Comparison of acromio-axillo-suprasternal notch index with ratio of neck circumference to thyromental distance in predicting difficult intubation
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 发起方
- 入组人数
- 340
- 试验地点
- 1
- 主要终点
- predictive accuracy(sensitivity, apecificity and predictive value) of AASI and NC to TMD ration in identifying difficult intubation, validated against Cormack-Lehane grade or intubation difficulty score(IDS)
研究概览
简要总结
Title:
Comparison of acromio-axillo-suprasternal notch index with ratio of neck circumference to thyromental distance n predicting difficult intubation
This prospective observational study aims to compare the effectiveness of the acromio-axillo-suprasternal notch index and neck circumference to thyromental distance ratio in predicting difficult intubation in adult surgical patients. Preoperative assessments will include age, sex, surgery, ASA status, height, weight, BMI, mouth opening, mallampati class, temoromandibular joint, sternomental distance, hyomental distance, upper lip bite test, inter incisor gap, thyromental distance , neck circumference, AASI, CL grading, IDS score. The study seeks to determine the sensitivity, specificity and predictive values of these indices for identifying patients at risk of difficult intubation, providing valuable insights for improving airway management strategies.
研究设计
- 研究类型
- Observational
入排标准
- 年龄范围
- 18.00 Year(s) 至 60.00 Year(s)（—）
- 性别
- All
入选标准
- •Patients aged 18-60 years scheduled to undergo elective surgery under general endotracheal anaesthesia Adults belonging to ASA physical status (ASA PS)I,II & III.
排除标准
- •Patients with obvious pathological condition in and around the mouth and neck Restricted mouth opening Pregnant ladies Patients requiring rapid sequence intubation.
结局指标
主要结局
predictive accuracy(sensitivity, apecificity and predictive value) of AASI and NC to TMD ration in identifying difficult intubation, validated against Cormack-Lehane grade or intubation difficulty score(IDS)
时间窗: Baseline
次要结局
- sensitivity, specificity, correlation with other predictive tools.(Baseline)
研究者
Nithya Ramachandran
K S Hegde Medical Academy