Intubation difficulty scale contributors and time delay in clinical practice. Issue 4 (28th January 2022)

• Record Type: Journal Article
• Authors: Kang, Ting-Wei; Wang, Jung-Der; Tsai, Yi-Seng; Lin, Chung-Ren; Tseng, Chia-Chih Alex
• Editors: Tokumine., Joho
• Is Part Of: Medicine. Volume 101:Issue 4(2022)
• Page Start: e28724
• Publication Date: 2022-01-28
• Subjects: airway management -- difficult intubation -- duration of successful intubation -- IDS -- intubation time -- perceived difficulty of intubation; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000028724
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract : Abstract: The intubation difficulty scale (IDS) includes 7 contributors that provide a comprehensive assessment of difficult intubation. However, the effect of each contributor is unclear, and the scale has not been revalidated recently and has not been validated in orient. This study determined the duration of successful intubation (DSI) for each of these 7 contributors. The patients were intubated by attending anesthesiologists. The duration and other data were recorded by 2 research assistants. Anaesthesiologists reported the IDS and their perceptions. A linear mixed-effects model with a DSI was constructed using IDS factors. In total, 1095 patients were enrolled. The average DSI was 23.9 ± 21.8 seconds (37.1% IDS = 0). All 7 factors were independently associated with duration, with the exception of vocal cord adduction. The best model was as follows: DSI (in seconds) = 15.2 + 31.1 (number of additional attempts) + 26.2 (number of additional operators) + 11.4 (number of alternative techniques) + 7.9 (increased lift force) + 4.9 (external laryngeal pressure) + 3.5 (Cormack grade 1). The mixed models were similar except for the regression coefficient for the number of alternative techniques that decreased from 11.4 to 6.9 seconds. We confirmed that each IDS contributor affects the DSI and validated a prediction model with 6 IDS contributors. This prediction model may facilitate the development of strategic plans for critical airway management. Furthermore, it could improve simulations and monitor learning progress and help provide valuable feedback.