Routine computerised tomography in patients with acute supraglottitis for the diagnosis of epiglottic abscess: is it necessary? – a prospective, multicentre study

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Abstract

Objectives

To evaluate the predictive factor of epiglottic abscess and to investigate whether routine computerised tomography (CT) in patients with acute supraglottitis are necessary.

Design

A prospective and multicentre study.

Settings

Tertiary care referral medical centre.

Participants

A total of 202 patients with suspected acute supraglottitis were enrolled. All patients underwent CT to confirm the presence of abscess.

Main outcome measures

The patients' characteristics, symptoms at presentation, laryngoscopic findings of epiglottic swelling and arytenoid swelling by scope classification and initial laboratory finding were analysed.

Results

Of 202 patients, 158 (78%) had acute supraglottitis and 44 (22%) had epiglottic abscess. There was no significant difference in age between the acute supraglottitis group and the epiglottic abscess group. Men were significantly more frequent in the epiglottic abscess group than females (P = 0.042). When comparing the symptom at presentation, the patients with epiglottic abscess complained of voice change more frequently (P = 0.003). Moderate or severe epiglottic swelling in scope classification was significantly associated with epiglottic abscess (P < 0.001). In logistic regression analysis, voice change [OR = 2.64, 95% CI = 1.29–5.40, P = 0.008] and moderate or severe epiglottic swelling in laryngoscopic findings [OR = 3.94, 95% CI = 1.63–9.53, P = 0.002] were independent predictive factors for epiglottic abscess. The positive predictive values of voice change and moderate or severe epiglottic swelling were 33% and 30%, respectively. The negative predictive values of voice change and moderate or severe epiglottic swelling were 15% and 9%, respectively.

Conclusions

Routine CT might be suggested for diagnosis of epiglottic abscess in the patients with acute supraglottitis, because of the poor predictive values of symptoms and signs.

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