Myeloid-derived growth factor in diseases: structure, function and mechanisms.

Myeloid-derived growth factor (MYDGF) is a novel secreted protein with potent antiapoptotic and tissue-repairing properties that is present in nearly 140 human tissues and cell lines, with the highest abundance in the oral epithelium and skin. Initially, MYDGF was found in bone marrow-derived monocytes and macrophages for cardioprotection and repair after myocardial infarction. Subsequent studies have shown that MYDGF plays an important role in other cardiovascular diseases (e.g., atherosclerosis and heart failure), metabolic disorders, renal disease, autoimmune/inflammatory disorders, and cancers. Although the underlying mechanisms have not been fully explored, the role of MYDGF in health and disease may involve cell apoptosis and proliferation, tissue repair and regeneration, anti-inflammation, and glycolipid metabolism regulation. In this review, we summarize the current progress in understanding the role of MYDGF in health and disease, focusing on its structure, function and mechanisms. The graphical abstract shows the current role of MYDGF in different organs and diseases (Fig. 1).

Myocardial fibrosis and prognosis in heart failure with preserved ejection fraction: a pooled analysis of 12 cohort studies.

OBJECTIVES: Heart failure with preserved ejection fraction (HFpEF) is a syndrome with significant clinical heterogeneity. Myocardial fibrosis has been considered a common pathological process in the development and progress of HFpEF. This study aimed to consolidate data on the prognostic effect of myocardial fibrosis, evaluated by cardiovascular magnetic resonance (CMR) imaging in patients with HFpEF. METHODS: Three medical databases were searched for potentially related articles up to February 28, 2023. Cohort studies reporting associations between myocardial fibrosis and risk of all-cause mortality or composite major adverse cardiac outcomes (MACE) were included. Cardiac fibrosis was evaluated by CMR metrics, including late gadolinium enhancement (LGE) or myocardial extracellular volume (ECV). The hazard ratios (HRs) and 95% confidence intervals (CI) of the outcomes for higher myocardial fibrosis were calculated. RESULTS: Twelve studies with 2787 patients with HFpEF were included for analysis. After a median follow-up duration of 31.2 months, a higher level of cardiac fibrosis was associated with a significant increase in the risk of MACE (HR = 1.34, 95% CI = 1.14-1.57) and all-cause mortality (HR = 1.74, 95% CI = 1.27-2.39), respectively. Furthermore, the increased risk of outcomes was both observed when cardiac fibrosis was defined according to LGE or ECV, respectively. CONCLUSIONS: Higher burden of myocardial fibrosis evaluated by CMR can predict a poor prognosis in patients with HFpEF. Evaluation of LGE or ECV based on CMR could be recommended in these patients for risk stratification and guiding further treatment. CLINICAL RELEVANCE STATEMENT: Inclusion of cardiovascular magnetic resonance examination in the diagnostic and risk-evaluation algorithms in patients with heart failure with preserved ejection fraction should be considered in clinical practice and future studies. KEY POINTS: • Myocardial fibrosis is a common pathological process in heart failure with preserved ejection fraction. • A higher myocardial fibrosis burden on cardiac magnetic resonance predicts a poor prognosis in patients with heart failure with preserved ejection fraction. • Evaluation of myocardial fibrosis may be useful in patients with heart failure with preserved ejection fraction for risk stratification and treatment guidance.

Trends in cardiovascular health metrics and associations with long-term mortality among US adults with coronary heart disease.

BACKGROUND AND AIMS: Our study examined the trends of cardiovascular health metrics in individuals with coronary heart disease (CHD) and their associations with all-cause and cardiovascular disease mortality in the US. METHODS AND RESULTS: The cohort study was conducted based on the National Health and Nutrition Examination Survey 1999-2018 and their linked mortality files (through 2019). Baseline CHD was defined as a composite of self-reported doctor-diagnosed coronary heart disease, myocardial infarction, and angina pectoris. Cardiovascular health metrics were assessed according to the American Heart Association recommendations. Long-term all-cause and cardiovascular disease mortality were the primary outcomes. Survey-adjusted Cox regression models were used to estimate hazard ratios and corresponding 95% confidence intervals for the associations between cardiovascular health metrics and all-cause and cardiovascular disease mortality. The prevalence of one or fewer ideal cardiovascular health metrics increased from 14.15% to 22.79% (P < 0.001) in CHD, while the prevalence of more than four ideal cardiovascular health metrics decreased from 21.65% to 15.70 % (P < 0.001) from 1999 to 2018, respectively. Compared with CHD participants with one or fewer ideal cardiovascular health metrics, those with four or more ideal cardiovascular health metrics had a 35% lower risk (hazard ratio, 0.65; 95% confidence interval: 0.51, 0.82) and a 44% lower risk (0.56; 0.38, 0.84) in all-cause and cardiovascular disease mortality, respectively. CONCLUSION: Substantial declines were noted in ideal cardiovascular health metrics in US adults with CHD. A higher number of cardiovascular health metrics was associated with lower all-cause and cardiovascular disease mortality in them.

Joint trajectories of pain, depression and frailty and associations with adverse outcomes among community-dwelling older adults: A longitudinal study.

This study aimed to examine joint trajectories of pain, depression and frailty and their associations with adverse outcomes. Four waves of national data from the China Health and Retirement Longitudinal Study (CHARLS 2011-2018) were used, involving 4217 participants aged ≥60 years. Joint trajectories were fit using parallel-process latent class growth analysis, and their associations with adverse outcomes were evaluated using modified Poisson regression. Four joint trajectories were identified. Compared with most favorable group, other three joint trajectory groups had higher risk of functional disability and hospitalization. Slowly progressive pain, depression and frailty and persistent combination of pain, depression and frailty were also associated with cognitive decline, while slowly reduced pain and depression but persistent frailty was associated with all-cause mortality. The findings highlight unique characteristics and health impacts of concurrent changes in pain, depression and frailty over time, implicating the integrated physical and psychological care for older adults.

Joint trajectories of loneliness, social isolation and sarcopenia and associations with adverse outcomes: A prospective cohort study.

This study aimed to examine joint trajectories of loneliness, social isolation and sarcopenia and their associations with adverse outcomes. A total of 4701 participants aged ≥60 years who had a baseline and at least one follow-up assessment of loneliness, social isolation and sarcopenia across 2011, 2013 and 2015 waves in China Health and Retirement Longitudinal Study. Adverse outcomes were obtained in 2018 wave. Joint trajectories were fit using the parallel process latent class growth analysis, and their associations with adverse outcomes were evaluated using modified Poisson regression. Joint trajectory patterns for social relationship and sarcopenia did not vary by the assessment for sarcopenia, but did vary by the assessment for social relationship. Older adults exhibit distinct joint trajectories and those with persistent combination of loneliness or social isolation and sarcopenia experience greatest risk of adverse outcomes. These findings implicate integration of health care and social care for community-dwelling older adults.

Helicobacter pylori infection and risk of cardiovascular disease.

BACKGROUND: Whether Helicobacter pylori (H. pylori) infection is associated with an increased risk of cardiovascular disease (CVD) remains controversial. This study aimed to investigate the association between H. pylori infection and the risk of CVD. METHODS: Potentially related studies were searched in the electronic databases, including PubMed, EMBASE and Cochrane Library, from inception to 31 August 2022. Observational cohort studies that reported the multivariable-adjusted relative risks (RRs) for composite CVD, CHD, stroke, or all-cause mortality associated with H. pylori infection were included in the meta-analysis, using random-effects models. RESULTS: Forty-one cohort studies with 230,288 participants were included. After a median follow-up duration of 6.3 years, H. pylori infection was associated with a mildly increased risk of composite CVD (RR 1.10, 95% CI 1.03, 1.18) and coronary heart disease (RR 1.10, 95% CI 1.02, 1.18) compared with those without H. pylori infection. No significant association was observed between H. pylori infection and risk of stroke (RR 1.08, 95% CI 0.94, 1.23) or all-cause mortality (RR 1.02, 95% CI 0.90, 1.16). Compared with cytotoxin-associated gene-A (CagA) negative H. pylori infection, the risk of CVD was significantly increased in patients with CagA positive H. pylori infection (RR 1.58, 95% CI 1.03, 2.41). CONCLUSIONS: Helicobacter pylori infection is associated with a mildly increased risk of CVD. It may be of great public health and clinical significance to screen H. pylori infection in patients with a high risk of CVD.

Treatment of pacemaker-induced superior vena cava syndrome by direct oral anticoagulant.

BACKGROUND: The use of cardiac implantable electronic devices has grown substantially over the past two decades, lead-related vascular issues are commonly encountered in clinical practice. Superior vena cava (SVC) syndrome due to pacemaker leads is an uncommon complication. Anticoagulation remains the mainstay of therapy to restore some degree of patency and relieve swelling. However, there are limited clinical trials on direct oral anticoagulants (DOACs). CASE PRESENTATION: We report a case of an 80-year-old man who developed SVC syndrome after transvenous pacemaker implantation with symptoms of obstruction that were significantly relieved after four months of DOACs. His symptoms had completely resolved nine months later. CONCLUSIONS: DOACs are effective in the treatment of SVC syndrome after pacemaker implantation, representing an important new approach. It is a very good choice for patients who do not want to undergo interventional therapy.

Prediction of gestational diabetes mellitus at the first trimester: machine-learning algorithms.

PURPOSE: Short- and long-term complications of gestational diabetes mellitus (GDM) involving pregnancies and offspring warrant the development of an effective individualized risk prediction model to reduce and prevent GDM together with its associated co-morbidities. The aim is to use machine learning (ML) algorithms to study data gathered throughout the first trimester in order to predict GDM. METHODS: Two independent cohorts with forty-five features gathered through first trimester were included. We constructed prediction models based on three different algorithms and traditional logistic regression, and deployed additional two ensemble algorithms to identify the importance of individual features. RESULTS: 4799 and 2795 pregnancies were included in the Xinhua Hospital Chongming branch (XHCM) and the Shanghai Pudong New Area People's Hospital (SPNPH) cohorts, respectively. Extreme gradient boosting (XGBoost) predicted GDM with moderate performance (the area under the receiver operating curve (AUC) = 0.75) at pregnancy initiation and good-to-excellent performance (AUC = 0.99) at the end of the first trimester in the XHCM cohort. The trained XGBoost showed moderate performance in the SPNPH cohort (AUC = 0.83). The top predictive features for GDM diagnosis were pre-pregnancy BMI and maternal abdominal circumference at pregnancy initiation, and FPG and HbA1c at the end of the first trimester. CONCLUSION: Our work demonstrated that ML models based on the data gathered throughout the first trimester achieved moderate performance in the external validation cohort.

Convolutional Neural Networks for Classifying Cervical Cancer Types Using Histological Images.

Cervical cancer is the most common cancer among women worldwide. The diagnosis and classification of cancer are extremely important, as it influences the optimal treatment and length of survival. The objective was to develop and validate a diagnosis system based on convolutional neural networks (CNN) that identifies cervical malignancies and provides diagnostic interpretability. A total of 8496 labeled histology images were extracted from 229 cervical specimens (cervical squamous cell carcinoma, SCC, n = 37; cervical adenocarcinoma, AC, n = 8; nonmalignant cervical tissues, n = 184). AlexNet, VGG-19, Xception, and ResNet-50 with five-fold cross-validation were constructed to distinguish cervical cancer images from nonmalignant images. The performance of CNNs was quantified in terms of accuracy, precision, recall, and the area under the receiver operating curve (AUC). Six pathologists were recruited to make a comparison with the performance of CNNs. Guided Backpropagation and Gradient-weighted Class Activation Mapping (Grad-CAM) were deployed to highlight the area of high malignant probability. The Xception model had excellent performance in identifying cervical SCC and AC in test sets. For cervical SCC, AUC was 0.98 (internal validation) and 0.974 (external validation). For cervical AC, AUC was 0.966 (internal validation) and 0.958 (external validation). The performance of CNNs falls between experienced and inexperienced pathologists. Grad-CAM and Guided Gard-CAM ensured diagnoses interpretability by highlighting morphological features of malignant changes. CNN is efficient for histological image classification tasks of distinguishing cervical malignancies from benign tissues and could highlight the specific areas of concern. All these findings suggest that CNNs could serve as a diagnostic tool to aid pathologic diagnosis.

[mRNA Expression Profile Changes in Angiotensin-â ¡-Induced Atrial Myocardial Fibrosis in Rats].

Objective: To study the differences between the mRNA expression profile in angiotensin Ⅱ (Ang Ⅱ)-induced fibrotic cardiomyocytes and that of normal cardiomyocytes and the relevant signaling pathways. Methods: Six 8-week-old male Sprague-Dawley (SD) rats were randomly assigned to a control group and an Ang Ⅱ group, with 3 rats in each group. Rats in the control group were injected via caudal vein with 0.9% normal saline at 2 mg/kg per day, while rats in the Ang Ⅱ group were injected with Ang Ⅱ via caudal vein at 2 mg/kg per day. The medications were continuously administered in the two groups for 14 days. The degree of myocardial fibrosis was determined by Masson's Trichrome staining and the content of collagen Ⅰ was determined by immunohistochemistry. High throughput sequencing was performed to measure the mRNA expression of rat cardiomyocytes in the two groups and to screen for differentially-expressed mRNAs. The differentially-expressed mRNAs were analyzed by Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Results: Compared with those of the control group, the degree of myocardial fibrosis and the content of collagen Ⅰ in Ang Ⅱ group were significantly higher ( P<0.05). Through sequencing, 313 differentially-expressed mRNAs were identified, with 201 being up-regulated and 112 being down-regulated. Go and KEGG analyses showed that these differentially-expressed mRNA were involved in a variety of biological regulatory functions and pathways of myocardial fibrosis. Conclusion: Ang Ⅱ can cause myocardial fibrosis in rats. There are significant differences in mRNA expression between fibrotic cardiomyocytes and normal cardiomyocytes. The differentially expressed mRNAs may play an important role in biological processes, including immune response, cell remodeling, and extracellular matrix deposition.

Coordination of Intraoperative Neurophysiologic Monitoring Technologist and Surgery Schedules.

Resource coordination in surgical scheduling remains challenging in health care delivery systems. This is especially the case in highly-specialized settings such as coordinating Intraoperative Neurophysiologic Monitoring (IONM) resources. Inefficient coordination yields higher costs, limited access to care, and creates constraints to surgical quality and outcomes. To maximize utilization of IONM resources, optimization-based algorithms are proposed to effectively schedule IONM surgical cases and technologists and evaluate staffing needs. Data with 10 days of case volumes, their surgery durations, and technologist staffing was used to demonstrate method effectiveness. An iterative optimization-based model that determines both optimal surgery and technologist start time (operational scenario 4) was built in an Excel spreadsheet along with Excel's Solver settings. It was compared with current practice (operational scenario 1) and optimization solution on only surgery start time (operational scenario 2) or technologist start time (operational scenario 3). Comparisons are made with respect to technologist overtime and under-utilization time. The results conclude that scenario 4 significantly reduces overtime by 74% and under-utilization time by 86% as well as technologist needs by 10%. For practices that do not have flexibility to alter surgeon preference on surgery start time or IONM technologist staffing levels, both scenarios 2 and 3 also result in substantial reductions in technologist overtime and under-utilization. Moreover, IONM technologist staffing options are discussed to accommodate technologist preferences and set constraints for surgical case scheduling. All optimization-based approaches presented in this paper are able to improve utilization of IONM resources and ultimately improve the coordination and efficiency of highly-specialized resources.

Prediabetes and the risk of heart failure: A meta-analysis.

AIM: To determine the role of prediabetes in the incidence of heart failure (HF). MATERIALS AND METHODS: We searched electronic databases (PubMed, Embase, Google Scholar and OpenGrey) for studies up to 31 December 2020. Studies were included for meta-analysis if they reported adjusted relative risks (RRs) and 95% confidence intervals (CIs) for the risk of HF for prediabetes compared with normoglycaemia. Prediabetes was defined as impaired fasting glucose (IFG) according to the World Health Organization (WHO) criteria (IFG-WHO), or according to the American Diabetes Association (ADA) definition (IFG-ADA), impaired glucose tolerance (IGT), raised HbA1c according to the ADA criteria (HbA1c-ADA), or according to the International Expert Committee (IEC) recommendation (HbA1c-IEC). RESULTS: A total of 15 studies comprising 9,827,430 individuals provided data for this analysis. The median follow-up duration of the included studies was 8.0 years. Compared with normoglycaemia, prediabetes was associated with an increased risk for HF: IFG-ADA (RR: 1.09, 95% CI: 1.05-1.13), IFG-WHO (RR: 1.18, 95% CI: 1.07-1.30), IGT (RR 1.58, 95% CI 1.04-2.39), HbA1c-ADA (RR 1.28, 95% CI 1.16-1.41) or HbA1c-IEC (RR 1.40, 95% CI 1.09-1.79), respectively. CONCLUSIONS: Prediabetes is associated with an increased risk of HF. Future studies are needed to evaluate effective treatments for prediabetes to prevent the development and progression of HF.

Association between prediabetes and adverse outcomes in heart failure.

AIMS: Patients with heart failure (HF) and with diabetes experienced significantly worse outcomes than those without diabetes. However, data on the prognostic impact of prediabetes in HF are inconclusive. This meta-analysis aimed to explore the association between prediabetes and the risk of all-cause mortality and adverse cardiac outcomes in patients with HF. MATERIALS AND METHODS: We searched multiple electronic databases (PubMed, Embase and Google Scholar) for relevant studies up to 31 March 2021. Studies were included for analysis if multivariable adjusted relative risks of adverse outcomes were reported in patients with prediabetes and with HF compared with those with normoglycaemia. Random-effects models were used to calculate the pooled hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: Twelve studies comprising 28 643 patients with HF reported the risk of all-cause mortality and cardiac outcomes associated with prediabetes. The prevalence of prediabetes ranged from 9.6% to 37.2%. After a median follow-up duration of 2.3 years, patients with HF and with prediabetes were associated with an increased risk of all-cause mortality (HR 1.29, 95% CI 1.06-1.58), cardiovascular mortality (HR 1.59, 95% CI 1.09-2.32), HF hospitalization (HR 1.33, 95% CI 1.09-1.61), all-cause mortality and/or HF hospitalization (HR 1.22, 95% CI 1.01-1.47), as well as cardiovascular mortality and/or HF hospitalization (HR 1.21, 95% CI 1.07-1.37). CONCLUSIONS: Prediabetes is associated with a worse prognosis in patients with HF. Further risk stratification and effective treatment strategies are needed in patients with prediabetes and with HF to improve the prognosis.

Sodium-glucose co-transporter-2 inhibition and ocular outcomes in patients with type 2 diabetes: A systematic review and meta-analysis.

Sodium-glucose co-transporter-2 (SGLT2) inhibitors are effective for the treatment of macrovascular complications and nephropathy in type 2 diabetes, but effects on microvascular eye outcomes are unclear. We conducted a systematic review and meta-analysis of randomized placebo-controlled trials to evaluate the effect of SGLT2 inhibition on total ocular events and retinopathy in patients with type 2 diabetes. We searched MEDLINE and Embase for the period from database inception date to October 11, 2019. Two reviewers working independently extracted relevant data. Random-effects models with inverse variance weighting were selected to estimate summary risk ratios (RRs) and 95% confidence intervals (CIs). We included nine studies, involving 39 982 patients with a mean follow-up of 2.8 years. There were 1414 total ocular events, of which 624 were retinopathy events. SGLT2 inhibition was not associated with a change in the risk of total ocular events (RR 0.97, 95% CI 0.85, 1.11) or retinopathy (RR 0.98, 95% CI 0.84, 1.16), with consistent effects across studies (P for heterogeneity = 0.35 and 0.45, respectively). The effects of SGLT2 inhibition on eye disease in individuals with type 2 diabetes are probably null, although the available data cannot exclude small to moderate benefits or harms.

A case series of medically managed Candida parapsilosis complex prosthetic valve endocarditis.

BACKGROUND: In recent years, Candida parapsilosis is recognized as a species complex and is composed of Candida parapsilosis sensu stricto, Candida orthopsilosis and Candida metapsilosis. Candida parapsilosis complex prosthetic valve endocarditis (PVE) is rare and the survival rate is still low despite of optimal therapeutic strategies. In our report, it is novel to report cases as Candida parapsilosis complex PVE at species and identify Candida parapsilosis using MALDI-TOF MS. Case presentation A series of 4 cases of Candida parapsilosis complex PVE from our institution was reported. Three were infected by Candida parapsilosis sensu stricto and one was infected by Candida metapsilosis. The condition of two cases got better and the other died. CONCLUSIONS: More attention should be paid to Candida parapsilosis complex PVE and early diagnosis and prompt antibiotic therapy may play a role in the treatment for Candida parapsilosis complex PVE. It is recommended to identify Candida parapsilosis complex at species level and MALDI-TOF MS as an easy, fast and efficient identification method is worth promoting in clinical microbiology.

Evaluation of Lipoprotein-Associated Phospholipase A2 as a Prognostic Biomarker in Chronic Kidney Disease.

BACKGROUND: The leading cause of death in patients with chronic kidney disease (CKD) is atherosclerosis (AS). Lipoprotein-associated phospholipase A2 (Lp-PLA2) is a biomarker of atherosclerotic plaque stability. The aim of our study was to analyze the association of Lp-PLA2 with CKD complicated with carotid atherosclerotic stenosis (CAS). METHODS: Serum specimens were collected from 77 CKD patients and 39 healthy controls. Laboratory examination results including glucose, total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) and Lp-PLA2 were measured. Receiver operating characteristic (ROC) was drawn and the area under the curve (AUC) was calculated. RESULTS: Multivariate logistic regression analysis showed that age, gender, glucose, and Lp-PLA2 were considered as risks for CKD-CAS with odds ratios (OR) of 1.111 (95% CI: 1.055, 1.170), 5.123 (95% CI: 1.482, 17.714), 1.679 (95% CI: 1.123, 2.512), and 1.023 (95% CI: 1.008, 1.037), respectively. The AUC for Lp-PLA2 and glucose was 0.618 (p = 0.014) and 0.592 (p = 0.057), respectively. The best diagnostic value was archived by Lp-PLA2 with the cutoff value of 201.06 ng/mL. CONCLUSIONS: Lp-PLA2 is a potential prognostic and diagnostic biomarker for CKD-CAS.

Reduce Patient Treatment wait time in a Proton Beam Facility - A Gatekeeper Approach.

Patient wait time can negatively impact treatment quality in a proton therapy center, where multiple treatment rooms share one proton beam. Wait time increases patient discomfort that can lead to patient motion, dissatisfaction, and longer treatment delay. This study was to develop a patient call-back model that reduced patient wait while efficiently utilizing the proton beam. A "Gatekeeper" logic allowing therapists to adjust the time of a patient's call-back to the treatment room was developed. It uses a two-pronged approach to minimize overlap of long treatment and the possibility of excessive wait in the queue to receive the proton beam. The goal was to reduce the maximum wait time to less than eight minutes per field for a four-room facility. The effectiveness of this logic was evaluated through simulation, and five scenarios were compared. Four scenarios implementing various levels of gatekeeper logic were compared with the original scenario without the logic. The best performing model provided a reduction of the maximum field wait by 26% and met the predefined goal. Adjusting call-back extended the treatment day length by an average of 6 min and a maximum of 12 min in total. The use of this gatekeeper logic significantly reduces patient field wait with minimal impact on treatment day length for a four-room proton facility. A sample interface that adopts this logic for therapists to make informed decision on patient call-back time is demonstrated.

An Algorithm for Pairing Interventionalists and Surgeons for the TAVR Procedure.

The Transcatheter Aortic Valve Replacement (TAVR) procedure requires an initial consultation and a subsequent procedure by an interventionalist (IC) and surgeon. The IC-surgeon pair coordination is extremely challenging, especially at Mayo Clinic due to provider time commitments distributed across practice, research, and education activities. Current practice aims to establish the coordination manually, resulting in a scheduling process that is cumbersome and time consuming for the schedulers. We develop an algorithm for pairing ICs and surgeons that minimizes the lead time (days elapsed between the clinic consult and procedure). As compared to current practice, this algorithm is able to reduce average lead time by 59% and increase possible IC-surgeon pairs by 7%. The proposed algorithm is shown to be flexible enough to incorporate practice variations such as lead time upper bound and two procedure days for a single consult day. Algorithm alternatives are also presented for practices who may find the proposed algorithm infeasible for their practice.

Nonalcoholic fatty liver disease is associated with increased risk of atrial fibrillation.

BACKGROUND & AIMS: Whether nonalcoholic fatty liver disease (NAFLD) is associated with risk of incident atrial fibrillation (AF) independent of established cardiovascular risk factors remains controversial. We aimed to provide a quantitative estimate of the association between NAFLD and risk of AF after adjustment for cardiometabolic risk factors. METHODS: In this study, we searched PubMed and Embase for studies published from database inception until January 31, 2020. Cohort studies reported adjusted relative risks (RRs) and 95% confidence intervals (CIs) for AF of NAFLD compared with non-NAFLD were included for analysis. RESULTS: A total of 6 cohort studies were included, comprising 614 673 individuals for analysis. The median follow-up duration was 10.0 years with 7271 cases of incident AF. Compared with non-NAFLD, minimally adjusted models without adjustment for cardiometabolic risk factors showed that NAFLD was associated with increased risk of AF (RR 1.65, 95% CI 1.23-2.20, I2  = 63.0%). After adjustment for multiple cardiometabolic risk factors, the association between NAFLD and risk of AF was still higher than that in non-NAFLD (RR 1.19, 95% CI 1.04-1.31, I2  = 54.0%). There was significant heterogeneity for the risk of AF between minimally and maximally adjusted models (I2  = 77.1%, P for heterogeneity = 0.04). Compared with non-NAFLD, the absolute risk increase in NAFLD for AF was 1.3 (95% CI 0.5-2.1) per 1000 person-years. CONCLUSIONS: NAFLD is associated with increased risk of incident AF. The strength of the association between NAFLD and AF is partially attributed to the co-existing cardiometabolic risk factors.

The effect of canagliflozin on amputation risk in the CANVAS program and the CREDENCE trial.

AIM: To determine whether there was an explanation as to why the effects of the sodium-glucose co-transporter-2 (SGLT2) inhibitor canagliflozin on amputation risk vary between the CANVAS program and the CREDENCE trial. METHODS: We performed a pooled analysis of patient-level data from the CANVAS program and the CREDENCE trial. Patient characteristics associated with amputation risk were assessed in univariable and multivariable regression models and compared between studies. Effects of canagliflozin on amputation risk were determined from Cox proportional hazards models and compared between studies, subgroups and for a range of amputation outcomes. Effects over time were explored by cumulative event curves. RESULTS: In the CANVAS program (n = 10 142; median follow-up 2.4 years) and CREDENCE trial (n = 4401; median follow-up 2.5 years), 2.3% and 5.3% of participants, respectively, reported baseline amputation history. Key differences at baseline were the proportions with nephropathy (CREDENCE higher, 100% vs. 17.5%) and cardiovascular disease (CANVAS higher, 66% vs. 50%). There were 133 amputations in CREDENCE (3.0% annual event rate) and 187 amputations in CANVAS (1.8% annual event rate), with prior amputation being the strongest predictor of future amputation in both groups. Effects of canagliflozin on amputation risk were significantly different between trials (Pheterogeneity .02, I2 = 82%), but this was not explained by participant or trial differences. There was no evidence that foot disease management protocols instituted during CREDENCE ameliorated amputation risk. CONCLUSIONS: We identified no explanation for the difference in amputation risk between the CREDENCE trial and the CANVAS program. In the context of null effects of SGLT2 inhibition on amputation in CREDENCE and all other large trials, there is a possibility that the finding in CANVAS was the result of chance.