Deep neck infection: analysis of 80 cases.

Braz J Otorhinolaryngol

Head & Neck Surgery Discipline, São Paulo Santa Casa, Brazil.

Published: August 2008

Unlabelled: Deep neck infections are serious diseases that involve several spaces in the neck. The most dreadful complication is descending necrotizing fasciitis, which needs early diagnosis and aggressive treatment.

Aim: To analyze 80 treated cases of deep neck infection and propose a schematic guideline for managing this disease.

Method: The authors present a retrospective analysis of 80 treated cases of deep neck infection, from June 1997 to June 2003.

Results: Odontogenic and tonsilar causes were the more frequent ones. Submandibular and parapharyngeal spaces were the most frequent location of deep neck infection. Staphylococcus aureus and Streptococcus sp were the microorganisms more commonly isolated.

Conclusions: Airway control should be priority in managing deep neck infections and if the patient has to be submitted to surgery special care should be taken at the moment of intubation - when curare must never be used. CT scan is the gold-standard imaging evaluation for the diagnosis of deep neck infection. Morbi-mortality is high when associated with septic shock and mediastinitis. Our mortality rate was 11.2% and only one, in five patients with mediastinitis, survived.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9442126PMC
http://dx.doi.org/10.1016/s1808-8694(15)31097-1DOI Listing

Publication Analysis

Top Keywords

deep neck
28
neck infection
20
neck infections
8
treated cases
8
cases deep
8
deep
7
neck
7
infection
5
infection analysis
4
analysis cases
4

Similar Publications

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

A non-local dual-stream fusion network for laryngoscope recognition.

Am J Otolaryngol

December 2024

Department of Otorhinolaryngology Head and Neck Surgery, Tianjin First Central Hospital, Tianjin 300192, China; Institute of Otolaryngology of Tianjin, Tianjin, China; Key Laboratory of Auditory Speech and Balance Medicine, Tianjin, China; Key Clinical Discipline of Tianjin (Otolaryngology), Tianjin, China; Otolaryngology Clinical Quality Control Centre, Tianjin, China.

Purpose: To use deep learning technology to design and implement a model that can automatically classify laryngoscope images and assist doctors in diagnosing laryngeal diseases.

Materials And Methods: The experiment was based on 3057 images (normal, glottic cancer, granuloma, Reinke's Edema, vocal cord cyst, leukoplakia, nodules and polyps) from the dataset Laryngoscope8. A classification model based on deep neural networks was developed and tested.

View Article and Find Full Text PDF

Objective: Pharmacoresistant tremors, often seen in Parkinson disease and essential tremor, significantly impair patient quality of life. Although deep brain stimulation has been effective, its invasive nature limits its applicability. MR-guided focused ultrasound (MRgFUS) thalamotomy offers a noninvasive alternative, but its cognitive impacts are not fully understood.

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!