Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Pulse rhythm

Pulse rhythm

Pulse rhythm refers to the pattern of pulsations within specific intervals, offering valuable insights into the regularity or irregularity of the heart's beats as observed through the pattern of pulsation within specific intervals. A regular pulse exhibits a consistent heart rate with uniform waveforms and pulsation force, variations of which can be classified as normal, weak, or bounding.
Conversely, an irregular pulse pattern is termed dysrhythmia, stemming from disruptions in cardiac...

Healthcare Associated Infections II: Preventive Measures

Healthcare Associated Infections II: Preventive Measures

Essential infection prevention measures are based on the knowledge of the infection chain, the modes of transmission in healthcare settings, and the use of the best practices in all healthcare settings. Compulsory public reporting of healthcare-associated infection rates is needed to allow individuals and the community to make informed choices regarding selecting a healthcare facility.
The best practices for preventing healthcare-associated infections include hand hygiene, patient risk...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Deep learning for time-series segmentation of mechanical ventilator waveforms.

Scientific reports·2026

Same author

Medical Record Abstraction for Quality Improvement in Sepsis Care Using Artificial Intelligence: A Cluster Randomized Trial.

JAMA network open·2026

Same author

Temporal Recurrent Neural Networks for Predicting Acute Kidney Injury Recovery by Time of Discharge.

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science·2026

Same author

Large Language Models for Summarizing Advance Care Planning Information From Goals of Care Notes in the EHR.

Learning health systems·2026

Same author

Glucagon Like Peptide 1 Receptor Agonists and Age-Related Macular Degeneration Incidence.

Ophthalmology. Retina·2026

Same author

Machine Learning-Predicted Risk Trajectories for Incident Chronic Kidney Disease and Associations with Post-CKD Outcomes.

Journal of medical systems·2026

Search research articles

Related Experiment Video

Updated: Jul 8, 2025

A Data-Driven Approach to Quantifying Immune States in Sepsis

A Data-Driven Approach to Quantifying Immune States in Sepsis

Published on: February 7, 2025

Predicting Hospital Readmission among Patients with Sepsis Using Clinical and Wearable Data.

Fatemeh Amrollahi, Supreeth Prajwal Shashikumar, Aaron Boussina

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|December 12, 2023

Summary

This summary is machine-generated.

Activity levels before and after hospital discharge can predict sepsis readmission risk within 90 days. Integrating wearable data with clinical information may improve prediction accuracy for sepsis patients.

More Related Videos

A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program

A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program

Published on: April 19, 2019

Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies

Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies

Published on: February 3, 2023

Related Experiment Videos

Last Updated: Jul 8, 2025

A Data-Driven Approach to Quantifying Immune States in Sepsis

A Data-Driven Approach to Quantifying Immune States in Sepsis

Published on: February 7, 2025

A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program

A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program

Published on: April 19, 2019

Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies

Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies

Published on: February 3, 2023

Area of Science:

Critical Care Medicine
Digital Health
Health Services Research

Background:

Sepsis poses a significant health burden with high hospital readmission rates.
Physical activity levels are linked to readmission risk in various conditions.
Understanding sepsis patient recovery patterns is crucial for reducing readmissions.

Purpose of the Study:

To investigate the predictive value of physical activity levels for 90-day unplanned hospital readmissions in sepsis patients.
To explore the potential of integrating wearable device data with clinical data for enhanced readmission prediction.

Main Methods:

Analysis of patient activity levels (wearable data) before and after hospital discharge.
Statistical modeling to assess the association between activity patterns and 90-day readmission.
Exploration of combined clinical and wearable data for predictive model improvement.

Main Results:

Activity level distribution prior to and post-discharge significantly predicts 90-day unplanned rehospitalization in sepsis patients (P<1e-3).
Preliminary findings suggest that combining Fitbit data with clinical measurements enhances predictive model performance.

Conclusions:

Physical activity monitoring is a promising tool for predicting sepsis readmission.
Wearable technology integration holds potential for improving sepsis care management and reducing healthcare costs.