Computational Evidence for Laboratory Diagnostic Pathways: Extracting Predictive Analytes for Myocardial Ischemia from Routine Hospital Data

Background: Laboratory parameters are critical parts of many diagnostic pathways, mortality scores, patient follow-ups, and overall patient care, and should therefore have underlying standardized, evidence-based recommendations. Currently, laboratory parameters and their significance are treated differently depending on expert opinions, clinical environment, and varying hospital guidelines. In our study, we aimed to demonstrate the capability of a set of algorithms to identify predictive analytes for a specific diagnosis. As an illustration of our proposed methodology, we examined the analytes associated with myocardial ischemia; it was a well-researched diagnosis and provides a substrate for comparison. We intend to present a toolset that will boost the evolution of evidence-based laboratory diagnostics and, therefore, improve patient care. Methods: The data we used consisted of preexisting, anonymized recordings from the emergency ward involving all patient cases with a measured value for troponin T. We used multiple imputation technique, orthogonal data augmentation, and Bayesian Model Averaging to create predictive models for myocardial ischemia. Each model incorporated different analytes as cofactors. In examining these models further, we could then conclude the predictive importance of each analyte in question. Results: The used algorithms extracted troponin T as a highly predictive analyte for myocardial ischemia. As this is a known relationship, we saw the predictive importance of troponin T as a proof of concept, suggesting a functioning method. Additionally, we could demonstrate the algorithm’s capabilities to extract known risk factors of myocardial ischemia from the data. Conclusion: In this pilot study, we chose an assembly of algorithms to analyze the value of analytes in predicting myocardial ischemia. By providing reliable correlations between the analytes and the diagnosis of myocardial ischemia, we demonstrated the possibilities to create unbiased computational-based guidelines for laboratory diagnostics by using computational power in today’s era of digitalization

Data-driven reduction of dendritic morphologies with preserved dendro-somatic responses

Dendrites shape information flow in neurons. Yet, there is little consensus on the level of spatial complexity at which they operate. Through carefully chosen parameter fits, solvable in the least-squares sense, we obtain accurate reduced compartmental models at any level of complexity. We show that (back-propagating) action potentials, Ca2+ spikes, and N-methyl-D-aspartate spikes can all be reproduced with few compartments. We also investigate whether afferent spatial connectivity motifs admit simplification by ablating targeted branches and grouping affected synapses onto the next proximal dendrite. We find that voltage in the remaining branches is reproduced if temporal conductance fluctuations stay below a limit that depends on the average difference in input resistance between the ablated branches and the next proximal dendrite. Furthermore, our methodology fits reduced models directly from experimental data, without requiring morphological reconstructions. We provide software that automatizes the simplification, eliminating a common hurdle toward including dendritic computations in network models

Extending outbreak investigation with machine learning and graph theory: Benefits of new tools with application to a nosocomial outbreak of a multidrug-resistant organism.

OBJECTIVE From January 1, 2018, until July 31, 2020, our hospital network experienced an outbreak of vancomycin-resistant enterococci (VRE). The goal of our study was to improve existing processes by applying machine-learning and graph-theoretical methods to a nosocomial outbreak investigation. METHODS We assembled medical records generated during the first 2 years of the outbreak period (January 2018 through December 2019). We identified risk factors for VRE colonization using standard statistical methods, and we extended these with a decision-tree machine-learning approach. We then elicited possible transmission pathways by detecting commonalities between VRE cases using a graph theoretical network analysis approach. RESULTS We compared 560 VRE patients to 86,684 controls. Logistic models revealed predictors of VRE colonization as age (aOR, 1.4 (per 10 years), with 95% confidence interval [CI], 1.3-1.5; P < .001), ICU admission during stay (aOR, 1.5; 95% CI, 1.2-1.9; P < .001), Charlson comorbidity score (aOR, 1.1; 95% CI, 1.1-1.2; P < .001), the number of different prescribed antibiotics (aOR, 1.6; 95% CI, 1.5-1.7; P < .001), and the number of rooms the patient stayed in during their hospitalization(s) (aOR, 1.1; 95% CI, 1.1-1.2; P < .001). The decision-tree machine-learning method confirmed these findings. Graph network analysis established 3 main pathways by which the VRE cases were connected: healthcare personnel, medical devices, and patient rooms. CONCLUSIONS We identified risk factors for being a VRE carrier, along with 3 important links with VRE (healthcare personnel, medical devices, patient rooms). Data science is likely to provide a better understanding of outbreaks, but interpretations require data maturity, and potential confounding factors must be considered

Integrated trajectories of the maternal metabolome, proteome, and immunome predict labor onset

Estimating the time of delivery is of high clinical importance because pre- and postterm deviations are associated with complications for the mother and her offspring. However, current estimations are inaccurate. As pregnancy progresses toward labor, major transitions occur in fetomaternal immune, metabolic, and endocrine systems that culminate in birth. The comprehensive characterization of maternal biology that precedes labor is key to understanding these physiological transitions and identifying predictive biomarkers of delivery. Here, a longitudinal study was conducted in 63 women who went into labor spontaneously. More than 7000 plasma analytes and peripheral immune cell responses were analyzed using untargeted mass spectrometry, aptamer-based proteomic technology, and single-cell mass cytometry in serial blood samples collected during the last 100 days of pregnancy. The high-dimensional dataset was integrated into a multiomic model that predicted the time to spontaneous labor [R = 0.85, 95% confidence interval (CI) [0.79 to 0.89], P = 1.2 × 10−40, N = 53, training set; R = 0.81, 95% CI [0.61 to 0.91], P = 3.9 × 10−7, N = 10, independent test set]. Coordinated alterations in maternal metabolome, proteome, and immunome marked a molecular shift from pregnancy maintenance to prelabor biology 2 to 4 weeks before delivery. A surge in steroid hormone metabolites and interleukin-1 receptor type 4 that preceded labor coincided with a switch from immune activation to regulation of inflammatory responses. Our study lays the groundwork for developing blood-based methods for predicting the day of labor, anchored in mechanisms shared in preterm and term pregnancies

Vocal Culture in the Age of Laryngoscopy

For several months beginning in 1884, readers of Life, Science, Health, the Atlantic Monthly and similar magazines would have encountered half-page advertisements for a newly patented medical device called the ‘ammoniaphone’ (Figure 2.1). Invented and promoted by a Scottish doctor named Carter Moffat and endorsed by the soprano Adelina Patti, British Prime Minister William Gladstone and the Princess of Wales, the ammoniaphone promised a miraculous transformation in the voices of its users. It was recommended for ‘vocalists, clergymen, public speakers, parliamentary men, readers, reciters, lecturers, leaders of psalmody, schoolmasters, amateurs, church choirs, barristers, and all persons who have to use their voices professionally, or who desire to greatly improve their speaking or singing tones’. Some estimates indicated that Moffat sold upwards of 30,000 units, yet the ammoniaphone was a flash in the pan as far as such things go, fading from public view after 1886

Opera and Hypnosis: Victor Maurel’s Experiments with Verdi’s Otello

One day in his private home on the avenue Bugeaud, in Paris’s sixteenth arrondissement, the famous baritone Victor Maurel hosted a meeting which combined music with hypnotism of a young woman

Unsound Seeds

With this image of a curtain hiding and at the same time heightening some terrible secret, Max Kalbeck began his review of the first Viennese performance of Richard Strauss’s Salome. Theodor W. Adorno picked up the image of the curtain in the context of Strauss’s fabled skill at composing non-musical events, when he identified the opening flourish of Strauss’s Salome as the swooshing sound of the rising curtain. If this is so, the succès de scandale of the opera was achieved, in more than one sense, as soon as the curtain rose at Dresden’s Semperoper on 10 December 1905. Critics of the premiere noted that the opera set ‘boundless wildness and degeneration to music’; it brought ‘high decadence’ onto the operatic stage; a ‘composition of hysteria’, reflecting the ‘disease of our time’, Salome is ‘hardly music any more’.The outrage did not end there

Science, Technology and Love in Late Eighteenth-Century Opera

It is a tale told by countless operas: young love, thwarted by an old man’s financially motivated marriage plans, triumphs in the end thanks to a deception that tricks the old man into blessing the young lovers’ union. Always a doddering fool, the old man is often also an enthusiast for knowledge. Such is the case, for instance, in Carlo Goldoni’s comic opera libretto Il mondo della luna (1750), in which Buonafede’s interest in the moon opens him to an elaborate hoax that has him believe he and his daughters have left Earth for the lunar world; and also in the Singspiel Die Luftbälle, oder der Liebhaber à la Montgolfier (1788), wherein the apothecary Wurm trades Sophie, the ward he intended to marry himself, for a technological innovation that will make him a pioneering aeronaut

Operatic Fantasies in Early Nineteenth-Century Psychiatry

In his celebrated essay on insanity in the Dictionnaire des sciences médicales (1816), French psychiatrist Étienne Esquirol marvelled at the earlier custom of allowing asylum inmates to attend theatrical productions at Charenton