CLAIR Score: A Novel Risk Prediction Tool for Unmasking Unanticipated Difficult Airways

CLAIR Score: A Novel Risk Prediction Tool for Unmasking Unanticipated Difficult Airways | 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 Article CLAIR Score: A Novel Risk Prediction Tool for Unmasking Unanticipated Difficult Airways Chanatthee Kitsiripant, Wilasinee Jitpakdee, Maliwan Oofuvong, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6273929/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 Background Unanticipated difficult airways remain a significant challenge in anesthesia practice and are associated with increased severe complication risk. In this study, we developed and validated the CLAIR risk prediction tool to enhance early identification of unanticipated difficult airways. Methods This retrospective case-control study analyzed data from 62,111 patients who underwent general anesthesia between 2015 and 2020. Among them, 98 unanticipated difficult airways were identified and matched in a 1:3 ratio with 294 controls. Multivariate logistic regression identified key predictors, forming the CLAIR score, which incorporates coagulopathy, hypocalcemia, female sex, potential airway difficulty, and inexperienced residents. Results The incidence of unanticipated difficult airways was 0.16%. The CLAIR score demonstrated an area under the receiver operating characteristic curve of 0.633, with high sensitivity (98%) despite lower specificity (16%). A cutoff of 0 effectively stratified patients into high (≥ 1), and low (≤-1) risk groups, guiding airway management strategies. Its web-based risk calculator and QR code enhance accessibility for real-time clinical applications. Conclusions The CLAIR score is a simple, practical, and user-friendly tool that improves preoperative risk assessment and preparedness for difficult airways. While further external validation is necessary, its integration into routine anesthesia practice may enhance patient safety and optimize airway management strategies. Health sciences/Medical research Health sciences/Risk factors patient safety preoperative assessment predictors unanticipated difficult airway Figures Figure 1 Figure 2 Figure 3 BACKGROUND Securing a patent airway is a fundamental requirement for safe anesthesia. Unanticipated difficult airways, reported in 1.5–8.5% of cases, pose significant challenges and can result in life-threatening complications [ 1 – 6 ]. The 2015 Perioperative and Anesthetic Adverse Events in Thailand (PAAd Thai) study demonstrated a 2.3% incidence of unanticipated difficult intubation [ 7 ]. Ineffective management of such cases can lead to severe complications, including emergency surgical airway, airway trauma, hypoxic brain injury, and death due to oxygen deprivation [ 8 , 9 ]. Traditional predictive tools, such as the Mallampati score, upper lip bite test (ULBT), interincisor distance (IID), and thyromental distance (TMD), have variable accuracy and relying on a single factor often leads to poor predictive performance [ 10 ]. While comprehensive assessment models integrating multiple factors improve accuracy, they are complex and time-consuming, limiting their practicality in daily practice [ 11 – 14 ]. Advanced airway ultrasound techniques offer promising sensitivity and specificity [ 15 – 17 ] but remain inaccessible in resource-limited settings. A more practical, efficient, and accurate risk stratification tool remains a critical need. This study aims to clarify the predictive factors associated with unanticipated airway difficulties during anesthesia to enhance patient safety and preparedness for critical situations. METHODS This retrospective observational case-control study was conducted at an 858-bed tertiary care teaching hospital in southern Thailand from January 2015 to December 2020. All procedures adhered to relevant laws and institutional guidelines. The study protocol was approved by the institutional review board (approval number 63-560-8-1), which granted a waiver for informed consent due to the study’s retrospective nature design. The privacy rights of all participants were rigorously observed. Patient selection The inclusion comprised patients undergoing general anesthesia with endotracheal intubation for elective or emergency surgeries who encountered difficult airway management, defined as requiring three or more intubation attempts by anesthesia providers. Patients who were already on preoperative mechanical ventilation or had anticipated difficult airways were excluded from the analysis. Matching procedure A rigorous matching algorithm was implemented to minimize selection bias and control for potential confounding variables in the analysis. Cases of difficult airway management were matched with controls who underwent routine airway management, based on age (± 5 years), surgical type, and year, in a 1:3 ratio. For each difficult airway case, three controls were selected: one with a preoperatively anticipated difficult airway and two with normal airway assessments. Definition of unanticipated difficult intubation Unanticipated difficult intubation was defined as three or more attempts at endotracheal tube intubation using direct or video laryngoscopy in a patient not preoperatively identified as having a difficult airway. Intubations were performed by anesthesia personnel with at least one year of experience, including anesthesia residents, nurse anesthetists, and attending anesthesiologists. Potential risk factors and confounding variables Potential predictors included patient, surgical, and anesthesia-related factors, such as sex, age, weight, height, body mass index (BMI), American Society of Anesthesiologists (ASA) physical status, preoperative airway assessment, history of difficult intubation and ventilation, comorbidities (e.g., medical conditions, congenital heart disease, obstructive sleep apnea, head and neck radiation, anatomical abnormalities due to infection, trauma, tumors, or burns, and abnormal laboratory values), type of surgery, laryngoscopic view grades, intubation attempts, intubation devices, incidence of emergency tracheostomy for rescue airway, the clinician’s first intubation attempt, and intubation experience. Sample size determination A sample size calculation estimated that 70 unanticipated difficult airway cases and 280 controls were required to detect an odds ratio of 2.5, assuming a 15% prevalence of exposure among controls, with 80% power and a 0.05 significance level. Based on the institution’s annual incidence of 10–15 cases, a 6-year study period was required. Statistical analysis Statistical analyses were performed using R version 4.3.1 (R Foundation, Vienna, Austria). Descriptive statistics are reported as medians with interquartile ranges for continuous variables and as frequencies with percentages for categorical variables. Associations between categorical variables and difficult intubation were assessed using the chi-squared or Fisher’s exact test, while continuous variables were evaluated with Student’s t-tests or Mann–Whitney U tests, depending on data distribution. Collinearity diagnostics and bivariate correlation matrices were evaluated for all variables. In cases of multicollinearity, only one variable was retained for multivariate analysis. Variables with a p-value < 0.25 in the univariate analysis were considered for inclusion in the initial multivariate logistic regression model. The final regression model was derived using backward selection, retaining all significant variables. The optimal cutoff point was identified using Youden’s index. Statistical significance was defined as a p-value < 0.05. Score derivation and validation The risk prediction score system was developed using predictors derived from the multivariate logistic regression model. Risk scores were calculated by assigning weights to regression coefficients and scaling the total to 5. In the final model, the total predictor score was used to estimate the likelihood of unanticipated difficult airways. Youden’s index determined the cutoff value that maximized specificity and sensitivity. The performance of the final model was reported as the area under the receiver operating characteristic curve (AUC), with an AUC greater than 80 indicating excellent predictive accuracy. RESULTS Among 62,111 patients undergoing general anesthesia over 6 years, 168 cases of difficult airways were identified. After excluding 70 anticipated difficult airway cases, 98 unanticipated difficult airway cases, and 294 matched controls were analyzed (Fig. 1 ), yielding an incidence of 0.16%. Patient demographics and perioperative characteristics are presented in Table 1 . Notably, only 3.1% of patients in the unanticipated difficult airway group were preoperatively assessed as having a probable difficult airway, compared with 16% in the control group (p = 0.002). Most first-attempt intubations (66.1%) were performed by anesthesiology residents. The unanticipated difficult airway group had significantly more intubation attempts (median 4 (3,5) vs. 1 (1,1), p < 0.001) and worse laryngoscopic view grades (p < 0.001). They were also more likely to require video laryngoscope (78.6% vs. 13.7%, p < 0.001). Table 1 Patient demographics and perioperative characteristics Characteristics Unanticipated difficult airway (n = 98) Non-difficult airway (n = 294) p-value Sex 0.243 Male 56 (57.1) 146 (49.7) Female 42 (42.9) 148 (50.3) Age (years) , median (IQR) 55 (38.0, 65.8) 56 (36.2, 64.0) 0.790 Age (years) match ≤ 7 12 (12.2) 34 (11.6) 8–20 3 (3.1) 14 (4.8) 21–64 56 (57.1) 180 (61.2) ≥ 65 27 (27.6) 66 (22.4) Weight (kg) , median (IQR) 58.8 (49.1, 70.0) 59.5 (48.4, 69.0) 0.980 Height (cm) , median (IQR) 160 (152.2,165.9) 158.5 (150,165) 0.346 BMI (kg/m 2 ) median (IQR) 23.3 (19,25.9) 22.7 (19.2,26) 0.494 BMI (kg/m 2 ) 0.286 < 15 8 (8.2) 21 (7.1) 15–29 82 (83.7) 231 (78.6) ≥ 30 8 (8.2) 42 (14.3) ASA classification 0.798 I 2 (2) 13 (4.4) II 52 (53.1) 155 (52.7) III 43 (43.9) 123 (41.8) IV 1 (1) 3 (1) Preoperative probable difficult airway 0.002 No 95 (96.9) 247 (84) Yes 3 (3.1) 47 (16) Modified Mallampati classification 0.911 1–2 79 (80.6) 239 (81.3) 3–4 10 (10.2) 26 (8.8) unknown 9 (9.2) 29 (9.9) Thyromental distance 0.832 3 finger breadths 22 (22.4) 80 (27.2) unknown 9 (9.2) 25 (8.5) Inter-incisor gap 0.824 1–2 cm 7 (7.1) 16 (5.4) 3–4 cm 82 (83.7) 251 (85.4) unknown 9 (9.2) 27 (9.2) Limited neck flexion and extension 1 No 94 (95.9) 284 (96.6) Yes 3 (3.1) 8 (2.7) Cannot evaluate 1 (1) 2 (0.7) Upper lip bite test classification 0.681 1 53 (54.1) 175 (59.5) 2 26 (26.5) 75 (25.5) 3 1 (1) 3 (1) unknown 18 (18.4) 41 (13.9) Facial appearance or syndrome 0.418 Normal 95 (96.9) 289 (98.3) Abnormal 3 (3.1) 5 (1.7) Edentulous 0.840 No 88 (89.8) 268 (91.2) Yes 10 (10.2) 26 (8.8) Overbite 0.250 No 97 (99) 294 (100) Yes 1 (1) 0 (0) Previous history of difficult intubation and ventilation 1 No 98 (100) 293 (99.7) Yes 0 (0) 1 (0.3) Medical conditions 1 No 93 (94.9) 278 (94.9) Yes 5 (5.1) 16 (5.4) Congenital heart disease 0.770 No 95 (96.9) 281 (95.6) Yes 3 (3.1) 13 (4.4) Airway/neck/oral deformity 0.639 No 90 (91.8) 276 (93.9) Yes 8 (8.2) 18 (6.1) Foreign body aspiration 0.438 No 97 (99) 293 (99.7) Yes 1 (1) 1 (0.3) Infection: retropharyngeal abscess, epiglottitis, supraglottitis 1 No 97 (99) 292 (99.3) Yes 1 (1) 2 (0.7) Post-surgical procedure: thyroid, cervical vertebrae 0.504 No 94 (95.9) 286 (97.3) Yes 4 (4.1) 8 (2.7) OSA/Snoring 0.875 No 83 (84.7) 245 (83.3) Yes 15 (15.3) 49 (16.7) Tumors: thyroid, pharynx, larynx and tracheobronchus, esophagus 0.634 No 86 (87.8) 265 (90.1) Yes 12 (12.2) 29 (9.9) Trauma: face, neck 0.643 No 96 (98) 290 (98.6) Yes 2 (2) 4 (1.4) Burns (head, neck, face), smoke inhalation, massive burn 0.261 No 96 (98) 292 (99.3) Yes 2 (2) 2 (0.7) History radiation of head, neck 0.697 No 95 (96.9) 288 (98) Yes 3 (3.1) 6 (2) Laryngeal edema: angioedema, allergic, post rigid bronchoscopy 1 No 97 (99) 292 (99.3) Yes 1 (1) 2 (0.7) Coagulopathy and hypocalcemia 0.102 No 95 (96.9) 292 (99.3) Yes 3 (3.1) 2 (0.7) Type of surgery match Remote 14 (14.3) 41 (13.9) Neuro/Orthopedic 6 (6.1) 18 (6.1) Eye/superficial 12 (12.2) 40 (13.6) ENT 31 (31.6) 90 (30.6) Thoracic/Vascular 12 (12.2) 34 (11.6) Abdomen 23 (23.5) 71 (24.1) Intubation attempts , median (IQR) 4 (3,5) 1 (1,1) < 0.001 Intubation device Direct laryngoscope Video laryngoscope Supraglottic airway device Other Fiberoptic intubation 19 (19.4) 77 (78.6) 6 (6.1) 2 (2) 2 (2) 252 (85.7) 40 (13.7) 4 (1.4) 2 (0.7) 5 (1.7) < 0.001 Emergency tracheostomy No 97 (99) 293 (99.7) 0.439 Yes 1 (1) 1 (0.3) First-attempt intubation personnel 0.152 Anesthesia instructors 9 (9.2) 31 (10.5) Anesthesiology residents 72 (73.5) 187 (63.6) 0.096 Certified registered nurse anesthetists 3 (3.1) 28 (9.5) Nurse anesthetist students 14 (14.3) 48 (16.3) Intubation experience (years) 0.837 20 0 (0) 2 (0.7) Laryngoscopic view < 0.001 Grade 1 10 (10.2) 227 (77.2) Grade 2 14 (14.3) 49 (16.7) Grade 3 43 (43.9) 14 (4.8) Grade 4 30 (30.6) 0 (0) Unknown 1 (1) 4 (1.4) Data are presented as numbers (%) unless otherwise indicated. IQR, interquartile range; BMI, body mass index; ASA, American Society of Anesthesiologists; OSA, obstructive sleep apnea; ENT, ear, nose, and throat. Development of the CLAIR risk prediction tool The initial multivariate model included seven variables with p-values < 0.25: sex, preoperative assessment of probable difficult airway, overbite, coagulopathy, hypocalcemia, first-attempt intubation personnel, and laryngoscopic view. Since laryngoscopic view represents an outcome rather than a predictor, it was excluded from the final model. Table 2 presents the final multivariate analysis, which led to the development of the CLAIR risk score, integrating four key predictors: Coagulopathy and hypoCalcemia (C), Lady (L), potential Airway difficulty (A), and first-attempt intubation by residents (In-experienced Residents) (IR). The score ranged from − 4 to 6 (IQR − 1 to 1), with an AUC was 0.633 (Fig. 2 ). A cutoff score of 0 provided 98% sensitivity and 16% specificity. The CLAIR scores were classified into high (≥ 1), and low (≤ -1) risk groups to optimize airway management strategies. The diagnostic performance of the CLAIR score is detailed in Table 3 . Table 2 Multivariate logistic regression of predictive factors of unanticipated difficult airway (CLAIR score) Predictive factors Coefficient Adjusted OR (95% CI) p- value Risk score C : Coagulopathy and hypo C alcemia 2.36 10.62 (1.27, 88.81) 0.029 5 L: L ady -0.34 0.71 (0.44, 1.14) 0.157 -1 A : potential A irway difficulty -2.04 0.13 (0.04, 0.47) < 0.001 -4 IR: I nexperienced R esidents 0.48 1.62 (0.97, 2.72) 0.063 1 OR, odds ratio; CI, confidence interval. Table 3 Diagnostic performance of the CLAIR score for predicting unanticipated difficult airway Score Sensitivity Specificity PPV NPV Accuracy +LR -LR -4 100.00 0 25.00 NA 50.00 1.00 NA -3 100.00 5.10 25.99 100.00 52.55 1.05 0 -2 97.96 15.65 27.91 95.83 56.80 1.16 0.13 -1 97.96 15.65 27.91 95.83 56.80 1.16 0.13 0 97.96 15.65 27.91 95.83 56.80 1.16 0.13 1 73.47 46.94 31.58 84.15 60.20 1.39 0.57 2 2.04 99.32 50.00 75.26 50.68 2.99 0.99 3 2.04 99.66 66.67 75.32 50.85 6.00 0.98 4 2.04 99.66 66.67 75.32 50.85 6.00 0.98 5 2.04 99.66 66.67 75.32 50.85 6.00 0.98 6 1.02 99.66 50.00 75.13 50.34 3.00 0.99 PPV, positive predictive value; NPV, negative predictive value; +LR, positive likelihood ratio; -LR, negative likelihood ratio. Web-based risk calculator and accessibility The CLAIR score calculator, now a web-based tool, enables clinicians to quickly categorize patients into risk groups for tailored airway management. Accessible via a QR code (Fig. 3 ), the tool supports real-time use during preoperative assessments or emergency scenarios, helping to swiftly identify at-risk patients, optimize resource allocation, and enhance airway management strategies, ultimately improving patient safety and outcomes. DISCUSSION Key findings The CLAIR risk prediction tool represents a significant advancement in identifying unanticipated difficult airways, addressing a critical gap in anesthesia practice. Our study revealed an incidence of unanticipated difficult airways of 0.16%, significantly lower than the 2.3% reported in the 2015 PAAd Thai study [ 7 ]. This discrepancy may be due to the development of preoperative assessment techniques, increased awareness of airway difficulties, or differences in patient populations and clinical settings. However, it also underscores the persistent challenges in airway assessment and highlights the potential value of our novel approach. Interpretation and implications CLAIR score: A paradigm shift in airway risk prediction The CLAIR score demonstrated a moderate predictive performance for unanticipated difficult airways, with an AUC of 0.633. Notably, it maintains a high sensitivity (98%), enabling early identification of at-risk patients. Although its specificity is lower (16%), the model remains a valuable screening tool due to its simplicity, practicality, and ease of use in clinical settings. Unlike traditional models that emphasize anatomical factors, CLAIR incorporates patient, clinical, and procedural elements, aligning with evolving airway management guidelines such as those from the ASA [ 18 ]. By enhancing routine airway assessment and preparedness, the CLAIR score provides a user-friendly approach to improving patient safety and first-attempt success in airway management. The CLAIR score incorporates four key factors: Coagulopathy and hypocalcemia Coagulopathy (abnormal rotational thromboelastometry, international normalized ratio > 1.3, prothrombin time > control by 3 s, or partial thromboplastin time > control by 10 s) and hypocalcemia (serum calcium < 8.2 mg/dL or ionized calcium < 4.4 mg/dL) pose significant challenges in airway management. Coagulopathy increases the risk of bleeding during airway manipulation, whereas hypocalcemia increases neuromuscular excitability, potentially causing masseter spasms despite using muscle relaxants [ 19 ]. These conditions complicate airway management and increase the difficulty of intubation. Including this factor in the CLAIR score emphasizes the importance of a comprehensive preoperative evaluation that extends beyond traditional airway assessment. Lady (female sex) Several studies have identified male sex as a risk factor for both difficult mask ventilation and intubation [ 20 – 22 ]. Moreover, Hindman et al. reported a significantly higher intubation force required in male patients compared to females [ 23 ]. Similarly, our findings suggest that female sex may serve as a protective factor against unanticipated difficult airways. Potential airway difficulty The limited predictive value of conventional preoperative airway assessments, with an observed accuracy of only 3.1% in this study, aligns with findings by Roth et al. [ 24 ]. This underscores the need for a more comprehensive, multimodal approach to identifying risk factors for unanticipated difficult airways. The CLAIR score addresses this limitation by integrating multiple assessment criteria, thereby enhancing prediction accuracy, as evidenced by previous studies [ 25 – 27 ]. Despite routine screening, difficult airway scenarios may still arise unexpectedly, highlighting the importance of heightened vigilance and preparedness. Inexperienced residents Our findings regarding the increased likelihood of unanticipated difficult airways among less experienced anesthesiology residents highlight the significance of ongoing training and supervision. In this study, inexperienced people were defined as having less than one year of intubation experience, including first-year residents, anesthetic nurse students, and medical students. These findings align with the previous studies examining the learning curve in airway management skills. Integrating the CLAIR score into resident training programs, alongside simulation-based education and regular assessments, could enhance skill development, improve decision-making, and strengthen preparedness for managing challenging airway situations [ 28 , 29 ]. Clinical implications in anesthesia practice The CLAIR risk prediction tool offers a practical approach for enhancing preoperative risk stratification and airway management. Its implementation could optimize resource allocation, ensure the availability of advanced airway tools, and guide the use of specialized techniques, such as video laryngoscopy. The stratification of patients into high, intermediate, and low-risk categories enables tailored airway management strategies, potentially reducing adverse events and improving patient safety, especially in resource-limited settings or emergency scenarios where rapid, accurate risk assessment is essential. Strengths and limitations Despite the large sample size and rigorous matching, this study’s retrospective design and reliance on existing medical records introduce potential data variability. Its single-center setting may limit generalizability to other healthcare systems or patient populations. Additionally, this case-control study limited the estimation of absolute risk, as the artificially set prevalence may bias predicted probabilities. While ORs remain valid, the risk calculator might require prevalence adjustment. Future research directions Future studies should validate the CLAIR score in a prospective cohort and refine its predictive accuracy through prevalence-adjusted recalibration. Beyond validation, integrating the CLAIR score into existing airway management protocols and developing targeted strategies for high-risk patients are essential next steps. Additionally, assessing its economic impact will provide insights into its feasibility for widespread adoption. These efforts will not only enhance the accuracy and reliability and clinical utility of the CLAIR score but also contribute to a more standardized and effective approach to difficult airway management. Ultimately, this could transform anesthesia practice, improving patient safety across diverse clinical settings. Conclusions The CLAIR risk prediction tool offers a practical approach for early identification of unanticipated difficult airways, demonstrating high sensitivity (98%) despite a moderate AUC of 0.633. Its simplicity, accessibility via a web-based calculator and QR code, and integration of clinical and procedural factors make a valuable screening tool for routine anesthesia practice. Implementing the CLAIR score may enhance risk stratification, preparedness, and patient safety. Further validation in diverse populations is necessary to refine its clinical impact and optimize airway management strategies. Abbreviations PAAd Thai Perioperative and Anesthetic Adverse Events in Thailand BMI body mass index ASA American Society of Anesthesiologists AUC area under the receiver operating characteristic curve Declarations Ethics approval and consent to participate: This study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Ethics Committee of the Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand (Approval Reference: REC.63-560-8-1) on January 15, 2021. Patient consent was waived due to the retrospective nature of the cohort study. Consent for publication: Not applicable Availability of data and materials: The data supporting the findings of this study are available within the article. Competing interests: The authors declare no conflict of interest. Funding: This research received no external funding. Authors’ contributions: MO and PB conceived of the study. MO developed the methodology. CK, WJ, ND, WJ, and PP collected the data. MO and PV conducted the formal analysis. CK and QY were responsible for validation. CK and WJ wrote the original draft. CK, MO, ND, WJ, and PP reviewed and edited the manuscript. PB supervised the study. QY was responsible for project administration. PV gathered the resources for the study. All authors have read and agreed to the published version of the manuscript. Acknowledgments: Not applicable References Koh, W., Kim, H., Kim, K., Ro, Y. J. & Yang, H. S. Encountering unexpected difficult airway: relationship with the intubation difficulty scale. Korean J. Anesthesiol . 69 , 244–249 (2016). Crosby, E. T. et al. The unanticipated difficult airway with recommendations for management. Can. J. Anaesth. 45 , 757–776 (1998). Benumof, J. L. Management of the difficult adult airway. With special emphasis on awake tracheal intubation. Anesthesiology 75 , 1087–1110 (1991). Heinrich, S., Birkholz, T., Irouschek, A., Ackermann, A. & Schmidt, J. 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Learning curves for bag-and-mask ventilation and orotracheal intubation: an application of the cumulative sum method. Anesthesiology 112 , 1525–1531 (2010). Purva, E. J. S. K., Chander, M. & Parameswari, M. S. Impact of repeated simulation on learning curve characteristics of residents exposed to rare life threatening situations. BMJ Simul. Technol. Enhanc Learn. 6 , 351–355 (2020). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-6273929","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":441782200,"identity":"b822e361-a664-4ba4-a82b-55492a45bd45","order_by":0,"name":"Chanatthee Kitsiripant","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyklEQVRIiWNgGAWjYDACCQhlwA8iEwqI1pLAYCDZAKINSNFicABsGRE6+Gc3P3vw8weDsfH51YkfHhgwyPOLHSBgyZ1j5oY9CQxmZjfebpYAOsxw5uwE/FoMJBLMJHgSGGzMbpzdANKSYHCboJb0b5J/gFqMZ5zd/INILTlm0kBbzAz4e7cRZ4vEjZwyaZk0CWOJG7zbLBIMJAj7hX9G+jbJNzY2hv39Zzff/FFhI88vTUALzDIgSoAyiAf8B0hRPQpGwSgYBSMJAAALqj48MataywAAAABJRU5ErkJggg==","orcid":"","institution":"Prince of Songkla University","correspondingAuthor":true,"prefix":"","firstName":"Chanatthee","middleName":"","lastName":"Kitsiripant","suffix":""},{"id":441782201,"identity":"5a5854d4-75fa-4832-b76c-406890ac0706","order_by":1,"name":"Wilasinee Jitpakdee","email":"","orcid":"","institution":"Prince of Songkla University","correspondingAuthor":false,"prefix":"","firstName":"Wilasinee","middleName":"","lastName":"Jitpakdee","suffix":""},{"id":441782202,"identity":"11611a83-cc68-420a-88f1-e415fc5941db","order_by":2,"name":"Maliwan Oofuvong","email":"","orcid":"","institution":"Prince of Songkla University","correspondingAuthor":false,"prefix":"","firstName":"Maliwan","middleName":"","lastName":"Oofuvong","suffix":""},{"id":441782203,"identity":"22825ea0-8e9d-4251-a92f-94d50c016397","order_by":3,"name":"Pannawit Benjawaleemas","email":"","orcid":"","institution":"Prince of Songkla University","correspondingAuthor":false,"prefix":"","firstName":"Pannawit","middleName":"","lastName":"Benjawaleemas","suffix":""},{"id":441782204,"identity":"974a5ef0-79fa-4a48-8a1b-97cf4e20ff97","order_by":4,"name":"Nussara Dilokrattanaphichit","email":"","orcid":"","institution":"Prince of Songkla University","correspondingAuthor":false,"prefix":"","firstName":"Nussara","middleName":"","lastName":"Dilokrattanaphichit","suffix":""},{"id":441782205,"identity":"af98031c-c590-4d07-9cb8-926c0c497961","order_by":5,"name":"Wipharat Juthasantikul","email":"","orcid":"","institution":"Prince of Songkla University","correspondingAuthor":false,"prefix":"","firstName":"Wipharat","middleName":"","lastName":"Juthasantikul","suffix":""},{"id":441782206,"identity":"3ddb162a-746f-4af7-a3b9-26f94803348c","order_by":6,"name":"Pannipa Phakam","email":"","orcid":"","institution":"Prince of Songkla University","correspondingAuthor":false,"prefix":"","firstName":"Pannipa","middleName":"","lastName":"Phakam","suffix":""},{"id":441782207,"identity":"49f8fe54-8e4a-43b3-b245-43b79a3ff236","order_by":7,"name":"Qistina Yunuswangsa","email":"","orcid":"","institution":"Prince of Songkla University","correspondingAuthor":false,"prefix":"","firstName":"Qistina","middleName":"","lastName":"Yunuswangsa","suffix":""},{"id":441782209,"identity":"1843f1fd-f3b2-4ee4-9399-2f0b1f059b5d","order_by":8,"name":"Polathep Vichitkunakorn","email":"","orcid":"","institution":"Prince of Songkla University","correspondingAuthor":false,"prefix":"","firstName":"Polathep","middleName":"","lastName":"Vichitkunakorn","suffix":""}],"badges":[],"createdAt":"2025-03-21 04:23:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6273929/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6273929/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":80820346,"identity":"82a5852e-5275-4fc7-904b-781a3ebe9f9e","added_by":"auto","created_at":"2025-04-17 12:05:30","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":278539,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram of the study. GA, general anesthesia\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6273929/v1/fb3357970e31dc6d25c478e4.jpeg"},{"id":80818656,"identity":"b8e91310-50f6-42f4-8edf-f7a307ad5137","added_by":"auto","created_at":"2025-04-17 11:49:30","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":51832,"visible":true,"origin":"","legend":"\u003cp\u003eReceiver operating characteristic (ROC) curve for the CLAIR score predictive model, demonstrating an area under the curve of 0.633. An optimal cutoff score of 0 yielded 98% sensitivity and 16% specificity. Risk stratification categories: high (≥ 1), and low (≤ -1).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6273929/v1/9237a84cc60d03c99b745dab.png"},{"id":80819722,"identity":"ff27af4a-c14b-40da-a55a-5fdc4f5843e5","added_by":"auto","created_at":"2025-04-17 11:57:30","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2206,"visible":true,"origin":"","legend":"\u003cp\u003eQR code linking to the CLAIR Score Calculator, a web\u003cstrong\u003e-\u003c/strong\u003ebased tool designed to predict unanticipated difficult airways\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6273929/v1/001bbf546de3a9c2141d1087.png"},{"id":96452783,"identity":"2e01e1b1-beb2-47d5-a1b3-d37dba30387d","added_by":"auto","created_at":"2025-11-21 09:44:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2119011,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6273929/v1/f026b96f-917d-4ee0-97fd-ad72d8a31837.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"CLAIR Score: A Novel Risk Prediction Tool for Unmasking Unanticipated Difficult Airways","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eSecuring a patent airway is a fundamental requirement for safe anesthesia. Unanticipated difficult airways, reported in 1.5\u0026ndash;8.5% of cases, pose significant challenges and can result in life-threatening complications [\u003cspan additionalcitationids=\"CR2 CR3 CR4 CR5\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The 2015 Perioperative and Anesthetic Adverse Events in Thailand (PAAd Thai) study demonstrated a 2.3% incidence of unanticipated difficult intubation [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Ineffective management of such cases can lead to severe complications, including emergency surgical airway, airway trauma, hypoxic brain injury, and death due to oxygen deprivation [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Traditional predictive tools, such as the Mallampati score, upper lip bite test (ULBT), interincisor distance (IID), and thyromental distance (TMD), have variable accuracy and relying on a single factor often leads to poor predictive performance [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. While comprehensive assessment models integrating multiple factors improve accuracy, they are complex and time-consuming, limiting their practicality in daily practice [\u003cspan additionalcitationids=\"CR12 CR13\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Advanced airway ultrasound techniques offer promising sensitivity and specificity [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] but remain inaccessible in resource-limited settings. A more practical, efficient, and accurate risk stratification tool remains a critical need. This study aims to clarify the predictive factors associated with unanticipated airway difficulties during anesthesia to enhance patient safety and preparedness for critical situations.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e This retrospective observational case-control study was conducted at an 858-bed tertiary care teaching hospital in southern Thailand from January 2015 to December 2020. All procedures adhered to relevant laws and institutional guidelines. The study protocol was approved by the institutional review board (approval number 63-560-8-1), which granted a waiver for informed consent due to the study\u0026rsquo;s retrospective nature design. The privacy rights of all participants were rigorously observed.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatient selection\u003c/h2\u003e \u003cp\u003eThe inclusion comprised patients undergoing general anesthesia with endotracheal intubation for elective or emergency surgeries who encountered difficult airway management, defined as requiring three or more intubation attempts by anesthesia providers. Patients who were already on preoperative mechanical ventilation or had anticipated difficult airways were excluded from the analysis.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMatching procedure\u003c/h3\u003e\n\u003cp\u003eA rigorous matching algorithm was implemented to minimize selection bias and control for potential confounding variables in the analysis. Cases of difficult airway management were matched with controls who underwent routine airway management, based on age (\u0026plusmn;\u0026thinsp;5 years), surgical type, and year, in a 1:3 ratio. For each difficult airway case, three controls were selected: one with a preoperatively anticipated difficult airway and two with normal airway assessments.\u003c/p\u003e\n\u003ch3\u003eDefinition of unanticipated difficult intubation\u003c/h3\u003e\n\u003cp\u003eUnanticipated difficult intubation was defined as three or more attempts at endotracheal tube intubation using direct or video laryngoscopy in a patient not preoperatively identified as having a difficult airway. Intubations were performed by anesthesia personnel with at least one year of experience, including anesthesia residents, nurse anesthetists, and attending anesthesiologists.\u003c/p\u003e\n\u003ch3\u003ePotential risk factors and confounding variables\u003c/h3\u003e\n\u003cp\u003ePotential predictors included patient, surgical, and anesthesia-related factors, such as sex, age, weight, height, body mass index (BMI), American Society of Anesthesiologists (ASA) physical status, preoperative airway assessment, history of difficult intubation and ventilation, comorbidities (e.g., medical conditions, congenital heart disease, obstructive sleep apnea, head and neck radiation, anatomical abnormalities due to infection, trauma, tumors, or burns, and abnormal laboratory values), type of surgery, laryngoscopic view grades, intubation attempts, intubation devices, incidence of emergency tracheostomy for rescue airway, the clinician\u0026rsquo;s first intubation attempt, and intubation experience.\u003c/p\u003e\n\u003ch3\u003eSample size determination\u003c/h3\u003e\n\u003cp\u003eA sample size calculation estimated that 70 unanticipated difficult airway cases and 280 controls were required to detect an odds ratio of 2.5, assuming a 15% prevalence of exposure among controls, with 80% power and a 0.05 significance level. Based on the institution\u0026rsquo;s annual incidence of 10\u0026ndash;15 cases, a 6-year study period was required.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using R version 4.3.1 (R Foundation, Vienna, Austria). Descriptive statistics are reported as medians with interquartile ranges for continuous variables and as frequencies with percentages for categorical variables. Associations between categorical variables and difficult intubation were assessed using the chi-squared or Fisher\u0026rsquo;s exact test, while continuous variables were evaluated with Student\u0026rsquo;s t-tests or Mann\u0026ndash;Whitney U tests, depending on data distribution. Collinearity diagnostics and bivariate correlation matrices were evaluated for all variables. In cases of multicollinearity, only one variable was retained for multivariate analysis. Variables with a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.25 in the univariate analysis were considered for inclusion in the initial multivariate logistic regression model. The final regression model was derived using backward selection, retaining all significant variables. The optimal cutoff point was identified using Youden\u0026rsquo;s index. Statistical significance was defined as a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eScore derivation and validation\u003c/h3\u003e\n\u003cp\u003eThe risk prediction score system was developed using predictors derived from the multivariate logistic regression model. Risk scores were calculated by assigning weights to regression coefficients and scaling the total to 5.\u003c/p\u003e \u003cp\u003eIn the final model, the total predictor score was used to estimate the likelihood of unanticipated difficult airways. Youden\u0026rsquo;s index determined the cutoff value that maximized specificity and sensitivity. The performance of the final model was reported as the area under the receiver operating characteristic curve (AUC), with an AUC greater than 80 indicating excellent predictive accuracy.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eAmong 62,111 patients undergoing general anesthesia over 6 years, 168 cases of difficult airways were identified. After excluding 70 anticipated difficult airway cases, 98 unanticipated difficult airway cases, and 294 matched controls were analyzed (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), yielding an incidence of 0.16%. Patient demographics and perioperative characteristics are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Notably, only 3.1% of patients in the unanticipated difficult airway group were preoperatively assessed as having a probable difficult airway, compared with 16% in the control group (p\u0026thinsp;=\u0026thinsp;0.002). Most first-attempt intubations (66.1%) were performed by anesthesiology residents. The unanticipated difficult airway group had significantly more intubation attempts (median 4 (3,5) vs. 1 (1,1), p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and worse laryngoscopic view grades (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). They were also more likely to require video laryngoscope (78.6% vs. 13.7%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\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\u003ePatient demographics and perioperative characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" 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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnanticipated\u003c/p\u003e \u003cp\u003edifficult airway\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;98)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-difficult airway\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;294)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\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 \u003cp\u003e0.243\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56 (57.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e146 (49.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (42.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e148 (50.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 (38.0, 65.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56 (36.2, 64.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.790\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\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 \u003cp\u003ematch\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le; 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (12.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (11.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u0026ndash;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u0026ndash;64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56 (57.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e180 (61.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge; 65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (27.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66 (22.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWeight (kg)\u003c/b\u003e, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58.8 (49.1, 70.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.5 (48.4, 69.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.980\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHeight (cm)\u003c/b\u003e, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e160 (152.2,165.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e158.5 (150,165)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.346\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI (kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.3 (19,25.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.7 (19.2,26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.494\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI (kg/m\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\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 \u003cp\u003e0.286\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; 15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (7.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82 (83.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e231 (78.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge; 30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (14.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eASA classification\u003c/b\u003e\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 \u003cp\u003e0.798\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52 (53.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e155 (52.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43 (43.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e123 (41.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePreoperative probable difficult airway\u003c/b\u003e\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 \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95 (96.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e247 (84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModified Mallampati classification\u003c/b\u003e\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 \u003cp\u003e0.911\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79 (80.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e239 (81.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u0026ndash;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (10.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eunknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (9.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (9.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eThyromental distance\u003c/b\u003e\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 \u003cp\u003e0.832\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; 3 finger breadths\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3 finger breadths\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64 (65.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e181 (61.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt; 3 finger breadths\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (22.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80 (27.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eunknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (9.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInter-incisor gap\u003c/b\u003e\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 \u003cp\u003e0.824\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;2 cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (7.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u0026ndash;4 cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82 (83.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e251 (85.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eunknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (9.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (9.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLimited neck flexion and extension\u003c/b\u003e\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 \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94 (95.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e284 (96.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCannot evaluate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUpper lip bite test classification\u003c/b\u003e\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 \u003cp\u003e0.681\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53 (54.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e175 (59.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26 (26.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75 (25.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eunknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (18.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41 (13.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFacial appearance or syndrome\u003c/b\u003e\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 \u003cp\u003e0.418\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95 (96.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e289 (98.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbnormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEdentulous\u003c/b\u003e\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 \u003cp\u003e0.840\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88 (89.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e268 (91.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (10.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOverbite\u003c/b\u003e\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 \u003cp\u003e0.250\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97 (99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e294 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrevious history of difficult intubation and ventilation\u003c/b\u003e\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 \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e293 (99.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedical conditions\u003c/b\u003e\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 \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93 (94.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e278 (94.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCongenital heart disease\u003c/b\u003e\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 \u003cp\u003e0.770\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95 (96.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e281 (95.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAirway/neck/oral deformity\u003c/b\u003e\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 \u003cp\u003e0.639\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90 (91.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e276 (93.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (6.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eForeign body aspiration\u003c/b\u003e\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 \u003cp\u003e0.438\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97 (99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e293 (99.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInfection: retropharyngeal abscess, epiglottitis, supraglottitis\u003c/b\u003e\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 \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97 (99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e292 (99.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePost-surgical procedure: thyroid, cervical vertebrae\u003c/b\u003e\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 \u003cp\u003e0.504\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94 (95.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e286 (97.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOSA/Snoring\u003c/b\u003e\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 \u003cp\u003e0.875\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e83 (84.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e245 (83.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (15.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTumors: thyroid, pharynx, larynx and tracheobronchus, esophagus\u003c/b\u003e\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 \u003cp\u003e0.634\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86 (87.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e265 (90.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (12.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (9.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTrauma: face, neck\u003c/b\u003e\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 \u003cp\u003e0.643\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96 (98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e290 (98.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBurns (head, neck, face), smoke inhalation, massive burn\u003c/b\u003e\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 \u003cp\u003e0.261\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96 (98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e292 (99.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHistory radiation of head, neck\u003c/b\u003e\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 \u003cp\u003e0.697\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95 (96.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e288 (98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLaryngeal edema: angioedema, allergic, post rigid bronchoscopy\u003c/b\u003e\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 \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97 (99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e292 (99.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCoagulopathy and hypocalcemia\u003c/b\u003e\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 \u003cp\u003e0.102\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95 (96.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e292 (99.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType of surgery\u003c/b\u003e\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 \u003cp\u003ematch\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRemote\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (14.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41 (13.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeuro/Orthopedic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (6.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (6.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEye/superficial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (12.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40 (13.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eENT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31 (31.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90 (30.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThoracic/Vascular\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (12.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (11.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbdomen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (23.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71 (24.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIntubation attempts\u003c/b\u003e, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (3,5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1,1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIntubation device\u003c/b\u003e\u003c/p\u003e \u003cp\u003eDirect laryngoscope\u003c/p\u003e \u003cp\u003eVideo laryngoscope\u003c/p\u003e \u003cp\u003eSupraglottic airway device\u003c/p\u003e \u003cp\u003eOther\u003c/p\u003e \u003cp\u003eFiberoptic intubation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (19.4)\u003c/p\u003e \u003cp\u003e77 (78.6)\u003c/p\u003e \u003cp\u003e6 (6.1)\u003c/p\u003e \u003cp\u003e2 (2)\u003c/p\u003e \u003cp\u003e2 (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e252 (85.7)\u003c/p\u003e \u003cp\u003e40 (13.7)\u003c/p\u003e \u003cp\u003e4 (1.4)\u003c/p\u003e \u003cp\u003e2 (0.7)\u003c/p\u003e \u003cp\u003e5 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEmergency tracheostomy\u003c/b\u003e\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97 (99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e293 (99.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.439\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFirst-attempt intubation personnel\u003c/b\u003e\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 \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnesthesia instructors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (9.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (10.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnesthesiology residents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72 (73.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e187 (63.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCertified registered nurse anesthetists\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNurse anesthetist students\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (14.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 (16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIntubation experience (years)\u003c/b\u003e\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 \u003cp\u003e0.837\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93 (94.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e275 (93.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u0026ndash;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u0026ndash;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt; 20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLaryngoscopic view\u003c/b\u003e\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 \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (10.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e227 (77.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (14.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43 (43.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (30.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eData are presented as numbers (%) unless otherwise indicated.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eIQR, interquartile range; BMI, body mass index; ASA, American Society of Anesthesiologists; OSA, obstructive sleep apnea; ENT, ear, nose, and throat.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDevelopment of the CLAIR risk prediction tool\u003c/h2\u003e \u003cp\u003eThe initial multivariate model included seven variables with p-values\u0026thinsp;\u0026lt;\u0026thinsp;0.25: sex, preoperative assessment of probable difficult airway, overbite, coagulopathy, hypocalcemia, first-attempt intubation personnel, and laryngoscopic view. Since laryngoscopic view represents an outcome rather than a predictor, it was excluded from the final model. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the final multivariate analysis, which led to the development of the CLAIR risk score, integrating four key predictors: Coagulopathy and hypoCalcemia (C), Lady (L), potential Airway difficulty (A), and first-attempt intubation by residents (In-experienced Residents) (IR). The score ranged from \u0026minus;\u0026thinsp;4 to 6 (IQR \u0026minus;\u0026thinsp;1 to 1), with an AUC was 0.633 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). A cutoff score of 0 provided 98% sensitivity and 16% specificity. The CLAIR scores were classified into high (\u0026ge;\u0026thinsp;1), and low (\u0026le; -1) risk groups to optimize airway management strategies. The diagnostic performance of the CLAIR score is detailed in Table\u0026nbsp;\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\u003eMultivariate logistic regression of predictive factors of unanticipated difficult airway (CLAIR score)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictive factors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdjusted OR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep-\u003c/em\u003evalue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRisk score\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eC\u003c/b\u003e: Coagulopathy and hypo\u003cb\u003eC\u003c/b\u003ealcemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.62 (1.27, 88.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eL: L\u003c/b\u003eady\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.71 (0.44, 1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eA\u003c/b\u003e: potential \u003cb\u003eA\u003c/b\u003eirway difficulty\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-2.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.13 (0.04, 0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIR: I\u003c/b\u003enexperienced \u003cb\u003eR\u003c/b\u003eesidents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.62 (0.97, 2.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eOR, odds ratio; CI, confidence interval.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\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 performance of the CLAIR score for predicting unanticipated difficult airway\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" 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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScore\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePPV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNPV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAccuracy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e+LR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-LR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e50.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e52.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e97.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e56.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e97.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e56.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e97.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e56.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e73.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e84.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e60.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e50.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e50.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e66.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e50.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e66.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e50.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e66.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e50.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e50.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e50.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003ePPV, positive predictive value; NPV, negative predictive value; +LR, positive likelihood ratio; -LR, negative likelihood ratio.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eWeb-based risk calculator and accessibility\u003c/h2\u003e \u003cp\u003eThe CLAIR score calculator, now a web-based tool, enables clinicians to quickly categorize patients into risk groups for tailored airway management. Accessible via a QR code (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), the tool supports real-time use during preoperative assessments or emergency scenarios, helping to swiftly identify at-risk patients, optimize resource allocation, and enhance airway management strategies, ultimately improving patient safety and outcomes.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eKey findings\u003c/h2\u003e \u003cp\u003eThe CLAIR risk prediction tool represents a significant advancement in identifying unanticipated difficult airways, addressing a critical gap in anesthesia practice. Our study revealed an incidence of unanticipated difficult airways of 0.16%, significantly lower than the 2.3% reported in the 2015 PAAd Thai study [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. This discrepancy may be due to the development of preoperative assessment techniques, increased awareness of airway difficulties, or differences in patient populations and clinical settings. However, it also underscores the persistent challenges in airway assessment and highlights the potential value of our novel approach.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eInterpretation and implications\u003c/h2\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003eCLAIR score: A paradigm shift in airway risk prediction\u003c/h2\u003e \u003cp\u003eThe CLAIR score demonstrated a moderate predictive performance for unanticipated difficult airways, with an AUC of 0.633. Notably, it maintains a high sensitivity (98%), enabling early identification of at-risk patients. Although its specificity is lower (16%), the model remains a valuable screening tool due to its simplicity, practicality, and ease of use in clinical settings. Unlike traditional models that emphasize anatomical factors, CLAIR incorporates patient, clinical, and procedural elements, aligning with evolving airway management guidelines such as those from the ASA [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. By enhancing routine airway assessment and preparedness, the CLAIR score provides a user-friendly approach to improving patient safety and first-attempt success in airway management. The CLAIR score incorporates four key factors:\u003c/p\u003e \u003cp\u003eCoagulopathy and hypocalcemia\u003c/p\u003e \u003cp\u003eCoagulopathy (abnormal rotational thromboelastometry, international normalized ratio\u0026thinsp;\u0026gt;\u0026thinsp;1.3, prothrombin time\u0026thinsp;\u0026gt;\u0026thinsp;control by 3 s, or partial thromboplastin time\u0026thinsp;\u0026gt;\u0026thinsp;control by 10 s) and hypocalcemia (serum calcium\u0026thinsp;\u0026lt;\u0026thinsp;8.2 mg/dL or ionized calcium\u0026thinsp;\u0026lt;\u0026thinsp;4.4 mg/dL) pose significant challenges in airway management. Coagulopathy increases the risk of bleeding during airway manipulation, whereas hypocalcemia increases neuromuscular excitability, potentially causing masseter spasms despite using muscle relaxants [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. These conditions complicate airway management and increase the difficulty of intubation. Including this factor in the CLAIR score emphasizes the importance of a comprehensive preoperative evaluation that extends beyond traditional airway assessment.\u003c/p\u003e \u003cp\u003eLady (female sex)\u003c/p\u003e \u003cp\u003eSeveral studies have identified male sex as a risk factor for both difficult mask ventilation and intubation [\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Moreover, Hindman et al. reported a significantly higher intubation force required in male patients compared to females [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Similarly, our findings suggest that female sex may serve as a protective factor against unanticipated difficult airways.\u003c/p\u003e \u003cp\u003ePotential airway difficulty\u003c/p\u003e \u003cp\u003eThe limited predictive value of conventional preoperative airway assessments, with an observed accuracy of only 3.1% in this study, aligns with findings by Roth et al. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This underscores the need for a more comprehensive, multimodal approach to identifying risk factors for unanticipated difficult airways. The CLAIR score addresses this limitation by integrating multiple assessment criteria, thereby enhancing prediction accuracy, as evidenced by previous studies [\u003cspan additionalcitationids=\"CR26\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Despite routine screening, difficult airway scenarios may still arise unexpectedly, highlighting the importance of heightened vigilance and preparedness.\u003c/p\u003e \u003cp\u003eInexperienced residents\u003c/p\u003e \u003cp\u003eOur findings regarding the increased likelihood of unanticipated difficult airways among less experienced anesthesiology residents highlight the significance of ongoing training and supervision. In this study, inexperienced people were defined as having less than one year of intubation experience, including first-year residents, anesthetic nurse students, and medical students. These findings align with the previous studies examining the learning curve in airway management skills. Integrating the CLAIR score into resident training programs, alongside simulation-based education and regular assessments, could enhance skill development, improve decision-making, and strengthen preparedness for managing challenging airway situations [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eClinical implications in anesthesia practice\u003c/h2\u003e \u003cp\u003eThe CLAIR risk prediction tool offers a practical approach for enhancing preoperative risk stratification and airway management. Its implementation could optimize resource allocation, ensure the availability of advanced airway tools, and guide the use of specialized techniques, such as video laryngoscopy. The stratification of patients into high, intermediate, and low-risk categories enables tailored airway management strategies, potentially reducing adverse events and improving patient safety, especially in resource-limited settings or emergency scenarios where rapid, accurate risk assessment is essential.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eDespite the large sample size and rigorous matching, this study\u0026rsquo;s retrospective design and reliance on existing medical records introduce potential data variability. Its single-center setting may limit generalizability to other healthcare systems or patient populations. Additionally, this case-control study limited the estimation of absolute risk, as the artificially set prevalence may bias predicted probabilities. While ORs remain valid, the risk calculator might require prevalence adjustment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eFuture research directions\u003c/h2\u003e \u003cp\u003eFuture studies should validate the CLAIR score in a prospective cohort and refine its predictive accuracy through prevalence-adjusted recalibration. Beyond validation, integrating the CLAIR score into existing airway management protocols and developing targeted strategies for high-risk patients are essential next steps. Additionally, assessing its economic impact will provide insights into its feasibility for widespread adoption. These efforts will not only enhance the accuracy and reliability and clinical utility of the CLAIR score but also contribute to a more standardized and effective approach to difficult airway management. Ultimately, this could transform anesthesia practice, improving patient safety across diverse clinical settings.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe CLAIR risk prediction tool offers a practical approach for early identification of unanticipated difficult airways, demonstrating high sensitivity (98%) despite a moderate AUC of 0.633. Its simplicity, accessibility via a web-based calculator and QR code, and integration of clinical and procedural factors make a valuable screening tool for routine anesthesia practice. Implementing the CLAIR score may enhance risk stratification, preparedness, and patient safety. Further validation in diverse populations is necessary to refine its clinical impact and optimize airway management strategies.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003ePAAd Thai\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Perioperative and Anesthetic Adverse Events in Thailand\u003c/p\u003e\n\u003cp\u003eBMI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;body mass index\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eASA\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;American Society of Anesthesiologists\u003c/p\u003e\n\u003cp\u003eAUC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;area under the receiver operating characteristic curve\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e This study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Ethics Committee of the Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand (Approval Reference: REC.63-560-8-1) on January 15, 2021. Patient consent was waived due to the retrospective nature of the cohort study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e The data supporting the findings of this study are available within the article.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e The authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions:\u003c/strong\u003e MO and PB conceived of the study. MO developed the methodology. CK, WJ, ND, WJ, and PP collected the data. MO and PV conducted the formal analysis. CK and QY were responsible for validation. CK and WJ wrote the original draft. CK, MO, ND, WJ, and PP reviewed and edited the manuscript. PB supervised the study. QY was responsible for project administration. PV gathered the resources for the study. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e Not applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKoh, W., Kim, H., Kim, K., Ro, Y. J. \u0026amp; Yang, H. S. Encountering unexpected difficult airway: relationship with the intubation difficulty scale. \u003cem\u003eKorean J. Anesthesiol\u003c/em\u003e. \u003cb\u003e69\u003c/b\u003e, 244\u0026ndash;249 (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCrosby, E. T. et al. The unanticipated difficult airway with recommendations for management. \u003cem\u003eCan. J. Anaesth.\u003c/em\u003e \u003cb\u003e45\u003c/b\u003e, 757\u0026ndash;776 (1998).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBenumof, J. L. Management of the difficult adult airway. With special emphasis on awake tracheal intubation. \u003cem\u003eAnesthesiology\u003c/em\u003e \u003cb\u003e75\u003c/b\u003e, 1087\u0026ndash;1110 (1991).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHeinrich, S., Birkholz, T., Irouschek, A., Ackermann, A. \u0026amp; Schmidt, J. Incidences and predictors of difficult laryngoscopy in adult patients undergoing general anesthesia: a single-center analysis of 102,305 cases. \u003cem\u003eJ. Anesth.\u003c/em\u003e \u003cb\u003e27\u003c/b\u003e, 815\u0026ndash;821 (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShah, P. N. \u0026amp; Sundaram, V. Incidence and predictors of difficult mask ventilation and intubation. \u003cem\u003eJ. Anaesthesiol. Clin. 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P. \u0026amp; Singh, U. K. Comparison of sensitivity, specificity, and accuracy of Wilson\u0026rsquo;s score and intubation prediction score for prediction of difficult airway in an eastern Indian population-a prospective single-blind study. \u003cem\u003eJ. Family Med. Prim. Care\u003c/em\u003e. \u003cb\u003e9\u003c/b\u003e, 1436\u0026ndash;1441 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCarsetti, A., Sorbello, M., Adrario, E., Donati, A. \u0026amp; Falcetta, S. Airway ultrasound as predictor of difficult direct laryngoscopy: a systematic review and meta-analysis. \u003cem\u003eAnesth. Analg\u003c/em\u003e. \u003cb\u003e134\u003c/b\u003e, 740\u0026ndash;750 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Luis-Cabez\u0026oacute;n, N. et al. A new score for airway assessment using clinical and ultrasound parameters. \u003cem\u003eFront. Med. (Lausanne)\u003c/em\u003e. \u003cb\u003e11\u003c/b\u003e, 1334595 (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFulkerson, J. S., Moore, H. M., Anderson, T. S. \u0026amp; Lowe, R. F. Jr Ultrasonography in the preoperative difficult airway assessment. \u003cem\u003eJ. Clin. Monit. Comput.\u003c/em\u003e \u003cb\u003e31\u003c/b\u003e, 513\u0026ndash;530 (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eApfelbaum, J. L. et al. 2022 American Society of Anesthesiologists Practice guidelines for management of the difficult airway. \u003cem\u003eAnesthesiology\u003c/em\u003e \u003cb\u003e136\u003c/b\u003e, 31\u0026ndash;81 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKatiyar, S., Srinivasan, S. \u0026amp; Jain, R. K. Hypocalcaemia leading to difficult airway in sepsis. \u003cem\u003eJ. Anaesthesiol. Clin. Pharmacol.\u003c/em\u003e \u003cb\u003e27\u003c/b\u003e, 123\u0026ndash;124 (2011).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChristie, J. Airway physical examination tests for detection of difficult airway management in apparently normal adult patients. \u003cem\u003eInt. J. Nurs. Pract.\u003c/em\u003e \u003cb\u003e26\u003c/b\u003e, e12805 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArtime, C. A., Roy, S. \u0026amp; Hagberg, C. A. The difficult airway. \u003cem\u003eOtolaryngol. Clin. North. Am.\u003c/em\u003e \u003cb\u003e52\u003c/b\u003e, 1115\u0026ndash;1125 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSag\u0026uuml;n, A., Ozdemir, L. \u0026amp; Melikogullari, S. B. The assessment of risk factors associated with difficult intubation as endocrine, musculoskeletal diseases and intraoral cavity mass: a nested case control study. \u003cem\u003eUlus Travma Acil Cerrahi Derg\u003c/em\u003e. \u003cb\u003e28\u003c/b\u003e, 1270\u0026ndash;1276 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHindman, B. J., Dexter, F., Gadomski, B. C. \u0026amp; Bucx, M. J. Sex-specific intubation biomechanics: intubation forces are greater in male than in female patients, independent of body weight. \u003cem\u003eCureus\u003c/em\u003e \u003cb\u003e12\u003c/b\u003e, e8749 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoth, D. et al. Airway physical examination tests for detection of difficult airway management in apparently normal adult patients. \u003cem\u003eCochrane Database Syst. Rev.\u003c/em\u003e \u003cb\u003e5\u003c/b\u003e, CD008874 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMallhi, A. I. et al. A comparison of Mallampati classification, thyromental distance and a combination of both to predict difficult intubation. \u003cem\u003eAnaesth. Pain Intensive Care\u003c/em\u003e. \u003cb\u003e22\u003c/b\u003e, 468\u0026ndash;473 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmbesh, S. P. et al. A combination of the modified Mallampati score, thyromental distance, anatomical abnormality, and cervical mobility (M-TAC) predicts difficult laryngoscopy better than Mallampati classification. \u003cem\u003eActa Anaesthesiol. Taiwan.\u003c/em\u003e \u003cb\u003e51\u003c/b\u003e, 58\u0026ndash;62 (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang, L-Y. et al. Evaluation of the reliability of the upper lip bite test and the modified mallampati test in predicting difficult intubation under direct laryngoscopy in apparently normal patients: a prospective observational clinical study. \u003cem\u003eBMC Anesthesiol\u003c/em\u003e. \u003cb\u003e22\u003c/b\u003e, 314 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKomatsu, R. et al. Learning curves for bag-and-mask ventilation and orotracheal intubation: an application of the cumulative sum method. \u003cem\u003eAnesthesiology\u003c/em\u003e \u003cb\u003e112\u003c/b\u003e, 1525\u0026ndash;1531 (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePurva, E. J. S. K., Chander, M. \u0026amp; Parameswari, M. S. Impact of repeated simulation on learning curve characteristics of residents exposed to rare life threatening situations. \u003cem\u003eBMJ Simul. Technol. Enhanc Learn.\u003c/em\u003e \u003cb\u003e6\u003c/b\u003e, 351\u0026ndash;355 (2020).\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":"patient safety, preoperative assessment, predictors, unanticipated difficult airway","lastPublishedDoi":"10.21203/rs.3.rs-6273929/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6273929/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eUnanticipated difficult airways remain a significant challenge in anesthesia practice and are associated with increased severe complication risk. In this study, we developed and validated the CLAIR risk prediction tool to enhance early identification of unanticipated difficult airways.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis retrospective case-control study analyzed data from 62,111 patients who underwent general anesthesia between 2015 and 2020. Among them, 98 unanticipated difficult airways were identified and matched in a 1:3 ratio with 294 controls. Multivariate logistic regression identified key predictors, forming the CLAIR score, which incorporates coagulopathy, hypocalcemia, female sex, potential airway difficulty, and inexperienced residents.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe incidence of unanticipated difficult airways was 0.16%. The CLAIR score demonstrated an area under the receiver operating characteristic curve of 0.633, with high sensitivity (98%) despite lower specificity (16%). A cutoff of 0 effectively stratified patients into high (\u0026ge;\u0026thinsp;1), and low (\u0026le;-1) risk groups, guiding airway management strategies. Its web-based risk calculator and QR code enhance accessibility for real-time clinical applications.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe CLAIR score is a simple, practical, and user-friendly tool that improves preoperative risk assessment and preparedness for difficult airways. While further external validation is necessary, its integration into routine anesthesia practice may enhance patient safety and optimize airway management strategies.\u003c/p\u003e","manuscriptTitle":"CLAIR Score: A Novel Risk Prediction Tool for Unmasking Unanticipated Difficult Airways","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-17 11:49:26","doi":"10.21203/rs.3.rs-6273929/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":"9f122f41-98e3-44cf-9810-fa5cbdb88d52","owner":[],"postedDate":"April 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":47043129,"name":"Health sciences/Medical research"},{"id":47043130,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2025-11-14T05:23:39+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-17 11:49:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6273929","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6273929","identity":"rs-6273929","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}