Aims
The risk of HeartMate II (HMII) left ventricular assist device (LVAD) thrombosis has been reported, and serum lactate dehydrogenase (LDH), a biomarker of haemolysis, increases secondary to LVAD ...thrombosis. This study evaluated longitudinal measurements of LDH post‐LVAD implantation, hypothesizing that LDH trends could timely predict future LVAD thrombosis.
Methods and results
From October 2004 to October 2014, 350 HMIIs were implanted in 323 patients at Cleveland Clinic. Of these, patients on 339 HMIIs had at least one post‐implant LDH value (7996 total measurements). A two‐step joint model combining longitudinal biomarker data and pump thrombosis events was generated to assess the effect of changing LDH on thrombosis risk. Device‐specific LDH trends were first smoothed using multivariate boosted trees, and then used as a time‐varying covariate function in a multiphase hazard model to analyse time to thrombosis. Pre‐implant variables associated with time‐varying LDH values post‐implant using boostmtree were also investigated. Standardized variable importance for each variable was estimated as the difference between model‐based prediction error of LDH when the variable was randomly permuted and prediction error without permuting the values. The larger this difference, the more important a variable is for predicting the trajectory of post‐implant LDH. Thirty‐five HMIIs (10%) had either confirmed (18) or suspected (17) thrombosis, with 15 (43%) occurring within 3 months of implant. LDH was associated with thrombosis occurring both early and late after implant (P < 0.0001 for both hazard phases). The model demonstrated increased probability of HMII thrombosis as LDH trended upward, with steep changes in LDH trajectory paralleling trajectories in probability of pump thrombosis. The most important baseline variables predictive of the longitudinal pattern of LDH were higher bilirubin, higher pre‐implant LDH, and older age. The effect of some pre‐implant variables such as sodium on the post‐implant LDH longitudinal pattern differed across time.
Conclusions
Longitudinal trends in surveillance LDH for patients on HMII support are useful for dynamic prediction of pump thrombosis, both early after implant and late. Incorporating upward and downward trends in LDH that dynamically update a model of LVAD thrombosis risk provides a useful tool for clinical management and decisions.
The study objective was to characterize preoperative and postoperative continuous electroencephalogram metrics and hemodynamic adverse events as predictors of neurodevelopment in congenital heart ...disease infants undergoing cardiac surgery.
From 2010 to 2021, 320 infants underwent congenital heart disease surgery at our institution, of whom 217 had perioperative continuous electroencephalogram monitoring and were included in our study. Neurodevelopment was assessed in 76 patients by the Bayley Scales of Infant and Toddler Development, 3rd edition, consisting of cognitive, communication, and motor scaled scores. Patient and procedural factors, including hemodynamic adverse events, were included by means of the likelihood of covariate selection in our predictive model. Median (25th, 75th percentile) follow-up was 1.03 (0.09, 3.44) years with 3 (1, 6) Bayley Scales of Infant and Toddler Development, 3rd Edition evaluations per patient.
Median age at index surgery was 7 (4, 23) days, and 81 (37%) were female. Epileptiform discharges, encephalopathy, and abnormality (lethargy and coma) were more prevalent on postoperative continuous electroencephalograms, compared with preoperative continuous electroencephalograms (P < .005). In 76 patients with Bayley Scales of Infant and Toddler Development, 3rd edition evaluations, patients with diffuse abnormality (P = .009), waveform discontinuity (P = .007), and lack of continuity (P = .037) on preoperative continuous electroencephalogram had lower cognitive scores. Patients with synchrony (P < .005) on preoperative and waveform continuity (P = .009) on postoperative continuous electroencephalogram had higher fine motor scores. Patients with postoperative adverse events had lower cognitive (P < .005) and gross motor scores (P < .005).
Phenotypic patterns of perioperative continuous electroencephalogram metrics are associated with late-term neurologic injury in infants with congenital heart disease requiring surgery. Continuous electroencephalogram metrics can be integrated with hemodynamic adverse events in a predictive algorithm for neurologic impairment.
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Bicuspid aortic valve (BAV) aortopathy is defined by 3 phenotypes—root, ascending, and diffuse—based on region of maximal aortic dilation. We sought to determine the association between aortic ...mechanical behavior and aortopathy phenotype versus other clinical variables.
From August 1, 2016, to March 1, 2023, 375 aortic specimens were collected from 105 patients undergoing elective ascending aortic aneurysm repair for BAV aortopathy. Planar biaxial data (191 specimens) informed constitutive descriptors of the arterial wall that were combined with in vivo geometry and hemodynamics to predict stiffness, stress, and energy density under physiologic loads. Uniaxial testing (184 specimens) evaluated failure stretch and failure Cauchy stress. Boosting regression was implemented to model the association between clinical variables and mechanical metrics.
There were no significant differences in mechanical metrics between the root phenotype (N = 33, 31%) and ascending/diffuse phenotypes (N = 72, 69%). Biaxial testing demonstrated older age was associated with increased circumferential stiffness, decreased stress, and decreased energy density. On uniaxial testing, longitudinally versus circumferentially oriented specimens failed at significantly lower Cauchy stress (50th 15th, 85th percentiles: 1.0 0.7, 1.6 MPa vs 1.9 1.3, 3.1 MPa; P < .001). Age was associated with decreased failure stretch and stress. Elongated ascending aortas were also associated with decreased failure stress.
Aortic mechanical function under physiologic and failure conditions in BAV aortopathy is robustly associated with age and poorly associated with aortopathy phenotype. Data suggesting that the root phenotype of BAV aortopathy portends worse outcomes are unlikely to be related to aberrant, phenotype-specific tissue mechanics.
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To identify effects of surgeon experience and age, in the context of cumulative institutional experience, on risk-adjusted hospital mortality after cardiac reoperations.
From 1951–2020, 36 surgeons ...performed 160,338 cardiac operations, including 32,871 reoperations. Hospital death was modeled using a novel tree-bagged, generalized varying-coefficient method with 6 variables reflecting cumulative surgeon and institutional experience up to each cardiac operation: 1) number of total and 2) reoperative cardiac operations performed by a surgeon, 3) cumulative institutional number of total and 4) reoperative cardiac operations, 5) year of surgery, and 6) surgeon age at each operation. These were adjusted for 46 patient characteristics and surgical components.
1,470 hospital deaths occurred after cardiac reoperations (4.5%). At the institutional level, hospital death fell exponentially and became less variable, leveling at 1.2% after approximately 14,000 cardiac reoperations. For all surgeons as a group, hospital death decreased rapidly over the first 750 reoperations, then gradually decreased with increasing experience to below 1% after about 4,000 reoperations. Surgeon age up to 75 was associated with ever-decreasing hospital death.
Surgeon age and experience have been implicated in adverse surgical outcomes, particularly after complex cardiac operations, with young surgeons being novices and older surgeons having declining ability. However, at Cleveland Clinic, outcome of cardiac reoperations improved with increasing primary surgeon experience, without any suggestion to mid-70s of an age cut-off. Patients were protected by the cumulative background of institutional experience that created a culture of safety and teamwork that mitigated adverse events after cardiac surgery.
We evaluate the independent effects of patient and aortic tissue characteristics on biaxial physiologic mechanical metrics in aneurysmal and non-aneurysmal tissues, and uniaxial failure metrics in ...aneurysmal tissue, comparing longitudinal and circumferential behavior.
From 2/2017-10/2022, 382 aortic specimens were collected from 134 patients; 268 specimens underwent biaxial and 114 uniaxial testing. Biaxial testing evaluated Green-Lagrange transition strain and low and high tangent moduli. Uniaxial testing evaluated failure stretch, Cauchy stress, and low and high tangent moduli. Longitudinal gradient boosting models were implemented to estimate mechanical metrics and covariates of importance.
On biaxial testing, non-aneurysmal tissue was less deformable, and exhibited a lower transition strain than aneurysmal tissue in the longitudinal (0.18 vs. 0.30,P<.001) and circumferential (0.25 vs. 0.30,P=.01) directions. Older age and increasing ascending aortic length contributed most to predicting transition strain. On uniaxial testing, longitudinal specimens failed at lower stretch (1.4 vs. 1.5,P=.003) and Cauchy stress (1.0 vs. 1.9 kPa, P<.001), than circumferential specimens. Failure stretch and Cauchy stress were most strongly associated with tissue orientation and decreased sharply with older age. Age, ascending aortic length, and tissue thickness were the most frequent covariates predicting mechanical metrics across 10 prediction models.
Age was the strongest predictor of mechanical behavior. Adjusting for age, non-aneurysmal tissue was less deformable than aneurysmal tissue. Differences in longitudinal and circumferential mechanics contribute to tissue dysfunction and failure in ascending aneurysms. This highlights the need to better understand the effects of age, ascending aortic length, and thickness on clinical aortic behavior.
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Objective. The aim of this study was to compare SUDOSCAN, a new device to evaluate sweat function (reflecting peripheral small C-fiber status), with conventional measures of peripheral and cardiac ...neuropathy in patients with type 2 diabetes. Methods. 265 diabetic patients were tested for symptoms and clinical signs of neuropathy using Michigan Neuropathy Screening Instrument (MNSI), vibration perception threshold (VPT) using biothesiometer, and cardiac autonomic neuropathy (CAN) using Ewing’s protocol. Sudomotor function was investigated with SUDOSCAN through measurement of electrochemical skin conductance (ESC) of hands and feet. Lower ESC is suggestive of sudomotor dysfunction. Results. Lower ESC at feet was significantly associated both with increasing symptoms (MNSI A) and increasing score on physical abnormalities (MNSI B). Lower ESC at feet was also significantly associated with increasing VPT by biothesiometry (P<0.01), and with higher number of abnormal CAN results (P<0.05). ESC was associated with postural fall in blood pressure (sympathetic abnormality) (P<0.05), but not with heart rate variability (HRV) tests (parasympathetic abnormalities). Conclusions. Sudomotor dysfunction testing may be a simple test to alert physicians to peripheral nerve and cardiac sympathetic dysfunction. Ease of performance could make it useful in a busy diabetic clinic. Further studies with hard clinical outcomes are indicated.
Surveillance metrics in pediatric and young adult Marfan syndrome (pMFS) are challenging. We evaluated the utility of aortic root cross-sectional area/height index (CSA/Ht) on echocardiogram among ...pMFS patients as a risk stratification and surgical triage metric.
Genotype or phenotype positive pMFS patients aged 25 years or younger seen at our center from 2001 to 2020 were identified. Time-related transition to surgery was modeled using parametric methods. Predictive utility of CSA/Ht compared with aortic root diameter (ARd) and root Z score (ARz) were modeled using nonlinear multivariable parametric and nonparametric longitudinal regression models.
Seventy-nine patients (43% female) presented at median age of 5.8 years (15th-85th percentile, 0.75-17 years) with median follow-up of 4.4 years (range, 0-18.5 years). Baseline echocardiography data were: CSA/Ht, 3.9 ± 1.4 cm2/m; ARd, 2.4 ± 0.89 cm; and ARz, 2.4 ± 1.7. CSA/Ht tracked ARd better compared with ARz (r = 0.91 vs 0.24). Eighteen patients underwent surgery. Surgical procedures included at least 2 components in 17 (aortic, mitral, tricuspid, aortic root, and arch procedures) and isolated mitral valve procedures in 1 patient. Time-related transition to surgery showed a prominent early phase to 1 year post presentation, followed by a slowly increasing late phase. CSA/Ht had a more linear correlation versus ARz during periods of rapid somatic growth in surgical patients. Surgical repair occurred at CSA/Ht between 5 and 7 cm2/m.
CSA/Ht tracked ARd well over time. CSA/Ht between 5 and 7 cm2/m might be a promising metric for surgical triage in pMFS patients. CSA/Ht surgical threshold values in pMFS patients occurred at lower than current accepted “surgical” threshold values for CSA/Ht in adult Marfan syndrome patients.
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Machine learning methods provide a powerful approach for analyzing longitudinal data in which repeated measurements are observed for a subject over time. We boost multivariate trees to fit a novel ...flexible semi-nonparametric marginal model for longitudinal data. In this model, features are assumed to be nonparametric, while feature-time interactions are modeled semi-nonparametrically utilizing
P
-splines with estimated smoothing parameter. In order to avoid overfitting, we describe a relatively simple in sample cross-validation method which can be used to estimate the optimal boosting iteration and which has the surprising added benefit of stabilizing certain parameter estimates. Our new multivariate tree boosting method is shown to be highly flexible, robust to covariance misspecification and unbalanced designs, and resistant to overfitting in high dimensions. Feature selection can be used to identify important features and feature-time interactions. An application to longitudinal data of forced 1-second lung expiratory volume (FEV1) for lung transplant patients identifies an important feature-time interaction and illustrates the ease with which our method can find complex relationships in longitudinal data.
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