Prediction of Difficult Airways in Elderly Patients Using Bedside Ultrasound: A Prospective Single-Blind Observational Study

Prediction of Difficult Airways in Elderly Patients Using Bedside Ultrasound: A Prospective Single-Blind Observational Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Prediction of Difficult Airways in Elderly Patients Using Bedside Ultrasound: A Prospective Single-Blind Observational Study Bin LIU, Qingda WU, Wuhua MA, Lu CHEN, Ruiming DU, Qi ZOU, Zhenhao DING, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6804003/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose Several ultrasound predictors have been shown to be useful for predicting difficult airways in adult patients. However, it remains uncertain whether these predictors can predict difficult airways with comparable accuracy in elderly patients. The primary objective of this study was to evaluate the predictive value of ultrasound predictors for difficult laryngoscopy and difficult intubation in elderly patients. Methods This was a prospective, single-blind observational study in which 242 elderly patients scheduled for elective surgery under general anaesthesia with endotracheal intubation were enrolled. During the preanaesthesia phase, demographic information, classical clinical predictors, and ultrasound predictors were collected. The ultrasound predictors included mandibular condylar translation distance (MCTD), tongue thickness (TT), tongue volume (TV), hyomental distance in the extended position (HMDe), and hyomental distance ratio (HMDR). After anaesthesia induction, laryngoscopic views were graded, and intubation difficulty was scored. The diagnostic value of each parameter for difficult laryngoscopy and difficult intubation was evaluated via receiver operating characteristic (ROC) curves. The primary outcome was difficult laryngoscopy, and the secondary outcome was difficult intubation. Results The final analysis included 226 elderly patients, 44 (19.5%) of whom experienced difficult laryngoscopy and 25 (11.1%) of whom experienced difficult intubation. There were significant differences between elderly patients with and without difficult laryngoscopy, as well as with and without difficult intubation in the following ultrasound predictors: MCTD, TT, HMDe, and HMDR. Compared with the other predictors, the mandibular condylar translation distance had the highest area under the receiver operating characteristic curve (AUC) for both difficult laryngoscopy (AUC 0.89; 95% CI: 0.84–0.94; P < 0.001) and difficult intubation (AUC 0.91; 95% CI: 0.86–0.97; P < 0.001). Conclusion Ultrasonic measurements of the mandibular condylar translation distance, the hyomental distance ratio, the hyomental distance in the extended position, and tongue thickness can be used to predict difficult laryngoscopy and difficult intubation in elderly patients. Notably, the mandibular condylar translation distance demonstrated the highest predictive value for difficult laryngoscopy and difficult intubation in elderly patients. Study registration Retrospectively registered at www.chictr.org.cn (ChiCTR2300076196), 27 September 2023. Elderly Ultrasonography Airway management Laryngoscopy Intubation Figures Figure 1 Figure 2 Figure 3 Introduction Owing to age-related pathological, anatomical, and cognitive changes, 1 – 8 elderly patients are significantly more likely to experience difficult airways than the general population. 1 , 2 , 9 , 10 , 11 Unanticipated difficult laryngoscopy (DL) and difficult intubation (DI) are serious problems in elderly patients, potentially leading to adverse outcomes such as death, brain injury, cardiopulmonary arrest, airway trauma, and dental damage. 1 , 9 , 10 However, predicting difficult laryngoscopy and difficult intubation in elderly patients remains challenging because of the limited research on difficult airways in elderly patients. The accurate prediction of difficult airways is crucial for ensuring perioperative safety in elderly patients. Although current guidelines offer various methods for predicting difficult airways, including anatomical measurements, ultrasonic measurements, and comprehensive scores, 9 , 10 no single method has yet been universally accepted as the best. As a useful, simple, and noninvasive bedside tool, ultrasound has been proposed as a clinical adjunct and is used for airway management. In recent years, several studies have identified several ultrasound predictors with predictive value for difficult laryngoscopy or difficult intubation. 12 – 14 The ultrasound predictors that are widely used for airway assessment include mandibular condylar translation distance (MCTD), 15 tongue thickness (TT), 11 tongue volume (TV), 16 , 17 the hyomental distance in the extended position (HMDe), and the hyomental distance ratio (HMDR). 18 – 20 However, most of these studies are limited to specific patient groups, and few have focused on elderly patients. The predictive value of these predictors for difficult laryngoscopy and difficult intubation in elderly patients remains unclear. Therefore, identifying rapid and accurate predictive methods for difficult airways in elderly patients remains an important goal. Hence, this study aimed to investigate the predictive value of these ultrasound predictors for difficult laryngoscopy and difficult intubation in elderly patients. Materials and methods This study was approved by the Ethics Committee of the Second Affiliated Hospital of Shantou University Medical College (No. 2022 − 117) and retrospectively registered at chictr.org.cn on 27 September 2023 (No. ChiCTR2300076196). Written informed consent was obtained from all participants prior to enrollment. Patients This prospective, single-blind observational study was implemented from October 1, 2022, to June 1, 2024. Patients aged 60 to 89 years with American Society of Anesthesiologists (ASA) physical status Ⅰ to Ⅲ, who were scheduled for elective surgery under general anaesthesia with endotracheal intubation, were enrolled in this study. Patients with conditions that could affect measurement accuracy were excluded: (1) maxillofacial or neck deformities, trauma, or tumors; (2) history of neck surgery or tracheostomy; (3) identified difficult airway or history of difficult intubation; (4) withdrawal of consent; (5) suspension of the operation; (6) change of anaesthesia method; and (7) inability to cooperate with the examination. Classic clinical airway assessments All airway assessments were conducted during the preoperative visit on the day before surgery. After thorough communication with the patients, routine measurements were performed in the ward. Classic clinical airway assessments include interincisal distance (IID), 21 , 22 modified Mallampati score (MMS), 21 – 24 sternomental distance (SMD), 21 , 22 and thyromental distance (TMD). 21 , 22 , 25 The interincisal distance was measured as the distance between the upper and lower incisors at the midline with the mouth fully open. The MMS was graded on the basis of the visibility of pharyngeal structures when the patient was seated upright, opened the mouth, and fully extended the tongue without vocalization, and patients were classified into four grades. The sternomental distance was measured from the superior border of the manubrium sterni to the mentum with the mouth closed and the neck fully extended. The thyromental distance was measured from the thyroid notch to the inferior border of the mentum with the mouth closed and the neck fully extended. Ultrasound measurements An ultrasound machine (Navi, Wisonic) equipped with a low-frequency convex array probe (1–5 MHz) and a high-frequency linear array probe (6–15 MHz) was used for the measurements. The ultrasonographic image acquisition and measurement were performed by an anesthesiologist who had conducted more than 60 ultrasound assessments of airway parameters. This anesthesiologist successfully passed the credentialing committee's evaluation, with a verified measurement error rate of less than 5%. To ensure the objectivity of the measurement data, the anesthesiologist performing the ultrasonographic measurement did not participate in airway management. Measurement of mandibular condylar translation distance: 15 patients were seated upright, and a high-frequency linear array probe was placed transversely at the level of the zygomatic arch. The probe was kept perpendicular to the ear’s skin, ensuring that there was no relative movement. Patients were asked to open and close their mouths (Figs. 1 a, 1 c). During the opening process, the direction and height of the probe were adjusted to ensure that the probe did not drop below the condyle, allowing for accurate dynamic assessment of MCTD (Figs. 1 b, 1 d). Measurement of tongue thickness: 11 Patients were positioned supine with their heads fully extended without a pillow, and they were instructed to keep their mouths closed, with the tongue tip lightly touching the incisors and without vocalization (Fig. 1 e). The low-frequency probe was subsequently placed in the midsagittal plane under the chin and adjusted to visualize the entire tongue outline. The maximal vertical distance between the tongue surface and the submental skin surface was measured and defined as tongue thickness (Fig. 1 f). Measurement of tongue volume: 16 , 17 tongue volume is calculated by multiplying the tongue cross-sectional area (TCSA) by the tongue width. The tongue outline was visualized via the same ultrasonic measurement method used for tongue thickness (Fig. 1 e). The midsagittal TCSA was measured by tracing the tongue outline on the ultrasound machine (Fig. 1 f). The probe was subsequently rotated 90° and positioned transversely under the chin to visualize the tongue outline in the transverse plane (Fig. 1 g). Tongue width was determined by measuring the distance between the most distant points on the middle surface of the tongue (Fig. 1 h). Measurement of hyomental distance in the extended position and the hyomental distance ratio: 18 – 20 Patients were placed in the supine position and instructed to gaze straight ahead while maintaining a neutral head position. The low-frequency probe was placed in the midsagittal plane under the chin (Fig. 1 i) and adjusted to visualize the border of the mandible and hyoid bone clearly. The distance between the lower border of the mandible and the upper border of the hyoid bone was defined as the HMDn (Fig. 1 j). The patients were subsequently instructed to fully extend their heads without a pillow (Fig. 1 e), and HMDe was measured using the same method (Fig. 1 f). The hyomental distance ratio was calculated as the ratio of HMDe to HMDn. Induction of general anaesthesia On the day of operation, patients were placed in a supine position with a 10 cm soft pillow underneath. Multiparameter monitoring was initiated, including noninvasive blood pressure, oxygen saturation, electrocardiogram, respiration, and end-tidal carbon dioxide partial pressure. Preoxygenation was performed via a mask for at least 5 minutes. The standard induction protocol consisted of the administration of midazolam (0.04 mg/kg), propofol (1.5 mg/kg), sufentanil (0.3 µg/kg), and rocuronium bromide (0.9 mg/kg). After full muscle relaxation was confirmed, the patient's head was positioned in the sniffing position. 26 Laryngoscopy was then performed by one of four anesthesiologists, each with more than 5 years of clinical experience, using a curved Macintosh blade (size 3 or 4). External laryngeal pressure was permitted to improve the glottic view. An appropriately sized endotracheal tube was subsequently inserted into the trachea. To ensure patient safety, the number of intubation attempts was restricted to three, with each attempt not exceeding 1 minute. Mask ventilation was performed for at least 1 minute between attempts. Video laryngoscopy or other alternative techniques were immediately employed when initial attempts failed. In cases of an emergency airway, the anesthesiologist immediately requested assistance from the difficult airway management team and ventilated the patients via a noninvasive airway tool or method. If ventilation is impossible, a surgical airway should be established immediately. The four anesthesiologists who performed the laryngoscopic examination were blinded to the ultrasonic measurement data. Study end points The primary endpoint was difficult laryngoscopy, and the secondary endpoint was difficult intubation. The visibility of the glottis during each laryngoscopy was graded using the Cormack–Lehane grading. 27 , 28 Grade 3 or 4 was deemed a difficult laryngoscopy. The difficulty of tracheal intubation was scored using the Intubation Difficulty Scale (IDS). 29 A score greater than 5 was deemed a difficult intubation. Although the application of video laryngoscopes has gained increasing popularity, the current standard for determining difficult laryngoscopy remains direct laryngoscopy views. Therefore, this study continues to employ direct laryngoscopy views as the criterion for determining difficult laryngoscopy. Statistical analysis A data analysis and statistical plan was written and filed with a private entity (institutional review board or other) before the data were accessed (approved by the Ethics Committee of the Second Affiliated Hospital of Shantou University Medical College, No. 2022 − 117). Data analysis was performed via SPSS software version 27.0 (IBM, Armonk, NY, USA). The Shapiro‒Wilk normality test was used to assess the normality of continuous variables. Continuous variables are presented as the means, whereas categorical variables are presented as numbers and percentages. Differences in variables were compared between patients with and without difficult laryngoscopy or between patients with and without difficult intubation. For numerical variables, the differences in the means between the two groups were compared via Student’s t-test. For categorical variables, the differences in the means between the two groups were compared via the Chi-square test or Fisher’s exact test. All the statistical tests were two-tailed, and P < 0.05 was considered to be significant. Receiver operating characteristic (ROC) curve analysis and the area under the curve (AUC) were used to assess the diagnostic performance of the predictors for difficult laryngoscopy and difficult intubation. Youden’s Index (the maximum difference between sensitivity and 1 - specificity) was used to determine the optimal cut-off values for predictors to predict difficult laryngoscopy and difficult intubation. The accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the predictors were calculated via QuickCalcs software (GraphPad Inc., La Jolla, CA, USA). Given the limited studies on the use of ultrasound to predict difficult airways in elderly patients, a preliminary experiment was designed. On the basis of preliminary experimental data, the incidence rates of difficult laryngoscopy and difficult intubation in elderly patients at our institution were approximately 20.0% and 11.0%, respectively. Then, PASS software version 11.0 was used to estimate the sample size on the basis of the preliminary experimental data. 30 , 31 With a type I error (alpha) of 0.05 and power (1-beta) of 0.8, the calculations indicated that a minimum of 187 patients were needed for difficult laryngoscopy comparisons and 193 patients for difficult intubation comparisons to detect statistically significant differences between groups. Considering a potential dropout rate of 20%, this study should enrol a total of 242 patients. Results During the observation period (February 2023 to February 2024), a total of 242 elderly patients met the inclusion criteria. Among them, 16 patients were excluded for the following reasons: withdrawal of consent (5 patients), suspension of the operation (3 patients), change of anaesthesia method (2 patients), and inability to cooperate with the examination (6 patients). Ultimately, 226 patients were included in the final analysis. Figure 2 shows the study flow chart and the patient outcomes. Among these patients, 44 (19.5%) cases experienced difficult laryngoscopy: 39 cases with Cormack–Lehane grade 3, and 5 cases with Cormack–Lehane grade 4. Difficult intubation (IDS > 5) was identified in 25 patients (11.1%): 20 cases with Cormack–Lehane grade 3, and 5 cases with grade 4. All 25 cases were successfully intubated, with 24 cases using video laryngoscope and 1 case using flexible fibroscope. None of the patients experienced difficult mask ventilation. The descriptive data of the patients and airway assessment results are presented in Table 1 . Table 1 Comparisons of patients with and without difficult laryngoscopy or patients with and without difficult intubation Variable Difficult laryngoscopy Difficult intubation Yes (n = 44) No (n = 182) P value AUC (95% CI) Yes (n = 25) No (n = 201) P value AUC (95% CI) Sex Male (n) 33 (14.6%) 77 (34.1%) <0.001 (C) 21 (9.3%) 89 (39.4%) <0.001 (C) Female (n) 11 (4.9%) 105 (46.5%) 4 (1.8%) 112 (49.6%) Age (years) 68.6 68.1 0.681 (T) 0.53 (0.43–0.62) 69.7 68.0 0.218 (T) 0.57 (0.46–0.69) Weight (kg) 61.1 59.7 0.445 (T) 0.54 (0.44–0.64) 59.9 60.7 0.680 (T) 0.54 (0.41–0.66) BMI (kg/m 2 ) 23.2 23.1 0.890 (T) 0.52 (0.42–0.62) 22.81 23.2 0.543 (T) 0.51 (0.39–0.63) MMS Class 1 (n) 3 (1.3%) 65 (28.8%) <0.001 (C) 0.73 (0.64–0.80) 2 (0.9%) 60 (26.5%) <0.001 (C) 0.75 (0.65–0.85) Class 2 (n) 9 (4.0%) 45 (19.9%) 3 (1.3%) 51 (22.6%) Class 3 (n) 22 (9.7%) 65 (28.8%) 12 (5.3%) 75 (33.2%) Class 4 (n) 10 (4.4%) 7 (3.1%) 8 (3.5%) 9 (4.0%) IID (cm) 3.8 4.4 <0.001 (T) 0.81 (0.74–0.88) 3.7 4.4 <0.001 (T) 0.83 (0.76–0.91) TMD (cm) 6.0 6.6 <0.001 (T) 0.74 (0.66–0.82) 5.9 6.6 < 0.001 (T) 0.75 (0.66–0.84) SMD (cm) 14.2 15.6 0.048 (T) 0.68 (0.60–0.77) 13.8 15.5 0.060 (T) 0.76 (0.66–0.84) MCTD (cm) 1.1 1.4 <0.001 (T) 0.89 (0.84–0.94) 1.0 1.4 < 0.001 (T) 0.91 (0.86–0.97) TV (cm 3 ) 95.9 97.8 0.562 (T) 0.53 (0.43–0.63) 93.5 97.9 0.287 (T) 0.56 (0.43–0.69) TT (cm) 6.2 5.9 <0.001 (T) 0.67 (0.58–0.77) 6.3 5.9 < 0.001 (T) 0.70 (0.59–0.81) HMDe (cm) 4.5 4..9 <0.001 (T) 0.69 (0.60–0.78) 4.4 4.8 < 0.001 (T) 0.73 (0.62–0.83) HMDR 1.2 1.3 <0.001 (T) 0.73 (0.65–0.81) 1.2 1.3 < 0.001 (T) 0.74 (0.62–0.85) Abbreviations: (T) Two-sided t-test; (C) Chi-square test; BMI, body mass index; MMS, modified Mallampati score; IID, interincisal distance; TMD, thyromental distance; SMD, sternomental distance; MCTD, mandibular condylar translation distance; TV, tongue volume; TT, tongue thickness; HMDe, hyomental distance in the extended position; HMDR, hyomental distance ratio. ROC, receiver operating characteristic; AUC, area under the curve; CI, confidence interval. In the univariate analysis, significant differences were observed in the following predictors for difficult laryngoscopy: sex, MMS, TMD, IID, SMD, MCTD, TT, HMDe, and HMDR. Similar significant predictors for difficult intubation included sex, MMS, TMD, IID, MCTD, TT, HMDe, and HMDR. These indicators are considered effective predictors of difficult laryngoscopy or difficult intubation. In the ROC curve analysis, Table 1 shows that the AUCs of three clinical airway assessment indicators (IID, TMD, and MMS) for predicting difficult laryngoscopy and difficult intubation ranged from 0.7 to 0.9. Additionally, the AUCs of two ultrasonic measurement indicators (MCTD and HMDR) for predicting difficult laryngoscopy and three ultrasonic measurement indicators (HMDR, HMDe, and tongue thickness) for predicting difficult intubation were also within this range. Notably, the AUC of the mandibular condylar translation distance for predicting difficult intubation exceeded 0.9. Figure 3 presents the ROC curves for all indicators (excluding sex due to its dichotomous nature). In this study, the optimal cut-off value of each effective predictor was determined via Youden’s Index. Tables 2 and 3 show the optimal cut-off values of the effective predictors for difficult laryngoscopy and difficult intubation. Additionally, the diagnostic performance metrics (accuracies, sensitivities, specificities, PPVs, and NPVs, all with 95% CIs) of the effective predictors are shown in Tables 2 and 3 . Table 2 Diagnostic validity profiles of effective predictors of difficult laryngoscopy in elderly patients Predictors Accuracy (95% CI) Sensitivity (95% CI) Specificity (95% CI) PPV (95% CI) NPV (95% CI) Sex (male) 0.61 (0.55–0.67) 0.75 (0.59–0.86) 0.58 (0.50–0.65) 0.30 (0.23–0.40) 0.91 (0.83–0.95) Age > 68 years 0.59 (0.53–0.65) 0.45 (0.31–0.61) 0.62 (0.55–0.69) 0.22 (0.15–0.33) 0.82 (0.75–0.88) Weight > 62.2 kg 0.64 (0.58–0.70) 0.48 (0.33–0.63) 0.68 (0.61–0.75) 0.27 (0.18–0.38) 0.84 (0.77–0.90) BMI > 23.8 kg/m 2 0.58 (0.52–0.64) 0.48 (0.33–0.63) 0.61 (0.53–0.68) 0.23 (0.15–0.33) 0.83 (0.75–0.89) Modified Mallampati score > 2 0.63 (0.57–0.69) 0.73 (0.57–0.85) 0.60 (0.53–0.68) 0.31 (0.22–0.41) 0.90 (0.83–0.95) Interincisal distance < 4.0 cm 0.77 (0.71–0.83) 0.66 (0.50–0.79) 0.80 (0.74–0.86) 0.45 (0.32–0.57) 0.91 (0.85–0.95) Thyromental distance < 6.4 cm 0.65 (0.59–0.71) 0.77 (0.62–0.88) 0.62 (0.55–0.69) 0.33 (0.24–0.43) 0.92 (0.85–0.96) Sternomental distance < 14.6 cm 0.66 (0.60–0.72) 0.61 (0.46–0.75) 0.68 (0.60–0.74) 0.31 (0.22–0.42) 0.88 (0.81–0.93) Mandibular condylar translation distance 6.3 cm 0.76 (0.70–0.82) 0.45 (0.31–0.61) a 0.84 (0.77–0.88) 0.40 (0.27–0.55) 0.86 (0.80–0.91) Hyomental distance in the extended position < 4.6 cm 0.69 (0.63–0.75) 0.59 (0.43–0.73) a 0.71 (0.64–0.77) c 0.33 (0.23–0.45) 0.88 (0.81–0.92) Hyomental distance ratio < 1.2 0.69 (0.63–0.75) 0.77 (0.62–0.88) 0.66 (0.59–0.73) bc 0.36 (0.26–0.46) 0.92 (0.86–0.96) Abbreviations: CI, confidence interval; PPV, positive predictive value; NPV, negative predictive value; a Statistically significant difference in sensitivity compared with MCTD ( P < 0.05, chi-square test); b Statistically significant difference in specificity compared with MCTD ( P < 0.05, chi-square test); c Statistically significant difference in specificity compared with tongue thickness ( P < 0.05, chi-square test). Table 3 Diagnostic validity profiles of effective predictors of difficult intubation in elderly patients Predictors Accuracy (95% CI) Sensitivity (95% CI) Specificity (95% CI) PPV (95% CI) NPV (95% CI) Sex (male) 0.59 (0.53–0.65) 0.84 (0.63–0.95) 0.56 (0.49–0.63) 0.19 (0.12–0.28) 0.97 (0.91–0.99) Age > 66 years 0.46 (0.40–0.53) 0.72 (0.50–0.87) 0.42 (0.35–0.46) 0.13 (0.08–0.21) 0.92 (0.84–0.97) Weight > 62.3 kg 0.65 (0.59–0.71) 0.48 (0.28–0.68) 0.67 (0.60–0.73) 0.15 (0.08–0.25) 0.91 (0.85–0.95) BMI > 23.8 kg/m 2 0.60 (0.54–0.66) 0.48 (0.28–0.68) 0.60 (0.53–0.67) 0.13 (0.07–0.22) 0.90 (0.84–0.95) Modified Mallampati score > 2 0.61 (0.55–0.67) 0.80 (0.59–0.92) 0.58 (0.51–0.65) 0.19 (0.12–0.28) 0.96 (0.90–0.98) Interincisal distance < 4.1 cm 0.73 (0.67–0.79) 0.76 (0.54–0.90) 0.73 (0.66–0.79) 0.26 (0.17–0.37) 0.96 (0.91–0.98) Thyromental distance < 6.4 cm 0.61 (0.55–0.67) 0.80 (0.59–0.92) 0.59 (0.52–0.66) 0.19 (0.13–0.29) 0.96 (0.90–0.98) Sternomental distance < 15.3 cm 0.58 (0.52–0.64) 0.84 (0.63–0.95) 0.54 (0.47–0.61) 0.19 (0.12–0.27) 0.96 (0.91–0.99) Mandibular condylar translation distance 6.4 cm 0.81 (0.76–0.86) 0.48 (0.28–0.68) a 0.86 (0.80–0.90) b 0.29 (0.17–0.46) 0.93 (0.88–0.96) Hyomental distance in the extended position < 4.6 cm 0.70 (0.64–0.76) 0.72 (0.50–0.87) a 0.70 (0.63–0.76) c 0.23 (0.15–0.34) 0.95 (0.90–0.98) Hyomental distance ratio < 1.2 0.67 (0.61–0.73) 0.72 (0.50–0.87) a 0.67 (0.60–0.73) c 0.21 (0.13–0.32) 0.95 (0.90–0.98) Abbreviations: CI, confidence interval; PPV, positive predictive value; NPV, negative predictive value; a Statistically significant difference in sensitivity compared with MCTD ( P < 0.05, chi-square test); b Statistically significant difference in specificity compared with MCTD ( P < 0.05, chi-square test). c Statistically significant difference in specificity compared with tongue thickness ( P < 0.05, chi-square test). Discussion This study identified several ultrasound predictors that can help identify elderly patients with difficult laryngoscopy (shortened MCTD and reduced HMDR) or with difficult intubation (shortened MCTD and HMDe, reduced HMDR and increased tongue thickness). This study also demonstrated that the AUC values of these predictors were greater than 0.7, suggesting that these predictors have moderate or higher diagnostic value for difficult laryngoscopy or difficult intubation in elderly patients. Among these predictors, the mandibular condylar translation distance had the highest AUC values for both difficult laryngoscopy and difficult intubation. Among the 226 elderly patients included in this study, 44 experienced difficult laryngoscopy, including 39 with Cormack–Lehane grade 3, and 5 with Cormack–Lehane grade 4. Difficult intubation occurred in 25 of the 44 difficult laryngoscopy cases (56.8%), suggesting that Cormack–Lehane grades 3 and 4 may contribute to a high incidence of difficult intubation in elderly patients. The incidence rates of difficult laryngoscopy and difficult intubation in elderly patients in this study were 19.5% and 11.1%, respectively, which were higher than those reported in adult patients in previous studies and are consistent with findings reported by Moon et al. 2 This higher incidence could be attributed to airway degeneration in elderly patients. Increased parapharyngeal fat, 3 age-related pharyngeal collapse, 4 reduced collagen and elastic fibre content in the hyoepiglottic ligament, 5 , 6 and changes in the head and neck joints 7 , 8 collectively make airway visualization more challenging. Recently, ultrasound-based airway assessment has been proposed as a noninvasive and valuable bedside tool that can serve as a useful complement to clinical airway assessment. However, only a limited number of studies have demonstrated the role of ultrasound in predicting difficult airways. Yao and colleagues 15 reported that ultrasonic measurement of MCTD might be an independent predictor of difficult laryngoscopy. The present study demonstrated that MCTD strongly predicts difficult laryngoscopy and difficult intubation in elderly patients, with a sensitivity of 0.84 for difficult laryngoscopy and 0.96 for difficult intubation, as well as a specificity of 0.83 for difficult laryngoscopy and 0.69 for difficult intubation. Unlike the optimal cut-off value of 1.0 cm for MCTD in adult patients for difficult laryngoscopy reported by Yao et al., 15 the optimal cut-off value for elderly patients in this study was 1.2 cm. This difference may be attributed to age-related changes in condylar morphology and the stretching of ligaments and the temporomandibular joint capsule. 32 , 33 Using the cut-off value of MCTD (1.0 cm) from Yao et al.’s study for airway assessment in elderly patients may result in many elderly patients with difficult airways being misdiagnosed as having nondifficult airways. This study found that higher optimal cut-off values (1.2 cm for difficult laryngoscopy, 1.3 cm for difficult intubation) in elderly patients may improve the diagnostic accuracy of MCTD in predicting difficult laryngoscopy and difficult intubation. As shown in Tables 2 and 3 , the sensitivity of MCTD in diagnosing elderly patients with difficult laryngoscopy was comparable to that of the hyomental distance ratio and higher than those of tongue thickness and HMDe. Moreover, the MCTD exhibited the highest sensitivity among the ultrasound indicators for diagnosing elderly patients with difficult intubation. These findings suggest that the mandibular condylar translation distance has superior diagnostic efficacy in identifying elderly patients with difficult laryngoscopy or difficult intubation. The predictive power of HMDe and hyomental distance ratio for difficult laryngoscopy and difficult intubation has been supported by multiple studies. 18 – 20 This study showed that a lower hyomental distance ratio measured by ultrasound could be used to predict difficult laryngoscopy and difficult intubation in elderly patients effectively. The hyomental distance ratio demonstrated comparable sensitivity to MCTD (0.77 vs 0.84, P > 0.05) for predicting difficult laryngoscopy while maintaining equivalent specificity for difficult intubation (0.67 vs 0.69, P > 0.05). Additionally, a short HMDe was associated with difficult intubation in elderly patients, with an AUC of 0.73. However, the diagnostic value of HMDe for difficult laryngoscopy in elderly patients was relatively low (AUC 0.69), suggesting that its predictive value may require validation through studies with larger sample sizes. In the present study, the optimal cut-off value of HMDe for predicting both difficult laryngoscopy and difficult intubation in elderly patients was 4.6 cm, which was lower than the 5.3 cm reported by Kalezić et al. 20 This difference may arise from the use of different measurement methods. Notably, in Andruszkiewicz et al.’s study, 19 the average HMDe measured by ultrasound was 4.28 cm in the difficult laryngoscopy group and 4.82 cm in the nondifficult laryngoscopy group, which is similar to the findings of the present study (difficult laryngoscopy group: 4.5 cm; nondifficult laryngoscopy group: 4.9 cm). These findings confirm that the classical measurement method may produce higher HMDe values compared with ultrasonic measurement. Yao and colleagues 11 reported that a thicker tongue can be used to predict difficult laryngoscopy and difficult intubation. The present study showed that tongue thickness may be a reliable predictor in elderly patients, with low sensitivity (0.45 for difficult laryngoscopy and 0.48 for difficult intubation) but high specificity (0.84 for difficult laryngoscopy and 0.86 for difficult intubation). As presented in Tables 2 and 3 , tongue thickness demonstrated high specificity and low sensitivity in diagnosing difficult laryngoscopy or difficult intubation in elderly patients, indicating that tongue thickness is more effective in identifying nondifficult laryngoscopy and nondifficult intubation in elderly patients. Notably, tongue thickness showed significantly superior specificity compared with MCTD in diagnosing difficult intubation, suggesting that a composite model combining MCTD and tongue thickness could substantially improve the accuracy of predicting difficult intubation in elderly patients. In contrast to the conclusions reached by Parameswari et al., 16 , 17 the present study revealed that a larger tongue volume was not associated with difficult laryngoscopy or difficult intubation in elderly patients. Possible reasons for the limited predictive value of tongue volume are as follows: (1) the formula for calculating tongue volume may overestimate the actual tongue volume, and (2) age-related changes in tongue muscles may affect tongue volume, 34 potentially reducing the impact on glottic exposure. Consequently, tongue volume may not be suitable for predicting difficult laryngoscopy and difficult intubation in elderly patients. Similar to many previous studies, 21 , 22 the results of the present study confirmed that the IID, TMD, and MMS can also be used to identify elderly patients with difficult laryngoscopy and difficult intubation. Among these parameters, the interincisal distance showed superior predictive ability, with an AUC of 0.81 for difficult laryngoscopy and 0.83 for difficult intubation. Additionally, the interincisal distance demonstrated high diagnostic accuracy and specificity in identifying difficult laryngoscopy and difficult intubation among elderly patients. Therefore, preoperative clinical airway assessment remains crucial for anesthesiologists to identify elderly patients with difficult laryngoscopy and difficult intubation. Although both the interincisal distance and the MCTD are indexes of temporomandibular joint mobility, the MCTD reflects only the anteroinferior sliding mobility of the joint, whereas the interincisal distance reflects both rotational and anteroinferior sliding mobility. In this study, the Spearman correlation coefficient between the interincisal distance and the MCTD was 0.47, indicating that while the two indicators are correlated, they cannot completely substitute for each other. When measuring the interincisal distance in elderly patients, toothless patients are occasionally encountered. In such cases, these patients should wear dentures before measurement to ensure accuracy. This study has revealed two important insights for elderly patients. We identified distinct optimal cut-off values for various indicators in elderly patients, differing from those in adult patients. These specific optimal cut-off values demonstrate higher accuracy in predicting difficult laryngoscopy and difficult intubation in elderly patients. Moreover, this study demonstrated that certain classic clinical airway assessments also have substantial predictive value for difficult laryngoscopy and difficult intubation in elderly patients, which enriches the assessment approach for elderly patients. This study has certain limitations. First, the patients were drawn from routine clinical practice without intentional selection, moreover, patients at higher risk of difficult airways might be more willing to participate in this study due to enhanced risk awareness following health education, which may introduce selection bias. Second, this study has a limited sample size (226 cases) from a single institution and a single ethnic group (Han Chinese). Third, this study was limited to univariate analysis for predicting difficult airways. Future studies should employ multivariable models to comprehensively evaluate the predictive value of combined predictors for difficult laryngoscopy and difficult intubation in elderly patients. Conclusions This study demonstrated that ultrasonic measurements of the mandibular condylar translation distance, the hyomental distance ratio, the hyomental distance in the extended position, and tongue thickness are effective indicators for predicting difficult laryngoscopy and difficult intubation in elderly patients. Among these indicators, the mandibular condylar translation distance had the highest diagnostic value, with optimal cut-off values of 1.2 cm for difficult laryngoscopy and 1.3 cm for difficult intubation, it demonstrated a sensitivity of 0.84 and a specificity of 0.83 for identifying difficult laryngoscopy, as well as 0.96 sensitivity with 0.69 specificity for identifying difficult intubation in elderly patients, highlighting its considerable clinical potential for predicting difficult airways in elderly patients. This study also demonstrated that the interincisal distance, modified Mallampati score, the sternomental distance, and the thyromental distance remain effective in identifying difficult airways among elderly patients. Declarations Study registration Retrospectively registered at www.chictr.org.cn (ChiCTR2300076196), 27 September 2023. Implication Statement This study demonstrated that specific ultrasound predictors can identify difficult airways in elderly patients. Using preoperative bedside ultrasound may improve anaesthesia safety for geriatric surgery. Acknowledgements We are grateful to our colleagues (Department of Anesthesiology, Second Affiliated Hospital of Shantou University Medical College) for their help with sample collection. Author contributions Bin LIU and Qingda WU contributed to study conceptualization, experimental design, data acquisition, analysis, and manuscript drafting. Wuhua MA and Ruiming DU enhanced the methodological rigor and clinical relevance through critical appraisal. Lu CHEN and Qi ZOU developed standardized airway protocols. Zhenhao DING and Xiaoxia ZHENG visualized the data through figure or table creation. Zhenwei ZHENG supervised all the research phases. All the authors participated in manuscript revision and approved the final version. Funding This study was supported by the Clinical Research Fund of Guangdong Medical Association (CN) [No. 2024HY-A4003] and the Shantou Medical Health Science and Technology Project (CN) [No. 169 [2022] - 51]. Data availability The data are provided within the supplementary information files. Ethics approval and consent to participate This study was approved by the Ethics Committee of the Second Affiliated Hospital of Shantou University Medical College (No. 2022-117) and was conducted according to the principles expressed in the Declaration of Helsinki. Written informed consent was obtained from all participants prior to enrollment, and the data were anonymized to ensure confidentiality and privacy compliance. Consent for publication Written informed consent for publication of the clinical details and de-identified images was obtained from all participants. Clinical trial number This study was retrospectively registered with the Chinese Clinical Trial Registry (ChiCTR; registration number: ChiCTR2300076196) on 27 September 2023. Competing interests The authors declare that they have no competing interests. Author details 1 Department of Anesthesiology, Second Affiliated Hospital of Shantou University Medical College, Shantou, China 2 Department of Anesthesiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China References Johnson KN, Botros DB, Groban L, Bryan YF. Anatomic and physiopathologic changes affecting the airway of the elderly patient: implications for geriatric-focused airway management. Clin Interv Aging. 2015;10:1925–34. https://doi.org/10.2147/CIA.S93796 . Moon HY, Baek CW, Kim JS, et al. The causes of difficult tracheal intubation and preoperative assessments in different age groups. Korean J Anesthesiol. 2013;64(4):308–14. https://doi.org/10.4097/kjae.2013.64.4.308 . 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Anesth Analg. 1997;84(3):672–83. https://doi.org/10.1097/00000539-199703000-00038 . Adams MA, McNally DS, Dolan P. Stress' distributions inside intervertebral discs. The effects of age and degeneration. J Bone Joint Surg Br. 1996;78(6):965–72. https://doi.org/10.1302/0301-620x78b6.1287 . Frerk C, Mitchell VS, McNarry AF, et al. Difficult Airway Society 2015 guidelines for management of unanticipated difficult intubation in adults. Br J Anaesth. 2015;115(6):827–48. https://doi.org/10.1093/bja/aev371 . Apfelbaum JL, Hagberg CA, Connis RT, et al. 2022 American Society of Anesthesiologists Practice Guidelines for Management of the Difficult Airway. Anesthesiology. 2022;136(1):31–81. https://doi.org/10.1097/ALN.0000000000004002 . Yao W, Wang B. Can tongue thickness measured by ultrasonography predict difficult tracheal intubation? Br J Anaesth. 2017;118(4):601–9. https://doi.org/10.1093/bja/aex051 . Wang B, Yao W, Xue Q, et al. Nomograms for predicting difficult airway based on ultrasound assessment. BMC Anesthesiol. 2022;22(1):23. https://doi.org/10.1186/s12871-022-01567-y . Srinivasarangan M, Akkamahadevi P, Balkal VC, Javali RH. Diagnostic Accuracy of Ultrasound Measurements of Anterior Neck Soft Tissue in Determining a Difficult Airway. J Emerg Trauma Shock. 2021;14(1):33–7. https://doi.org/10.4103/JETS.JETS_12_20 . Carsetti A, Sorbello M, Adrario E, Donati A, Falcetta S. Airway Ultrasound as Predictor of Difficult Direct Laryngoscopy: A Systematic Review and Meta-analysis. Anesth Analg. 2022;134(4):740–50. https://doi.org/10.1213/ANE.0000000000005839 . Yao W, Zhou Y, Wang B, et al. Anesth Analg. 2017;124(3):800–6. https://doi.org/10.1213/ANE.0000000000001528 . Can Mandibular Condylar Mobility Sonography Measurements Predict Difficult Laryngoscopy?. Parameswari A, Govind M, Vakamudi M. Correlation between preoperative ultrasonographic airway assessment and laryngoscopic view in adult patients: A prospective study. J Anaesthesiol Clin Pharmacol. 2017;33(3):353–8. https://doi.org/10.4103/joacp.JOACP_166_17 . Zheng Z, Ma W, Du R. Effectiveness and validity of midsagittal tongue cross-sectional area and width measured by ultrasound to predict difficult airways. Minerva Anestesiol. 2021;87(4):403–13. https://doi.org/10.23736/S0375-9393.20.14769-2 . Zheng Z, Wang X, Du R, Wu Q, Chen L, Ma W. Effectiveness of ultrasonic measurement for the hyomental distance and distance from skin to epiglottis in predicting difficult laryngoscopy in children. Eur Radiol. 2023;33(11):7849–56. https://doi.org/10.1007/s00330-023-09757-z . Andruszkiewicz P, Wojtczak J, Sobczyk D, Stach O, Kowalik I. Effectiveness and Validity of Sonographic Upper Airway Evaluation to Predict Difficult Laryngoscopy. J Ultrasound Med. 2016;35(10):2243–52. https://doi.org/10.7863/ultra.15.11098 . Kalezić N, Lakićević M, Miličić B, Stojanović M, Sabljak V, Marković D. Hyomental distance in the different head positions and hyomental distance ratio in predicting difficult intubation. Bosn J Basic Med Sci. 2016;16(3):232–6. https://doi.org/10.17305/bjbms.2016.1217 . Khan ZH, Mohammadi M, Rasouli MR, Farrokhnia F, Khan RH. The diagnostic value of the upper lip bite test combined with sternomental distance, thyromental distance, and interincisor distance for prediction of easy laryngoscopy and intubation: a prospective study. Anesth Analg. 2009;109(3):822–4. https://doi.org/10.1213/ane.0b013e3181af7f0d . Kharrat I, Achour I, Trabelsi JJ, et al. Prediction of difficulty in direct laryngoscopy. Sci Rep. 2022;12(1):10722. https://doi.org/10.1038/s41598-022-13523-4 . Khan ZH, Kashfi A, Ebrahimkhani E. A comparison of the upper lip bite test (a simple new technique) with modified Mallampati classification in predicting difficulty in endotracheal intubation: a prospective blinded study. Anesth Analg. 2003;96(2):595–9. https://doi.org/10.1097/00000539-200302000-00053 . Hanouz JL, Bonnet V, Buléon C, et al. Comparison of the Mallampati Classification in Sitting and Supine Position to Predict Difficult Tracheal Intubation: A Prospective Observational Cohort Study. Anesth Analg. 2018;126(1):161–9. https://doi.org/10.1213/ANE.0000000000002108 . Salimi A, Farzanegan B, Rastegarpour A, Kolahi AA. Comparison of the upper lip bite test with measurement of thyromental distance for prediction of difficult intubations. Acta Anaesthesiol Taiwan. 2008;46(2):61–5. https://doi.org/10.1016/S1875-4597(08)60027-2 . Horton WA, Fahy L, Charters P. Defining a standard intubating position using angle finder. Br J Anaesth. 1989;62(1):6–12. https://doi.org/10.1093/bja/62.1.6 . Samsoon GL, Young JR. Difficult tracheal intubation: a retrospective study. Anaesthesia. 1987;42(5):487–90. https://doi.org/10.1111/j.1365-2044.1987.tb04039.x . Yentis SM, Lee DJ. Evaluation of an improved scoring system for the grading of direct laryngoscopy. Anaesthesia. 1998;53(11):1041–44. https://doi.org/10.1046/j.1365-2044.1998.00605.x . Adnet F, Borron SW, Racine SX, et al. The intubation difficulty scale (IDS): proposal and evaluation of a new score characterizing the complexity of endotracheal intubation. Anesthesiology. 1997;87(6):1290–7. https://doi.org/10.1097/00000542-199712000-00005 . Serdar CC, Cihan M, Yücel D, Serdar MA. Sample size, power and effect size revisited: simplified and practical approaches in pre-clinical, clinical and laboratory studies. Biochem Med (Zagreb). 2021;31(1):010502. https://doi.org/10.11613/BM.2021.010502 . Wang YY, Sun RH. Application of PASS in sample size estimation of non-inferiority, equivalence and superiority design in clinical trials. Zhonghua Liu Xing Bing Xue Za Zhi. 2016;37(5):741–4. https://doi.org/10.3760/cma.j.issn.0254-6450.2016.05.032 . Whittaker DK, Davies G, Brown M. Tooth loss, attrition and temporomandibular joint changes in a Romano-British population. J Oral Rehabil. 1985;12(5):407–19. https://doi.org/10.1111/j.1365-2842.1985.tb01546.x . Alexiou K, Stamatakis H, Tsiklakis K. Evaluation of the severity of temporomandibular joint osteoarthritic changes related to age using cone beam computed tomography. Dentomaxillofac Radiol. 2009;38(3):141–7. https://doi.org/10.1259/dmfr/59263880 . Yamaguchi K, Hara K, Nakagawa K et al. Ultrasonography Shows Age-related Changes and Related Factors in the Tongue and Suprahyoid Muscles. J Am Med Dir Assoc. 2021; 22(4): 766 – 72. https://doi.org/10.1016/j.jamda.2020.10.012 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6804003","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":476583110,"identity":"2c1fbd61-53c4-4f17-8bb3-a10a793c5cde","order_by":0,"name":"Bin LIU","email":"","orcid":"","institution":"Second Affiliated Hospital of Shantou University Medical College","correspondingAuthor":false,"prefix":"","firstName":"Bin","middleName":"","lastName":"LIU","suffix":""},{"id":476583111,"identity":"94a583b3-0bee-45ea-8786-4163b94ee963","order_by":1,"name":"Qingda WU","email":"","orcid":"","institution":"Second Affiliated Hospital of Shantou University Medical College","correspondingAuthor":false,"prefix":"","firstName":"Qingda","middleName":"","lastName":"WU","suffix":""},{"id":476583113,"identity":"a478c64c-5bb7-45a8-8fd7-ea419227f4d1","order_by":2,"name":"Wuhua MA","email":"","orcid":"","institution":"First Affiliated Hospital of Guangzhou University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Wuhua","middleName":"","lastName":"MA","suffix":""},{"id":476583114,"identity":"69cbd672-a16b-4471-97d9-e653c1bab5f8","order_by":3,"name":"Lu CHEN","email":"","orcid":"","institution":"Second Affiliated Hospital of Shantou University Medical College","correspondingAuthor":false,"prefix":"","firstName":"Lu","middleName":"","lastName":"CHEN","suffix":""},{"id":476583115,"identity":"da6eca44-62db-40b8-8ca3-57c725ee7241","order_by":4,"name":"Ruiming DU","email":"","orcid":"","institution":"Second Affiliated Hospital of Shantou University Medical College","correspondingAuthor":false,"prefix":"","firstName":"Ruiming","middleName":"","lastName":"DU","suffix":""},{"id":476583116,"identity":"b473dfc2-de73-4741-a9c5-d973161690e4","order_by":5,"name":"Qi ZOU","email":"","orcid":"","institution":"Second Affiliated Hospital of Shantou University Medical College","correspondingAuthor":false,"prefix":"","firstName":"Qi","middleName":"","lastName":"ZOU","suffix":""},{"id":476583117,"identity":"6417ac36-eded-44f2-b6f0-ba12fcfac901","order_by":6,"name":"Zhenhao DING","email":"","orcid":"","institution":"Second Affiliated Hospital of Shantou University Medical College","correspondingAuthor":false,"prefix":"","firstName":"Zhenhao","middleName":"","lastName":"DING","suffix":""},{"id":476583118,"identity":"fe6e4010-8e79-4c27-b727-262c624cdaa2","order_by":7,"name":"Xiaoxia ZHENG","email":"","orcid":"","institution":"Second Affiliated Hospital of Shantou University Medical College","correspondingAuthor":false,"prefix":"","firstName":"Xiaoxia","middleName":"","lastName":"ZHENG","suffix":""},{"id":476583119,"identity":"23c6f94f-6108-45ba-9e56-269e735f9eb1","order_by":8,"name":"Zhenwei ZHENG","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYDACZgYGCYYKGzl+9sbGhx+I13ImzViy53CzsQSxFkkwth1O3HAjvU2AhxjlBsd5D95gOMPMOHPmwzagfXZyug2EtBzmS7ZgqGBj5pdObHtQwJBsbHaAgBazwzxmQL/wsEnOTmw3kGA4kLiNKC2MbRI8BjcPAkkStBhIGNxgJFKL/WEeYwuGMwkGkj2JwEA2IMIvkv1nDG8wVPyv72c//vDhhwo7OYJaQID5D5xpQITyUTAKRsEoGAWEAQCAAz8TUd553gAAAABJRU5ErkJggg==","orcid":"","institution":"Second Affiliated Hospital of Shantou University Medical College","correspondingAuthor":true,"prefix":"","firstName":"Zhenwei","middleName":"","lastName":"ZHENG","suffix":""}],"badges":[],"createdAt":"2025-06-02 16:23:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6804003/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6804003/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85864182,"identity":"57bf0177-2537-457f-85cf-ba8084f58a52","added_by":"auto","created_at":"2025-07-02 12:48:18","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":713000,"visible":true,"origin":"","legend":"\u003cp\u003ePositioning of the ultrasound probe and sonographic images: (a) and (c) the high-frequency probe was placed transversely at the level of the zygomatic arch and kept perpendicular to the ear’s skin; (b) and (d) MCTD, mandibular condylar translation distance, d = d´; (e) the low-frequency probe was placed under the chin in the midsagittal plane with the head in the extended position; (f) TT, tongue thickness; HMDe, hyomental distance in the extended position; TCSA, tongue cross-sectional area; (g) the low-frequency probe was placed transversely under the chin with the head in the extended position; (h) TW, tongue width; (i) the low-frequency probe was placed at the midsagittal plane under the chin with the head in the neutral position; (j) HMDn, hyomental distance in the neutral position.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6804003/v1/b28bd9c3cd833e242a4afc84.jpeg"},{"id":85865421,"identity":"9cb1f514-72f1-4c3c-a94b-e26550f11ac3","added_by":"auto","created_at":"2025-07-02 12:56:18","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":510891,"visible":true,"origin":"","legend":"\u003cp\u003eStudy flow chart and patient outcomes.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6804003/v1/23f8d2b89bb6fed4e06c31d1.jpeg"},{"id":85864186,"identity":"cec0d383-9e46-467f-a96d-963173d7dd01","added_by":"auto","created_at":"2025-07-02 12:48:18","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":513254,"visible":true,"origin":"","legend":"\u003cp\u003eReceiver operating characteristic curve analysis of predictors and their areas under the curve (AUC) for predicting difficult laryngoscopy (a) and difficult intubation (b) in elderly patients. Abbreviations: BMI, body mass index; MMS, modified Mallampati score; IID, interincisal distance; TMD, thyromental distance; SMD, sternomental distance; MCTD, mandibular condylar translation distance; TV, tongue volume; TT, tongue thickness; HMDe, hyomental distance in the extended position; HMDR, hyomental distance ratio.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6804003/v1/3a3335a5ac0212546ef7e3cc.jpeg"},{"id":98622012,"identity":"dea678e5-7170-4d1c-b803-25d861d1a167","added_by":"auto","created_at":"2025-12-19 16:41:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2810156,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6804003/v1/36c0bb19-1513-469a-85e7-909b0cfcaf11.pdf"},{"id":85864181,"identity":"133b68cf-d4e8-411f-ba36-aa65d73379a4","added_by":"auto","created_at":"2025-07-02 12:48:18","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":29464,"visible":true,"origin":"","legend":"","description":"","filename":"Date.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6804003/v1/ccf4bf7d88205032f2058fec.xlsx"},{"id":85864185,"identity":"c5d9c363-535a-4a3d-9d23-6e6eb62227bf","added_by":"auto","created_at":"2025-07-02 12:48:18","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":159455,"visible":true,"origin":"","legend":"","description":"","filename":"Registrationdetails.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6804003/v1/b14808fd1a9d122321a0a08b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prediction of Difficult Airways in Elderly Patients Using Bedside Ultrasound: A Prospective Single-Blind Observational Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOwing to age-related pathological, anatomical, and cognitive changes,\u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3 CR4 CR5 CR6 CR7\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e elderly patients are significantly more likely to experience difficult airways than the general population.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Unanticipated difficult laryngoscopy (DL) and difficult intubation (DI) are serious problems in elderly patients, potentially leading to adverse outcomes such as death, brain injury, cardiopulmonary arrest, airway trauma, and dental damage.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e However, predicting difficult laryngoscopy and difficult intubation in elderly patients remains challenging because of the limited research on difficult airways in elderly patients.\u003c/p\u003e \u003cp\u003eThe accurate prediction of difficult airways is crucial for ensuring perioperative safety in elderly patients. Although current guidelines offer various methods for predicting difficult airways, including anatomical measurements, ultrasonic measurements, and comprehensive scores,\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e no single method has yet been universally accepted as the best. As a useful, simple, and noninvasive bedside tool, ultrasound has been proposed as a clinical adjunct and is used for airway management. In recent years, several studies have identified several ultrasound predictors with predictive value for difficult laryngoscopy or difficult intubation.\u003csup\u003e\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e The ultrasound predictors that are widely used for airway assessment include mandibular condylar translation distance (MCTD),\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e tongue thickness (TT),\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e tongue volume (TV),\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e the hyomental distance in the extended position (HMDe), and the hyomental distance ratio (HMDR).\u003csup\u003e\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e However, most of these studies are limited to specific patient groups, and few have focused on elderly patients. The predictive value of these predictors for difficult laryngoscopy and difficult intubation in elderly patients remains unclear. Therefore, identifying rapid and accurate predictive methods for difficult airways in elderly patients remains an important goal.\u003c/p\u003e \u003cp\u003eHence, this study aimed to investigate the predictive value of these ultrasound predictors for difficult laryngoscopy and difficult intubation in elderly patients.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e This study was approved by the Ethics Committee of the Second Affiliated Hospital of Shantou University Medical College (No. 2022\u0026thinsp;\u0026minus;\u0026thinsp;117) and retrospectively registered at chictr.org.cn on 27 September 2023 (No. ChiCTR2300076196). Written informed consent was obtained from all participants prior to enrollment.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003eThis prospective, single-blind observational study was implemented from October 1, 2022, to June 1, 2024. Patients aged 60 to 89 years with American Society of Anesthesiologists (ASA) physical status Ⅰ to Ⅲ, who were scheduled for elective surgery under general anaesthesia with endotracheal intubation, were enrolled in this study. Patients with conditions that could affect measurement accuracy were excluded: (1) maxillofacial or neck deformities, trauma, or tumors; (2) history of neck surgery or tracheostomy; (3) identified difficult airway or history of difficult intubation; (4) withdrawal of consent; (5) suspension of the operation; (6) change of anaesthesia method; and (7) inability to cooperate with the examination.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eClassic clinical airway assessments\u003c/h3\u003e\n\u003cp\u003eAll airway assessments were conducted during the preoperative visit on the day before surgery. After thorough communication with the patients, routine measurements were performed in the ward. Classic clinical airway assessments include interincisal distance (IID),\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e modified Mallampati score (MMS),\u003csup\u003e\u003cspan additionalcitationids=\"CR22 CR23\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e sternomental distance (SMD),\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e and thyromental distance (TMD).\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e The interincisal distance was measured as the distance between the upper and lower incisors at the midline with the mouth fully open. The MMS was graded on the basis of the visibility of pharyngeal structures when the patient was seated upright, opened the mouth, and fully extended the tongue without vocalization, and patients were classified into four grades. The sternomental distance was measured from the superior border of the manubrium sterni to the mentum with the mouth closed and the neck fully extended. The thyromental distance was measured from the thyroid notch to the inferior border of the mentum with the mouth closed and the neck fully extended.\u003c/p\u003e\n\u003ch3\u003eUltrasound measurements\u003c/h3\u003e\n\u003cp\u003eAn ultrasound machine (Navi, Wisonic) equipped with a low-frequency convex array probe (1\u0026ndash;5 MHz) and a high-frequency linear array probe (6\u0026ndash;15 MHz) was used for the measurements. The ultrasonographic image acquisition and measurement were performed by an anesthesiologist who had conducted more than 60 ultrasound assessments of airway parameters. This anesthesiologist successfully passed the credentialing committee's evaluation, with a verified measurement error rate of less than 5%. To ensure the objectivity of the measurement data, the anesthesiologist performing the ultrasonographic measurement did not participate in airway management.\u003c/p\u003e \u003cp\u003eMeasurement of mandibular condylar translation distance:\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e patients were seated upright, and a high-frequency linear array probe was placed transversely at the level of the zygomatic arch. The probe was kept perpendicular to the ear\u0026rsquo;s skin, ensuring that there was no relative movement. Patients were asked to open and close their mouths (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea, \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). During the opening process, the direction and height of the probe were adjusted to ensure that the probe did not drop below the condyle, allowing for accurate dynamic assessment of MCTD (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb, \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMeasurement of tongue thickness:\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Patients were positioned supine with their heads fully extended without a pillow, and they were instructed to keep their mouths closed, with the tongue tip lightly touching the incisors and without vocalization (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee). The low-frequency probe was subsequently placed in the midsagittal plane under the chin and adjusted to visualize the entire tongue outline. The maximal vertical distance between the tongue surface and the submental skin surface was measured and defined as tongue thickness (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ef).\u003c/p\u003e \u003cp\u003eMeasurement of tongue volume:\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e tongue volume is calculated by multiplying the tongue cross-sectional area (TCSA) by the tongue width. The tongue outline was visualized via the same ultrasonic measurement method used for tongue thickness (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee). The midsagittal TCSA was measured by tracing the tongue outline on the ultrasound machine (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ef). The probe was subsequently rotated 90\u0026deg; and positioned transversely under the chin to visualize the tongue outline in the transverse plane (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eg). Tongue width was determined by measuring the distance between the most distant points on the middle surface of the tongue (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eh).\u003c/p\u003e \u003cp\u003eMeasurement of hyomental distance in the extended position and the hyomental distance ratio:\u003csup\u003e\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e Patients were placed in the supine position and instructed to gaze straight ahead while maintaining a neutral head position. The low-frequency probe was placed in the midsagittal plane under the chin (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ei) and adjusted to visualize the border of the mandible and hyoid bone clearly. The distance between the lower border of the mandible and the upper border of the hyoid bone was defined as the HMDn (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ej). The patients were subsequently instructed to fully extend their heads without a pillow (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee), and HMDe was measured using the same method (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ef). The hyomental distance ratio was calculated as the ratio of HMDe to HMDn.\u003c/p\u003e\n\u003ch3\u003eInduction of general anaesthesia\u003c/h3\u003e\n\u003cp\u003eOn the day of operation, patients were placed in a supine position with a 10 cm soft pillow underneath. Multiparameter monitoring was initiated, including noninvasive blood pressure, oxygen saturation, electrocardiogram, respiration, and end-tidal carbon dioxide partial pressure. Preoxygenation was performed via a mask for at least 5 minutes. The standard induction protocol consisted of the administration of midazolam (0.04 mg/kg), propofol (1.5 mg/kg), sufentanil (0.3 \u0026micro;g/kg), and rocuronium bromide (0.9 mg/kg). After full muscle relaxation was confirmed, the patient's head was positioned in the sniffing position.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e Laryngoscopy was then performed by one of four anesthesiologists, each with more than 5 years of clinical experience, using a curved Macintosh blade (size 3 or 4). External laryngeal pressure was permitted to improve the glottic view. An appropriately sized endotracheal tube was subsequently inserted into the trachea. To ensure patient safety, the number of intubation attempts was restricted to three, with each attempt not exceeding 1 minute. Mask ventilation was performed for at least 1 minute between attempts. Video laryngoscopy or other alternative techniques were immediately employed when initial attempts failed. In cases of an emergency airway, the anesthesiologist immediately requested assistance from the difficult airway management team and ventilated the patients via a noninvasive airway tool or method. If ventilation is impossible, a surgical airway should be established immediately. The four anesthesiologists who performed the laryngoscopic examination were blinded to the ultrasonic measurement data.\u003c/p\u003e\n\u003ch3\u003eStudy end points\u003c/h3\u003e\n\u003cp\u003eThe primary endpoint was difficult laryngoscopy, and the secondary endpoint was difficult intubation. The visibility of the glottis during each laryngoscopy was graded using the Cormack\u0026ndash;Lehane grading.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e Grade 3 or 4 was deemed a difficult laryngoscopy. The difficulty of tracheal intubation was scored using the Intubation Difficulty Scale (IDS).\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e A score greater than 5 was deemed a difficult intubation. Although the application of video laryngoscopes has gained increasing popularity, the current standard for determining difficult laryngoscopy remains direct laryngoscopy views. Therefore, this study continues to employ direct laryngoscopy views as the criterion for determining difficult laryngoscopy.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eA data analysis and statistical plan was written and filed with a private entity (institutional review board or other) before the data were accessed (approved by the Ethics Committee of the Second Affiliated Hospital of Shantou University Medical College, No. 2022\u0026thinsp;\u0026minus;\u0026thinsp;117). Data analysis was performed via SPSS software version 27.0 (IBM, Armonk, NY, USA). The Shapiro‒Wilk normality test was used to assess the normality of continuous variables. Continuous variables are presented as the means, whereas categorical variables are presented as numbers and percentages. Differences in variables were compared between patients with and without difficult laryngoscopy or between patients with and without difficult intubation. For numerical variables, the differences in the means between the two groups were compared via Student\u0026rsquo;s t-test. For categorical variables, the differences in the means between the two groups were compared via the Chi-square test or Fisher\u0026rsquo;s exact test. All the statistical tests were two-tailed, and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered to be significant.\u003c/p\u003e \u003cp\u003eReceiver operating characteristic (ROC) curve analysis and the area under the curve (AUC) were used to assess the diagnostic performance of the predictors for difficult laryngoscopy and difficult intubation. Youden\u0026rsquo;s Index (the maximum difference between sensitivity and 1 - specificity) was used to determine the optimal cut-off values for predictors to predict difficult laryngoscopy and difficult intubation. The accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the predictors were calculated via QuickCalcs software (GraphPad Inc., La Jolla, CA, USA).\u003c/p\u003e \u003cp\u003eGiven the limited studies on the use of ultrasound to predict difficult airways in elderly patients, a preliminary experiment was designed. On the basis of preliminary experimental data, the incidence rates of difficult laryngoscopy and difficult intubation in elderly patients at our institution were approximately 20.0% and 11.0%, respectively. Then, PASS software version 11.0 was used to estimate the sample size on the basis of the preliminary experimental data.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e With a type I error (alpha) of 0.05 and power (1-beta) of 0.8, the calculations indicated that a minimum of 187 patients were needed for difficult laryngoscopy comparisons and 193 patients for difficult intubation comparisons to detect statistically significant differences between groups. Considering a potential dropout rate of 20%, this study should enrol a total of 242 patients.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eDuring the observation period (February 2023 to February 2024), a total of 242 elderly patients met the inclusion criteria. Among them, 16 patients were excluded for the following reasons: withdrawal of consent (5 patients), suspension of the operation (3 patients), change of anaesthesia method (2 patients), and inability to cooperate with the examination (6 patients). Ultimately, 226 patients were included in the final analysis. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the study flow chart and the patient outcomes. Among these patients, 44 (19.5%) cases experienced difficult laryngoscopy: 39 cases with Cormack\u0026ndash;Lehane grade 3, and 5 cases with Cormack\u0026ndash;Lehane grade 4. Difficult intubation (IDS\u0026thinsp;\u0026gt;\u0026thinsp;5) was identified in 25 patients (11.1%): 20 cases with Cormack\u0026ndash;Lehane grade 3, and 5 cases with grade 4. All 25 cases were successfully intubated, with 24 cases using video laryngoscope and 1 case using flexible fibroscope. None of the patients experienced difficult mask ventilation. The descriptive data of the patients and airway assessment results are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparisons of patients with and without difficult laryngoscopy or patients with and without difficult intubation\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eDifficult laryngoscopy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003eDifficult intubation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes (n\u0026thinsp;=\u0026thinsp;44)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo (n\u0026thinsp;=\u0026thinsp;182)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAUC (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes (n\u0026thinsp;=\u0026thinsp;25)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo (n\u0026thinsp;=\u0026thinsp;201)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eAUC (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale (n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33 (14.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77 (34.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001 (C)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e21 (9.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e89 (39.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;0.001 (C)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale (n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11 (4.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e105 (46.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e112 (49.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.681 (T)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.53 (0.43\u0026ndash;0.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e69.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e68.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.218 (T)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.57 (0.46\u0026ndash;0.69)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.445 (T)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.54 (0.44\u0026ndash;0.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e59.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e60.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.680 (T)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.54 (0.41\u0026ndash;0.66)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.890 (T)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.52 (0.42\u0026ndash;0.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e22.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e23.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.543 (T)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.51 (0.39\u0026ndash;0.63)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMMS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClass 1 (n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e65 (28.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001 (C)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.73 (0.64\u0026ndash;0.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e60 (26.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;0.001 (C)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.75 (0.65\u0026ndash;0.85)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClass 2 (n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9 (4.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e45 (19.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e51 (22.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClass 3 (n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22 (9.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e65 (28.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12 (5.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e75 (33.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClass 4 (n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10 (4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7 (3.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8 (3.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9 (4.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIID (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001 (T)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.81 (0.74\u0026ndash;0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;0.001 (T)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.83 (0.76\u0026ndash;0.91)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTMD (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001 (T)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.74 (0.66\u0026ndash;0.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001 (T)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.75 (0.66\u0026ndash;0.84)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSMD (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.048 (T)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.68 (0.60\u0026ndash;0.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e15.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.060 (T)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.76 (0.66\u0026ndash;0.84)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCTD (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001 (T)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.89 (0.84\u0026ndash;0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001 (T)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.91 (0.86\u0026ndash;0.97)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTV (cm\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e95.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e97.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.562 (T)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.53 (0.43\u0026ndash;0.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e93.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e97.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.287 (T)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.56 (0.43\u0026ndash;0.69)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTT (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001 (T)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.67 (0.58\u0026ndash;0.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001 (T)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.70 (0.59\u0026ndash;0.81)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHMDe (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4..9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001 (T)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.69 (0.60\u0026ndash;0.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001 (T)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.73 (0.62\u0026ndash;0.83)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHMDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001 (T)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.73 (0.65\u0026ndash;0.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001 (T)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.74 (0.62\u0026ndash;0.85)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eAbbreviations: (T) Two-sided t-test; (C) Chi-square test; BMI, body mass index; MMS, modified Mallampati score; IID, interincisal distance; TMD, thyromental distance; SMD, sternomental distance; MCTD, mandibular condylar translation distance; TV, tongue volume; TT, tongue thickness; HMDe, hyomental distance in the extended position; HMDR, hyomental distance ratio. ROC, receiver operating characteristic; AUC, area under the curve; CI, confidence interval.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the univariate analysis, significant differences were observed in the following predictors for difficult laryngoscopy: sex, MMS, TMD, IID, SMD, MCTD, TT, HMDe, and HMDR. Similar significant predictors for difficult intubation included sex, MMS, TMD, IID, MCTD, TT, HMDe, and HMDR. These indicators are considered effective predictors of difficult laryngoscopy or difficult intubation. In the ROC curve analysis, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows that the AUCs of three clinical airway assessment indicators (IID, TMD, and MMS) for predicting difficult laryngoscopy and difficult intubation ranged from 0.7 to 0.9. Additionally, the AUCs of two ultrasonic measurement indicators (MCTD and HMDR) for predicting difficult laryngoscopy and three ultrasonic measurement indicators (HMDR, HMDe, and tongue thickness) for predicting difficult intubation were also within this range. Notably, the AUC of the mandibular condylar translation distance for predicting difficult intubation exceeded 0.9. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the ROC curves for all indicators (excluding sex due to its dichotomous nature).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn this study, the optimal cut-off value of each effective predictor was determined via Youden\u0026rsquo;s Index. Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e show the optimal cut-off values of the effective predictors for difficult laryngoscopy and difficult intubation. Additionally, the diagnostic performance metrics (accuracies, sensitivities, specificities, PPVs, and NPVs, all with 95% CIs) of the effective predictors are shown in Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDiagnostic validity profiles of effective predictors of difficult laryngoscopy in elderly patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAccuracy (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSensitivity (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSpecificity (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePPV (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNPV (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (male)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.61 (0.55\u0026ndash;0.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.75 (0.59\u0026ndash;0.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.58 (0.50\u0026ndash;0.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.30 (0.23\u0026ndash;0.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.91 (0.83\u0026ndash;0.95)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u0026thinsp;\u0026gt;\u0026thinsp;68 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.59 (0.53\u0026ndash;0.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.45 (0.31\u0026ndash;0.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.62 (0.55\u0026ndash;0.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.22 (0.15\u0026ndash;0.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.82 (0.75\u0026ndash;0.88)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight\u0026thinsp;\u0026gt;\u0026thinsp;62.2 kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.64 (0.58\u0026ndash;0.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.48 (0.33\u0026ndash;0.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.68 (0.61\u0026ndash;0.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.27 (0.18\u0026ndash;0.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.84 (0.77\u0026ndash;0.90)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026gt;\u0026thinsp;23.8 kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.58 (0.52\u0026ndash;0.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.48 (0.33\u0026ndash;0.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.61 (0.53\u0026ndash;0.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.23 (0.15\u0026ndash;0.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.83 (0.75\u0026ndash;0.89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModified Mallampati score\u0026thinsp;\u0026gt;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.63 (0.57\u0026ndash;0.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.73 (0.57\u0026ndash;0.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.60 (0.53\u0026ndash;0.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.31 (0.22\u0026ndash;0.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.90 (0.83\u0026ndash;0.95)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterincisal distance\u0026thinsp;\u0026lt;\u0026thinsp;4.0 cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.77 (0.71\u0026ndash;0.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.66 (0.50\u0026ndash;0.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.80 (0.74\u0026ndash;0.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.45 (0.32\u0026ndash;0.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.91 (0.85\u0026ndash;0.95)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThyromental distance\u0026thinsp;\u0026lt;\u0026thinsp;6.4 cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.65 (0.59\u0026ndash;0.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.77 (0.62\u0026ndash;0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.62 (0.55\u0026ndash;0.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.33 (0.24\u0026ndash;0.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.92 (0.85\u0026ndash;0.96)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSternomental distance\u0026thinsp;\u0026lt;\u0026thinsp;14.6 cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.66 (0.60\u0026ndash;0.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.61 (0.46\u0026ndash;0.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.68 (0.60\u0026ndash;0.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.31 (0.22\u0026ndash;0.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.88 (0.81\u0026ndash;0.93)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMandibular condylar translation distance\u0026thinsp;\u0026lt;\u0026thinsp;1.2 cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.83 (0.78\u0026ndash;0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.84 (0.69\u0026ndash;0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.83 (0.77\u0026ndash;0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.54 (0.42\u0026ndash;0.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.96 (0.91\u0026ndash;0.98)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTongue thickness\u0026thinsp;\u0026gt;\u0026thinsp;6.3 cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.76 (0.70\u0026ndash;0.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.45 (0.31\u0026ndash;0.61)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.84 (0.77\u0026ndash;0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.40 (0.27\u0026ndash;0.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.86 (0.80\u0026ndash;0.91)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyomental distance in the extended position\u0026thinsp;\u0026lt;\u0026thinsp;4.6 cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.69 (0.63\u0026ndash;0.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.59 (0.43\u0026ndash;0.73)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.71 (0.64\u0026ndash;0.77)\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.33 (0.23\u0026ndash;0.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.88 (0.81\u0026ndash;0.92)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyomental distance ratio\u0026thinsp;\u0026lt;\u0026thinsp;1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.69 (0.63\u0026ndash;0.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.77 (0.62\u0026ndash;0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.66 (0.59\u0026ndash;0.73)\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.36 (0.26\u0026ndash;0.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.92 (0.86\u0026ndash;0.96)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eAbbreviations: CI, confidence interval; PPV, positive predictive value; NPV, negative predictive value; \u003csup\u003ea\u003c/sup\u003eStatistically significant difference in sensitivity compared with MCTD (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, chi-square test); \u003csup\u003eb\u003c/sup\u003eStatistically significant difference in specificity compared with MCTD (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, chi-square test); \u003csup\u003ec\u003c/sup\u003eStatistically significant difference in specificity compared with tongue thickness (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, chi-square test).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDiagnostic validity profiles of effective predictors of difficult intubation in elderly patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAccuracy (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSensitivity (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSpecificity (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePPV (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNPV (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (male)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.59 (0.53\u0026ndash;0.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.84 (0.63\u0026ndash;0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.56 (0.49\u0026ndash;0.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.19 (0.12\u0026ndash;0.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.97 (0.91\u0026ndash;0.99)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u0026thinsp;\u0026gt;\u0026thinsp;66 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.46 (0.40\u0026ndash;0.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.72 (0.50\u0026ndash;0.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.42 (0.35\u0026ndash;0.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.13 (0.08\u0026ndash;0.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.92 (0.84\u0026ndash;0.97)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight\u0026thinsp;\u0026gt;\u0026thinsp;62.3 kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.65 (0.59\u0026ndash;0.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.48 (0.28\u0026ndash;0.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.67 (0.60\u0026ndash;0.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.15 (0.08\u0026ndash;0.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.91 (0.85\u0026ndash;0.95)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026gt;\u0026thinsp;23.8 kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.60 (0.54\u0026ndash;0.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.48 (0.28\u0026ndash;0.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.60 (0.53\u0026ndash;0.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.13 (0.07\u0026ndash;0.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.90 (0.84\u0026ndash;0.95)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModified Mallampati score\u0026thinsp;\u0026gt;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.61 (0.55\u0026ndash;0.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.80 (0.59\u0026ndash;0.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.58 (0.51\u0026ndash;0.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.19 (0.12\u0026ndash;0.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.96 (0.90\u0026ndash;0.98)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterincisal distance\u0026thinsp;\u0026lt;\u0026thinsp;4.1 cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.73 (0.67\u0026ndash;0.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.76 (0.54\u0026ndash;0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.73 (0.66\u0026ndash;0.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.26 (0.17\u0026ndash;0.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.96 (0.91\u0026ndash;0.98)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThyromental distance\u0026thinsp;\u0026lt;\u0026thinsp;6.4 cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.61 (0.55\u0026ndash;0.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.80 (0.59\u0026ndash;0.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.59 (0.52\u0026ndash;0.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.19 (0.13\u0026ndash;0.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.96 (0.90\u0026ndash;0.98)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSternomental distance\u0026thinsp;\u0026lt;\u0026thinsp;15.3 cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.58 (0.52\u0026ndash;0.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.84 (0.63\u0026ndash;0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.54 (0.47\u0026ndash;0.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.19 (0.12\u0026ndash;0.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.96 (0.91\u0026ndash;0.99)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMandibular condylar translation distance\u0026thinsp;\u0026lt;\u0026thinsp;1.3 cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.72 (0.66\u0026ndash;0.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.96 (0.78\u0026minus;1.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.69 (0.62\u0026ndash;0.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.28 (0.19\u0026ndash;0.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.99 (0.95\u0026minus;1.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTongue thickness\u0026thinsp;\u0026gt;\u0026thinsp;6.4 cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.81 (0.76\u0026ndash;0.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.48 (0.28\u0026ndash;0.68)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.86 (0.80\u0026ndash;0.90)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.29 (0.17\u0026ndash;0.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.93 (0.88\u0026ndash;0.96)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyomental distance in the extended position\u0026thinsp;\u0026lt;\u0026thinsp;4.6 cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.70 (0.64\u0026ndash;0.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.72 (0.50\u0026ndash;0.87)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.70 (0.63\u0026ndash;0.76)\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.23 (0.15\u0026ndash;0.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.95 (0.90\u0026ndash;0.98)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyomental distance ratio\u0026thinsp;\u0026lt;\u0026thinsp;1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.67 (0.61\u0026ndash;0.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.72 (0.50\u0026ndash;0.87)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.67 (0.60\u0026ndash;0.73)\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.21 (0.13\u0026ndash;0.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.95 (0.90\u0026ndash;0.98)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eAbbreviations: CI, confidence interval; PPV, positive predictive value; NPV, negative predictive value; \u003csup\u003ea\u003c/sup\u003eStatistically significant difference in sensitivity compared with MCTD (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, chi-square test); \u003csup\u003eb\u003c/sup\u003eStatistically significant difference in specificity compared with MCTD (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, chi-square test). \u003csup\u003ec\u003c/sup\u003eStatistically significant difference in specificity compared with tongue thickness (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, chi-square test).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study identified several ultrasound predictors that can help identify elderly patients with difficult laryngoscopy (shortened MCTD and reduced HMDR) or with difficult intubation (shortened MCTD and HMDe, reduced HMDR and increased tongue thickness). This study also demonstrated that the AUC values of these predictors were greater than 0.7, suggesting that these predictors have moderate or higher diagnostic value for difficult laryngoscopy or difficult intubation in elderly patients. Among these predictors, the mandibular condylar translation distance had the highest AUC values for both difficult laryngoscopy and difficult intubation.\u003c/p\u003e \u003cp\u003eAmong the 226 elderly patients included in this study, 44 experienced difficult laryngoscopy, including 39 with Cormack\u0026ndash;Lehane grade 3, and 5 with Cormack\u0026ndash;Lehane grade 4. Difficult intubation occurred in 25 of the 44 difficult laryngoscopy cases (56.8%), suggesting that Cormack\u0026ndash;Lehane grades 3 and 4 may contribute to a high incidence of difficult intubation in elderly patients. The incidence rates of difficult laryngoscopy and difficult intubation in elderly patients in this study were 19.5% and 11.1%, respectively, which were higher than those reported in adult patients in previous studies and are consistent with findings reported by Moon et al.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e This higher incidence could be attributed to airway degeneration in elderly patients. Increased parapharyngeal fat,\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e age-related pharyngeal collapse,\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e reduced collagen and elastic fibre content in the hyoepiglottic ligament,\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e and changes in the head and neck joints\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e collectively make airway visualization more challenging.\u003c/p\u003e \u003cp\u003eRecently, ultrasound-based airway assessment has been proposed as a noninvasive and valuable bedside tool that can serve as a useful complement to clinical airway assessment. However, only a limited number of studies have demonstrated the role of ultrasound in predicting difficult airways. Yao and colleagues\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e reported that ultrasonic measurement of MCTD might be an independent predictor of difficult laryngoscopy. The present study demonstrated that MCTD strongly predicts difficult laryngoscopy and difficult intubation in elderly patients, with a sensitivity of 0.84 for difficult laryngoscopy and 0.96 for difficult intubation, as well as a specificity of 0.83 for difficult laryngoscopy and 0.69 for difficult intubation. Unlike the optimal cut-off value of 1.0 cm for MCTD in adult patients for difficult laryngoscopy reported by Yao et al.,\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e the optimal cut-off value for elderly patients in this study was 1.2 cm. This difference may be attributed to age-related changes in condylar morphology and the stretching of ligaments and the temporomandibular joint capsule.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e Using the cut-off value of MCTD (1.0 cm) from Yao et al.\u0026rsquo;s study for airway assessment in elderly patients may result in many elderly patients with difficult airways being misdiagnosed as having nondifficult airways. This study found that higher optimal cut-off values (1.2 cm for difficult laryngoscopy, 1.3 cm for difficult intubation) in elderly patients may improve the diagnostic accuracy of MCTD in predicting difficult laryngoscopy and difficult intubation. As shown in Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the sensitivity of MCTD in diagnosing elderly patients with difficult laryngoscopy was comparable to that of the hyomental distance ratio and higher than those of tongue thickness and HMDe. Moreover, the MCTD exhibited the highest sensitivity among the ultrasound indicators for diagnosing elderly patients with difficult intubation. These findings suggest that the mandibular condylar translation distance has superior diagnostic efficacy in identifying elderly patients with difficult laryngoscopy or difficult intubation.\u003c/p\u003e \u003cp\u003eThe predictive power of HMDe and hyomental distance ratio for difficult laryngoscopy and difficult intubation has been supported by multiple studies.\u003csup\u003e\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e This study showed that a lower hyomental distance ratio measured by ultrasound could be used to predict difficult laryngoscopy and difficult intubation in elderly patients effectively. The hyomental distance ratio demonstrated comparable sensitivity to MCTD (0.77 vs 0.84, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) for predicting difficult laryngoscopy while maintaining equivalent specificity for difficult intubation (0.67 vs 0.69, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Additionally, a short HMDe was associated with difficult intubation in elderly patients, with an AUC of 0.73. However, the diagnostic value of HMDe for difficult laryngoscopy in elderly patients was relatively low (AUC 0.69), suggesting that its predictive value may require validation through studies with larger sample sizes. In the present study, the optimal cut-off value of HMDe for predicting both difficult laryngoscopy and difficult intubation in elderly patients was 4.6 cm, which was lower than the 5.3 cm reported by Kalezić et al.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e This difference may arise from the use of different measurement methods. Notably, in Andruszkiewicz et al.\u0026rsquo;s study,\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e the average HMDe measured by ultrasound was 4.28 cm in the difficult laryngoscopy group and 4.82 cm in the nondifficult laryngoscopy group, which is similar to the findings of the present study (difficult laryngoscopy group: 4.5 cm; nondifficult laryngoscopy group: 4.9 cm). These findings confirm that the classical measurement method may produce higher HMDe values compared with ultrasonic measurement.\u003c/p\u003e \u003cp\u003eYao and colleagues\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e reported that a thicker tongue can be used to predict difficult laryngoscopy and difficult intubation. The present study showed that tongue thickness may be a reliable predictor in elderly patients, with low sensitivity (0.45 for difficult laryngoscopy and 0.48 for difficult intubation) but high specificity (0.84 for difficult laryngoscopy and 0.86 for difficult intubation). As presented in Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, tongue thickness demonstrated high specificity and low sensitivity in diagnosing difficult laryngoscopy or difficult intubation in elderly patients, indicating that tongue thickness is more effective in identifying nondifficult laryngoscopy and nondifficult intubation in elderly patients. Notably, tongue thickness showed significantly superior specificity compared with MCTD in diagnosing difficult intubation, suggesting that a composite model combining MCTD and tongue thickness could substantially improve the accuracy of predicting difficult intubation in elderly patients. In contrast to the conclusions reached by Parameswari et al.,\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e the present study revealed that a larger tongue volume was not associated with difficult laryngoscopy or difficult intubation in elderly patients. Possible reasons for the limited predictive value of tongue volume are as follows: (1) the formula for calculating tongue volume may overestimate the actual tongue volume, and (2) age-related changes in tongue muscles may affect tongue volume,\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e potentially reducing the impact on glottic exposure. Consequently, tongue volume may not be suitable for predicting difficult laryngoscopy and difficult intubation in elderly patients.\u003c/p\u003e \u003cp\u003eSimilar to many previous studies,\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e the results of the present study confirmed that the IID, TMD, and MMS can also be used to identify elderly patients with difficult laryngoscopy and difficult intubation. Among these parameters, the interincisal distance showed superior predictive ability, with an AUC of 0.81 for difficult laryngoscopy and 0.83 for difficult intubation. Additionally, the interincisal distance demonstrated high diagnostic accuracy and specificity in identifying difficult laryngoscopy and difficult intubation among elderly patients. Therefore, preoperative clinical airway assessment remains crucial for anesthesiologists to identify elderly patients with difficult laryngoscopy and difficult intubation. Although both the interincisal distance and the MCTD are indexes of temporomandibular joint mobility, the MCTD reflects only the anteroinferior sliding mobility of the joint, whereas the interincisal distance reflects both rotational and anteroinferior sliding mobility. In this study, the Spearman correlation coefficient between the interincisal distance and the MCTD was 0.47, indicating that while the two indicators are correlated, they cannot completely substitute for each other. When measuring the interincisal distance in elderly patients, toothless patients are occasionally encountered. In such cases, these patients should wear dentures before measurement to ensure accuracy.\u003c/p\u003e \u003cp\u003eThis study has revealed two important insights for elderly patients. We identified distinct optimal cut-off values for various indicators in elderly patients, differing from those in adult patients. These specific optimal cut-off values demonstrate higher accuracy in predicting difficult laryngoscopy and difficult intubation in elderly patients. Moreover, this study demonstrated that certain classic clinical airway assessments also have substantial predictive value for difficult laryngoscopy and difficult intubation in elderly patients, which enriches the assessment approach for elderly patients.\u003c/p\u003e \u003cp\u003eThis study has certain limitations. First, the patients were drawn from routine clinical practice without intentional selection, moreover, patients at higher risk of difficult airways might be more willing to participate in this study due to enhanced risk awareness following health education, which may introduce selection bias. Second, this study has a limited sample size (226 cases) from a single institution and a single ethnic group (Han Chinese). Third, this study was limited to univariate analysis for predicting difficult airways. Future studies should employ multivariable models to comprehensively evaluate the predictive value of combined predictors for difficult laryngoscopy and difficult intubation in elderly patients.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study demonstrated that ultrasonic measurements of the mandibular condylar translation distance, the hyomental distance ratio, the hyomental distance in the extended position, and tongue thickness are effective indicators for predicting difficult laryngoscopy and difficult intubation in elderly patients. Among these indicators, the mandibular condylar translation distance had the highest diagnostic value, with optimal cut-off values of 1.2 cm for difficult laryngoscopy and 1.3 cm for difficult intubation, it demonstrated a sensitivity of 0.84 and a specificity of 0.83 for identifying difficult laryngoscopy, as well as 0.96 sensitivity with 0.69 specificity for identifying difficult intubation in elderly patients, highlighting its considerable clinical potential for predicting difficult airways in elderly patients. This study also demonstrated that the interincisal distance, modified Mallampati score, the sternomental distance, and the thyromental distance remain effective in identifying difficult airways among elderly patients.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eStudy registration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRetrospectively registered at www.chictr.org.cn (ChiCTR2300076196), 27 September 2023.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImplication Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study demonstrated that specific ultrasound predictors can identify difficult airways in elderly patients. Using preoperative bedside ultrasound may improve anaesthesia safety for geriatric surgery.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful to our colleagues (Department of Anesthesiology, Second Affiliated Hospital of Shantou University Medical College) for their help with sample collection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBin LIU and Qingda WU contributed to study conceptualization, experimental design, data acquisition, analysis, and manuscript drafting. Wuhua MA and Ruiming DU enhanced the methodological rigor and clinical relevance through critical appraisal. Lu CHEN and Qi ZOU developed standardized airway protocols. Zhenhao DING and Xiaoxia ZHENG visualized the data through figure or table creation. Zhenwei ZHENG supervised all the research phases. All the authors participated in manuscript revision and approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Clinical Research Fund of Guangdong Medical Association (CN)\u0026nbsp;[No. 2024HY-A4003]\u0026nbsp;and the Shantou Medical Health Science and Technology Project (CN)\u0026nbsp;[No. 169 [2022] - 51].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data are provided within the supplementary information files.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study\u0026nbsp;was\u0026nbsp;approved by the Ethics Committee of the Second Affiliated Hospital of Shantou University Medical College (No. 2022-117) and was conducted according to the principles expressed in the Declaration of Helsinki. Written informed consent was obtained from all participants prior to enrollment, and the data were anonymized to ensure confidentiality and privacy compliance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWritten informed consent for publication of the clinical details and de-identified images was obtained from all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was retrospectively registered with the Chinese Clinical Trial Registry (ChiCTR; registration number: ChiCTR2300076196) on 27 September 2023.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eDepartment of Anesthesiology, Second Affiliated Hospital of Shantou University Medical\u0026nbsp;College, Shantou, China\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003eDepartment of Anesthesiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eJohnson KN, Botros DB, Groban L, Bryan YF. 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J Am Med Dir Assoc. 2021; 22(4): 766\u0026thinsp;\u0026ndash;\u0026thinsp;72. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jamda.2020.10.012\u003c/span\u003e\u003cspan address=\"10.1016/j.jamda.2020.10.012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Elderly, Ultrasonography, Airway management, Laryngoscopy, Intubation","lastPublishedDoi":"10.21203/rs.3.rs-6804003/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6804003/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose\u003c/strong\u003e \u003cem\u003eSeveral ultrasound predictors have been shown to be useful for predicting difficult airways in adult patients. However, it remains uncertain whether these predictors can predict difficult airways with comparable accuracy in elderly patients. The primary objective of this study was to evaluate the predictive value of ultrasound predictors for difficult laryngoscopy and difficult intubation in elderly patients.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods \u003c/strong\u003e\u003cem\u003eThis was a prospective, single-blind observational study in which 242 elderly patients scheduled for elective surgery under general anaesthesia with endotracheal intubation were enrolled. During the preanaesthesia phase, demographic information, classical clinical predictors, and ultrasound predictors were collected. The ultrasound predictors included mandibular condylar translation distance (MCTD), tongue thickness (TT), tongue volume (TV), hyomental distance in the extended position (HMDe), and hyomental distance ratio (HMDR). After anaesthesia induction, laryngoscopic views were graded, and intubation difficulty was scored. The diagnostic value of each parameter for difficult laryngoscopy and difficult intubation was evaluated via receiver operating characteristic (ROC) curves. The primary outcome was difficult laryngoscopy, and the secondary outcome was difficult intubation.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e \u003cem\u003eThe final analysis included 226 elderly patients, 44 (19.5%) of whom experienced difficult laryngoscopy and 25 (11.1%) of whom experienced difficult intubation. There were significant differences between elderly patients with and without difficult laryngoscopy, as well as with and without difficult intubation in the following ultrasound predictors: MCTD, TT, HMDe, and HMDR. Compared with the other predictors, the mandibular condylar translation distance had the highest area under the receiver operating characteristic curve (AUC) for both difficult laryngoscopy (AUC 0.89; 95% CI: 0.84–0.94; P \u0026lt; 0.001) and difficult intubation (AUC 0.91; 95% CI: 0.86–0.97; P \u0026lt; 0.001).\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e \u003cem\u003eUltrasonic measurements of the mandibular condylar translation distance, the hyomental distance ratio, the hyomental distance in the extended position, and tongue thickness can be used to predict difficult laryngoscopy and difficult intubation in elderly patients. Notably, the mandibular condylar translation distance demonstrated the highest predictive value for difficult laryngoscopy and difficult intubation in elderly patients.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy registration \u003c/strong\u003e\u003cem\u003eRetrospectively registered at www.chictr.org.cn (ChiCTR2300076196), 27 September 2023.\u003c/em\u003e\u003c/p\u003e","manuscriptTitle":"Prediction of Difficult Airways in Elderly Patients Using Bedside Ultrasound: A Prospective Single-Blind Observational Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-02 12:48:09","doi":"10.21203/rs.3.rs-6804003/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6ac9e91b-3eb8-49d2-9039-6d3e949251de","owner":[],"postedDate":"July 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-01T11:25:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-02 12:48:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6804003","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6804003","identity":"rs-6804003","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}