ABSTRACT
Unplanned reinterventions following pulmonary artery banding (PAB) in single ventricle patients are common before stage 2 palliation (S2P) but associated risk factors are unknown. We hypothesized that reintervention is more common when PAB is placed at younger age and with a looser band, reflected by lower PAB pressure gradient. Retrospective single center study of single ventricle patients undergoing PAB between Jan 2000 and Dec 2020. The association with reintervention and successful S2P was modeled using exploratory cause-specific hazard regression. A multivariable model was developed adjusting for clinical and statistically relevant predictors. The cumulative proportion of patients undergoing reintervention were summarized using a competing risk model. 77 patients underwent PAB at median (IQR) 47 (24-66) days and 3.73 (3.2-4.5) kg. Within18 months of PAB, 60 (78%) reached S2P, 9 (12%) died, 1 (1%) transplanted and 7 (9%) were alive without S2P. Within 18 months of PAB 10 (13%) patients underwent reintervention related to pulmonary blood flow modification: PAB adjustment (n = 6) and conversion to Damus-Kaye-Stansel/Blalock-Taussig-Thomas shunt (n = 4). 6/10 (60%) reached S2P following reintervention. A trend toward higher intervention in patients with a genetic syndrome (p-0.06) and weight < 3 kg (p-0.057) at time of PAB was noted. Only genetic syndrome was a risk factor associated with poor outcome (p-0.025). PAB has a reasonable outcome in SV patients with unobstructed systemic and pulmonary blood flow, but with a high reintervention rate. Only a quarter of patients with genetic syndromes reach S2P and further study is required to explore the benefits from an alternative palliative strategy.
Subject(s)
Fontan Procedure , Heart Defects, Congenital , Univentricular Heart , Humans , Child , Infant , Pulmonary Artery/surgery , Heart Defects, Congenital/complications , Retrospective Studies , Treatment Outcome , Heart Ventricles/surgery , Palliative CareABSTRACT
BACKGROUND: Del Nido cardioplegia (DNc) was designed for superior myocardial protection during cardiopulmonary bypass (CPB). We conducted a retrospective review to explore if DNc was associated with increase in systemic ventricle dysfunction (sVD) following pediatric CPB. METHODS AND RESULTS: This single-center, retrospective study included 1534 patients undergoing CPB between 2013 and 2016, 997 prior to center-wide conversion to DNc and 537 following. The primary outcome was new postoperative ≥moderate sVD by echocardiogram. Secondary outcomes included sVD of any severity and right ventricular dysfunction. Data was evaluated by interrupted time-series analysis. Groups had similar cardiac diagnoses and surgical complexity. Del Nido cardioplegia was associated with longer median (IQR) CPB [117 (84-158) vs 108 (81-154), p = 0.04], and aortic cross-clamp [83 (55-119) vs 76 (53-106), p = 0.03], and fewer cardioplegia doses [2 (1-2) vs 3 (2-4), p < 0.0001]. Mortality was similar in both groups. Frequency of sVD was unchanged following DNc, including predetermine subgroups (neonates, infants, and prolonged cross-clamp). Logistic regression showed a significant rise in right ventricular dysfunction (OR 5.886 [95% CI: 0.588, 11.185], p = 0.03) but similar slope. CONCLUSIONS: Use of DNc was not associated with increased in reported sVD, and provided similar myocardical protection to the systemic ventricle compared to conventional cardioplegia but may possibly impact right ventricular function. Studies evaluating quantitative systolic and diastolic function are needed.
Subject(s)
Cardiac Surgical Procedures , Ventricular Dysfunction, Right , Infant , Infant, Newborn , Humans , Child , Retrospective Studies , Cardioplegic Solutions , Heart Arrest, Induced/adverse effects , Heart Arrest, Induced/methods , Cardiac Surgical Procedures/adverse effectsABSTRACT
INTRODUCTION: Predicted heart mass (PHM) was neither derived nor evaluated in an obese population. Our objective was to evaluate size mismatch using actual body weight or ideal body weight (IBW)-adjusted PHM on mortality and risk assessment. METHODS: We conducted a retrospective cohort study of adult recipients with BMI ≥30 kg/m2 or recipients of donors with BMI≥30 kg/m2 from the ISHLT registry. We used multivariable Cox proportional hazard models to evaluate 30-day and 1-year mortality. The two models were compared using net reclassification index. RESULTS: 10,817 HT recipients, age 55 (IQR 46-62) years, 23% female, BMI 31 kg/m2 (IQR 28-33) were included. Donors were age 34 (IQR 24-44) years, 31% female, and BMI 31 kg/m2 (IQR 26-34). There was a significant nonlinear association between mortality and actual PHM but not IBW-adjusted PHM. Undersizing using actual PHM was associated with higher 30-day and 1-year mortality (p < .01), not seen with IBW-adjusted PHM. Actual PHM better risk classified .6% (95% CI .3-.8) patients compared to IBW-adjusted PHM. CONCLUSION: Actual PHM can be used for size matching when assessing mortality risk in obese recipients or recipients of obese donors. There is no advantage to re-calculating PHM using IBW to define candidate risk at the time of organ allocation.
Subject(s)
Heart Transplantation , Adult , Body Mass Index , Female , Humans , Male , Middle Aged , Obesity/complications , Retrospective Studies , Tissue Donors , Transplant RecipientsABSTRACT
BACKGROUND: Cardiac allograft vasculopathy (CAV) is the leading cause of late graft loss. While there are numerous post-transplant factors which may increase the risk of the development of CAV, there is a paucity of data on the impact of donor-derived atherosclerosis (DA), early discontinuation of prednisone, and early initiation of proliferation signal inhibitors (PSI) as assessed by intravascular ultrasound (IVUS). METHODS: Retrospective single-center study of all adult transplant patients (2008-2017) with serial IVUS at baseline and annually for 5 years. DA was defined as a baseline maximal intimal thickness (MIT) ≥0.5 mm, and CAV development was defined as MIT ≥1 mm or an increase in MIT ≥0.5 mm at year 1 compared with baseline or an increase in 0.3 mm annually thereafter. Clinical risk factors for CAV were identified using multivariable hazard regression. Separate multistate models were applied to assess the association of prednisone discontinuation and PSI initiation and CAV. RESULTS: Of 282 patients screened, 186 patients had a 1-year angiogram. The mean age of those included in the cohort was 51 ± 11 years, 70% were male, 58% were Caucasian, and 27% were supported by a left ventricular assist device. Donor atherosclerosis was present in 40%. The cumulative incidence of CAV at 5 years is 41% in DA- vs. 59% in DA + (p = .012). Donor age was a strong predictor of DA (p = .016). Significant risk factors for CAV included male sex (HR = 4.141, p = .001), non-Caucasian race (HR = 1.98, p = .011), BMI < 18 kg/m2 (HR = 4.596, p = .042), longer ischemic time (HR = 1.374, p = .028), older donor age (HR = 1.158, p = .009), and rejection with hemodynamic compromise within the first year (HR = 2.858, p = .043). Prednisone discontinuation within 1 year was associated with a lower risk of CAV (HR 0.58 p = .047). Initiation of proliferation signal inhibitors (PSI) within 2 years resulted in fewer cases of CAV (HR 0.397 p < .001). CONCLUSION: In patients with an angiogram at 1 year, those with DA were significantly more likely to develop CAV. Lower incidence of CAV by IVUS was seen in patients who discontinued prednisone in the first year or had initiation of a PSI within two years of transplantation. Knowledge of early IVUS may allow a more tailored approach to patient management.
Subject(s)
Coronary Artery Disease , Heart Transplantation , Adult , Allografts , Coronary Angiography , Coronary Artery Disease/diagnostic imaging , Coronary Artery Disease/etiology , Female , Heart Transplantation/adverse effects , Humans , Male , Middle Aged , Retrospective Studies , Risk Factors , Ultrasonography, InterventionalABSTRACT
OBJECTIVES: To determine impact of enteral nutrition delivery on the relationship among inflammation, insulin resistance, and outcomes following pediatric cardiopulmonary bypass surgery. DESIGN: Pilot, randomized study analyzed according to intention-to-treat analysis. SETTING: Pediatric cardiac ICU. PATIENTS: Infants (≤ 6 mo) undergoing cardiopulmonary bypass. INTERVENTIONS: Patients randomly assigned to receive rapid escalation to enteral nutrition reaching goal feeds by 27 hours or standard feeding practice reaching goal feeds by 63 hours. Feeds were initiated on the first postoperative day. MEASUREMENTS AND MAIN RESULTS: Fifty patients were randomized equally to study arms. Patients were a median (interquartile range) of 16 days old (7-110 d old), undergoing biventricular surgery (88%) with a median cardiopulmonary bypass time of 125 minutes (105-159 min). Serial blood samples were drawn before and after cardiopulmonary bypass, cardiac ICU admission, and every 12 hours (up to 96 hr) for glucose, insulin, and cytokines (interleukin-1α, interleukin-6, interleukin-8, interleukin-10, and tumor necrosis factor-α) levels. Glucose-insulin ratio was calculated to quantify insulin resistance. Patient characteristics, time to enteral nutrition initiation, enteral nutrition interruptions, and insulin administration were similar across intervention arms. FF reached goal feeds at similar intervals as standard feeding (39 hr [30-60 hr] vs 60 hr [21-78 hr]; p = 0.75). No difference in cytokine, insulin, or glucose-insulin ratio was noted between groups. Higher inflammation was associated with increased glucose-insulin ratio and higher risk of adverse events. In multivariable models of interleukin-8, FF was associated with increased glucose-insulin ratio (estimate of effect [95% CI], 0.152 [0.033-0.272]; p = 0.013). Although higher interleukin-8 was associated with an elevated risk of adverse event, this relationship was possibly mitigated by FF (odds ratio [95% CI], 0.086 [0.002-1.638]; p = 0.13). CONCLUSIONS: A FF strategy was not associated with changes to early enteral nutrition delivery. Inflammation, insulin resistance, and morbidity were similar, but FF may modify the relationship between inflammation and adverse event. Multicenter nutrition studies are possible and necessary in this vulnerable population.
Subject(s)
Cardiopulmonary Bypass , Enteral Nutrition , Inflammation/prevention & control , Child , Enteral Nutrition/methods , Homeostasis , Humans , Infant , InsulinABSTRACT
Sudden cardiac death (SCD) is responsible for ~10% of post-heart transplant deaths. We conducted a retrospective analysis of the ISHLT registry evaluating the risk of post-transplant SCD. Adult heart transplant recipients (2004-2014) surviving the first year were included. We used multivariable multistate competing risk survival analysis to evaluate the impact of history of treated rejection and cardiac allograft vasculopathy (CAV) on SCD risk. We used a probabilistic analytical model and Monte Carlo simulation to estimate the impact of CAV severity and graft dysfunction on SCD. We included 25 242 recipients. During a median follow-up of 4.7 (2.3-7.0) years, 582 patients died suddenly. Treated rejection (HR 1.76, 95% CI 1.36-2.31) and CAV (HR 3.32, 95% CI 2.73-4.03) were important risk factors for SCD. The estimated SCD risk in patients with severe CAV without and with graft dysfunction was 3.2% (95% CI 2.0-4.6) and 5.4% (95% CI 3.8-7.0), respectively, at 2 years from the CAV diagnosis, and 4.9% (95% CI 3.4-6.5) and 8.0% (95% CI 6.1-10.0), respectively, in those who also had treated rejection. These results provide evidence that recipients with severe CAV and graft dysfunction or treated rejection are at clinically significant increased SCD risk. The benefit of ICD post-transplant remains uncertain.
Subject(s)
Death, Sudden, Cardiac/etiology , Graft Rejection/etiology , Heart Transplantation/adverse effects , Postoperative Complications , Registries/statistics & numerical data , Adult , Female , Follow-Up Studies , Graft Survival , Humans , Male , Middle Aged , Prognosis , Retrospective Studies , Risk Factors , Survival RateABSTRACT
We evaluated the effect of pre-heart transplant body mass index (BMI) on posttransplant outcomes using the International Society for Heart and Lung Transplantation Registry. Kaplan-Meier analysis and a multivariable Cox proportional hazard regression model were used for all-cause mortality, and cause-specific hazard regression for cause-specific mortality and morbidity. We assessed 38 498 recipients from 2000 to 2014 stratified by pretransplant BMI. Ten-year survival was 56% in underweight, 59% in normal weight, 57% in overweight, 52% in obese class I, 54% in class II, and 47% in class III patients (P < 0.001). Mortality was increased in underweight (HR 1.29, 95% CI 1.24-1.35), obese class I (HR 1.19, 95% CI 1.13-1.26), class II (HR 1.20, 95% CI 1.08-1.32), and class III patients (HR 1.45, 95% CI 1.15-1.83). Obesity was independently associated with increased death from myocardial infarction, chronic rejection, infection, and renal dysfunction. An underweight BMI lead to increased death from infection, acute and chronic rejection, malignancy, and bleeding. Obese patients had a higher incidence of renal dysfunction, diabetes, stroke, acute rejection, cardiac allograft vasculopathy, and malignancy, and underweight recipients had increased acute rejection. We have shown that pretransplant obese and underweight patients have increased post-heart transplant mortality and morbidity. This has implications for candidate selection and posttransplant management.
Subject(s)
Body Mass Index , Graft Rejection/mortality , Heart Transplantation/mortality , Obesity/physiopathology , Postoperative Complications/mortality , Registries/statistics & numerical data , Thinness/physiopathology , Adolescent , Adult , Female , Follow-Up Studies , Graft Rejection/etiology , Graft Rejection/pathology , Graft Survival , Heart Transplantation/adverse effects , Humans , Male , Middle Aged , Postoperative Complications/etiology , Postoperative Complications/pathology , Prognosis , Retrospective Studies , Risk Factors , Young AdultABSTRACT
BACKGROUND: It is estimated that 25%-35% of heart transplant recipients develop de novo donor-specific antibodies (dnDSA). One factor that appears to play a role in clinical outcomes is DSA persistence. The objective of this study was to determine the incidence of transient and persistent dnDSA in a Canadian heart transplant population and to evaluate their impact on coronary allograft vasculopathy (CAV), graft function, and mortality. METHODS: A retrospective study of consecutive adult and transitioned pediatric heart transplant recipients (2008-2015) in Toronto was performed. Clinical demographics were collected prospectively. HLA antibody testing was performed using Luminex single antigen assays. In statistical analysis, dnDSA was modeled as a time dependent covariate. RESULTS: During a median follow-up of 4.1 years, dnDSA were detected in 42 (23%) with a median time to detection of 329 days (156-740); 27 (64%) developed persistent dnDSA. Persistent dnDSA conferred an increased risk of death with a HR 4.0 (95%CI 1.4-12.1) when adjusted recipient age, CAV, and cytomegalovirus status. CONCLUSIONS: Transient dnDSA were not associated with adverse outcomes after heart transplantation. This suggests that transient dnDSA may not require enhanced immunosuppression, increased HLA antibody monitoring, or additional physiological assessment. By knowing the transient dnDSA status, clinicians may minimize both recipient morbidity and cost without increasing harm.
Subject(s)
Graft Rejection/mortality , Heart Failure/mortality , Heart Transplantation/mortality , Isoantibodies/adverse effects , Tissue Donors/supply & distribution , Adult , Female , Follow-Up Studies , Graft Rejection/etiology , Graft Rejection/pathology , Graft Survival , Heart Failure/surgery , Heart Transplantation/adverse effects , Humans , Isoantibodies/blood , Male , Middle Aged , Prognosis , Retrospective Studies , Risk Factors , Survival RateABSTRACT
PURPOSE: Sudden cardiac death (SCD) is an important post-transplant problem being responsible for ~10% of deaths. We conducted a systematic review and meta-analysis to evaluate incidence and predictors of post-heart transplant SCD and the use of implantable cardiac defibrillator (ICD). METHODS: Citations were identified in electronic databases and references of included studies. Observational studies on adults reporting on incidence and predictors of post-transplant SCD and ICD use were selected. We meta-analyzed SCD in person-years using random effects models. We qualitatively summarized predictors. RESULTS: This study includes 55 studies encompassing 47 901 recipients. The pooled incidence rate of SCD was 1.30 per 100 person-years (95% CI: 1.08-1.52). Cardiac allograft vasculopathy (CAV) was associated with higher SCD risk (2.40 per 100 patient-years, 95% CI: 1.46-3.34). Independent predictors of SCD identified by two moderate-quality studies were older donor age, younger recipient age, non-Caucasian race, reduced left ventricular ejection fraction, rejection, infection, and cancer. Authors rarely reported on ICD use. CONCLUSION: This meta-analysis found that post-transplant SCD risk in heart transplant recipients is higher than that in the general population. CAV was associated with increased SCD risk. Observational studies reporting on absolute risk of SCD are needed to better identify populations at a clinically significant increased risk.
Subject(s)
Death, Sudden, Cardiac/epidemiology , Death, Sudden, Cardiac/etiology , Heart Failure/surgery , Heart Transplantation/adverse effects , Canada/epidemiology , Death, Sudden, Cardiac/pathology , Humans , Incidence , Prognosis , Risk FactorsABSTRACT
BACKGROUND: Cardiac allograft vasculopathy (CAV) is the leading cause of late graft dysfunction in heart transplantation. Building on previous unsupervised learning models, we sought to identify CAV clusters using serial maximal intimal thickness and baseline clinical risk factors to predict the development of early CAV. METHODS: This is a single-center retrospective study including adult heart transplantation recipients. A latent class mixed-effects model was used to identify patient clusters with similar trajectories of maximal intimal thickness posttransplant and pretransplant covariates associated with each cluster. RESULTS: Among 186 heart transplantation recipients, we identified 4 patient phenotypes: very low, low, moderate, and high risk. The 5-year risk (95% CI) of the International Society for Heart and Lung Transplantation-defined CAV in the high, moderate, low, and very low risk groups was 49.1% (35.2%-68.5%), 23.4% (13.3%-41.2%), 5.0% (1.3%-19.6%), and 0%, respectively. Only patients in the moderate to high risk cluster developed the International Society for Heart and Lung Transplantation CAV 2-3 at 5 years (P=0.02). Of the 4 groups, the low risk group had significantly younger female recipients, shorter ischemic time, and younger female donors compared with the high risk group. CONCLUSIONS: We identified 4 clusters characterized by distinct maximal intimal thickness trajectories. These clusters were shown to discriminate against the development of angiographic CAV. This approach allows for the personalization of surveillance and CAV-directed treatment before the development of angiographically apparent disease.
Subject(s)
Coronary Artery Disease , Heart Failure , Heart Transplantation , Adult , Humans , Female , Coronary Artery Disease/diagnostic imaging , Coronary Artery Disease/etiology , Coronary Angiography , Retrospective Studies , Heart Failure/etiology , Heart Transplantation/adverse effects , Ultrasonography, Interventional , Allografts , Machine LearningABSTRACT
Aims: Mathematical models previously developed to predict outcomes in patients with heart failure (HF) generally have limited performance and have yet to integrate complex data derived from cardiopulmonary exercise testing (CPET), including breath-by-breath data. We aimed to develop and validate a time-to-event prediction model using a deep learning framework using the DeepSurv algorithm to predict outcomes of HF. Methods and results: Inception cohort of 2490 adult patients with high-risk cardiac conditions or HF underwent CPET with breath-by-breath measurements. Potential predictive features included known clinical indicators, standard summary statistics from CPETs, and mathematical features extracted from the breath-by-breath time series of 13 measurements. The primary outcome was a composite of death, heart transplant, or mechanical circulatory support treated as a time-to-event outcomes. Predictive features ranked as most important included many of the features engineered from the breath-by-breath data in addition to traditional clinical risk factors. The prediction model showed excellent performance in predicting the composite outcome with an area under the curve of 0.93 in the training and 0.87 in the validation data sets. Both the predicted vs. actual freedom from the composite outcome and the calibration of the prediction model were excellent. Model performance remained stable in multiple subgroups of patients. Conclusion: Using a combined deep learning and survival algorithm, integrating breath-by-breath data from CPETs resulted in improved predictive accuracy for long-term (up to 10 years) outcomes in HF. DeepSurv opens the door for future prediction models that are both highly performing and can more fully use the large and complex quantity of data generated during the care of patients with HF.
ABSTRACT
BACKGROUND: The Melody valve (Medtronic, Minneapolis, MN) for mitral valve replacement (MVR) (MelodyMVR) has been an effective strategy to treat unrepairable mitral valve disease in small children. This study analyzed survival, durability, and complications of the MelodyMVR strategy. METHODS: Patients who underwent MelodyMVR between 2014 and 2023 were included. Transplant-free survival was analyzed with Kaplan-Meier analysis. The Fine and Gray subdistribution method was applied to quantify the cumulative incidence. RESULTS: Twenty-five patients underwent MelodyMVR. Median age and weight were 6.3 months (interquartile range, 4.4-15.2 months) and 6.36 kg (interquartile range, 4.41-7.57 kg). Fifteen patients (60%) had congenital mitral valve disease and 13 (52%) had dominant mitral regurgitation. The median diameter of the implanted Melody was 16 mm (interquartile range, 14-18 mm). Mortality at 6 months, 1 year, and 5 years was 8.3% (95% CI, 2.2%-29.4%), 12.5% (95% CI, 4.2%-33.9%), and 17.6% (95% CI, 7.0%-40.7%), respectively. Two hospital survivors (8%) required early Melody replacement. Competing risk analysis showed that â¼50% of patients underwent mechanical MVR by 3.5 years after MelodyMVR. Freedom from bleeding and thrombosis at 4 years was 87.5% (95% CI, 74.2%-100%). Eleven patients underwent subsequent mechanical MVR with no deaths. One (9%) required pacemaker implantation after mechanical MVR. CONCLUSIONS: MelodyMVR provides reasonable early and medium-term survival in small children and a high rate of successful bridge to mechanical MVR. MelodyMVR is associated with minimal pacemaker requirement, bleeding, and thrombosis. Early Melody functional deterioration necessitates early repeat MVR, which can be achieved with minimal morbidity and mortality.
Subject(s)
Heart Valve Prosthesis Implantation , Heart Valve Prosthesis , Mitral Valve , Humans , Male , Female , Infant , Mitral Valve/surgery , Retrospective Studies , Heart Valve Prosthesis Implantation/methods , Prosthesis Design , Mitral Valve Insufficiency/surgery , Treatment Outcome , Postoperative Complications/epidemiology , Heart Valve Diseases/surgery , Survival Rate/trends , Follow-Up StudiesABSTRACT
PURPOSE: The purpose of this study was to compare outcomes of Melody mitral valve to mechanical mitral valve replacement (MVR) for young children. DESCRIPTION: Children who underwent Melody MVR from 2014 to 2020 were case-matched to mechanical MVR patients. Transplant-free survival and cumulative incidence of reintervention were compared. A subanalysis was performed for infants aged < 1 year (9 Melody MVRs and their matches). EVALUATION: Twelve children underwent Melody MVR. Two children (17%) salvaged from mechanical support died. Five of 10 survivors (50%) had subsequent MVR. At 1 and 3 years, transplant-free survival (Melody: 83%, 83%; mechanical: 83%, 67%; P = .180) and reintervention (Melody: 9%, 39%; mechanical: 0%, 18%; P = .18) were equivalent between groups. For children < 1 year of age, Melody MVR had a modest survival benefit (Melody: 89%, 89%; mechanical: 80%, 60%; P = .046), while rate of reintervention remained equivalent (Melody: 13%, 32%; mechanical: 0%, 22%; P = .32). CONCLUSIONS: For patients < 1 year old, Melody MVR offers a promising alternative and is a reasonable bridge to mechanical MVR, which can be performed safely at an older age. Further studies are necessary to corroborate these findings.
Subject(s)
Heart Valve Prosthesis Implantation , Heart Valve Prosthesis , Mitral Valve Insufficiency , Mitral Valve Stenosis , Infant , Humans , Child , Child, Preschool , Mitral Valve/surgery , Treatment Outcome , Mitral Valve Insufficiency/surgery , Mitral Valve Stenosis/surgery , Retrospective StudiesABSTRACT
BACKGROUND: In Europe, there is greater acceptance of hearts from higher-risk donors for transplantation, whereas in North America, the donor heart discard rate is significantly higher. A Donor Utilization Score (DUS) was used to compare European and North American donor characteristics for recipients included in the International Society for Heart and Lung Transplantation registry from 2000 to 2018. DUS was further evaluated as an independent predictor for 1-year freedom from graft failure, after adjusting for recipient risk. Lastly, we assessed donor-recipient risk matching with the outcome of 1-year graft failure. METHODS: DUS was applied to the International Society for Heart and Lung Transplantation cohort using meta-modeling. Posttransplant freedom from graft failure was summarized by Kaplan-Meier survival. Multivariable Cox proportional hazard regression was applied to quantify the effects of DUS and Index for Mortality Prediction After Cardiac Transplantation score on the 1-year risk of graft failure. We present 4 donor/recipient risk groups using the Kaplan-Meier method. RESULTS: European centers accept significantly higher-risk donor hearts compared to North America. DUS 0.45 versus 0.54, P<0.005). DUS was an independent predictor for graft failure with an inverse linear relationship when adjusted for covariates (P<0.001). The Index for Mortality Prediction After Cardiac Transplantation score, a validated tool to assess recipient risk, was also independently associated with 1-year graft failure (P<0.001). In North America, 1-year graft failure was significantly associated with donor-recipient risk matching (log-rank P<0.001). One-year graft failure was highest with pairing of high-risk recipients and donors (13.1% [95% CI, 10.7%-13.9%]) and lowest among low-risk recipients and donors (7.4% [95% CI, 6.8%-8.0%]). Matching of low-risk recipients with high-risk donors was associated with significantly less graft failure (9.0% [95% CI, 8.3%-9.7%]) than high-risk recipients with low-risk donors (11.4% [95% CI, 10.7%-12.2%]) Conclusions: European heart transplantation centers are more likely to accept higher-risk donor hearts than North American centers. Acceptance of borderline-quality donor hearts for lower-risk recipients could improve donor heart utilization without compromising recipient survival.
Subject(s)
Heart Failure , Heart Transplantation , Humans , Tissue Donors , Heart Transplantation/adverse effects , Heart Failure/surgery , North America , Europe , Graft Survival , Retrospective StudiesABSTRACT
BACKGROUND: Diagnosing left ventricular diastolic dysfunction (DD) noninvasively in children is difficult as no validated pediatric diagnostic algorithm is available. The aim of this study is to explore the use of machine learning to develop a model that uses echocardiographic measurements to explain patterns in invasively measured markers of DD in children. METHODS: Children at risk for developing DD were enrolled, including patients with Kawasaki disease, heart transplantation, aortic stenosis, and coarctation of the aorta when undergoing clinical left heart catheterization. Simultaneous invasive pressure measurements were made using a high-fidelity catheter (time constant of isovolumic relaxation [Tau, τ], left ventricular end-diastolic pressure, and maximum negative rate of pressure change) and echocardiographic DD measurements. Spearman correlations were performed for each echocardiographic feature with invasive markers to understand pairwise relationships. Separate random forest (RF) models were implemented to assess all echocardiographic features, key demographic data, and clinical diagnosis in predicting invasive markers. A backward stepwise regression model was simultaneously implemented as a comparative conventional reference model. The relative importance of all parameters was ranked in terms of accuracy reduction. Model approximation was then performed using a regression tree with the top-ranked features of each RF model to improve model interpretability. Regression coefficients of the linear models were presented. RESULTS: Fifty-nine children were included. Spearman correlations were generally low. The RF models' performance measures were noninferior to those of the linear model. However, the linear model's regression coefficients were unintuitive. The highest ranked important features for the RF models were propagation velocity for Tau, E/propagation velocity ratio for left ventricular end-diastolic pressure, and systolic global longitudinal strain rate for maximum negative rate of pressure change. CONCLUSIONS: Estimating individual components of DD can potentially improve the noninvasive assessment of pediatric DD. Although pairwise correlations measured were weak and linear regression coefficients unintuitive, approximated machine learning models aided in understanding how echocardiographic and invasive parameters of DD are related. This machine learning approach could help in further development of pediatric-specific diagnostic algorithms.
Subject(s)
Aortic Valve Stenosis , Ventricular Dysfunction, Left , Cardiac Catheterization , Child , Diastole , Echocardiography , Humans , Ventricular Dysfunction, Left/diagnostic imaging , Ventricular Function, LeftABSTRACT
BACKGROUND: Metabolic predictors and potential mediators of survival in sepsis have been incompletely characterized. We examined whether machine learning (ML) tools applied to the human plasma metabolome could consistently identify and prioritize metabolites implicated in sepsis survivorship, and whether these methods improved upon conventional statistical approaches. METHODS: Plasma gas chromatography-liquid chromatography mass spectrometry quantified 411 metabolites measured ≤ 72 h of ICU admission in 60 patients with sepsis at a single center (Brigham and Women's Hospital, Boston, USA). Seven ML approaches were trained to differentiate survivors from non-survivors. Model performance predicting 28 day mortality was assessed through internal cross-validation, and innate top-feature (metabolite) selection and rankings were compared across the 7 ML approaches and with conventional statistical methods (logistic regression). Metabolites were consensus ranked by a summary, ensemble ML ranking procedure weighing their contribution to mortality risk prediction across multiple ML models. RESULTS: Median (IQR) patient age was 58 (47, 62) years, 45% were women, and median (IQR) SOFA score was 9 (6, 12). Mortality at 28 days was 42%. The models' specificity ranged from 0.619 to 0.821. Partial least squares regression-discriminant analysis and nearest shrunken centroids prioritized the greatest number of metabolites identified by at least one other method. Penalized logistic regression demonstrated top-feature results that were consistent with many ML methods. Across the plasma metabolome, the 13 metabolites with the strongest linkage to mortality defined through an ensemble ML importance score included lactate, bilirubin, kynurenine, glycochenodeoxycholate, phenylalanine, and others. Four of these top 13 metabolites (3-hydroxyisobutyrate, indoleacetate, fucose, and glycolithocholate sulfate) have not been previously associated with sepsis survival. Many of the prioritized metabolites are constituents of the tryptophan, pyruvate, phenylalanine, pentose phosphate, and bile acid pathways. CONCLUSIONS: We identified metabolites linked with sepsis survival, some confirming prior observations, and others representing new associations. The application of ensemble ML feature-ranking tools to metabolomic data may represent a promising statistical platform to support biologic target discovery.
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AIMS: Cardiogenic shock (CS) with variable systemic inflammation may be responsible for patient heterogeneity and the exceedingly high mortality rate. Cardiovascular events have been associated with clonal haematopoiesis (CH) where specific gene mutations in haematopoietic stem cells lead to clonal expansion and the development of inflammation. This study aims to assess the prevalence of CH and its association with survival in a population of CS patients in a quaternary centre. METHODS AND RESULTS: We compared the frequency of CH mutations among 341 CS patients and 345 ambulatory heart failure (HF) patients matched for age, sex, ejection fraction, and HF aetiology. The association of CH with survival and levels of circulating inflammatory cytokines was analysed. We detected 266 CH mutations in 149 of 686 (22%) patients. CS patients had a higher prevalence of CH-related mutations than HF patients (odds ratio 1.5; 95% confidence interval [CI] 1.0-2.1, p = 0.02) and was associated with decreased survival (30 days: hazard ratio [HR] 2.7; 95% CI 1.3-5.7, p = 0.006; 90 days: HR 2.2; 95% CI 1.3-3.9, p = 0.003; and 3 years: HR 1.7; 95% CI 1.1-2.8, p = 0.01). TET2 or ASXL1 mutations were associated with lower survival in CS patients at all time-points (p ≤ 0.03). CS patients with TET2 mutations had higher circulating levels of SCD40L, interferon-γ, interleukin-4, and tumour necrosis factor-α (p ≤ 0.04), while those with ASXL1 mutations had decreased levels of CCL7 (p = 0.03). CONCLUSIONS: Cardiogenic shock patients have high frequency of CH, notably mutations in TET2 and ASXL1. This was associated with reduced survival and dysregulation of circulating inflammatory cytokines in those CS patients with CH.
Subject(s)
Heart Failure , Shock, Cardiogenic , Clonal Hematopoiesis , Heart Failure/complications , Heart Failure/genetics , Humans , Inflammation , Interferon-gamma , Interleukin-4 , Shock, Cardiogenic/etiology , Tumor Necrosis Factor-alphaABSTRACT
BACKGROUND: Endothelial cell (EC) activation, endotheliitis, vascular permeability, and thrombosis have been observed in patients with severe coronavirus disease 2019 (COVID-19), indicating that the vasculature is affected during the acute stages of SARS-CoV-2 infection. It remains unknown whether circulating vascular markers are sufficient to predict clinical outcomes, are unique to COVID-19, and if vascular permeability can be therapeutically targeted. METHODS: Prospectively evaluating the prevalence of circulating inflammatory, cardiac, and EC activation markers as well as developing a microRNA atlas in 241 unvaccinated patients with suspected SARS-CoV-2 infection allowed for prognostic value assessment using a Random Forest model machine learning approach. Subsequent ex vivo experiments assessed EC permeability responses to patient plasma and were used to uncover modulated gene regulatory networks from which rational therapeutic design was inferred. FINDINGS: Multiple inflammatory and EC activation biomarkers were associated with mortality in COVID-19 patients and in severity-matched SARS-CoV-2-negative patients, while dysregulation of specific microRNAs at presentation was specific for poor COVID-19-related outcomes and revealed disease-relevant pathways. Integrating the datasets using a machine learning approach further enhanced clinical risk prediction for in-hospital mortality. Exposure of ECs to COVID-19 patient plasma resulted in severity-specific gene expression responses and EC barrier dysfunction, which was ameliorated using angiopoietin-1 mimetic or recombinant Slit2-N. INTERPRETATION: Integration of multi-omics data identified microRNA and vascular biomarkers prognostic of in-hospital mortality in COVID-19 patients and revealed that vascular stabilizing therapies should be explored as a treatment for endothelial dysfunction in COVID-19, and other severe diseases where endothelial dysfunction has a central role in pathogenesis. FUNDING: This work was directly supported by grant funding from the Ted Rogers Center for Heart Research, Toronto, Ontario, Canada and the Peter Munk Cardiac Center, Toronto, Ontario, Canada.
Subject(s)
COVID-19 , MicroRNAs , Vascular Diseases , COVID-19/diagnosis , COVID-19/mortality , Capillary Permeability , Humans , MicroRNAs/metabolism , SARS-CoV-2 , Vascular Diseases/virologyABSTRACT
BACKGROUND: As patients with advanced heart failure are living longer, defining the impact of left ventricular assist devices (LVADs) on outcomes in an aging population is of great importance. We describe overall survival, rates of adverse events (AEs), and post-AE survival in patients age ≥ 70 years vs age 50-69 years after destination-therapy (DT) LVAD implantation. METHODS: A retrospective analysis was conducted with the use of the International Society for Heart and Lung Transplantation Mechanically Assisted Circulatory Support (IMACS) registry. All adults age ≥ 50 years with a continuous-flow DT LVAD from 2013 to 2017 were included. The primary outcome was all-cause mortality. The secondary outcomes were the incidence of and survival after gastrointestinal (GI) bleeding, infection, stroke, pump thrombosis, pump exchange, and right-side heart failure. Mortality and AEs were assessed with the use of competing risk models. RESULTS: At total of 5,572 patients were included: 3,700 aged 50-69 and 1,872 aged ≥ 70. All-cause mortality by 42 months was 55.8% in patients aged ≥ 70 and 44.8% in patients aged 50-69 (P = 0.001). Patients aged ≥ 70 had a 37.8% higher risk of death after DT LVAD implantation (hazard ratio 1.378, 95% CI 1.251-1.517). Patients aged ≥ 70 had higher risk of GI bleeding but lower risk of right-side heart failure. There was no difference between age groups for risk of infection or stroke. Experiencing any AE was associated with an increased risk of death that did not vary with age. CONCLUSIONS: Patients aged ≥ 70 years have reduced survival after DT LVAD, in part because of increased GI bleeding, while the incidence of other AEs is similar to that of patients aged 50-69 years. Careful patient selection beyond age alone may allow for optimal outcomes after DT LVAD implantation.
Subject(s)
Heart Failure/surgery , Heart-Assist Devices , Quality of Life , Registries , Ventricular Function, Left/physiology , Age Factors , Aged , Female , Heart Failure/physiopathology , Humans , Male , Middle Aged , Patient Selection , Retrospective Studies , Treatment OutcomeABSTRACT
The etiology of Kawasaki Disease (KD), the most common cause of acquired heart disease in children in developed countries, remains elusive, but could be multifactorial in nature as suggested by the numerous environmental and infectious exposures that have previously been linked to its epidemiology. There is still a lack of a comprehensive model describing these complex associations. We present a Bayesian disease model that provides insight in the spatiotemporal distribution of KD in Canada from 2004 to 2017. The disease model including environmental factors had improved Watanabe-Akaike information criterion (WAIC) compared to the base model which included only spatiotemporal and demographic effects and had excellent performance in recapitulating the spatiotemporal distribution of KD in Canada (98% and 86% spatial and temporal correlations, respectively). The model suggests an association between the distribution of KD and population composition, weather-related factors, aeroallergen exposure, pollution, atmospheric concentration of spores and algae, and the incidence of healthcare encounters for bacterial pneumonia or viral intestinal infections. This model could be the basis of a hypothetical data-driven framework for the spatiotemporal distribution of KD. It also generates novel hypotheses about the etiology of KD, and provides a basis for the future development of a predictive and surveillance model.