Background and purpose: Headache is an important manifestation during SARS-CoV-2 infection. In this study, the aim was to identify factors associated with headache in COVID-19 and headache characteristics.Methods: This case-control study includes COVID-19 hospitalized patients with pneumonia during March 2020. Controls comprise COVID-19 patients without headache and the cases are COVID-19 patients with headache. Demographic, clinical and laboratory data were obtained from the medical records. Headache characteristics were evaluated by semi-structured telephonic interview after discharge.Results: Of a total of 379 COVID-19 patients, 48 (13%) developed headache. Amongst these, 30 (62%) were men and the median age was 57.9 (47-73) years. Headache was associated with younger age, fewer comorbidities and reduced mortality, as well as with low levels of C-reactive protein, mild acute respiratory distress syndrome and oropharyngeal symptoms. A logistic multiple regression model revealed that headache was directly associated with D-dimer and creatinine levels, the use of high flow nasal cannula and arthromyalgia, whilst urea levels, beta-lactamic treatment and hypertension were negatively associated with headache. COVID-19-associated headache characteristics were available for 23/48 (48%) patients. Headache was the onset symptom in 8/20 (40%) patients, of mild or moderate intensity in 17/20 (85%) patients, with oppressive characteristics in 17/18 (94%) and of holocranial 8/19 (42%) or temporal 7/19 (37%) localization. Conclusions:Our results show that headache is associated with a more benign SARS-CoV-2 infection. COVID-19-associated headache appears as an early symptom and as a novel headache with characteristics of headache attributed to systemic viral infection.Further research addressing the underlying mechanisms to confirm these findings is warranted.
Perampanel, a non‐competitive antagonist of the α‐amino‐3‐hydroxy‐5‐methyl‐4‐isoxazole‐propionic acid receptors, is the most recent antiepileptic drug available in Spain, marketed in January 2014. It was initially approved by the European Medicines Agency as adjunctive treatment for partial‐onset seizures in patients 12 years and older, but recently also for primary generalized tonic‐clonic seizures. Although clinical trials provide essential information about the drug, they do not reflect daily clinical practice. This retrospective study shows the initial experience with perampanel in 11 Spanish hospitals during its first year post‐commercialisation. All patients who started perampanel treatment were included, but efficacy and tolerability were only assessed in those patients with a minimum follow‐up period of six months. In total, 256 patients were treated with perampanel before September 2014, and 253 had an observational period of one year. After six months, 216/256 patients (84%) continued on perampanel and 180/253 (71.1%) completed one year of treatment. The mean number of previous antiepileptic drugs used was 6.83 and the median number of concomitant antiepileptic drugs was 2. The mean perampanel dose was 7.06 mg and 8.26 mg at six and 12 months, respectively. The responder rate was 39.5% and 35.9% at both follow‐up points, respectively. Adverse events were experienced by 91/253 (35.5%) and resulted in withdrawal in 37 (14.6%). The most common adverse events were somnolence, dizziness, and irritability. We found no significant differences between concomitant use of enzyme‐inducing and non‐inducing antiepileptic drugs, regarding efficacy, adverse effects, or withdrawals. Irritability was not influenced by concomitant use of levetiracetam, relative to other drugs, but was more frequently observed in patients with a history of psychiatric problems or learning disabilities.
Migraine affects the daily life of millions of people around the world. The most well-known disabling symptom associated with this illness is the intense headache. Nowadays, there are treatments that can diminish the level of pain. OnabotulinumtoxinA (BoNT-A) has become a very popular medication for treating migraine headaches in those cases in which other medication is not working, typically in chronic migraines. Currently, the positive response to Botox treatment is not clearly understood, yet understanding the mechanisms that determine the effectiveness of the treatment could help with the development of more effective treatments. To solve this problem, this paper sets up a realistic scenario of electronic medical records of migraineurs under BoNT-A treatment where some clinical features from real patients are labeled by doctors. Medical registers have been preprocessed. A label encoding method based on simulated annealing has been proposed. Two methodologies for predicting the results of the first and the second infiltration of the BoNT-A based treatment are contempled. Firstly, a strategy based on the medical HIT6 metric is described, which achieves an accuracy over 91%. Secondly, when this value is not available, several classifiers and clustering methods have been performed in order to predict the reduction and adverse effects, obtaining an accuracy of 85%. Some clinical features as Greater occipital nerves (GON), chronic migraine time evolution and others have been detected as relevant features when examining the prediction models. The GON and the retroocular component have also been described as important features according to doctors.
Deciding on the continuous treatment of chronic diseases is vital in terms of economy, quality of life, and time. We present a holistic data mining approach that addresses the prediction of the therapeutic response in a panoramic and feedback way while unveiling relevant medical factors. Panoramic prediction makes it possible to decide whether the treatment will be beneficial without using previous knowledge and without involving unnecessary treatments. Feedback prediction can be more accurate prediction since it considers the results of previous stages of the treatment. A novel label encoding called simulated annealing and rounding (SAR) encoding is also proposed to help improve the accuracy of prediction in both approaches. To unveil the medical factors that make the treatment effective for patients, various techniques are applied to the prediction models found through the proposed approaches. Finally, this methodology is applied in the realistic scenario of analyzing electronic medical records of migraineurs under BoNT-A treatment. The results show a significant improvement in accuracy due to the use of SAR encoding, from close to 60% (baseline) to 75% with panoramic prediction, and up to around 90% when using feedback prediction. Furthermore, the following factors have been found to be relevant when predicting the migraine treatment responses: migraine time evolution, unilateral pain, analgesic abuse, headache days, and the retroocular component. According to doctors, these factors are also medically relevant and in alignment with the medical literature.INDEX TERMS Multi-target prediction, classification algorithms, data mining, simulated annealing.
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