2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). Developed with the special contribution of the Heart Failure Association (HFA) of the ESC.

Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

XI. STRATEGIES FOR IMPROVING DIABETES CARE D iabetes is a chronic illness that requires continuing medical care and patient self-management education to prevent acute complications and to reduce the risk of long-term complications. Diabetes care is complex and requires that many issues, beyond glycemic control, be addressed. A large body of evidence exists that supports a range of interventions to improve diabetes outcomes. These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care. While individual preferences, comorbidities, and other patient factors may require modification of goals, targets that are desirable for most patients with diabetes are provided. These standards are not intended to preclude more extensive evaluation and management of the patient by other specialists as needed. For more detailed information, refer to Bode (Ed.): Medical Management of Type 1 Diabetes (1), Burant (Ed): Medical Management of Type 2 Diabetes (2), and Klingensmith (Ed): Intensive Diabetes Management (3). The recommendations included are diagnostic and therapeutic actions that are known or believed to favorably affect health outcomes of patients with diabetes. A grading system (Table 1), developed by the American Diabetes Association (ADA) and modeled after existing methods, was utilized to clarify and codify the evidence that forms the basis for the recommendations. The level of evidence that supports each recommendation is listed after each recommendation using the letters A, B, C, or E.

Standards of Medical Care in Diabetes

Data Mining Practical Machine Learning Tools and Techniques

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2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure.

Cardiac amyloidosis (CA) is increasingly diagnosed due to the advancements made in diagnostics and therapeutics in the last decades, particularly in the field of transthyretin-related CA. Studies that have used bone scintigraphy for screening at-risk conditions have shown that about one out of ten patients with heart failure with preserved ejection fraction (HFpEF), aortic stenosis undergoing valve replacement, or hypertrophic cardiomyopathy (HCM) diagnosed later in life might have an underlying or concomitant CA. At the same time, the epidemiology of these conditions is also rapidly evolving. HFpEF has become the leading form of heart failure, and HFpEF patients are increasingly cared for in non-cardiology settings due to their older age and substantial burden of comorbidities. Aortic stenosis is increasingly treated percutaneously at earlier stages of the disease, determining a significant gain in survival. Hypertrophic cardiomyopathy is nowadays mostly diagnosed in middle-aged adults with near-normal life expectancy, with a greater chance of misdiagnosing CA as HCM or of an overlap between the two conditions. In all these contexts, the therapeutic and prognostic implications of diagnosing CA will have to be further investigated. Meanwhile, the diagnostic workup of patients with suspected CA should always be completed with the systematic exclusion of a plasma cell dyscrasia, the acquisition of tomographic imaging at bone scintigraphy, and the completion of genetic testing for transthyretin-related forms.

Cardiac amyloidosis: a changing epidemiology with open challenges

Tyr78Phe is a rare pathogenic transthyretin (TTR) mutation. Few previous reports described a late-onset hereditary transthyretin-related amyloidosis (ATTR-m) form with a variable phenotype, mainly dominated by neurological manifestations. We describe the case of a 69-year-old male with massive but asymptomatic cardiac infiltration and only subclinical neurological involvement, and review the literature to depict characteristics of the Tyr78Phe TTR mutation.

Amyloid Cardiomyopathy in the Rare Transthyretin Tyr78Phe Mutation

Letter regarding the article 'Heart failure with preserved ejection fraction: from mechanisms to therapies' by Lam and colleagues.

To compare the efficacy and safety of different mechanical circulatory support (MCS) devices in CS. A total of 24 studies (7 randomized controlled trials—RCTs—and 17 non-RCTs) involving 11,117 patients were entered in a Bayesian network meta-analysis. The primary endpoint was 30-day mortality. Secondary endpoints were stroke and bleeding (requiring transfusion and/or intracranial and/or fatal). Compared with no MCS, extra-corporeal membrane oxygenation (ECMO) reduced 30-day mortality when used both alone (OR 0.37, 95% CrI 0.15–0.90) and together with the micro-axial pump Impella (OR 0.13, 95% CrI 0.02–0.80) or intra-aortic balloon pump (IABP) (OR 0.19, 95% CrI 0.05–0.63), although the relevant articles were affected by significant publication bias. Consistent results were obtained in a sensitivity analysis including only studies of CS due to myocardial infarction. After halving the weight of studies with a non-RCT design, only the benefit of ECMO + IABP on 30-day mortality was maintained (OR 0.22, 95% CI 0.057–0.76). The risk of bleeding was increased by TandemHeart (OR 13, 95% CrI 3.50–59), Impella (OR 5, 95% CrI 1.60–18), and IABP (OR 2.2, 95% CrI 1.10–4.4). No significant differences were found across MCS strategies regarding stroke. Although limited by important quality issues, the studies performed so far indicate that ECMO, especially if combined with Impella or IABP, reduces short-term mortality in CS. MCS increases the hazard of bleeding.

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Mechanical circulatory support in patients with cardiogenic shock not secondary to cardiotomy: a network meta-analysis

BACKGROUND In the last years translation from bench to bedside of findings regarding cardiac cell therapy is swinging between delays and accelerations Based on experimental studies, clinical trials were started in 2001 To date in Europe more than 900 patients have been treated with cell transplantation or mobilization and new clinical trials are ongoing in many countries Published data provide a limited idea of current Italian clinical research in this field This investigation intends to report Italian clinical trials and projects using cell therapy in cardiology METHODS Italian Centers involved in cell therapy clinical studies have been detected exploring scientific bibliography and online search engine Selected Centers have been classified by the origin of collected information: i) peer-reviewed journals; ii) abstract, poster or communications; iii) press or media A questionnaire was used and face-to-face or telephonic interviews were performed to obtain further details where needed RESULTS Among the 16 selected Centers, 5 published their experiences on peer-reviewed journals, 5 produced abstracts or communications for scientific meetings and 6 bring out their protocols through press or media Usually Italian clinical trials are monocenter (11 monocenter studies, 2 multicenter) and enrol few patients (an average of about 10 patients treated in each study); 2 Centers are waiting for protocol approval by the Italian Institute of Health; in one case approval was not obtained by the Ethics Committee Few centers found projects on their own preclinical studies CONCLUSIONS The investigation on Italian clinical experiences with cardiac cell therapy demonstrates the limits of what has been produced so far An Italian working group on cardiovascular regenerative therapies could represent a useful tool to improve national clinical research in this field

Marco Canepa

Papers

Cardiac amyloidosis: a changing epidemiology with open challenges

Amyloid Cardiomyopathy in the Rare Transthyretin Tyr78Phe Mutation

Letter regarding the article 'Heart failure with preserved ejection fraction: from mechanisms to therapies' by Lam and colleagues.

Mechanical circulatory support in patients with cardiogenic shock not secondary to cardiotomy: a network meta-analysis

[Italian clinical trials on cardiac cell therapy: where we are and where are we going?].