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

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.