Nomograms for predicting difficult airway based on ultrasound assessment
Abstract Background Accurate prediction of the difficult airway (DA) could help to prevent catastrophic consequences in emergency resuscitation, intensive care, and general anesthesia. Until now, there is no nomogram prediction model for DA based on ultrasound assessment. In this study, we aimed to...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2022-01-01
|
| Series: | BMC Anesthesiology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12871-022-01567-y |
| _version_ | 1818752799168528384 |
|---|---|
| author | Bin Wang Weidong Yao Qi Xue Mingfang Wang Jianling Xu Yongquan Chen Ye Zhang |
| author_facet | Bin Wang Weidong Yao Qi Xue Mingfang Wang Jianling Xu Yongquan Chen Ye Zhang |
| author_sort | Bin Wang |
| collection | DOAJ |
| description | Abstract Background Accurate prediction of the difficult airway (DA) could help to prevent catastrophic consequences in emergency resuscitation, intensive care, and general anesthesia. Until now, there is no nomogram prediction model for DA based on ultrasound assessment. In this study, we aimed to develop a predictive model for difficult tracheal intubation (DTI) and difficult laryngoscopy (DL) using nomogram based on ultrasound measurement. We hypothesized that nomogram could utilize multivariate data to predict DTI and DL. Methods A prospective observational DA study was designed. This study included 2254 patients underwent tracheal intubation. Common and airway ultrasound indicators were used for the prediction, including thyromental distance (TMD), modified Mallampati test (MMT) score, upper lip bite test (ULBT) score temporomandibular joint (TMJ) mobility and tongue thickness (TT). Univariate and the Akaike information criterion (AIC) stepwise logistic regression were used to identify independent predictors of DTI and DL. Nomograms were constructed to predict DL and DTL based on the AIC stepwise analysis results. Receiver operating characteristic (ROC) curves were used to evaluate the accuracy of the nomograms. Results Among the 2254 patients enrolled in this study, 142 (6.30%) patients had DL and 51 (2.26%) patients had DTI. After AIC stepwise analysis, ULBT, MMT, sex, TMJ, age, BMI, TMD, IID, and TT were integrated for DL nomogram; ULBT, TMJ, age, IID, TT were integrated for DTI nomogram. The areas under the ROC curves were 0.933 [95% confidence interval (CI), 0.912–0.954] and 0.974 (95% CI, 0.954–0.995) for DL and DTI, respectively. Conclusion Nomograms based on airway ultrasonography could be a reliable tool in predicting DA. Trial registration Chinese Clinical Trial Registry (No. ChiCTR-RCS-14004539 ), registered on 13th April 2014. |
| first_indexed | 2024-12-18T04:57:12Z |
| format | Article |
| id | doaj.art-f2f78e5b66584b1bab628313d4ce5a91 |
| institution | Directory Open Access Journal |
| issn | 1471-2253 |
| language | English |
| last_indexed | 2024-12-18T04:57:12Z |
| publishDate | 2022-01-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Anesthesiology |
| spelling | doaj.art-f2f78e5b66584b1bab628313d4ce5a912022-12-21T21:20:14ZengBMCBMC Anesthesiology1471-22532022-01-012211810.1186/s12871-022-01567-yNomograms for predicting difficult airway based on ultrasound assessmentBin Wang0Weidong Yao1Qi Xue2Mingfang Wang3Jianling Xu4Yongquan Chen5Ye Zhang6Department of Anesthesiology, The Second Affiliated Hospital of Anhui Medical UniversityDepartment of Anesthesiology, The First Affiliated Hospital of Wannan Medical College, Yijishan HospitalDepartment of Anesthesiology, The Second Affiliated Hospital of Anhui Medical UniversityDepartment of Anesthesiology, The First Affiliated Hospital of Wannan Medical College, Yijishan HospitalDepartment of Anesthesiology, The First Affiliated Hospital of Wannan Medical College, Yijishan HospitalDepartment of Anesthesiology, The First Affiliated Hospital of Wannan Medical College, Yijishan HospitalDepartment of Anesthesiology, The Second Affiliated Hospital of Anhui Medical UniversityAbstract Background Accurate prediction of the difficult airway (DA) could help to prevent catastrophic consequences in emergency resuscitation, intensive care, and general anesthesia. Until now, there is no nomogram prediction model for DA based on ultrasound assessment. In this study, we aimed to develop a predictive model for difficult tracheal intubation (DTI) and difficult laryngoscopy (DL) using nomogram based on ultrasound measurement. We hypothesized that nomogram could utilize multivariate data to predict DTI and DL. Methods A prospective observational DA study was designed. This study included 2254 patients underwent tracheal intubation. Common and airway ultrasound indicators were used for the prediction, including thyromental distance (TMD), modified Mallampati test (MMT) score, upper lip bite test (ULBT) score temporomandibular joint (TMJ) mobility and tongue thickness (TT). Univariate and the Akaike information criterion (AIC) stepwise logistic regression were used to identify independent predictors of DTI and DL. Nomograms were constructed to predict DL and DTL based on the AIC stepwise analysis results. Receiver operating characteristic (ROC) curves were used to evaluate the accuracy of the nomograms. Results Among the 2254 patients enrolled in this study, 142 (6.30%) patients had DL and 51 (2.26%) patients had DTI. After AIC stepwise analysis, ULBT, MMT, sex, TMJ, age, BMI, TMD, IID, and TT were integrated for DL nomogram; ULBT, TMJ, age, IID, TT were integrated for DTI nomogram. The areas under the ROC curves were 0.933 [95% confidence interval (CI), 0.912–0.954] and 0.974 (95% CI, 0.954–0.995) for DL and DTI, respectively. Conclusion Nomograms based on airway ultrasonography could be a reliable tool in predicting DA. Trial registration Chinese Clinical Trial Registry (No. ChiCTR-RCS-14004539 ), registered on 13th April 2014.https://doi.org/10.1186/s12871-022-01567-yAirway managementIntubation, IntratrachealLaryngoscopyNomogramUltrasonography |
| spellingShingle | Bin Wang Weidong Yao Qi Xue Mingfang Wang Jianling Xu Yongquan Chen Ye Zhang Nomograms for predicting difficult airway based on ultrasound assessment BMC Anesthesiology Airway management Intubation, Intratracheal Laryngoscopy Nomogram Ultrasonography |
| title | Nomograms for predicting difficult airway based on ultrasound assessment |
| title_full | Nomograms for predicting difficult airway based on ultrasound assessment |
| title_fullStr | Nomograms for predicting difficult airway based on ultrasound assessment |
| title_full_unstemmed | Nomograms for predicting difficult airway based on ultrasound assessment |
| title_short | Nomograms for predicting difficult airway based on ultrasound assessment |
| title_sort | nomograms for predicting difficult airway based on ultrasound assessment |
| topic | Airway management Intubation, Intratracheal Laryngoscopy Nomogram Ultrasonography |
| url | https://doi.org/10.1186/s12871-022-01567-y |
| work_keys_str_mv | AT binwang nomogramsforpredictingdifficultairwaybasedonultrasoundassessment AT weidongyao nomogramsforpredictingdifficultairwaybasedonultrasoundassessment AT qixue nomogramsforpredictingdifficultairwaybasedonultrasoundassessment AT mingfangwang nomogramsforpredictingdifficultairwaybasedonultrasoundassessment AT jianlingxu nomogramsforpredictingdifficultairwaybasedonultrasoundassessment AT yongquanchen nomogramsforpredictingdifficultairwaybasedonultrasoundassessment AT yezhang nomogramsforpredictingdifficultairwaybasedonultrasoundassessment |