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.

There is some evidence that male gender could have a negative impact on the prognosis and severity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The aim of the present study was to compare the characteristics of coronavirus disease 2019 (COVID-19) between hospitalized men and women with confirmed SARS-CoV-2 infection. This multicenter, retrospective, observational study is based on the SEMI-COVID-19 Registry. We analyzed the differences between men and women for a wide variety of demographic, clinical, and treatment variables, and the sex distribution of the reported COVID-19 deaths, as well as intensive care unit (ICU) admission by age subgroups. This work analyzed 12,063 patients (56.8% men). The women in our study were older than the men, on average (67.9 vs. 65.7 years; p < 001). Bilateral condensation was more frequent among men than women (31.8% vs. 29.9%; p = 0.007). The men needed non-invasive and invasive mechanical ventilation more frequently (5.6% vs. 3.6%, p < 0.001, and 7.9% vs. 4.8%, p < 0.001, respectively). The most prevalent complication was acute respiratory distress syndrome, with severe cases in 19.9% of men (p < 0.001). In men, intensive care unit admission was more frequent (10% vs. 6.1%; p < 0.001) and the mortality rate was higher (23.1% vs. 18.9%; p < 0.001). Regarding mortality, the differences by gender were statistically significant in the age groups from 55 years to 89 years of age. A multivariate analysis showed that female sex was significantly and independently associated with a lower risk of mortality in our study. Male sex appears to be related to worse progress in COVID-19 patients and is an independent prognostic factor for mortality. In order to fully understand its prognostic impact, other factors associated with sex must be considered.

Introduction. Sepsis is the main cause of death in hospitals and the implementation of diagnosis and treatment bundles has shown to improve its evolution. However, there is a lack of evidence about patients attended in conventional units. Methods. A 3-year retrospective cohort study was conducted. Patients hospitalized in Internal Medicine units with sepsis were included and assigned to two cohorts according to Sepsis Code (SC) activation (group A) or not (B). Baseline and evolution variables were collected. Results. A total of 653 patients were included. In 296 cases SC was activated. Mean age was 81.43 years, median Charlson comorbidity index (CCI) was 2 and 63.25% showed some functional disability. More bundles were completed in group A: blood cultures 95.2% vs 72.5% (p < 0.001), extended spectrum antibiotics 59.1% vs 41.4% (p < 0.001), fluid resuscitation 96.62% vs 80.95% (p < 0.001). Infection control at 72 hours was quite higher in group A (81.42% vs 55.18%, odds ratio 3.55 [2.48-5.09]). Antibiotic was optimized more frequently in group A (60.77% vs 47.03%, p 0.008). Mean in-hospital stay was 10.63 days (11.44 vs 8.53 days, p < 0.001). Complications during hospitalization appeared in 51.76% of patients, especially in group B (45.95% vs 56.58%, odds ratio 1.53 [1.12-2.09]). Hospital readmissions were higher in group A (40% vs 24.76%, p < 0.001). 28-day mortality was significantly lower in group A (20.95% vs 42.86%, odds ratio 0.33 [0.23-0.47]). Conclusions. Implementation of SC seems to be effective in improving short-term outcomes in IM patients, although therapy should be tailored in an individual basis.

The significant impact of COVID-19 worldwide has made it necessary to develop tools to identify patients at high risk of severe disease and death. This work aims to validate the RIM Score-COVID in the SEMI-COVID-19 Registry. The RIM Score-COVID is a simple nomogram with high predictive capacity for in-hospital death due to COVID-19 designed using clinical and analytical parameters of patients diagnosed in the first wave of the pandemic. The nomogram uses five variables measured on arrival to the emergency department (ED): age, sex, oxygen saturation, C-reactive protein level, and neutrophil-to-platelet ratio. Validation was performed in the Spanish SEMI-COVID-19 Registry, which included consecutive patients hospitalized with confirmed COVID-19 in Spain. The cohort was divided into three time periods: T1 from February 1 to June 10, 2020 (first wave), T2 from June 11 to December 31, 2020 (second wave, pre-vaccination period), and T3 from January 1 to December 5, 2021 (vaccination period). The model’s accuracy in predicting in-hospital COVID-19 mortality was assessed using the area under the receiver operating characteristics curve (AUROC). Clinical and laboratory data from 22,566 patients were analyzed: 15,976 (70.7%) from T1, 4,233 (18.7%) from T2, and 2,357 from T3 (10.4%). AUROC of the RIM Score-COVID in the entire SEMI-COVID-19 Registry was 0.823 (95%CI 0.819–0.827) and was 0.834 (95%CI 0.830–0.839) in T1, 0.792 (95%CI 0.781–0.803) in T2, and 0.799 (95%CI 0.785–0.813) in T3. The RIM Score-COVID is a simple, easy-to-use method for predicting in-hospital COVID-19 mortality that uses parameters measured in most EDs. This tool showed good predictive ability in successive disease waves. Supplementary Information The online version contains supplementary material available at 10.1007/s11739-023-03200-3.