Gastric perforation after accidental esophageal intubation in a patient with deep neck infection.

Acta Anaesthesiol Taiwan

Department of Anesthesiology, Kaohsiung Medical University Hospital, Kaohsiung City, Taiwan; Department of Anesthesiology, Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung City, Taiwan. Electronic address:

Published: September 2014

Deep neck infection with airway obstruction may complicate endotracheal intubation with limited neck motion, pharyngeal swelling, and prominent secretion. Unrecognized esophageal intubation (EI) may unduly overinflate the stomach to inhibit effective ventilation, increase the incidence of hypoxia, and produce a ruptured visceral organ. We report an 81-year-old female patient with deep neck infection and impending respiratory failure who suffered gastric perforation after accidental EI in the intensive care unit. After failed attempts of intubation, EI was recognized rapidly as the culprit, although roughly audible bilateral breathing sounds were present but not gastric bubble sounds. A catastrophic complication of gastric rupture occurred due to ambu-bagging and mechanical ventilation. Surgical intervention was performed immediately. Possible mechanisms are discussed.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.aat.2014.06.001DOI Listing

Publication Analysis

Top Keywords

deep neck
12
neck infection
12
gastric perforation
8
perforation accidental
8
esophageal intubation
8
patient deep
8
gastric
4
accidental esophageal
4
intubation
4
intubation patient
4

Similar Publications

Multi-Energy Evaluation of Image Quality in Spectral CT Pulmonary Angiography Using Different Strength Deep Learning Spectral Reconstructions.

Acad Radiol

December 2024

Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, Gainesville, FL (M.H-S., H.S.S., A.G.R., S.E.M., J.C.P., E.Y.A., B.H., R.F.); Department of Radiology, University of Florida College of Medicine, Gainesville, FL (M.H-S., H.S.S., A.G.R., J.C.P., E.Y.A., B.H., R.F.); Division of Medical Physics, University of Florida College of Medicine, Gainesville, FL (R.F.); Department of Neurology, Division of Movement Disorders, University of Florida College of Medicine, Gainesville, FL (R.F.); Department of Otolaryngology - Head and Neck Surgery, McGill University, Montreal, Quebec, Canada (R.F.); Department of Radiology, AdventHealth Medical Group, Maitland, FL (R.F.). Electronic address:

Rationale And Objectives: To evaluate and compare image quality of different energy levels of virtual monochromatic images (VMIs) using standard versus strong deep learning spectral reconstruction (DLSR) on dual-energy CT pulmonary angiogram (DECT-PA).

Materials And Methods: A retrospective study was performed on 70 patients who underwent DECT-PA (15 PE present; 55 PE absent) scans. VMIs were reconstructed at different energy levels ranging from 35 to 200 keV using standard and strong levels with deep learning spectral reconstruction.

View Article and Find Full Text PDF

Introduction: Deep neck infections are lethal diseases; however, factors related to their prevention remain unclear. The national emergency declaration in April 2020, in response to COVID-19, spurred widespread adoption of nonpharmaceutical interventions (NPIs) such as hand washing, mask wearing, and social distancing.

Methods: This retrospective cohort study examines the impact of these interventions on the incidence of deep neck infections in Japan through interrupted time series analysis using National Database of Health Insurance Claims and Specific Health Checkups of Japan Open Data.

View Article and Find Full Text PDF

The quantity of cable conductors is a crucial parameter in cable manufacturing, and accurately detecting the number of conductors can effectively promote the digital transformation of the cable manufacturing industry. Challenges such as high density, adhesion, and knife mark interference in cable conductor images make intelligent detection of conductor quantity particularly difficult. To address these challenges, this study proposes the YOLO-cable model, which is an improvement made upon the YOLOv10 model.

View Article and Find Full Text PDF

Radiomics is a method that extracts many features from medical images using various algorithms. Medical nomograms are graphical representations of statistical predictive models that produce a likelihood of a clinical event for a specific individual based on biological and clinical data. The radiomic nomogram was first introduced in 2016 to study the integration of specific radiomic characteristics with clinically significant risk factors for patients with colorectal cancer lymph node metastases.

View Article and Find Full Text PDF

Deep Learning Model for the Differential Diagnosis of Nasal Polyps and Inverted Papilloma by CT Images: A Multicenter Study.

Acad Radiol

December 2024

Department of Otorhinolaryngology, Head and Neck Surgery, Yantai Yuhuangding Hospital, Qingdao University, Yantai, China (Y.W., P.Y., J.W., Z.Z., G.W., Y.Z., Y.Y., Y.M., X.S.); Shandong Provincial Clinical Research Center for Otorhinolaryngologic Diseases, Yantai Yuhuangding Hospital, Yantai, China (Y.W., P.Y., J.W., Z.Z., G.W., Y.Z., Y.Y., Y.M., X.S.); Yantai Key Laboratory of Otorhinolaryngologic Diseases, Yantai Yuhuangding Hospital, Yantai, China (Y.W., P.Y., J.W., Y.Z., Y.Y., Y.M., X.S.). Electronic address:

Rationale And Objectives: Nasal polyps (NP) and inverted papilloma (IP) are benign tumors within the nasal cavity, each necessitating distinct treatment approaches. Herein, we investigate the utility of a deep learning (DL) model for distinguishing between NP and IP.

Materials And Methods: A total of 1791 patients with nasal benign tumors from two hospitals were retrospectively enrolled.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!