Airway Management Clinical Trial
Official title:
Clinical Trial of Comparative Evaluation of Modified Mallampati Score and Modified Mallampati Score Along With Thyromental Distance, Anatomical Abnormalities and Cervical Mobility in Predicting Difficult Airway
The study title "Clinical trial of comparative evaluation of the Modified Mallampati Score
and Modified Mallampati Score along with Thyromental distance, Anatomical abnormality, and
Cervical mobility (M-TAC) in Predicting Difficult Airway " was undertaken to evaluate
prediction of difficult airway by comparing preoperative airway evaluation tests.
Mallampati classification is the most used screening test for detection of difficult
intubation it is a classification of oropharyngeal view. Other tests include sternomental
distance, thyromental distance, Wilson risk sum score, upper lip bite test, protrusion of
mandible, tooth morphology, head extension, mouth opening, body mass index, 3-3-2 rule and
ultrasonography of neck soft tissue. We studied 200 adult ASA I & II patients of either sex,
aged between 18-60 yrs undergoing elective surgery receiving general anesthesia.
Modified mallampati classification had four grades & each grade was given a score, similarly
thyromental distance (TMD), anatomical abnormality (AA) & cervical mobility (CM) was
classified into three grades & each grade was given a score. For M-TAC individual scores
were added.
The term 'airway' refers to the upper airway which may be defined as the extra-pulmonary air
passage, consisting of the nasal and oral cavities, pharynx, larynx, trachea and large
bronchi.
The most commonly applied methods of oxygenation is ventilation through a tracheal tube, a
laryngeal mask, or a face mask. Problems with tracheal intubation remain the major cause of
death and disability due to anaesthesia in analyses of records of the United Kingdom medical
defence societies and in the American Society of Anaesthesiologists closed claims database.
'Difficult airway' is one in which there is a problem in establishing or maintaining gas
exchange via a mask, an artificial airway or both. Prediction of difficult airway management
remains a pivotal challenge for anaesthesiologists because accurate prediction gets altered
the potentially dangerous unanticipated airway to an anticipated difficult airway with,
predominantly, ample time for proper preparation. This is helpful in reducing potential
complications by the allocation of experienced personnel and by using relevant equipment and
well planned strategies .
However rare, in spite of this, occurrence of difficult airway management still occurs and
it prompts to increase the risk of morbidity and mortality - especially when not
anticipated. Unanticipated difficulty in intubation in patients for elective surgical
procedures can occur in 1.5 to 13 percent cases with none of the above mentioned
abnormalities resulting in both morbidity and mortality.
Several pre-operative risk factors for assessing airway difficulties have been identified,
yet none have convincing diagnostic accuracy when using in isolation. Combining several risk
factors increase the predictive value of the test and multivariable risk models have been
developed.
As the anatomy of the head and neck region plays a leading role in deciding the fateful
profile of the airway, especially associated with influential abnormality. So, simple
bedside test, such as the modified Mallampati test, has been found to be of limited value
and cannot be relied on for using in predicting difficult laryngoscopy. Exclusively when
each individual was investigated in isolation using a single scoring test, as it has long
been realized that difficult laryngoscopy is a multifactorial problem. Thus, effective
prediction requires a combination of multiple tests to provide a high index of sensitivity
and specificity for prediction of difficult airway. Thus, we ventured to combine Mallampati
score with some other anatomical factors (thyromental distance, anatomical abnormality and
cervical mobility) to develop a new and simpler clinical prediction model for a better
predictive ability.
;
Observational Model: Case-Crossover, Time Perspective: Prospective
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