Abstract
Background
Unanticipated difficult airway management remains a major contributor to perioperative morbidity and mortality. Conventional bedside tests have shown limited and variable predictive accuracy, and no single test reliably identifies patients at risk. Point-of-care airway ultrasonography has emerged as a promising adjunct, but the diagnostic performance of specific sonographic parameters — particularly the skin-to-epiglottis distance (SED) — requires further evaluation.
Methods
In this prospective, single-center observational study, 400 adults (18–70 years; ASA I–III) scheduled for elective surgery under general anesthesia with orotracheal intubation were enrolled. Before induction, the attending anesthesiologist performed a standardized bedside assessment (modified Mallampati classification, upper lip bite test, and thyromental, sternomental, interincisor, and mentohyoid distances). A second anesthesiologist experienced in airway ultrasonography, blinded to the bedside findings and intraoperative outcomes, obtained sonographic measurements including SED, skin-to-thyroid cartilage and thyroid cartilage-to-epiglottis distances, pre-epiglottic space depth, tongue thickness, and hyomental distance in neutral and extended positions. The prespecified primary outcome was difficult intubation (two or more intubation attempts); difficult mask ventilation (DMV; requiring two-handed two-provider technique or airway adjuncts) was the prespecified secondary outcome. Between-group comparisons and receiver operating characteristic (ROC) curve analysis were performed, with optimal cutoffs identified by the Youden index.
Results
Difficult intubation occurred in 20 patients (5.0%) and DMV in 27 (6.8%). Among bedside tests, the upper lip bite test and modified Mallampati classification were significantly associated with difficult intubation. SED yielded the highest point-estimate discrimination (AUC 0.912; 95% CI 0.811–1.000; optimal cutoff 2.14 cm; 85% sensitivity, 91% specificity); given the limited number of events, these estimates are subject to imprecision and should be interpreted as exploratory. Predictors of DMV followed a distinct pattern, dominated by demographic, comorbid, and broader anatomical factors rather than by any single ultrasound parameter.
Conclusions
Preoperative airway ultrasonography — and in particular SED — provided supplementary anatomical information beyond conventional bedside assessment for difficult intubation, whereas predictors of difficult mask ventilation followed a distinct pattern, supporting the view that these are related but non-identical airway phenotypes. Given the single-center design and the limited number of events, these findings require external validation in multicenter studies incorporating multiparametric ultrasound-and-clinical models and contemporary videolaryngoscopy-based airway management.
Trial registration
The study was retrospectively registered at ClinicalTrials.gov (NCT07383610; registered 26 January 2026) after study initiation. This timing is reported transparently and does not affect data integrity or the prespecified analyses.
Keywords: Airway ultrasonography, Difficult intubation, Difficult mask ventilation, Preoperative airway assessment, Skin-to-epiglottis distance
Background
Airway management remains a core responsibility of anesthesiologists and a major determinant of perioperative safety. Despite advances in airway devices, monitoring, and structured management algorithms, unanticipated difficulty in mask ventilation or tracheal intubation continues to contribute to serious perioperative complications, particularly when difficulty is recognized late, repeated attempts occur, or oxygenation cannot be maintained [1, 2].
Preoperative airway evaluation traditionally relies on bedside clinical tests such as the Mallampati classification, airway distance measurements, and functional assessments. However, systematic reviews and major evidence syntheses have consistently shown that the diagnostic performance of individual bedside tests is modest and variable, and that no single bedside assessment provides sufficient certainty to reliably rule in or rule out difficult intubation in routine adult practice [3–5]. These limitations underscore the need for additional assessment tools that are anatomically informative and clinically applicable [3, 5].
Point-of-care ultrasonography has emerged as a practical adjunct for airway assessment because it enables quantifiable evaluation of anterior neck soft tissue and upper airway structures that cannot be inferred reliably from surface landmarks alone [6, 7]. As preoperative airway assessment has evolved, ultrasonography has been increasingly discussed as a promising extension of conventional bedside evaluation rather than a replacement for it [8]. A growing body of literature has investigated sonographic parameters such as tongue thickness, pre-epiglottic space depth, hyomental distances, and multiparametric combinations of ultrasound and clinical variables, with heterogeneous results across patient populations, measurement protocols, and outcome definitions [9–11].
Among these sonographic indices, the skin-to-epiglottis distance (SED) has attracted particular interest because it reflects the cumulative anterior soft-tissue thickness overlying the laryngeal inlet and may plausibly influence laryngoscopic exposure [12, 13]. Across several cohorts and methodological settings, SED has repeatedly emerged as one of the strongest, or at least one of the most consistent, ultrasonographic predictors of difficult laryngoscopy or intubation, although reported thresholds vary according to patient characteristics, head position, measurement plane, and the airway outcome selected [11, 12, 14]. Additional contemporary studies have continued to evaluate SED alongside other ultrasound parameters and derived models, supporting its central role within broader sonographic airway assessment frameworks [11, 15].
At the same time, the literature is no longer limited to direct laryngoscopy alone. Recent work has increasingly examined multiparametric ultrasound approaches and their relation to videolaryngoscopic intubation, suggesting that sonographic anatomy may remain informative even as airway management practice evolves beyond conventional direct laryngoscopy [16]. This broader perspective is important because anatomical visualization, laryngoscopic grade, and intubation success are related but non-equivalent outcomes, and recent commentary has emphasized the need for more standardized videolaryngoscopy-based evaluation frameworks [17].
Difficult mask ventilation (DMV) represents another clinically important airway problem that may occur independently of difficult intubation and may have partially distinct determinants [18]. Large multicenter analyses have shown that the combination of difficult mask ventilation and difficult laryngoscopy represents a particularly high-risk phenotype, reinforcing the importance of preoperative recognition and preparation [19]. More recent ultrasound-based work has also suggested that sonographic measurements may contribute to the prediction of difficult mask ventilation, supporting a broader role for airway ultrasound beyond intubation alone [20].
Therefore, this prospective observational study aimed to evaluate the predictive performance of preoperative ultrasonographic airway measurements, with particular emphasis on SED, for difficult intubation and to compare these findings with conventional bedside airway tests. As a secondary aim, we assessed factors associated with difficult mask ventilation and explored whether the pattern of ultrasonographic and bedside predictors differed between these two clinically related but non-identical airway outcomes.
Methods
Study design and ethical approval
This prospective, single-center observational study was conducted at the Department of Anesthesiology and Reanimation of an academic tertiary-care institution between 1 October 2023 and 1 October 2024. The study protocol was approved by the institutional Ethics Committee (approval no. 2023/10–19; 06 September 2023) and was conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants before enrollment. The study was registered at ClinicalTrials.gov after study initiation (NCT07383610; 26 January 2026).
Study population
Adult patients aged 18–70 years with American Society of Anesthesiologists (ASA) physical status I-III who were scheduled for elective surgery under general anesthesia requiring orotracheal intubation were considered eligible.
Exclusion criteria were emergency surgery, pregnancy, known upper airway pathology likely to affect laryngoscopy, previous major upper airway surgery, restricted mouth opening (< 3 cm) due to fixed pathology, cervical spine instability or clinically significant limitation of neck mobility, morbid obesity (body mass index ≥ 40 kg/m²), prior neck radiotherapy, clinically relevant neck masses, major facial or mandibular trauma, marked craniofacial anomalies, and planned awake intubation. The study was designed to evaluate sonographic airway measurements in a protocolized elective airway-management setting; therefore, patients in whom awake fiberoptic intubation or other advanced techniques were planned a priori were excluded.
Preoperative clinical airway assessment
All patients underwent a standardized preoperative airway assessment performed by the anesthesiologist who was also responsible for intraoperative airway management. Bedside assessment findings were documented before induction, whereas ultrasonographic measurements were obtained independently by a separate anesthesiologist. Bedside tests included the modified Mallampati classification, thyromental distance, sternomental distance, interincisor distance, upper lip bite test, and mentohyoid distance. Assessments were performed with the patient seated, with the head in a neutral position, and distances were recorded in centimeters using a flexible measuring tape according to predefined criteria.
Ultrasonographic airway assessment
Before anesthetic induction, airway ultrasonography was performed in the operating room using a Philips Affiniti 50G system (Philips Healthcare, Andover, MA, USA) equipped with a 3–12 MHz high-frequency linear transducer. Ultrasonographic measurements were obtained by a single anesthesiologist with 4 years of experience in perioperative airway ultrasonography, who was independent of the anesthesiologist performing the preoperative bedside clinical assessment and intraoperative airway management.
To improve measurement standardization, the transducer was applied with minimal pressure, all measurements were obtained in predefined midline planes using anatomical landmarks, and each parameter was measured twice with the mean value used for analysis. Patients were examined in the supine position, and whenever feasible measurements were acquired during quiet breathing at end-expiration to reduce respiratory variability.
The following sonographic parameters were recorded: skin-to-epiglottis distance (SED), skin-to-thyroid cartilage distance, thyroid cartilage-to-epiglottis distance, pre-epiglottic space depth, tongue thickness, and hyomental distance. SED was defined as the shortest distance from the skin surface to the anterior border of the epiglottis, measured in the standardized midline laryngeal view with the head in an extended position; the skin-to-thyroid cartilage distance and the thyroid cartilage-to-epiglottis distance were obtained in the same view. Tongue thickness was measured in the submental view with the head in the neutral position. Hyomental distance was recorded sonographically in both the neutral and extended head positions.
A representative parasagittal midline ultrasound image illustrating the skin-to-epiglottis distance, skin-to-thyroid cartilage distance, and thyroid cartilage-to-epiglottis distance is provided in Fig. 1, and a representative submental view demonstrating tongue thickness and hyomental distance is provided in Fig. 2. Representative probe positioning for the laryngeal and submental views is shown in Figs. 3 and 4, respectively.
Fig. 1.
Representative parasagittal ultrasound image of the anterior neck demonstrating the sonographic landmarks and measurement planes used in the present study. E, anterior border of the epiglottis; T, thyroid cartilage. Blue line: skin-to-epiglottis distance (SED). Red line: skin-to-thyroid cartilage distance. Green line: thyroid cartilage-to-epiglottis distance. Orange line: pre-epiglottic space depth. The transducer was applied in the midline with minimal pressure, and the patient was examined in the supine position with the head in a standardized extended position
Fig. 2.
A typical submental ultrasound image showing the measurement of tongue thickness and the hyomental distance. The image was obtained using a curved (convex) probe placed over the submental region in the sagittal plane, with the probe tip directed cranially. Anatomical landmarks: 1, hyoid bone; 2, mental surface of the mandible. The yellow arrow (between points 1 and 2) indicates the hyomental distance. The red arrow (between points 3 and 4) indicates the thickness of the tongue
Fig. 3.
Representative probe positioning for preoperative airway ultrasonography. The Philips L12-3 linear transducer is applied in the parasagittal midline plane over the anterior neck, with the patient in the supine position and the head in a standardized extended position
Fig. 4.
Typical placement of a convex probe for submental airway ultrasound. With the patient in the supine position with the head extended, a curved probe (Philips C6-2) is placed over the submental region in the sagittal plane
Anesthesia protocol and airway management
General anesthesia was administered according to institutional standard practice. Induction medications, including the hypnotic, opioid, and neuromuscular blocking agent, were selected by the attending anesthesiologist based on routine practice and patient characteristics. Adequacy of neuromuscular blockade was confirmed clinically and/or with neuromuscular monitoring when available before airway instrumentation.
Tracheal intubation was initially attempted using direct laryngoscopy with an appropriately sized Macintosh blade. Intubations were performed by anesthesiologists with at least 4 years of airway-management experience. Patient positioning, external laryngeal manipulation, and adjunct maneuvers were optimized as needed. After a failed initial attempt, rescue devices such as a stylet or bougie, levering laryngoscope, or videolaryngoscope were available and were used when clinically indicated.
Outcome definitions
The primary outcome was difficult intubation, defined a priori as the requirement for two or more intubation attempts to achieve successful tracheal intubation. Difficult mask ventilation (DMV) was defined as inadequate face-mask ventilation requiring two-handed ventilation by two providers and/or the use of airway adjuncts (e.g., an oral airway) to achieve effective ventilation, as judged by visible chest rise and, when available, capnography. These definitions were established before study initiation and applied uniformly to all patients.
Statistical analysis
Data were analyzed using SPSS Statistics version 26.0 (IBM Corp., Armonk, NY, USA). Distributional assumptions for continuous variables were evaluated using the Shapiro-Wilk test. Continuous variables are presented as mean ± standard deviation or median (interquartile range), as appropriate, and categorical variables as counts and percentages.
Comparisons between patients with and without difficult intubation and between patients with and without DMV were performed using the independent-samples t test for normally distributed continuous variables and the Mann-Whitney U test for non-normally distributed variables. Categorical variables were compared using the chi-square test or Fisher’s exact test, as appropriate.
Discriminatory performance of bedside and ultrasonographic airway parameters was evaluated using receiver operating characteristic (ROC) curve analysis. The area under the curve (AUC) with 95% confidence intervals was calculated, and optimal cutoff values were determined using the Youden index; sensitivity and specificity at the identified cutoffs were reported.
Given the limited number of primary outcome events, analyses for difficult intubation were intentionally restricted to between-group comparisons and ROC-based discrimination estimates, and no multivariable prediction model was fitted for the primary endpoint in order to avoid unstable estimates and overfitting. DMV analyses were prespecified as secondary and exploratory. No formal adjustment for multiple comparisons was applied; therefore, these analyses should be interpreted as hypothesis-generating. A two-sided p value < 0.05 was considered statistically significant.
Sample size planning
The sample size was planned a priori using G*Power (version 3.1.9.6; Heinrich-Heine-Universität Düsseldorf, Germany). In line with systematic-review data on the prevalence of bedside airway predictors in adult elective surgical populations [3, 4], we prespecified an approximate 30:70 allocation between patients carrying at least one conventional high-risk bedside feature (e.g., modified Mallampati class III–IV, upper lip bite test grade 3, thyromental distance < 6.5 cm, or body mass index ≥ 30 kg/m²) and those without any such feature, corresponding to an allocation ratio N2/N1 = 2.33. For the SED contrast between these two strata, we adopted a conservative standardized mean difference of Cohen’s d = 0.30 (small-to-medium), intentionally more conservative than the effect sizes reported in enriched or selected cohorts (e.g., Prathep et al. in morbidly obese patients [13]; Fernández-Vaquero et al. in the sniffing position [14]; Rastogi et al. in a mixed adult cohort [15]) in order to remain appropriate for a heterogeneous elective surgical population and to avoid overestimation of power. With α = 0.05 (two-sided) and statistical power of 1 − β = 0.80, the minimum required total sample size was 383 participants. To accommodate non-participation, exclusions, and missing preoperative measurements, enrolment was targeted at 400 evaluable patients.
Results
A total of 580 patients were assessed for eligibility during the study period. Of these, 142 declined to participate and 38 were excluded because of missing preoperative bedside and/or ultrasonographic airway measurements. Missing preoperative measurements were primarily attributable to operating-room workflow constraints and occasional technical limitations (e.g., incomplete bedside assessment documentation and/or inadequate ultrasound image acquisition before induction. A total of 400 patients were therefore included in the final analysis (Fig. 5). The incidence of difficult intubation, defined a priori as the requirement for ≥ 2 intubation attempts, was 5.0% (20/400), and difficult mask ventilation occurred in 6.8% of patients (27/400).
Fig. 5.
Participant flow diagram
Difficult intubation (≥ 2 attempts)
Patient characteristics
Demographic characteristics (age, sex, anthropometrics) and ASA physical status did not differ significantly between patients intubated on the first attempt (n = 380) and those requiring ≥ 2 attempts (n = 20). Most comorbidities did not differ significantly; however, diabetes mellitus was more frequent among patients with difficult intubation (Table 1). Comorbidity information was available in a subset of 254 patients (239 in the first-attempt group and 15 in the ≥ 2 attempts group); denominators and percentages are therefore reported accordingly in Table 1 and should be interpreted with this in mind.
Table 1.
Baseline characteristics and comorbidities by intubation attempts
| Variable | First attempt (n = 380) | ≥2 attempts (n = 20) | p-value |
|---|---|---|---|
| Age (years) | 47.66 ± 15.94 | 49.9 ± 8.28 | 0.279 |
| Sex, male | 178 (46.8%) | 11 (55.0%) | 0.629 |
| Sex, female | 202 (53.2%) | 9 (45.0%) | |
| Height (cm) | 166.9 ± 9.13 | 170.15 ± 10.85 | 0.125 |
| Weight (kg) | 76.46 ± 13.91 | 85.6 ± 19.92 | 0.056 |
| Body mass index (kg/m²) | 27.46 ± 4.95 | 29.34 ± 4.97 | 0.100 |
| ASA I | 141 (37.1%) | 5 (25.0%) | 0.519 |
| ASA II | 183 (48.2%) | 12 (60.0%) | |
| ASA III | 56 (14.7%) | 3 (15.0%) | |
| Hypertension | 82/239 (34.3%) | 8/15 (53.3%) | 0.229 |
| Diabetes mellitus | 46/239 (19.2%) | 7/15 (46.7%) | 0.012 |
| Rheumatoid arthritis | 1/239 (0.4%) | 0/15 (0.0%) | 0.801 |
| Ankylosing spondylitis | 2/239 (0.8%) | 0/15 (0.0%) | 0.722 |
| Other comorbidity | 191/239 (80.3%) | 10/15 (66.7%) | 0.207 |
Percentages for comorbidity variables are calculated among patients with available comorbidity data (First attempt: N = 239; ≥2 attempts: N = 15, comorbidity data available for n: 239)
Abbreviations: ASA American Society of Anesthesiologists physical status
Bedside airway assessment tests
Several preoperative bedside tests were associated with difficult intubation (Table 2). Upper lip bite test (ULBT) grade 3 was more common in patients with difficult intubation (20.0% [4/20]) than in those intubated on the first attempt (6.6% [25/380]; p = 0.024). Modified Mallampati classification also differed significantly between groups (p = 0.003), with a higher proportion of Mallampati class 4 among patients requiring ≥ 2 attempts (40.0% vs. 9.2%). In contrast, sternomental distance, thyromental distance, interincisor distance, and mentohyoid distance did not differ significantly between groups (all p > 0.05) (Table 2).
Table 2.
Bedside airway assessments by intubation attempts
| Assessment | Category / value | First attempt (n = 380) | ≥ 2 attempts (n = 20) | p-value |
|---|---|---|---|---|
| Upper lip bite test (ULBT) | Easy (grade 1–2) | 355 (93.4%) | 16 (80.0%) | 0.024 |
| Difficult (grade 3) | 25 (6.6%) | 4 (20.0%) | ||
| Mallampati class | I | 17 (4.5%) | 0 (0.0%) | 0.003 |
| II | 127 (33.4%) | 6 (30.0%) | ||
| III | 201 (52.9%) | 6 (30.0%) | ||
| IV | 35 (9.2%) | 8 (40.0%) | ||
| Sternomental distance (cm) | mean ± SD | 14.56 ± 1.80 | 13.95 ± 2.78 | 0.343 |
| Thyromental distance (cm) | mean ± SD | 9.29 ± 1.23 | 8.60 ± 1.90 | 0.127 |
| Interincisor distance (cm) | mean ± SD | 5.49 ± 0.84 | 5.30 ± 0.92 | 0.318 |
| Mentohyoid distance (cm) | mean ± SD | 5.86 ± 0.68 | 5.80 ± 1.08 | 0.811 |
Ultrasonographic airway assessment
Several preoperative airway ultrasound measurements differed between groups (Table 3). SED was higher in patients with difficult intubation than in those intubated on the first attempt (2.29 ± 0.32 vs. 1.80 ± 0.23 cm; p < 0.001). Similarly, the skin-to-thyroid cartilage distance (1.26 ± 0.23 vs. 0.99 ± 0.20 cm; p < 0.001), thyroid cartilage-to-epiglottis distance (1.03 ± 0.26 vs. 0.84 ± 0.15 cm; p = 0.004), tongue thickness (5.55 ± 0.92 vs. 4.95 ± 0.59 cm; p = 0.009), and pre-epiglottic space depth (PES) (0.79 ± 0.18 vs. 0.68 ± 0.14 cm; p = 0.009) were higher in the difficult intubation group.
Table 3.
Preoperative airway ultrasound measurements by intubation outcome
| Ultrasound parameter (cm) | Easy intubation (n = 380) | Difficult intubation (n = 20) | p-value |
|---|---|---|---|
| Skin to epiglottis distance (SED) | 1.80 ± 0.23 | 2.29 ± 0.32 | < 0.001 |
| Skin to thyroid cartilage distance | 0.99 ± 0.20 | 1.26 ± 0.23 | < 0.001 |
| Thyroid cartilage to epiglottis distance | 0.84 ± 0.15 | 1.03 ± 0.26 | 0.004 |
| Tongue thickness | 4.95 ± 0.59 | 5.55 ± 0.92 | 0.009 |
| Pre-epiglottic space depth (PES) | 0.68 ± 0.14 | 0.79 ± 0.18 | 0.009 |
ROC analysis
In ROC analysis, SED yielded the highest point-estimate discrimination for difficult intubation, with an AUC of 0.912 (SE 0.051; 95% CI 0.811–1.000). The optimal cutoff value for SED was 2.14 cm, yielding 85% sensitivity and 91% specificity. The skin-to-thyroid cartilage distance demonstrated moderate discriminatory performance (AUC 0.796, SE 0.045; 95% CI 0.708–0.885) with an optimal cutoff of 1.09 cm (70% sensitivity; 67% specificity). Similarly, the thyroid cartilage-to-epiglottis distance demonstrated moderate discriminatory performance (AUC 0.762, SE 0.067; 95% CI 0.631–0.892) with an optimal cutoff of 0.94 cm (65% sensitivity; 79% specificity) (Table 4) (Fig. 6). However, given the limited number of difficult intubation events (n = 20), these ROC-derived point estimates are subject to imprecision — as reflected by the width of the 95% confidence intervals, including an upper bound reaching 1.000 for SED — and should be interpreted as exploratory and hypothesis-generating rather than as definitive measures of diagnostic accuracy.
Table 4.
ROC analysis of ultrasound predictors for difficult intubation (≥2 attempts)
| Predictor | AUC | SE | p-value | 95% CI (lower) | 95% CI (upper) | Cutoff | Sensitivity | Specificity |
|---|---|---|---|---|---|---|---|---|
| Skin-to-epiglottis distance (SED) | 0.912 | 0.051 | <0.001 | 0.811 | 1.000 | 2.14 | 0.85 | 0.91 |
| Skin to thyroid cartilage distance | 0.796 | 0.045 | <0.001 | 0.708 | 0.885 | 1.09 | 0.70 | 0.67 |
| Thyroid cartilage to epiglottis distance | 0.762 | 0.067 | <0.001 | 0.631 | 0.892 | 0.94 | 0.65 | 0.79 |
Fig. 6.
Receiver operating characteristic (ROC) curves for ultrasonographic predictors of difficult intubation. ROC curves illustrating the discriminatory performance of three ultrasonographic airway parameters for the prediction of difficult intubation, defined as requiring ≥2 intubation attempts. Skin-to-epiglottis distance (SED) yielded the highest point-estimate discrimination (AUC 0.912; 95% CI 0.811–1.000), with an optimal cutoff of 2.14 cm yielding 85% sensitivity and 91% specificity; however, given the limited number of difficult intubation events, this estimate should be interpreted cautiously. Skin-to-thyroid cartilage distance showed moderate performance (AUC 0.796; 95% CI 0.708–0.885), with a cutoff of 1.09 cm (sensitivity 70%; specificity 67%). Thyroid cartilage-to-epiglottis distance also demonstrated moderate discrimination (AUC 0.762; 95% CI 0.631–0.892), with a cutoff of 0.94 cm (sensitivity 65%; specificity 79%). Optimal cutoff values were determined using the Youden index. The diagonal dashed line represents the reference line of no discrimination (AUC = 0.50). AUC, area under the curve; CI, confidence interval; SED, skin-to-epiglottis distance
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Difficult mask ventilation (DMV)
Patient characteristics
Patients with DMV (n = 27) were older than those without DMV (58.19 ± 13.66 vs. 47.02 ± 15.53 years; p < 0.001) and were more frequently male (20/27 [74.1%] vs. 169/373 [45.3%]; p = 0.007). Height and weight were higher in the DMV group (171.41 ± 10.50 vs. 166.75 ± 9.07 cm; p = 0.011; and 86.52 ± 17.02 vs. 76.22 ± 13.94 kg; p < 0.001, respectively), whereas BMI did not reach statistical significance (29.33 ± 4.77 vs. 27.43 ± 4.95 kg/m²; p = 0.055). ASA physical status distribution differed between groups (p = 0.002), with a higher proportion of ASA III in the DMV group (10/27 [37.0%] vs. 49/373 [13.1%]). In the subset of patients with available comorbidity information (n = 253; 22 in the DMV group and 231 in the non-DMV group), hypertension and diabetes mellitus were more frequent among patients with DMV (13/22 [59.1%] vs. 77/231 [33.3%], p = 0.029; and 10/22 [45.5%] vs. 43/231 [18.6%], p = 0.003, respectively). Ankylosing spondylitis was also numerically more common in the DMV group (1/22 [4.5%] vs. 1/231 [0.4%]; p = 0.037), although this observation was based on only two affected patients and should be regarded as exploratory (Table 5).
Table 5.
Preoperative characteristics and intraoperative airway management in patients with and without difficult mask ventilation (DMV)
| Variable | DMV Yes (n = 27) | DMV No (n = 373) | p-value |
|---|---|---|---|
| Preoperative characteristics, bedside tests, and ultrasonographic measurements | |||
| Age (years) | 58.19 ± 13.66 | 47.02 ± 15.53 | < 0.001 |
| Sex, male | 20 (74.1%) | 169 (45.3%) | 0.007 |
| Sex, female | 7 (25.9%) | 204 (54.7%) | |
| Height (cm) | 171.41 ± 10.50 | 166.75 ± 9.07 | 0.011 |
| Weight (kg) | 86.52 ± 17.02 | 76.22 ± 13.94 | < 0.001 |
| Body mass index (kg/m²) | 29.33 ± 4.77 | 27.43 ± 4.95 | 0.055 |
| ASA I | 5 (18.5%) | 141 (37.8%) | 0.002 |
| ASA II | 12 (44.4%) | 183 (49.1%) | |
| ASA III | 10 (37.0%) | 49 (13.1%) | |
| Hypertension | 13 (59.1%) | 77 (33.3%) | 0.029 |
| Diabetes mellitus | 10 (45.5%) | 43 (18.6%) | 0.003 |
| Ankylosing spondylitis | 1 (4.5%) | 1 (0.4%) | 0.037 |
| Upper lip bite test, (grade 3) | 5 (18.5%) | 24 (6.4%) | 0.019 |
| Mallampati class IV | 10 (37.0%) | 33 (8.8%) | 0.001 |
| Mentohyoid distance (cm) | 5.56 ± 0.80 | 5.88 ± 0.69 | 0.022 |
| Skin-to-epiglottis distance (SED) (cm) | 2.02 ± 0.36 | 1.81 ± 0.25 | 0.007 |
| Skin-to-thyroid cartilage distance (cm) | 1.12 ± 0.28 | 1.00 ± 0.20 | 0.004 |
| Hyomental distance (extension) (cm) | 7.41 ± 0.70 | 7.06 ± 0.74 | 0.018 |
| Intraoperative airway management | |||
| Airway adjunct used | 23 (85.2%) | 59 (15.8%) | < 0.001 |
| BURP maneuver performed | 12 (44.4%) | 58 (15.5%) | < 0.001 |
| Bougie used | 9 (33.3%) | 6 (1.6%) | < 0.001 |
| Lever laryngoscope used | 5 (18.5%) | 4 (1.1%) | < 0.001 |
| Videolaryngoscope used (rescue) | 4 (14.8%) | 3 (0.8%) | < 0.001 |
Comorbidity data were available for 22/27 DMV patients and 231/373 non-DMV patients. The upper section of the table lists preoperative characteristics, bedside airway tests, and ultrasonographic measurements assessed before induction. The lower section reports intraoperative airway management variables — airway adjunct use, BURP maneuver, bougie use, levering laryngoscope use, and rescue videolaryngoscopy — which represent intraoperative management responses to mask ventilation difficulty rather than preoperative predictors. These variables are presented descriptively to characterize the clinical course of DMV events and should not be interpreted as predictors of DMV
Abbreviations: DMV difficult mask ventilation, BURP backward-upward-rightward pressure
Bedside airway assessment tests and airway management
ULBT grade 3 was more frequent among patients with DMV than among those without DMV (5/27 [18.5%] vs. 24/373 [6.4%]; p = 0.019), yielding 18.5% sensitivity and 93.6% specificity for DMV in the study cohort. Mallampati class IV was also more frequent in the DMV group (10/27 [37.0%] vs. 33/373 [8.8%]; p = 0.001) and demonstrated high sensitivity (85.2%) with limited specificity (39.1%) for DMV. Mentohyoid distance was lower in patients with DMV (5.56 ± 0.80 vs. 5.88 ± 0.69 cm; p = 0.022). Rescue airway maneuvers and adjuncts were used more frequently in the DMV group, including airway adjuncts, BURP maneuver, bougie, levering laryngoscope, and video laryngoscopy (Table 5). These variables represent management responses to mask ventilation difficulty rather than preoperative predictors of DMV, and are reported descriptively to characterize the clinical course of DMV events.
Ultrasonographic airway assessment and ROC analysis
On ultrasonography, SED and the skin-to-thyroid cartilage distance were higher in patients with DMV than in those without DMV (2.02 ± 0.36 vs. 1.81 ± 0.25 cm; and 1.12 ± 0.28 vs. 1.00 ± 0.20 cm, respectively). Hyomental distance in the extended head position was also greater in the DMV group (7.41 ± 0.70 vs. 7.06 ± 0.74 cm). In ROC analysis, SED demonstrated only modest discrimination for DMV (AUC 0.689, SE 0.062; 95% CI 0.568–0.810), with an optimal cutoff of 1.89 cm (62% sensitivity; 63% specificity). The skin-to-thyroid cartilage distance showed similar performance (AUC 0.649, SE 0.062; 95% CI 0.528–0.771), with a cutoff of 1.06 cm (61% sensitivity; 63% specificity). Hyomental distance in the extended position yielded an AUC of 0.655 (SE 0.054; 95% CI 0.550–0.760), with a cutoff of 7.31 cm (68% sensitivity; 63% specificity) (Table 6) (Fig. 7).
Table 6.
ROC analysis of selected predictors for difficult mask ventilation
| Predictor | AUC | SE | p-value | 95% CI (lower) | 95% CI (upper) | Cutoff | Sensitivity | Specificity |
|---|---|---|---|---|---|---|---|---|
| Skin to epiglottis distance (SED) (cm) | 0.689 | 0.062 | 0.001 | 0.568 | 0.810 | 1.89 | 0.62 | 0.63 |
| Skin to thyroid cartilage distance (cm) | 0.649 | 0.062 | 0.009 | 0.528 | 0.771 | 1.06 | 0.61 | 0.63 |
| Hyomental distance (extension) (cm) | 0.655 | 0.054 | 0.007 | 0.550 | 0.760 | 7.31 | 0.68 | 0.63 |
Fig. 7.
Receiver operating characteristic (ROC) curves for ultrasonographic predictors of difficult mask ventilation. ROC curves illustrating the discriminatory performance of selected ultrasonographic parameters for the prediction of difficult mask ventilation (DMV), defined as requiring two-handed mask ventilation or inability to achieve adequate ventilation. All three parameters demonstrated modest discrimination for DMV. Skin-to-epiglottis distance (SED) yielded an AUC of 0.689 (95% CI 0.568–0.810), with a cutoff of 1.89 cm (sensitivity 62%; specificity 63%). Skin-to-thyroid cartilage distance showed an AUC of 0.649 (95% CI 0.528–0.771), with a cutoff of 1.06 cm (sensitivity 61%; specificity 63%). Hyomental distance in the extended head position yielded an AUC of 0.655 (95% CI 0.550–0.760), with a cutoff of 7.31 cm (sensitivity 68%; specificity 63%). Overall, ultrasonographic parameters demonstrated lower discriminative performance for DMV than for difficult intubation. The diagonal dashed line represents the reference line of no discrimination (AUC = 0.50). AUC, area under the curve; CI, confidence interval; DMV, difficult mask ventilation; SED, skin-to-epiglottis distance
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Overall, ultrasonographic predictors showed lower and less precise discriminative performance for DMV than for difficult intubation, consistent with the exploratory nature of this secondary analysis.
Discussion
The present prospective observational study evaluated the predictive performance of preoperative airway ultrasonography for difficult intubation and for difficult mask ventilation in a heterogeneous elective surgical cohort. Among the parameters evaluated, the skin-to-epiglottis distance (SED) yielded the highest point-estimate discrimination for difficult intubation, while the modified Mallampati classification and the upper lip bite test were the only bedside assessments significantly associated with the outcome. Predictors of difficult mask ventilation, by contrast, followed a clearly different pattern dominated by demographic and comorbid factors rather than by any single dominant ultrasound parameter, supporting the view that difficult intubation and difficult mask ventilation represent related but non-identical clinical phenotypes [18, 19]. Given the limited number of difficult intubation events and the single-center exploratory design, these observations should be interpreted as hypothesis-generating rather than as definitive estimates of diagnostic accuracy.
Our findings are consistent with a growing body of literature suggesting that SED is among the most informative ultrasonographic markers of difficult laryngoscopy and intubation, although reported thresholds vary substantially across populations and measurement protocols [9, 10, 12, 15]. The point estimate observed in our cohort (AUC 0.91) lies at the upper end of values previously reported and most plausibly reflects an optimistic estimate in the setting of only 20 difficult intubation events; the width of the corresponding confidence interval, with an upper bound reaching 1.000, supports this interpretation. We therefore avoid framing SED as a stand-alone diagnostic test and instead position it as one informative component of a broader anatomical phenotype that includes increased anterior soft-tissue thickness, increased tongue thickness, and a deeper pre-epiglottic space, all of which differed between groups in our analysis [21, 22]. Such a soft-tissue phenotype is mechanistically plausible because cumulative anterior neck thickness may impede direct laryngoscopic alignment of the oral, pharyngeal, and laryngeal axes and can be only partially inferred from surface landmarks alone [6, 8].
The limited discriminative performance of most conventional bedside tests observed in this study is consistent with prior evidence syntheses highlighting the modest sensitivity, variable specificity, and substantial interobserver variability of these tools [3–5]. Tests such as the Mallampati classification and most distance-based measurements depend on patient cooperation, head and neck positioning, and examiner technique, which may attenuate their reliability when used in isolation. In our cohort, the upper lip bite test and the modified Mallampati classification were associated with difficult intubation, whereas thyromental, sternomental, interincisor, and mentohyoid distances were not. The upper lip bite test may capture a functional combination of mandibular mobility and dentition that is not fully reflected in static distance measurements [23]. Even so, the discriminative performance of these bedside tests remained lower than that of the most informative sonographic parameters, supporting the view that ultrasonography may provide additional anatomical information that is not readily captured by surface-based clinical examination — while remaining itself an operator-dependent technique.
Importantly, the recent literature has increasingly moved away from single-parameter sonographic predictors and towards multiparametric airway-assessment scores that integrate ultrasound measurements with clinical variables. Such composite approaches appear to provide more stable and clinically useful predictive frameworks than any single measurement and are also more readily aligned with contemporary videolaryngoscopy-based airway management [11, 16, 24]. Although the present study was not designed to develop or validate a multiparametric model, the consistency between SED and several other anatomical measurements in our cohort supports the rationale for such composite approaches and reinforces the view that no single parameter — including SED — should be treated as a definitive predictor in isolation. Future work should focus on multiparametric ultrasound-and-clinical models, prospectively externally validated and ideally evaluated against videolaryngoscopic outcomes rather than direct laryngoscopy alone.
A particularly informative finding of the present study is the divergence between predictors of difficult intubation and predictors of difficult mask ventilation. Difficult mask ventilation appeared to be more strongly related to demographic characteristics, comorbid conditions, and broader anatomical features rather than to any single dominant sonographic parameter. Older age, male sex, higher body weight, and a higher prevalence of hypertension and diabetes mellitus were observed among patients with difficult mask ventilation, alongside higher Mallampati grades and modest associations with several ultrasound and anthropometric measures [20, 25, 26]. This pattern is consistent with a multifactorial mechanism of mask ventilation difficulty and supports the concept that, although difficult intubation and difficult mask ventilation may coexist within high-risk airway phenotypes, they are not driven by identical determinants [19]. For this reason, difficult mask ventilation was treated as a secondary, exploratory outcome and was reported descriptively rather than through a separate predictive model.
The clinical implications of these findings should be framed cautiously. Sonographic measurement of SED — and more broadly, structured assessment of the anterior neck soft tissue — may contribute incremental anatomical information that complements, but does not replace, conventional bedside airway evaluation. In selected patients, particularly those with multiple risk factors or borderline bedside findings, sonographic assessment may help refine preoperative risk perception and inform planning of airway equipment and personnel [2]. However, the present results are not sufficient to recommend SED, or any single ultrasound parameter, as a stand-alone screening test or as an indication for advanced airway techniques. We therefore view our findings as supportive of further evaluation of multiparametric, ultrasound-augmented airway assessment within prospectively designed studies that incorporate external validation and contemporary videolaryngoscopy-based airway management.
Strengths and limitations
This study has several strengths, including a prospective design, a relatively large overall sample size (n = 400), standardized preoperative bedside and ultrasound assessments, and complete blinding of the operator performing the ultrasound evaluation to intraoperative airway outcomes. Both difficult intubation and difficult mask ventilation were prespecified outcomes, and the analytical strategy was planned a priori.
Several limitations should nevertheless be acknowledged. First, the primary outcome — difficult intubation defined as the requirement for two or more intubation attempts — is an operational definition that captures clinically relevant procedural difficulty and escalation in airway management, but does not exclusively reflect anatomical difficulty. Operator experience, technique, patient positioning, and clinical decision-making may all influence the number of attempts undertaken before successful intubation. A definition based on the laryngoscopic view (e.g., Cormack–Lehane grade) would more directly capture purely anatomical difficulty, and our results should not be extrapolated to alternative outcome definitions without further evaluation. This limitation should be kept in mind when interpreting all primary endpoint analyses.
Second, the absolute number of difficult intubation events was low (n = 20; 5.0% of the cohort), which limits the precision and stability of the ROC-derived performance estimates and increases the risk of optimistic point estimates, particularly for the strongest single predictor (SED). The wide confidence intervals around the AUC estimates — including an upper bound reaching 1.000 for SED — should be interpreted with this in mind. To avoid further overfitting and unstable inference, we deliberately did not fit a multivariable prediction model for the primary endpoint.
Third, the eligibility criteria were intentionally restrictive in order to study sonographic airway parameters within a protocolized elective airway-management context. As a consequence, several patient groups in whom airway difficulty is most clinically pressing — including patients with morbid obesity, ASA IV physical status, anticipated difficult airway, planned awake intubation, marked craniofacial pathology, or significant cervical spine abnormalities — were not represented in our cohort. Our findings therefore cannot be extrapolated to these populations, in which both the prevalence and the predictors of difficult airway management are likely to differ substantially.
Fourth, external validation of the proposed SED cutoff value (2.14 cm) was not performed, and this threshold should not be applied uncritically to other patient populations or measurement protocols. Reported SED thresholds in the literature vary considerably according to head position, transducer orientation, anatomical reference point, and outcome definition, and any clinical use of a specific cutoff requires further validation.
Fifth, although a Macintosh-based direct laryngoscopy approach was used as the initial intubation technique in accordance with our institutional standard at the time of the study, contemporary practice is increasingly oriented towards videolaryngoscopy. The relationship between sonographic airway measurements and videolaryngoscopic outcomes therefore warrants dedicated evaluation in future work [16].
Finally, the trial was registered at ClinicalTrials.gov after study initiation. This retrospective registration is reported transparently and does not affect data integrity or the prespecified analyses, but it is acknowledged as a procedural limitation.
Conclusions
In this prospective observational study, preoperative airway ultrasonography — and in particular the skin-to-epiglottis distance — yielded the highest point-estimate discrimination for difficult intubation among the parameters evaluated and may provide useful supplementary anatomical information when interpreted alongside conventional bedside airway assessment. Predictors of difficult mask ventilation followed a clearly different pattern, dominated by demographic, comorbid, and broader anatomical factors, supporting the view that difficult intubation and difficult mask ventilation represent related but non-identical clinical phenotypes. Given the limited number of difficult intubation events, the single-center design and the absence of external validation, these findings should be regarded as hypothesis-generating rather than definitive. Multicenter prospective studies — ideally incorporating multiparametric ultrasound-and-clinical models, contemporary videolaryngoscopy-based airway management, broader eligibility criteria, and external validation of proposed cutoff values — are warranted to clarify the role of preoperative airway ultrasonography in routine clinical practice.
Acknowledgements
Not applicable.
Abbreviations
- ASA
American Society of Anesthesiologists
- BURP
Backward-upward-rightward pressure
- CI
Confidence interval
- DMV
Difficult mask ventilation
- IQR
Interquartile range
- PES
Pre-epiglottic space depth
- ROC
Receiver operating characteristic
- SD
Standard deviation
- SED
Skin-to-epiglottis distance
- SE
Standard error
- SpO₂
Peripheral oxygen saturation
- ULBT
Upper lip bite test
- AUC
Area under the curve
- BMI
Body mass index
Authors' contributions
All authors had full access to the data, contributed to the work, and approved the final version for publication, and took responsibility for its accuracy and completeness.Concept or design of the study: ST, AG, CBData Collection and/or Processing: ST, AGAnalysis or interpretation of data: ST, AGLiterature Research: AGWriting Manuscript: ST, AG, CB.Critical revision for important intellectual content: ST, CB.
Funding
This study received no external funding.
Data availability
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
This study was approved by the Institutional Ethics Committee of Kütahya Health Sciences University (approval no. 2023/10–19; 06 September 2023) and was conducted in accordance with the principles of the Declaration of Helsinki. Written informed consent was obtained from all participants prior to enrollment.
Consent for publication
Written informed consent for publication of the images shown in Figs. 4, 5, 6 and 7 was obtained from the individual depicted.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.