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Journal ArticleDOI

Clinical decision rule to predict the presence of interstitial lung disease in systemic sclerosis.

TLDR
A clinical decision rule to predict the presence of interstitial lung disease in systemic sclerosis (SSc; scleroderma) and to estimate the prevalence of SSc‐ILD is developed.
Abstract
Objective To develop a clinical decision rule to predict the presence of interstitial lung disease (ILD) in systemic sclerosis (SSc; scleroderma) and to estimate the prevalence of SSc-ILD. Methods Patient data were extracted from the Canadian Scleroderma Research Group registry. Three algorithms for the clinical decision rule were considered based on lung auscultation, chest radiography (CXR), and % predicted forced vital capacity (FVC). High-resolution computed tomography (HRCT) scans were used as the gold standard to determine the diagnostic properties of the 3 algorithms. Multiple imputation was used to impute HRCT data when missing, thereby avoiding bias due to differential referral for HRCT. Results This study included 1,168 patients. Of the patients with HRCT scans, 65% had evidence of ILD, compared to 26% by physical examination and 22% by CXR. The FVC of those who did not have HRCT was 8.8% greater than those who did (95% confidence interval [95% CI] 6.0–11.6%). Algorithm A, which identified the presence of ILD based on crackles on lung auscultation and/or findings on CXR, had a likelihood ratio of 3.9, compared to 3.2 for Algorithm B (which included patients with FVC <70%) and 2.2 for Algorithm C (which included patients with FVC <80%). The prevalence of ILD in the cohort was estimated to be 52% (95% CI 46–59%). Conclusion We developed a simple clinical decision rule to predict SSc-ILD with good test characteristics. The prevalence of ILD in a large, unselected SSc cohort was estimated to be 52%.

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Citations
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Journal ArticleDOI

Prediction of pulmonary complications and long-term survival in systemic sclerosis.

TL;DR: To assess survival and incidence of organ‐based complications in a large single‐center cohort of unselected systemic sclerosis patients, and to explore predictors of survival and clinically significant pulmonary fibrosis and pulmonary hypertension.
Journal ArticleDOI

Scleroderma lung disease

TL;DR: The direct and indirect pulmonary manifestations of SSc are reviewed and recent therapeutic trials that have attempted to target these manifestations are reviewed.
Journal ArticleDOI

Systemic sclerosis-associated interstitial lung disease.

TL;DR: Systemic sclerosis-associated interstitial lung disease most commonly presents with dyspnoea, cough, and a non-specific interstitial pneumonia pattern on CT scan, with a minority of cases fulfilling the criteria for usual interstitial tuberculosis.
Journal ArticleDOI

Brief Report: Pulmonary Function Tests: High Rate of False-Negative Results in the Early Detection and Screening of Scleroderma-Related Interstitial Lung Disease.

TL;DR: PFTs are evaluated compared with high‐resolution computed tomography of the chest for the detection of SSc‐related ILD in clinical practice, and predictors of lung involvement that is functionally occult but significant on HRCT are identified.
References
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Journal Article

R: A language and environment for statistical computing.

R Core Team
- 01 Jan 2014 - 
TL;DR: Copyright (©) 1999–2012 R Foundation for Statistical Computing; permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and permission notice are preserved on all copies.
Book

Multiple imputation for nonresponse in surveys

TL;DR: In this article, a survey of drinking behavior among men of retirement age was conducted and the results showed that the majority of the participants reported that they did not receive any benefits from the Social Security Administration.
Journal ArticleDOI

mice: Multivariate Imputation by Chained Equations in R

TL;DR: Mice adds new functionality for imputing multilevel data, automatic predictor selection, data handling, post-processing imputed values, specialized pooling routines, model selection tools, and diagnostic graphs.
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