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The exact pathophysiology of contrast-induced nephropathy (CIN) is not fully clarified, yet the osmotic characteristics of contrast media (CM) have been a significant focus in many investigations of CIN. Osmotic effects of CM specific to the kidney include transient decreases in blood flow, filtration fraction, and glomerular filtration rate. Potentially significant secondary effects include an osmotically induced diuresis with a concomitant dehydrating effect. Clinical experiences that have compared the occurrence of CIN between the various classes of CM based on osmolality have suggested a much less than anticipated advantage, if any, with a lower osmolality. Recent animal experiments actually suggest that induction of a mild osmotic diuresis in association with iso-osmolar agents tends to offset potentially deleterious renal effects of high viscosity-mediated intratubular CM stagnation.
Purpose: The management of patients with suspected appendicitis remains a challenge in daily clinical practice, and the optimal management algorithm is still being debated. Negative appendectomy rates (NAR) continue to range between 10 and 15%. This prospective study evaluated the accuracy of a diagnostic pathway in acute appendicitis using clinical risk stratification (Alvarado score), routine ultrasonography, gynecology consult for females, and selected CT after clinical reassessment.
Methods: Patients presenting with suspected appendicitis between November 2015 and September 2017 from age 18 years and above were included. Decision-making followed a clear management pathway. Patients were followed up for 6 months after discharge. The hypothesis was that the algorithm can reduce the NAR to a value of under 10%.
Results: A total of 183 patients were included. In 65 of 69 appendectomies, acute appendicitis was confirmed by histopathology, corresponding to a NAR of 5.8%. Notably, all 4 NAR appendectomies had other pathologies of the appendix. The perforation rate was 24.6%. Only 36 patients (19.7%) received a CT scan. The follow-up rate after 30 days achieved 69%, including no patients with missed appendicitis. The sensitivity and specificity of the diagnostic pathway was 100% and 96.6%, respectively. The potential saving in costs can be as much as 19.8 million €/100,000 cases presenting with the suspicion of appendicitis.
Conclusion: The risk-stratified diagnostic algorithm yields a high diagnostic accuracy for patients with suspicion of appendicitis. Its implementation can safely reduce the NAR, simultaneously minimizing the use of CT scans and optimizing healthcare-related costs in the treatment of acute appendicitis.
We show that financial advisors recommend more costly products to female clients, based on minutes from about 27,000 real-world advisory meetings and client portfolio data. Funds recommended to women have higher expense ratios controlling for risk, and women less often receive rebates on upfront fees for any given fund. We develop a model relating these findings to client stereotyping, and empirically verify an additional prediction: Women (but not men) with higher financial aptitude reject recommendations more frequently. Women state a preference for delegating financial decisions, but appear unaware of associated higher costs. Evidence of stereotyping is stronger for male advisors.
DNA methylation-based prediction of response to immune checkpoint inhibition in metastatic melanoma
(2021)
Background: Therapies based on targeting immune checkpoints have revolutionized the treatment of metastatic melanoma in recent years. Still, biomarkers predicting long-term therapy responses are lacking. Methods: A novel approach of reference-free deconvolution of large-scale DNA methylation data enabled us to develop a machine learning classifier based on CpG sites, specific for latent methylation components (LMC), that allowed for patient allocation to prognostic clusters. DNA methylation data were processed using reference-free analyses (MeDeCom) and reference-based computational tumor deconvolution (MethylCIBERSORT, LUMP). Results: We provide evidence that DNA methylation signatures of tumor tissue from cutaneous metastases are predictive for therapy response to immune checkpoint inhibition in patients with stage IV metastatic melanoma. Conclusions: These results demonstrate that LMC-based segregation of large-scale DNA methylation data is a promising tool for classifier development and treatment response estimation in cancer patients under targeted immunotherapy.
Background: Computed tomography (CT) low-dose (LD) imaging is used to lower radiation exposure, especially in vascular imaging; in current literature, this is mostly on latest generation high-end CT systems.
Purpose: To evaluate the effects of reduced tube current on objective and subjective image quality of a 15-year-old 16-slice CT system for pulmonary angiography (CTPA).
Material and Methods: CTPA scans from 60 prospectively randomized patients (28 men, 32 women) were examined in this study on a 15-year-old 16-slice CT scanner system. Standard CT (SD) settings were 100 kV and 150 mAs, LD settings were 100 kV and 50 mAs. Attenuation of the pulmonary trunk, various anatomic landmarks, and image noise were quantitatively measured; contrast-to-noise ratios (CNR) and signal-to-noise ratios (SNR) were calculated. Three independent blinded radiologists subjectively rated each image series using a 5-point grading scale.
Results: CT dose index (CTDI) in the LD series was 66.46% lower compared to the SD settings (2.49 ± 0.55 mGy versus 7.42 ± 1.17 mGy). Attenuation of the pulmonary trunk showed similar results for both series (SD 409.55 ± 91.04 HU; LD 380.43 HU ± 93.11 HU; P = 0.768). Subjective image analysis showed no significant differences between SD and LD settings regarding the suitability for detection of central and peripheral PE (central SD/LD, 4.88; intra-class correlation coefficients [ICC], 0.894/4.83; ICC, 0.745; peripheral SD/LD, 4.70; ICC, 0.943/4.57; ICC, 0.919; all P > 0.4).
Conclusion: The LD protocol, on a 15-year-old CT scanner system without current high-end hardware or post-processing tools, led to a dose reduction of approximately 67% with similar subjective image quality and delineation of central and peripheral pulmonary arteries.
COVID-19 HAS AGAIN TIGHTENED ITS GRIP AROUND THE WORLD AND THE HEALTH SYSTEM. THIS ARTICLE GIVES AN INTRODUCTION TO EXPLAINABLE INTERACTIVE MACHINE LEARNING AND PROVIDES INSIGHTS ON HOW THIS METHOD MAY NOT ONLY HELP IN ENGINEERING MORE POWERFUL AI SYSTEMS, BUT ALSO HOW IT MAY HELP TO EASE THE BURDEN OF VIRAL STRAINS ON THE HEALTHCARE SYSTEM.
Objectives: To analyze the performance of radiological assessment categories and quantitative computational analysis of apparent diffusion coefficient (ADC) maps using variant machine learning algorithms to differentiate clinically significant versus insignificant prostate cancer (PCa). Methods: Retrospectively, 73 patients were included in the study. The patients (mean age, 66.3 ± 7.6 years) were examined with multiparametric MRI (mpMRI) prior to radical prostatectomy (n = 33) or targeted biopsy (n = 40). The index lesion was annotated in MRI ADC and the equivalent histologic slides according to the highest Gleason Grade Group (GrG). Volumes of interest (VOIs) were determined for each lesion and normal-appearing peripheral zone. VOIs were processed by radiomic analysis. For the classification of lesions according to their clinical significance (GrG ≥ 3), principal component (PC) analysis, univariate analysis (UA) with consecutive support vector machines, neural networks, and random forest analysis were performed. Results: PC analysis discriminated between benign and malignant prostate tissue. PC evaluation yielded no stratification of PCa lesions according to their clinical significance, but UA revealed differences in clinical assessment categories and radiomic features. We trained three classification models with fifteen feature subsets. We identified a subset of shape features which improved the diagnostic accuracy of the clinical assessment categories (maximum increase in diagnostic accuracy ΔAUC = + 0.05, p < 0.001) while also identifying combinations of features and models which reduced overall accuracy. Conclusions: The impact of radiomic features to differentiate PCa lesions according to their clinical significance remains controversial. It depends on feature selection and the employed machine learning algorithms. It can result in improvement or reduction of diagnostic performance.
Financial literacy affects wealth accumulation, and pension planning plays a key role in this relationship. In a large field experiment, we employ a digital pension aggregation tool to confront a treatment group with a simplified overview of their current pension claims across all pillars of the pension system. We combine survey and administrative bank data to measure the effects on actual saving behavior. Access to the tool decreases pension uncertainty for treated individuals. Average savings increase - especially for the financially less literate. We conclude that simplification of pension information can potentially reduce disparities in pension planning and savings behavior.
Zum ersten Mal wurde in Deutschland eine groß angelegte wissenschaftliche Studie zur Machbarkeit und zum Nutzen einer säulenübergreifenden Renteninformationsplattform durchgeführt, unter realen Bedingungen und mit mehreren tausend Teilnehmern. Die beiden zentralen Ergebnisse sind, dass ein elektronisches Rentencockpit auch in Deutschland technisch machbar ist und beträchtlichen individuellen Zusatznutzen für die Bürgerinnen und Bürger stiften würde. Die Langfristanalysen der Pilotstudie zeigen, dass selbst die einmalige Schaffung von Rententransparenz für viele Teilnehmer Anlass genug ist, ihren Rentenplan zu überdenken und sich aktiv mit ihrer Altersvorsorge auseinanderzusetzen und ihr Verhalten zu ändern. Teilnehmer mit Zugang zu einem elektronischen Rentencockpit fühlen sich nach der Studie deutlich besser informiert und neigen dazu ihr Sparverhalten stärker anzupassen als Personen ohne Zugang. Die außerordentlich hohe Bereitschaft zur Teilnahme und die Antworten in den Online-Befragungen sind zudem Beleg für den großen Bedarf an systemgestützter, individueller Rententransparenz. Soll ein Rentencockpit Verbreitung in Deutschland finden, scheint eine automatisierte, elektronische Bereitstellung von Vertragsdaten von Seiten der Rententräger jedoch unabdingbar, da die eigenständige Suche und teilmanuelle Bereitstellung von Standmitteilungen für die meisten Studienteilnehmer ein großes Hindernis darstellt.
