Histogram bandwidth is a better predictor than Echocardiographic Tissue Doppler peak systolic velocity for Cardiac Resynchronization Therapy response

Objectives: The aim of this study is to compare degree of left ventricular dyssynchrony as assessed with phase analysis from Gated myocardial perfusion SPECT (GMPS) to that assessed with Echocardiographic Tissue Doppler Imaging (TDI) in patients with left ventricular EF 120 ms. Patients & methodology: 30 patients were included, all scheduled for CRT. TDI was measured as standard deviation of time to peak systolic velocity in 6 basal segments. Gated SPECT TC-99m sestamibi acquisition was performed, software phase analysis parameters is histogram bandwidth which include 95% of the element of the phase distribution. Study population was divided into two groups: responders and non-responders according to increase of at least 15% of LVEF after 3 months. Results: ROC analysis was done to reveal that Phase analysis parameter acted in better way to predict CRT response with histogram bandwidth 55.5° Area Under Curve (AUC) 68.9% sensitivity 87% specificity 42.9% positive predictive value (PPV) 83.3% negative predictive value (NPV) 50% compared to TDI sensitivity 52.25%, specificity 71.4% PPV 85.7% NPV 31.3% When applying histogram bandwidth cutoff 55.5° dyssynchrony was illustrated in 20 (87%) patients in comparison to 14 (60%) patients with Echo TDI, there was significant difference in sensitivity of histogram bandwidth compared to TDI with p value 0.043. Conclusion: Histogram bandwidth of GMPS Tc99m sestamibi may be more predictive of significant response to CRT as compared to TDI

Understanding what matters most to patients in acute care in seven countries, using the flash mob study design

Background Truly patient-centred care needs to be aligned with what patients consider important, and is highly desirable in the first 24 h of an acute admission, as many decisions are made during this period. However, there is limited knowledge on what matters most to patients in this phase of their hospital stay. The objective of this study was to identify what mattered most to patients in acute care and to assess the patient perspective as to whether their treating doctors were aware of this. Methods This was a large-scale, qualitative, flash mob study, conducted simultaneously in sixty-six hospitals in seven countries, starting November 14th 2018, ending 50 h later. One thousand eight hundred fifty adults in the first 24 h of an acute medical admission were interviewed on what mattered most to them, why this mattered and whether they felt the treating doctor was aware of this. Results The most reported answers to “what matters most (and why)?” were ‘getting better or being in good health’ (why: to be with family/friends or pick-up life again), ‘getting home’ (why: more comfortable at home or to take care of someone) and ‘having a diagnosis’ (why: to feel less anxious or insecure). Of all patients, 51.9% felt the treating doctor did not know what mattered most to them. Conclusions The priorities for acutely admitted patients were ostensibly disease- and care-oriented and thus in line with the hospitals’ own priorities. However, answers to why these were important were diverse, more personal, and often related to psychological well-being and relations. A large group of patients felt their treating doctor did not know what mattered most to them. Explicitly asking patients what is important and why, could help healthcare professionals to get to know the person behind the patient, which is essential in delivering patient-centred care

Additional file 1 of Understanding what matters most to patients in acute care in seven countries, using the flash mob study design

Additional file 1: Figure S1. Developmental process of framework. Table S1. Framework for coding. Table S2. Top ten answers to the question ‘what matters most’. Table S3. Top ten answers to the question ‘why is this important’. Table S4. Differences in what matters and why between sex, age groups, length of stay and if patients feel the doctor knows what matters or not. Table S5. Differences in what matters and why to patients between countries. List of local collaborators