Future Failure Research Articles

Assessment of slope failure susceptibility along road networks in a forested region, northern Iran

The risk of slope failure is always associated with the roads constructed in mountain regions. Estimation of the susceptibility of roads to slope failure is a part of the solutions for decreasing road maintenance costs. In this study, we modeled the susceptibility of slope failure along a forest road in northern Iran using the random forest (RF) method. The distribution of past failures was surveyed during field reconnaissance to produce an inventory map. Then the failures were randomly divided into two groups such that 70% (176 locations) were used for model training and the remaining 30% (75 locations) were used for model validation. Eleven geoenvironmental factors (i.e., altitude, slope degree, slope direction, plan curvature, flow accumulation, stream power index, topographic wetness index, topographic position index, topographic roughness index, slope-length, and valley depth) that thought directly or indirectly affected slope failure were selected and linked to the failure locations. The spatial associations between the influencing factors and the failure locations were assessed using the RF method and used for generating spatially explicit maps of slope failure susceptibility. The results showed that stream power index, flow accumulation, and plan curvature with Gini coefficients of 74%, 66%, and 51%, respectively, were the most influential factors in the occurrence and distribution of slope failures. The slope failure susceptibility maps were classified using the natural breaks and geometrical intervals classification methods and showed that nearly 38.11% and 42.42% of the study area are in high to very high risk classes, respectively. Model validation using the sensitivity (92.31%), specificity (85.68%), accuracy (88.54%), root mean square error (RMSE) (0.303), and area under the curve (0.902) proved the excellent performance of the RF model in elucidating the failure mechanisms and predicting future failures. The slope failure susceptibility maps produced in this study allow the development of mitigation strategies for road construction projects.

Real options or fallen angels: Examining the complexities of learning from terminated projects

Do organizations learn from innovative failures? Extant research has been mixed. We posit that these disparate findings likely reflect an underlying (and under‐researched) spectrum of failure severity, which is comprised not only by the magnitude of the failure in question but by the frequency with which it occurs. Using fine‐grained, project‐level data, consisting of 33,905 projects in 2496 pharmaceutical firms, we decompose 1251 terminated projects into two types based on their phase of development: early‐ and late‐stage terminations. We use hazard rate modelling and an analysis of abnormal equity returns to assess the likelihood of future failure and the market's reaction to the project termination. Specifically, we are interested in understanding the role that magnitude and frequency of project terminations play in the likelihood and magnitude of future project terminations.

Case history on excessively large displacements and remediation of pile-supported excavation in a sloping ground

Pile-supported excavations in urban region slopes can result in excessively large retaining wall and ground surface displacements if not strutted or tied back correctly. Such an example is presented in this study showing the details of investigation works, construction procedure, monitoring, and 3D numerical analysis of a deep excavation in a stiff clay slope. Total excavation depth ranged from 4.8 m to 5.3 m, with additional 2.0 m high vertical wall and 2.8 m high steep slope in the vicinity of the pile capping beam. Before reaching the bottom of the designed excavation, the maximum cumulative monitored wall displacements were 115.0 mm, while the cracks observed on the nearby uphill structures exceeded 5.0 mm in width. Detailed field inspections and the 3D numerical analysis were performed to investigate the displacement pattern of the pile wall and the adjacent soil and structures in the uphill area. The numerical model results were further used to define specific supporting measures to enable excavation and building construction. Supporting measures were presented, and their effectiveness was assessed. Finally, the lessons learned were summarized to prevent future failures of similar structures.

Acceptance of psychosocial bridging measures in dementia : Treatment observation during the COVID-19 pandemic

HintergrundBei COVID-19 bedingtem Ausfall eines ambulanten Behandlungsprogramms im Rahmen demenzieller Erkrankungen wurden Patient:innen und deren Angehörigen Überbrückungsmaßnahmen auf Distanz angeboten. Ziel war es zu untersuchen, in welchem Maß die Teilnehmer:innen (TN) belastet waren, und wie die Angebote angenommen und bewertet wurden.Material und MethodenAllen TN (n = 63) wurden über den Zeitraum von 8 Wochen regelmäßige Telefonkontakte in unterschiedlicher Frequenz (wöchentlich, 14-tägig) sowie die Zusendung kognitiver und körperlicher Trainingsaufgaben im Abstand von 2 Wochen angeboten. Um die Akzeptanz der Maßnahmen sowie das Belastungserleben der TN zu erfassen, wurden aus der klinischen Routine erhobene Daten sowie retrospektiv eine schriftliche Befragung der TN in eine Behandlungsbeobachtung einbezogen.ErgebnisseVon 63 kontaktierten TN wurden die Daten von 45 TN eingeschlossen. Die Überbrückungsmaßnahmen wurden durchwegs positiv bewertet, wobei eine tendenziell höhere Zustimmung vonseiten der Angehörigen zu ermitteln war. Bei allen TN blieb das Belastungserleben stabil auf geringem Niveau; Angehörige waren signifikant stärker belastet.DiskussionDie Ergebnisse der vorliegenden Behandlungsbeobachtung sprechen für eine gut durchführbare und ortsunabhängige psychosoziale Behandlungsform im Rahmen demenzieller Erkrankungen. Diese kann sowohl als Überbrückungsmaßnahme für zukünftige pandemiebedingte Behandlungsausfälle als auch für die Routineversorgung (z. B. für mobilitätseingeschränkte oder im ländlichen Raum ohne direkte Klinikanbindung lebende Betroffene) geeignet sein. Daneben zeigt die Studie, wie notwendig es ist, für Angehörige ebenfalls Maßnahmen zu prüfen, um die Belastung zu reduzieren.Zusatzmaterial onlineZusätzliche Informationen sind in der Online-Version dieses Artikels (10.1007/s00391-022-02115-6) enthalten.

Prognostic value of left ventricular chamber stiffness and heart failure in patients with severe aortic stenosis undergoing aortic valve replacement

Abstract Background Increased left ventricular (LV) stiffness (LVStiffn) was shown to be associated with mortality in patients with severe aortic stenosis (AS), despite aortic valve replacement (AVR), and may contribute to future heart failure (HF) symptoms. The aim was to assess whether preoperative LVStiffn is a risk factor of HF in these patients. Methods A retrospective analysis was done in patients with severe AS who underwent AVR (93% surgical). LV end-diastolic pressure-volume relations (P=aVb) were reconstructed from LV end-diastolic volumes and estimated end-diastolic pressures (from E/e'); LVStiffn at 30 mmHg (CS30) and capacitance (V30) were then derived. Primary endpoint was development of symptomatic HF at >1 month post AVR. Results 1,837 patients were studied (age 76±10 years, 62% males, LVEF 61±12%; Table). Mean CS30 was 2.2±1.3 mmHg/mL and V30 64±17 mL/m2. Patients with higher CS30 ≥3 mmHg/mL were older, more frequently female, and had more comorbidities. During a median follow-up of 5.0 [3.0–7.9] years, 607 (33%) patients developed HF. A higher CS30 (≥3 mmHg/mL), but not V30 (P=0.32), was associated with higher risk of HF events (HR 1.86 [95% CI 1.52–2.27], P<0.0001), along with other clinical and echo predictors (Table). In multivariate analysis, adjusting for age, sex, comorbidities, advanced NYHA class III–IV, creatinine >1.5 mg/dL, medication use, severity of AS, reduced LVEF <50%, diastolic dysfunction grade ≥2, right ventricular size and pulmonary hypertension, a higher CS30 ≥3 mmHg/mL remained independently associated with HF events (adjusted HR 1.61 [1.29–2.01], P<0.0001; Figure). Conclusion Increased LVStiffn in patients with severe AS undergoing AVR is associated with HF at follow-up, despite the benefits brought by AVR, and can help identify patients with poorer outcomes who may need closer monitoring/more intensive treatment of comorbidities Funding Acknowledgement Type of funding sources: None.

Reduction in heart failure hospitalizations by sacubitril/valsartan; a post-hoc analysis of the PARALLAX trial

Abstract Background The PARALLAX trial recently showed a significant reduction in plasma N-terminal pro-B-type natriuretic peptide (NT-proBNP) concentrations by angiotensin receptor neprilysin inhibition with sacubitril/valsartan (S/V) compared to standard medical therapy (SMT) in patients with heart failure and ejection fraction ≥40%. As NT-proBNP reductions have been associated with a reduction in future heart failure hospitalizations (HHF), we aimed to investigate the impact of S/V on this endpoint in comparison to standard medical therapy. Methods The PARALLAX study was a 24-week, randomized, active-controlled, parallel group study to evaluate S/V compared to SMT for comorbidities. Eligible patients were stratified into three strata according to their individual RASi treatment (ACEi, ARB, ACEi/ARB-naïve) and randomized within each stratum 1:1 to S/V (N=1281; target dose (td), 97/103 mg b.i.d.) or individual comparator (N=1285; enalapril (td 10 mg b.i.d), valsartan (160 mg b.i.d.), or placebo). Hospitalizations for cardiac failure reported as serious adverse events by investigators were analysed in this post-oc secondary analysis. Results 2566 patients with heart failure and LVEF ≥40%, were randomized to receive either S/V or SMT according to RASi stratum (n=1,016 ACE inhibitor stratum, n=1,174 ARB stratum, n=326 no RAS stratum). After 12 weeks, adjusted geometric mean ratio of NT-proBNP showed a 16.4% greater reduction sith S/V vs. SMT (p<0.0001). S/V reduced the risk for cardiac failure events leading to hospitalization by 51% (hazard ratio (HR) 0.49; 95% CI 0.30, 0.81; p=0.005). Similar results were obtained in all three strata: HR 0.55 (0.25–1.19) in ACE inhibitor stratum, HR 0.50 (024–1.02) in ARB stratum and HR 0.37 (0.10–1.38) in no RAS stratum. Conclusion The significant reduction of NT-proBNP plasma levels by S/V in comparison to SMT in PARALLAX was associated with a significant reduction in heart failure hospitalisations. These results, together with evidence from the PARAGON trial, support the use of S/V in HFpEF for avoiding heart failure hospitalizations. Funding Acknowledgement Type of funding sources: Private company. Main funding source(s): Novartis

Breakdown Voltage Instability Mechanism on the Field Limiting Rings Edge Termination of Buried Layer Rectifier

In this article, an innovated buried layer rectifier (BLR) breakdown voltage (BV) instability has been tested and analyzed. Under the reverse current stress (RCS) condition, the BV read-out profiles show walk-in and walk-out phenomena. Based on the experimental results and surface traps theory, a sort of time-dependent degraded simulation is developed by TCAD tools, which is considered with hydrogen depassivation and diffusion process. In order to explore the inner mechanism, the dynamic electric parameters are analyzed during the degraded period. Due to the hole interface traps, the termination Si-SiO2 surface leakage current is deteriorated and the depletion boundary is shrunk, which reveal the BV values instability. Thus, the proposed physical model could clearly explain the whole process of degradation, while it fits BV and junction temperature curves to the experimental results identically. Furthermore, the investigated mechanism will be helpful to future device design and failure situations analysis.

Condition Monitoring of Power Electronic Systems Through Data Analysis of Measurement Signals and Control Output Variables

A major disadvantage of existing condition monitoring methods is the need for additional sensors and measuring equipment. In this work, this disadvantage is eliminated by completely avoiding additional hardware. Instead, software-based methods from the field of machine learning are used. Therefore, measurement signals and control output variables are utilized, which are acquired and processed in any power electronic system for the purpose of converter control. The publication focuses on two main converter components: power semiconductors and dc-link capacitor. For each component, the aging mechanisms that have been studied in the literature are explained. Based on the aging mechanisms, the degradation indicators are identified. Then, a converter model is built that allows the variation of degradation indicators in order to analyze their effects on the available dataset. These findings form the basis for mathematical models, which detects future failure mechanisms of this type during converter operation. The test setup must offer the possibility of generating reproducible failure cases in various components with the aid of additional failure equipment. Finally, failure mechanisms are intentionally introduced at the test bench in order to validate the methodology of the developed approach.

Sensitivity analysis applied to SiC failure probability in TRISO modeled with BISON

A sensitivity analysis on the failure probability of the Silicon Carbide (SiC) layer in tristructural isotropic (TRISO) nuclear fuel during transient conditions predicted by the BISON fuel performance code is performed. The principal goal of the analysis is to understand the most important parameters dictating SiC failure behavior in BISON during Reactivity Initiated Accidents (RIAs). SiC brittle fracture probability is modeled using Weibull statistics. A total of seven inputs related to SiC failure has been selected for the analysis, including the Weibull statistics parameters, elastic moduli for SiC and Pyrolitic Carbon (PyC) and SiC stress-free temperature. A 1D TRISO BISON model has been established for various reactivity insertions performed at the Nuclear Safety Research Reactor (NSRR). The principal advantage associated with the 1D TRISO model developed in this work is its computational efficiency. The Sobol variance decomposition method is used, and the sensitivity indices are presented for eight different values of the energy deposition. The results show that the two most important parameters impacting the predicted SiC failure probability are the Weibull modulus and the characteristic stress, and a co-variance amongst these parameters is obtained for low reactivity insertions. An additional new finding of this work is that the relative importance of Weibull parameters depends on the energy deposition, and thus reactivity, regime. For low energy depositions, two parameters are of influence on SiC failure probability, while for high energy depositions only one parameter impacts failure probability results. Moreover, optimization of the Weibull modulus and characteristic stress is performed by minimizing the RMSE between BISON failure probability predictions and experimental failure fractions for each energy deposition. This work also demonstrates the validity of the NSRR tests BISON simulations and of the respective sensitivity analysis results as conservative, yet indicative for slower transients characterized by lower deposited energies. Such verification is achieved through the partial extension of the analysis to a group Control Rod Withdrawal reproduced from a previous study. Another novel result of this analysis is that no single set of Weibull parameters can reproduce all reactivity insertion experimental failure results, which is related to the intrinsic nature of SiC failure properties, and a new range for the parameters is proposed to produce a failure probability envelope that encompasses the experimental fractions. Additionaly, this work proposes a new approach for future failure analysis with BISON, consisting in the use of Weibull parameters ranges, rather than fixed sets, along with failure envelopes generation.

Experimental investigation on static damage of concrete bridge under shear loading based on acoustic emission

This article presents techniques used to observe the shear behaviour of modified Z-shaped concrete specimens, experimental results, and a method proposed to classify the shear cracking pattern of a concrete bridge based on acoustic emission (AE). Z-shaped specimens under shear were designed with steel plate reinforcement. A finite element (FE) model for this specimen was developed to validate the concrete crack propagation. AE parameters, including the peak amplitude, counts, cumulative energy, average frequency (AF) and rise angle (RA), were found to successfully correlate with the observed cracking process in the specimens. A cluster analysis based on the K-means algorithm was proposed to automatically classify the AE signal into tensile and shear clusters. An existing bridge underwent reinforcement and then testing under two test scenarios. AE signals were detected at the web of the bridge under heavy truck loads or full random traffic flows. Using the proposed crack classification showed that the signals from the bridge belonged to shear crack clusters characterized by lower AE energy. Thus, this work developed an AE method to classify cracks in concrete shear tests and extended the method to classify the shear cracks in a bridge to provide an early warning of future failure.

The effectiveness of eHealth self-management interventions in patients with chronic heart failure: Protocol for a systematic review and meta-analysis.

PurposeThe objective of this paper is to design a protocol for a systematic review and meta-analysis on the effectiveness of self-management interventions in patients with chronic heart failure.MethodsThe protocol is developed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The protocol has been registered in PROSPERO (CRD42021246973). Base on the population, intervention, comparator, and outcome (PICO) framework, our research questions are: 1) What are the effects of eHealth self-management interventions on patients with chronic heart failure? 2) What factors of interventions might affect outcomes? The process includes: 1) search strategy and inclusion criteria; 2) data extraction; 3) risk of bias assessment and 4) data analysis. Searching process and data extraction will be guided by Cochrane Handbook for Systematic Reviews of Interventions. We will use Cochrane Risk of Bias tool to assess the risk of bias. The data analysis will be performed using Metafor package in R.ConclusionsThis systemic review will synthesize the current evidence and identify gaps. Findings in the meta-analysis will provide guidance for designing a more effective self-management intervention for patients with chronic heart failure in future.

Prioritization of Effective Lean Tools for Reliability Analysis & Maintenance Strategy

Asset or equipment reliability and availability have occupied extensive attention because of an emerging competitive environment and the overall operating and production cost. The main focus of this manuscript is to prioritize the lean tool and select an appropriate maintenance strategy for the repairable assets in the maintenance shop of the SIMGA1 shipyard. Five (5) assets of that maintenance shop such as an air compressor machine, 500-ton press machine, overhead crane machine, VDF lathe machine, and Roller machine were under breakdown maintenance. Due to the continuous degradation of those assets, attempts should be taken to enhance the reliability parameters by predicting upcoming failure events for each equipment or asset. QFD-AHP is a rapid tool in which quality function deployment is integrated with AHP to make an optimal selection. Firstly, the integrated QFD-AHP method is employed to prioritize the lean tools for that maintenance shop. 5S and KPI are the best fit for that shop among ten lean tools. Non Homogenous Poisson Process (NHPP) is a model which represents the no. of failure experienced up to time (t). NHPP and Weibull analysis are utilized to predict future failure events and analyzed the nature of the failure accordingly. From the results of the Weibull analysis and NHPP analysis, it is shown that the slope (β) of the failure rate is greater than 1 for all assets. Overhead crane m/c and 500-ton press m/c are the most critical m/c according to equipment criticality analysis. Finally, a decision diagram is utilized to extract the most congruent maintenance strategies based on the reliability parameter of five (5) assets. The approach employed in this study helps maintenance practitioners to achieve lean maintenance.

Predicting future failure times by using quantile regression

The purpose of the paper is to study how to predict the future failure times in a sample from the early failures (type II censored data). We consider both the case of independent and dependent lifetimes. In both cases we assume identically distributed random variables. To predict the future failures we use quantile regression techniques that also provide prediction regions for them. Some illustrative examples show how to apply the theoretical results to simulated and real data sets.

Concentration Dependent Feeding on Imidacloprid by Behaviorally Resistant House Flies, Musca domestica L. (Diptera: Muscidae).

The house fly (Musca domestica L.) is a cosmopolitan and synanthropic pest fly commonly associated with confined animal facilities, known to mechanically vector numerous disease-causing pathogens. Control of adult house flies often relies on insecticides formulated into insecticidal baits, though many baits have failed due to insecticide resistance. House fly resistance to imidacloprid, the most widely used neonicotinoid insecticide available for fly control, has evolved through physiological and behavioral mechanisms in field populations. Behavioral resistance to imidacloprid was documented in field populations of flies from southern California dairies. Lab colonies of these flies were established and behavioral resistance to imidacloprid was selected over several generations. The current study examined the ability of these lab-selected flies to feed on varying concentrations of imidacloprid formulated in sucrose, and if these flies would demonstrate a feeding preference for different concentrations of imidacloprid when exposed in bioassays. Behaviorally resistant flies preferred to feed on untreated sucrose as opposed to treated sucrose at concentrations greater than 25 µg/g imidacloprid when provided sucrose treated with and without imidacloprid. When provisioned with only sucrose treated with a low and high imidacloprid concentration, flies fed on the low concentrations (≤100 µg/g) imidacloprid but reduced feeding on either treatment when concentrations were >100 µg/g imidacloprid. The current study extends the body of knowledge on house fly behavioral resistance to imidacloprid, which could provide insights into future failures of granular fly baits.

Assessment of the variation of failure probability of upgraded rubble-mound breakwaters due to climate change

The effects of climate change on coastal areas are expected to significantly influence the risk for port operations. In the present work, a novel methodology for the quantitative assessment of the performances of upgraded rubble-mound breakwaters under a changing climate is proposed. For each considered upgrading option, the failure probability related to a certain limit state is calculated through the implementation of Monte Carlo (MC) simulations, using the factor of change (FoC) method to include the projected future climate. Three indexes are defined for the immediate and intuitive interpretation of the results: i) the ratio between the calculated and the maximum acceptable failure probability during lifetime (r); ii) the rate of the growth of the failure probability during lifetime (s); iii) the coefficient of variation of the failure probability due to both the intrinsic uncertainty of the MC simulation and the variability of future climate (v). The methodology was applied to the case study of the Catania harbor breakwater, considering the failure of different upgrading solutions due to the collapse of the outer armor layer and to excessive mean overtopping discharge. The results revealed the acceptability of the structural and hydraulic performances of all the tested configurations, under both present and future climate. Moreover, a high climate-related variability of the future failure probability was found. The usefulness of the proposed indexes for designer and decision-makers was also demonstrated. In particular, r gives direct information about the acceptability of the structure performances, enabling the immediate comparison between different configurations and climate scenarios. The index s is fundamental to calculate the appropriate times to implement repair interventions during the structure lifetime. Finally, v allows the identification of those situations which requires the design of highly flexible maintenance plans, able to adapt to a very variable climate avoiding excessive costs.

Discussion of signature‐based models of preventive maintenance

Discussion of signature‐based models of preventive maintenance

ELFpm: A machine learning framework for industrial machines prediction of remaining useful life

The topic of predictive maintenance has great relevance in the search for the rationalization and efficiency of the industrial plants in the context of Industry 4.0. Monitoring equipment parameters and identifying behavior changes that recognize a future failure allows for anticipation of maintenance while avoiding unnecessary preventive maintenance. There are numerous studies in the literature towards the prediction of the maintenance needs of various types of equipment. However, a piece of equipment may have different behavior depending on the conditions of use or the operating environment. Thus, tools to adjust prediction algorithms to new environments are necessary. This article proposes a framework called ELFpm, designed to predict equipment failures, regardless of location or condition of use. This framework introduces an ontology to store the statistics generated by the prediction algorithms and propose a novel suitability index that selects the appropriate prediction algorithm considering the current status of the equipment. The evaluation of ELFpm considers an engine failure scenario. Results show that ELFpm can predict failures up to three hours before they occur.

Inference for constant stress accelerated life test under the proportional reverse hazards lifetime distribution

AbstractIn this paper, we consider small sample statistical inference methods for the constant stress accelerated life test (CSALT) under the proportional reverse hazards family (PRHF). The model parameters are assumed to be the exponential functions of the stress. The generalized confidence intervals (GCIs) are derived for the model parameters and some commonly used reliability metrics such as the quantile and the reliability function of the lifetime at the designed stress level. The generalized prediction interval (GPI) is also proposed for the future failure time (FFT) and the remaining useful life (RUL) at the designed stress level. The Monte Carlo simulation study for the generalized Lindley distribution (GLD) and the inverse Weibull distribution are used to illustrate the performance of the proposed GCIs and GPI. The simulation results indicate that the performance of the proposed GCIs and GPI is better than the Wald confidence intervals (CIs) and bootstrap‐p CIs in terms of the coverage probability (CP). Finally, a real example is used to illustrate the developed procedures.

Analysis of early molecular response at 3 months in predicting overall response in newly diagnosed patients with chronic myeloid leukemia on imatinib

Objectives: This study aimed to study the correlation between Breakpoint Cluster Region- ABelson Leukemia virus 1 transcript levels at 3 months with the treatment responses at 6 and 12 months in patients on imatinib. Around 30% of patients with chronic myeloid leukemia (CML) might have treatment failure with the first-line tyrosine kinase inhibitors (TKI). Patients with a “warning response” at 3 months can continue therapy with the same TKI while monitoring for disease progression. However, newer pieces of evidence suggest that patients who fail treatment with imatinib do have suboptimal responses in the early time points, and hence, 1st 3-month assessment might be a useful indicator for future treatment failure. Material and Methods: It is a single-center prospective observational study involving 60 treatment-naive consecutive patients with CML-chronic phase who attended Hematology Outpatient Department at IHTM, Kolkata. Treatment responses were assessed by cytogenetics and BCR-ABL1 transcript levels by real-time quantitative polymerase chain reaction at 3 monthly time points. Results: About 51% and 70.2% of the study participants achieved complete cytogenetic response at 6 and 12 months, respectively. About 74% of the participants had achieved early molecular response (EMR) at 3 months. The failure rates of cytogenetic responses were 13% and 20% at 6 and 12 months, respectively. Patients who failed to achieve EMR at 3 months had higher failure rates at 6 months. The major, warning and failure of molecular responses at 6 and 12 months were found to be 15%, 25%, and 9%, and 34%, 39%, and 27%, respectively. The analyses showed that patients who failed to achieve EMR at 3 months are also more likely to have the failure of molecular response at 12 months, with a statistical significance of P < 0.01. Failure of EMR at 3 months also correlated with failure of overall responses (both cytogenetic and molecular at 12 months) with a statistical significance of P = 0.006. When followed up, there was a progression of disease in three including a death in the suboptimal response group. Conclusion: Our patients had inferior treatment responses to imatinib than that observed in the previous studies. The majority have baseline fibrosis of the marrow and splenomegaly at presentation which might contribute to adverse outcomes. The molecular response at 3 months was found to be a consistent and powerful indicator of treatment responses at later time points.

Ross Operation in Pediatric Population: Impact of the Surgical Timing and the Native Pulmonary Diameter on the Outcome.

Aortic valve replacement early in life may be inevitable. Ross operation, until present day, remains the favorite surgical option in pediatrics with irreparable aortic valve disease. Nonetheless, the necessity for re-operation was always its principal limitation due to aortic valve failure or homograft degeneration. We present our 25years of experience in the pediatric population. From August 1994 until June 2018, 157 children below 18years underwent the Ross operation. This retrospective review aims at assessing the long-term outcomes, as well as the risk factors for re-operation after Ross procedure. Median age was 10.9years, of which seven patients were infants, 79 children, and 71 adolescents. The median follow-up time was 14years. Hospital mortality was 0.6%. Freedom from autograft re-operation for children was 96.7% and 94.1% at 10 and 20years, respectively; whereas for adolescents, it was 92.6% and 74.9% at 10 and 20years. For children, freedom from homograft re-operation was 92.5%, 83.5%, and 56.2% at 10, 15, and 20years; while for adolescents, it was 96.8%, 91.8%, and 86.7% at 10, 15, and 20years. Homograft size (p = 0.008) and childhood (p = 0.05) were risk factors for homograft re-operation. Pulmonary valve diameter > 24mm (p = 0.044) and adolescence (p = 0.032) were risk factors for autograft re-operation. Our experience demonstrated excellent early and late survival. While children have preferential outcomes concerning autograft re-operation, those who received a smaller homograft had a higher right-sided re-intervention incidence than adolescents. Pulmonary diameter > 24mm at surgery was an indicator of future autograft failure.