Looking at the frame after the picture: "retrocardiac echocardiography".

We report three cases of mediastinal structures encroaching on the left atrium without haemodynamic compromise. These cases emphasize the potential role of echocardiography for the diagnosis and the management of several extracardiac mediastinal abnormalities.

Transfer Learning Video Classification of Preserved, Mid-Range, and Reduced Left Ventricular Ejection Fraction in Echocardiography.

Identifying patients with left ventricular ejection fraction (EF), either reduced [EF < 40% (rEF)], mid-range [EF 40-50% (mEF)], or preserved [EF > 50% (pEF)], is considered of primary clinical importance. An end-to-end video classification using AutoML in Google Vertex AI was applied to echocardiographic recordings. Datasets balanced by majority undersampling, each corresponding to one out of three possible classifications, were obtained from the Standford EchoNet-Dynamic repository. A train-test split of 75/25 was applied. A binary video classification of rEF vs. not rEF demonstrated good performance (test dataset: ROC AUC score 0.939, accuracy 0.863, sensitivity 0.894, specificity 0.831, positive predicting value 0.842). A second binary classification of not pEF vs. pEF was slightly less performing (test dataset: ROC AUC score 0.917, accuracy 0.829, sensitivity 0.761, specificity 0.891, positive predicting value 0.888). A ternary classification was also explored, and lower performance was observed, mainly for the mEF class. A non-AutoML PyTorch implementation in open access confirmed the feasibility of our approach. With this proof of concept, end-to-end video classification based on transfer learning to categorize EF merits consideration for further evaluation in prospective clinical studies.

D-dimer blood concentrations to exclude left atrial thrombus in patients with atrial fibrillation.

OBJECTIVE: Left atrial (LA) thrombus is routinely excluded by transoesophageal echocardiography (TOE) before cardioversion for non-valvular atrial fibrillation (AF). In the D-dimer blood concentrations to exclude LA thrombus in patients with AF study, two D-dimer cut-offs were compared to exclude LA thrombus prior to cardioversion. One was fixed to 500 ng/mL (DD500), based on clinical practice where such values are commonly accepted to exclude a thrombus. The other cut-off was adjusted to 10 times the patient's age (DDAge), based on the cut-off used to exclude pulmonary embolism. METHODS: 142 consecutive patients with non-valvular AF aged 69.7±11.4 years (52% with paroxysmal AF) referred for precardioversion TOE to exclude LA thrombus were prospectively enrolled. D-dimers were measured at the time of TOE by an ELISA test. RESULTS: LA thrombus was excluded with TOE in 129 (91%) and confirmed in 13 (9%) patients. D-dimers were significantly lower in patients without LA thrombus (729±611 vs 2376±1081 ng/L; p<0.05). DDAge indicated absence of LA thrombus with higher specificity than DD500 (66.4% vs 50.4%; p<0.05). Both cut-offs were able to identify all 13 patients with LA thrombus (false negative 0%). Patients with D-dimers

A description of medicines-related safety issues evaluated through a referral procedure at the EU level after 2012.

INTRODUCTION: Important drug safety issues are evaluated through a referral procedure in the EU by the Pharmacovigilance Risk Assessment Committee (PRAC) within the European Medicines Agency. We aim to describe all safety-related referrals assessed by the PRAC by June 2019. METHODS: Publicly available data on safety issues assessed through referral procedures that reached a final decision during July 2012-June 2019 were identified, analyzed and classified according to predefined criteria. RESULTS: Fifty-one safety issues were assessed by PRAC for 45 medicines/combinations/therapeutic classes during this timeframe. Referrals were initiated mostly by the European Commission (16) and France (8). Nine medicines were authorized in the last five years, the rest being well-established drugs. In four cases (flupirtine, hydroxyethyl-starch, valproate, codeine) PRAC re-assessed the same risks as previous recommendations have not been effective. Post-referral recommendations consisted of updates of the summary of product characteristics and package leaflet (42), Direct Healthcare Professional Communication (32), and other additional risk minimization measures (RMMs). Withdrawal was recommended for seven active substances. CONCLUSIONS: PRAC recommended routine or additional RMMs for most referrals. Complete withdrawal of a drug or withdrawal of certain pharmaceutical forms or concentrations was advised only when the risk could not be managed by RMMs.

An overview of the common methods used to measure treatment adherence.

BACKGROUND AND AIMS: The success of a treatment depends on the effectiveness of the medication regimen, provided that patients take the medicines as prescribed. A low rate of adherence in chronic conditions is associated with poor outcome and decreased quality of life, which constitutes an additional burden for the healthcare systems. To correctly identify the dimension of this problem may be a challenge, as there are numerous methods, definitions, patient settings and factors, each with their specific roles. Our aim was to give an appropriate overview of the most common validated methods that can be used to identify non-adherent patients. METHODS: This overview is based on an online search of PubMed database and includes the relevant articles in this field. RESULTS: We included both direct and indirect methods for measuring treatment adherence and presented concise information that can help researchers and clinicians when choosing an appropriate method. Both subjective and objective methods have advantages and disadvantages that should be fully understood and taken into consideration. CONCLUSIONS: Choosing a simple, accurate and inexpensive method that can give supplementary information about the patterns, beliefs and barriers of adherence would be desirable. But because this perfect method to measure treatment adherence does not exist, the best solution seems to be the combined use of at least two methods.

Medication adherence and persistence in patients with autoimmune rheumatic diseases: a narrative review.

BACKGROUND: Several drugs are available for the treatment of autoimmune rheumatic diseases; however, their effectiveness may be negatively influenced by inappropriate adherence. Low adherence and persistence rates have a significant impact on patient quality of life and are associated with health-related expenses. PURPOSE: To provide an up-to-date narrative review on treatment adherence and persistence rates, and discuss the factors that influence them, in patients with autoimmune rheumatic diseases. MATERIALS AND METHODS: We searched the PubMed database for studies among patients with a diagnosis of rheumatoid arthritis (RA), ankylosing spondylitis (AS), systemic lupus erythematosus (SLE), or psoriatic arthritis (PsA), published from January 2015 to February 2017. Only studies with a well-defined measurement of adherence/persistence and those that carried out an evaluation of the influencing factors were included. RESULTS: Fifteen relevant studies that evaluated adherence and/or persistence were included. Adherence rates varied between 9.3% and 94%, and persistence rates between 23% and 80%. Most of the studies used one method to evaluate adherence or persistence (different questionnaire scores, proportion of days covered, and mean treatment duration). A high concordance was found between the adherence measurements of the Medication Event Monitoring System and Visual Analog Scale. Factors of economic, demographic, and clinical nature were only moderately linked to treatment adherence or persistence. However, patient-related factors - such as positive and increased beliefs in medication necessity, strong views of the chronic nature of the diseases, and increased knowledge of the disease - were related to better treatment adherence. CONCLUSION: Owing to the heterogeneity of the study results, we consider that the use of more than one method to assess adherence/persistence should yield more comprehensive and accurate data about patient adherence behavior. Patient-related factors should be included and analyzed more often in adherence studies as the former may be modified to improve patient adherence.