12 research outputs found

    Incidence of acute cerebrovascular events in patients with rheumatic or calcific mitral stenosis: a systematic review and meta-analysis

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    Background Patients with mitral stenosis (MS) may be predisposed to acute cerebrovascular events (ACE) and peripheral thromboembolic events (TEE). Concomitant atrial fibrillation (AF), mitral annular calcification (MAC) and rheumatic heart disease (RHD) are independent risk factors. Our aim was to evaluate the incidence of ACEs in MS patients and the implications of AF, MAC, and RHD on thromboembolic risks. Methods This systematic review was registered on PROSPERO (CRD42021291316). Six databases were searched from inception to 19th December 2021. The clinical outcomes were composite ACE, ischaemic stroke/transient ischaemic attack (TIA), and peripheral TEE. Results We included 16 and 9 papers, respectively, in our qualitative and quantitative analyses. The MS cohort with AF had the highest incidence of composite ACE (31.55%; 95%CI 3.60-85.03; I 2 =99%), followed by the MAC (14.85%; 95%CI 7.21-28.11; I 2 =98%), overall MS (8.30%; 95%CI 3.45-18.63; I 2 =96%) and rheumatic MS population (4.92%; 95%CI 3.53-6.83; I 2 =38%). Stroke/TIA were reported in 29.62% of the concomitant AF subgroup (95%CI 2.91-85.51; I 2 =99%) and in 7.11% of the overall MS patients (95%CI 1.91-23.16; I 2 =97%). However, the heterogeneity of the pooled incidence of clinical outcomes in all groups, except the rheumatic MS group, were substantial and significant. The logit-transformed proportion of composite ACE increased by 0.0141 (95% CI 0.0111-0.0171; p<0.01) per year of follow-up. Conclusion In the MS population, MAC and concomitant AF are risk factors for the development of ACE. The scarcity of data in our systematic review reflects the need for further studies to explore thromboembolic risks in all MS subtypes

    Slow viscous flow of two porous spherical particles translating along the axis of a cylinder

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    We describe the motion of two freely moving porous spherical particles located along the axis of a cylindrical tube with background Poiseuille flow at low Reynolds number. The stream function and a framework based on cylindrical harmonics are adopted to solve the flow field around the particles and the flow within the tube, respectively. The two solutions are employed in an iterated framework using the method of reflections. We first consider the case of two identical particles, followed by two particles with different dimensions. In both cases, the drag force coefficients of the particles are solved as functions of the separation distance between the particles and the permeability of the particles. The detailed flow field in the vicinity of the two particles is investigated by plotting the streamlines and velocity contours. We find that the particle–particle interaction is dependent on the separation distance, particle sizes and permeability of the particles. Our analysis reveals that when the permeability of the particles is large, the streamlines are more parallel and the particle–particle interaction has less effect on the particle motion. We further show that a smaller permeability and bigger particle size generally tend to squeeze the streamlines and velocity contour towards the wall.Accepted versio

    Machine Learning Modeling to Predict Atrial Fibrillation Detection in Embolic Stroke of Undetermined Source Patients.

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    BackgroundIn patients with embolic stroke of undetermined source (ESUS), occult atrial fibrillation (AF) has been implicated as a key source of cardioembolism. However, only a minority acquire implantable cardiac loop recorders (ILRs) to detect occult paroxysmal AF, partly due to financial cost and procedural inconvenience. Without the initiation of appropriate anticoagulation, these patients are at risk of increased ischemic stroke recurrence. Hence, cost-effective and accurate methods of predicting AF in ESUS patients are highly sought after.ObjectiveWe aimed to incorporate clinical and echocardiography data into machine learning (ML) algorithms for AF prediction on ILRs in ESUS.MethodsThis was a single-center cohort study that included 157 consecutive patients diagnosed with ESUS from October 2014 to October 2017 who had ILR evaluation. We developed four ML models, with hyperparameters tuned, to predict AF detection on an ILR.ResultsThe median age of the cohort was 67 (IQR 59-74) years old and the median monitoring duration was 1051 (IQR 478-1287) days. Of the 157 patients, 32 (20.4%) had occult AF detected on the ILR. Support vector machine predicted for AF with a 95% confidence interval area under the receiver operating characteristic curve (AUC) of 0.736-0.737, multilayer perceptron with an AUC of 0.697-0.708, XGBoost with an AUC of 0.697-0.697, and random forest with an AUC of 0.663-0.674. ML feature importance found that age, HDL-C, and admitting heart rate were important non-echocardiography variables, while peak mitral A-wave velocity and left atrial volume were important echocardiography parameters aiding this prediction.ConclusionMachine learning modeling incorporating clinical and echocardiographic variables predicted AF in ESUS patients with moderate accuracy

    A systematic scoping review of ethical issues in mentoring in medical schools

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    BACKGROUND:Mentoring provides mentees and mentors with holistic support and research opportunities. Yet, the quality of this support has been called into question amidst suggestions that mentoring is prone to bullying and professional lapses. These concerns jeopardise mentoring's role in medical schools and demand closer scrutiny. METHODS:To better understand prevailing concerns, a novel approach to systematic scoping reviews (SSR) s is proposed to map prevailing ethical issues in mentoring in an accountable and reproducible manner. Ten members of the research team carried out systematic and independent searches of PubMed, Embase, ERIC, ScienceDirect, Scopus, OpenGrey and Mednar databases. The individual researchers employed 'negotiated consensual validation' to determine the final list of articles to be analysed. The reviewers worked in three independent teams. One team summarised the included articles. The other teams employed independent thematic and content analysis respectively. The findings of the three approaches were compared. The themes from non-evidence based and grey literature were also compared with themes from research driven data. RESULTS:Four thousand six titles were reviewed and 51 full text articles were included. Findings from thematic and content analyses were similar and reflected the tabulated summaries. The themes/categories identified were ethical concerns, predisposing factors and possible solutions at the mentor and mentee, mentoring relationship and/or host organisation level. Ethical concerns were found to stem from issues such as power differentials and lack of motivation whilst predisposing factors comprised of the mentor's lack of experience and personality conflicts. Possible solutions include better program oversight and the fostering of an effective mentoring environment. CONCLUSIONS:This structured SSR found that ethical issues in mentoring occur as a result of inconducive mentoring environments. As such, further studies and systematic reviews of mentoring structures, cultures and remediation must follow so as to guide host organisations in their endeavour to improve mentoring in medical schools

    Incidence of acute cerebrovascular events in patients with rheumatic or calcific mitral stenosis: A systematic review and meta-analysis

    No full text
    Background: Patients with mitral stenosis (MS) may be predisposed to acute cerebrovascular events (ACE) and peripheral thromboembolic events (TEE). Concomitant atrial fibrillation (AF), mitral annular calcification (MAC) and rheumatic heart disease (RHD) are independent risk factors. Our aim was to evaluate the incidence of ACEs in MS patients and the implications of AF, MAC and RHD on thromboembolic risks. Methods: This systematic review was registered on PROSPERO (CRD42021291316). Six databases were searched from inception to 19th December 2021. The clinical outcomes were composite ACE, ischaemic stroke/transient ischaemic attack (TIA) and peripheral TEE. Results: We included 16 and 9 papers, respectively, in our qualitative and quantitative analyses. The MS cohort with AF had the highest incidence of composite ACE (31.55%; 95% CI 3.60–85.03; I2 = 99%), followed by the MAC (14.85%; 95% CI 7.21–28.11; I2 = 98%), overall MS (8.30%; 95% CI 3.45–18.63; I2 = 96%) and rheumatic MS population (4.92%; 95% CI 3.53–6.83; I2 = 38%). Stroke/TIA were reported in 29.62% of the concomitant AF subgroup (95% CI 2.91–85.51; I2 = 99%) and in 7.11% of the overall MS patients (95% CI 1.91–23.16; I2 = 97%). However, the heterogeneity of the pooled incidence of clinical outcomes in all groups, except the rheumatic MS group, was substantial and significant. The logit-transformed proportion of composite ACE increased by 0.0141 (95% CI 0.0111–0.0171; p < 0.01) per year of follow-up. Conclusion: In the MS population, MAC and concomitant AF are risk factors for the development of ACE. The scarcity of data in our systematic review reflects the need for further studies to explore thromboembolic risks in all MS subtypes
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