A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 176

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016

File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

An observational, prospective study exploring the use of heart rate variability as a predictor of clinical outcomes in pre-hospital ambulance patients. | LitMetric

Objective: To explore the use of pre-hospital heart rate variability (HRV) as a predictor of clinical outcomes such as hospital admission, intensive care unit (ICU) admission and mortality. We also implemented an automated pre-analysis signal processing algorithm and multiple principal component analysis (PCA) for outcomes.

Materials And Methods: We conducted a prospective observational clinical study at an emergency medical services (EMS) system in a medium sized urban setting in the United States. Electrocardiogram (ECG) data was obtained from a sample of 45 ambulance patients conveyed to a tertiary hospital, monitored with a LIFEPAK12 defibrillator/monitor. After extracting the data, filtering for noise reduction and isolating non-sinus beats, various HRV parameters were computed. These included time domain, frequency domain and geometric parameters. PCA was performed on the hospital outcomes for these patients.

Results: We used a combination of HRV parameters, age and vital signs such as respiratory rate, SpO2 and Glasgow coma score (GCS) in a PCA analysis. For predicting admission to ICU, sensitivity was 100%, specificity was 48.6%, and negative predictive value (NPV) was 100%; for predicting admission to hospital, sensitivity was 78.9%, specificity was 85.7%, and NPV was 75.0%; for predicting death, sensitivity was 50.0%, specificity was 100%, and NPV was 97.4%. There was also a significant correlation of several HRV parameters with length of hospital stay.

Conclusions: With signal processing techniques, it is feasible to filter and analyze ambulance ECG data for HRV. We found a combination of HRV parameters and traditional 'vital signs' to have an association with clinical outcomes in pre-hospital patients. This may have potential as a triage tool for ambulance patients.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.resuscitation.2008.03.224DOI Listing

Publication Analysis

Top Keywords

hrv parameters
16
clinical outcomes
12
ambulance patients
12
heart rate
8
rate variability
8
predictor clinical
8
outcomes pre-hospital
8
signal processing
8
ecg data
8
combination hrv
8

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!