Letters
4. Meersch M, Schmidt C, Van Aken H, et al. Urinary TIMP-2 and IGFBP7 as early biomarkers of acute kidney injury and renal recovery following cardiac surgery. PLoS One. 2014;9(3):e93460. 5. Lauschke A, Teichgräber UKM, Frei U, Eckardt K-U. “Low-dose” dopamine worsens renal perfusion in patients with acute renal failure. Kidney Int. 2006;69 (9):1669-1674.
In Reply We agree with Dr Legrand and colleagues that our study provides further indirect evidence that nonhemodynamic factors may be important to the pathogenesis of AKI after cardiac surgery. We also agree that increases in serum creatinine level represent an already advanced level of decreased GFR, at which time interventions may be less likely to succeed in preserving GFR. However, in a previous randomized double-blind clinical trial of fenoldopam in which the drug was given at anesthesia induction, we also failed to see a beneficial effect.1 Moreover, although we have conducted several studies of renal biomarkers in the setting of cardiac surgery and the development of AKI,2-4 we are not aware of any studies conducted among cardiac surgery patients in which interventions triggered by novel biomarkers instead of creatinine level delivered better functional outcomes. Thus, the putative advantage of biomarkertriggered interventions, although interesting and perhaps logical, remains theoretical at this stage. Tiziana Bove, MD Giovanni Landoni, MD Rinaldo Bellomo, MD Author Affiliations: IRCCS San Raffaele Scientific Institute, Milan, Italy (Bove, Landoni); Australian and New Zealand Intensive Care Research Centre, Monash University School of Public Health and Preventive Medicine, Melbourne, Australia (Bellomo). Corresponding Author: Giovanni Landoni, MD, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan, Italy ([email protected]). Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. The IRCCS San Raffaele Scientific Institute received a grant from the Italian Ministry of Health to conduct the study and received an unrelated donation from Teva. No other disclosures were reported. 1. Bove T, Landoni G, Calabrò MG, et al. Renoprotective action of fenoldopam in high-risk patients undergoing cardiac surgery: a prospective, double-blind, randomized clinical trial. Circulation. 2005;111(24):3230-3235. 2. Silvetti S, Meroni R, Bignami E, et al. Preoperative urinary neutrophil gelatinase-associated lipocalin and outcome in high-risk heart failure patients undergoing cardiac surgery. J Cardiothorac Vasc Anesth. 2014;28(2):323-327. 3. Haase M, Bellomo R, Albert C, et al. The identification of three novel biomarkers of major adverse kidney events. Biomark Med. 2014;8(10):1207-1217. 4. Glassford NJ, Schneider AG, Xu S, et al. The nature and discriminatory value of urinary neutrophil gelatinase-associated lipocalin in critically ill patients at risk of acute kidney injury. Intensive Care Med. 2013;39(10):1714-1724.
Multifactorial Risk Assessment for Atherosclerotic Cardiovascular Disease To the Editor Drs Stine and Chokshi1 suggested that with the arrival of the new American College of Cardiology/American Heart Association guidelines for lipid reduction to reduce adverse outcomes from atherosclerotic cardiovascular disease, it is time to move from a low-density lipoprotein cholesterol target basis to a “multifactorial risk assessment,” especially since online calculators now make it easy to perform quantitation and may even
provide patient education tools (using simple natural frequency displays) to facilitate shared decision making. As sensible as this recommendation seems, it may be too soon to implement it for at least 3 reasons. First, existing tools appear to overstate the likelihood of coronary events2 or, equally troubling, are inconsistent while purporting to address the same risk groups.3 Second, results from online calculators lack error estimates (such as confidence intervals) to permit physicians to address uncertainty in discussions with their patients. Third, statistical numeracy among practicing physicians is far from satisfactory, undermining the practical value of those time-consuming discussions. There are instructive lessons regarding tools assessing multiple risk factors in other screening venues. For example, the World Health Organization’s Fracture Risk Assessment Tool (FRAX) has been available since 2008 and is strongly supported by professional organizations advocating its use in identifying individuals for prophylactic therapy to prevent osteoporosis-associated fractures.4 The FRAX online calculator5 stratifies risk by sex, race, geographic locale, and multiple influences on bone metabolism. Yet since the appearance of the online calculator in 2011, only about 3 million hits have been registered on the US-specific page.5 Because the lifetime risk for an osteoporotic fracture of the wrist, hip, or vertebrae approaches 40% in women in developed countries, and since medication can reduce this risk by about one-third, the calculator would appear to be vastly underused. There are approximately 41 million women older than 50 years in the United States whose risk for osteoporosis can be rapidly assessed using FRAX, which may then be supplemented with a dual-energy x-ray absorptiometry scan. Statistical illiteracy among physicians may in part be to blame for underuse of quantitative calculators, even for those like FRAX that almost certainly could help direct costeffective primary preventive therapies. It would seem prudent to forestall systemic application of new quantitative risk calculation for preventive intervention–related decision making in cardiovascular disease until there is supportive evidence of benefit to patients in controlled trials. Until then, straightforward cholesterol target guidelines may be best. Alan P. Zelicoff, MD Author Affiliation: Department of Environmental and Occupational Health, College for Public Health and Social Justice, St Louis University, St Louis, Missouri. Corresponding Author: Alan P. Zelicoff, MD, Department of Environmental and Occupational Health, College for Public Health and Social Justice, St Louis University, 3545 Lafayette Ave, St Louis, MO 63118 ([email protected]). Conflict of Interest Disclosures: The author has completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported. 1. Stine NW, Chokshi DA. Elimination of lipid levels from quality measures: implications and alternatives. JAMA. 2014;312(19):1971-1972. 2. Cook NR, Ridker PM. Further insight into the cardiovascular risk calculator: the roles of statins, revascularizations, and underascertainment in the Women’s Health Study. JAMA Intern Med. 2014;174(12):1964-1971. 3. Allan GM, Nouri F, Korownyk C, Kolber MR, Vandermeer B, McCormack J. Agreement among cardiovascular disease risk calculators. Circulation. 2013;127 (19):1948-1956.
jama.com
(Reprinted) JAMA March 3, 2015 Volume 313, Number 9
Copyright 2015 American Medical Association. All rights reserved.
Downloaded From: http://jama.jamanetwork.com/ by a New York University User on 05/15/2015
971
Letters
4. Committee on Practice Bulletins-Gynecology, American College of Obstetricians and Gynecologists. ACOG Practice Bulletin No. 129: Osteoporosis. Obstet Gynecol. 2012;120(3):718-734.
Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.
5. World Health Organization Collaborating Centre for Metabolic Bone Diseases. FRAX WHO Fracture Risk Assessment Tool. http://www.shef.ac.uk /FRAX/tool.aspx?country=9. Accessed November 20, 2014.
CORRECTION
In Reply Dr Zelicoff points to several significant challenges for the development and implementation of successful riskbased quality measures, including limitations of existing risk calculator tools and the ability of clinicians to interpret and communicate statistical risk. We share the sentiment that practical, standardized, and validated approaches to risk calculation and communication are a significant research and educational need. As Zelicoff effectively illustrates with the example of the FRAX tool for osteoporosis, best practice guidelines are imperfectly applied on the ground—perhaps more so when risk calculation is involved. Yet operational challenges should not lead to jettisoning of best practices. Rather, systems and policy solutions to facilitate a higher standard of care should be sought. In this way, we view the application of quality measures as a tool for driving improvement and promoting accountability, rather than merely a common denominator for assessment. Many guidelines are moving in the direction of multifactorial risk assessment, as with the American College of Cardiology/American Heart Association lipid guidelines. Our concern is ensuring that quality measures keep pace with more sophisticated guidelines. Zelicoff’s call for particular attention to the integrity of bedside tools and the statistical literacy of clinicians is an important and valuable addition to that conversation. Nicholas Stine, MD Dave Chokshi, MD, MSc Author Affiliations: New York City Health & Hospitals Corporation, New York. Corresponding Author: Nicholas Stine, MD, New York City Health and Hospitals Corporation, Department of Population Health, New York University School of Medicine, 125 Worth St, New York, NY 10013 (nicholas.stine @nychhc.org).
972
Incorrect Terminology : In the JAMA Clinical Guidelines Synopsis article entitled “Screening for Asymptomatic Carotid Artery Stenosis” published in the January 13, 2015, issue of JAMA (2015;313[2]:192-193. doi:10.1001/jama.2014 .16804), the incorrect shortening of “magnetic resonance angiography” to “angiography” appeared twice in the third paragraph of the Discussion. The last sentence of that paragraph should read “Noninvasive studies such as magnetic resonance angiography and computed tomography have risks associated with renal dysfunction, lack some degree of diagnostic accuracy (eg, the specificity for magnetic resonance angiography ranges from 82%-96%), and can still yield substantial numbers of false-positive results.” This article was corrected online.
Guidelines for Letters Letters discussing a recent JAMA article should be submitted within 4 weeks of the article's publication in print. Letters received after 4 weeks will rarely be considered. Letters should not exceed 400 words of text and 5 references and may have no more than 3 authors. Letters reporting original research should not exceed 600 words of text and 6 references and may have no more than 7 authors. They may include up to 2 tables or figures but online supplementary material is not allowed. All letters should include a word count. Letters must not duplicate other material published or submitted for publication. Letters not meeting these specifications are generally not considered. Letters being considered for publication ordinarily will be sent to the authors of the JAMA article, who will be given the opportunity to reply. Letters will be published at the discretion of the editors and are subject to abridgement and editing. Further instructions can be found at http://jama.com/public/InstructionsForAuthors.aspx. A signed statement for authorship criteria and responsibility, financial disclosure, copyright transfer, and acknowledgment and the ICMJE Form for Disclosure of Potential Conflicts of Interest are required before publication. Letters should be submitted via the JAMA online submission and review system at http://manuscripts.jama.com. For technical assistance, please contact [email protected]. Section Editor: Jody W. Zylke, MD, Deputy Editor.
JAMA March 3, 2015 Volume 313, Number 9 (Reprinted)
Copyright 2015 American Medical Association. All rights reserved.
Downloaded From: http://jama.jamanetwork.com/ by a New York University User on 05/15/2015
jama.com
4. Meersch M, Schmidt C, Van Aken H, et al. Urinary TIMP-2 and IGFBP7 as early biomarkers of acute kidney injury and renal recovery following cardiac surgery. PLoS One. 2014;9(3):e93460. 5. Lauschke A, Teichgräber UKM, Frei U, Eckardt K-U. “Low-dose” dopamine worsens renal perfusion in patients with acute renal failure. Kidney Int. 2006;69 (9):1669-1674.
In Reply We agree with Dr Legrand and colleagues that our study provides further indirect evidence that nonhemodynamic factors may be important to the pathogenesis of AKI after cardiac surgery. We also agree that increases in serum creatinine level represent an already advanced level of decreased GFR, at which time interventions may be less likely to succeed in preserving GFR. However, in a previous randomized double-blind clinical trial of fenoldopam in which the drug was given at anesthesia induction, we also failed to see a beneficial effect.1 Moreover, although we have conducted several studies of renal biomarkers in the setting of cardiac surgery and the development of AKI,2-4 we are not aware of any studies conducted among cardiac surgery patients in which interventions triggered by novel biomarkers instead of creatinine level delivered better functional outcomes. Thus, the putative advantage of biomarkertriggered interventions, although interesting and perhaps logical, remains theoretical at this stage. Tiziana Bove, MD Giovanni Landoni, MD Rinaldo Bellomo, MD Author Affiliations: IRCCS San Raffaele Scientific Institute, Milan, Italy (Bove, Landoni); Australian and New Zealand Intensive Care Research Centre, Monash University School of Public Health and Preventive Medicine, Melbourne, Australia (Bellomo). Corresponding Author: Giovanni Landoni, MD, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan, Italy ([email protected]). Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. The IRCCS San Raffaele Scientific Institute received a grant from the Italian Ministry of Health to conduct the study and received an unrelated donation from Teva. No other disclosures were reported. 1. Bove T, Landoni G, Calabrò MG, et al. Renoprotective action of fenoldopam in high-risk patients undergoing cardiac surgery: a prospective, double-blind, randomized clinical trial. Circulation. 2005;111(24):3230-3235. 2. Silvetti S, Meroni R, Bignami E, et al. Preoperative urinary neutrophil gelatinase-associated lipocalin and outcome in high-risk heart failure patients undergoing cardiac surgery. J Cardiothorac Vasc Anesth. 2014;28(2):323-327. 3. Haase M, Bellomo R, Albert C, et al. The identification of three novel biomarkers of major adverse kidney events. Biomark Med. 2014;8(10):1207-1217. 4. Glassford NJ, Schneider AG, Xu S, et al. The nature and discriminatory value of urinary neutrophil gelatinase-associated lipocalin in critically ill patients at risk of acute kidney injury. Intensive Care Med. 2013;39(10):1714-1724.
Multifactorial Risk Assessment for Atherosclerotic Cardiovascular Disease To the Editor Drs Stine and Chokshi1 suggested that with the arrival of the new American College of Cardiology/American Heart Association guidelines for lipid reduction to reduce adverse outcomes from atherosclerotic cardiovascular disease, it is time to move from a low-density lipoprotein cholesterol target basis to a “multifactorial risk assessment,” especially since online calculators now make it easy to perform quantitation and may even
provide patient education tools (using simple natural frequency displays) to facilitate shared decision making. As sensible as this recommendation seems, it may be too soon to implement it for at least 3 reasons. First, existing tools appear to overstate the likelihood of coronary events2 or, equally troubling, are inconsistent while purporting to address the same risk groups.3 Second, results from online calculators lack error estimates (such as confidence intervals) to permit physicians to address uncertainty in discussions with their patients. Third, statistical numeracy among practicing physicians is far from satisfactory, undermining the practical value of those time-consuming discussions. There are instructive lessons regarding tools assessing multiple risk factors in other screening venues. For example, the World Health Organization’s Fracture Risk Assessment Tool (FRAX) has been available since 2008 and is strongly supported by professional organizations advocating its use in identifying individuals for prophylactic therapy to prevent osteoporosis-associated fractures.4 The FRAX online calculator5 stratifies risk by sex, race, geographic locale, and multiple influences on bone metabolism. Yet since the appearance of the online calculator in 2011, only about 3 million hits have been registered on the US-specific page.5 Because the lifetime risk for an osteoporotic fracture of the wrist, hip, or vertebrae approaches 40% in women in developed countries, and since medication can reduce this risk by about one-third, the calculator would appear to be vastly underused. There are approximately 41 million women older than 50 years in the United States whose risk for osteoporosis can be rapidly assessed using FRAX, which may then be supplemented with a dual-energy x-ray absorptiometry scan. Statistical illiteracy among physicians may in part be to blame for underuse of quantitative calculators, even for those like FRAX that almost certainly could help direct costeffective primary preventive therapies. It would seem prudent to forestall systemic application of new quantitative risk calculation for preventive intervention–related decision making in cardiovascular disease until there is supportive evidence of benefit to patients in controlled trials. Until then, straightforward cholesterol target guidelines may be best. Alan P. Zelicoff, MD Author Affiliation: Department of Environmental and Occupational Health, College for Public Health and Social Justice, St Louis University, St Louis, Missouri. Corresponding Author: Alan P. Zelicoff, MD, Department of Environmental and Occupational Health, College for Public Health and Social Justice, St Louis University, 3545 Lafayette Ave, St Louis, MO 63118 ([email protected]). Conflict of Interest Disclosures: The author has completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported. 1. Stine NW, Chokshi DA. Elimination of lipid levels from quality measures: implications and alternatives. JAMA. 2014;312(19):1971-1972. 2. Cook NR, Ridker PM. Further insight into the cardiovascular risk calculator: the roles of statins, revascularizations, and underascertainment in the Women’s Health Study. JAMA Intern Med. 2014;174(12):1964-1971. 3. Allan GM, Nouri F, Korownyk C, Kolber MR, Vandermeer B, McCormack J. Agreement among cardiovascular disease risk calculators. Circulation. 2013;127 (19):1948-1956.
jama.com
(Reprinted) JAMA March 3, 2015 Volume 313, Number 9
Copyright 2015 American Medical Association. All rights reserved.
Downloaded From: http://jama.jamanetwork.com/ by a New York University User on 05/15/2015
971
Letters
4. Committee on Practice Bulletins-Gynecology, American College of Obstetricians and Gynecologists. ACOG Practice Bulletin No. 129: Osteoporosis. Obstet Gynecol. 2012;120(3):718-734.
Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.
5. World Health Organization Collaborating Centre for Metabolic Bone Diseases. FRAX WHO Fracture Risk Assessment Tool. http://www.shef.ac.uk /FRAX/tool.aspx?country=9. Accessed November 20, 2014.
CORRECTION
In Reply Dr Zelicoff points to several significant challenges for the development and implementation of successful riskbased quality measures, including limitations of existing risk calculator tools and the ability of clinicians to interpret and communicate statistical risk. We share the sentiment that practical, standardized, and validated approaches to risk calculation and communication are a significant research and educational need. As Zelicoff effectively illustrates with the example of the FRAX tool for osteoporosis, best practice guidelines are imperfectly applied on the ground—perhaps more so when risk calculation is involved. Yet operational challenges should not lead to jettisoning of best practices. Rather, systems and policy solutions to facilitate a higher standard of care should be sought. In this way, we view the application of quality measures as a tool for driving improvement and promoting accountability, rather than merely a common denominator for assessment. Many guidelines are moving in the direction of multifactorial risk assessment, as with the American College of Cardiology/American Heart Association lipid guidelines. Our concern is ensuring that quality measures keep pace with more sophisticated guidelines. Zelicoff’s call for particular attention to the integrity of bedside tools and the statistical literacy of clinicians is an important and valuable addition to that conversation. Nicholas Stine, MD Dave Chokshi, MD, MSc Author Affiliations: New York City Health & Hospitals Corporation, New York. Corresponding Author: Nicholas Stine, MD, New York City Health and Hospitals Corporation, Department of Population Health, New York University School of Medicine, 125 Worth St, New York, NY 10013 (nicholas.stine @nychhc.org).
972
Incorrect Terminology : In the JAMA Clinical Guidelines Synopsis article entitled “Screening for Asymptomatic Carotid Artery Stenosis” published in the January 13, 2015, issue of JAMA (2015;313[2]:192-193. doi:10.1001/jama.2014 .16804), the incorrect shortening of “magnetic resonance angiography” to “angiography” appeared twice in the third paragraph of the Discussion. The last sentence of that paragraph should read “Noninvasive studies such as magnetic resonance angiography and computed tomography have risks associated with renal dysfunction, lack some degree of diagnostic accuracy (eg, the specificity for magnetic resonance angiography ranges from 82%-96%), and can still yield substantial numbers of false-positive results.” This article was corrected online.
Guidelines for Letters Letters discussing a recent JAMA article should be submitted within 4 weeks of the article's publication in print. Letters received after 4 weeks will rarely be considered. Letters should not exceed 400 words of text and 5 references and may have no more than 3 authors. Letters reporting original research should not exceed 600 words of text and 6 references and may have no more than 7 authors. They may include up to 2 tables or figures but online supplementary material is not allowed. All letters should include a word count. Letters must not duplicate other material published or submitted for publication. Letters not meeting these specifications are generally not considered. Letters being considered for publication ordinarily will be sent to the authors of the JAMA article, who will be given the opportunity to reply. Letters will be published at the discretion of the editors and are subject to abridgement and editing. Further instructions can be found at http://jama.com/public/InstructionsForAuthors.aspx. A signed statement for authorship criteria and responsibility, financial disclosure, copyright transfer, and acknowledgment and the ICMJE Form for Disclosure of Potential Conflicts of Interest are required before publication. Letters should be submitted via the JAMA online submission and review system at http://manuscripts.jama.com. For technical assistance, please contact [email protected]. Section Editor: Jody W. Zylke, MD, Deputy Editor.
JAMA March 3, 2015 Volume 313, Number 9 (Reprinted)
Copyright 2015 American Medical Association. All rights reserved.
Downloaded From: http://jama.jamanetwork.com/ by a New York University User on 05/15/2015
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