Materials and Methods
Study Design and Population This prospective cross-sectional study involved adult patients presenting to participating otolaryngology clinics in Canada, Italy, and Spain, from May to August 2021. STROBE Statement was used as a guideline for reporting the results.
All adults (at least 18 years old) presenting to participating otolaryngology clinics with a pre-existing need for nasopharyngoscopy were screened for inclusion in the study. Exclusion criteria included an inability to understand the consent process, severe nasal obstruction at clinician’s discretion, previous facial cosmetic surgery, history of middle facial third orthognathic surgery or fractures, previous head and neck oncologic resection, or facial reconstruction altering measurement sites. Participants provided written consent before entering the study.
This study was performed in two steps. The primary objective was to gather normative data on nasopharyngeal depth in adults and assess its correlation with external facial measurements. Subsequently, we developed and validated a clinical predictor to aid in nasopharyngeal swab test performance.
Assessments
Self-reported participant demographics were collected, including age, sex, and ethnicity. The availability of a previous computed tomography (CT) scan of the sinonasal region was noted if present.
External facial measurements
Using a flexible surgical ruler, two external facial measurements were assessed in cm: the distance along the curvature of the face from the tragus to the alar-facial groove, and the distance anteriorly from the tragus to a plane perpendicular to the philtrum (Figure 1-A and 1-B). These variables are henceforth referred to as curved and perpendicular distances, respectively.
Nasopharynx depth (Nasoendoscopy)
Direct measurement of nasopharynx depth (ND) was performed using a flexible video endoscope by carefully bringing it into contact with the posterior wall of the nasopharynx along the floor of the nasal cavity. The point of the endoscope at the nasal sill was noted, and the instrument was removed. ND was determined by measuring the distance from the marked point to the tip of the endoscope in cm (Figure 2).
CT scan measurement
When a sinus CT scan was available, the distance in cm from the nasopharynx to the nasal sill was assessed along the floor of the nose in the axial plane.
Statistical analysis
Descriptive statistics were expressed in mean and standard deviation for continuous variables where normal distribution was assumed, whereas count and percentages were used to present the categorical ones. Statistical analysis was conducted using the program SPSS for Windows (version 20.0, Chicago, IL).
Step 1
All four measurements were presented as mean and standard deviation for the total group, and again for each sex. An independent samples T-test was used to compare groups, reported as a difference of mean, 95% CI and p-value. An analysis of variance (ANOVA) was performed for each sex to compare variables between ethnic groups.
Considering ND as the gold standard in the study, curved and perpendicular distances were compared against the ND by subtracting each participant’s measurement from their ND. The resulting variables represented an error estimation between each facial measurement and ND (i.e., Δ Perpendicular = Perpendicular - ND; Δ Curved = Curved - ND; Δ CT scan = CT scan - ND). Thus, negative error estimation values show an underestimation of ND, whereas positive values express ND overestimation.
In addition, we analyzed the correlation between ND, facial measurements, CT distance, ethnicity, sex, and age using the Pearson correlation analysis (r).
Step 2
The second step investigated the extent to which each clinical variable could function as a predictor for nasopharyngeal depth. A random number sequence generator was used to randomly select a group of 271 participants. Their data was input into multiple linear regression analyses to determine whether the external facial distances significantly predicted ND while controlling for sex and age. Then, the generated regression equations were validated using the remaining 100 study participants data by calculating the prediction error compared to the actual assessed ND for each participant (error = actual – predicted). The regression models’ errors were presented as mean, standard deviation and 95%CI.