The BioRef Infrastructure, a Framework for Real-Time, Federated, Privacy-Preserving, and Personalized Reference Intervals: Design, Development, and Application.

Background: Reference intervals (RIs) for patient test results are in standard use across many medical disciplines, allowing physicians to identify measurements indicating potentially pathological states with relative ease. The process of inferring cohort-specific RIs is, however, often ignored because of the high costs and cumbersome efforts associated with it. Sophisticated analysis tools are required to automatically infer relevant and locally specific RIs directly from routine laboratory data.

Machine Learning in Antibody Diagnostics for Inflammatory Bowel Disease Subtype Classification.

Antibody testing in inflammatory bowel disease (IBD) can add to diagnostic accuracy of the main subtypes Crohn's disease (CD) and ulcerative colitis (UC). Whether modern modeling techniques such as supervised and unsupervised machine learning are of value for finer distinction of subtypes such as IBD-unclassified (IBD-U) is not known. We determined the antibody profile of 100 adult IBD patients from the Swiss IBD cohort study with known subtype (50 CD, 50 UC) as well as of 76 IBD-U patients.

Multilingual RECIST classification of radiology reports using supervised learning.

Objectives: The objective of this study is the exploration of Artificial Intelligence and Natural Language Processing techniques to support the automatic assignment of the four Response Evaluation Criteria in Solid Tumors (RECIST) scales based on radiology reports. We also aim at evaluating how languages and institutional specificities of Swiss teaching hospitals are likely to affect the quality of the classification in French and German languages.

Methods: In our approach, 7 machine learning methods were evaluated to establish a strong baseline.

Prognostic models in COVID-19 infection that predict severity: a systematic review.

Current evidence on COVID-19 prognostic models is inconsistent and clinical applicability remains controversial. We performed a systematic review to summarize and critically appraise the available studies that have developed, assessed and/or validated prognostic models of COVID-19 predicting health outcomes. We searched six bibliographic databases to identify published articles that investigated univariable and multivariable prognostic models predicting adverse outcomes in adult COVID-19 patients, including intensive care unit (ICU) admission, intubation, high-flow nasal therapy (HFNT), extracorporeal membrane oxygenation (ECMO) and mortality.

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

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.

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).

Big Data in Laboratory Medicine-FAIR Quality for AI?

Laboratory medicine is a digital science. Every large hospital produces a wealth of data each day-from simple numerical results from, e.g.

Endocrinological and inflammatory markers in individuals with spinal cord injury: A systematic review and meta-analysis.

Spinal cord injury (SCI) can lead to dramatic physiological changes which can be a factor in developing secondary health conditions and might be reflected in biomarker changes in this elevated risk group. We focused specifically on the endocrine and inflammation profile differences between SCI and able-bodied individuals (ABI). Our aim was to determine the differences in inflammatory markers and endocrine profiles between SCI and ABI.

Collaborative Challenges of Multi-Cohort Projects in Pharmacogenetics-Why Time Is Essential for Meaningful Collaborations.

Multi-cohort projects in medicine provide an opportunity to investigate scientific questions beyond the boundaries of a single institution and endeavor to increase the sample size for obtaining more reliable results. However, the complications of these kinds of collaborations arise during management, with many administrative hurdles. Hands-on approaches and lessons learned from previous collaborations provide solutions for optimized collaboration models.

Short-Term Fasting Attenuates Overall Steroid Hormone Biosynthesis in Healthy Young Women.

Context: Fasting is stressful for the human body. It is managed by metabolic adaptations maintaining energy homeostasis and involves steroid hormone biosynthesis, but the exact interplay between energy and steroid metabolism remains elusive. Women with polycystic ovary syndrome (PCOS) suffer from disturbed metabolism and androgen excess, while in women with anorexia nervosa, cortisol and androgen production are decreased.

Machine Learning Prediction of Hypoglycemia and Hyperglycemia From Electronic Health Records: Algorithm Development and Validation.

Background: Acute blood glucose (BG) decompensations (hypoglycemia and hyperglycemia) represent a frequent and significant risk for inpatients and adversely affect patient outcomes and safety. The increasing need for BG management in inpatients poses a high demand on clinical staff and health care systems in addition.

Objective: This study aimed to generate a broadly applicable multiclass classification model for predicting BG decompensation events from patients' electronic health records to indicate where adjustments in patient monitoring and therapeutic interventions are required.

Urine Flow Cytometry Parameter Cannot Safely Predict Contamination of Urine-A Cohort Study of a Swiss Emergency Department Using Machine Learning Techniques.

Background: Urine flow cytometry (UFC) analyses urine samples and determines parameter counts. We aimed to predict different types of urine culture growth, including mixed growth indicating urine culture contamination.

Methods: A retrospective cohort study (07/2017-09/2020) was performed on pairs of urine samples and urine cultures obtained from adult emergency department patients.

Real-world Health Data and Precision for the Diagnosis of Acute Kidney Injury, Acute-on-Chronic Kidney Disease, and Chronic Kidney Disease: Observational Study.

Background: The criteria for the diagnosis of kidney disease outlined in the Kidney Disease: Improving Global Outcomes guidelines are based on a patient's current, historical, and baseline data. The diagnosis of acute kidney injury, chronic kidney disease, and acute-on-chronic kidney disease requires previous measurements of creatinine, back-calculation, and the interpretation of several laboratory values over a certain period. Diagnoses may be hindered by unclear definitions of the individual creatinine baseline and rough ranges of normal values that are set without adjusting for age, ethnicity, comorbidities, and treatment.

Cohort profile: The Swiss Transplant Cohort Study (STCS): A nationwide longitudinal cohort study of all solid organ recipients in Switzerland.

Purpose: The Swiss Transplant Cohort Study (STCS) is a prospective multicentre cohort study which started to actively enrol study participants in May 2008. It takes advantage of combining data from all transplant programmes in one unique system to perform comprehensive nationwide reporting and to promote translational and clinical post-transplant outcome research in the framework of Swiss transplantation medicine.

Participants: Over 5500 solid organ transplant recipients have been enrolled in all six Swiss transplant centres by end of 2019, around three-quarter of them for kidney and liver transplants.

The association between nurse staffing and inpatient mortality: A shift-level retrospective longitudinal study.

Background: Worldwide, hospitals face pressure to reduce costs. Some respond by working with a reduced number of nurses or less qualified nursing staff.

Objective: This study aims at examining the relationship between mortality and patient exposure to shifts with low or high nurse staffing.

Lipoprotein(a) is associated with large artery atherosclerosis stroke aetiology and stroke recurrence among patients below the age of 60 years: results from the BIOSIGNAL study.

Aims: Lipoprotein(a) [Lp(a)] is a recognized causal risk factor for atherosclerotic cardiovascular disease but its role for acute ischaemic stroke (AIS) is controversial. In this study, we evaluated the association of Lp(a) with large artery atherosclerosis (LAA) stroke and risk of recurrent cerebrovascular events in AIS patients.

Methods And Results: For this analysis of the prospective, observational, multicentre BIOSIGNAL cohort study we measured Lp(a) levels in plasma samples of 1733 primarily Caucasian (98.

Presentation and formatting of laboratory results: a narrative review on behalf of the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Working Group "postanalytical phase" (WG-POST).

In laboratory medicine, much effort has been put into analytical quality in the past decades, making this medical profession one of the most standardized with the lowest rates of error. However, even the best analytical quality cannot compensate for errors or low quality in the pre or postanalytical phase of the total testing process. Guidelines for data reporting focus solely on defined data elements, which have to be provided alongside the analytical test results.

Pathological cerebrospinal fluid protein concentration and albumin quotient at relapse predicts short-term disability progression in multiple sclerosis: a retrospective single center observational study.

Background: Blood-brain barrier dysfunction in active multiple sclerosis (MS) lesions leads to pathological changes of cerebrospinal fluid (CSF). Theoretically, CSF analyses could help to predict relapse recovery and the course of disability. In this monocentric study, we investigated the impact of CSF findings assessed during the first relapse of MS on the short-term course of disability.

Time Requirement and Feasibility of a Systematic Quality Peer Review of Reporting in Radiology.

Objective:  To estimate the human resources required for a retrospective quality review of different percentages of all routine diagnostic procedures in the Department of Radiology at Bern University Hospital, Switzerland.

Materials And Methods:  Three board-certified radiologists retrospectively evaluated the quality of the radiological reports of a total of 150 examinations (5 different examination types: abdominal CT, chest CT, mammography, conventional X-ray images and abdominal MRI). Each report was assigned a RADPEER score of 1 to 3 (score 1: concur with previous interpretation; score 2: discrepancy in interpretation/not ordinarily expected to be made; score 3: discrepancy in interpretation/should be made most of the time).

SPHN/PHRT - MedCo in Action: Empowering the Swiss Molecular Tumor Board with Privacy-Preserving and Real-Time Patient Discovery.

MedCo is the first operational system that makes sensitive medical-data available for research in a simple, privacy-conscious and secure way. It enables a consortium of clinical sites to collectively protect their data and to securely share them with investigators, without single points of failure. In this short paper, we report on our ongoing effort for the operational deployment of MedCo within the context of the Swiss Personalized Health Network (SPHN) for the Swiss Molecular Tumor Board.

Serum Free Light Chain Assay: Shift Toward a Higher κ/λ Ratio.

Background: The analysis of serum free light chains (FLCs) is clinically relevant for the diagnosis and therapeutic management of clonal plasma cell disorders. This study compares the performance of monoclonal and polyclonal FLC κ and λ assays in clinical samples determined in a single academic center.

Methods: Serum FLCs were analyzed from 102 patients using the Freelite (Binding Site) and N Latex (Siemens) assays on the BN ProSpec System (Siemens).

Effects of Freezing and Thawing Procedures on Selected Clinical Chemistry Parameters in Plasma.

Measurements from frozen sample collections are important key indicators in clinical studies. It is a prime concern of biobanks and laboratories to minimize preanalytical bias and variance through standardization. In this study, we aimed at assessing the effects of different freezing and thawing conditions on the reproducibility of medical routine parameters from frozen samples.

Longitudinal Study of the Variation in Patient Turnover and Patient-to-Nurse Ratio: Descriptive Analysis of a Swiss University Hospital.

Background: Variations in patient demand increase the challenge of balancing high-quality nursing skill mixes against budgetary constraints. Developing staffing guidelines that allow high-quality care at minimal cost requires first exploring the dynamic changes in nursing workload over the course of a day.

Objective: Accordingly, this longitudinal study analyzed nursing care supply and demand in 30-minute increments over a period of 3 years.