2020International Archives of OtorhinolaryngologyOpen access

Anosmia/Hyposmia is a Good Predictor of Coronavirus Disease 2019 (COVID-19) Infection: A Meta-Analysis

Timotius Ivan Hariyanto, Niken Ageng Rizki, Andree Kurniawan

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Abstract

Abstract Introduction The number of positive cases and deaths from the coronavirus disease 2019 (COVID-19) is still increasing. The early detection of the disease is very important. Olfactory dysfunction has been reported as the main symptom in part of the patients. Objective To analyze the potential usefulness of anosmia or hyposmia in the detection of the COVID-19 infection. Data Synthesis We systematically searched the PubMed Central database using specific keywords related to our aims until July 31st, 2020. All articles published on COVID-19 and anosmia or hyposmia were retrieved. A statistical analysis was performed using the Review Manager (RevMan, Cochrane, London, UK) software, version 5.4. A total of 10 studies involving 21,638 patients were included in the present analysis. The meta-analysis showed that anosmia or hyposmia is significantly associated with positive COVID-19 infections (risk ratio [RR]: 4.56; 95% confidence interval [95%CI]: 3.32–6.24; p < 0.00001; I2 = 78%, random-effects modeling). Conclusion The presence of anosmia or hyposmia is a good predictor of positive COVID-19 infections. Patients with onset of anosmia or hyposmia should take the test or undergo screening for the possibility of COVID-19 infection.

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Abstract Introduction The number of positive cases and deaths from the coronavirus disease 2019 (COVID-19) is still increasing. The early detection of the disease is very important. Olfactory dysfunction has been reported as the main symptom in part of the patients. Objective To analyze the potential usefulness of anosmia or hyposmia in the detection of the COVID-19 infection. Data Synthesis We systematically searched the PubMed Central database using specific keywords related to our aims until July 31st, 2020. All articles published on COVID-19 and anosmia or hyposmia were retrieved. A statistical analysis was performed using the Review Manager (RevMan, Cochrane, London, UK) software, version 5.4. A total of 10 studies involving 21,638 patients were included in the present analysis. The meta-analysis showed that anosmia or hyposmia is significantly associated with positive COVID-19 infections (risk ratio [RR]: 4.56; 95% confidence interval [95%CI]: 3.32–6.24; p < 0.00001; I2 = 78%, random-effects modeling). Conclusion The presence of anosmia or hyposmia is a good predictor of positive COVID-19 infections. Patients with onset of anosmia or hyposmia should take the test or undergo screening for the possibility of COVID-19 infection.

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Available abstract

Abstract Introduction The number of positive cases and deaths from the coronavirus disease 2019 (COVID-19) is still increasing. The early detection of the disease is very important. Olfactory dysfunction has been reported as the main symptom in part of the patients. Objective To analyze the potential usefulness of anosmia or hyposmia in the detection of the COVID-19 infection. Data Synthesis We systematically searched the PubMed Central database using specific keywords related to our aims until July 31st, 2020. All articles published on COVID-19 and anosmia or hyposmia were retrieved. A statistical analysis was performed using the Review Manager (RevMan, Cochrane, London, UK) software, version 5.4. A total of 10 studies involving 21,638 patients were included in the present analysis. The meta-analysis showed that anosmia or hyposmia is significantly associated with positive COVID-19 infections (risk ratio [RR]: 4.56; 95% confidence interval [95%CI]: 3.32–6.24; p < 0.00001; I2 = 78%, random-effects modeling). Conclusion The presence of anosmia or hyposmia is a good predictor of positive COVID-19 infections. Patients with onset of anosmia or hyposmia should take the test or undergo screening for the possibility of COVID-19 infection.

Key concepts: Hyposmia, Anosmia, Medicine, Coronavirus disease 2019 (COVID-19), Confidence interval, Disease, Internal medicine, Meta-analysis

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