Assessing the impact of vaccines on COVID-19 efficacy in survival rates: a survival analysis approach for clinical decision support.

Background: The global COVID-19 pandemic, caused by the SARS-CoV-2 virus, has presented significant challenges to healthcare systems worldwide.

Objective: This study, based on an analysis of a cohort from the Public Health System of Andalusia (Spain), aims to evaluate how vaccination affects case-fatality rate in patients hospitalized due to COVID-19 infection in Andalusia.

Methods: The cohort consists of 37,274 individuals after applying the inclusion criteria.

Assessing COVID-19 Vaccine Effectiveness and Risk Factors for Severe Outcomes through Machine Learning Techniques: A Real-World Data Study in Andalusia, Spain.

Background: COVID-19 vaccination has become a pivotal global strategy in managing the pandemic. Despite COVID-19 no longer being classified as a Public Health Emergency of International Concern, the virus continues affecting people worldwide. This study aimed to evaluate risk factors and vaccine effectiveness on COVID-19-related hospital admissions, intensive care unit (ICU) admission and mortality within the Andalusian population throughout the pandemic.

PDSS: A Pharmacological Decision Support System for Diabetics Patients with COVID-19.

With the advent of SARS-CoV-2, several studies have shown that there is a higher mortality rate in patients with diabetes and, in some cases, it is one of the side effects of overcoming the disease. However, there is no clinical decision support tool or specific treatment protocols for these patients. To tackle this issue, in this paper we present a Pharmacological Decision Support System (PDSS) providing intelligent decision support for COVID-19 diabetic patient treatment selection, based on an analysis of risk factors with data from electronic medical records using Cox regression.

A Large-Scale Multicenter Retrospective Study on Nephrotoxicity Associated With Empiric Broad-Spectrum Antibiotics in Critically Ill Patients.

Background: Evidence regarding acute kidney injury associated with concomitant administration of vancomycin and piperacillin-tazobactam is conflicting, particularly in patients in the ICU.

Research Question: Does a difference exist in the association between commonly prescribed empiric antibiotics on ICU admission (vancomycin and piperacillin-tazobactam, vancomycin and cefepime, and vancomycin and meropenem) and acute kidney injury?

Study Design And Methods: This was a retrospective cohort study using data from the eICU Research Institute, which contains records for ICU stays between 2010 and 2015 across 335 hospitals. Patients were enrolled if they received vancomycin and piperacillin-tazobactam, vancomycin and cefepime, or vancomycin and meropenem exclusively.

High resolution data modifies intensive care unit dialysis outcome predictions as compared with low resolution administrative data set.

High resolution clinical databases from electronic health records are increasingly being used in the field of health data science. Compared to traditional administrative databases and disease registries, these newer highly granular clinical datasets offer several advantages, including availability of detailed clinical information for machine learning and the ability to adjust for potential confounders in statistical models. The purpose of this study is to compare the analysis of the same clinical research question using an administrative database and an electronic health record database.

Sex-Specific Differences in Ventricular Remodeling and Response After Cardiac Resynchronization Therapy.

In this study, we investigated the baseline characteristics and "trajectories" of clinical response in men and women after cardiac resynchronization therapy (CRT) implantation. Although women enjoy improved echocardiographic response after CRT compared with men, the kinetics of this response and its relation to functional performance and outcomes are less clear. We identified 592 patients who underwent CRT implantation at our center between 2004 and 2017 and were serially followed in a multidisciplinary clinic.

A novel Vascular Leak Index identifies sepsis patients with a higher risk for in-hospital death and fluid accumulation.

Purpose: Sepsis is a leading cause of morbidity and mortality worldwide and is characterized by vascular leak. Treatment for sepsis, specifically intravenous fluids, may worsen deterioration in the context of vascular leak. We therefore sought to quantify vascular leak in sepsis patients to guide fluid resuscitation.

Intraoperative Hypotension and Acute Kidney Injury, Stroke, and Mortality during and outside Cardiopulmonary Bypass: A Retrospective Observational Cohort Study.

Background: In cardiac surgery, the association between hypotension during specific intraoperative phases or vasopressor-inotropes with adverse outcomes remains unclear. This study's hypothesis was that intraoperative hypotension duration throughout the surgery or when separated into hypotension during and outside cardiopulmonary bypass may be associated with postoperative major adverse events.

Methods: This retrospective observational cohort study included data for adults who had cardiac surgery between 2008 and 2016 in a tertiary hospital.

Can a low-cost exercise monitor provide useful heart rate monitoring for use in low-resource emergency departments?

Objective: Our objective was to study the clinical monitoring capabilities of a low-cost fitness wristband while measuring patient satisfaction with a mobility permitting device in the emergency department.

Methods: Patients enrolled were on continuous three-lead telemetry monitoring in a high acuity zone of the emergency department. Patients were given a fitness band to wear while simultaneously monitored with standard three-lead monitor.

Metabolic Cost of Exercise Initiation in Patients With Heart Failure With Preserved Ejection Fraction vs Community-Dwelling Adults.

Importance: Heart failure with preserved ejection fraction (HFpEF) is a joint metabolic and cardiovascular disorder with significant noncardiac contributions.

Objective: To define and quantify the metabolic cost of initiating exercise in individuals with and without HFpEF and its functional consequences.

Design, Setting, And Participants: This prospective cohort study included individuals with hemodynamically confirmed HFpEF from the Massachusetts General Hospital Exercise Study (MGH-ExS) and community-dwelling participants from the Framingham Heart Study (FHS).

Machine Learning Models with Preoperative Risk Factors and Intraoperative Hypotension Parameters Predict Mortality After Cardiac Surgery.

Objectives: Machine learning models used to predict postoperative mortality rarely include intraoperative factors. Several intraoperative factors like hypotension (IOH), vasopressor-inotropes, and cardiopulmonary bypass (CPB) time are significantly associated with postoperative outcomes. The authors explored the ability of machine learning models incorporating intraoperative risk factors to predict mortality after cardiac surgery.

Developing well-calibrated illness severity scores for decision support in the critically ill.

Illness severity scores are regularly employed for quality improvement and benchmarking in the intensive care unit, but poor generalization performance, particularly with respect to probability calibration, has limited their use for decision support. These models tend to perform worse in patients at a high risk for mortality. We hypothesized that a sequential modeling approach wherein an initial regression model assigns risk and all patients deemed then have their risk quantified by a second, high-risk-specific, regression model would result in a model with superior calibration across the risk spectrum.

Big data and machine learning in critical care: Opportunities for collaborative research.

The introduction of clinical information systems (CIS) in Intensive Care Units (ICUs) offers the possibility of storing a huge amount of machine-ready clinical data that can be used to improve patient outcomes and the allocation of resources, as well as suggest topics for randomized clinical trials. Clinicians, however, usually lack the necessary training for the analysis of large databases. In addition, there are issues referred to patient privacy and consent, and data quality.