Objectives: To study the inter-physician reliability using the universal classification (UC) of acute myocardial infarction (AMI) compared to the ST-segment classification (STC). The UC is based on clinical, electrocardiographic (ECG), and pathophysiologic characteristics compared to the STC, which is mainly ECG based.
Methods: In this registry of consecutive patients with AMI presenting to a tertiary hospital, we studied the inter-physician reliability [weighted kappa (wK)] using the UC and the STC. Two physician investigators independently classified each patient with AMI according to the UC and STC, and a third senior physician investigator resolved any disagreement.
Results: The study included Type 1=226 (89.7%), Type 2=16 (6.3%), Type 3=3 (1.2%), Type 4a=1 (0.4%), Type 4b=4 (1.6%), Type 5=2 (0.8%), ST-segment-elevation AMI (STEMI)=140 (55.6%), and non-ST-segment-elevation AMI (NSTEMI)=112 (44.4%). Inter-physician reliability using the UC was very good (wK=0.84, 95% CI 0.68-0.99) and using the STC was good (wK=0.78, 95% CI 0.70-0.86). Of patients with Type 1 AMI, 57.1% were STEMI and 42.9% were NSTEMI. In contrast, of patients with Type 2 AMI, 18.8% were STEMI and 81.2% were NSTEMI.
Conclusion: The UC is a reliable method to classify patients with AMI and performs better than the STC in this study. Validation of the two classifications should be performed in large prospective studies.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.carrev.2010.06.002 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Annotation Cost Minimization for Ultrasound Image Segmentation using Cross-domain Transfer Learning.
IEEE J Biomed Health Inform
January 2023
Deep learning techniques can help minimize inter-physician analysis variability and the medical expert workloads, thereby enabling more accurate diagnoses. However, their implementation requires large-scale annotated dataset whose acquisition incurs heavy time and human-expertise costs. Hence, to significantly minimize the annotation cost, this study presents a novel framework that enables the deployment of deep learning methods in ultrasound (US) image segmentation requiring only very limited manually annotated samples.
View Article and Find Full Text PDFIntra- and Inter-Physician Agreement in Therapeutic Decision for Sleep Apnea Syndrome.
Arch Bronconeumol (Engl Ed)
January 2020
Sleep Unit, Hospital Clínic, Barcelona, Spain; IDIBAPS, Barcelona, Spain; CIBER Enfermedades Respiratorias, Madrid, Spain; Universitat de Barcelona, Barcelona, Spain. Electronic address:
Background: Large variation in diagnostic procedures and treatment recommendations may hinder the management of obstructive sleep apnea (OSA) and also compromise correct interpretation of the results of multicenter clinical trials, especially in subjects with non-severe OSA. The aim of this study was to analyze the therapeutic decision-making between different sleep physicians in patients with AHI<40events/h.
Methods: Six experienced senior sleep specialists from different sleep centers of Spain were asked to make a therapeutic decision (CPAP treatment) based on anonymized recordings of patients with suspected OSA that has previously performed a sleep study.
ACSC Indicator: testing reliability for hypertension.
BMC Med Inform Decis Mak
June 2017
Department of Community Health Sciences, University of Calgary, 3280 Hospital Dr. NW, Calgary, AB, T2N 4Z6, Canada.
Background: With high-quality community-based primary care, hospitalizations for ambulatory care sensitive conditions (ACSC) are considered avoidable. The purpose of this study was to test the inter-physician reliability of judgments of avoidable hospitalizations for one ACSC, uncomplicated hypertension, derived from medical chart review.
Methods: We applied the Canadian Institute for Health Information's case definition to obtain a random sample of patients who had an ACSC hospitalization for uncomplicated hypertension in Calgary, Alberta.
Reliability using the universal classification of acute myocardial infarction compared to ST-segment classification.
Cardiovasc Revasc Med
December 2011
Washington Hospital Center, Georgetown University, Washington, DC 20010, USA.
Objectives: To study the inter-physician reliability using the universal classification (UC) of acute myocardial infarction (AMI) compared to the ST-segment classification (STC). The UC is based on clinical, electrocardiographic (ECG), and pathophysiologic characteristics compared to the STC, which is mainly ECG based.
Methods: In this registry of consecutive patients with AMI presenting to a tertiary hospital, we studied the inter-physician reliability [weighted kappa (wK)] using the UC and the STC.
Visual analogue scale for assessing breast nodularity in non-discrete lumpy breasts: the Lucknow-Cardiff breast nodularity scale.
Breast
June 2010
Department of Surgery, King George's Medical University, Lucknow, UP, India.
Background: Objective measurement of benign non-discrete lumpy breasts is not performed routinely that would lead to disease measurement, inter-physician communication, therapeutic response assessment and a normative function of reducing unnecessary biopsies. A schematic 5-point ordinal visual analogue scale was developed.
Methods: Two blinded experienced clinicians graded breast nodularity on a pre-determined five point analogue scale (grades 0-4) to determine its inter-observer reliability after its face validity that excluded inflammatory, nipple, areola and discrete lump problems.
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!