scholarly journals Difficult mask ventilation in general surgical population: observation of risk factors and predictors

F1000Research ◽  
2014 ◽  
Vol 3 ◽  
pp. 204 ◽  
Author(s):  
Davide Cattano ◽  
Peter V. Killoran ◽  
Chunyan Cai ◽  
Anastasia D. Katsiampoura ◽  
Ruggero M. Corso ◽  
...  
Keyword(s):  
Risk Factors ◽  
Elective Surgery ◽  
Univariate Analysis ◽  
Predictive Score ◽  
Mask Ventilation ◽  
Individual Subject ◽  
Facial Hair ◽  
Difficult Mask Ventilation ◽  
Obstructive Sleep ◽  
Patients At Risk

Background: There are few predictors of difficult mask ventilation and a simple, objective, predictive system to identify patients at risk of difficult mask ventilation does not currently exist. We present a retrospective - subgroup analysis aimed at identifying predictive factors for difficult mask ventilation (DMV) in patients undergoing pre-operative airway assessment before elective surgery at a major teaching hospital.Methods: Data for this retrospective analysis were derived from a database of airway assessments, management plans, and outcomes that were collected prospectively from August 2008 to May 2010 at a Level 1 academic trauma center. Patients were stratified into two groups based on the difficulty of mask ventilation and the cohorts were analyzed using univariate analysis and stepwise selection method.Results: A total of 1399 pre-operative assessments were completed with documentation stating that mask ventilation was attempted. Of those 1399, 124 (8.9%) patients were found to be difficult to mask ventilate. A comparison of patients with and without difficult mask ventilation identified seven risk factors for DMV: age, body mass index (BMI), neck circumference, history of difficult intubation, presence of facial hair, perceived short neck and obstructive sleep apnea. Although seven risk factors were identified, no individual subject had more than four risk factors.Conclusion: The results of this study confirm that in a real world clinical setting, the incidence of DMV is not negligible and suggest the use of a simple bedside predictive score to improve the accuracy of DMV prediction, thereby improving patient safety. Further prospective studies to validate this score would be useful.

scholarly journals Utilization of apnea-hypopnea index as a novel predictive factor for difficult mask ventilation in the Chinese population under general anesthesia

2021 ◽  
Author(s):  
Jiayi Wang ◽  
Jingjie Li ◽  
Pengcheng Zhao ◽  
Xuan Pu ◽  
Rong Hu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Elective Surgery ◽  
Chinese Patients ◽  
Apnea Hypopnea Index ◽  
Mask Ventilation ◽  
Clinical Predictors ◽  
Clinical Trial Registry ◽  
Difficult Mask Ventilation ◽  
Obstructive Sleep ◽  
Threatening Situation

Abstract Purpose Difficult mask ventilation (DMV) is a potentially life-threatening situation that can arise during anesthesia. However, most clinical predictors of DMV are based on European and US populations. On the other hand, most predictive models consist of multiple factors and complicated assessments. Since obstructive sleep apnea (OSA) is among the most important risk factors associated with DMV, the apnea-hypopnea index (AHI) may play an important role in determining patient risk.The purpose of this study was to investigate the relationship between DMV and AHI, and to determine preoperative risk factors for DMV in Chinese patients. Methods A prospective cohort trial enrolled patients scheduled for elective surgery. After obtaining informed consent, patient demographic information was collected, and patients were tested with pre-operative polysomnography. The anesthesiologist who managed the airway graded the mask ventilation. The difficult mask ventilation was defined as the mask ventilation provided by an unassisted anesthesiologist without oral airway or other adjuvant. A logistic regression model was used to analyze the association between AHI and DMV. Results A total of 159 patients were analyzed. For both primary and secondary outcomes, the unadjusted and adjusted odds ratio for DMV showed significant increases by 5 AHI units. AHI, age, and the Mallampati classification were found to be independent predictive factors for DMV. Conclusions AHI is associated with DMV as a novel independent risk factor in Chinese patients. Along with age and Mallampati classification, AHI should be included in establishing a superior predictive strategy for DMV screening. Trial registration Chinese Clinical Trial Registry ChiCTR-DDD-17013076

scholarly journals Utilization of apnea-hypopnea index as a novel predictive factor for difficult mask ventilation in the Chinese population under general anesthesia

2020 ◽  
Author(s):  
Jia-Yi Wang ◽  
Jing-Jie Li ◽  
Peng-Cheng Zhao ◽  
Jia-Li Peng ◽  
Rong Hu ◽  
...  
Keyword(s):  
Risk Factors ◽  
General Anesthesia ◽  
Elective Surgery ◽  
Chinese Patients ◽  
Apnea Hypopnea Index ◽  
Mask Ventilation ◽  
Clinical Trial Registry ◽  
Difficult Mask Ventilation ◽  
Physical Status Classification ◽  
Obstructive Sleep

Abstract Background: Difficult Mask Ventilation (DMV) is a potentially life-threatening situation that can arise during anesthesia. Accordingly, the majority of current airway management guidelines include risk assessments for DMV. Although Obstructive Sleep Apnea (OSA) is among the most important risk factors associated with DMV, other measurements such as the Apnea-Hypopnea Index (AHI) may play an important role in determining patient risk.This study investigated the relationship between DMV and AHI, and determined preoperative risk factors for DMV in Chinese patients.Methods: A prospective cohort trial enrolled patients scheduled for elective surgery. After obtaining informed consent, patient demographic information was collected, and patients were tested with pre-operative polysomnography. Inclusion criteria: Patients >18 years of age, American Society of Anesthesiologists Physical Status Classification (ASA) I-III, and planned elective surgery with general anesthesia. Exclusion criteria: malformations of the airway, patients undergoing regional anesthesia, and patients with contraindications to mask ventilation (i.e. planned awake intubation). A logistic regression model was used to analyze the association between AHI and DMV. Results: A total of 159 patients were analyzed. For both primary and secondary outcomes, the unadjusted and adjusted odds ratio for DMV showed significant increases of 5 AHI units. AHI, age, and the Mallampati classification were found to be independent predictive factors for DMV.Conclusions AHI is associated with DMV as a novel independent risk factor in Chinese patients. Along with age and Mallampati classification, AHI should be included in establishing a superior predictive strategy DMV screening.Trial registration: Chinese Clinical Trial Registry (Registration number # ChiCTR17013076; Date of Registration on October 22nd, 2017).

scholarly journals Cleft Lip and Palate Surgery: Prevalance of Intraoperative Airway Complications in a Tertiary Center in Nepal

2020 ◽  
Vol 4 (3) ◽  
pp. 805-808
Author(s):  
Ajay Singh Thapa ◽  
Rajesh Kumar Yadav
Keyword(s):  
Difficult Intubation ◽  
Cleft Lip ◽  
Cleft Lip And Palate ◽  
Univariate Analysis ◽  
Cross Sectional Study ◽  
Mask Ventilation ◽  
Cross Sectional ◽  
Airway Complications ◽  
Difficult Mask Ventilation ◽  
Tertiary Center

Introduction: Cleft lip and palate is one of the most common congenital malformations. Different syndromes have been described in association with cleft lip and palate, some of which have considerable anesthetic implications, and many involve potential airway problems. Objective: This study aimed to find the incidence of airway complications during cleft surgeries. Methods: The descriptive cross sectional study was conducted in College of Medical Sciences and Teaching Hospital, Bharatpur, Chitwan, Nepal over a period of one year from March 2017 toFebruary2018. All the 146 patients received general anesthesia. The parameters studied were incidence of difficult mask ventilation, difficult intubation, laryngospasm, bronchospasm, aspiration of blood and secretion. Univariate analysis of demographic and occurrence of complications was done. Results: A total of 146 patients underwent cleft surgery over the study duration out of which 42(28.76%) were female and 104(71.23%) were male. Isolated cleft lip was seen in 104 (71.23%)  patients among whom 42 (28.76%) had right sided, 50 (34.24%) had left sided and 12 (8.21%) had bilateral cleft lip. Isolated cleft palate was seen in 12 (8.21%) patients. Combined cleft lip and palate was seen in 30 (20.54%) patients. Prevalence of difficult mask ventilation, difficult laryngoscopy, difficult intubation, incidence of bleeding during intubation, bronchospasm and post extubationlaryngospasmwere4 (2.73%), 11 (7.53%), 6 (4.10%), 2 (1.36%), 2(1.36%) and 4(2.73%). Conclusion: In cleft repair surgeries, difficult laryngoscopic view is the most common problem followed by difficult intubation and difficult mask ventilation. Complications like laryngospasm, bronchospasm and laryngoscopy related bleeding are not uncommon. Vigilant perioperative preparation and continuous monitoring is essential to prevent complications during cleft repair surgery in paediatric patients.

The incidence and risk factors of difficult mask ventilation

2005 ◽  
Vol 19 (1) ◽  
pp. 7-11 ◽  
Author(s):  
Tulay Sahin Yildiz ◽  
Mine Solak ◽  
Kamil Toker
Keyword(s):  
Risk Factors ◽  
Mask Ventilation ◽  
Difficult Mask Ventilation

Prediction of Difficult Mask Ventilation

2000 ◽  
Vol 92 (5) ◽  
pp. 1229-1236 ◽  
Author(s):  
Olivier Langeron ◽  
Eva Masso ◽  
Catherine Huraux ◽  
Michel Guggiari ◽  
André Bianchi ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Multivariate Analysis ◽  
Confidence Interval ◽  
Body Mass ◽  
Univariate Analysis ◽  
Positive Pressure ◽  
Mask Ventilation ◽  
Airway Patency ◽  
Difficult Mask Ventilation ◽  
History Of

Background Maintenance of airway patency and oxygenation are the main objectives of face-mask ventilation. Because the incidence of difficult mask ventilation (DMV) and the factors associated with it are not well known, we undertook this prospective study. Methods Difficult mask ventilation was defined as the inability of an unassisted anesthesiologist to maintain the measured oxygen saturation as measured by pulse oximetry > 92% or to prevent or reverse signs of inadequate ventilation during positive-pressure mask ventilation under general anesthesia. A univariate analysis was performed to identify potential factors predicting DMV, followed by a multivariate analysis, and odds ratio and 95% confidence interval were calculated. Results A total of 1,502 patients were prospectively included. DMV was reported in 75 patients (5%; 95% confidence interval, 3.9-6.1%), with one case of impossible ventilation. DMV was anticipated by the anesthesiologist in only 13 patients (17% of the DMV cases). Body mass index, age, macroglossia, beard, lack of teeth, history of snoring, increased Mallampati grade, and lower thyromental distance were identified in the univariate analysis as potential DMV risk factors. Using a multivariate analysis, five criteria were recognized as independent factors for a DMV (age older than 55 yr, body mass index > 26 kg/m2, beard, lack of teeth, history of snoring), the presence of two indicating high likelihood of DMV (sensitivity, 0.72; specificity, 0.73). Conclusion In a general adult population, DMV was reported in 5% of the patients. A simple DMV risk score was established. Being able to more accurately predict DMV may improve the safety of airway management.

scholarly journals Development of a delirium predictive model for adult trauma patients in an emergency and critical care center: a retrospective study

2021 ◽  
Vol 6 (1) ◽  
pp. e000827
Author(s):  
Ayaka Matsuoka ◽  
Toru Miike ◽  
Mariko Miyazaki ◽  
Taku Goto ◽  
Akira Sasaki ◽  
...  
Keyword(s):  
Risk Factors ◽  
Scoring System ◽  
Validation Cohort ◽  
Care Center ◽  
Univariate Analysis ◽  
Area Under The Curve ◽  
Predictive Score ◽  
Calibration Plot ◽  
Trauma Patients ◽  
Time Of Admission

BackgroundDelirium has been shown to prolong the length of intensive care unit stay, hospitalization, and duration of ventilatory control, in addition to increasing the use of sedatives and increasing the medical costs. Although there have been a number of reports referring to risk factors for the development of delirium, no model has been developed to predict delirium in trauma patients at the time of admission. This study aimed to create a scoring system that predicts delirium in trauma patients.MethodsIn this single-center, retrospective, observational study, trauma patients aged 18 years and older requiring hospitalization more than 48 hours were included and divided into the development and validation cohorts. Univariate analysis was performed in the development cohort to identify factors significantly associated with prediction of delirium. The final scoring system for predicting delirium was developed using multivariate analysis and internal validation was performed.ResultsOf the 308 patients in the development cohort, 91 developed delirium. Clinical Frailty Score, fibrin/fibrinogen degradation products, low body mass index, lactate level, and Glasgow Coma Scale score were independently associated with the development of delirium. We developed a scoring system using these factors and calculated the delirium predictive score, which had an area under the curve of 0.85. In the validation cohort, 46 of 206 patients developed delirium. The area under the curve for the validation cohort was 0.86, and the calibration plot analysis revealed the scoring system was well calibrated in the validation cohort.DiscussionThis scoring system for predicting delirium in trauma patients consists of only five risk factors. Delirium prediction at the time of admission may be useful in clinical practice.Level of evidencePrognostic and epidemiological, level III.

scholarly journals Electronic health record cue identifies epilepsy patients at risk for obstructive sleep apnea

2018 ◽  
Vol 8 (6) ◽  
pp. 468-471 ◽  
Author(s):  
Martha A. Mulvey ◽  
Aravindhan Veerapandiyan ◽  
David A. Marks ◽  
Xue Ming
Keyword(s):  
Risk Factors ◽  
At Risk ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Electronic Health Record ◽  
Seizure Control ◽  
Health Record ◽  
Obstructive Sleep ◽  
Patients At Risk ◽  
Patients With Epilepsy

BackgroundPrior studies have reported that patients with epilepsy have a higher prevalence of obstructive sleep apnea (OSA) that contributes to poor seizure control. Detection and treatment of OSA can improve seizure control in some patients with epilepsy. In this study, we sought to develop, implement, and evaluate the effectiveness of an electronic health record (EHR) alert to screen for OSA in patients with epilepsy.MethodsA 3-month retrospective chart review was conducted of all patients with epilepsy >18 years of age who were evaluated in our epilepsy clinics prior to the intervention. An assessment for obstructive sleep apnea (AOSA) consisting of 12 recognized risk factors for OSA was subsequently developed and embedded in the EHR. The AOSA was utilized for a 3-month period. Patients identified with 2 or more risk factors were referred for polysomnography. A comparison was made to determine if there was a difference in the number of patients at risk for OSA detected and referred for polysomnography with and without an EHR alert to screen for OSA.ResultsThere was a significant increase in OSA patient recognition. Prior to the EHR alert, 25/346 (7.23%) patients with epilepsy were referred for a polysomnography. Postintervention, 405/414 patients were screened using an EHR alert for AOSA and 134/405 (33.1%) were referred for polysomnography (p < 0.001).ConclusionAn intervention with AOSA cued in the EHR demonstrated markedly improved identification of epilepsy patients at risk for OSA and referral for polysomnography.

Predicting Difficult Laryngoscopy in Morbidly Obese Patients by Ultrasound of Distance from Skin to Epiglottis: A Prospective Observational Study

2021 ◽  
Author(s):  
Sumidtra Prathep ◽  
Wilasinee Jitpakdee ◽  
Wisara Woraathasin ◽  
Maliwan Oofuvong
Keyword(s):  
Observational Study ◽  
Prospective Observational Study ◽  
Elective Surgery ◽  
Univariate Analysis ◽  
Difficult Laryngoscopy ◽  
Predictive Score ◽  
P Value ◽  
Morbidly Obese ◽  
Obese Patients ◽  
Measured Distance

Abstract BackgroundIn morbidly obese patients, airway management is challenging since the incidence of difficult intubation is 3 times that in normal patient. Standard preoperative airway evaluation may help to indicate for probability of difficult laryngoscopy. Recent studies have used ultrasonography-measured distance from skin to epiglottis and pretracheal soft tissue at the level of vocal cords, and cut-points of 27.5 mm and 28 mm respectively, to predict difficult laryngoscopy. The purpose of this study is to use ultrasonography-measured distance from skin to epiglottis for predicting difficult laryngoscopy in morbidly obese Thai patients.MethodsThis prospective observational study was approved by the Ethics Committee of the Faculty of Medicine, Prince of Songkla University. Data were collected from January 2018 to August 2020. Eighty-eight morbidly obese patients (BMI ≥ 35 kg/m2) requiring general anesthesia with endotracheal intubation for elective surgery in Songklanagarind Hospital were enrolled. Preoperatively, anesthesiologists or nurse anesthetists who were not involved with intubating the patients evaluated and recorded measurements (body mass index, neck circumference, inter incisor gap, sternomental distance, thyromental distance, modified Mallampati scoring, upper lip bite test, and distance from skin to epiglottis by ultrasound. The laryngoscopic view was graded on the Cormack and Lehane scale. ResultsMean BMI of the eighty-eight patients was 45.3 ± 7.6 kg/m2. The incidence of difficult laryngoscopy was 14.8%. Univariate analysis for difficult laryngoscopy indicated differences in thyromental distance, sternomental distance and the distance from skin to epiglottis by ultrasonography. The median (IQR) of thyromental distance in difficult laryngoscopy was 6.5 (6.3, 8.0) cm compared with 7.5(7.0, 8.0) cm in easy laryngoscopy (p-value 0.03). The median (IQR) of sternomental distance in difficult laryngoscopy was 16.8 (15.2, 18.0) cm compared with 16.0 (14.5, 16.0) cm in easy laryngoscopy (p-value 0.05). The mean distance from skin to epiglottis was 12.2 ± 3.3 mm Mean of distance from skin to epiglottis in difficult laryngoscopy was 12.5 ± 3.3 mm compared with 10.6 ± 2.9 mm in easy laryngoscopy (p-value 0.05). Multivariate logistic regression indicated the following factors associated with difficult laryngoscopy: age more than 43 years (A), thyromental distance more than 68 mm(B) and the distance from skin to epiglottis more than 13 mm(C). The scores to predict difficult laryngoscopy was calculated as 8A+7B+6C. One point is given for A if age was more than 43 years old, 1 point is given for B if thyromental distance was less than 6.8 cm and 1 point is given for C if the distance from skin to epiglottis by ultrasonography was more than 13.0 cm. The maximum predicting score is 21, which indicates a probability of difficult laryngoscopy among our patients of 36.36%, odds 0.57, likelihood ratio 3.29 and area under the ROC curve of 0.78.ConclusionsAge, thyromental distance and ultrasonography for the distance from skin and epiglottis can predict difficult laryngoscopy among obese Thai patients. The predictive score indicates the probability of difficult laryngoscopy.

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