Giri J, Sharp RR, Matey ET, Wright JA, Oyen LJ, Nicholson WT, Wiepert M, Sullard T, Curry TB, Vitek CRR, McAllister TM, Sauver JL, Caraballo PJ, Lazaridis KN, Venner E, Qin X, Hu J, Kovar CL, Korchina V, Walker K, Doddapaneni H, Wu TJ, Raj R, Denson S, Liu W, Chandanavelli G, Zhang L, Wang Q, Kalra D, Karow MB, Harris KJ, Sicotte H, Peterson SE, Barthel AE, Moore BE, Skierka JM, Kluge ML, Kotzer KE, Kloke K, Vander Pol JM, Marker H, Sutton JA, Kekic A, Ebenhoh A, Bierle DM, Schuh MJ, Grilli C, Erickson S, Umbreit A, Ward L, Crosby S, Nelson EA, Levey S, Elliott M, Peters SG, Pereira N, Frye M, Shamoun F, Goetz MP, Kullo IJ, Wermers R, Anderson JA, Formea CM, El Melik RM, Zeuli JD, Herges JR, Krieger CA, Hoel RW, Taraba JL, Thomas SR, Absah I, Bernard ME, Fink SR, Gossard A, Grubbs PL, Jacobson TM, Takahashi P, Zehe SC, Buckles S, Bumgardner M, Gallagher C, Fee-Schroeder K, Nicholas NR, Powers ML, Ragab AK, Richardson DM, Stai A, Wilson J, Pacyna JE, Olson JE, Sutton EJ, Beck AT, Horrow C, Kalari KR, Larson NB, Liu H, Wang L, Lopes GS, Borah BJ, Freimuth RR, Zhu Y, Jacobson DJ, Hathcock MA, Armasu SM, McGree ME, Jiang R, Koep TH, Ross JL, Hilden M, Bosse K, Ramey B, Searcy I, Boerwinkle E, Gibbs RA, Weinshilboum RM. Implementation of preemptive DNA sequence-based pharmacogenomics testing across a large academic medical center: The Mayo-Baylor RIGHT 10K Study. Genet Med 2022; 24:1062-1072. [PMID: 35331649 PMCID: PMC9272414 DOI: 10.1016/j.gim.2022.01.022] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 01/25/2022] [Accepted: 01/26/2022] [Indexed: 12/12/2022] Open
Abstract
PURPOSE The Mayo-Baylor RIGHT 10K Study enabled preemptive, sequence-based pharmacogenomics (PGx)-driven drug prescribing practices in routine clinical care within a large cohort. We also generated the tools and resources necessary for clinical PGx implementation and identified challenges that need to be overcome. Furthermore, we measured the frequency of both common genetic variation for which clinical guidelines already exist and rare variation that could be detected by DNA sequencing, rather than genotyping. METHODS Targeted oligonucleotide-capture sequencing of 77 pharmacogenes was performed using DNA from 10,077 consented Mayo Clinic Biobank volunteers. The resulting predicted drug response-related phenotypes for 13 genes, including CYP2D6 and HLA, affecting 21 drug-gene pairs, were deposited preemptively in the Mayo electronic health record. RESULTS For the 13 pharmacogenes of interest, the genomes of 79% of participants carried clinically actionable variants in 3 or more genes, and DNA sequencing identified an average of 3.3 additional conservatively predicted deleterious variants that would not have been evident using genotyping. CONCLUSION Implementation of preemptive rather than reactive and sequence-based rather than genotype-based PGx prescribing revealed nearly universal patient applicability and required integrated institution-wide resources to fully realize individualized drug therapy and to show more efficient use of health care resources.
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Affiliation(s)
- Liewei Wang
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN,Division of Clinical Pharmacology, Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN
| | - Steven E. Scherer
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX
| | - Suzette J. Bielinski
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Donna M. Muzny
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Leila A. Jones
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | - John Logan Black
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Ann M. Moyer
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Jyothsna Giri
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | | | | | | | | | - Wayne T. Nicholson
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN
| | - Mathieu Wiepert
- Department of Information Technology, Mayo Clinic, Rochester, MN
| | - Terri Sullard
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | - Timothy B. Curry
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN,Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN
| | | | | | - Jennifer L. Sauver
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN,Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN
| | - Pedro J. Caraballo
- Division of General Internal Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | - Konstantinos N. Lazaridis
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN,Division of Gastroenterology and Hepatology, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | - Eric Venner
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Xiang Qin
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
| | - Jianhong Hu
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Christie L. Kovar
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Viktoriya Korchina
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Kimberly Walker
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | | | - Tsung-Jung Wu
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Ritika Raj
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Shawn Denson
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Wen Liu
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Gauthami Chandanavelli
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Lan Zhang
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Qiaoyan Wang
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
| | - Divya Kalra
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
| | - Mary Beth Karow
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | | | - Hugues Sicotte
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Sandra E. Peterson
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Amy E. Barthel
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Brenda E. Moore
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | | | - Michelle L. Kluge
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Katrina E. Kotzer
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Karen Kloke
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | | | - Heather Marker
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | - Joseph A. Sutton
- Department of Information Technology, Mayo Clinic, Rochester, MN
| | | | | | - Dennis M. Bierle
- Division of General Internal Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | | | | | | | - Audrey Umbreit
- Department of Pharmacy, Mayo Clinic Health System, Mankato, MN
| | - Leah Ward
- Department of Pharmacy, Mayo Clinic, Jacksonville, FL
| | - Sheena Crosby
- Department of Pharmacy, Mayo Clinic, Jacksonville, FL
| | | | - Sharon Levey
- Department of Clinical Genomics, Mayo Clinic, Scottsdale, AZ
| | - Michelle Elliott
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | - Steve G. Peters
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | - Naveen Pereira
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
| | - Mark Frye
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN
| | - Fadi Shamoun
- Department of Cardiovascular Medicine Mayo Clinic, Phoenix, AZ
| | - Matthew P. Goetz
- Division of Medical Oncology, Department of Oncology, Mayo Clinic, Rochester, MN
| | | | - Robert Wermers
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | | | | | | | | | | | | | | | | | - Scott R. Thomas
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | - Imad Absah
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | | | - Stephanie R. Fink
- Division of Community Internal Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | - Andrea Gossard
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | | | | | - Paul Takahashi
- Division of Community Internal Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | | | - Susan Buckles
- Department of Public Affairs, Mayo Clinic, Rochester, MN
| | | | | | | | | | - Melody L. Powers
- Biospecimens Accessioning and Processing Laboratory, Mayo Clinic, Rochester, MN
| | - Ahmed K. Ragab
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | | | - Anthony Stai
- Department of Information Technology, Mayo Clinic, Rochester, MN
| | - Jaymi Wilson
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | - Joel E. Pacyna
- Biomedical Ethics Research Program, Mayo Clinic, Rochester, MN
| | - Janet E. Olson
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN,Biomedical Ethics Research Program, Mayo Clinic, Rochester, MN
| | - Erica J. Sutton
- Biomedical Ethics Research Program, Mayo Clinic, Rochester, MN
| | - Annika T. Beck
- Biomedical Ethics Research Program, Mayo Clinic, Rochester, MN
| | - Caroline Horrow
- Biomedical Ethics Research Program, Mayo Clinic, Rochester, MN
| | - Krishna R. Kalari
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Nicholas B. Larson
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Hongfang Liu
- Division of Digital Health Sciences, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Liwei Wang
- Division of Digital Health Sciences, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Guilherme S. Lopes
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN,Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Bijan J. Borah
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN,Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Robert R. Freimuth
- Division of Digital Health Sciences, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Ye Zhu
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN
| | - Debra J. Jacobson
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Matthew A. Hathcock
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Sebastian M. Armasu
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Michaela E. McGree
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Ruoxiang Jiang
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | | | | | | | | | | | | | - Eric Boerwinkle
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX,Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX,School of Public Health, University of Texas Health Science Center at Houston, Houston, TX
| | - Richard A. Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX,Corresponding Authors (), ()
| | - Richard M. Weinshilboum
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN,Division of Clinical Pharmacology, Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN,Corresponding Authors (), ()
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4
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Nuttall GA, Voogd SC, Danke H, Warner PA, Oyen LJ, Marienau MS, Ackerman MJ. The incidence of torsades de pointes with peri‐operative low‐dose ondansetron administration. Pharmacotherapy 2022; 42:292-297. [DOI: 10.1002/phar.2668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 12/20/2021] [Accepted: 12/21/2021] [Indexed: 11/10/2022]
Affiliation(s)
- Gregory A. Nuttall
- Department of Anesthesiology Mayo Clinic College of Medicine Rochester Minnesota USA
| | - Sarah C. Voogd
- Department of Anesthesiology Mayo Clinic College of Medicine Rochester Minnesota USA
| | - Heather Danke
- Department of Anesthesiology Mayo Clinic College of Medicine Rochester Minnesota USA
| | - Paul A. Warner
- Department of Anesthesiology Mayo Clinic College of Medicine Rochester Minnesota USA
| | - Lance J. Oyen
- Department of Pharmacy Mayo Clinic College of Medicine Rochester Minnesota USA
| | - Mary Shirk Marienau
- Department of Anesthesiology Nurse Anesthesia Program Mayo Clinic College of Medicine Rochester Minnesota USA
| | - Michael J. Ackerman
- Department of Medicine, Pediatrics and Pharmacology Mayo Clinic College of Medicine Rochester Minnesota USA
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5
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McBane RD, Torres Roldan VD, Niven AS, Pruthi RK, Franco PM, Linderbaum JA, Casanegra AI, Oyen LJ, Houghton DE, Marshall AL, Ou NN, Siegel JL, Wysokinski WE, Padrnos LJ, Rivera CE, Flo GL, Shamoun FE, Silvers SM, Nayfeh T, Urtecho M, Shah S, Benkhadra R, Saadi SM, Firwana M, Jawaid T, Amin M, Prokop LJ, Murad MH. Anticoagulation in COVID-19: A Systematic Review, Meta-analysis, and Rapid Guidance From Mayo Clinic. Mayo Clin Proc 2020; 95:2467-2486. [PMID: 33153635 PMCID: PMC7458092 DOI: 10.1016/j.mayocp.2020.08.030] [Citation(s) in RCA: 72] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Revised: 07/04/2020] [Accepted: 08/26/2020] [Indexed: 12/16/2022]
Abstract
A higher risk of thrombosis has been described as a prominent feature of coronavirus disease 2019 (COVID-19). This systematic review synthesizes current data on thrombosis risk, prognostic implications, and anticoagulation effects in COVID-19. We included 37 studies from 4070 unique citations. Meta-analysis was performed when feasible. Coagulopathy and thrombotic events were frequent among patients with COVID-19 and further increased in those with more severe forms of the disease. We also present guidance on the prevention and management of thrombosis from a multidisciplinary panel of specialists from Mayo Clinic. The current certainty of evidence is generally very low and continues to evolve.
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Key Words
- aptt, activated thromboplastin time
- covid-19, coronavirus disease 2019
- dic, disseminated intravascular coagulation
- doac, direct oral anticoagulant
- dvt, deep venous thrombosis
- icu, intensive care unit
- lmwh, low-molecular-weight heparin
- or, odds ratio
- pe, pulmonary embolism
- pt, prothrombin time
- sars-cov, severe acute respiratory syndrome coronavirus
- sc, subcutaneously
- vte, venous thromboembolism
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Affiliation(s)
- Robert D McBane
- Gonda Vascular Center, Mayo Clinic, Rochester, MN; Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
| | - Victor D Torres Roldan
- Evidence-based Practice Center and Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN
| | - Alexander S Niven
- Division of Pulmonary and Critical Care, Center for Sleep Medicine, Mayo Clinic, Rochester, MN
| | - Rajiv K Pruthi
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN; Division of Hematology, Mayo Clinic, Rochester, MN
| | | | | | - Ana I Casanegra
- Gonda Vascular Center, Mayo Clinic, Rochester, MN; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
| | - Lance J Oyen
- Department of Pharmacy, Mayo Clinic, Rochester, MN
| | - Damon E Houghton
- Gonda Vascular Center, Mayo Clinic, Rochester, MN; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
| | - Ariela L Marshall
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN; Division of Hematology, Mayo Clinic, Rochester, MN
| | - Narith N Ou
- Department of Pharmacy, Mayo Clinic, Rochester, MN
| | | | - Waldemar E Wysokinski
- Gonda Vascular Center, Mayo Clinic, Rochester, MN; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
| | | | - Candido E Rivera
- Division of Hematology and Medical Oncology, Mayo Clinic, Jacksonville, FL
| | - Gayle L Flo
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
| | - Fadi E Shamoun
- Department of Cardiovascular Medicine, Mayo Clinic, Scottsdale, AZ
| | - Scott M Silvers
- Department of Emergency Medicine, Mayo Clinic, Jacksonville, FL
| | - Tarek Nayfeh
- Evidence-based Practice Center and Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN
| | - Meritxell Urtecho
- Evidence-based Practice Center and Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN
| | - Sahrish Shah
- Evidence-based Practice Center and Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN
| | - Raed Benkhadra
- Evidence-based Practice Center and Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN
| | - Samer Mohir Saadi
- Evidence-based Practice Center and Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN
| | - Mohammed Firwana
- Evidence-based Practice Center and Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN
| | - Tabinda Jawaid
- Evidence-based Practice Center and Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN
| | - Mustapha Amin
- Evidence-based Practice Center and Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN
| | | | - M Hassan Murad
- Evidence-based Practice Center and Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN.
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6
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Bielinski SJ, St Sauver JL, Olson JE, Larson NB, Black JL, Scherer SE, Bernard ME, Boerwinkle E, Borah BJ, Caraballo PJ, Curry TB, Doddapaneni H, Formea CM, Freimuth RR, Gibbs RA, Giri J, Hathcock MA, Hu J, Jacobson DJ, Jones LA, Kalla S, Koep TH, Korchina V, Kovar CL, Lee S, Liu H, Matey ET, McGree ME, McAllister TM, Moyer AM, Muzny DM, Nicholson WT, Oyen LJ, Qin X, Raj R, Roger VL, Rohrer Vitek CR, Ross JL, Sharp RR, Takahashi PY, Venner E, Walker K, Wang L, Wang Q, Wright JA, Wu TJ, Wang L, Weinshilboum RM. Cohort Profile: The Right Drug, Right Dose, Right Time: Using Genomic Data to Individualize Treatment Protocol (RIGHT Protocol). Int J Epidemiol 2020; 49:23-24k. [PMID: 31378813 PMCID: PMC7124480 DOI: 10.1093/ije/dyz123] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/31/2019] [Indexed: 12/29/2022] Open
Affiliation(s)
- Suzette J Bielinski
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Jennifer L St Sauver
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
- Robert D and Patricia E Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA
| | - Janet E Olson
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
| | - Nicholas B Larson
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - John L Black
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Steven E Scherer
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | | | - Eric Boerwinkle
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Bijan J Borah
- Robert D and Patricia E Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA
- Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Pedro J Caraballo
- Division of General Internal Medicine, Department of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Timothy B Curry
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
- Department of Anesthesia and Perioperative Medicine, Mayo Clinic, Rochester, MN, USA
| | | | | | - Robert R Freimuth
- Division of Digital Health Sciences, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Richard A Gibbs
- Human Genome Sequencing Center, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Jyothsna Giri
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
| | - Matthew A Hathcock
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Jianhong Hu
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Debra J Jacobson
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Leila A Jones
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
| | - Sara Kalla
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | | | - Viktoriya Korchina
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Christie L Kovar
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Sandra Lee
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Hongfang Liu
- Division of Digital Health Sciences, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Eric T Matey
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
- Department of Pharmacy, Mayo Clinic, Rochester, MN, USA
| | - Michaela E McGree
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | | | - Ann M Moyer
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Donna M Muzny
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Wayne T Nicholson
- Department of Anesthesia and Perioperative Medicine, Mayo Clinic, Rochester, MN, USA
| | - Lance J Oyen
- Department of Pharmacy, Mayo Clinic, Rochester, MN, USA
| | - Xiang Qin
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Ritika Raj
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Véronique L Roger
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
- Division of Cardiovascular Diseases, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA
| | | | | | - Richard R Sharp
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
- Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Paul Y Takahashi
- Division of Community Internal Medicine, Department of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Eric Venner
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Kimberly Walker
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Liwei Wang
- Division of Digital Health Sciences, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Qiaoyan Wang
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Jessica A Wright
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
- Department of Pharmacy, Mayo Clinic, Rochester, MN, USA
| | - Tsung-Jung Wu
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Liewei Wang
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
- Division of Clinical Pharmacology, Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
| | - Richard M Weinshilboum
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
- Division of Clinical Pharmacology, Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
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Personett HA, Smoot DL, Stollings JL, Sawyer M, Oyen LJ. Intravenous metoprolol versus diltiazem for rate control in noncardiac, nonthoracic postoperative atrial fibrillation. Ann Pharmacother 2014; 48:314-9. [PMID: 24408816 DOI: 10.1177/1060028013512473] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Little guidance exists on effective management of postoperative atrial fibrillation (POAF) following noncardiac, nonthoracic (NCNT) surgery. OBJECTIVES The purpose of this study was to identify whether a difference exists between intravenous (IV) metoprolol and diltiazem when used to achieve hemodynamically stable rate control in POAF following NCNT surgery. METHODS This retrospective cohort study examined critically ill adult surgical patients experiencing POAF with rapid ventricular response. Inclusion in the metoprolol or diltiazem treatment group was determined by the initial rate control agent chosen by the prescriber. The primary end point was hemodynamically stable rate control, defined by heart rate (HR) <110 beats/min and blood pressure >90 mm Hg, maintained for 6 hours. MAIN RESULTS Patients on metoprolol (n = 66) and diltiazem (n = 55) were similar in age, comorbidities, surgical procedure distribution, acuity of illness, and home rate and rhythm control medications continued during hospitalization; 76% of diltiazem-treated patients achieved hemodynamically stable rate control, compared with only 53% of those receiving metoprolol (P = .005). Safety end points were similar between groups, including the portion requiring a new vasopressor or fluid bolus for hemodynamic support. CONCLUSIONS In NCNT surgery, patients with POAF, IV diltiazem more effectively controlled HR and hemodynamics compared with metoprolol. Results warrant further research into optimal medical management of POAF in this population using these 2 agents.
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Stollings JL, Diedrich DA, Oyen LJ, Brown DR. Rapid-sequence intubation: a review of the process and considerations when choosing medications. Ann Pharmacother 2013; 48:62-76. [PMID: 24259635 DOI: 10.1177/1060028013510488] [Citation(s) in RCA: 78] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
OBJECTIVE To summarize published data regarding the steps of rapid-sequence intubation (RSI); review premedications, induction agents, neuromuscular blockers (NMB), and studies supporting use or avoidance; and discuss the benefits and deficits of combinations of induction agents and NMBs used when drug shortages occur. DATA SOURCE A search of Medline databases (1966-October 2013) was conducted. STUDY SELECTION AND DATA EXTRACTION Databases were searched using the terms rapid-sequence intubation, fentanyl, midazolam, atropine, lidocaine, phenylephrine, ketamine, propofol, etomidate thiopental, succinylcholine, vecuronium, atracurium, and rocuronium. Citations from publications were reviewed for additional references. DATA SYNTHESIS Data were reviewed to support the use or avoidance of premedications, induction agents, and paralytics and combinations to consider when drug shortages occur. CONCLUSIONS RSI is used to secure a definitive airway in often uncooperative, nonfasted, unstable, and/or critically ill patients. Choosing the appropriate premedication, induction drug, and paralytic will maximize the success of tracheal intubation and minimize complications.
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Bauer SR, Ou NN, Dreesman BJ, Armon JJ, Anderson JA, Cha SS, Oyen LJ. Effect of body mass index on bleeding frequency and activated partial thromboplastin time in weight-based dosing of unfractionated heparin: a retrospective cohort study. Mayo Clin Proc 2009; 84:1073-8. [PMID: 19955244 PMCID: PMC2787393 DOI: 10.4065/mcp.2009.0220] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
OBJECTIVE To assess bleeding and activated partial thromboplastin time (APTT) in relation to body mass index (BMI) in patients prescribed weight-based dosing of intravenous unfractionated heparin (UFH) for cardiac indications without a maximum (dose-capped) initial bolus or capped initial infusion rate. PATIENTS AND METHODS Consecutive patients admitted to an academic medical center from February 1, 2002, through November 31, 2003, who were treated with a UFH nomogram consisting of a 60-U/kg intravenous bolus plus an initial continuous intravenous infusion of 12 U/kg hourly and titrated to a goal APTT range corresponding to thromboplastin-adjusted target heparin levels of 0.3 to 0.7 U/mL by anti-Xa assay were evaluated for this retrospective cohort study. Patients were excluded if they concomitantly received a fibrinolytic, glycoprotein IIb/IIIa inhibitor, or any other antithrombotic agent (except warfarin). Study patients were divided into quartiles by BMI. RESULTS Of the 1054 patients included in the study, 807 (76.6%) had an initial bolus dose higher than 4000 U, and 477 (45.3%) had an initial infusion rate higher than 1000 U/h. Despite a significant difference among BMI quartiles in proportion of supratherapeutic first APTT values (P<.001), no statistically significant difference was found in bleeding frequency (P=.26) or frequency of first APTT within the goal range (P=.27). Logistic regression analyses revealed that BMI was not a significant predictor of bleeding or first APTT within the goal range. CONCLUSION We did not find any difference in the proportion of first APTT values in the goal range or an increased risk of bleeding in obese patients treated with UFH without a capped initial dose. Our data demonstrate the safe use of weight-based UFH without a capped initial bolus dose or capped initial infusion rate in patients with medical cardiac conditions.
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Affiliation(s)
- Seth R Bauer
- Department of Pharmacy/JJN1-02, Cleveland Clinic, Cleveland, OH 44195, USA.
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10
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Lau YT, Oyen LJ, Malinchoc M, Arendt CJ, Barth MM. A retrospective analysis on the impact of caloric intake on glycemic control in critically ill patients. Intensive Care Med 2009; 36:725-6. [PMID: 19894034 DOI: 10.1007/s00134-009-1679-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/15/2009] [Indexed: 11/27/2022]
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11
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Lam SW, Bauer SR, Cha SS, Oyen LJ. Lack of an Effect of Body Mass on the Hemodynamic Response to Arginine Vasopressin During Septic Shock. Pharmacotherapy 2008; 28:591-9. [DOI: 10.1592/phco.28.5.591] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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12
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Nuttall GA, Gutierrez MC, Dewey JD, Johnson ME, Oyen LJ, Hanson AC, Oliver WC. A Preliminary Study of a New Tranexamic Acid Dosing Schedule for Cardiac Surgery. J Cardiothorac Vasc Anesth 2008; 22:230-5. [DOI: 10.1053/j.jvca.2007.12.016] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2007] [Indexed: 11/11/2022]
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13
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Barth MM, Oyen LJ, Warfield KT, Elmer JL, Evenson LK, Tescher AN, Kuper PJ, Bannon MP, Gajic O, Farmer JC. Comparison of a nurse initiated insulin infusion protocol for intensive insulin therapy between adult surgical trauma, medical and coronary care intensive care patients. BMC Emerg Med 2007; 7:14. [PMID: 17727725 PMCID: PMC2064915 DOI: 10.1186/1471-227x-7-14] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2007] [Accepted: 08/29/2007] [Indexed: 01/08/2023] Open
Abstract
Background Sustained hyperglycemia is a known risk factor for adverse outcomes in critically ill patients. The specific aim was to determine if a nurse initiated insulin infusion protocol (IIP) was effective in maintaining blood glucose values (BG) within a target goal of 100–150 mg/dL across different intensive care units (ICUs) and to describe glycemic control during the 48 hours after protocol discontinuation. Methods A descriptive, retrospective review of 366 patients having 28,192 blood glucose values in three intensive care units, Surgical Trauma Intensive Care Unit (STICU), Medical (MICU) and Coronary Care Unit (CCU) in a quaternary care hospital was conducted. Patients were > 15 years of age, admitted to STICU (n = 162), MICU (n = 110) or CCU (n = 94) over 8 months; October 2003-June 2004 and who had an initial blood glucose level > 150 mg/dL. We summarized the effectiveness and safety of a nurse initiated IIP, and compared these endpoints among STICU, MICU and CCU patients. Results The median blood glucose values (mg/dL) at initiation of insulin infusion protocol were lower in STICU (188; IQR, 162–217) than in MICU, (201; IQR, 170–268) and CCU (227; IQR, 178–313); p < 0.0001. Mean time to achieving a target glucose level (100–150 mg/dL) was similar between the three units: 4.6 hours in STICU, 4.7 hours in MICU and 4.9 hours in CCU (p = 0.27). Hypoglycemia (BG < 60 mg/dL) occurred in 7% of STICU, 5% of MICU, and 5% of CCU patients (p = 0.85). Protocol violations were uncommon in all three ICUs. Mean blood glucose 48 hours following IIP discontinuation was significantly different for each population: 142 mg/dL in STICU, 167 mg/dL in MICU, and 160 mg/dL in CCU (p < 0.0001). Conclusion The safety and effectiveness of nurse initiated IIP was similar across different ICUs in our hospital. Marked variability in glucose control after the protocol discontinuation suggests the need for further research regarding glucose control in patients transitioning out of the ICU.
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Affiliation(s)
- Melissa M Barth
- Department of Nursing, Mayo Clinic, Rochester, Minnesota, USA
| | - Lance J Oyen
- Pharmacy Services, Mayo Clinic, Rochester, Minnesota, USA
| | | | | | - Laura K Evenson
- Department of Nursing, Mayo Clinic, Rochester, Minnesota, USA
| | - Ann N Tescher
- Department of Nursing, Mayo Clinic, Rochester, Minnesota, USA
| | - Philip J Kuper
- Pharmacy Services, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Ognjen Gajic
- Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA
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Abstract
Nearly 14 million units of packed red blood cells are transfused in the United States each year. According to the U.S. Department of Health and Human Services, in 1999, 6% of hospitals reported a shortage of blood, resulting in the cancellation or postponement of surgical procedures. The many limitations and risks of transfusions of packed red blood cells in critically ill patients have facilitated interest in developing alternative agents for oxygen delivery. Over the past few decades, safe and effective substitutes have been in development. However, no currently approved agent provides both oxygen transport and volume in place of packed red blood cells. Oxygen therapeutic products have several advantages compared with packed red blood cells, including a prolonged shelf-life, lack of a cross-matching requirement, and minimal infectious risks or concerns about immunogenicity. Hemoglobin-based oxygen carriers and perfluorocarbons are being developed. Two products are undergoing clinical trials. Polyheme is undergoing a phase III study in trauma patients, and Hemopure is being evaluated in a phase II study in patients undergoing cardiopulmonary bypass surgery. A third product (Hemolink) was being evaluated in a phase III study in patients undergoing coronary artery bypass grafting surgery; however, the trial was suspended. In addition, several other hemoglobin-based oxygen carriers are in the preclinical stages. Oxygen therapeutics have several potential clinical applications in the management of perioperative blood loss, trauma, acute normovolemic hemodilution, traumatic brain injury, and blood requirements in patients who refuse or have contraindications to transfusions of red blood cells.
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Affiliation(s)
- Joanna L Stollings
- Hospital Pharmacy Services, Mayo Clinic, Rochester, Minnesota 55902, USA
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Bauer SR, Dreesman BJ, Ou NN, Armon JJ, Anderson JA, Pruthi RK, Nishimura RA, Oyen LJ. INITIATION OF A WEIGHT-BASED UNFRACTIONATED HEPARIN NOMOGRAM WITH AN INITIAL BOLUS IN MEDICAL CARDIAC PATIENTS DOES NOT INCREASE BLEEDING RATE OR PERCENT OF INITIAL APTT VALUES WITHIN GOAL RANGE. Chest 2006. [DOI: 10.1016/s0012-3692(16)51844-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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16
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Rea RS, Kane-Gill SL, Rudis MI, Seybert AL, Oyen LJ, Ou NN, Stauss JL, Kirisci L, Idrees U, Henderson SO. Comparing intravenous amiodarone or lidocaine, or both, outcomes for inpatients with pulseless ventricular arrhythmias*. Crit Care Med 2006; 34:1617-23. [PMID: 16614583 DOI: 10.1097/01.ccm.0000217965.30554.d8] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
OBJECTIVE To compare survival rates of patients with in-hospital cardiac arrest due to pulseless ventricular tachycardia/ventricular fibrillation treated with lidocaine, amiodarone, or amiodarone plus lidocaine. DESIGN Multicenter retrospective medical record review. SETTING Three academic medical centers in the United States. PATIENTS Hospitalized adult patients who received amiodarone, lidocaine, or a combination for pulseless ventricular tachycardia/ventricular fibrillation between August 1, 2000, and July 31, 2002. MEASUREMENTS AND MAIN RESULTS Data were collected according to the Utstein style. In-hospital proportion of patients living at 24 hrs and discharge were analyzed using chi-square analysis. Of the 605 patient medical records reviewed, 194 met criteria for inclusion (n=79 for lidocaine, n=74 for amiodarone, n=41 for combination). Available data showed no difference in proportion of patients alive 24 hrs post-cardiac arrest (p=.39). Cox regression analysis indicated a decreased likelihood of survival in patients with pulseless ventricular tachycardia/ventricular fibrillation as an initial rhythm as compared with those who presented with bradycardia followed by pulseless ventricular tachycardia/ventricular fibrillation and in those patients who received amiodarone as compared with lidocaine. However, only 14 patients (25%) in the amiodarone group received the recommended initial 300-mg intravenous bolus, and amiodarone was administered an average of 8 mins later in the code compared with lidocaine (p<.001). CONCLUSIONS These results generate the hypothesis that inpatients with cardiac arrest may have different benefits from lidocaine and amiodarone than previously demonstrated. Inadequate dosing and later administration of amiodarone in the code were two confounding factors in this study. Prospective studies evaluating these agents are warranted.
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Affiliation(s)
- Rhonda S Rea
- University of Pittsburgh School of Pharmacy, Center for Pharmacoinformatics and Outcomes Research, Department of Pharmaceutical Sciences, PA, and Saint Mary's Hospital-Mayo Foundation, Rochester, MN, USA
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17
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Abstract
STUDY OBJECTIVE To assess the agreement between bedside glucose (bGlu) measurements and laboratory plasma glucose (pGlu) measurements in the ICU setting. DESIGN Retrospective study. SETTING ICU of a tertiary academic medical center. PATIENTS One hundred ninety-seven patients admitted to the ICU from January through December 2002 who underwent 816 simultaneous bGlu and pGlu measurements. INTERVENTIONS None. MEASUREMENTS AND RESULTS To calculate the agreement between the two methods of glucose measurement, the mean difference was obtained, and the limits of the agreement were calculated as the mean difference +/- 2 SDs. On 767 occasions, the mean bGlu was 159 mg/dL and the mean pGlu was 151 mg/dL (p < 0.001). The mean difference between the two techniques was 7.9 mg/dL (SD, 17.6 mg/dL), and the limits of agreement were + 43.1 and -27.2. On 31 occasions, the bGlu was reported as > 400 mg/dL, and in these cases the mean pGlu was 423 mg/dL (range, 300 to 900 mg/dL). On 18 occasions, the bGlu was reported as < 50 mg/dL, and in these cases the mean pGlu was 66.9 mg/dL (range, 13 to 198 mg/dL). CONCLUSIONS On average, bGlu provides a reasonable estimate for pGlu. However, for the individual patient, bGlu gives an unreliable estimate for pGlu. All of those taking care of critically ill patients should be aware of the limitations of bedside glucometry.
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Affiliation(s)
- Javier Daniel Finkielman
- Division of Pulmonary and Critical Care Medicine, Mayo Clinic College of Medicine, Rochester, MN 55905, USA
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18
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Oyen LJ, Nishimura RA, Ou NN, Armon JJ, Zhou M. Effectiveness of a Computerized System for Intravenous Heparin Administration: Using Information Technology to Improve Patient Care and Patient Safety. ACTA ACUST UNITED AC 2005; 3:75-81. [PMID: 15860993 DOI: 10.1111/j.1541-9215.2005.04394.x] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Abstract
To overcome errors in prescribing, calculating doses, and monitoring intravenous heparin, a computerized heparin nomogram system (HepCare) was developed to improve heparin safety using interactive cues between the prescriber, nurse, pharmacist, and the laboratory. The frequency of deviations decreased from 0.5 per patient before HepCare with the protocol to 0.006 per patient with HepCare and the protocol. The goal activated partial thromboplastin time results of the HepCare system (group I) were compared with patients who were not treated using the HepCare system (group II). There was a higher mean percentage of activated partial thromboplastin times within goal range in group I vs. II-44% vs. 27% (p<0.01). There were reminders of a drop in platelet count in 6% of patients, hemoglobin drop in 0.7%, and validation activated partial thromboplastin time values in 7% of patients by HepCare. HepCare-guided intravenous heparin resulted in significant improvements in safety, quality assurance, and targeted activated partial thromboplastin time values.
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Affiliation(s)
- Lance J Oyen
- Mayo Clinic and Foundation, Rochester, MN 55905 USA
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19
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Wilson JW, Oyen LJ, Ou NN, McMahon MM, Thompson RL, Manahan JM, Graner KK, Lovely JK, Estes LL. Hospital rules-based system: The next generation of medical informatics for patient safety. Am J Health Syst Pharm 2005; 62:499-505. [PMID: 15745913 DOI: 10.1093/ajhp/62.5.499] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
PURPOSE The hospital rules-based system (HRBS) and its subsystems at a major medical center are described. SUMMARY The HRBS was implemented at the Mayo Clinic to rapidly identify and communicate crucial information to the clinician in order to optimize patient care. The system also enhances workload efficiency and improves documentation and communication. The system is used by the infectious-diseases division, pharmacy services, nutritional support services, infection control, and the nursing department. The six HRBS subsystems are Web-based programs that share a common structural design and integrate computerized information from multiple institutional databases. The integrated data are presented in a user-friendly format that improves the efficiency of data retrieval. Information, such as monitoring notes and intervention information, can be entered for specific patients. The subsystems use rules designed to detect suboptimal therapy or monitoring and identify opportunities for cost savings in a timely manner. CONCLUSION The HRBS enhances the identification of drug-related problems while optimizing patient care and improving communication and efficiency at a major medical center.
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Affiliation(s)
- John W Wilson
- Pharmacy Services and Division of Infectious Diseases, Mayo Clinic, Rochester, MN 55905, USA.
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20
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Abstract
OBJECTIVE: To review dexamethasone interaction with corticotropin stimulation testing, particularly as it applies to treating septic shock. DATA SOURCES: Pertinent literature was identified through MEDLINE (1966–February 2004) using combinations of the key words dexamethasone, adrenocorticotropic hormone stimulation, and pretreat. Only articles written in the English language and evaluating human subjects were considered. Reference lists of identified articles were reviewed for additional citations. DATA SYNTHESIS: Accurate interpretation of the corticotropin stimulation test is important to identify patients with septic shock who may benefit from corticosteroid supplementation. In healthy volunteers, short-term dexamethasone administration prior to the corticotropin stimulation test may depress the baseline cortisol level, but does not inhibit the response to the corticotropin challenge. This may result in a slight increase in the difference between baseline and post-stimulation values. CONCLUSIONS: In 2 small trials in healthy adults, short-term, low-dose dexamethasone pretreatment decreased baseline cortisol levels, but values following corticotropin stimulation were unaffected. Accordingly, caution in interpreting corticotropin stimulation test results is warranted. However, the application of the findings from these studies to patients with septic shock is difficult, given the important differences in physiology between normal and septic patients. As of December 29, 2004, a dexamethasone dose >2 mg or prolonged dexamethasone therapy (>2 days, totaling 4 mg) preceding corticotropin stimulation has not been studied in any population.
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Affiliation(s)
- Amy N Bower
- College of Medicine and Department of Hospital Pharmacy Services, Mayo Clinic, Rochester, MN, USA
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Abstract
Although the use of low-molecular-weight heparins for treatment of acute coronary syndromes (ACS) has increased in recent years, unfractionated heparin (UFH) remains the drug of choice for many patients and institutions. One reason is that this agent is safe for patients with renal dysfunction as well as those who undergo percutaneous coronary intervention or coronary artery bypass graft. The use of UFH is complicated by the increased risk of bleeding due to concurrent administration of numerous antiplatelet drugs in most patients with ACS, the limited data regarding ideal therapeutic range, and the wide variability of patient response. Knowledge regarding the optimal therapeutic range and how to achieve it efficiently may enable clinicians to improve clinical outcomes in patients with ACS. We reviewed and analyzed the available evidence to clarify how to best manage UFH therapy in patients with ACS. Current data support the use of a lower and narrower therapeutic range for patients with ACS than the range that is used for venous thromboembolism. Many factors in addition to weight affect patient response to UFH, including age, sex, diabetes mellitus, smoking status, and obesity.
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Affiliation(s)
- Omar Badawi
- Department of Pharmacy Practice and Science, School of Pharmacy, University of Maryland, Baltimore, Maryland 21201, USA.
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22
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Hall LG, Oyen LJ, Taner CB, Cullinane DC, Baird TK, Cha SS, Sawyer MD. Fixed-dose vasopressin compared with titrated dopamine and norepinephrine as initial vasopressor therapy for septic shock. Pharmacotherapy 2004; 24:1002-12. [PMID: 15338849 DOI: 10.1592/phco.24.11.1002.36139] [Citation(s) in RCA: 36] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
STUDY OBJECTIVE To investigate the early blood pressure effects of vasopressin compared with titrated catecholamines as initial drug therapy in patients with septic shock. DESIGN Retrospective cohort, single-center study. SETTING Intensive care units at the Mayo Clinic, Rochester, Minnesota. PATIENTS Fifty, 49, and 51 intensive care patients treated initially with vasopressin, norepinephrine, and dopamine, respectively. INTERVENTION Patients received either intravenous infusion of fixed-dose vasopressin 0.04 U/minute or titrated infusions of norepinephrine or dopamine for low systemic arterial pressures. MEASUREMENTS AND MAIN RESULTS Patients treated with vasopressin, norepinephrine, and dopamine were similar in all measured characteristics except for their score on the Acute Physiology and Chronic Health Evaluation (APACHE) III (dopamine > vasopressin, p=0.049), renal comorbidities (dopamine > vasopressin, p=0.03) and baseline mean arterial pressure (MAP) (norepinephrine < vasopressin, p=0.005 or dopamine < vasopressin, p=0.05). In all patients, MAP 1 hour before and 1 hour afte intervention, heart rate, and systolic blood pressure were obtained. No treatment differences were identified in achieving postvasopressin MAP after adjusting for APACHE III score, renal dysfunction, and baseline MAP. In patients receiving vasopressin, 28-day mortality was 52%, similar to those receiving norepinephrine (65%, p=0.28) and dopamine (60%, p=0.53). CONCLUSION Initial, fixed-dose vasopressin infusions increased MAP to 70 mm Hg or greater at 1 hour in intensive care patients with septic shock, similar to titrated norepinephrine or dopamine. Fixed-dose vasopressin appears appropriate as an alternative agent for hemodynamic support in patients with septic shock.
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Affiliation(s)
- Lisa G Hall
- Hospital Pharmacy Services, Mayo Clinic, Rochester, Minnesota 55902, USA
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23
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Abstract
UNLABELLED Aprotinin is effective during cardiac surgery for reducing blood loss and transfusion requirements, but it is expensive. Aprotinin is usually administered to adults according to a fixed protocol regardless of the patient's weight. We previously developed a weight-based dosing protocol for aprotinin. The purpose of this prospective observational study was to determine aprotinin levels in four patient groups (n = 10 each) using the new weight-based aprotinin dosing schedule that should achieve concentrations over 100, 150, 200, and 250 kallikrein inhibitory units/mL compared with full-dose aprotinin regimen (n = 10) by a simple functional aprotinin assay. There was no difference in patient demographic or surgical variables among groups. There was less within patient variation in plasma aprotinin concentrations over time in the new weight-based aprotinin dosing schedule groups compared with the full-dose aprotinin regimen group (P < 0.02 for all comparisons). The mean plasma aprotinin concentration achieved with the new weight-based aprotinin dosing schedule was similar to the desired concentrations, but we were unable to reduce between-patient variability in aprotinin concentrations. IMPLICATIONS The current dosing schedule for aprotinin results in a large variation in aprotinin plasma concentrations between patients and a large variation within each patient over time. A new weight-based dosing schedule reduced variation of aprotinin concentration over time, but was unable to reduce between-patient variability in aprotinin concentration.
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Affiliation(s)
- Gregory A Nuttall
- Department of Anesthesiology, Mayo Graduate School of Medicine, Rochester, Minnesota 55905, USA.
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Abstract
Evaluation of analgesic agents is multifactorial. The authors know of no direct comparisons among the choices in analgesic agents that suggest one therapy over another in global outcomes such as mortality or morbidity. Therefore, until further outcome differentiation between agents is proved, understanding the primary difference of delivery routes, mechanisms of action, pharmacokinetics, and adverse effects serves as the best guide for selecting the appropriate agent for each patient.
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Affiliation(s)
- L G Hall
- Department of Pharmacy, Mayo Medical School, Mayo Clinic Rochester, Rochester, Minnesota, USA
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Fiechtner BK, Nuttall GA, Johnson ME, Dong Y, Sujirattanawimol N, Oliver WC, Sarpal RS, Oyen LJ, Ereth MH. Plasma tranexamic acid concentrations during cardiopulmonary bypass. Anesth Analg 2001; 92:1131-6. [PMID: 11323334 DOI: 10.1097/00000539-200105000-00010] [Citation(s) in RCA: 128] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
UNLABELLED Although tranexamic acid is used to reduce bleeding after cardiac surgery, there is large variation in the recommended dose, and few studies of plasma concentrations of the drug during cardiopulmonary bypass (CPB) have been performed. The plasma tranexamic acid concentration reported to inhibit fibrinolysis in vitro is 10 microg/mL. Twenty-one patients received an initial dose of 10 mg/kg given over 20 min followed by an infusion of 1 mg. kg(-1). h(-1) via a central venous catheter. Two patients were removed from the study secondary to protocol violation. Perioperative plasma tranexamic acid concentrations were measured with high-performance liquid chromatography. Plasma tranexamic acid concentrations (microg/mL; mean +/- SD [95% confidence interval]) were 37.4 +/- 16.9 (45.5, 29.3) after bolus, 27.6 +/- 7.9 (31.4, 23.8) after 5 min on CPB, 31.4 +/- 12.1 (37.2, 25.6) after 30 min on CPB, 29.2 +/- 9.0 (34.6, 23.8) after 60 min on CPB, 25.6 +/- 18.6 (35.1, 16.1) at discontinuation of tranexamic acid infusion, and 17.7 +/- 13.1 (24.1, 11.1) 1 h after discontinuation of tranexamic acid infusion. Four patients with renal insufficiency had increased concentrations of tranexamic acid at discontinuation of the drug. Repeated-measures analysis revealed a significant main effect of abnormal creatinine concentration (P = 0.02) and time (P < 0.001) on plasma tranexamic acid concentration and a significant time x creatinine concentration interaction (P < 0.001). IMPLICATIONS A 10 mg/kg initial dose of tranexamic acid followed by an infusion of 1 mg.kg(-1).h(-1)produced plasma concentrations throughout the cardiopulmonary bypass period sufficient to inhibit fibrinolysis in vitro. The dosing of tranexamic acid may require adjustment for renal insufficiency.
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Affiliation(s)
- B K Fiechtner
- Mayo Clinic and Graduate School of Medicine, Rochester, MN 55905, USA
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Beath SM, Nuttall GA, Fass DN, Oliver WC, Ereth MH, Oyen LJ. Plasma Aprotinin Concentrations During Cardiac Surgery: Full- Versus Half-Dose Regimens. Anesth Analg 2000. [DOI: 10.1213/00000539-200008000-00002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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Abstract
UNLABELLED Aprotinin is an effective but expensive drug used during cardiac surgery to reduce blood loss and transfusion requirements. Currently, aprotinin is administered to adults according to a fixed protocol regardless of the patient's weight. The purpose of this study was to determine aprotinin levels in patients receiving full- and half-dose aprotinin regimens by a simple functional aprotinin assay and to design a more individualized aprotinin dosage regimen for cardiac surgical patients. The mean plasma aprotinin concentration peaked 5 min after the initiation of cardiopulmonary bypass (full 401 +/- 92 KIU/mL, half 226 +/- 56 KIU/mL). The mean plasma aprotinin concentration after 60 min on cardiopulmonary bypass was less (full 236 +/- 81 KIU/mL, half 160 +/- 63 KIU/mL). There was large variation in the aprotinin concentration among patients. A statistically significant correlation was found between aprotinin concentration and patient weight (r(2) = 0.67, P < 0.05). IMPLICATIONS The current dosing schedule for aprotinin results in a large variation in aprotinin plasma concentrations among patients and a large variation within each patient over time. We combined the information provided by our study with that of a previous pharmacokinetic study to develop a potentially improved, weight-based, dosing regime for aprotinin.
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Affiliation(s)
- S M Beath
- Departments of Cardiovascular Anesthesiology and Anesthesiology, Mayo Graduate School of Medicine, Rochester, MN 55905, USA
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Abstract
Severe acute necrotizing pancreatitis is a disease that is caused by premature activation of pancreatic enzymes. Cytokine release contributes to systemic manifestations such as systemic inflammatory response syndrome (SIRS), multiple organ dysfunction syndrome (MODS), adult respiratory distress syndrome (ARDS), and sepsis. Diagnosis is based on a history of abdominal pain, laboratory values such as serum amylase and lipase levels, and CT scan. Medical management focuses on fluid and electrolyte balance, antibiotic therapy, pain control, and decreasing systemic complications. Surgery is indicated when infectious pancreatic necrosis has been identified. This article addresses incidence and etiology; pathophysiology; clinical manifestations; diagnostics; and medical and surgical patient care management.
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Affiliation(s)
- D M Wrobleski
- Critical Care Section, Mayo Clinic, Rochester, Minnesota 55905, USA
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