A matching-adjusted indirect comparison of combination nivolumab plus ipilimumab with BRAF plus MEK inhibitors for the treatment of BRAF-mutant advanced melanoma☆

Background

Approved first-line treatments for patients with BRAF V600–mutant advanced melanoma include nivolumab (a programmed cell death protein 1 inhibitor) plus ipilimumab (a cytotoxic T lymphocyte antigen-4 inhibitor; NIVO+IPI) and the BRAF/MEK inhibitors dabrafenib plus trametinib (DAB+TRAM), encorafenib plus binimetinib (ENCO+BINI), and vemurafenib plus cobimetinib (VEM+COBI). Results from prospective randomized clinical trials (RCTs) comparing these treatments have not yet been reported. This analysis evaluated the relative efficacy and safety of NIVO+IPI versus DAB+TRAM, ENCO+BINI, and VEM+COBI in patients with BRAF-mutant advanced melanoma using a matching-adjusted indirect comparison (MAIC).

Patients and methods

A systematic literature review identified RCTs for DAB+TRAM, ENCO+BINI, and VEM+COBI in patients with BRAF-mutant advanced melanoma. Individual patient-level data for NIVO+IPI were derived from the phase III CheckMate 067 trial (BRAF-mutant cohort) and restricted to match the inclusion/exclusion criteria of the comparator trials. Treatment effects for overall survival (OS) and progression-free survival (PFS) were estimated using Cox proportional hazards and time-varying hazard ratio (HR) models. Safety outcomes (grade 3 or 4 treatment-related adverse events) with NIVO+IPI and the comparators were compared.

Results

In the Cox proportional hazards analysis, NIVO+IPI showed improved OS compared with DAB+TRAM (HR = 0.53; 95% confidence interval [CI], 0.39-0.73), ENCO+BINI (HR = 0.60; CI, 0.42-0.85), and VEM+COBI (HR = 0.50; CI, 0.36-0.70) for the overall study period. In the time-varying analysis, NIVO+IPI was associated with significant improvements in OS and PFS compared with the BRAF/MEK inhibitors 12 months after treatment initiation. There were no significant differences between NIVO+IPI and BRAF/MEK inhibitor treatment from 0 to 12 months. Safety outcomes favored DAB+TRAM over NIVO+IPI, whereas NIVO+IPI was comparable to VEM+COBI.

Conclusion

Results of this MAIC demonstrated durable OS and PFS benefits for patients with BRAF-mutant advanced melanoma treated with NIVO+IPI compared with BRAF/MEK inhibitors, with the greatest benefits noted after 12 months.

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First-line treatments for BRAF V600-mutant melanoma include NIVO+IPI and BRAF/MEK inhibitors.

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Results from prospective RCTs comparing NIVO+IPI and BRAF/MEK inhibitors have not yet been reported.

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This MAIC evaluated NIVO+IPI versus BRAF/MEK inhibitors for BRAF-mutant advanced melanoma.

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OS and PFS benefits were noted with NIVO+IPI versus BRAF/MEK inhibitors beginning at 12 months.

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These findings may provide information relevant to the selection of treatments for BRAF-mutant advanced melanoma.

Molecular Simulations of Hydrophobic Gating of Pentameric Ligand Gated Ion Channels: Insights into Water and Ions

Ion channels are proteins which form gated nanopores in biological membranes. Many channels exhibit hydrophobic gating, whereby functional closure of a pore occurs by local dewetting. The pentameric ligand gated ion channels (pLGICs) provide a biologically important example of hydrophobic gating. Molecular simulation studies comparing additive vs polarizable models indicate predictions of hydrophobic gating are robust to the model employed. However, polarizable models suggest favorable interactions of hydrophobic pore-lining regions with chloride ions, of relevance to both synthetic carriers and channel proteins. Electrowetting of a closed pLGIC hydrophobic gate requires too high a voltage to occur physiologically but may inform designs for switchable nanopores. Global analysis of ∼200 channels yields a simple heuristic for structure-based prediction of (closed) hydrophobic gates. Simulation-based analysis is shown to provide an aid to interpretation of functional states of new channel structures. These studies indicate the importance of understanding the behavior of water and ions within the nanoconfined environment presented by ion channels.

Outcomes of neonatal chylous effusions: A 20-year west-Australian tertiary center experience

Neonatal chylous effusions are rare entity with limited evidence-based management. We conducted a retrospective review of neonates admitted to King Edward Memorial and Princess Margaret/Perth Children's Hospital over 20 years with laboratory-confirmed chylous effusions. A total of 51 infants with chylous effusion were identified. Median gestational age and birth weight were 35.5 weeks and 2620 grams respectively. Congenital [27/ 51] and acquired [24/51] cases were included. Antenatal interventions were performed in 17/22 with antenatal hydrops and 50/51 needed postnatal drains. Effusions were monitored with serial (≥2) chest ultrasounds in 29/51 infants and multiple (≥5) x-rays in 45/51 infants. Median duration of mechanical ventilation, oxygen requirement, and hospital stay was 294.5 hours, 400 hours, and 49 days respectively. 39/51 received medium chain triglyceride (MCT) diet while 8/51 received octreotide. Six infants died during hospital stay. 12/19 had normal developmental assessment at one-year. The acquired group had higher number of xrays done, need for MCT diet and inotropes, and hospital stay vs congenital group. Duration of drains, radiological investigations and immunoglobulin administration were higher in neonates who received octreotide. Syndromic association, duration of ventilation and oxygenation were risk factors for mortality. In our setting, neonatal chylous effusions are associated with significant morbidity and mortality.

Difficulties in developmental follow-up of preterm neonates in a randomised-controlled trial of Bifidobacterium breve M16-V - Experience from Western Australia

BACKGROUND

Probiotics may be neuroprotective for preterm neonates due to their anti-inflammatory effects and ability to facilitate nutrition.

AIM

To assess long-term effects of early probiotic supplementation on neuropsychological development in preterm infants.

STUDY DESIGN

Follow up study.

SUBJECTS

Children at age 3 to 5 years who had participated as preterm infants (<33 week) in the randomised controlled trial.

OUTCOMES

Primary: Continuous early learning composite measure derived from the Mullen's Scale of Early Learning (MSEL). Other outcomes were assessed by the Developmental, Dimensional and Diagnostic Interview, Developmental NEuroPSYchological assessment-2nd Edition, Parental questionnaires using children's communication checklist-2nd edition, social responsiveness scale, and Vineland Adaptive Behavioural Scales-2nd edition.

MEASURES

Continuous scores derived from all the measures.

RESULTS

67 children of the 159 participants (42%) (Probiotic: 36/79, Placebo: 31/80) were followed-up for at least one neuropsychological assessment. All six assessments were completed in 18/31 (58.1%) of the control vs. 11/36 (30.6%) probiotic group children. Multivariable analysis of MSEL composite score showed no evidence of probiotic effect univariately, or after adjustment for gestation, intrauterine growth restriction, Apgar <7 at 5 min and age at assessment (adjusted mean effect in probiotic group: -2.7, 95% CI -8.5-3.0, p = 0.349).

CONCLUSION

There was no significant effect on neurodevelopment of children assessed at the age of 3 to 5 years who participated as preterm neonates in the RCT of B. breve M-16V. The validity of these results is limited by the reduced sample size due to high rate of loss to follow up.

Efficacy of a formalin-inactivated Lactococcus garvieae vaccine in farmed grey mullet (Mugil cephalus)

Lactococcosis [Lactococcus garvieae (LG)] is one of the most prevalent bacterial diseases affecting grey mullet (Mugil cephalus) aquaculture. Therefore, the present research evaluated the efficacy of formalin-killed LG vaccine with an oil-based adjuvant in grey mullet under laboratory and field trials. The laboratory evaluation for LG vaccine and its cross-protection upon challenge in grey mullet found that single-dose immunization of formalin-killed LG with adjuvant resulted in 91.4% and 100% relative per cent survival (RPS) when challenged with homologous and heterologous strains. The levels of specific antibody titre and lysozyme activity increased significantly in the vaccinated group. Immune gene expression at 24 hr after challenge showed an increase in levels of pro-inflammatory and anti-inflammatory cytokines. A parallel field trial experiment was conducted to investigate the long-term effectiveness of the LG vaccine. Results demonstrated that at one month and three months post-immunization with heterologous strain, 100% RPS was recorded in the vaccinated group. The findings suggested that the formalin-inactivated LG vaccine strain (S3) protected grey mullet against LG infection for a period of three months.

The MscS-like channel YnaI has a gating mechanism based on flexible pore helices

The mechanosensitive channel of small conductance (MscS) is the prototype of an evolutionarily diversified large family that fine-tunes osmoregulation but is likely to fulfill additional functions. Escherichia coli has six osmoprotective paralogs with different numbers of transmembrane helices. These helices are important for gating and sensing in MscS but the role of the additional helices in the paralogs is not understood. The medium-sized channel YnaI was extracted and delivered in native nanodiscs in closed-like and open-like conformations using the copolymer diisobutylene/maleic acid (DIBMA) for structural studies. Here we show by electron cryomicroscopy that YnaI has an extended sensor paddle that during gating relocates relative to the pore concomitant with bending of a GGxGG motif in the pore helices. YnaI is the only one of the six paralogs that has this GGxGG motif allowing the sensor paddle to move outward. Access to the pore is through a vestibule on the cytosolic side that is fenestrated by side portals. In YnaI, these portals are obstructed by aromatic side chains but are still fully hydrated and thus support conductance. For comparison with large-sized channels, we determined the structure of YbiO, which showed larger portals and a wider pore with no GGxGG motif. Further in silico comparison of MscS, YnaI, and YbiO highlighted differences in the hydrophobicity and wettability of their pores and vestibule interiors. Thus, MscS-like channels of different sizes have a common core architecture but show different gating mechanisms and fine-tuned conductive properties.

Cardiometabolic disease, comorbidities and risk of death: findings using data from large-scale electronic health records

Background

Myocardial infarction (MI), stroke and diabetes are separately associated with increased risk of mortality but it is uncertain if their combined effects are proportional, amplified or less than the expected risk of each disease individually. In addition, patients with these conditions tend to also have other long-term comorbidities. How the relationship between cardiometabolic disease and risk of death is modified by the presence of comorbidity is unclear.

Purpose

We investigated the separate and combined effects of MI, stroke and diabetes on all-cause mortality, and examined the impact of comorbidity on these associations.

Methods

We selected a patient cohort of 2,007,731 (51% women) aged ≥16 years at registration with their general practice, using large-scale UK primary care electronic health records that were linked to the national death registry. We identified patients with a recorded diagnosis of MI, stroke, diabetes or none before 2005 (baseline), and classified the patient cohort into mutually exclusive categories of their baseline disease status. For each group, we also extracted information on another major 53 long-term conditions prior to baseline. The cohort was followed until death, deregistration from the practice or censored at the end of study (31 Dec 2014). We used Cox regression, and tested for departure from additivity and multiplicativity to assess interaction.

Results

At baseline, the mean age of the cohort was 51 (SD=18) years and 7% (N=145,910) had a cardiometabolic disease. Over an average follow-up of 7 (SD=3) years, 270,036 died (mean age of death=79 years). After adjusting for baseline age and sex, the hazard ratio (HR) (95% confidence interval [CI]), relative to those without cardiometabolic disease, were as follows: diabetes=1.53 (1.51 to 1.55), MI=1.54 (1.51 to 1.56), stroke=1.87 (1.84 to 1.90), diabetes and MI=2.16 (2.09 to 2.23), MI and stroke=2.39 (2.28 to 2.49), diabetes and stroke=2.56 (2.47 to 2.65), and all three=3.17 (2.95 to 3.41). After adjusting for the 53 comorbidities, the HR (95% CI) were attenuated: diabetes=1.37 (1.35 to 1.39), MI=1.25 (1.23 to 1.27), stroke=1.49 (1.46 to 1.52), diabetes and MI=1.60 (1.55 to 1.65), MI and stroke=1.52 (1.45 to 1.59), diabetes and stroke=1.91 (1.84 to 1.98), and all three=1.77 (1.64 to 1.91). The results did not materially changed with adjustment for smoking and deprivation level. Test for interaction revealed some minor synergistic effects when cardiometabolic disease co-occurred but excess risks were lower than expected for two combined vs individual disease effects; no significant interaction was seen for all three vs individual disease effects.

Conclusion

MI, stroke and diabetes are associated with excess mortality, which was partly due to associated chronic conditions. We found no evidence that the co-occurrence of these three conditions contribute to a higher excess mortality than expected from each of them separately.

Funding Acknowledgement

Type of funding source: Public Institution(s). Main funding source(s): NIHR Oxford Biomedical Research Centre; Oxford Martin School, University of Oxford

Does cardiac transplant protect against broken hearts?

Background

Takotsubo cardiomyopathy (TC) is a reversible stress-induced myocardial dysfunction with increased sympathetic activity caused by excessive release of catecholamines playing a central role in its pathophysiology. The occurrence of TC in transplanted hearts is rare given the complete denervation done during transplantation. However, it has been demonstrated that 40% of transplant recipients undergo sympathetic re-innervation. There have only been case reports describing TC in post-transplant recipients.

Purpose

To evaluate the incidence, baseline characteristics and outcomes of TC occurring in heart transplant recipients using Healthcare Cost and Utilization Project (HCUP) National (nationwide) Inpatient Sample (NIS) in United States from 2009 to 2014.

Methods

Using NIS data, we identified patients who underwent cardiac transplantation using ICD9 procedure codes 37.5 and 33.6. Among these patients, we identified those admitted to the hospital with diagnosis of TC based on ICD-9-CM code 429.83. We presented categorical data as percentages and continuous data as mean or median as appropriate.

Results

We identified 257 hospitalizations for TC in heart transplant recipient patients. There was an approximately 9-fold increase in admissions from 11 in 2009 to 95 in 2014. Among patients with TC, the mean age was 65.3±1.8 years and majority were female (76.6%). A majority of patients were Caucasians (63%) followed by smaller proportion of African-Americans (13.2%).

In-patient mortality in patients admitted with TC following heart transplant was 11.3% (n=29). During the hospitalization, 4.8% of patients had cardiogenic shock and 2.8% required mechanical circulatory support. The average length of stay for patients with TC was 16.6±3.3 days. The mean cost of hospitalization for these patients when adjusted for inflation were 237248±55709 dollars.

Conclusion

TC can still occur in substantially in heart transplant recipients and should be considered one of the differential diagnosis in transplant patients presenting to the hospital.

Funding Acknowledgement

Type of funding source: None

An interpretable model for incident heart failure prediction with uncertainty estimation

Background

Forecasting incident heart failure is a critical demand for prevention. Recent research suggested the superior performance of deep learning models on the prediction tasks using electronic health records. However, even with a relatively accurate predictive performance, the major impediments to the wider use of deep learning models for clinical decision making are the difficulties of assigning a level of confidence to model predictions and the interpretability of predictions.

Purpose

We aimed to develop a deep learning framework for more accurate incident heart failure prediction, with provision of measures of uncertainty and interpretability.

Methods

We used a longitudinal linked electronic health records dataset, Clinical Practice Research Datalink, involving 788,880 patients, 8.3% of whom had an incident heart failure diagnosis. To embed the uncertainty estimation mechanism into the deep learning models, we developed a probabilistic framework based on a novel transformer deep learning model: deep Bayesian Gaussian processes (DBGP). We investigated the performance of incident heart failure prediction and uncertainty estimation for the model and validated it using an external held-out dataset. Diagnoses, medications, and age for each encounter were included as predictors. By comparing the uncertainty, we investigated the possibility of identifying the correct predictions from wrong ones to avoid potential misclassification. Using model distillation meant to mimic a well-trained complex model with simple models, we investigated the importance of associations between diagnoses, medications and heart failure with an interpretable linear regression component learned from DBGP.

Results

The DBGP achieved high precision with 0.941 as AUROC for external validation. More importantly, it showed the uncertainty information could distinguish the correct predictions from wrong ones, with significant difference (p-value with 500 samples) between distribution of uncertainties for negative predictions (3.21e-69 between true negative and false negative), and positive predictions (3.39e-22 between true positive and false positive). Utilising the distilled model, we can specify the contribution of each diagnosis and medication to heart failure prediction. For instance, Losartan/Fosinopril, Bisoprolol and Left bundle-branch block showed strong association to heart failure incidence with coefficient 0.11 (95% CI: 0.10, 0.12), 0.09 (0.08, 0.11) and 0.09 (0.07, 0.11) respectively; Peritoneal adhesions, Trochanteric bursitis and Galactorrhea showed strong disassociations with coefficient −0.07 (−0.09, −0.05), −0.07 (−0.09, −0.04) and −0.06 (−0.08, −0.04) individually.

Conclusions

Our novel probabilistic deep learning framework adds a measure of uncertainty the prediction and helps to mitigate misclassification. Model distillation provides an opportunity to interpret deep learning models and offers a data-driven perspective for risk factor analysis.

Funding Acknowledgement

Type of funding source: Public Institution(s). Main funding source(s): Oxford Martin School,University of Oxford; NIHR Oxford Biomedical Research Centre, University of Oxford

A nationwide 16 year analysis of trends and impact of arrythmias in transplant recipients

Background

Orthotopic heart transplantation is the most effective long-term therapy for end-stage heart disease. Denervation of transplanted heart with the loss of autonomic modulation, vasculopathy, utilization of immunosuppressant drugs, and risk of allograft rejection may result in change in the prevalence of arrhythmias in transplanted hearts.

Purpose

To describe the trends, distribution and the clinical impact of arrhythmias in transplanted hearts in a large nationwide population.

Methods

We queried the National Inpatient Sample with administrative codes. Cardiac transplant patients were identified using procedure ICD-9-CM codes 37.5 and 33.6. Common arrhythmias were extracted using appropriate validated ICD-9-CM codes. Statistical Analysis System (SAS) version 9.4 was used for analysis of data.

Results

There was a total of 30,020 hospitalizations of heart transplant recipients between 1999 and 2014 in the United States and 16342 (54.4%) of these had arrhythmias. The prevalence of total arrhythmias increased from 53.6% (n=1,158) in 1999 to 67.3% (n=1,575) in 2014. The most common arrhythmia was atrial fibrillation (26.83%) followed by ventricular tachycardia (22.86%) and the prevalence of individual arrhythmias is as shown in Figure 1.

Cardiogenic shock was higher in transplanted hearts with arrhythmias when compared with patients without arrhythmias (25.96% vs 18.18%; p&lt;0.001). Transplant recipients with arrhythmias were also associated with an increased use of mechanical circulatory device (18.22% vs 12.67%, p&lt;0.001). The use of implantable cardiac defibrillators and permanent pacemaker was also higher in the arrhythmia group (2.19% vs 0.63% and 40.43% vs 30.24% respectively, p&lt;0.0001). However, there was no significant difference in inpatient mortality between transplant recipients with arrhythmias and without arrhythmias (7.72% vs 6.90%, p=0.225). Further, there was no significant difference in frequency of strokes between the groups (4.98% vs 5.08%; p=0.857).

The total hospital cost when adjusted for inflation was significantly higher in the arrhythmic patients, with an average cost of about $570,415±9,590 vs $439,707±8362 in patients without arrhythmias (p&lt;0.0001). The mean length of hospitalization was 44.2±0.8 days in patients with arrhythmias compared to 33.9±0.8 days in patients without arrhythmias (p&lt;0.0001).

Conclusion

A significant proportion of patients with heart transplant have cardiac arrhythmias and are associated with worse in-hospital outcomes of cardiogenic shock, increased length of stay, and cost of hospitalization. However, they are not associated with worse inpatient mortality.

Funding Acknowledgement

Type of funding source: None

BEHRT-HF: an interpretable transformer-based, deep learning model for prediction of incident heart failure

Background/Introduction

Predicting incident heart failure has been challenging. Deep learning models when applied to rich electronic health records (EHR) offer some theoretical advantages. However, empirical evidence for their superior performance is limited and they remain commonly uninterpretable, hampering their wider use in medical practice.

Purpose

We developed a deep learning framework for more accurate and yet interpretable prediction of incident heart failure.

Methods

We used longitudinally linked EHR from practices across England, involving 100,071 patients, 13% of whom had been diagnosed with incident heart failure during follow-up. We investigated the predictive performance of a novel transformer deep learning model, “Transformer for Heart Failure” (BEHRT-HF), and validated it using both an external held-out dataset and an internal five-fold cross-validation mechanism using area under receiver operating characteristic (AUROC) and area under the precision recall curve (AUPRC). Predictor groups included all outpatient and inpatient diagnoses within their temporal context, medications, age, and calendar year for each encounter. By treating diagnoses as anchors, we alternatively removed different modalities (ablation study) to understand the importance of individual modalities to the performance of incident heart failure prediction. Using perturbation-based techniques, we investigated the importance of associations between selected predictors and heart failure to improve model interpretability.

Results

BEHRT-HF achieved high accuracy with AUROC 0.932 and AUPRC 0.695 for external validation, and AUROC 0.933 (95% CI: 0.928, 0.938) and AUPRC 0.700 (95% CI: 0.682, 0.718) for internal validation. Compared to the state-of-the-art recurrent deep learning model, RETAIN-EX, BEHRT-HF outperformed it by 0.079 and 0.030 in terms of AUPRC and AUROC. Ablation study showed that medications were strong predictors, and calendar year was more important than age. Utilising perturbation, we identified and ranked the intensity of associations between diagnoses and heart failure. For instance, the method showed that established risk factors including myocardial infarction, atrial fibrillation and flutter, and hypertension all strongly associated with the heart failure prediction. Additionally, when population was stratified into different age groups, incident occurrence of a given disease had generally a higher contribution to heart failure prediction in younger ages than when diagnosed later in life.

Conclusions

Our state-of-the-art deep learning framework outperforms the predictive performance of existing models whilst enabling a data-driven way of exploring the relative contribution of a range of risk factors in the context of other temporal information.

Funding Acknowledgement

Type of funding source: Private grant(s) and/or Sponsorship. Main funding source(s): National Institute for Health Research, Oxford Martin School, Oxford Biomedical Research Centre

A nationwide analysis of 16 year trends in cardiac transplantation for cardiac sarcoidosis

Background

Orthotopic heart transplant (OHT) is indicated for end-stage heart failure due to cardiac sarcoidosis (CS). However, utilization of OHT for CS has been controversial due to concern for involvement of other organs by sarcoidosis affecting long term outcomes.

Purpose

Our objective was to study the trends in OHT in patients with CS in the United States using Healthcare Cost and Utilization Project (HCUP) National (nationwide) Inpatient Sample (NIS) from 1999 to 2014.

Methods

Using NIS data, we identified patients older than 18 years with cardiac sarcoidosis using codes ICD 9-CM codes of 135 and 425.8. Among these patients, we identified those who underwent cardiac transplantation using ICD 9-CM procedure codes 37.5 and 33.6. We presented categorical data as percentages and continuous data as mean or median as appropriate.

Results

A weighted total of 24231 hospitalizations for CS was extracted from 1999 to 2014 of which 248 (1.02%) CS patients underwent OHT. The trends in cardiac transplant for CS is as shown in Figure 1.

The mean age of CS patients undergoing OHT was 51.7±1.1 years and 60.4% (n=150) were males. 114 (45.9%) were Caucasians and 27.8% (n=25) were African-American. 100% of the transplants were performed at medium (n=5) or large sized (n=243) teaching hospitals and 97.9% of cardiac transplants were also done at teaching hospitals. Heart transplants were mostly done in the South (36.3%) followed by Midwest (26.2%), West (25%) and Northeast (12.5%). Private insurance was the major payor source which covered 149 (60.1%) patients followed by Medicare covering 65 (26.2%) patients.

A total of 10 (3.9%) cardiac sarcoidosis patients died during the same hospitalization for cardiac transplantation. Following OHT, 84.2% (n=209) were discharged home and 11.6% (n=29) to short term hospitalization. The mean cost of hospitalization for OHT in CS when adjusted for inflation was 535144±56060 dollars while the average length of stay for heart transplant for CS was 46.2±6.6 days.

Conclusions

Cardiac transplant trends in CS have not changed from 1999 to 2014 despite recent studies showing improved outcomes and are associated with substantial cost of hospitalization and length of stay. Majority of cardiac transplant was done in Caucasians despite cardiac sarcoidosis being more common in African-Americans.

Funding Acknowledgement

Type of funding source: None

A nationwide analysis of 16 year trends in cardiac transplantation for acute myocarditis

Background

Orthotopic heart transplant (OHT) is indicated in 1–8% of patients with myocarditis. However, national trends in the utilization of transplantation and outcomes in myocarditis across the United States are not well established.

Purpose

Our objective was to study the trends and baseline characteristic of myocarditis patients undergoing heart transplant in the United States using Healthcare Cost and Utilization Project (HCUP) National (nationwide) Inpatient Sample (NIS) from 1999 to 2014.

Methods

Using NIS data, we identified patients older than 18 years with myocarditis using codes ICD9 codes of 422.0 and 422.9. Among these patients, we identified those who underwent cardiac transplantation using ICD9 procedure codes 37.5 and 33.6. We presented categorical data as percentages and continuous data as mean or median as appropriate.

Results

We identified a total of 62,264 hospitalizations for myocarditis from 1999–2014. 430 (0.69%) myocarditis patients underwent OHT which consisted of 0.82% of all 29990 cardiac transplants identified in the same period. The trends in OHT for myocarditis is as shown in Figure 1.

The mean age was 32.9±2.4 years and 51.1% (n=219) were females. 235 (54.6%) were Caucasians and 60 (13.9%) were Hispanic. Majority of the transplants were performed at medium (16%) and large sized hospitals (80.4%). Cardiac transplants were mainly done at teaching hospitals (98.9%). Further, with regards to the geographical distribution of transplant procedure, most were done in the West (37.2%) followed by South (25.3%), Northeast (21.4%) and Mid-west (16%) of the United States. Private insurance was the major payor source which covered 245 (58%) patients followed by Medicaid covering 112 (26%) patients.

A total of 26 (6%) myocarditis patients died during the same hospitalization for OHT. In terms of discharge following OHT in myocarditis 85.8% (n=369) were discharged home and 8.1% (n=35) to short term hospitalization. The average length of stay for OHT for myocarditis was 64.3±6.3 days. Also, the mean cost of hospitalization for heart transplant in myocarditis when adjusted for inflation was 789,566±93,108 dollars.

In-patient mortality following OHT was not significantly different in large sized hospital compared to small and medium sized hospitals (7.6% vs 5.7%, p=0.54). However, the cost of hospitalization was significantly lesser in small and medium sized hospitals (588,363±154,349 vs 826,864±106,110 dollars, p&lt;0.0001).

Conclusions

Only a small percentage of OHT is done for myocarditis with high proportion done in female when compared to OHT for other etiologies. Further studies need to be done to compare long term outcomes of heart transplant in myocarditis.

Funding Acknowledgement

Type of funding source: None

Water in Nanopores and Biological Channels: A Molecular Simulation Perspective

This Review explores the dynamic behavior of water within nanopores and biological channels in lipid bilayer membranes. We focus on molecular simulation studies, alongside selected structural and other experimental investigations. Structures of biological nanopores and channels are reviewed, emphasizing those high-resolution crystal structures, which reveal water molecules within the transmembrane pores, which can be used to aid the interpretation of simulation studies. Different levels of molecular simulations of water within nanopores are described, with a focus on molecular dynamics (MD). In particular, models of water for MD simulations are discussed in detail to provide an evaluation of their use in simulations of water in nanopores. Simulation studies of the behavior of water in idealized models of nanopores have revealed aspects of the organization and dynamics of nanoconfined water, including wetting/dewetting in narrow hydrophobic nanopores. A survey of simulation studies in a range of nonbiological nanopores is presented, including carbon nanotubes, synthetic nanopores, model peptide nanopores, track-etched nanopores in polymer membranes, and hydroxylated and functionalized nanoporous silica. These reveal a complex relationship between pore size/geometry, the nature of the pore lining, and rates of water transport. Wider nanopores with hydrophobic linings favor water flow whereas narrower hydrophobic pores may show dewetting. Simulation studies over the past decade of the behavior of water in a range of biological nanopores are described, including porins and β-barrel protein nanopores, aquaporins and related polar solute pores, and a number of different classes of ion channels. Water is shown to play a key role in proton transport in biological channels and in hydrophobic gating of ion channels. An overall picture emerges, whereby the behavior of water in a nanopore may be predicted as a function of its hydrophobicity and radius. This informs our understanding of the functions of diverse channel structures and will aid the design of novel nanopores. Thus, our current level of understanding allows for the design of a nanopore which promotes wetting over dewetting or vice versa. However, to design a novel nanopore, which enables fast, selective, and gated flow of water de novo would remain challenging, suggesting a need for further detailed simulations alongside experimental evaluation of more complex nanopore systems.