Development of a deep learning model that predicts critical events of pediatric patients admitted to general wards.

Early detection of deteriorating patients is important to prevent life-threatening events and improve clinical outcomes. Efforts have been made to detect or prevent major events such as cardiopulmonary resuscitation, but previously developed tools are often complicated and time-consuming, rendering them impractical. To overcome this problem, we designed this study to create a deep learning prediction model that predicts critical events with simplified variables. This retrospective observational study included patients under the age of 18 who were admitted to the general ward of a tertiary children's hospital between 2020 and 2022. A critical event was defined as cardiopulmonary resuscitation, unplanned transfer to the intensive care unit, or mortality. The vital signs measured during hospitalization, their measurement intervals, sex, and age were used to train a critical event prediction model. Age-specific z-scores were used to normalize the variability of the normal range by age. The entire dataset was classified into a training dataset and a test dataset at an 8:2 ratio, and model learning and testing were performed on each dataset. The predictive performance of the developed model showed excellent results, with an area under the receiver operating characteristics curve of 0.986 and an area under the precision-recall curve of 0.896. We developed a deep learning model with outstanding predictive power using simplified variables to effectively predict critical events while reducing the workload of medical staff. Nevertheless, because this was a single-center trial, no external validation was carried out, prompting further investigation.

Development of a model to predict vancomycin serum concentration during continuous infusion of vancomycin in critically ill pediatric patients.

Vancomycin is a frequently used antibiotic in intensive care units, and the patient's renal clearance affects the pharmacokinetic characteristics of vancomycin. Several advantages have been reported for vancomycin continuous intravenous infusion, but studies on continuous dosing regimens based on patients' renal clearance are insufficient. The aim of this study was to develop a vancomycin serum concentration prediction model by factoring in a patient's renal clearance. Children admitted to our institution between July 1, 2021, and July 31, 2022 with records of continuous infusion of vancomycin were included in the study. Sex, age, height, weight, vancomycin dose by weight, interval from the start of vancomycin administration to the time of therapeutic drug monitoring sampling, and vancomycin serum concentrations were analyzed with the linear regression analysis of the mixed effect model. Univariable regression analysis was performed using the vancomycin serum concentration as a dependent variable. It showed that vancomycin dose (p < 0.001) and serum creatinine (p = 0.007) were factors that had the most impact on vancomycin serum concentration. Vancomycin serum concentration was affected by vancomycin dose (p < 0.001) and serum creatinine (p = 0.001) with statistical significance, and a multivariable regression model was obtained as follows: Vancomycin serum concentration (mg/l) = -1.296 + 0.281 × vancomycin dose (mg/kg) + 20.458 × serum creatinine (mg/dl) (adjusted coefficient of determination, R2 = 0.66). This prediction model is expected to contribute to establishing an optimal continuous infusion regimen for vancomycin.

Wigner-molecularization-enabled dynamic nuclear polarization.

Multielectron semiconductor quantum dots (QDs) provide a novel platform to study the Coulomb interaction-driven, spatially localized electron states of Wigner molecules (WMs). Although Wigner-molecularization has been confirmed by real-space imaging and coherent spectroscopy, the open system dynamics of the strongly correlated states with the environment are not yet well understood. Here, we demonstrate efficient control of spin transfer between an artificial three-electron WM and the nuclear environment in a GaAs double QD. A Landau-Zener sweep-based polarization sequence and low-lying anticrossings of spin multiplet states enabled by Wigner-molecularization are utilized. Combined with coherent control of spin states, we achieve control of magnitude, polarity, and site dependence of the nuclear field. We demonstrate that the same level of control cannot be achieved in the non-interacting regime. Thus, we confirm the spin structure of a WM, paving the way for active control of correlated electron states for application in mesoscopic environment engineering.

Prognostic impact of total body irradiation dose in pediatric acute lymphoblastic leukemia patients treated with allogeneic hematopoietic stem cell transplantation in second complete remission.

Background: Allogeneic HSCT may improve survival in pediatric ALL patients who relapse. In this study, we analyzed the outcome and prognostic factors of 62 ALL patients (35 male, 56.5%) who received allogeneic HSCT in second complete remission (CR) at our institution between April 1st 2009 and December 31st 2019. Methods: The median time from diagnosis to relapse was 35.1 months (range, 6.0‒113.6 mo). Fifty-three patients (85.5%) experienced bone marrow relapse only. The number of patients who received transplant according to each donor type was as follows: HLA matched family donor 17 (27.4%), matched unrelated donor (UD) 22 (35.5%), mismatched donor 23 (37.1%). All patients received HSCT with a myeloablative conditioning, 58 patients (93.5%) with the incorporation of TBI [31 patients 12 Gray (Gy), 24 patients 13.2 Gy, 3 patients 8 Gy]. Results: The 5-year event-free survival (EFS), and overall survival of the study group was 41.3±6.3% (26/62), and 42.3±6.6% (27/62), respectively. The cumulative incidence of relapse and transplant-related mortality was 57.1±6.4% and 1.6±1.6%, respectively. Infant ALL, shorter time from diagnosis to relapse, and TBI dose of 12 Gy, rather than 13.2 Gy, resulted in significantly worse EFS. In multivariate analysis, infant ALL and TBI dose of 12 Gy during conditioning predicted significantly lower EFS. Conclusion: In our study group, treatment with a higher dose of TBI during conditioning resulted in better EFS for ALL patients who underwent HSCT in second CR. Further study is needed to determine potential long-term complications associated with a higher TBI dose.

Approaching Ideal Visibility in Singlet-Triplet Qubit Operations Using Energy-Selective Tunneling-Based Hamiltonian Estimation.

We report energy-selective tunneling readout-based Hamiltonian parameter estimation of a two-electron spin qubit in a GaAs quantum dot array. Optimization of readout fidelity enables a single-shot measurement time of 16 µs on average, with adaptive initialization and efficient qubit frequency estimation based on real-time Bayesian inference. For qubit operation in a frequency heralded mode, we observe a 40-fold increase in coherence time without resorting to dynamic nuclear polarization. We also demonstrate active frequency feedback with quantum oscillation visibility, single-shot measurement fidelity, and gate fidelity of 97.7%, 99%, and 99.6%, respectively, showcasing the improvements in the overall capabilities of GaAs-based spin qubits. By pushing the sensitivity of the energy-selective tunneling-based spin to charge conversion to the limit, the technique is useful for advanced quantum control protocols such as error mitigation schemes, where fast qubit parameter calibration with a large signal-to-noise ratio is crucial.

Single-Shot Readout of a Driven Hybrid Qubit in a GaAs Double Quantum Dot.

We report a single-shot-based projective readout of a semiconductor hybrid qubit formed by three electrons in a GaAs double quantum dot. Voltage-controlled adiabatic transitions between the qubit operations and readout conditions allow high-fidelity mapping of quantum states. We show that a large ratio both in relaxation time vs tunneling time (≈50) and singlet-triplet splitting vs thermal energy (≈20) allows energy-selective tunneling-based spin-to-charge conversion with a readout visibility of ≈92.6%. Combined with ac driving, we demonstrate high visibility coherent Rabi and Ramsey oscillations of a hybrid qubit in GaAs. Further, we discuss the generality of the method for use in other materials, including silicon.