Abstract

Background: Due to the lack of a gold standard diagnostic test, reference centres with experienced personnel and costly procedures are needed for primary ciliary dyskinesia (PCD) diagnostics. Diagnostic flowcharts always start with clinical symptoms. Therefore, the aim of this work is to define differential clinical criteria so that only patients clinically compatible with PCD are referred to reference centres. Materials and methods: 18 variables from 476 Mediterranean patients with clinically suspicious PCD were collected. After analysing cilia function and ultrastructure, 89 individuals were diagnosed with PCD and 387 had a negative diagnosis. Simple logistic regression analysis, considering PCD as a dependent variable and the others as independent variables, was done. In order to define the variables that best explain PCD, a step-wise logistic regression model was defined. Aiming to classify individuals as PCD or PCD-like patients, based on variables included in the study, a classification and regression tree (CART) was designed. Results and conclusions: Simple logistic regression analysis shows statistically significant association between age at the beginning of their symptomatology, periodicity, fertility, situs inversus, recurrent otitis, atelectasis, bronchiectasis, chronic productive cough, rhinorrea, rhinusinusitis and recurrent pneumonias, and PCD. The step-wise logistic regression model selected situs inversus, atelectasis, rhinorrea, chronic productive cough, bronchiectasis, recurrent pneumonias, and otitis as PCD predictive variables (82% sensitivity, 88% specificity, and 0.92 Area Under the Curve (AUC)). A decision tree was designed in order to classify new individuals based on pansinusitis, situs inversus, periodicity, rhinorrea, bronchiectasis, and chronic wet cough.

Highlights

  • Primary ciliary dyskinesia (PCD) is a rare disease with an estimated prevalence of 1/20,000–40,000 births (Code Orphanet: ORPHA244)

  • There already exist other studies that aim to identify candidate patients for primary ciliary dyskinesia (PCD) diagnostic studies [10,11], our work complements studies by defining specific parameters that allow us to differentiate between a group of patients clinically similar to PCD from those who are PCD-confirmed by diagnostic tests

  • Diagnostics were established with the study of ciliary motility using HSMV and ciliary structure by transmission electron microscopy (TEM), according to the criteria established by the European Respiratory Society guidelines2

Read more

Summary

Introduction

Primary ciliary dyskinesia (PCD) is a rare disease with an estimated prevalence of 1/20,000–40,000 births (Code Orphanet: ORPHA244). It is a genetically determined condition, characterized by abnormal or absent mobility of motile cilia and flagella. PCD testing is expensive and time-consuming and requires an experienced team of clinicians and scientists It is, necessary to define specific and differential clinical criteria regarding other causes of chronic respiratory disease, so that only patients clinically compatible with PCD are referred to diagnostic centres [1,2,9]. The definition of a specific clinical profile together with the decision tree based on clinical manifestations will help clinicians to know when do they have to refer a patient to a PCD diagnostic reference centre. There already exist other studies that aim to identify candidate patients for PCD diagnostic studies [10,11], our work complements studies by defining specific parameters that allow us to differentiate between a group of patients clinically similar to PCD from those who are PCD-confirmed by diagnostic tests

Materials and Methods
Study Population and Clinical Data
Data Analysis
Multivariate Logistic Regression Model
Demographic Characteristics
Age at the Beginning of Symptomatology
Periodicity
Fertility Problems
Situs Inversus
Chronic Otitis Media
3.1.11. Atelectasis
3.1.12. Bronchiectasis
3.1.13. Chronic Productive Cough
3.1.14. Rhinorrhea
3.1.15. Rhinosinusitis
3.1.16. Pansinusitis
3.1.17. Pneumonias
Stepwise Logistic Regression Model
Conclusions
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call