Comparison of the Acromio Axillosuprasternal Notch Index with Ratio of Height to Thyromental Distance and Mallampati Classification for the Anticipation of Difficult Intubation in Apparently Normal Patients

Download Article

DOI: 10.21522/TIJPH.2013.13.01.Art093

Authors : Maghimaa M, Nagapriya Nagendran, Sathyapriya Sathiyamoorthy, Lakshmi R, Hemapriya Namassivayam, Bharath S

Abstract:

Airway management is crucial in anaesthesia, with difficult intubation posing risks. The Acromio Axillo acromio-axillo-suprasternal notch Index (AASI) has shown promise in predicting difficult airways. This study compares AASI with height to thyromental distance ratio and Mallampati classification in anticipating difficult intubation. A prospective observational study at Saveetha Medical College & Hospital assessed 60 patients from September 2023 to August 2023. Inclusion criteria were ages 18-60 and consent for elective surgery under general anesthesia. Exclusions included distorted head and neck anatomy, mouth opening < 3 cm, obesity, sleep apnea, pregnancy, or refusal. Measurements utilized a Thyromental scale. Participants (n=60) had a mean age of 35.021 years, with 45% males and 55% females. The mean BMI was 31.182. Most were ASA class 2 (66.6%) and MMP grade 2 (46.6%). AASI >0.5 was seen in 76.6% of participants. CL Grade distribution showed 33.3% in Grade 1 and 73.3% in Grades 1 and 2 combined. AASI emerged as a superior predictor for Difficult Visualization of the Larynx (DVL), surpassing MMP and TMD. Its heightened sensitivity makes it an effective screening tool, complementing existing methods. Further studies are needed to validate these findings and assess AASI's applicability across diverse patient populations. Integrating AASI into routine clinical practice may enhance patient outcomes by enabling proactive airway management strategies in high-risk individuals.

References:

[1].   Venkatalakshmana, S. K., Kaaviya, R., 2024. Enhancing Airway Management: A Comparative Study of Macintosh and TAS Scope in Difficult Intubations. J Pharm Bioallied Sci, 16, S2205.

[2].   Avva, U., Lata, J. M., Kiel, J., 2024. Airway Management. StatPearls. Treasure Island (FL): StatPearls Publishing.

[3].   Crawley, S. M., Dalton, A. J., 2015, Predicting the difficult airway. BJA Educ, 15, 253–258.

[4].   Apfelbaum, J. L., Hagberg, C. A., Connis, R. T., Abdelmalak, B. B., Agarkar, M., Dutton, R. P., et al., 2022. American Society of Anesthesiologists Practice Guidelines for Management of the Difficult Airway*. Anesthesiology, 136, 31–81.

[5].   Divatia, J., Bhowmic., 2005. Complications of endotracheal intubation and other airway management procedures. Indian J Anaesth, 49, 308–318.

[6].   Rajkhowa, T., Saikia, P., Das, D., 2018. An observational prospective study of performance of acromioaxillosuprasternal notch index in predicting difficult visualisation of the larynx. Indian J Anaesth, 62, 945–950.

[7].   Alanazi, A., 2015. Intubations and airway management: An overview of Hassles through third millennium. J Emerg Trauma Shock, 8, 99–107.

[8].   8.     Ravindran, B., 2023. Innovations in the Management of the Difficult Airway: A Narrative Review. Cureus, 15(2), e35117.

[9].   Kamranmanesh, M. R., Jafari, A. R., Gharaei, B., Aghamohammadi, H., Poor Zamany, N. K. M., Kashi, A. H., 2015. Comparison of acromioaxillosuprasternal notch index (a new test) with modified Mallampati test in predicting difficult visualization of larynx. Acta Anaesthesiol Taiwan, 51, 141–144.

[10].  Ezri, T., Gewürtz, G., Sessler, D. I., Medalion, B., Szmuk, P., Hagberg, C., 2003. Prediction of difficult laryngoscopy in obese patients by ultrasound quantification of anterior neck soft tissue. Anaesthesia, 58, 1111–1114.

[11].  Hillman, D. R., Platt, P. R., Eastwood, P. R., 2003. The upper airway during anaesthesia. Br J Anaesth, 91, 31–39.

[12].  Nasr-Esfahani, M., Honarmand, A., Safavi, S. M., Anvari Tafti, M., 2020. How to Predict Difficult Tracheal Intubation: The Application of Acromio-axillo-suprasternal Notch Index. Adv Biomed Res, 9, 19.

[13].  Stutz, E. W., Rondeau, B., 2024. Mallampati Score. StatPearls. Treasure Island (FL): StatPearls Publishing.

[14].  Mallhi, A. I., Abbas, N., Naqvi, S. M. N., Murtaza, G., Rafique, M., Alam, S. S., 2018. A comparison of Mallampati classification, thyromental distance and a combination of both to predict difficult intubation. Anaesth Pain Intensive Care, 22.

[15].  Merah, N. A., Foulkes-Crabbe, D. J. O., Kushimo, O. T., Ajayi, P. A., 2004. Prediction of difficult laryngoscopy in a population of Nigerian obstetric patients. West Afr J Med, 23, 38–41.

[16].  Merola, R., Troise, S., Palumbo, D., D’Auria, D., Dell’Aversana Orabona, G., Vargas, M., 2024. Airway management in patients undergoing maxillofacial surgery: State of art review. J Stomatol Oral Maxillofac Surg, 102044.

[17].  Shahzan, M. S., Gounder, R., Ganapathy, D., 2019. Assessment of buccal vestibular depth among completely edentulous patients. Drug Invent Today, 11, 256–258.

[18].  Antony, M., & Mohanraj, K. G., 2019. Sex determination using geometric dimensions of greater sciatic notch and subpubic angle of human pelvic bone: A morphometric study. Drug Invention Today, 12(10).

[19].  Jaganathan, R., Vishnuvanditha, V., Selvankumar, T. 2024. Control of Multidrug-Resistant Hospitalized Pathogenic Bacteria Using the Secondary Metabolites of Calotropis procera and In-silico Analysis of Bacterial Virulent Proteins. Texila International Journal of Public Health. DOI: 10.21522/TIJPH.2013.SE.24.05.Art036

[20].  Safavi, M., Honarmand, A., Hirmanpour, A., Zareian, N., 2016. Acromio-axillo-suprasternal notch index: a new screening test to predict difficult laryngoscopy in obstetric patients scheduled for caesarean delivery. Eur J Anaesthesiol, 33, 596–598.

[21].  Kamranmanesh, M. R., Jafari, A. R., Gharaei, B., 2013. Aghamohammadi, H, Poor Zamany, N K. M, Kashi, A. H. Comparison of acromioaxillosuprasternal notch index (a new test) with modified Mallampati test in predicting difficult visualization of larynx. Acta Anaesthesiol Taiwanica Off J Taiwan Soc Anesthesiol, 51, 141–144.

[22].  Honarmand, A., Kheirabadi, D., Safavi, M. R., Taghaei, M., Golshani Nasab, M., 2019. Comparison of the acromio-axillosuprasternal notch index with five anatomical indices for the prediction of difficult laryngoscopy and intubation. Eur J Anaesthesiol, 36, 542–544.

[23].  Saritha, P., Arunprakash, S., Srinivasan, P., Selvankumar, T., Aldawood, S., Kim, W., & Song, K. S., 2024, Synthesis of Luminescent Copper Nanoparticles Using Couroupita guianensis Flower Extract: Evaluation of Antibacterial and Anticancer Activities. Luminescence, 39(10), e4913.

[24].  Abareethan, M., Sathiyapriya, R., Pavithra, M. E., Parvathy, S., Thirumalaisamy, R., Selvankumar, T., & Almoallim, H. S., 2024, Biogenic silver nanoparticles from Solanum trilobatum leaf extract and assessing their antioxidant and antimicrobial potential. Chemical Physics Impact, 9, 100771.

[25].  Jaganathan, R., Kumaradhas, P. 2024. Structural insights into Furin enzyme inhibition to block SARS-CoV-2 spike protein cleavage: an in-silico approach. 3 Biotech, 14(9), 213.

[26].  Jaganathan, R., Vishnuvanditha, V., Selvankumar, T. 2024. Control of Multidrug-Resistant Hospitalized Pathogenic Bacteria Using the Secondary Metabolites of Calotropis procera and In-silico Analysis of Bacterial Virulent Proteins. Texila International Journal of Public Health. DOI: 10.21522/TIJPH.2013.SE.24.05.Art036.