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Background: Optimal antithrombotic management of patients with preexisting atrial fibrillation undergoing transcatheter aortic valve replacement is challenging given the need to balance the risk of bleeding and thromboembolism. We aimed to examine variation in care and association of antithrombotic therapies with 1-year outcomes of stroke, bleeding, and mortality in patients undergoing transcatheter aortic valve replacement with concomitant atrial fibrillation in the United States., Methods: Patients who underwent transcatheter aortic valve replacement with preexisting atrial fibrillation from November 2011 through September 2015 in the Society of Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapy registry linked to the Medicare database were examined according to receipt of oral anticoagulants (OACs) or antiplatelet therapies (APTs) or a combination of these (OAC+APT) at discharge. To assess the associations of antithrombotic therapies with 1-year outcomes of stroke, bleeding, and mortality, we utilized inverse probability weighting for antithrombotic therapies and multivariable regression modeling to adjust for patient- and hospital-level variables., Results: In the 11 382 patients included in our study, 5833 (51.2%) were discharged on OAC+APT, 4786 (42.0%) on APT alone, and 763 (6.7%) on OAC alone. There was significant variability in discharge medication patterns, including 42% of patients discharged without OAC therapy. In adjusted analyses, the risk for all-cause mortality and stroke was not significantly different when comparing the 3 different antithrombotic strategies. Risk of bleeding was higher with OAC+APT compared with APT alone (hazard ratio, 1.16 [95% CI, 1.05–1.27]) and similar compared with OAC alone (hazard ratio, 1.17 [95% CI, 0.93–1.47])., Conclusions: There was significant variability in discharge medication patterns across US sites in patients with atrial fibrillation undergoing transcatheter aortic valve replacement, including significant underuse of OAC in this high-risk cohort. The use of OAC+APT (versus OAC alone or APT alone) was not associated with a lower risk of stroke or mortality but was associated with increased risk of bleeding complications at 1 year compared with APT alone.

The last half century has seen extraordinary advances in the field of cardiology, including innovations in medications, diagnostic modalities, and therapeutics. Even so, cardiovascular disease remains the leading cause of morbidity and mortality globally, with suboptimal quality of care, inconsistent health outcomes, and unsustainable costs. It is clear that cardiovascular medicine must undergo a digital transformation to enhance the delivery of quality care and to improve outcomes. To meet this need, the American College of Cardiology developed an innovation program focused on the digital transformation of cardiovascular care, with the goal of improving heart health for individuals and populations., Competing Interests: Conflict of Interest Disclosure: Dr. Rumsfeld is the chief innovation officer and chief science officer for the American College of Cardiology. Dr. Shah is a consultant for and/or conducts research on behalf of the National Institutes of Health, American Heart Association, the National Heart, Lung and Blood Institute, Women as One, Doris Duke Charitable Foundation, and the American College of Cardiology., (© 2020 Houston Methodist Hospital Houston, Texas.)

The worldwide pandemic caused by the novel acute respiratory syndrome coronavirus 2 has resulted in a new and lethal disease termed coronavirus disease 2019 (COVID-19). Although there is an association between cardiovascular disease and COVID-19, the majority of patients who need cardiovascular care for the management of ischemic heart disease may not be infected with this novel coronavirus. The objective of this document is to provide recommendations for a systematic approach for the care of patients with an acute myocardial infarction (AMI) during the COVID-19 pandemic. There is a recognition of two major challenges in providing recommendations for AMI care in the COVID-19 era. Cardiovascular manifestations of COVID-19 are complex with patients presenting with AMI, myocarditis simulating an ST-elevation myocardial infarction (STEMI) presentation, stress cardiomyopathy, non-ischemic cardiomyopathy, coronary spasm, or nonspecific myocardial injury, and the prevalence of COVID-19 disease in the US population remains unknown with risk of asymptomatic spread. This document addresses the care of these patients focusing on (a) varied clinical presentations; (b) appropriate personal protection equipment (PPE) for health care workers; (c) the roles of the emergency department, emergency medical system, and the cardiac catheterization laboratory (CCL); and (4) regional STEMI systems of care. During the COVID-19 pandemic, primary percutaneous coronary intervention (PCI) remains the standard of care for STEMI patients at PCI-capable hospitals when it can be provided in a timely manner, with an expert team outfitted with PPE in a dedicated CCL room. A fibrinolysis-based strategy may be entertained at non-PCI-capable referral hospitals or in specific situations where primary PCI cannot be executed or is not deemed the best option., (© 2020 Wiley Periodicals, Inc.)

Importance: The US health care system faces an unsustainable trajectory of high costs and inconsistent outcomes. The fee-for-service payment model has contributed to inefficiency, and new payment methods are a promising approach to improving value. Health reforms are needed to increase patient access, reduce costs, and improve health care quality, and the landmark Medicare Access and CHIP Reauthorization Act presents a roadmap for reform. The product of a collaboration between primary care and cardiology clinicians, this review describes a conceptual approach to delivery and payment reforms that aim to better support primary care-cardiology comanagement of chronic cardiovascular disease (CVD)., Observations: Few existing alternative payment models specifically address long-term management of CVD. Primary care medical homes and accountable care organizations come closest, but both emphasize primary care, and cardiologists have often not been well engaged. A collaborative care framework should articulate distinct roles and responsibilities for primary care and cardiology in CVD comanagement. Finally, a series of payment models aim to better support clinicians in providing accountable, seamless, and patient-centered cardiac care., Conclusions & Relevance: Clinical leadership is essential during this time of change in the health care system. Patients often struggle to navigate a fragmented and expensive system, whereas clinicians often practice with incomplete information about tests, treatments, and recommendations by their colleagues. The payment models described in this review offer an opportunity to create more satisfying approaches to patient care while improving value. These models have potential to support more effective coordination and to facilitate broader health care system transformation.

Background: Million Hearts is a national initiative to prevent 1 million heart attacks and strokes over 5 years by improving cardiovascular prevention. An important tool in the success of programs like Million Hearts is public ranking on the quality of practices, yet different measures may provide different rankings, so the true quality of practices is difficult to discern. We evaluated the quality of ambulatory cardiology care using performance measure metrics., Methods: We compared rankings of practices participating in the National Cardiovascular Data Registry's Practice Innovation and Clinical Excellence Registry using measures from (1) the physician quality reporting system and (2) the American College of Cardiology/American Heart Association/Physician Consortium for Performance Improvement. We compared achievement rates for measures between the 2 frameworks and determined correlations in rankings using Spearman correlation coefficients., Results: From January 1, 2008 to December 31, 2012, there were 1,711,326 patients enrolled from 111 US practices. Among eligible patients, the physician quality reporting system and American College of Cardiology/American Heart Association/Physician Consortium for Performance Improvement measures were achieved in 76.1% versus 77.4% for antiplatelet prescription (P < .001), 68.3% versus 90.8% for blood pressure control (P < .001), 26.9% versus 43.4% for cholesterol control (P < .001), and 37.4% versus 40.6% for smoking cessation (P = .383). Practice rankings were strongly correlated for antiplatelet prescription (correlation coefficient 0.98) and cholesterol control (0.92) but poorly correlated for blood pressure control (0.39) and smoking cessation (0.22)., Conclusions: Evaluation of preventive care and individual practice rankings vary significantly depending on how measures are defined. Publicly reported measures need to be validly associated with outcomes to avoid incorrectly evaluating practice performance and failing to achieve public health goals., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Public reporting of hospital and individual provider quality of care measures is not a new concept. In the United States, the first national public reports of hospital mortality data occurred in 1986, and detailed physician-level data for cardiac surgery are now reported in 4 states. The development of the "Hospital Compare," and more recently, the "Physician Compare" websites has further expanded public reporting for hospitals and providers. Several professional organizations, including the American Medical Association, Society of Thoracic Surgeons, and the American College of Cardiology, have published policy statements articulating key principles to guide the public reporting process. Despite the rapid proliferation of public reporting efforts, more research is needed to better define meaningful measures to report and fully understand the impact of public reporting on healthcare delivery., (Copyright © 2014 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Objectives: This study applied risk adjustment methods to evaluate member institutions of the American College of Cardiology-National Cardiovascular Data Registry with respect to in-hospital mortality in percutaneous coronary intervention patients over a 4-year period to assess variability in risk-adjusted performance measures., Background: Cardiac catheterization laboratories, hospital networks, and third-party payers are interested in assessing the outcomes of percutaneous coronary interventions. Evaluation of outcomes without considering case selection may lead to erroneous conclusions about program quality., Methods: The National Cardiovascular Data Registry database was queried for all percutaneous coronary intervention cases performed between January 1, 2001, and September 30, 2004. Random effects logistic regression was used to develop models of in-hospital mortality and compute an expected mortality rate for each program. The observed mortality rate in each program was divided by the program's predicted rate to obtain the observed/expected (O/E) mortality ratio. Change in the O/E ratio was assessed by a generalized estimating equation approach to repeated measures. An index of variability was calculated by the mean absolute difference between O/E ratios of each pair of years., Results: There were 664,909 interventional procedures performed in 403 National Cardiovascular Data Registry programs from 2001 to 2004. There was no significant systematic change in O/E ratios over the 4-year period, but there was significantly greater variation in O/E ratios associated with lower percutaneous coronary intervention volume programs., Conclusions: Our risk-adjustment models had very good discrimination and were relatively consistent over the study period. There was substantial within-program variation in O/E ratios. This information would provide an indication for a detailed examination of individual programs.

The American College of Cardiology (ACC) and the American Heart Association (AHA) have provided leadership in enhancing the quality of cardiovascular care, including the development of clinical performance measures and clinical registries that permit the evaluation of quality of care and stimulate quality improvement. Compliance with ACC/AHA performance measures and metrics encourages the provision of the strongest evidence-based quality of care, including therapies that are life-extending or life-enhancing. Among quality metrics, only a subset should be considered performance measures-that is, those measures specifically suitable for public reporting, external comparisons, and possibly pay-for-performance programs, in addition to quality improvement. These performance measures have been developed using ACC/AHA methodology, often in collaboration with other organizations, and include the process of public comment and peer review. Quality metrics are those measures that have been developed to support self assessment and quality improvement at the provider, hospital, and/or health care system level. These metrics represent valuable tools to aid clinicians and hospitals in improving quality of care and enhancing patient outcomes, but may not meet all specifications of formal performance measures. These quality metrics may also be considered "candidate" measures that with further research of field testing would meet the criteria for formal performance measures in the future. This measure classification is intended to aid providers, hospitals, health systems, and payers in identifying those measures that the ACC and AHA formally endorse as performance measures, while at the same time promoting the broader range of clinical metrics that are useful for quality improvement efforts.

The assessment of medical practice is evolving rapidly in the United States. An initial focus on structure and process performance measures assessing the quality of medical care is now being supplemented with efficiency measures to quantify the "value" of healthcare delivery. This statement, building on prior work that articulated standards for publicly reported outcomes measures, identifies preferred attributes for measures used to assess efficiency in the allocation of healthcare resources. The attributes identified in this document combined with the previously published standards are intended to serve as criteria for assessing the suitability of efficiency measures for public reporting. This statement identifies the following attributes to be considered for publicly reported efficiency measures: integration of the quality and cost; valid cost measurement and analysis; minimal incentive to provide poor quality care; and proper attribution of the measure. The attributes described in this statement are relevant to a wide range of efforts to profile the efficiency of various healthcare providers, including hospitals, healthcare systems, managed-care organizations, physicians, group practices, and others that deliver coordinated care.

An American College of Cardiology (ACC)/American Heart Association (AHA) task force on practice guidelines in 2001 published evidence-based recommendations for performing percutaneous coronary interventions (PCIs). These guidelines grouped the indications for PCI into 4 classes (I, IIa, IIb, and III) based on analyses of risks and benefits. In a previous study, we found that clinical success and in-hospital adverse events varied by indications class. However, no adjustment for risk was used in those comparisons. The ACC/National Cardiovascular Data Registry (ACC-NCDR) previously developed a risk-adjustment model for the adverse event of in-hospital PCI mortality. We investigated how the 14 individual risk factors in the ACC-NCDR PCI mortality model might differ across the 4 indications classes and whether estimated mortality for each class approximated the observed mortality for that class. We analyzed the ACC-NCDR PCI database for January 1, 2001 to December 31, 2004. We excluded procedures performed for treatment of acute ST-segment elevation myocardial infarction; all others were included, yielding 559,273 procedures for analysis. An algorithm derived from the 2001 guidelines was used to assign procedures to an indications class. Increasing frequencies of risk components were observed across classes I, IIa, IIb, and III. Expected mortalities for each class calculated by the risk-adjustment model were close to observed values (expected 0.52%, 0.59%, 1.72%, and 1.96%, respectively; observed 0.49%, 0.63%, 1.88%, and 1.60%, respectively). In conclusion, the ACC-NCDR risk-adjusted mortality model can be linked to the ACC/AHA PCI guidelines, and together these produce mortality risk estimates by indications classes that are close to actual observed values. With further refinement, these methods should be able to be used as powerful analytic tools for quality assurance and appropriateness purposes.

Objectives: The goal of this study was to determine if cardiology subspecialty involvement improves the attainment of recommended low-density lipoprotein (LDL) cholesterol and blood pressure (BP) targets in coronary artery disease (CAD) patients., Background: The impact of physician specialty on secondary prevention measures for CAD in ambulatory care is unknown., Methods: This was a retrospective cohort study of 13,995 patients with CAD seen at eight ambulatory care Veteran Affairs facilities from 1998 to 2000. Patients with cardiology involvement were defined as those seen in cardiology clinic in addition to primary care. The main outcomes of interest were LDL cholesterol < or =100 mg/dl and BP < or =130/85 mm Hg. Multivariable hierarchical regression analyses were used to determine the independent association of cardiology involvement with improved LDL cholesterol and BP control., Results: Overall, 3,771 (27.0%) patients had cardiology involvement. A higher proportion of patients with cardiology involvement achieved LDL cholesterol (55.6% vs. 45.6%; p < 0.01) and BP (45.3% vs. 35.9%; p < 0.01) goals. In multivariable hierarchical regression analysis, cardiology involvement was independently associated with better LDL cholesterol (odds ratio [OR], 1.59; 95% confidence interval [CI], 1.40 to 1.82) and BP (OR, 1.52; 95% CI, 1.32 to 1.77) control. The benefit of cardiology involvement was consistent across a range of LDL and BP targets, in analysis of LDL and BP as continuous outcomes, and among subgroups of high-risk patients, including diabetic patients, the elderly, and those with prior revascularization., Conclusions: Cardiology involvement is associated with better LDL cholesterol and BP control among CAD patients. However, significant room for improvement in secondary prevention measures remains, irrespective of physician specialty.

Background The current acute kidney injury (AKI) risk prediction model for patients undergoing percutaneous coronary intervention (PCI) from the American College of Cardiology (ACC) National Cardiovascular Data Registry (NCDR) employed regression techniques. This study aimed to evaluate whether models using machine learning techniques could significantly improve AKI risk prediction after PCI. Methods and findings We used the same cohort and candidate variables used to develop the current NCDR CathPCI Registry AKI model, including 947,091 patients who underwent PCI procedures between June 1, 2009, and June 30, 2011. The mean age of these patients was 64.8 years, and 32.8% were women, with a total of 69,826 (7.4%) AKI events. We replicated the current AKI model as the baseline model and compared it with a series of new models. Temporal validation was performed using data from 970,869 patients undergoing PCIs between July 1, 2016, and March 31, 2017, with a mean age of 65.7 years; 31.9% were women, and 72,954 (7.5%) had AKI events. Each model was derived by implementing one of two strategies for preprocessing candidate variables (preselecting and transforming candidate variables or using all candidate variables in their original forms), one of three variable-selection methods (stepwise backward selection, lasso regularization, or permutation-based selection), and one of two methods to model the relationship between variables and outcome (logistic regression or gradient descent boosting). The cohort was divided into different training (70%) and test (30%) sets using 100 different random splits, and the performance of the models was evaluated internally in the test sets. The best model, according to the internal evaluation, was derived by using all available candidate variables in their original form, permutation-based variable selection, and gradient descent boosting. Compared with the baseline model that uses 11 variables, the best model used 13 variables and achieved a significantly better area under the receiver operating characteristic curve (AUC) of 0.752 (95% confidence interval [CI] 0.749-0.754) versus 0.711 (95% CI 0.708-0.714), a significantly better Brier score of 0.0617 (95% CI 0.0615-0.0618) versus 0.0636 (95% CI 0.0634-0.0638), and a better calibration slope of observed versus predicted rate of 1.008 (95% CI 0.988-1.028) versus 1.036 (95% CI 1.015-1.056). The best model also had a significantly wider predictive range (25.3% versus 21.6%, p < 0.001) and was more accurate in stratifying AKI risk for patients. Evaluated on a more contemporary CathPCI cohort (July 1, 2015-March 31, 2017), the best model consistently achieved significantly better performance than the baseline model in AUC (0.785 versus 0.753), Brier score (0.0610 versus 0.0627), calibration slope (1.003 versus 1.062), and predictive range (29.4% versus 26.2%). The current study does not address implementation for risk calculation at the point of care, and potential challenges include the availability and accessibility of the predictors. Conclusions Machine learning techniques and data-driven approaches resulted in improved prediction of AKI risk after PCI. The results support the potential of these techniques for improving risk prediction models and identification of patients who may benefit from risk-mitigation strategies., Author(s): Chenxi Huang 1, Karthik Murugiah 2, Shiwani Mahajan 1, Shu-Xia Li 1, Sanket S. Dhruva 3,4, Julian S. Haimovich 5, Yongfei Wang 1, Wade L. Schulz 1,6, Jeffrey M. [...]

Background: Controversy remains regarding whether gender differences exist in clinical management after exercise treadmill testing (ETT). Methods: We studied 7,506 patients (49.8% women) without documented coronary heart disease referred for ETT from July 2001 to June 2004 in a community-based setting. We assessed the relationship between gender and subsequent diagnostic testing (secondary stress testing or coronary angiography) within 6 months after ETT. Secondary outcomes included subsequent stress testing, coronary angiography, and new cardiology visits in the 6-month interval. Multivariable analyses assessed the relationship between gender and these outcomes adjusting for demographic, clinical, and stress test characteristics. In subsequent analyses, patients were stratified by Duke Treadmill Scores (Duke University, Durham, NC). Results: Compared with men, women referred for ETT were older, had a higher prevalence of some cardiac risk factors, achieved lower peak workloads, and, more often, experienced chest pain or ST-segment changes. After accounting for differences in clinical and ETT parameters, gender was not associated with any subsequent diagnostic testing in the 6 months after ETT (OR 1.0, 95% CI 0.85-1.18). In secondary analyses, women were less likely to undergo angiography (OR 0.63, 95% CI 0.47-0.83) with a trend toward more subsequent stress testing. Stratified analyses revealed less subsequent testing in high-to-intermediate Duke Treadmill Score women compared with men (OR 0.61, 95% CI 0.48-0.79). Women and men were equally likely to die (hazards ratio 0.93, 95% CI 0.61-1.44) in the adjusted survival analysis. Conclusions: Overall, women and men equally underwent subsequent diagnostic testing after ETT. Although women were less likely to undergo angiography and higher-risk women were less likely to undergo subsequent testing, adverse events were not higher in women. Given these findings, assumptions regarding gender disparities in clinical management after ETT should be reevaluated in other settings. [Copyright &y& Elsevier]

Background: Unstable angina (UA) patients have lower mortality and reinfarction risks than ST-elevation (STEMI) or non-ST elevation myocardial infarction (NSTEMI) patients and, accordingly, receive less aggressive treatment. Little is known, however, about the health status outcomes (angina, physical function, and quality of life) of UA versus MI patients among survivors of an ACS hospitalization. Methods: In a cohort of 1,192 consecutively enrolled ACS survivors from two Kansas City hospitals, we evaluated the associations between ACS presentation (UA, NSTEMI, and STEMI) and one-year health status (angina, physical functioning and quality of life), one-year cardiac rehospitalization rates, and two year mortality outcomes, using multivariable regression modeling. Results: After multivariable adjustment for demographic, hospital, co-morbidity, baseline health status, and treatment characteristics, UA patients had a greater prevalence of angina at 1 year than STEMI patients (adjusted relative risk [RR] = 1.42; 95% CI [1.06, 1.90]) and similar rates as NSTEMI patients (adjusted RR = 1.1; 95% CI [0.85, 1.42]). In addition, UA patients fared no better than MI patients in Short Form-12 physical component scores (UA as. STEMI score difference -0.05 points; 95% CI [-2.41, 2.3]; UA as. NSTEMI score difference -1.91 points; 95% CI [-4.01, 0.18]) or Seattle Angina Questionnaire quality of life scores (UA as. STEMI score difference -1.39 points; 95% CI [-5.63, 2.85]; UA as. NSTEMI score difference -0.24 points 95% CI [-4.01, 3.54]). Finally, UA patients had similar rehospitalization rates as MI patients (UA as. STEMI adjusted hazard ratio [HR] = 1.31; 95% CI [0.86, 1.99]; UA as. NSTEMI adjusted HR = 1.03; 95% CI [0.73, 1.47]), despite better 2-year survival (UA as. STEMI adjusted HR = 0.51; 95% confidence interval (CI) [0.28, 0.95]; UA as. NSTEMI adjusted HR = 0.40; 95% CI [0.24, 0.65]). Conclusion: Although UA patients have better survival rates, they have similar or worse one-year health status outcomes and cardiac rehospitalization rates as compared with MI patients. Clinicians should be aware of the adverse health status outcome risks for UA patients and consider close monitoring for the opportunity to improve their health status and minimize the need for subsequent rehospitalization. [ABSTRACT FROM AUTHOR]

Background: Few studies report on the effect of organizational factors facilitating transfer between primary and tertiary care hospitals either within an integrated health care system or outside it. In this paper, we report on the relationship between degree of clinical integration of cardiology services and transfer rates of acute coronary syndrome (ACS) patients from primary to tertiary hospitals within and outside the Veterans Health Administration (VHA) system. Methods: Prospective cohort study. Transfer rates were obtained for all patients with ACS diagnoses admitted to 12 primary VHA hospitals between 1998 and 1999. Binary variables measuring clinical integration were constructed for each primary VHA hospital reflecting: presence of on-site VHA cardiologist; referral coordinator at the associated tertiary VHA hospital; and/or referral coordinator at the primary VHA hospital. We assessed the association between the integration variables and overall transfer from primary to tertiary hospitals, using random effects logistic regression, controlling for clustering at two levels and adjusting for patient characteristics. Results: Three of twelve hospitals had a VHA cardiologist on site, six had a referral coordinator at the tertiary VHA hospital, and four had a referral coordinator at the primary hospital. Presence of a VHA staff cardiologist on site and a referral coordinator at the tertiary VHA hospital decreased the likelihood of any transfer (OR 0.45, 95% CI 0.27-0.77, and 0.46, p = 0.002, CI 0.27-0.78). Conversely, having a referral coordinator at the primary VHA hospital increased the likelihood of transfer (OR 6.28, CI 2.92-13.48). Conclusions: Elements of clinical integration are associated with transfer, an important process in the care of ACS patients. In promoting optimal patient care, clinical integration factors should be considered in addition to patient characteristics. [ABSTRACT FROM AUTHOR]

Discusses the predictors of the quality of life in patients who suffered from acute coronary syndromes in the past. Key issues of interest; Analysis of pertinent topics and relevant issues; Implications on cardiology.

The article discusses cardiac risk management in conjunction with severe mental illness. The authors note that patients with serious mental illness have a rate of mortality 1.5 times greater than the general population. The article contends that the higher death rates are related to coronary heart disease. Drugs that patients with severe mental illnesses, (such as schizophrenia), take can affect cardiac health. For example, many antipsychotic drugs affect weight and insulin levels. Also, it is possible that schizophrenics are more prone to becoming addicted to nicotine than non schizophrenics. Beyond the risk factors that smoking and diabetes represent for heart disease, it is thought that as many as half of the mentally ill do not follow doctors' instructions at some time during their treatment.

Before the coronavirus disease 2019 (COVID-19) pandemic, use of telehealth services had been limited in cardiovascular care. Potential benefits of telehealth include improved access to care, more efficient care management, reduced costs, the ability to assess patients within their homes while involving key caretakers in medical decisions, maintaining social distance, and increased patient satisfaction. Challenges include changes in payment models, issues with data security and privacy, potential depersonalization of the patient-clinician relationship, limitations in the use of digital health technologies, and the potential impact on disparities, including socioeconomic, gender, and age-related issues and access to technology and broadband. Implementation and expansion of telehealth from a policy and reimbursement practice standpoint are filled with difficult decisions, yet addressing these are critical to the future of health care. [ABSTRACT FROM AUTHOR]