Fractional flow reserve guided stent optimisation in focal and diffuse coronary artery disease

Assessing coronary physiology after stent implantation facilitates the optimisation of percutaneous coronary intervention (PCI). Coronary artery disease (CAD) patterns can be characterised by the pullback pressure gradient (PPG) index. The impact of focal vs. diffuse disease on physiology-guided incremental optimisation strategy (PIOS) is unknown. This is a sub-study of the TARGET-FFR randomized clinical trial (NCT03259815). The study protocol directed that optimisation be attempted for patients in the PIOS arm when post-PCI FFR was <0.90. Overall, 114 patients (n = 61 PIOS and 53 controls) with both pre-PCI fractional flow reserve (FFR) pullbacks and post-PCI FFR were included. A PPG ≥ 0.74 defined focal CAD. The PPG correlated significantly with post-PCI FFR (r = 0.43; 95% CI 0.26 to 0.57; p-value < 0.001) and normalised delta FFR (r = 0.49; 95% CI 0.34 to 0.62; p-value < 0.001). PIOS was more frequently applied to vessels with diffuse CAD (6% focal vs. 42% diffuse; p-value = 0.006). In patients randomized to PIOS, those with focal disease achieved higher post-PCI FFR than patients with diffuse CAD (0.93 ± 0.05 vs. 0.83 ± 0.07, p < 0.001). There was a significant interaction between CAD patterns and the randomisation arm for post-PCI FFR (p-value for interaction = 0.004). Physiology-guided stent optimisation was applied more frequently to vessels with diffuse disease; however, patients with focal CAD at baseline achieved higher post-PCI FF

Functionality and feedback: a realist synthesis of the collation, interpretation and utilisation of patient-reported outcome measures data to improve patient care

Background: The feedback of patient-reported outcome measures (PROMs) data is intended to support the care of individual patients and to act as a quality improvement (QI) strategy. Objectives: To (1) identify the ideas and assumptions underlying how individual and aggregated PROMs data are intended to improve patient care, and (2) review the evidence to examine the circumstances in which and processes through which PROMs feedback improves patient care. Design: Two separate but related realist syntheses: (1) feedback of aggregate PROMs and performance data to improve patient care, and (2) feedback of individual PROMs data to improve patient care. Interventions: Aggregate – feedback and public reporting of PROMs, patient experience data and performance data to hospital providers and primary care organisations. Individual – feedback of PROMs in oncology, palliative care and the care of people with mental health problems in primary and secondary care settings. Main outcome measures: Aggregate – providers’ responses, attitudes and experiences of using PROMs and performance data to improve patient care. Individual – providers’ and patients’ experiences of using PROMs data to raise issues with clinicians, change clinicians’ communication practices, change patient management and improve patient well-being. Data sources: Searches of electronic databases and forwards and backwards citation tracking. Review methods: Realist synthesis to identify, test and refine programme theories about when, how and why PROMs feedback leads to improvements in patient care. Results: Providers were more likely to take steps to improve patient care in response to the feedback and public reporting of aggregate PROMs and performance data if they perceived that these data were credible, were aimed at improving patient care, and were timely and provided a clear indication of the source of the problem. However, implementing substantial and sustainable improvement to patient care required system-wide approaches. In the care of individual patients, PROMs function more as a tool to support patients in raising issues with clinicians than they do in substantially changing clinicians’ communication practices with patients. Patients valued both standardised and individualised PROMs as a tool to raise issues, but thought is required as to which patients may benefit and which may not. In settings such as palliative care and psychotherapy, clinicians viewed individualised PROMs as useful to build rapport and support the therapeutic process. PROMs feedback did not substantially shift clinicians’ communication practices or focus discussion on psychosocial issues; this required a shift in clinicians’ perceptions of their remit. Strengths and limitations: There was a paucity of research examining the feedback of aggregate PROMs data to providers, and we drew on evidence from interventions with similar programme theories (other forms of performance data) to test our theories. Conclusions: PROMs data act as ‘tin openers’ rather than ‘dials’. Providers need more support and guidance on how to collect their own internal data, how to rule out alternative explanations for their outlier status and how to explore the possible causes of their outlier status. There is also tension between PROMs as a QI strategy versus their use in the care of individual patients; PROMs that clinicians find useful in assessing patients, such as individualised measures, are not useful as indicators of service quality. Future work: Future research should (1) explore how differently performing providers have responded to aggregate PROMs feedback, and how organisations have collected PROMs data both for individual patient care and to improve service quality; and (2) explore whether or not and how incorporating PROMs into patients’ electronic records allows multiple different clinicians to receive PROMs feedback, discuss it with patients and act on the data to improve patient care

Time to change direction in training load monitoring in elite football? The application of MEMS accelerometers for the evaluation of movement requirements

In elite football, the emphasis is placed on monitoring the output from the Global Positioning Systems (GPS) component of a Micro-Electro-Mechanical Systems (MEMS) device; however, this does not comprehensively overview the total demands due to the intermittent multidirectional nature. The aim of the study was to investigate the application of accelerometer data provided by MEMS, to evaluate movement requirements in elite football. A two-staged research approach, involving an effectiveness and efficacy stage, was deployed. The effectiveness stage examined two MEMS-accelerometer variables (PlayerLoadTM (PL) and PlayerLoadTM per meter (PL.m−1)) for four years and four months. Ninety-nine English Premier League outfield football players’ participated. In the efficacy stage, 26 elite outfield football players completed three different training modalities (running, possession and dribbling) and a range of MEMS-accelerometer variables were analysed. In the effectiveness stage, the mean difference in PL for all training activities other than Set Pieces were similar to Matches (−283 to −246au). Model coefficients for PL.m−1 were smallest in Team Shape (−0.00114au), Attacking (0.00025au) and Games (0.00196au), and largest for Possession (0.03356AU), Defending (0.03182au) and Skills Games (0.03106au) compared to Matches. The findings suggest that PL.m−1 but not PL may be effective at describing differences in movement requirements. In the efficacy stage, PL.m−1 and inertial movement analysis (IMA) efforts were the only variables that had greater mean differences in the smaller conditions, confirming PL.m−1’s suitability in evaluating movement requirements of different training activities and pitch dimensions. The findings suggest such a variable offers value in a monitoring strategy in football.</p

Synthesis and Biological Evaluation of 1-(Diarylmethyl)-1<i>H</i>-1,2,4-triazoles and 1-(Diarylmethyl)-1<i>H</i>-imidazoles as a Novel Class of Anti-Mitotic Agent for Activity in Breast Cancer

We report the synthesis and biochemical evaluation of compounds that are designed as hybrids of the microtubule targeting benzophenone phenstatin and the aromatase inhibitor letrozole. A preliminary screening in estrogen receptor (ER)-positive MCF-7 breast cancer cells identified 5-((2H-1,2,3-triazol-1-yl)(3,4,5-trimethoxyphenyl)methyl)-2-methoxyphenol 24 as a potent antiproliferative compound with an IC50 value of 52 nM in MCF-7 breast cancer cells (ER+/PR+) and 74 nM in triple-negative MDA-MB-231 breast cancer cells. The compounds demonstrated significant G2/M phase cell cycle arrest and induction of apoptosis in the MCF-7 cell line, inhibited tubulin polymerisation, and were selective for cancer cells when evaluated in non-tumorigenic MCF-10A breast cells. The immunofluorescence staining of MCF-7 cells confirmed that the compounds targeted tubulin and induced multinucleation, which is a recognised sign of mitotic catastrophe. Computational docking studies of compounds 19e, 21l, and 24 in the colchicine binding site of tubulin indicated potential binding conformations for the compounds. Compounds 19e and 21l were also shown to selectively inhibit aromatase. These compounds are promising candidates for development as antiproliferative, aromatase inhibitory, and microtubule-disrupting agents for breast cancer

Mechanistic and evolutionary insights into isoform-specific ‘supercharging’ in DCLK family kinases

Catalytic signaling outputs of protein kinases are dynamically regulated by an array of structural mechanisms, including allosteric interactions mediated by intrinsically disordered segments flanking the conserved catalytic domain. The Doublecortin Like Kinases (DCLKs) are a family of microtubule-associated proteins characterized by a flexible C-terminal autoregulatory ‘tail’ segment that varies in length across the various human DCLK isoforms. However, the mechanism whereby these isoform-specific variations contribute to unique modes of autoregulation is not well understood. Here, we employ a combination of statistical sequence analysis, molecular dynamics simulations and in vitro mutational analysis to define hallmarks of DCLK family evolutionary divergence, including analysis of splice variants within the DCLK1 sub-family, which arise through alternative codon usage and serve to ‘supercharge’ the inhibitory potential of the DCLK1 C-tail. We identify co-conserved motifs that readily distinguish DCLKs from all other Calcium Calmodulin Kinases (CAMKs), and a ‘Swiss-army’ assembly of distinct motifs that tether the C-terminal tail to conserved ATP and substrate-binding regions of the catalytic domain to generate a scaffold for auto-regulation through C-tail dynamics. Consistently, deletions and mutations that alter C-terminal tail length or interfere with co-conserved interactions within the catalytic domain alter intrinsic protein stability, nucleotide/inhibitor-binding, and catalytic activity, suggesting isoform-specific regulation of activity through alternative splicing. Our studies provide a detailed framework for investigating kinome–wide regulation of catalytic output through cis-regulatory events mediated by intrinsically disordered segments, opening new avenues for the design of mechanistically-divergent DCLK1 modulators, stabilizers or degraders.</jats:p

Post-stenting fractional flow reserve vs coronary angiography for optimization of percutaneous coronary intervention (TARGET-FFR)

Aims: A fractional flow reserve (FFR) value ≥0.90 after percutaneous coronary intervention (PCI) is associated with a reduced risk of adverse cardiovascular events. TARGET-FFR is an investigator-initiated, single-centre, randomized controlled trial to determine the feasibility and efficacy of a post-PCI FFR-guided optimization strategy vs. standard coronary angiography in achieving final post-PCI FFR values ≥0.90. Methods and results: After angiographically guided PCI, patients were randomized 1:1 to receive a physiology-guided incremental optimization strategy (PIOS) or a blinded coronary physiology assessment (control group). The primary outcome was the proportion of patients with a final post-PCI FFR ≥0.90. Final FFR ≤0.80 was a prioritized secondary outcome. A total of 260 patients were randomized (131 to PIOS, 129 to control) and 68.1% of patients had an initial post-PCI FFR &lt;0.90. In the PIOS group, 30.5% underwent further intervention (stent post-dilation and/or additional stenting). There was no significant difference in the primary endpoint of the proportion of patients with final post-PCI FFR ≥0.90 between groups (PIOS minus control 10%, 95% confidence interval −1.84 to 21.91, P = 0.099). The proportion of patients with a final FFR ≤0.80 was significantly reduced when compared with the angiography-guided control group (−11.2%, 95% confidence interval −21.87 to −0.35], P = 0.045). Conclusion: Over two-thirds of patients had a physiologically suboptimal result after angiography-guided PCI. An FFR-guided optimization strategy did not significantly increase the proportion of patients with a final FFR ≥0.90, but did reduce the proportion of patients with a final FFR ≤0.80

Individual quality of life: can it be accounted for by psychological or subjective well-being?

individual quality of life, psychological well-being, SEIQoL, subjective well-being, SEM, theoretical model,