Assessing the documentation of publicly available medical image and signal datasets and their impact on bias using the BEAMRAD tool.

Medical datasets are vital for advancing Artificial Intelligence (AI) in healthcare. Yet biases in these datasets on which deep-learning models are trained can compromise reliability. This study investigates biases stemming from dataset-creation practices.

From intensive care monitors to cloud environments: a structured data pipeline for advanced clinical decision support.

Background: Clinical decision-making is increasingly shifting towards data-driven approaches and requires large databases to develop state-of-the-art algorithms for diagnosing, detecting and predicting diseases. The intensive care unit (ICU), a data-rich setting, faces challenges with high-frequency, unstructured monitor data. Here, we showcase a successful example of a data pipeline to efficiently move patient data to the cloud environment for structured storage.

Plasma transfusion in the intensive care unit.

Background: Current guidelines discourage prophylactic plasma use in non-bleeding patients. This study assesses global plasma transfusion practices in the intensive care unit (ICU) and their alignment with current guidelines.

Study Design And Methods: This was a sub-study of an international, prospective, observational cohort.

A review of precision medicine in developing pharmaceutical products: Perspectives and opportunities.

Over the next decade, Precision Medicine (PM) is poised to become the standard of care in pharmaceutical therapy, necessitating a fundamental transformation in the design and development of innovative custom-made drug products. To date, a comprehensive review linking PM with practical personalized drug formulations is missing. This review attempts to provide an overview of state-of-the-art formulation approaches capable of translating PM evaluation and resulting recommendations (clinical research) into tailored drug products (non-clinical research) for real-world patients.

A Q-Operator for Open Spin Chains II: Boundary Factorization.

One of the features of Baxter's Q-operators for many closed spin chain models is that all transfer matrices arise as products of two Q-operators with shifts in the spectral parameter. In the representation-theoretical approach to Q-operators, underlying this is a factorization formula for L-operators (solutions of the Yang-Baxter equation associated to particular infinite-dimensional representations). To extend such a formalism to open spin chains, one needs a factorization identity for solutions of the reflection equation (boundary Yang-Baxter equation) associated to these representations.

Incorporating the concept of overtransfusion into hemovigilance monitoring: An expert-based definition and criteria from the International HIT-OVER Forum.

Background: Liberal or overtransfusion (OT) may be regarded as "inappropriate," but it is not reported as a transfusion-related adverse event. A definition of OT is lacking. OT may include overdosing of components, giving the incorrect component, or unnecessary administration without evidence of need for transfusion.

Temporal Transitions of the Hyperinflammatory and Hypoinflammatory Phenotypes in Critical Illness.

Rationale: Systemic molecular phenotypes of critical illness are prognostically informative, yet their temporal kinetics and implications of changing phenotypes remain incompletely understood.

Objectives: To determine the temporal nature of the Hyperinflammatory and Hypoinflammatory phenotypes and assess the impact of transition between the phenotypes on mortality.

Methods: We used data from one prospective observational cohort (MARS) and two randomized controlled trials in ARDS (ALVEOLI) and sepsis (CLOVERS).

Comparison of ROTEM® Delta and ROTEM® Sigma transfusion algorithm performance in thoracic aortic surgery: a single-centre prospective observational cohort study.

Background: Thromboelastometry plays a key role in many transfusion algorithms. ROTEM® Sigma is the fully automated successor of ROTEM® Delta. Compatibility with current ROTEM® Delta-based algorithms remains uncertain.

Effect of a Machine Learning-Derived Early Warning Tool With Treatment Protocol on Hypotension During Cardiac Surgery and ICU Stay: The Hypotension Prediction 2 (HYPE-2) Randomized Clinical Trial.

Objectives: Cardiac surgery is associated with perioperative complications, some of which might be attributable to hypotension. The Hypotension Prediction Index (HPI), a machine-learning-derived early warning tool for hypotension, has only been evaluated in noncardiac surgery. We investigated whether using HPI with diagnostic guidance reduced hypotension during cardiac surgery and in the ICU.

Clinical Subtype Trajectories in Sepsis Patients Admitted to the ICU: A Secondary Analysis of an Observational Study.

Objectives: Sepsis is an evolving process and proposed subtypes may change over time. We hypothesized that previously established sepsis subtypes are dynamic, prognostic of outcome, and trajectories are associated with host response alterations.

Design: A secondary analysis of two observational critically ill sepsis cohorts: the Molecular diAgnosis and Risk stratification of Sepsis (MARS) and the Medical Information Mart for Intensive Care-IV (MIMIC-IV).

Sex disparities in myocardial infarction related cardiogenic shock.

Background: Women are underrepresented In cardiovascular disease research, constituting only 30 % of the cardiogenic shock (CS) population. Consequently, guidelines are mainly based on male patients. This study aims to comprehensively examine the sex-specific aspects of acute myocardial infarction (AMI)-related CS, encompassing presentation, treatment and outcomes.

The influence of anesthetic drug strategy on the incidence of post-induction hypotension in elective, non-cardiac surgery - A prospective observational cohort study.

Study Objectives: To identify the influence of modifiable factors in anesthesia induction strategy on post-induction hypotension (PIH), specifically the type, dosage and speed of administration of induction agents. A secondary aim was to identify patient related non-modifiable factors associated with PIH.

Design: Single-center, prospective observational cohort study.

Defining Postinduction Hemodynamic Instability With an Automated Classification Model.

Background: Postinduction hypotension (PIH) may be associated with increased morbidity and mortality. In earlier studies, the definition of PIH is solely based on different absolute or relative thresholds. However, the time-course (eg, how fast blood pressure drops during induction) is rarely incorporated, whereas it might represent the hemodynamic instability of a patient.

Quality of care after a horizontal merger between two large academic hospitals.

Background: Hospital mergers remain common, but their influence on healthcare quality varies. Data on effects of European hospital mergers are ill defined, and academic hospitals in particular. This case study assesses early quality of care changes in two formerly competing Dutch academic hospitals that merged on June 6, 2018.

A comparison between invasive and noninvasive measurement of the Hypotension Prediction Index: A post hoc analysis of a prospective cohort study.

Background: Clinical trials and validation studies demonstrate promising hypotension prediction capability by the Hypotension Prediction Index (HPI). Most studies that evaluate HPI derive it from invasive blood pressure readings, but a direct comparison with the noninvasive alternative remains undetermined. Such a comparison could provide valuable insights for clinicians in deciding between invasive and noninvasive monitoring strategies.

Exploring the Impact of Extracorporeal Membrane Oxygenation on the Endothelium: A Systematic Review.

Extracorporeal membrane oxygenation (ECMO) is a life-saving intervention for patients with circulatory and/or pulmonary failure; however, the rate of complications remains high. ECMO induces systemic inflammation, which may activate and damage the endothelium, thereby causing edema and organ dysfunction. Advancing our understanding in this area is crucial for improving patient outcomes during ECMO.

Prediction of emergency department presentations for acute coronary syndrome using a machine learning approach.

The relationship between weather and acute coronary syndrome (ACS) incidence has been the subject of considerable research, with varying conclusions. Harnessing machine learning techniques, our study explores the relationship between meteorological factors and ACS presentations in the emergency department (ED), offering insights into seasonal variations and inter-day fluctuations to optimize patient care and resource allocation. A retrospective cohort analysis was conducted, encompassing ACS presentations to Dutch EDs from 2010 to 2017.

Developments in Transfusion Medicine: Pulmonary Transfusion Reactions and Novel Blood Cell Labeling Techniques.

Staying updated on advancements in transfusion medicine is crucial, especially in critical care and perioperative setting, where timely and accurate transfusions can be lifesaving therapeutic interventions. This narrative review explores the landscape of transfusion-related adverse events, focusing on pulmonary transfusion reactions such as transfusion-associated circulatory overload (TACO) and transfusion-related acute lung injury (TRALI). TACO and TRALI are the leading causes of transfusion-related morbidity and mortality; however, specific treatments are lacking.