Hospital-Based Medicine

Effectiveness of hypotension prediction index software in reducing intraoperative hypotension in prolonged prone-position spine surgery: a single-center clinical trial.

Intraoperative hypotension (IOH) is associated with morbidity and mortality. The Hypotension Prediction Index (HPI), a machine learning-based tool, offers the opportunity for a proactive approach by predicting hypotensive events. This single center, single blind randomized clinical trial aimed to evaluate the hypothesis that an HPI software-guided approach to IOH management during prone position s...

Long COVID's Hidden Complexity: Machine Learning Reveals Why Personalized Care Remains Essential.

Long COVID can develop in individuals who have had COVID-19, regardless of the severity of their initial infection or the treatment they received. Several studies have examined the prevalence and manifestation of symptom phenotypes to comprehend the pathophysiological mechanisms associated with these symptoms. Numerous articles outlined specific approaches for multidisciplinary management and tre...

Performance of Machine Learning Models in Predicting 30-Day General Medicine Readmissions Compared to Traditional Approaches in Australian Hospital Setting.

: Hospital readmissions are a key quality metric impacting both patient outcomes and healthcare costs. Traditional logistic regression models, includi...

Spatiotemporal variations in Pearl River plume dispersion over the last decade based on VIIRS-derived sea surface salinity.

A river plume indicates the dispersion and transport path of pollutants from runoff, monitoring the spatiotemporal variation of river plume distributi...

The silent epidemic of non-adherence - insights from the 2024 a:care congress.

Medication non-adherence is a global challenge with profound implications for patient health outcomes, healthcare systems, and society at large. This ...

Using Traditional and Deep Machine Learning to Predict Emergency Room Triage Levels.

Accurate triage in emergency rooms is crucial for efficient patient care and resource allocation. We developed methods to predict triage levels using ...

Using interpretable survival analysis to assess hospital length of stay.

Accurate in-hospital length of stay prediction is a vital quality metric for hospital leaders and health policy decision-makers. It assists with decis...

Influence of the CONCERN Early Warning System on Unanticipated ICU Transfers, In-Hospital Mortality, and Length of Stay: Results from a Multi-site Pragmatic Randomized Controlled Clinical Trial.

Communicating Narrative Concerns Entered by RNs Early Warning System (CONCERN EWS) is a machine-learning predictive model that leverages nursing surve...

The Core Outcome Measures Index (COMI) comes of age: 18 years of efficient and effective patient-reported outcome measurement in the field of spinal disorders. Part 2. COMI item-content, scoring, language versions, and applications.

In 1998, an international and multidisciplinary group of experts (from the fields of spine surgery, physiotherapy, occupational therapy, rheumatology,...

The Core Outcome Measures Index (COMI) comes of age: 18 years of efficient and effective patient-reported outcome measurement in the field of spinal disorders. Part 1. Development of the COMI, interpretation of scores, and use in research.

In 1998, an international and multidisciplinary group of experts (from the fields of spine surgery, physiotherapy, occupational therapy, rheumatology,...

Beyond episodic early warning systems: a continuous clinical alert system for early detection of in-hospital deterioration.

Efficient patient monitoring on the medical-surgical wards is crucial to prevent significant in-hospital adverse events. Standard episodic inpatient a...

Stem Cell and Synthetic Embryo Models: Advances, Applications, and Ethical Considerations.

Independent traditional gametes and recent advances in stem cell biology have made it possible to create synthetic embryo models (SEMs), altering our ...

New Insights into the Diagnosis and Treatment of Hepatocellular Carcinoma.

Hepatocellular carcinoma remains one of the leading contributors to global cancer mortality, frequently stemming from chronic liver conditions, such a...

Strategies to Reduce Hospital Length of Stay: Evidence and Challenges.

Hospital length of stay (HLOS) is a critical healthcare metric influencing patient outcomes, resource utilization, and healthcare costs. While reducin...

Exploring the Potential of Digital Twins in Cancer Treatment: A Narrative Review of Reviews.

Digital twin (DT) technology, integrated with artificial intelligence (AI) and machine learning (ML), holds significant potential to transform oncolo...

Applying Machine Learning to the ANZELA-QI Database to Predict Adverse Outcomes for Patients Undergoing Emergency Laparotomy.

BACKGROUND: Emergency laparotomy is associated with high rates of morbidity and mortality. Accurate, individualised risk prediction models can be used...

Contemporary Prevention and Management of Postoperative Delirium in Cardiac Surgery Patients.

This review examines the prevention and management of postoperative delirium in cardiac surgery patients, a frequent complication linked with signific...

The "Outpatient Arthroplasty Risk Assessment" Score for Same Day Outpatient Primary Total Joint Arthroplasty: A Multicenter Study.

BACKGROUND: The Outpatient Arthroplasty Risk Assessment (OARA) Score was developed to risk-stratify patients for safe same-day discharge outpatient to...

Data-Driven Defragmentation: Achieving Value-Based Sarcoma and Rare Cancer Care Through Integrated Care Pathway Mapping.

Sarcomas, a rare and complex group of cancers, require multidisciplinary care across multiple healthcare settings, often leading to delays, redundant ...

Dynamic Predictive Models of Cardiogenic Shock in STEMI: Focus on Interventional and Critical Care Phases.

: While early risk stratification in STEMI is essential, the threat of cardiogenic shock (CS) persists after revascularization due to reperfusion inju...