Predictive analytics for cardiovascular patient readmission and mortality: An explainable approach

Background: Cardiovascular patients experience high rates of adverse outcomes following discharge from hospital, which may be preventable through early identification and targeted action. This study aimed to investigate the effectiveness and explainability of machine learning algorithms in predicting unplanned readmission and death in cardiovascular patients at 30 days and 180 days from discharge. Methods: Gradient boosting machines were trained and evaluated using data from hospital electronic medical records linked to hospital administrative and mortality data for 39,255 patients admitted to four hospitals in New South Wales, Australia between 2017 and 2021. Sociodemographic variables, admission history, and clinical information were used as potential predictors. The performance was compared to LASSO regression, as well as the HOSPITAL and LACE risk score indices. Important risk factors identified by the gradient-boosting machine model were explored using Shapley values. Results: The models performed well, especially for the mortality outcomes. Area under the receiver operating characteristic curve values were 0.70 for readmission and 0.87–0.90 for mortality using the full gradient boosting machine algorithms. Among the top predictors for 30-day and 180-day readmission were increased red cell distribution width, old age (especially above 80 years), high measured troponin and urea levels, not being married or in a relationship, and low albumin levels. For mortality, these included increased red cell distribution width, old age (especially older than 70 years), high measured troponin and urea levels, high neutrophil and monocyte counts, and low eosinophil and lymphocyte counts. The Shapley values gave clear insight into the dynamics of decision-tree-based models. Conclusions: We demonstrated an explainable predictive algorithm to identify cardiovascular patients who are at high risk of readmission or death at discharge from the hospital and identified key risk factors

Whole lifespan microscopic observation of budding yeast aging through a microfluidic dissection platform

Important insights into aging have been generated with the genetically tractable and short-lived budding yeast. However, it is still impossible today to continuously track cells by high-resolution microscopic imaging (e.g., fluorescent imaging) throughout their entire lifespan. Instead, the field still needs to rely on a 50-y-old laborious and time-consuming method to assess the lifespan of yeast cells and to isolate differentially aged cells for microscopic snapshots via manual dissection of daughter cells from the larger mother cell. Here, we are unique in achieving continuous and high-resolution microscopic imaging of the entire replicative lifespan of single yeast cells. Our microfluidic dissection platform features an optically prealigned single focal plane and an integrated array of soft elastomer-based micropads, used together to allow for trapping of mother cells, removal of daughter cells, monitoring gradual changes in aging, and unprecedented microscopic imaging of the whole aging process. Using the platform, we found remarkable age-associated changes in phenotypes (e.g., that cells can show strikingly differential cell and vacuole morphologies at the moment of their deaths), indicating substantial heterogeneity in cell aging and death. We envision the microfluidic dissection platform to become a major tool in aging research.

Measurement of mechanical vibrations excited in aluminium resonators by 0.6 GeV electrons

We present measurements of mechanical vibrations induced by 0.6 GeV electrons impinging on cylindrical and spherical aluminium resonators. To monitor the amplitude of the resonator's vibrational modes we used piezoelectric ceramic sensors, calibrated by standard accelerometers. Calculations using the thermo-acoustic conversion model, agree well with the experimental data, as demonstrated by the specific variation of the excitation strengths with the absorbed energy, and with the traversing particles' track positions. For the first longitudinal mode of the cylindrical resonator we measured a conversion factor of 7.4 +- 1.4 nm/J, confirming the model value of 10 nm/J. Also, for the spherical resonator, we found the model values for the L=2 and L=1 mode amplitudes to be consistent with our measurement. We thus have confirmed the applicability of the model, and we note that calculations based on the model have shown that next generation resonant mass gravitational wave detectors can only be expected to reach their intended ultra high sensitivity if they will be shielded by an appreciable amount of rock, where a veto detector can reduce the background of remaining impinging cosmic rays effectively.Comment: Tex-Article with epsfile, 34 pages including 13 figures and 5 tables. To be published in Rev. Scient. Instr., May 200

Respiratory muscle activity and patient-ventilator asynchrony during different settings of noninvasive ventilation in stable hypercapnic COPD:Does high inspiratory pressure lead to respiratory muscle unloading?

Introduction: High-intensity noninvasive ventilation (NIV) has been shown to improve outcomes in stable chronic obstructive pulmonary disease patients. However, there is insufficient knowledge about whether with this more controlled ventilatory mode optimal respiratory muscle unloading is provided without an increase in patient-ventilator asynchrony (PVA). Patients and methods: Ten chronic obstructive pulmonary disease patients on home mechanical ventilation were included. Four different ventilatory settings were investigated in each patient in random order, each for 15 min, varying the inspiratory positive airway pressure and backup breathing frequency. With surface electromyography (EMG), activities of the intercostal muscles, diaphragm, and scalene muscles were determined. Furthermore, pressure tracings were derived simultaneously in order to assess PVA. Results: Compared to spontaneous breathing, the most pronounced decrease in EMG activity was achieved with the high-pressure settings. Adding a high breathing frequency did reduce EMG activity per breath, while the decrease in EMG activity over 1 min was comparable with the high-pressure, low-frequency setting. With high backup breathing frequencies less breaths were pressure supported (25% vs 97%). PVAs occurred more frequently with the low-frequency settings (P=0.017). Conclusion: High-intensity NIV might provide optimal unloading of respiratory muscles, without undue increases in PVA

Nuclear structure studies with the 7Li(e,e'p) reaction

Experimental momentum distributions for the transitions to the ground state and first excited state of 6He have been measured via the reaction 7Li(e,e'p)6He, in the missing momentum range from -70 to 260 MeV/c. They are compared to theoretical distributions calculated with mean-field wave functions and with variational Monte Carlo (VMC) wave functions which include strong state-dependent correlations in both 7Li and 6He. These VMC calculations provide a parameter-free prediction of the momentum distribution that reproduces the measured data, including its normalization. The deduced summed spectroscopic factor for the two transitions is 0.58 +/- 0.05, in perfect agreement with the VMC value of 0.60. This is the first successful comparison of experiment and ab initio theory for spectroscopic factors in p-shell nuclei.Comment: 4 pages, 3 figure