Data collection:
Patients were identified from the regional multidisciplinary team (MDT) database, which includes all patients recovered from COVID-19 infection.
Recovery of COVID-19 infection confirmed by 2 consecutive negative polymerase chain reaction (PCR) swabs. All patients were submitted for detailed endoscopic nasal examination.
The study depended on baseline visits at the outpatient clinic of ENT and follow up for 4 weeks. Patients age, sex, olfactory dysfunction onset and duration, severity of COVID infection, isolation place, hospitalization, medication used, medical history, date of confirmed positive and negative COVID swabs and potential risk factors as obesity, hypertension, diabetes mellitus, tobacco smoking and asthma were taken in consideration.
Patients allocated into four groups each group 30 patients:
All enrolled participants received medications for 4 weeks in addition to olfactory training in the form of sniffing of 4 different scents typically phenylethyl alcohol (rose), citronella (lemon), eugenol(clove) and eucalyptol (eucalyptus), each odorant for 15 seconds, with10 seconds rest between odorant twice daily for one month.
Olfactory function evaluation (normal smell, anosmia, hyposmia) based on patient subjective senses, visual analog scale (VAS)-smell score. This was used with familiar nonirritant substances with a distinctive odor like mint, coffee, and garlic. Score from 0 to 10, 0 means do not recognize it at all (total loss of smell) and 10 means fully recognize it (complete normal smell). This test was done before starting medications and every week for one month for all participants.
Smell loss duration was considered from the onset of olfactory dysfunction to complete recovery of the smell sensation.
Statistical analysis:
The data were recorded on an “Investigation report form”. These data were tabulated, coded then analyzed using the computer program SPSS (Statistical package for social science) version 26. Descriptive statistics were calculated for the data in the form of mean and standard deviation (±SD), Median and interquartile range (IQR) and Number and percent. In the statistical comparison between the different groups, the significance of difference was tested using student’s t -test to compare between mean of two groups of numerical data, for continuous non- parametric data, Mann-Whitney U- test was used for inter-group analysis, Anova to compare between mean of more than two groups of numerical data, for continuous non- parametric data, Kruskal Wallis test was used for inter-group analysis Inter-group comparison of categorical data was performed by using chi square test (X2- value). P value <0.05 was considered statistically significant.
Results:
Patient characteristics:
A total of 120 patients met the iclusion criteria of the study allocated into four groups of 30 patients. Among the total included and analyzed 120 adult patients, 52 patients were male (43.3%) and 68 were female (56.6%). Patient ages ranged from 18 to 62 years; the median age was 38.5 years (IQR 24.75). 38 patients (36.3%) were managed in hospital while 82 patients (68.3%) were home isolated. severity: to COVID-19 illness severity; 87 patients (72.5%) were mild, 25 patients (20.83%) were moderate, and 8 patients (6.67%) suffered severe illness. The study included 23 diabetic patients (19.1%) and 41 patients (34.2%) were hypertensive. 20 patients (16.7%) were suffering from obesity and 18 patients (15%) were asthmatic and 37 patients (30.8%) were smokers.
Regarding age and sex, all groups showed non-significant differences. There were no statistically significant differences between all groups as regards prognostic factors such as place of management, severity of COVID-19 illness, obesity as shown in (15) .
We found a high signigant association between other prognostic factors as; diabetes (P-Value=<0.001***) , hypertension(P-Value=<0.001***) , smoking (P-Value=<0.001***) , and asthma ( P-Value=<0.001***) as shown in (15) .
Also, there were no statistically significant differences between the studied groups as regards the duration of COVID-19 illness (P-Value =0.5) and the duration of anosmia/hyposmia before recovery/discharge (P-Value =0.2) . There is signigant difference between the studied groups as regards Duration of anosmia/hyposmia till complete recovery (P-Value=<0.02*) . [Table 2]
Duration of anosmia/hyposmia and smell scores of the studied groups:
As regards duration of anosmia/hyposmia till complete recovery, the comparison between studied groups showed statistically significant difference as the average time (Mean ± SD) for complete recovery of smell in group A was 28.97± 4.29 days and was 25.70± 9.20 days among group B and 24.80±6.67among group C and was 23.50± 7.13 days among group D (P value <0.02*) . [Table 2]
Recovery of anosmia/hyposmia:
Regarding smell scores at recovery/discharge at the initial assessment, there was no statistically significant difference between the studied groups, (P value = 0.2) . On comparing smell scores after1 week, 2 weeks and 3 weeks of treatment, there were high statistically significant differences between the studied groups (P-values <0.001*) . But there is no significant difference after the fourth week of treatment (p value =0.6) as shown in [Table 3 ].
In group A, 17 out of 30 patients (56.6%) had their sense of smell completely recovered by the end of the fourth week, compared to 18 out of 30 patients (60%) in group B and 21 out of 30 patients (70%) in groups C and D.
Table 2 : Comparison between the studied groups.