Efficacy of Palmitoylethanolamide and Luteolin Association on Post-Covid Olfactory Dysfunction: A Systematic Review and Meta-Analysis of Clinical Studies

Abstract

Post-Covid Olfactory Dysfunction (PCOD) is characterized by olfactory abnormalities, hyposmia, and anosmia, which are among the most often enduring symptoms in individuals who have recovered from SARS-CoV-2 infection. This disorder has been reported to persist in subsets of patients well after 12 months following infection, significantly affecting their quality of life. Despite the high prevalence of PCOD among patients who suffered from SARS-CoV-2 infection, specific therapeutic strategies are still limited. Among these, emerging evidence seems to indicate the administration of CoUltraPEALut, a combination of micronized Palmitoylethanolamide (PEA), an endogenous fatty acid amide, and Luteolin, a natural antioxidant flavonoid, as a viable therapy, especially when given as an adjuvant to olfactory training. Based on the above, a systematic review and a meta-analysis of the literature were conducted, with the aim of evaluating the efficacy of CoUltraPEALut as an addition to olfactory training (OT), in treating PCOD symptoms. Pubmed (MEDLINE), Embase (OVID), and Web of Science scientific databases were screened from the inception until 31 May 2023, and a total of 407 articles were recovered; only five of these studies (441 total patients between treated and control groups) were included in the systematic review. CoUltraPEALut demonstrated significant efficacy in the overall recovery of the olfactory function, compared to the conventional therapy, suggesting that it could represent a possible future adjuvant treatment for PCOD.

Keywords: COVID-19; CoUltraPEALut; Luteolin; Post-Covid Olfactory Dysfunction (PCOD); SARS-CoV-2; palmitoylethanolamide (PEA); respiratory disorders.

Figure 1

PRISMA flow diagram. The picture outlines each phase of the search strategy and screening procedure, which was carried out in accordance with PRISMA-P guidelines.

Figure 2

Forest plot of the studies analyzed in the quantitative synthesis [20,22,24]. By subtracting the value at endpoint with the value at baseline and calculating the combined SD, the forest plot shows how the TDI score improved in treated patients and control individuals. The impact estimate (ORs) is displayed as squares, with the size of each green square reflecting the weight assigned to each research in the meta-analysis. The 95% confidence intervals (CIs) for each effect estimate are shown as horizontal lines. The black diamond’s width, which indicates the total 95% CI, represents the overall effect of intervention. A measurement of heterogeneity is the I² statistic. Effect size OR: 3.07 [2.22, 3.92]; p < 0.00001.

Figure 3

Forest plot of the studies analyzed in the quantitative synthesis [20,22,24]. By subtracting the value at endpoint with the value at baseline and calculating the combined SD, the forest plot shows how the TDI score improved in treated patients and control individuals. The impact estimate (ORs) is displayed as squares, with the size of each green square reflecting the weight assigned to each research in the meta-analysis. The 95% confidence intervals (CIs) for each effect estimate are shown as horizontal lines. The black diamond’s width, which indicates the total 95% CI, represents the overall effect of intervention. A measurement of heterogeneity is the I² statistic. Effect size OR: 4.28 [−0.04, 8.60]; p = 0.05.