Pleural fluid volume estimation: a chest radiograph prediction rule.

Acad Radiol

Robert Wood Johnson Clinical Scholars Program, University of Washington, Seattle, USA.

Published: February 1996

Rationale And Objectives: We devised a prediction rule for estimating pleural effusion volume on the basis of posteroanterior and lateral chest radiographs.

Methods: A prediction rule was devised for estimating pleural effusion volume on the basis of the presence or absence of a meniscus on chest radiographs. The rule was tested and validated using separate data sets obtained from a retrospective review of patients having both a chest radiograph and computed tomography (CT) scan (the gold standard) within 24 hr of each other. The accuracy of the prediction rule and the degree of interobserver agreement between the two independent readers were determined.

Results: For the test and validation sets, the weighted accuracies of the prediction rule were 86% and 85%, respectively. The respective weighted interobserver agreements were 97% and 88%. Pleural effusions became visible as a meniscus on the lateral chest radiograph at a volume of approximately 50 ml; at a volume of 200 ml, the meniscus could be identified on the posteroanterior radiograph. At a volume of about 500 ml, the meniscus obscured the hemidiaphragm.

Conclusion: The volume of a pleural effusion can be estimated from the chest radiograph appearance with a reasonable degree of accuracy.

Download full-text PDF

Source
http://dx.doi.org/10.1016/s1076-6332(05)80373-3DOI Listing

Publication Analysis

Top Keywords

prediction rule
20
chest radiograph
16
pleural effusion
12
estimating pleural
8
effusion volume
8
volume basis
8
lateral chest
8
radiograph volume
8
volume
7
chest
6

Similar Publications

The Calgary Kids' Hand Rule: External Validation of a Prediction Model to Triage Pediatric Hand Fractures.

Plast Surg (Oakv)

February 2025

Department of Surgery and Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Alberta Children's Hospital, Calgary, Alberta, Canada.

The Calgary Kids' Hand Rule (CKHR) is a clinical prediction rule intended to guide referral decisions for pediatric hand fractures presenting to the emergency department, identifying "complex" fractures that require surgical referral and optimizing care through better matching of patients' needs to provider expertise. The objective of this study was to externally validate the CKHR in two different tertiary pediatric hospitals in Canada. We partnered with British Columbia Children's Hospital (BCCH) and the Children's Hospital of Eastern Ontario (CHEO) to externally validate the CKHR using data from retrospective cohorts of pediatric hand fractures (via electronic medical record and x-ray review).

View Article and Find Full Text PDF

Background: This prospective, two-centre study derived and validated predictive algorithms for the Siemens Atellica IM high-sensitivity cardiac troponin I (hs-cTnI) assay in the emergency department (ED).

Methods: Algorithms for predicting 30-day myocardial infarction type 1 and 2 (MI) and death or non-ST-elevation myocardial infarction (NSTEMI, type 1 and 2) at index admission were developed from a derivation cohort of 1896 patients and validated using a synthetic dataset with nearly 1 million patient cases. Performance was compared to the European Society of Cardiology algorithms for hs-cTnT (Roche Diagnostics) and hs-cTnI (Abbott Diagnostics).

View Article and Find Full Text PDF

Contrastive learning with transformer for adverse endpoint prediction in patients on DAPT post-coronary stent implantation.

Front Cardiovasc Med

January 2025

Department of Artificial Intelligence and Informatics, Mayo Clinic, Jacksonville, FL, United States.

Background: Effective management of dual antiplatelet therapy (DAPT) following drug-eluting stent (DES) implantation is crucial for preventing adverse events. Traditional prognostic tools, such as rule-based methods or Cox regression, despite their widespread use and ease, tend to yield moderate predictive accuracy within predetermined timeframes. This study introduces a new contrastive learning-based approach to enhance prediction efficacy over multiple time intervals.

View Article and Find Full Text PDF

Unlabelled: Breast cancer remains a global health challenge, with rising cases predicted in the coming decades. The complexity of breast cancer treatment arises from its complex nature, often involving multiple therapeutic strategies. One promising approach is targeting the ERK5 pathway, a key regulator in cancer cell proliferation and survival.

View Article and Find Full Text PDF

Repetitive mechanical stresses on the knee joint during daily activities accumulate fatigue damage in the articular cartilage (AC), leading to wear and knee osteoarthritis (KOA). Effective treatments remain limited, underscoring the need for predictive approaches to identify KOA early. This study proposes a mathematical model to estimate AC degradation under cyclic loading from walking.

View Article and Find Full Text PDF

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!