谷歌浏览器插件
订阅小程序
在清言上使用

Clinical characteristics and oral manifestations of COVID-19: a cross-sectional study from Peshawar, Pakistan

KHYBER MEDICAL UNIVERSITY JOURNAL-KMUJ(2023)

引用 0|浏览3
暂无评分
摘要
OBJECTIVES: To determine the prevalence of oral manifestations among PCR-confirmed COVID-19-positive patients and their potential correlations with age, gender, and systemic manifestations. METHODS: This cross-sectional study was conducted at Khyber Medical University among 117 randomly selected PCR-confirmed COVID-19-positive patients from October 1, 2020, to January 30, 2021. All the patient records were taken from the Public Health Reference Lab, Peshawar, Pakistan. Telephonic interviews were conducted for data collection using a structured questionnaire. SPSS version 24.0 was used for data analysis. Regression analysis was done to determine the association between dependent variables (oral manifestations) and independent data like age, gender, and systemic features. RESULTS: Among 117 participants, 56% experienced oral manifestations associated with COVID-19. Taste alterations were experienced by 49.6% (n = 58), xerostomia 34.2% (n = 40), inflammation of the oral cavity 14.5% (n = 17), oral ulcers 10.3% (n = 12), angular cheilitis 6% (n = 7), white lesions 0.9% (n = 1), and bleeding gums 0.9% (n = 1). The average duration for symptoms to last was 10 days. General clinical manifestation of COVID-19 include fever, cough, sore throat, nasal congestion, body aches, diarrhea, difficulty breathing, etc. Oral manifestations had a significant association with gender (p<0.02), loss of smell (OR 0.034, 95%CI 0.008-0.153, p <0.001) and use of medication (OR 0.051, 95% CI 0.011-0.231, p<0.001). CONCLUSIONS: Oral manifestations were observed in 56% of PCR-confirmed COVID-19-positive patients, with taste alterations being the most common at 49.6%. Significant associations were identified with gender, loss of smell and medication use.
更多
查看译文
关键词
COVID-19,Oral Manifestations,Dysgeusia,Taste Disorders,Xerostomia,Oral Ulcer,Anosmia,Fever,Fatigue,Cough
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要