Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

This review systematically summarizes the current status of cognitive frailty in maintenance hemodialysis patients, including its prevalence, assessment and diagnostic criteria, associated risk factors, and the clinical application status and progress of related risk prediction models both domestically and internationally. The analysis aims to provide methodological references for future development and implementation of cognitive frailty risk prediction models tailored to this specific patient population.

Download full-text PDF

Source
http://dx.doi.org/10.1111/1744-9987.70081DOI Listing

Publication Analysis

Top Keywords

risk prediction
12
prediction models
12
cognitive frailty
12
risk factors
8
frailty maintenance
8
maintenance hemodialysis
8
hemodialysis patients
8
advances risk
4
factors development
4
risk
4

Similar Publications

Study Objective: Accurately predicting which Emergency Department (ED) patients are at high risk of leaving without being seen (LWBS) could enable targeted interventions aimed at reducing LWBS rates. Machine Learning (ML) models that dynamically update these risk predictions as patients experience more time waiting were developed and validated, in order to improve the prediction accuracy and correctly identify more patients who LWBS.

Methods: The study was deemed quality improvement by the institutional review board, and collected all patient visits to the ED of a large academic medical campus over 24 months.

View Article and Find Full Text PDF

Background: Sarcomas are rare cancer with a heterogeneous group of tumors. They affect both genders across all age groups and present significant heterogeneity, with more than 70 histological subtypes. Despite tailored treatments, the high metastatic potential of sarcomas remains a major factor in poor patient survival, as metastasis is often the leading cause of death.

View Article and Find Full Text PDF

Background: In-hospital cardiac arrest (IHCA) remains a public health conundrum with high morbidity and mortality rates. While early identification of high-risk patients could enable preventive interventions and improve survival, evidence on the effectiveness of current prediction methods remains inconclusive. Limited research exists on patients' prearrest pathophysiological status and predictive and prognostic factors of IHCA, highlighting the need for a comprehensive synthesis of predictive methodologies.

View Article and Find Full Text PDF

Background And Objectives: Myelitis is a relatively common clinical entity for neurologists, with diverse underlying causes. The aim of this study was to describe the incidence of myelitis, its causes, clinical presentation, and factors predicting functional outcomes and relapses.

Methods: Using the Swedish National Patient Registry, we identified all adult patients in Stockholm County between 2008 and 2018 using International Classification of Diseases, 10th Edition (ICD-10) codes likely to include myelitis.

View Article and Find Full Text PDF

Objectives Background: Monocyte anisocytosis (monocyte distribution width [MDW]) has been previously validated to predict sepsis and outcome in patients presenting in the emergency department and mixed-population ICUs. Determining sepsis in a critically ill surgical/trauma population is often difficult due to concomitant inflammation and stress. We examined whether MDW could identify sepsis among patients admitted to a surgical/trauma ICU and predict clinical outcome.

View Article and Find Full Text PDF