Reliability and reproducibility of clinical phenotypes developed during the first wave of COVID-19: A validation study in critically ill patients from the second and third wave (preprint)

Background: During the first wave of the COVID-19 pandemic, different clinical phenotypes were published. However, none of them have been validated in subsequent waves, so their current validity is unknown. The aim of the study is to validate the unsupervised cluster model developed during the first pandemic wave in a cohort of critically ill patients from the second and third pandemic waves. Methods: Retrospective, multicentre, observational study of critically ill patients with confirmed COVID-19 disease and acute respiratory failure admitted from 74 Intensive Care Units (ICU) in Spain. To validate our original phenotypes model, we assigned a phenotype to each patient of the validation cohort using the same medoids, the same number of clusters (n= 3), the same number of variables (n= 25) and the same discretisation used in the development cohort. The performance of the classification was determined by Silhouette analysis and general linear modelling. The prognostic models were validated, and their performance was measured using accuracy test and area under curve (AUC)ROC. Results: The database included a total of 2,033 patients (mean age 63[53-92] years, 1643(70.5%) male, median APACHE II score (12[9-16]) and SOFA score (4[3-6]) points. The ICU mortality rate was 27.2%. Although the application of unsupervised cluster analysis classified patients in the validation population into 3 clinical phenotypes. Phenotype A (n=1,206 patients, 59.3%), phenotype B (n=618 patients, 30.4%) and phenotype C (n=506 patients, 24.3%), the characteristics of patients within each phenotype were significantly different from the original population. Furthermore, the silhouette coefficients were close to or below zero and the inclusion of phenotype classification in a regression model did not improve the model performance (accuracy =0.78, AUC=0.78) with respect to a standard model (accuracy = 0.79, AUC=0.79) or even worsened when the model was applied to patients within each phenotype (accuracy = 0.80, AUC 0.77 for Phenotype A, accuracy=0.73, AUC= 0.67 for phenotype B and accuracy= 0.66 , AUC= 0.76 for phenotype C ) Conclusion:  Models developed using machine learning techniques during the first pandemic wave cannot be applied with adequate performance to patients admitted in subsequent waves without prior validation. Trial Registration: The study was retrospectively registered (NCT 04948242) on June 30, 2021

Patients With Hereditary Angioedema Do Not Develop More Severe COVID-19 but SARS-CoV-2 Infection May Trigger Attacks: 66 Cases (preprint)

Purpose: Hereditary angioedema (HAE) is a rare genetic disease with hyperactivated contact and kallikrein-kinin systems leading to bradykinin (BK) release and edema. SARS-CoV-2 infection results in inflammatory exacerbation. C1 inhibitor (C1-INH) deficiency could aggravate clinical outcomes, with HAE patients at a greater risk of adverse outcomes of COVID-19, however, data are still limited. Our aim was to characterize the course and severity of COVID-19 in patients with HAE.MethodsLatin American HAE reference centers evaluated SARS-CoV-2 infection in this population. Patients with confirmed diagnosis of HAE with (HAE-C1-INH) or without C1-INH deficiency (HAE-nC1-INH) were included. HAE symptomatology and the course of COVID-19 were characterized with the application of a questionnaire. Results66 patients from 10 countries (HAE-C1-INH 80,3%; HAE-nC1-INH 19.6%) were reported with SARS-CoV-2 infection. Comorbidities were absent in 69.7% of the patients and obesity present in 12.1%. Attacks occurred in 45.5% of patients with HAE during SARS-CoV-2 infection. Long term prophylaxis was reported in 52% (34/66) of HAE patients. Complete cure was observed in 61 patients (92.4%), pulmonary sequelae in 4 and death in one HAE-C1-INH patient. The cause of death was septic shock secondary to bacterial pulmonary coinfection. Disease progression was not impacted by sex, therapy or type of HAE (p = 0.803). ConclusionAttacks occurred in almost half of HAE patients suggesting that SARS-CoV-2 infection is a trigger. HAE did not represent a risk factor for a worse outcome of COVID-19, even in use of androgens.

Preventive measures against the COVID-19 pandemic in Mexico: A cross-sectional study (preprint)

Background: In December 2019, the World Health Organization announced a new viral pneumonia due to SARS-CoV-2, which originated in Wuhan, China. In Mexico, the official announcement regarding the first coronavirus disease 2019 (COVID-19) case was made on February 29, 2020. Understanding how Mexicans behave during the pandemic could present a complete picture of the pandemic in Mexico while providing better handling of the pandemic. Methods: : This was a cross-sectional survey in which we inquired about the Mexican population's behavior and preventive measures. In total, 4004 subjects from the general population responded to the survey. The survey comprised a questionnaire that included demographic data, housing conditions, daily coexistence with people, use of preventive measures, confidence in the Mexican health-care sector, acceptance of medical procedures, and knowledge of COVID-19. Results: : Participants' mean age was 30 ± 13.7 years, and 43.8% of participants reported at least one comorbidity. Almost 99% of the participants mentioned knowing the symptoms of COVID-19. Moreover, 68.1% of them lived with three to five cohabitants, and 87.4% of them stated that at least one household member had to break social isolation every week. Although 77.5% of participants considered that they followed proper social distancing measures, 60% of them mentioned that they knew at least six individuals who did not follow social distancing measures. Furthermore, 96.2% of participants reported using preventive measures at least 50% of the time. Face masks were used by 99.5% of them, but only 51.3% used a certified mask. Conclusions: : The COVID-19 pandemic outcomes in Mexico are the result of multiple negative factors, such as high rates of comorbidities (e.g., diabetes and hypertension); a high number of people living together at home, with many people breaking social isolation; and most of the population using noncertified preventive measures, which may not have the necessary effectiveness.