To the Editor,
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus primary affects the respiratory system; however, a multiorganic affection is evident. Neurological symptoms are frequent at the acute- and post-acute phases after infection [1]. Headache is a neurological symptom experienced as a COVID-19-onset symptom associated with a more benign course of the disease [2]; however, it has been also associated with a higher prevalence of post-COVID headache [3].
During the acute COVID-19 phase, headache often co-exists with other neurological symptoms, e.g., anosmia or ageusia [4]. The presence of anosmia as an onset symptom is also associated with lower mortality rate and a less severe disease, although it seems that patients with anosmia and ageusia represent a different group than those with headache [5]. In this letter, we applied a network analysis to determine the relevance of COVID-19-onset symptoms, including headache, as well as pre-existing medical co-morbidities in a sample of previously hospitalised COVID-19 patients.
The LONG-COVID-EXP-CM is a multicentre cohort study including individuals with a diagnosis of SARS-CoV-2 infection by RT-PCR technique and/or radiological findings hospitalised during the first wave of the pandemic in five hospitals of Madrid (Spain). Among all patients hospitalised during the first wave, a sample of 400 from each hospital was randomly selected. The Ethics Committee of all the hospitals approved the study (HCSC20/495E, HSO25112020, HUFA20/126, HUIL/092-20, HUF/EC1517). Verbal informed consent was obtained from participants for the use of their data in this analysis. Demographic data, pre-existing medical comorbidities, COVID-19 symptoms at hospital admission, days at hospital, and intensive care unit (ICU) admission were collected from hospital records.
The network included 28 nodes linked by edges weighted by partial correlation coefficients. The dataset as well as the related two vectors specifying the type (“g” for Gaussian, “p” for Poisson, “c” for categorical) and the number of levels (or categories) for each variable is provided. The mgm was estimated for order = 2 to only take pairwise interactions into account, using least absolute shrinkage and selection operator (LASSO, ℓ1-regularisation) that seeks to maximise specificity (to include as few false positives as possible) with rule = “AND” (which specifies whether the two estimates for an edge are combined with an “AND” or an “OR” rule). Since not all nodes in a network are equally important, centrality was assessed by calculating strength centrality (defined as the sum of weights of edges), betweenness centrality (defined as the total number of shortest paths that pass through the target node, moderated by the total number of shortest paths existing between any couple of nodes in the graph) and closeness centrality (defined as the inverse sum of the distances of shortest of the target node from all other nodes in the network).
Two thousand (n = 2000) patients were randomly selected and invited to participate. A total of 1969 (age:61 ± 16 years, 46.4% women) were included. The most common symptoms at hospital admission were fever (74.6%), dyspnoea (31.5%), myalgia (30.7%) and cough (27.9%). The network identified one group of variables grouping all COVID-19-onset symptoms at hospitalisation, and a second one grouping all pre-existing medical co-morbidities (Fig. 1). Multiple positive correlations between the variables in each group were found. The highest correlation (ρρ:5.87) in the medical co-morbidity group was between asthma (node 9) and rheumatological diseases (node 13). Within the COVID-19-onset symptoms group, headache (node 20) had several high correlations with fever (node 16, ρρ:5.981), dyspnoea (node 17, ρρ:5.617), anosmia (node 22, ρρ:5.2276 and ageusia (node 23, ρρ:4.660). No correlations between both groups of variables were seen. In the group of COVID-19-onset symptoms, headache was the node showing the highest strength centrality, highest betweenness centrality and highest closeness centrality (node 20, Fig. 2).
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Source: Fernández-de-las-Peñas, C., Varol, U., Gómez-Mayordomo, V. et al. The relevance of headache as an onset symptom in COVID-19: a network analysis of data from the LONG-COVID-EXP-CM multicentre study. Acta Neurol Belg (2022). https://doi.org/10.1007/s13760-022-01998-x https://link.springer.com/article/10.1007/s13760-022-01998-x (Full text)