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Annals of Noninvasive Electrocardiology... Nov 2022This systematic review aimed to explore an association of new TR and its quantification in patients undergoing His bundle pacing (HBP). (Review)
Review
OBJECTIVE
This systematic review aimed to explore an association of new TR and its quantification in patients undergoing His bundle pacing (HBP).
METHODS
A literature review was conducted using Mesh terms (His bundle pacing, tricuspid regurgitation, tricuspid valve incompetence, etc.) in PubMed, EMBASE, Web of science CINAHL, and the Cochrane Library till October 2021. Relevant studies evaluating tricuspid regurgitation in HBP were included and information regarding TR and its related factors (ejection fraction (EF) and New York Heart Association (NYHA) class) were retrieved from the eligible studies.
RESULTS
Out of 196 articles, 10 studies met the inclusion criteria, which consisted of 546 patients with HBP. The mean age of the patients ranged between 61.2 ± 12.3 and 75.1 ± 7.9 years with 54.1% males. The overall implant success rate was 79.2%. Only one study reported a 5% incidence of TR, while 9 studies reported no new TR after HBP. Four studies reported overall decrease in TR by 1 grade and 3 studies demonstrated increased TR from baseline. Two studies showed no change from baseline TR.
CONCLUSION
HBP causes improvement in TR grade after HBP for cardiac resynchronization therapy (CRT) as well as atrioventricular block (AVB). Further studies in the form of randomized controlled trials are required to further evaluate the effect of HBP on tricuspid valve functioning.
Topics: Male; Humans; Middle Aged; Aged; Female; Bundle of His; Tricuspid Valve Insufficiency; Electrocardiography; Treatment Outcome; Cardiac Resynchronization Therapy; Cardiac Pacing, Artificial
PubMed: 35763445
DOI: 10.1111/anec.12986 -
Clinical Cardiology Jul 2023Cardiac resynchronization therapy (CRT) strategy for heart failure with mildly reduced ejection fraction (HFmrEF) is controversial. Left bundle branch area pacing... (Meta-Analysis)
Meta-Analysis Review
Cardiac resynchronization therapy (CRT) strategy for heart failure with mildly reduced ejection fraction (HFmrEF) is controversial. Left bundle branch area pacing (LBBAP) is an emerging pacing modality and an alternative option to CRT. This analysis aimed to perform a systematic review of the literature and meta-analysis on the impact of the LBBAP strategy in HFmrEF, with left ventricular ejection fraction (LVEF) between 35% and 50%. PubMed, Embase, and Cochrane Library were searched for full-text articles on LBBAP from inception to July 17, 2022. The outcomes of interest were QRS duration and LVEF at baseline and follow-up in mid-range heart failure. Data were extracted and summarized. A random-effect model incorporating the potential heterogeneity was used to synthesize the results. Out of 1065 articles, 8 met the inclusion criteria for 211 mid-range heart failure patients with an implant LBBAP across the 16 centers. The average implant success rate with lumenless pacing lead use was 91.3%, and 19 complications were reported among all 211 enrolled patients. During the average follow-up of 9.1 months, the average LVEF was 39.8% at baseline and 50.5% at follow-up (MD: 10.90%, 95% CI: 6.56-15.23, p < .01). Average QRS duration was 152.6 ms at baseline and 119.3 ms at follow-up (MD: -34.51 ms, 95% CI: -60.00 to -9.02, p < .01). LBBAP could significantly reduce QRS duration and improve systolic function in a patient with LVEF between 35% and 50%. Application of LBBAP as a CRT strategy for HFmrEF may be a viable option.
Topics: Humans; Stroke Volume; Cardiac Pacing, Artificial; Ventricular Function, Left; Heart Conduction System; Cardiac Resynchronization Therapy; Heart Failure; Electrocardiography; Treatment Outcome
PubMed: 37144691
DOI: 10.1002/clc.24028 -
Diagnostics (Basel, Switzerland) Dec 2022Heart disease is one of the leading causes of mortality throughout the world. Among the different heart diagnosis techniques, an electrocardiogram (ECG) is the least... (Review)
Review
Heart disease is one of the leading causes of mortality throughout the world. Among the different heart diagnosis techniques, an electrocardiogram (ECG) is the least expensive non-invasive procedure. However, the following are challenges: the scarcity of medical experts, the complexity of ECG interpretations, the manifestation similarities of heart disease in ECG signals, and heart disease comorbidity. Machine learning algorithms are viable alternatives to the traditional diagnoses of heart disease from ECG signals. However, the black box nature of complex machine learning algorithms and the difficulty in explaining a model's outcomes are obstacles for medical practitioners in having confidence in machine learning models. This observation paves the way for interpretable machine learning (IML) models as diagnostic tools that can build a physician's trust and provide evidence-based diagnoses. Therefore, in this systematic literature review, we studied and analyzed the research landscape in interpretable machine learning techniques by focusing on heart disease diagnosis from an ECG signal. In this regard, the contribution of our work is manifold; first, we present an elaborate discussion on interpretable machine learning techniques. In addition, we identify and characterize ECG signal recording datasets that are readily available for machine learning-based tasks. Furthermore, we identify the progress that has been achieved in ECG signal interpretation using IML techniques. Finally, we discuss the limitations and challenges of IML techniques in interpreting ECG signals.
PubMed: 36611403
DOI: 10.3390/diagnostics13010111 -
Intensive Care Medicine Nov 2022The aim of this study was to perform a systematic review and meta-analysis to investigate the incidence rate of cardiac arrest and severe complications occurring under... (Meta-Analysis)
Meta-Analysis
PURPOSE
The aim of this study was to perform a systematic review and meta-analysis to investigate the incidence rate of cardiac arrest and severe complications occurring under non-invasive ventilation (NIV).
METHODS
We performed a systematic review and meta-analysis of studies between 1981 and 2020 that enrolled adults in whom NIV was used to treat acute respiratory failure (ARF). We generated the pooled incidence and confidence interval (95% CI) of NIV-related cardiac arrest per patient (primary outcome) and performed a meta-regression to assess the association with study characteristics. We also generated the pooled incidences of NIV failure and hospital mortality.
RESULTS
Three hundred and eight studies included a total of 7,601,148 participants with 36,326 patients under NIV (8187 in 138 randomized controlled trials, 9783 in 99 prospective observational studies, and 18,356 in 71 retrospective studies). Only 19 (6%) of the analyzed studies reported the rate of NIV-related cardiac arrest. Forty-nine cardiac arrests were reported. The pooled incidence was 0.01% (95% CI 0.00-0.02, I = 0% (0-15)). NIV failure was reported in 4371 patients, with a pooled incidence of 11.1% (95% CI 9.0-13.3). After meta-regression, NIV failure and the study period (before 2010) were significantly associated with NIV-related cardiac arrest. The hospital mortality pooled incidence was 6.0% (95% CI 4.4-7.9).
CONCLUSION
Cardiac arrest related to NIV occurred in one per 10,000 patients under NIV for ARF treatment. NIV-related cardiac arrest was associated with NIV failure.
Topics: Adult; Humans; Noninvasive Ventilation; Respiratory Insufficiency; Retrospective Studies; Respiration, Artificial; Respiratory Distress Syndrome; Hospital Mortality; Heart Arrest; Observational Studies as Topic
PubMed: 36112157
DOI: 10.1007/s00134-022-06821-y -
Frontiers in Human Neuroscience 2023Autonomous navigation of catheters and guidewires in endovascular interventional surgery can decrease operation times, improve decision-making during surgery, and reduce...
BACKGROUND
Autonomous navigation of catheters and guidewires in endovascular interventional surgery can decrease operation times, improve decision-making during surgery, and reduce operator radiation exposure while increasing access to treatment.
OBJECTIVE
To determine from recent literature, through a systematic review, the impact, challenges, and opportunities artificial intelligence (AI) has for the autonomous navigation of catheters and guidewires for endovascular interventions.
METHODS
PubMed and IEEEXplore databases were searched to identify reports of AI applied to autonomous navigation methods in endovascular interventional surgery. Eligibility criteria included studies investigating the use of AI in enabling the autonomous navigation of catheters/guidewires in endovascular interventions. Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA), articles were assessed using Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). PROSPERO: CRD42023392259.
RESULTS
Four hundred and sixty-two studies fulfilled the search criteria, of which 14 studies were included for analysis. Reinforcement learning (RL) (9/14, 64%) and learning from expert demonstration (7/14, 50%) were used as data-driven models for autonomous navigation. These studies evaluated models on physical phantoms (10/14, 71%) and (4/14, 29%) models. Experiments within or around the blood vessels of the heart were reported by the majority of studies (10/14, 71%), while non-anatomical vessel platforms "idealized" for simple navigation were used in three studies (3/14, 21%), and the porcine liver venous system in one study. We observed that risk of bias and poor generalizability were present across studies. No procedures were performed on patients in any of the studies reviewed. Moreover, all studies were limited due to the lack of patient selection criteria, reference standards, and reproducibility, which resulted in a low level of evidence for clinical translation.
CONCLUSION
Despite the potential benefits of AI applied to autonomous navigation of endovascular interventions, the field is in an experimental proof-of-concept stage, with a technology readiness level of 3. We highlight that reference standards with well-identified performance metrics are crucial to allow for comparisons of data-driven algorithms proposed in the years to come.
SYSTEMATIC REVIEW REGISTRATION
identifier: CRD42023392259.
PubMed: 37600553
DOI: 10.3389/fnhum.2023.1239374 -
Metabolites Mar 2022Parkinson’s disease (PD) is a severe, incurable, and costly condition leading to heart failure. The link between PD and cardiovascular disease (CVD) is not available,... (Review)
Review
Parkinson’s disease (PD) is a severe, incurable, and costly condition leading to heart failure. The link between PD and cardiovascular disease (CVD) is not available, leading to controversies and poor prognosis. Artificial Intelligence (AI) has already shown promise for CVD/stroke risk stratification. However, due to a lack of sample size, comorbidity, insufficient validation, clinical examination, and a lack of big data configuration, there have been no well-explained bias-free AI investigations to establish the CVD/Stroke risk stratification in the PD framework. The study has two objectives: (i) to establish a solid link between PD and CVD/stroke; and (ii) to use the AI paradigm to examine a well-defined CVD/stroke risk stratification in the PD framework. The PRISMA search strategy selected 223 studies for CVD/stroke risk, of which 54 and 44 studies were related to the link between PD-CVD, and PD-stroke, respectively, 59 studies for joint PD-CVD-Stroke framework, and 66 studies were only for the early PD diagnosis without CVD/stroke link. Sequential biological links were used for establishing the hypothesis. For AI design, PD risk factors as covariates along with CVD/stroke as the gold standard were used for predicting the CVD/stroke risk. The most fundamental cause of CVD/stroke damage due to PD is cardiac autonomic dysfunction due to neurodegeneration that leads to heart failure and its edema, and this validated our hypothesis. Finally, we present the novel AI solutions for CVD/stroke risk prediction in the PD framework. The study also recommends strategies for removing the bias in AI for CVD/stroke risk prediction using the PD framework.
PubMed: 35448500
DOI: 10.3390/metabo12040312 -
Cardiology 2022Heart failure (HF) is a severe and terminal stage of various heart diseases. Left ventricular assist devices (LVADs) are relatively mature and have contributed to the...
INTRODUCTION
Heart failure (HF) is a severe and terminal stage of various heart diseases. Left ventricular assist devices (LVADs) are relatively mature and have contributed to the treatment of end-stage HF. Ventricular arrhythmia (VA) is a common complication after LVAD implantation, including ventricular tachycardia and ventricular fibrillation, both of which may cause abnormal circulation.
METHODS
A literature search was conducted in the PubMed database, "Ventricular Arrhythmia" OR "VA" OR "Arrhythmia" OR "Ventricular Tachycardia," OR "Ventricular Fibrillation" AND "LVAD" OR "Left Ventricular Assist Device" OR "Heart Assist Device" as either keywords or MeSH terms, the authors screened the titles and abstracts of the articles. Eventually, 12 original research articles were retrieved.
RESULTS
The 0.83 [95% CI: 0.77, 0.89] of patients were male. A whole of 53% [95% CI: 0.25, 0.81] of VA patients had a history of atrial fibrillation and 61% [95% CI: 0.52, 0.69] had a history of VA. 39% [95% CI: 0.29, 0.49] of the participants had no prior history of VA and experienced new VA following CF-LVAD implantation. Following CF-LVAD implantation, 59% [95% CI: 0.51, 0.67] of patients developed early VA (VA ≤30 days). The 30-day mortality rate of patients was 4% [95% CI: 0.01, 0.07]. And overall mortality was 28% [95% CI: 0.15, 0.41]. The reported incidence of VA after LVAD implantation is not identical in different medical centers and ranges from 20% to 60%. The mechanism of VA after LVAD implantation is summarized as primary cardiomyopathy-related, device mechanical stimulation, myocardial scarring, ventricular displacement, electrolyte regulation, and other processes.
CONCLUSIONS
A preoperative VA history is considered a predictor of VA following LVAD implantation in most studies. Multiple mechanisms and factors, such as prevention of "suction events," ablation, and implantable cardioverter defibrillator, should be considered for the prevention and treatment of postoperative VA in patients requiring long-term VAD treatment. This study provides a reference for the clinical application of LAVD and the prevention of postoperative VA after LVAD implantation. Future multicenter prospective studies with uniform patient follow-up are needed to screen for additional potential risk factors and predictors. These studies will help to define the incidence rate of VA after LAVD implantation. As a result, we provide guidance for the selection of preventive intervention.
Topics: Arrhythmias, Cardiac; Female; Heart Failure; Heart-Assist Devices; Humans; Male; Risk Factors; Tachycardia, Ventricular; Treatment Outcome; Ventricular Fibrillation
PubMed: 35483328
DOI: 10.1159/000524779 -
The Lancet. Respiratory Medicine Dec 2022The association of respiratory mechanics, particularly respiratory system static compliance (C), with severity of hypoxaemia in patients with COVID-19-related acute... (Meta-Analysis)
Meta-Analysis Review
Respiratory system mechanics, gas exchange, and outcomes in mechanically ventilated patients with COVID-19-related acute respiratory distress syndrome: a systematic review and meta-analysis.
The association of respiratory mechanics, particularly respiratory system static compliance (C), with severity of hypoxaemia in patients with COVID-19-related acute respiratory distress syndrome (ARDS) has been widely debated, with some studies reporting distinct ARDS phenotypes based on C. Ascertaining whether such phenotypes exist is important, because they might indicate the need for ventilation strategies that differ from those used in patients with ARDS due to other causes. In a systematic review and meta-analysis of studies published between Dec 1, 2019, and March 14, 2022, we evaluated respiratory system mechanics, ventilator parameters, gas exchange parameters, and clinical outcomes in patients with COVID-19-related ARDS. Among 11 356 patients in 37 studies, mean reported C, measured close to the time of endotracheal intubation, was 35·8 mL/cm HO (95% CI 33·9-37·8; I=96·9%, τ=32·6). Pooled mean C was normally distributed. Increasing ARDS severity (assessed by PaO/FiO ratio as mild, moderate, or severe) was associated with decreasing C. We found no evidence for distinct C-based clinical phenotypes in patients with COVID-19-related ARDS, and we therefore conclude that no change in conventional lung-protective ventilation strategies is warranted. Future studies should explore the personalisation of mechanical ventilation strategies according to factors including respiratory system mechanics and haemodynamic status in patients with ARDS.
Topics: Humans; Respiration, Artificial; COVID-19; Respiratory Distress Syndrome; Respiratory Mechanics; Lung
PubMed: 36335956
DOI: 10.1016/S2213-2600(22)00393-9 -
Frontiers in Artificial Intelligence 2022The medical complexity and high acuity of patients in the cardiac intensive care unit make for a unique patient population with high morbidity and mortality. While there... (Review)
Review
The medical complexity and high acuity of patients in the cardiac intensive care unit make for a unique patient population with high morbidity and mortality. While there are many tools for predictions of mortality in other settings, there is a lack of robust mortality prediction tools for cardiac intensive care unit patients. The ongoing advances in artificial intelligence and machine learning also pose a potential asset to the advancement of mortality prediction. Artificial intelligence algorithms have been developed for application of electrocardiogram interpretation with promising accuracy and clinical application. Additionally, artificial intelligence algorithms applied to electrocardiogram interpretation have been developed to predict various variables such as structural heart disease, left ventricular systolic dysfunction, and atrial fibrillation. These variables can be used and applied to new mortality prediction models that are dynamic with the changes in the patient's clinical course and may lead to more accurate and reliable mortality prediction. The application of artificial intelligence to mortality prediction will fill the gaps left by current mortality prediction tools.
PubMed: 35711617
DOI: 10.3389/frai.2022.876007 -
Journal of the Academy of... 2022Chronic cerebral hypoperfusion is a potential mechanism that causes cognitive impairment in patients with heart failure. Cognitive impairment in this population is... (Review)
Review
BACKGROUND
Chronic cerebral hypoperfusion is a potential mechanism that causes cognitive impairment in patients with heart failure. Cognitive impairment in this population is associated with an increased mortality and poorer quality of life. Understanding the etiopathogenesis of cognitive impairment is crucial to developing effective treatment. A left ventricular assist device (LVAD) is a durable mechanical circulatory support device that restores systemic perfusion in patients with heart failure, potentially reversing cerebral hypoperfusion and cognitive impairment.
OBJECTIVE
This case series and systematic review examines the effect of LVAD implantation on cognition in patients with heart failure.
METHODS
We report a case series of 4 LVAD recipients at a tertiary academic center who underwent preimplant and postimplant cognitive testing. We also conducted a systematic review of studies with adult recipients of a continuous-flow LVAD whose cognition was measured before and after implantation. We searched Medline, EMBASE, SCOPUS, and the Cochrane library (start of database to July 16, 2021) for longitudinal, peer-reviewed studies written in English.
RESULTS
Cognitive improvement after LVAD implantation was observed in the case series, with improvement on phonemic fluency and digit symbol coding assessments. Two out of 4 cases in the case series improved on Clinical Dementia Rating: one from moderate dementia to mild cognitive impairment and another from mild cognitive impairment to unimpaired. Seven studies were included in the systematic review and were heterogeneous regarding cognitive tests employed, follow-up period, and measured outcomes. Montreal Cognitive Assessment and Trail-Making Test Part B were used most commonly. Cognitive improvement was reported in all 7 studies with at least 1 study reporting statistically significant improvements in each the following cognitive domains: delayed and immediate recall, executive function, visuospatial function, verbal function, attention, and processing speed. Most studies had small sample sizes and lacked a control group.
CONCLUSIONS
LVAD implantation appears to be associated with improved cognition. Adequately powered, prospective studies are needed to examine the effect of LVAD on cognitive function in patients with heart failure. Additionally, studies that directly examine cerebral blood flow in conjunction with cognitive assessment are needed to establish the relationship between the reversal of cerebral hypoperfusion and improved cognition.
Topics: Adult; Humans; Heart-Assist Devices; Quality of Life; Heart Failure; Treatment Outcome; Cognition
PubMed: 36116764
DOI: 10.1016/j.jaclp.2022.09.003