Comparison of Mallampati test with and without phonation for prediction of difficult airways on adult patient (Prospective observational study)

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The Mallampati test without phonation is routinely practiced, but its sensitivity in predicting difficult intubation is controversial. Objective To compare the Malampati test with and without phonation in predicting difficult laryngoscopy and tracheal intubation among adult elective surgical patients who underwent general anaesthesia. Method A hospital based cross-sectional study was performed on 258 adult elective surgery patients who required tracheal intubation at Tikur Anbessa specialized hospital. A systemic random sampling technique was employed to select study participant and the Mallampati test with and without phonation was performed during preoperative assessment. Then a laryngoscopic view was recorded at the time of tracheal intubation, and Mallampati test grades I and II were classified as easy, while grades III and IV were classified as difficult for tracheal intubation. The data was entered by Epi info and analysed with the statistics package of the social science software version 26. Statistical significance was defined at p-value of less than 0.05. This study used specificity, sensitivity, accuracy, and positive and negative predictive values as statistical measures. Result The prevalence of laryngoscopy and intubation difficulty was 13.6% and 10.5%, respectively. Mallampati test without phonation had a sensitivity of 82.9% and a specificity of 79.1% for difficult laryngoscope. And it had a sensitivity of 88.9%, a specificity of 87% for difficult intubation. MMT with phonation had a sensitivity of 74.3% and a specificity of 91.9% for difficult laryngoscopy and it had a sensitivity of 77.8% and specificity of 90% for difficult intubation. Conclusion Based on our study results, MMT with phonation has higher accuracy, specificity, and PPV in the prediction of difficult laryngoscopy and intubation than the non-phonation approach. Mallapati test phonation difficult laryngoscopy difficult intubation Figures Figure 1 Figure 2 1. Introduction Difficult tracheal intubation is a major cause of morbidity and mortality in the practice of anaesthesia. The frequency of tracheal intubation difficulties in the operation theatre has been reported to range from 1–18% 1,2 . Patients are at a greater risk of developing sore throat to major airway trauma, brain damage, and even death as a result of unexpectedly difficult laryngoscopy intubation. These conditions are most likely the result of a failure to accurately predict difficult intubation and insufficient preoperative airway evaluations 3 . The anesthesiologist's main goal in pre-anesthesia airway assessment is to predict difficult airways as accurately as possible 4 . There are some airway evaluation tools. Mallampati test is the most commonly used airway assessment. Mallampati was introduced in 1985 5 . The original Mallampati test has three classes and it was modified by Samsoon and Young. Those tests include four classes 6 . Both the original Mallampati test and the modified Samsoon and Young did not include a phonation approach during airway assessment 7 . Combined with the Cormack-Lehane classification and other airway assessment parameters, it provides more accurate and precise predictive information about difficult laryngoscopy and tracheal intubation. In our day-to-day clinical operations, the Mallampti test without phonation is the most commonly utilized strategy for predicting unanticipated difficult airways. However, its effectiveness is in question, and it shows limited anticipation of difficult airways as it shows many false predictions of both easy and difficult airways 4 . Anaesthesia professionals are continually looking for a rapid and straightforward airway assessment technique at the bedside that has good sensitivity and specificity to predict and avoid difficult intubation. This study compared the Mallampati test while the patient was in a sitting position with and without phonation to determine the best predictor of difficult laryngoscopy and tracheal intubation at Tikur Anbessa Specialized Hospital. 2. Methodology 2.1 Study area The research was conducted at Tikur Anbessa specialized hospital in Ethiopia's, Addis Ababa. Addis Ababa is Ethiopia's capital city, covering more than 600Km2. TASH is one of Ethiopia's largest government hospitals, with patients traveling from all across the nation for specialized care. TASH is a medical center that also functions as a teaching center for higher education. The hospital has roughly 15 surgical departments [from hospital data base]. 2 .2 Study design and period A hospital based cross sectional study was conducted from December 2021 to February 2022. 2 .3 Population 2 .3.1 Source population All patients who underwent surgery at TASH from December 2021 to February 2022. 2 .3.2 Study population Adult surgical patients who need tracheal intubation for general anaesthesia at TASH. 2 .4 Inclusion and exclusion criteria 2 .4.1 Inclusion criteria Adult surgical patients who underwent surgery by general anaesthesia and those need tracheal intubation at TASH from December 2021 to February 2022. 2 .4.2 Exclusion criteria Infection (submandibular and peritonsillar abscess) and congenital abnormality patients Airway burn injury and traumatic patient (limited neck movement, cervical spine fracture, mandible and maxilla fracture, TMJ pain) 2 .5 Sample size Since this study is new in Ethiopia, this study use P-value is 50%. Where; n= the minimum sample size require z= the critical value for a given confidence interval, z=1.96 p= expected proportion of the event to be studied d= desired degree of precision or margin of error tolerated (5%) Therefore: p=0.5, q=1-p, 1- 0.5=0.5 n= (1.96)2 x (0.5) (0.5)/ (0.05)2 = 384 Since the size of population less than 10,000 this study uses the correction formula. n = 384 N = the total number of adult surgical patient who underwent surgery by general anaesthesia within three month were 600. Corrected sample size =384x600/384+600 = 234.14 Sample size is 234.14 plus 10% contingency the final sample size is equal to 258. 2 .6 Sampling technique To select the right participant, this study used a systematic random sampling technique in which samples were taken at regular intervals based on the sampling fraction (K). K= sampling interval, n= sample size, N= total study population in a given 3 months from hospital analysis were 600 elective surgery. N=600, n=258 K=N/n………..600/258=2.32≈2 the sampling fraction was two and the first participant was taken by using the lottery method for the daily elective patients. 2 .8.1 Data source, data gathering tools, data collector, and procedure After the department and college granted ethical authorization, data collection began by obtaining written informed consent from the chosen participant using pretested written questionnaires. Data collectors received extensive training on the research variables, the basic concept of the questionnaire, and how to collect data. From December 2021 to February 2022, data was collected for three months. During the preoperative phase, the principal investigator (an experienced anaesthetist) recorded the client's demographic features and assessed the Mallampati with and without phonation in the sitting position. Another experienced anaesthetist watched the laryngoscopy view during intubation with ether using macintosh blade 3 or 4 and recorded CM-L scoring and determining IDS. Mallampati grades I and II are regarded as simple or low risk for intubation, but grades III and IV are considered as tough. Laryngoscopy is regarded as Easy when Cormack-Lehane scores I and II, and Difficult when Cormack-Lehane scores III and IV. IDS≤5 were considered as Easy intubation whereas IDS> 5 were considered as Difficult Intubation 2 .8.2 Data processing and analysis This study used Epi Info version 7 to code, edit, enter, and clear the data, and then the data was transferred into the Version 26 of the statistics program for social sciences (SPSS) software. The continuous variables were presented as a mean with standard deviation. A chi-square test was used to compare the Mallampati test with and without phonation in relation to Cormack-Lehane's score and intubation difficulty score. Specificity, sensitivity, accuracy, positive and negative predictive values and, AUC were determined in this study in order to identify the most significant predictor of difficult laryngoscopy and intubation among the two approaches in a time of airway assessment. The result was presented in both numerical and percentage form. Statistical significance is defined as a P-value of less than 0.05. 2 .8.3 Data quality and assurance Meticulous training was given to anaesthetists who collected data. All acquired data were properly filled in and checked according to the established format. The researcher checked the completeness of the data obtained by the collectors every day. 3. Result 3.1 Socio-demographic features The study comprised a total of 258 adult patients. Among those, 54.3% were female and 45.7% were male. The patients' mean age was 40.17 ± 12.3 years (SD). The socio demographic distribution of the participants depicted at Table 1 . Table 1 BMI and sex frequency and proportion Variables frequency Percentage (%) Sex Male 118 45.7 female 140 54.3 BMI BMI 30 20 7.8 total 258 100 MMT without phonation was higher prediction of difficulty 54 (20.9%) than the phonation approach 44 (17.1%). MMT with phonation, on the other hand, had a higher prediction of easy 214 (83%) than MMT without phonation 204 (79%). The frequency of mallampati grades with or without depicted at Table 2 . Table 2 frequency and percentage of Mallampati grading variables Frequency Percentage (%) MMT without phonation Grade I 93 36 Grade II 111 43 Grade III 47 18.2 Grade IV 7 2.7 MMT with phonation Grade I 154 59.7 Grade II 60 23.3 Grade III 43 16.7 Grade IV 1 0.4 Total 258 100 The agreement between MMT grading with and without phonation was examined using kappa analysis and it had moderate agreement and the agreement between MMT grading with and without phonation, using MMT without phonation as the baseline technique mentioned at Table 3 . Table 3 MMT grading without and with phonation a kappa agreement Variable MMT without phonation K P-value Level of agreement difficult easy MMT with phonation difficult 33 11 0.598 < 0.001 Moderate easy 21 193 By using CM-L scoring as the gold standard, an agreement of the modified Mallampati test with and without phonation in predicting difficult laryngoscopy depicted at Table 4 and IDS as the gold standard, an agreement analysis of the modified Mallamapati test with and without phonation in predicting difficult intubation depicted at Table 5 . Table 4 CM-L scoring as the gold standard, an agreement of the modified Mallampati test with and without phonation in predicting difficult laryngoscopy Variables CML scoring Level of agreement Kappa P-value MMT without phonation 0.574 <0.001 Moderate MMT with phonation 0.597 <0.001 Moderate Table 5 IDS as the gold standard, an agreement analysis of the modified Mallamapati test with and without phonation in predicting difficult intubation Variables Difficult intubation Level of agreement Kappa P-value MMT without phonation 0.518 <0.001 Moderate MMT with phonation 0.531 <0.001 Moderate The χ2 test was significant and showed P < 0.001 association between CM-L scoring and IDS within Mallampati test for both approaches to predict difficulty laryngoscopy is summarized at Table 6 by comparing statistical data . The diagnostic power of the MMT without and with phonation in predicting of difficult intubation in relation to IDS and CM-L scoring is summarized at Table 7 by comparing statistical data. MMT conducted without phonation had the highest sensitivity for predicting difficult laryngoscopy and intubation, but MMT performed with phonation had a superior specificity for identifying easy intubation. Table 6 using Cormack-Lehane scoring as a gold standard, the modified mallampati test predictive power in various approaches to diagnosing difficulties laryngoscopy Statistical parameters MMT without phonation MMT with phonation Sensitivity (%) 82.9 74.3 Specificity (%) 88.3 91.9 True positive 29 26 False positive 25 18 True negative 198 205 False negative 6 9 PPV (%) 52.7 59.1 NPV (%) 97.06 95.8 Accuracy (%) 87.98 89.5 P-value < 0.001 < 0.001 Phi 0.603 0.603 AUC 0.858 0.831 Table 7 using IDS as a gold standard, the modified mallampati test predictive power in various approaches to diagnosing difficulties intubation Statistical parameters MMT without phonation MMT with phonation Sensitivity (%) 88.9 77.8 Specificity (%) 86.6 90 True positive 24 21 False positive 30 23 True negative 201 208 False negative 3 6 PPV (%) 43.6 47.7 NPV (%) 98.5 97.2 Accuracy (%) 87.2 88.75 P-value < 0.001 < 0.001 Phi 0.571 0.552 AUC 0.880 0.839 Both techniques have good sensitivity and specificity on the prediction of difficult laryngoscopy and intubation, and the area under curve in ROC analysis shows that they had a level of good in terms of sensitivity and 1-specificity (Fig. 1 and Fig. 2 ), making them a useful diagnostic tool for predicting difficult laryngoscopy and intubation outcomes. The Table 7 summarize the sensitivity, specificity, accuracy, true positive, false negative, AUC, positive predictive value, and negative predictive value of the Mallampati test during various approaches as tested during laryngoscopy. 4. Discussion There are many airway assessment techniques that exist with the goal of accurately predicting difficult airways. The Mallampati test is the most commonly used airway assessment in clinical practice. It can be performed with and without phonation to predict difficult airways. This study comprised a total of 258 adult patients. Among those, difficult laryngoscopy and intubation were identified 35 (13.6%) and 27 (10.5%), respectively. The results of our study are similar to a study done in Ethiopia, at Gonder University Hospital, which states that the incidence of laryngoscopy and intubation difficulties is approximately 12.3% and 9%, respectively, 8 . In contrast to our results, Sankal et al. 9 state that the incidence of difficult laryngoscopy and intubation was 23.1% and 14.6%, respectively, which was higher. This could be due to their study's use modified CML scoring, which includes grade IIb as a difficult laryngoscopic view, as opposed to classic Cormack–Lehane scoring, which considers grade II without subdivision as easy, thereby omitting the vast majority of patients. Our study shows that the kappa agreement between MMT grading with and without a phonation approach is 0.598, which indicates moderate agreement. In terms of predicting difficult laryngoscopy and tracheal intubation, both the Mallampati tests with and without phonation demonstrated moderate agreement. The result of this study is consistent with the kappa agreement reported by Sankal et al 9 . In our study, MMT without phonation identified 29 of 35 true difficult laryngoscopy with a sensitivity of around 82.9%, whereas the modified Mallampati test with phonation identified 26 out of 35 with a sensitivity of about 74.3%. However, the Mallampati test without phonation had a larger false positive than the phonation approach on the prediction of difficult laryngoscopy (FP, 25 vs FP, 18), respectively, making it less specific than the phonation approach. MMT with phonation had 91.9% specificity in relation to laryngoscopy, whereas MMT without phonation had 88.3% specificity. In line with our study khan et al, described that, the sensitivity and specificity of Mallampati test without phonation on prediction of difficult laryngoscopy had (Se, 86.3% vs Sp, 84.7%), respectively. On the other hand, the phonation approach had the sensitivity and the specificity of (Se, 46.41% Vs Sp, 96.92%), respectively 10 . In contrary to our study, Kentaro et al 11 described that the Mallampati test with phonation has a good correlation with Cormack-Lehane scoring for prediction of difficult laryngoscopy. This study shows that MMT without phonation identified 24 patients with a sensitivity of 88.9% out of 27 patients who actually had difficulty during intubation. On the other hand, MMT with phonation, on the other hand, detected 21 individuals from the difficult intubation with a sensitivity of 77.8%. However, the Mallampati test with a phonation method exhibited a better specificity for predicting easy intubation than the non-phonation approach, with a specificity of (90% vs 86.6), respectively. This indicates that MMT without phonation has higher sensitivity in the prediction of difficult intubation with less specificity as compared to MMT with phonation. This study result was consistent with the study done by Awashti et al, who stated that, Mallampati test without phonation had sensitivity and specificity for difficult intubation were 80% and 93.68%, respectively, whereas the phonation approach had the sensitivity and specificity for difficult intubation were 40% and 98.95%, respectively 4 . In addition, our study analysed the positive and negative predictive values and accuracy of each approach for predicting difficult laryngoscopy and intubation. The MMT with phonation exhibited a higher PPV than the non-phonation approach. However, in the Mallampati test, NPV is higher when it is conducted without phonation than with the phonation approach. The MMT with phonation demonstrated higher accuracy in predicting difficult laryngoscopy and intubation, with an accuracy of 89.5% and 88.75%, respectively, than the non-phonation approach, with an accuracy of 87.98% and 87.2%, respectively. This finding was in line with the findings of Sankal et al, who state that, MMT in the sitting posture without phonation had 75.4% accuracy, whereas MMT in the supine position without phonation had 67.7% accuracy. When performed in the supine position with phonation, MMT is more effective at predicting difficult laryngoscopic views (accuracy 85.4%) 9 . ROC curve analysis was used to compare the predictive ability of the Mallampati test with and without phonation to Cormack-Lehane as well as IDS findings (easy/difficult). The MMT without phonation had an AUC for predicting difficult laryngoscopy of 0.858, which was higher than the phonation approach, which had an AUC of 0.831. In addition, the AUC for predicting difficult tracheal intubation was higher in the non-phonation approach (0.880) than in MMT with phonation (0.839). Our findings were consistent with the study done by Awasthi et al 4 , who found that the AUC for predicting difficult laryngoscopy and intubation were higher in MMT without phonation (0.830 and 0.868, respectively) than in the phonation approach (0.637 and 0.695, respectively). As the results show, the diagnostic performance of both approaches is comparable, making them very good airway assessment techniques. 5. Conclusion and Recommendation Based on our study results, MMT with phonation has higher accuracy, specificity, and PPV in the prediction of difficult laryngoscopy and intubation than the non-phonation approach. Even though it has a little lower sensitivity than the non-phonation technique, it has a very good and comparable prediction of difficult airways. We believe that MMT combined with phonation can be used as an alternative assessment tool for predicting difficult airways. 6. Strength and limitation of the study 6.1 Strength Because the study is unique to our country, it lays the groundwork for future research, particularly for those interested in studying the effects of phonation on MMT with other airway assessment parameters for prediction of difficult airways. 6.2 Limitation The area where the investigation was conducted was not only a medical centre but also a learning centre. It tends to involve less experienced students in the intubation process. The Mallampati test is significantly prone to subjectivity. 7. Operational definition 7.1 Mallampati: - Identifies the size of the tongue with the oral cavity (Grade I: Soft palate, uvula, fauces, pillars visible; Grade II: Soft palate, major part of uvula, fauces visible. Grade III: only soft palate visible; Grade IV: only hard palate visible) MMT with phonation - Patient open mouth and protrude tongue maximally with saying "Ah sound". MMT without phonation: - Patient open mouth and protrude tongue maximally without saying "Ah sound". 7.2 Cormack-Lehane score Score I: glottis fully visible Score II: glottis partially visible Score III: only epiglottis visible Score IV: epiglottis not visible Score I and II considered as easy Laryngoscopy Score III and IV considered as difficult Laryngoscopy 7.3. Intubation difficulty score (IDS) IDS ≤ 5, easy intubation IDS > 5, Difficult Intubation (Table 8 ) Table 8 IDS score Symbol Parameters Criteria N1 Number of attempts Each additional attempts adds one point N2 Number of operators Each additional operators adds one point N3 Number of alternatives methods: A. Repositioning of patient B. Change of material (blade, tube, using a stylet) C. Change in approach (orotracheal or nasotracheal) D. Use of another technique (fiberscopy, intubation through a laryngeal mask) Every alternative methods adds one points N4 Cormack-Lehane scoring n-1 N5 Lifting force required Normal force = 0 Increased force = 1 N6 Laryngeal pressure Not applied pressure = 0 Applied pressure = 1 N7 Vocal cord mobility Abduction = 0 Adduction = 1 Abbreviations AAU (Addis Ababa University); AUC (Area under curve); CML (Cormack-Lehane Score); IDS (Intubation Difficulty Score) MMT Modified Mallampati Test NPV (Negative Predictive Value); PPV (Positive Predictive Value) ROC (Receiver Operating Characteristics curve); TASH (Tikure Anbessa Specialized Hospital) Declarations Ethics approval: This study was reviewed and approved by an institutional review board (ethics committee) of Addis Ababa university ethical review board with meeting No 130-/2021. Written form of consent from the patient was taken and the assessment done accordingly, the confidentiality of participant records and privacy of the health facility were maintained. Consent for publication: Not applicable Competing interests : the Authors have no conflict of interest to declare Guarantors: All authors Funding : no financial aid Availability of data and material: The data used in this study was collected by data collectors and submitted to authors, who are willing to share the data upon request from peer researchers. Authors Contribution: Authors will take public responsibility for the contents, have contributed substantially to the drafting and have approved the final version. All authors Involved on substantial intellectual contributions to conception, design and acquisition of data analysis and interpretation of data as well as on preparing the manuscript to this study Acknowledgement: we would like to thank Addis Ababa University for the financial support. Additionally, we would like to express our sincere gratitude to everyone who participated in the study, collected data, and used and one other way to help us to complete this work. References Bellhouse P. Predicting difficult intubation. Br J Anaesth. 1991;67:505. Tse JC, Rimm EB, Hussain A. Predicting Difficult Patients Scheduled Blind Study. Anaesthesia 254–8 (1995). Prakash S, et al. Difficult laryngoscopy and intubation in the Indian population: An assessment of anatomical and clinical risk factors. Indian J Anaesth. 2013;57:569–75. Awasthi P et al. Comparison of Mallampati test in supine and upright positions with and without phonation in predicting difficult laryngoscopy and intubation in age groups 3–10 years. 6, 61–7 (2018). Mallampati SR, et al. A clinical sign to predict difficult tracheal intubation; a prospective study. Can Anaesth Soc J. 1985;32:429–34. SAMSOON GLT, YOUNG JR. B. Difficult tracheal intubation: a retrospective study. Anaesthesia. 1987;42:487–90. Mallampati SR et al. A clinical sign to predict difficult tracheal intubation: a prospective study. 429–34 (1985). Workeneh SA, Gebregzi AH, Denu ZA. Magnitude and Predisposing Factors of Difficult Airway during Induction of General Anaesthesia. Anesthesiol. Res. Pract. 2017, (2017). Sankal A, Halemani KR, Bhadrinath N. Assessment of the Effect of Supine Posture and Phonation on Modified Mallampati Grading and its Applicability in Prediction of Difficult Airway. 19–24 (2018) 10.4103/jmgims.jmgims . Khan ZH, Eskandari S, Yekaninejad MS. A comparison of the Mallampati test in supine and upright positions with and without phonation in predicting difficult laryngoscopy and intubation: A prospective study. J Anaesthesiol Clin Pharmacol. 2015;31:207–11. Ouchi K, Hosokawa R, Yamanaka H, Nakajima Y, Nakamura Y. Mallampati test with phonation, tongue protrusion and supine position is most correlated with Cormack – Lehane test. Odontology. 2020. 10.1007/s10266-020-00490-3 . 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Introduction","content":"\u003cp\u003eDifficult tracheal intubation is a major cause of morbidity and mortality in the practice of anaesthesia. The frequency of tracheal intubation difficulties in the operation theatre has been reported to range from 1\u0026ndash;18% \u003csup\u003e1,2\u003c/sup\u003e. Patients are at a greater risk of developing sore throat to major airway trauma, brain damage, and even death as a result of unexpectedly difficult laryngoscopy intubation. These conditions are most likely the result of a failure to accurately predict difficult intubation and insufficient preoperative airway evaluations\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. The anesthesiologist's main goal in pre-anesthesia airway assessment is to predict difficult airways as accurately as possible \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThere are some airway evaluation tools. Mallampati test is the most commonly used airway assessment. Mallampati was introduced in 1985 \u003csup\u003e5\u003c/sup\u003e. The original Mallampati test has three classes and it was modified by Samsoon and Young. Those tests include four classes \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Both the original Mallampati test and the modified Samsoon and Young did not include a phonation approach during airway assessment \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCombined with the Cormack-Lehane classification and other airway assessment parameters, it provides more accurate and precise predictive information about difficult laryngoscopy and tracheal intubation. In our day-to-day clinical operations, the Mallampti test without phonation is the most commonly utilized strategy for predicting unanticipated difficult airways.\u003c/p\u003e \u003cp\u003eHowever, its effectiveness is in question, and it shows limited anticipation of difficult airways as it shows many false predictions of both easy and difficult airways \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Anaesthesia professionals are continually looking for a rapid and straightforward airway assessment technique at the bedside that has good sensitivity and specificity to predict and avoid difficult intubation. This study compared the Mallampati test while the patient was in a sitting position with and without phonation to determine the best predictor of difficult laryngoscopy and tracheal intubation at Tikur Anbessa Specialized Hospital.\u003c/p\u003e"},{"header":"2. Methodology","content":"\u003cp\u003e\u003cstrong\u003e2.1\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Study area\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research was conducted at Tikur Anbessa specialized hospital in Ethiopia\u0026apos;s, Addis Ababa. Addis Ababa is Ethiopia\u0026apos;s capital city, covering more than 600Km2. TASH is one of Ethiopia\u0026apos;s largest government hospitals, with patients traveling from all across the nation for specialized care. TASH is a medical center that also functions as a teaching center for higher education. The hospital has roughly 15 surgical departments [from hospital data base].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e.2 Study design and period\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA hospital based cross sectional study was conducted from December 2021 to February 2022.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e.3 Population\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e.3.1 Source population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll patients who underwent surgery at TASH from December 2021 to February 2022.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e.3.2 Study population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAdult surgical patients who need tracheal intubation for general anaesthesia at TASH.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e.4 Inclusion and exclusion criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e.4.1 Inclusion criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAdult surgical patients who underwent surgery by general anaesthesia and those need tracheal intubation at TASH from December 2021 to February 2022.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e.4.2 Exclusion criteria\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInfection (submandibular and peritonsillar abscess) and congenital abnormality patients Airway burn injury and traumatic patient (limited neck movement, cervical spine fracture, mandible and maxilla fracture, TMJ pain)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e.5 Sample size\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSince this study is new in Ethiopia, this study use P-value is 50%.\u003c/p\u003e\n\u003cp\u003eWhere;\u003c/p\u003e\n\u003cp\u003en= the minimum sample size require\u003c/p\u003e\n\u003cp\u003ez= the critical value for a given confidence interval, z=1.96\u003c/p\u003e\n\u003cp\u003ep= expected proportion of the event to be studied\u003c/p\u003e\n\u003cp\u003ed= desired degree of precision or margin of error tolerated (5%)\u003c/p\u003e\n\u003cp\u003eTherefore: p=0.5, q=1-p, 1- 0.5=0.5\u003c/p\u003e\n\u003cp\u003en= (1.96)2 x (0.5) (0.5)/ (0.05)2 = 384\u003c/p\u003e\n\u003cp\u003eSince the size of population less than 10,000 this study uses the correction formula.\u003c/p\u003e\n\u003cp\u003en = 384\u003c/p\u003e\n\u003cp\u003eN = the total number of adult surgical patient who underwent surgery by general anaesthesia within three month were 600.\u003c/p\u003e\n\u003cp\u003eCorrected sample size =384x600/384+600 = 234.14\u003c/p\u003e\n\u003cp\u003eSample size is 234.14 plus 10% contingency the final sample size is equal to 258.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e.6 Sampling technique\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo select the right participant, this study used a systematic random sampling technique in which samples were taken at regular intervals based on the sampling fraction (K). K= sampling interval, n= sample size, N= total study population in a given 3 months from hospital analysis were 600 elective surgery.\u003c/p\u003e\n\u003cp\u003eN=600, n=258\u003c/p\u003e\n\u003cp\u003eK=N/n\u0026hellip;\u0026hellip;\u0026hellip;..600/258=2.32\u0026asymp;2 the sampling fraction was two and the first participant was taken by using the lottery method for the daily elective patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e.8.1 Data source, data gathering tools, data collector, and procedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter the department and college granted ethical authorization, data collection began by obtaining written informed consent from the chosen participant using pretested written questionnaires. Data collectors received extensive training on the research variables, the basic concept of the questionnaire, and how to collect data. From December 2021 to February 2022, data was collected for three months.\u003c/p\u003e\n\u003cp\u003eDuring the preoperative phase, the principal investigator (an experienced anaesthetist) recorded the client\u0026apos;s demographic features and assessed the Mallampati with and without phonation in the sitting position. Another experienced anaesthetist watched the laryngoscopy view during intubation with ether using macintosh blade 3 or 4 and recorded CM-L scoring and determining IDS. Mallampati grades I and II are regarded as simple or low risk for intubation, but grades III and IV are considered as tough. Laryngoscopy is regarded as Easy when Cormack-Lehane scores I and II, and Difficult when Cormack-Lehane scores III and IV. IDS\u0026le;5 were considered as Easy intubation whereas IDS\u0026gt; 5 were considered as Difficult Intubation\u003c/p\u003e\n\u003cp\u003e2\u003cstrong\u003e.8.2 Data processing and analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study used Epi Info version 7 to code, edit, enter, and clear the data, and then the data was transferred into the Version 26 of the statistics program for social sciences (SPSS) software. The continuous variables were presented as a mean with standard deviation.\u003c/p\u003e\n\u003cp\u003eA chi-square test was used to compare the Mallampati test with and without phonation in relation to Cormack-Lehane\u0026apos;s score and intubation difficulty score. Specificity, sensitivity, accuracy, positive and negative predictive values and, AUC were determined in this study in order to identify the most significant predictor of difficult laryngoscopy and intubation among the two approaches in a time of airway assessment. The result was presented in both numerical and percentage form. Statistical significance is defined as a P-value of less than 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e.8.3 Data quality and assurance\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMeticulous training was given to anaesthetists who collected data. All acquired data were properly filled in and checked according to the established format. The researcher checked the completeness of the data obtained by the collectors every day.\u003c/p\u003e"},{"header":"3. Result","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Socio-demographic features\u003c/h2\u003e \u003cp\u003eThe study comprised a total of 258 adult patients. Among those, 54.3% were female and 45.7% were male. The patients' mean age was 40.17\u0026thinsp;\u0026plusmn;\u0026thinsp;12.3 years (SD). The socio demographic distribution of the participants depicted at Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\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\u003eBMI and sex frequency and proportion\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\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003efrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026lt;\u0026thinsp;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBMI 18 to 24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBMI 25 to 29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026gt;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003etotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMMT without phonation was higher prediction of difficulty 54 (20.9%) than the phonation approach 44 (17.1%). MMT with phonation, on the other hand, had a higher prediction of easy 214 (83%) than MMT without phonation 204 (79%). The frequency of mallampati grades with or without depicted at Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\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\u003efrequency and percentage of Mallampati grading\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\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003evariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eMMT without phonation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrade I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrade II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrade III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrade IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eMMT with phonation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrade I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrade II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrade III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrade IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe agreement between MMT grading with and without phonation was examined using kappa analysis and it had moderate agreement and the agreement between MMT grading with and without phonation, using MMT without phonation as the baseline technique mentioned at Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\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\u003eMMT grading without and with phonation a kappa agreement\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eMMT without phonation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLevel of agreement\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003edifficult\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eeasy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMMT with phonation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003edifficult\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.598\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eeasy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e193\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBy using CM-L scoring as the gold standard, an agreement of the modified Mallampati test with and without phonation in predicting difficult laryngoscopy depicted at Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and IDS as the gold standard, an agreement analysis of the modified Mallamapati test with and without phonation in predicting difficult intubation depicted at Table \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCM-L scoring as the gold standard, an agreement of the modified Mallampati test with and without phonation in predicting difficult laryngoscopy\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\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCML scoring\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLevel of agreement\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKappa\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\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\u003eMMT without phonation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.574\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMMT with phonation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.597\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIDS as the gold standard, an agreement analysis of the modified Mallamapati test with and without phonation in predicting difficult intubation\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\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eDifficult intubation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLevel of agreement\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKappa\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\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\u003eMMT without phonation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.518\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMMT with phonation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.531\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe χ2 test was significant and showed P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 association between CM-L scoring and IDS within Mallampati test for both approaches to predict difficulty laryngoscopy is summarized at Table \u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e \u003cem\u003eby comparing statistical data\u003c/em\u003e. The diagnostic power of the MMT without and with phonation in predicting of difficult intubation in relation to IDS and CM-L scoring is summarized at Table \u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e by comparing statistical data. MMT conducted without phonation had the highest sensitivity for predicting difficult laryngoscopy and intubation, but MMT performed with phonation had a superior specificity for identifying easy intubation.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eusing Cormack-Lehane scoring as a gold standard, the modified mallampati test predictive power in various approaches to diagnosing difficulties laryngoscopy\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStatistical parameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMMT without phonation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMMT with phonation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSensitivity (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecificity (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrue positive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFalse positive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrue negative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e205\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFalse negative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePPV (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNPV (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAccuracy (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\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\u003ePhi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.603\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.603\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.858\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.831\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eusing IDS as a gold standard, the modified mallampati test predictive power in various approaches to diagnosing difficulties intubation\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStatistical parameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMMT without phonation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMMT with phonation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSensitivity (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecificity (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrue positive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFalse positive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrue negative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e208\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFalse negative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePPV (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNPV (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAccuracy (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\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\u003ePhi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.552\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.880\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.839\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBoth techniques have good sensitivity and specificity on the prediction of difficult laryngoscopy and intubation, and the area under curve in ROC analysis shows that they had a level of good in terms of sensitivity and 1-specificity (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cem\u003eand\u003c/em\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), making them a useful diagnostic tool for predicting difficult laryngoscopy and intubation outcomes. The Table \u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e summarize the sensitivity, specificity, accuracy, true positive, false negative, AUC, positive predictive value, and negative predictive value of the Mallampati test during various approaches as tested during laryngoscopy.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThere are many airway assessment techniques that exist with the goal of accurately predicting difficult airways. The Mallampati test is the most commonly used airway assessment in clinical practice. It can be performed with and without phonation to predict difficult airways. This study comprised a total of 258 adult patients. Among those, difficult laryngoscopy and intubation were identified 35 (13.6%) and 27 (10.5%), respectively.\u003c/p\u003e \u003cp\u003eThe results of our study are similar to a study done in Ethiopia, at Gonder University Hospital, which states that the incidence of laryngoscopy and intubation difficulties is approximately 12.3% and 9%, respectively, \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. In contrast to our results, Sankal et al.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e state that the incidence of difficult laryngoscopy and intubation was 23.1% and 14.6%, respectively, which was higher.\u003c/p\u003e \u003cp\u003eThis could be due to their study's use modified CML scoring, which includes grade IIb as a difficult laryngoscopic view, as opposed to classic Cormack\u0026ndash;Lehane scoring, which considers grade II without subdivision as easy, thereby omitting the vast majority of patients.\u003c/p\u003e \u003cp\u003eOur study shows that the kappa agreement between MMT grading with and without a phonation approach is 0.598, which indicates moderate agreement. In terms of predicting difficult laryngoscopy and tracheal intubation, both the Mallampati tests with and without phonation demonstrated moderate agreement. The result of this study is consistent with the kappa agreement reported by Sankal et al \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn our study, MMT without phonation identified 29 of 35 true difficult laryngoscopy with a sensitivity of around 82.9%, whereas the modified Mallampati test with phonation identified 26 out of 35 with a sensitivity of about 74.3%. However, the Mallampati test without phonation had a larger false positive than the phonation approach on the prediction of difficult laryngoscopy (FP, 25 vs FP, 18), respectively, making it less specific than the phonation approach. MMT with phonation had 91.9% specificity in relation to laryngoscopy, whereas MMT without phonation had 88.3% specificity. In line with our study khan et al, described that, the sensitivity and specificity of Mallampati test without phonation on prediction of difficult laryngoscopy had (Se, 86.3% vs Sp, 84.7%), respectively. On the other hand, the phonation approach had the sensitivity and the specificity of (Se, 46.41% Vs Sp, 96.92%), respectively \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. In contrary to our study, Kentaro et al\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e described that the Mallampati test with phonation has a good correlation with Cormack-Lehane scoring for prediction of difficult laryngoscopy.\u003c/p\u003e \u003cp\u003eThis study shows that MMT without phonation identified 24 patients with a sensitivity of 88.9% out of 27 patients who actually had difficulty during intubation. On the other hand, MMT with phonation, on the other hand, detected 21 individuals from the difficult intubation with a sensitivity of 77.8%. However, the Mallampati test with a phonation method exhibited a better specificity for predicting easy intubation than the non-phonation approach, with a specificity of (90% vs 86.6), respectively. This indicates that MMT without phonation has higher sensitivity in the prediction of difficult intubation with less specificity as compared to MMT with phonation. This study result was consistent with the study done by Awashti et al, who stated that, Mallampati test without phonation had sensitivity and specificity for difficult intubation were 80% and 93.68%, respectively, whereas the phonation approach had the sensitivity and specificity for difficult intubation were 40% and 98.95%, respectively \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn addition, our study analysed the positive and negative predictive values and accuracy of each approach for predicting difficult laryngoscopy and intubation. The MMT with phonation exhibited a higher PPV than the non-phonation approach. However, in the Mallampati test, NPV is higher when it is conducted without phonation than with the phonation approach. The MMT with phonation demonstrated higher accuracy in predicting difficult laryngoscopy and intubation, with an accuracy of 89.5% and 88.75%, respectively, than the non-phonation approach, with an accuracy of 87.98% and 87.2%, respectively. This finding was in line with the findings of Sankal et al, who state that, MMT in the sitting posture without phonation had 75.4% accuracy, whereas MMT in the supine position without phonation had 67.7% accuracy. When performed in the supine position with phonation, MMT is more effective at predicting difficult laryngoscopic views (accuracy 85.4%) \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eROC curve analysis was used to compare the predictive ability of the Mallampati test with and without phonation to Cormack-Lehane as well as IDS findings (easy/difficult). The MMT without phonation had an AUC for predicting difficult laryngoscopy of 0.858, which was higher than the phonation approach, which had an AUC of 0.831. In addition, the AUC for predicting difficult tracheal intubation was higher in the non-phonation approach (0.880) than in MMT with phonation (0.839). Our findings were consistent with the study done by Awasthi et al \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, who found that the AUC for predicting difficult laryngoscopy and intubation were higher in MMT without phonation (0.830 and 0.868, respectively) than in the phonation approach (0.637 and 0.695, respectively). As the results show, the diagnostic performance of both approaches is comparable, making them very good airway assessment techniques.\u003c/p\u003e"},{"header":"5. Conclusion and Recommendation","content":"\u003cp\u003eBased on our study results, MMT with phonation has higher accuracy, specificity, and PPV in the prediction of difficult laryngoscopy and intubation than the non-phonation approach. Even though it has a little lower sensitivity than the non-phonation technique, it has a very good and comparable prediction of difficult airways. We believe that MMT combined with phonation can be used as an alternative assessment tool for predicting difficult airways.\u003c/p\u003e"},{"header":"6. Strength and limitation of the study","content":"\u003cp\u003e \u003cb\u003e6.1 Strength\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eBecause the study is unique to our country, it lays the groundwork for future research, particularly for those interested in studying the effects of phonation on MMT with other airway assessment parameters for prediction of difficult airways.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e6.2 Limitation\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eThe area where the investigation was conducted was not only a medical centre but also a learning centre. It tends to involve less experienced students in the intubation process.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eThe Mallampati test is significantly prone to subjectivity.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e"},{"header":"7. Operational definition","content":"\u003cp\u003e\u003cspan\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e7.1 Mallampati: - Identifies\u003c/strong\u003e the size of the tongue with the oral cavity (Grade I: Soft palate, uvula, fauces, pillars visible; Grade II: Soft palate, major part of uvula, fauces visible.\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eGrade III: only soft palate visible; Grade IV: only hard palate visible)\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eMMT with phonation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e- Patient open mouth and protrude tongue maximally with saying \u0026quot;Ah sound\u0026quot;.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMMT without phonation: -\u003c/strong\u003e Patient open mouth and protrude tongue maximally without saying \u0026quot;Ah sound\u0026quot;.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e7.2 Cormack-Lehane score\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eScore I: glottis fully visible\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eScore II: glottis partially visible\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eScore III: only epiglottis visible\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eScore IV: epiglottis not visible\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eScore I and II considered as easy Laryngoscopy\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eScore III and IV considered as difficult Laryngoscopy\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003e7.3. Intubation difficulty score (IDS)\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eIDS\u0026thinsp;\u0026le;\u0026thinsp;5, easy intubation\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eIDS\u0026thinsp;\u0026gt;\u0026thinsp;5, Difficult Intubation (Table \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e)\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab8\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eIDS score\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSymbol\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eParameters\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCriteria\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumber of attempts\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEach additional attempts adds one point\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumber of operators\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEach additional operators adds one point\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumber of alternatives methods:\u003c/p\u003e\n \u003cp\u003eA. Repositioning of patient\u003c/p\u003e\n \u003cp\u003eB. Change of material (blade, tube, using a\u003c/p\u003e\n \u003cp\u003estylet)\u003c/p\u003e\n \u003cp\u003eC. Change in approach\u003c/p\u003e\n \u003cp\u003e(orotracheal or nasotracheal)\u003c/p\u003e\n \u003cp\u003eD. Use of another technique\u003c/p\u003e\n \u003cp\u003e(fiberscopy, intubation through a\u003c/p\u003e\n \u003cp\u003elaryngeal mask)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEvery alternative methods adds one points\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCormack-Lehane scoring\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003en-1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLifting force required\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNormal force\u0026thinsp;=\u0026thinsp;0\u003c/p\u003e\n \u003cp\u003eIncreased force\u0026thinsp;=\u0026thinsp;1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLaryngeal pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot applied pressure\u0026thinsp;=\u0026thinsp;0\u003c/p\u003e\n \u003cp\u003eApplied pressure\u0026thinsp;=\u0026thinsp;1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVocal cord mobility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAbduction\u0026thinsp;=\u0026thinsp;0\u003c/p\u003e\n \u003cp\u003eAdduction\u0026thinsp;=\u0026thinsp;1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e"},{"header":"Abbreviations","content":"AAU (Addis Ababa University); AUC (Area under curve); CML (Cormack-Lehane Score); IDS (Intubation Difficulty Score) MMT Modified Mallampati Test NPV (Negative Predictive Value); PPV (Positive Predictive Value) ROC (Receiver Operating Characteristics curve); TASH (Tikure Anbessa Specialized Hospital)"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval:\u003c/strong\u003e This study was reviewed and approved by an institutional review board (ethics committee) of Addis Ababa university ethical review board with meeting No 130-/2021. Written form of consent from the patient was taken and the assessment done accordingly, the confidentiality of participant records and privacy of the health facility were maintained.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e: the Authors have no conflict of interest to declare\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGuarantors:\u003c/strong\u003e All authors\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: \u0026nbsp;no financial aid\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material:\u003c/strong\u003e The data used in this study was collected by data collectors and submitted to authors, who are willing to share the data upon request from peer researchers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors Contribution:\u003c/strong\u003e Authors will take public responsibility for the contents, have contributed substantially to the drafting and have approved the final version. All authors Involved on substantial intellectual contributions to conception, design and acquisition of data analysis and interpretation of data as well as on preparing the manuscript to this study \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cstrong\u003eAcknowledgement:\u0026nbsp;\u003c/strong\u003e\u003c/strong\u003ewe would like to thank Addis Ababa University for the financial support. Additionally, we would like to express our sincere gratitude to everyone who participated in the study, collected data, and used and one other way to help us to complete this work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBellhouse P. Predicting difficult intubation. Br J Anaesth. 1991;67:505.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTse JC, Rimm EB, Hussain A. Predicting Difficult Patients Scheduled Blind Study. Anaesthesia 254\u0026ndash;8 (1995).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePrakash S, et al. Difficult laryngoscopy and intubation in the Indian population: An assessment of anatomical and clinical risk factors. Indian J Anaesth. 2013;57:569\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAwasthi P et al. Comparison of Mallampati test in supine and upright positions with and without phonation in predicting difficult laryngoscopy and intubation in age groups 3\u0026ndash;10 years. 6, 61\u0026ndash;7 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMallampati SR, et al. A clinical sign to predict difficult tracheal intubation; a prospective study. Can Anaesth Soc J. 1985;32:429\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSAMSOON GLT, YOUNG JR. B. Difficult tracheal intubation: a retrospective study. Anaesthesia. 1987;42:487\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMallampati SR et al. A clinical sign to predict difficult tracheal intubation: a prospective study. 429\u0026ndash;34 (1985).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorkeneh SA, Gebregzi AH, Denu ZA. Magnitude and Predisposing Factors of Difficult Airway during Induction of General Anaesthesia. \u003cem\u003eAnesthesiol. Res. Pract.\u003c/em\u003e 2017, (2017).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSankal A, Halemani KR, Bhadrinath N. Assessment of the Effect of Supine Posture and Phonation on Modified Mallampati Grading and its Applicability in Prediction of Difficult Airway. 19\u0026ndash;24 (2018) \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4103/jmgims.jmgims\u003c/span\u003e\u003cspan address=\"10.4103/jmgims.jmgims\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhan ZH, Eskandari S, Yekaninejad MS. A comparison of the Mallampati test in supine and upright positions with and without phonation in predicting difficult laryngoscopy and intubation: A prospective study. J Anaesthesiol Clin Pharmacol. 2015;31:207\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOuchi K, Hosokawa R, Yamanaka H, Nakajima Y, Nakamura Y. Mallampati test with phonation, tongue protrusion and supine position is most correlated with Cormack \u0026ndash; Lehane test. Odontology. 2020. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10266-020-00490-3\u003c/span\u003e\u003cspan address=\"10.1007/s10266-020-00490-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Mallapati test, phonation, difficult laryngoscopy, difficult intubation","lastPublishedDoi":"10.21203/rs.3.rs-3982259/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3982259/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMallampati test is one of the most widely used airway tests to predict laryngoscopy and tracheal intubation difficulties. The Mallampati test without phonation is routinely practiced, but its sensitivity in predicting difficult intubation is controversial.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo compare the Malampati test with and without phonation in predicting difficult laryngoscopy and tracheal intubation among adult elective surgical patients who underwent general anaesthesia.\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e \u003cp\u003eA hospital based cross-sectional study was performed on 258 adult elective surgery patients who required tracheal intubation at Tikur Anbessa specialized hospital. A systemic random sampling technique was employed to select study participant and the Mallampati test with and without phonation was performed during preoperative assessment. Then a laryngoscopic view was recorded at the time of tracheal intubation, and Mallampati test grades I and II were classified as easy, while grades III and IV were classified as difficult for tracheal intubation. The data was entered by Epi info and analysed with the statistics package of the social science software version 26. Statistical significance was defined at p-value of less than 0.05. This study used specificity, sensitivity, accuracy, and positive and negative predictive values as statistical measures.\u003c/p\u003e\u003ch2\u003eResult\u003c/h2\u003e \u003cp\u003eThe prevalence of laryngoscopy and intubation difficulty was 13.6% and 10.5%, respectively. Mallampati test without phonation had a sensitivity of 82.9% and a specificity of 79.1% for difficult laryngoscope. And it had a sensitivity of 88.9%, a specificity of 87% for difficult intubation. MMT with phonation had a sensitivity of 74.3% and a specificity of 91.9% for difficult laryngoscopy and it had a sensitivity of 77.8% and specificity of 90% for difficult intubation.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eBased on our study results, MMT with phonation has higher accuracy, specificity, and PPV in the prediction of difficult laryngoscopy and intubation than the non-phonation approach.\u003c/p\u003e","manuscriptTitle":"Comparison of Mallampati test with and without phonation for prediction of difficult airways on adult patient (Prospective observational study)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-15 19:48:51","doi":"10.21203/rs.3.rs-3982259/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":"e71b3df4-5390-4ffa-a0c7-8848bd476250","owner":[],"postedDate":"March 15th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-18T06:15:08+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-15 19:48:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3982259","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3982259","identity":"rs-3982259","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}