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Predictive Performance Neutrophil-to-Lymphocyte Ratio of Acute Tonsillitis with Deep Neck Space Infection in Adult Patients

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EMERGENCY MEDICINE INTERNATIONAL
卷 2023, 期 -, 页码 -

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HINDAWI LTD
DOI: 10.1155/2023/8456427

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The aim of this study was to examine the neutrophil-to-lymphocyte ratio (NLR) in patients with a deep neck infection (DNI) and identify helpful indicators for initial differential diagnosis. The study found significant differences in NLR between patients with acute tonsillitis with and without DNI. Age, gender, body temperature, C-reactive protein, and NLR were identified as significant independent risk factors for DNI in patients with tonsillitis. NLR, especially in patients with normal body temperature, can be used to predict the prognosis of tonsillitis patients.
The aim of this study was to examine the neutrophil-to-lymphocyte ratio (NLR) in patients diagnosed with a deep neck infection (DNI) to identify helpful indicators for the initial differential diagnosis. This study was conducted as a single-center, retrospective cohort study that utilized data from the electronic medical records of patients who visited the emergency department in a tertiary university hospital between February 2018 and April 2022. The study enrolled patients aged >= 18 years who were diagnosed with tonsillitis with or without DNI during the study period. The NLR of patients without DNI was 6.1 +/- 5.03, and the NLR of patients with acute tonsillitis with DNI was 8.0 +/- 5.67, showing significant differences. The rate of admission in the general wards (GWs) and ICUs was significantly higher in patients with DNI, and the length of hospital stay was also significantly longer in patients with DNI. Older age, male, lower body temperature, C-reactive protein, and NLR were significant independent risk factors for DNI in patients with tonsillitis. The cutoff value for predicting DNI in patients with body temperature <37.5 was 3.09. The NLR of patients with tonsillitis, especially those with normal body temperature, can be used to predict their prognosis.

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