Plain English Summary
Background and study aim
Obstructive sleep apnea syndrome (OSAS) affects nearly one billion people worldwide. Specific screening tools are not available to identify OSAS in nocturnal polyuria (NP) populations. To develop a screening tool for detecting severe OSAS in patients presenting with NP.
Who can participate?
Men aged over 18 years who have nocturia due to nocturnal polyuria
What does the study involve?
This is a retrospective review of patients diagnosed with nocturia due to nocturnal polyuria and screened for obstructive sleep apnea syndrome between 2016 and 2018. The researchers gathered data about the collection of data, the characteristic of patients and their follow up. This is done to develop a screening tool for detecting severe OSAS in patients presenting with nocturnal polyuria.
What are the possible benefits and risks of participating?
There are no benefits or risks for participating.
Where is the study run from?
Clinique Pasteur, Toulouse
When is the study starting and how long is it expected to run for?
January 2016 to December 2018.
Who is funding the study?
The Clinique Pasteur
Who is the main contact?
Dr Vincent Misrai
A tool for severe obstructive sleep apnea syndrome screening in patients with unexplained nocturnal polyuria
Obstructive sleep apnea syndrome (OSAS) affects nearly one billion people worldwide. Specific screening tools are not available to identify OSAS in nocturnal polyuria (NP) populations. Our aim was to develop a screening tool for detecting severe OSAS using a large single-institutional dataset of patients referred for nocturnal polyuria.
Approved 17/01/2016, Commission nationale de l'informatique et des libertés (CNIL, 3 Place de Fontenoy, TSA 80715, 75334 PARIS CEDEX 07, France; +33(0)153732222), ref: 2212434
Prospective observational cohort study
Primary study design
Secondary study design
Patient information sheet
No participant information sheet available
Medical records of patients diagnosed with nocturia due to nocturnal polyuria and screened for obstructive sleep apnea syndrome (OSAS) with a sleep study (overnight polygraphy)
Patients diagnosed with severe OSAS were compared to a group of patients without OSAS or diagnosed with mild to moderate OSAS. Clinical predictive factors associated with severe OSAS were identified via logistic regression. A score combining the main predictors was
created and evaluated.
Primary outcome measure
To design and validate a new “score” (the Clinique Pasteur score) to detect severe OSAS in patients with unexplained nocturnal polyuria.
Secondary outcome measures
To validate this “score” (internal validation)
Development of the score
Step 1: logistic regression model
The first step in constructing the score was to perform a multivariate logistic regression analysis. All variables associated with severe OSAS according to a p value <0.2 in the logistic regression were selected. For continuous variables, the log-linearity assumption had to be fulfilled to ensure the validity of the model. If this assumption was not fulfilled, the continuous variable was categorized. The continuous variables included in the final model were age and BMI, and the assumption of log-linearity was not fulfilled. The thresholds chosen for the categorization of BMI were 25 kg/m2 and 30 kg/m2 according to anthropometric definition (normal/overweight/obese). The threshold for age (70 years) was much more arbitrary and was choose for sample size and powerful of the prediction reasons. The results of the model are expressed by means of odd-ratio together with their 95% confidence intervals computed by Wald’s methods.
The performance was assessed by the rate of prediction error, the receiver operating characteristic (ROC) curve and a graphical illustration of the specificity/sensitivity of the model. The area under this curve (AUC) and its 95% confidence interval computed by bootstrap procedure (2000 replicates) indicated the predictive performances of the model.
The internal validity of the model was investigated by splitting the database into two cohorts: a learning cohort (65% of the sample size) to create the model and a validation cohort (35% of the sample size) to assess. Individuals were randomly assigned to one of the cohorts. The predictive performance was assessed by the rate of prediction error and ROC curves.
Step 2: construction of the score
As the variables involved in the model were discrete, it was possible to construct a simplified score by choosing intergern proportional values to rounded values of the logistic regression coefficients. This simplified score was constructed by using the connection between the values of the score and the predicted probabilities for a patient presenting with unexplained NP to have a severe OSAS. The choice of the cut-off score was made according to the plot of PPV and NPV as a function of the threshold.
Overall trial start date
Overall trial end date
Reason abandoned (if study stopped)
Participant inclusion criteria
1. Diagnosed with a nocturia due to nocturnal polyuria
2. Screened for sleep apnea syndrome with overnight polygraphy
Target number of participants
Participant exclusion criteria
1. Patients presenting with the following potential causes of nocturnal polyuria:
1.1 Diabetes insipidus
1.2 Uncontrolled diabetes mellitus (defined by a serum glucose level > 200 mg/dL)
1.3 Severe renal impairment (defined by a glomerular filtration rate of <30 ml/min)
1.4 Hart failure
1.5 Oedematous state
Recruitment start date
Recruitment end date
Countries of recruitment
Trial participating centre
45 avenue de Lombez
45 avenue de Lombez
Funding Body Type
Funding Body Subtype
Results and Publications
Publication and dissemination plan
Planned publication in a high-impact peer-reviewed journal.
IPD sharing statement: the data sharing plans for the current study are unknown and will be made available at a later date.
Intention to publish date
Participant level data
To be made available at a later date
Basic results (scientific)