Investigation of Predictive Indices to Objectively Guide Choice of CPAP Interface

Selecting the Appropriate CPAP Interface: Investigation of Predictive Indices to Objectively Guide the Choice of Interface

Obstructive sleep apnea (OSA) is a prevalent disease, and one that is associated with significant negative impact on long-term survival. There is convincing evidence that treatment of OSA can improve outcome in patients with cardiovascular disease, improve blood pressure and blood glucose control, and improve the overall metabolic syndrome. Treatment is usually with continuous positive airway pressure (CPAP). However, many patients face problems with their CPAP interfaces, affecting their compliance and response to treatment. Proper mask fit is important in decreasing air leak and increasing comfort, thus leading to better compliance. Currently, the choice of interfaces depends mainly on the experience of the sleep disorder unit (SDU) technicians. Unsuitable choice of interface not only affects response to treatment but also increases medical costs when interfaces need to be replaced to better fitting ones. It is thus important to develop selection criteria to objectively guide the SDU technicians in choosing the suitable interfaces. The objective of this study is to study the facial profile of patients and look for predictive indices that can be used to objectively guide the choice of appropriate interfaces. Frontal and side profile photographs of patients will be taken and facial measurements will be recorded. Patients will then be given a one monthly trial of each of the 3 interfaces (nasal masks, oronasal masks, nasal cushions) in a randomised order. The patients' subjective perception of each of the interface will be assessed and patients will nominate their preferred interface at the end of the trial. The amount of leak and the hours of adherence for each type of interface will also be analysed. A multinomial logistic regression analysis will then be done to look for facial measurements that will predict the interface that patients will be most satisfied with. Hypothesis That measurement of facial structures and clinical features will be able to predict the best-fit CPAP interface for each patient. Study Objective To determine anthropometric facial measurements and clinical factors important in achieving a good interface fit for each patient To derive a prediction rule or equation that will be able to accurately predict which interface a patient should be prescribed

This clinical research will be a prospective crossover trial in which frontal and side facial profile photographs of patients will be taken and facial measurement will be recorded including the height and width of the face and nose. Body Mass Index (BMI), Apnea Hypopnea Index (AHI) and Epworth Sleepiness Score(ESS) will be recorded. Baseline symptoms of mouth breathing and nasal congestion will also be assessed. Patients will undergo a quick 5minute trial of the interfaces at CPAP setting of 6cm H2O and give feedback of their preferred interface and satisfaction of each interface (Visual analogue scale) at the end of the quick trial. Patients will then be given a one month trial of each of the 3 interfaces (nasal masks, oronasal masks, nasal cushions) in a randomised order. For purpose of standardisation to avoid confounders, humidification and auto-titrating CPAP (autoPAP) mode of ventilation will be used in all patients. The brand of interfaces and CPAP devices used will also be standardised. This standardised CPAP treatment will be provided free of charge to patients during the duration of the study (3 months). The patients' subjective perception of each of the interface will be assessed with a visual analogue scale to assess level of satisfaction. Patients will nominate their preferred interface at the end of the trial. The amount of leak and the hours of adherence to CPAP for each type of interface will also be analysed by downloading data from the CPAP devices. A multinomial logistic regression analysis will then be done to look for facial measurements and factors that will predict the interface that patients will be most satisfied with.

Prospective crossover trial. All patients will undergo a one month trial of each of the 3 interfaces (nasal masks, oronasal masks, nasal cushions) in a randomised order.

All patients in study underwent crossover prospective trial of the same 3 types of CPAP interfaces in randomized order. Trial was 1 month duration for each interface.

All patients in study underwent crossover prospective trial of the same 3 types of CPAP interfaces in randomized order. Trial was 1 month duration for each interface.

All patients in study underwent crossover prospective trial of the same 3 types of CPAP interfaces in randomized order. Trial was 1 month duration for each interface.

All patients in study underwent crossover prospective trial of the same 3 types of CPAP interfaces (nasal mask, oronasal mask, nasal pillows) in randomized order. Trial was 1 month duration for each interface.

Assessed with downloaded data from the CPAP machine on Percentage of days with usage of more than 4 hours, mean average usage per night

Inclusion Criteria: Patients with OSA of at least moderate severity (Apnea hypopnea index (AHI) score of ≥15 on baseline polysomnography with ESS ≥ 10 or AHI≥30 regardless of ESS). Patients with no previous experience with CPAP. Patients who are between 21 - 90 year old Exclusion Criteria: Patients with significant orofacial problems that preclude the use of the interfaces. Patients who did not consent to participate in study or are unable to give informed consent. Patients with significant underlying cardiorespiratory disease that will preclude the use of AutoPAP mode of ventilation for treatment of OSA. Patients who cannot tolerate a 5minute quick trial of the interface during counselling Pregnancy

Goh KJ, Soh RY, Leow LC, Toh ST, Song PR, Hao Y, Lee KCH, Tan GL, Ong TH. Choosing the right mask for your Asian patient with sleep apnoea: A randomized, crossover trial of CPAP interfaces. Respirology. 2019 Mar;24(3):278-285. doi: 10.1111/resp.13396. Epub 2018 Sep 6.