The COVID-19 epidemic curve and vaccine acceptance among patients with rheumatic diseases: an ecological study.

The attitudes toward emerging COVID-19 vaccines have been of great interest worldwide, especially among vulnerable populations such as patients with rheumatic and musculoskeletal diseases (RMDs). The aim of this study was to analyze the relationship between the nationwide number of COVID-19 cases and deaths, and vaccine acceptance or hesitancy of patients with RMDs from four patient care centers in Mexico. Furthermore, we explored differences in acceptance according to specific diagnoses: rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). This ecological study was a secondary analysis of a cross-sectional study using a validated questionnaire to measure vaccine acceptance. We generated a global Likert scale to evaluate overall attitudes toward the COVID-19 vaccine. We analyzed data from 1336 patients from March to September 2021: 85.13% (1169) were women, with a mean age of 47.87 (SD 14.14) years. The most frequent diagnoses were RA (42.85%, 559) and SLE (27.08%, 393). 635(47.52%) patients were unvaccinated, 253(18.93%) had one dose and 478(35.77%) had two doses. Of all participating patients, 94% were accepting toward the COVID-19 vaccine. Vaccine acceptance remained consistently high throughout the study. However, differences in vaccine acceptance are identified when comparing diagnoses. The peak of the national epidemic curve coincided with an increase in hesitancy among patients with RA. Contrastingly, patients with SLE became more accepting as the epidemic curve peaked. Mexican patients show high acceptance of the COVID-19 vaccine, influenced in part by a patient's specific diagnosis. Furthermore, vaccine acceptance increased mirroring the curve of COVID-19 cases and deaths in the country. This should be taken into consideration when updating recommendations for clinical practice.

Inequity and vulnerability in Latin American Indigenous and non-Indigenous populations with rheumatic diseases: a syndemic approach.

Syndemics are a framework that documents health inequities and vulnerabilities in populations with rheumatic diseases. Compared with other approaches, syndemics are able to conjunctly consider epidemiological, biological, sociodemographic and economic factors, and their interactions. OBJECTIVE: To estimate health inequity and vulnerability among Indigenous and non-Indigenous populations with rheumatic and musculoskeletal diseases (RMD) in Latin America using the syndemic approach. DESIGN: This is a secondary analysis of a previously published large-scale study on the prevalence of RMD. SETTING: Studies carried out in five Latin American countries (Argentina, Colombia, Ecuador, Mexico and Venezuela). Health inequity and vulnerability in RMD were identified through a syndemic approach using network and cluster analysis. PARTICIPANTS: A total of 44 560 individuals were studied: 29.78% self-identified as Indigenous, 60.92% were female, the mean age was 43.25 years. Twenty clusters were identified in the Indigenous population and 17 in the non-Indigenous population. RESULTS: The variables associated with RMD among Indigenous populations were rurality, public health system, high joint biomechanical stress, greater pain, disability and alcoholism; and among non-Indigenous people they were being a woman, urban origin, older age, private health system, joint biomechanical stress, greater pain and disability. We identified different health inequities among patients with RMD (ie, lower educational attainment, more comorbidities), associated with factors such as Indigenous self-identification and rural residence. CONCLUSIONS: A syndemic approach enables us to identify health inequities in RMD, as shown by higher prevalence of comorbidities, disability and socioeconomic factors like lower educational attainment. These inequities exist for the overall population of patients with RMD, although it is more evident in Indigenous groups with added layers of vulnerability.

Perception of risk and impact of the COVID-19 pandemic on patients with rheumatic diseases: a case-control study.

OBJECTIVES: Risk perception of the COVID-19 pandemic may affect chronic disease outcomes among patients with rheumatic diseases (RD). To describe and compare the perception of risk and effects of the COVID-19 pandemic on patients with RD from two health care centers compared with a control group. METHODS: A retrospective case-control study was conducted. Patient respondents completed an online survey to measure risk perception and effects of the COVID-19 pandemic. The case group consisted of patients with a confirmed diagnosis of RD, coming from two third-level health care centers. The control group was a population group without RD from a public university. RESULTS: A total of 3944 participants were included: 986 patients with an RD (cases) from the two hospital centers and 2958 controls without RD. A greater perception of risk severity and perception of contagion was observed in the group of patients with RD, OR: 1.70, 95% CI 1.44‒2.01 and OR: 2.0, 95% CI 1.79‒2.23, respectively; more significant deterioration in family life OR: 1.14, 95% CI 1.01‒1.29; greater economic impact, OR 3.94, 95% CI 3.48‒4.46; as well as negative emotions and feelings (alarmed, anxiety, depression, confusion, fear, isolation, and discrimination). This impact was maintained when the model was adjusted for comorbidities. CONCLUSION: In the face of an unexpected and catastrophic event such as the COVID-19 pandemic, patients with RD report apparently greater impact on their mental state and economic situation than the control population, as well as increased perception of discrimination. Key Points • The multidisciplinary analyses of risk perception are required to promote actions that can enhance the preparedness and responses of public efforts for possible future pandemics in a way that considers the specific needs of vulnerable people like patients with rheumatic diseases. • Identifying risk perceptions of possible effects of the pandemic, sources of communication, and opinions is essential to ensure self-care in rheumatic disease. • The impact of COVID-19 has been much greater for people with rheumatic disease, especially in terms of the perceived severity of the pandemic, impacts on family and economy, preventive behaviors, and uncertainty.

Factors associated to COVID-19 vaccine acceptance in Mexican patients with rheumatic diseases: A cross-sectional and multicenter study.

COVID-19 vaccination is recommended in patients with rheumatic diseases (RDs) to prevent hospitalized COVID-19 and worse outcomes. However, patients' willingness to receive a SARS-CoV-2 vaccine and the associated factors vary across populations, vaccines, and time. The objective was to identify factors associated with COVID-19 vaccine acceptance (VA) in Mexican outpatients with RDs. This multicenter study was performed between March 1 and September 30, 2021, and four national centers contributed with patients. Participants filled out a questionnaire, which included 32 items related to patients' perception of the patient-doctor relationship, the COVID-19 vaccine component, the pandemic severity, the RD-related disability, comorbid conditions control, immunosuppressive treatment impact on the immune system, and moral/civil position of COVID-19 vaccine. Sociodemographic, disease-related, and treatment-related variables and previous influenza record vaccination were also obtained. Multiple logistic regression analyses identified factors associated with VA, which was defined based on a questionnaire validated in our population. There were 1439 patients whose data were analyzed, and the most frequent diagnoses were Rheumatoid Arthritis in 577 patients (40.1%) and Systemic Lupus Erythematosus in 427 (29.7%). Patients were primarily middle-aged women (1235 [85.8%]), with (mean±SD) 12.1 (±4.4) years of formal education. Years of education, corticosteroid use, patient perceptions about the vaccine and the pandemic severity, patient civil/moral position regarding COVID-19 vaccine, and previous influenza vaccination were associated with VA. In Mexican patients with RDs, COVID-19 VA is associated with individual social-demographic and disease-related factors, patient´s perceptions, and previous record vaccination. This information is crucial for tailoring effective vaccine messaging in Mexican patients with RDs.

Heterogeneity of COVID-19 Risk Perception: A Socio-Mathematical Model.

The perception of risk has been a key element in the experiences, containment and differential impact of the COVID-19 pandemic worldwide. The complexity of this phenomenon requires the interdisciplinary integration of theoretical and methodological aspects, as this integration informs the objective of developing a mathematical proposal based on a conceptual model located within the social theory of risk at the micro-social level. The mathematical risk model used here was developed from a secondary analysis of a study of 12,649 individuals on the experiences of the COVID-19 pandemic in a population in which the quantity and quality of the information made it possible to define a risk factor and its relationship to emotions and the sources of information used. Four sequential strategies were used to construct the model: choosing the variables for the questionnaire that theoretically corresponded to the conceptual model, constructing the risk vector and initial grouping of individuals by perception of risk, modeling by using principal component analysis and applying network methods. The theoretical model of risk, proposed and constructed through the analysis of groupings by quartiles and by networks in the studied population from a social and mathematical perspective, demonstrates the heterogeneity of risk perception as manifested by differences in perception by age, gender, expression of feelings and media consulted in a university community. The knowledge and methodology generated in these analyses contribute to the body of knowledge informing the response to future epidemiological contingencies.

The basics of data, big data, and machine learning in clinical practice.

Health informatics and biomedical computing have introduced the use of computer methods to analyze clinical information and provide tools to assist clinicians during the diagnosis and treatment of diverse clinical conditions. With the amount of information that can be obtained in the healthcare setting, new methods to acquire, organize, and analyze the data are being developed each day, including new applications in the world of big data and machine learning. In this review, first we present the most basic concepts in data science, including the structural hierarchy of information and how it is managed. A section is dedicated to discussing topics relevant to the acquisition of data, importantly the availability and use of online resources such as survey software and cloud computing services. Along with digital datasets, these tools make it possible to create more diverse models and facilitate collaboration. After, we describe concepts and techniques in machine learning used to process and analyze health data, especially those most widely applied in rheumatology. Overall, the objective of this review is to aid in the comprehension of how data science is used in health, with a special emphasis on the relevance to the field of rheumatology. It provides clinicians with basic tools on how to approach and understand new trends in health informatics analysis currently being used in rheumatology practice. If clinicians understand the potential use and limitations of health informatics, this will facilitate interdisciplinary conversations and continued projects relating to data, big data, and machine learning.

Epidemiology and socioeconomic impact of the rheumatic diseases on indigenous people: an invisible syndemic public health problem.

Epidemiological studies in Latin America suggest indigenous people lack proper healthcare for musculoskeletal (MSK) and rheumatic diseases. OBJECTIVES: This study aimed to estimate the prevalence of MSK disorders and rheumatic diseases in eight Latin American indigenous communities, and to identify which factors influence such prevalence using network analysis and syndemic approach. METHODS: This is a cross-sectional, community-based census study according to Community-Oriented Program for the Control of Rheumatic Diseases methodology. Individuals with MSK pain, stiffness or swelling in the past and/or during the last 7 days were evaluated by participating physicians. A descriptive, univariable and multivariable analysis was performed, followed by a network analysis. RESULTS: We surveyed 6155 indigenous individuals with a mean age of 41.2 years (SD 17.6; range 18-105); 3757 (61.0%) were women. Point prevalence in rank order was: low back pain in 821 (13.3%); osteoarthritis in 598 (9.7%); rheumatic regional pain syndromes in 368 (5.9%); rheumatoid arthritis in 85 (1.3%); undifferentiated arthritis in 13 (0.2%); and spondyloarthritis in 12 (0.1%). There were marked variations in the prevalence of each rheumatic disease among the communities. Multivariate models and network analysis revealed a complex relationship between rheumatic diseases, comorbidities and socioeconomic conditions. CONCLUSIONS: The overall prevalence of MSK disorders in Latin American indigenous communities was 34.5%. Although low back pain and osteoarthritis were the most prevalent rheumatic diseases, wide variations according to population groups occurred. The relationship between rheumatic diseases, comorbidities and socioeconomic conditions allows taking a syndemic approach to the study.

Improved Surface-Based Registration of CT and Intraoperative 3D Ultrasound of Bones.

The intraoperative registration of preoperative CT volumes is a key process of most computer-assisted orthopedic surgery (CAOS) systems. In this work, is reported a new method for automatic registration of long bones, based on the segmentation of the bone cortical in intraoperative 3D ultrasound images. A bone classifier was developed based on features, obtained from the principal component analysis of the Hessian matrix, of every voxel in an intraoperative ultrasound volume. 3D freehand ultrasound was used for the acquisition of the intraoperative ultrasound volumes. Corresponding bone surface segmentations in ultrasound and preoperative CT imaging were used for the intraoperative registration. Validation on a phantom of the tibia produced encouraging results, with a maximum mean segmentation error of 0.34⁡mm (SD=0.26⁡mm) and a registration accuracy error of 0.64⁡mm (SD=0.49⁡mm).

Young adult binge drinkers have immunophenotypic changes in peripheral polymorphonuclear cells and monocytes.

BACKGROUND: High alcohol intake on weekends (binge drinking) is more frequent in young adults, who could undergo early liver damage. Alcohol-induced liver damage is characterized by polymorphonuclear cell (PMN) infiltration, which can be represented in the peripheral blood by altered trafficking and activation profiles. OBJECTIVE: To evaluate the PMN trafficking and activation immunophenotypic profiles in people with a binge drinking pattern. METHODS: People with binge drinking (n = 18, 8 females) or at low risk (n = 16, 13 females) based on their AUDIT and HEPCA scores were studied. Hematic biometry and liver enzyme tests were conducted. Peripheral blood leukocytes were stained for CCR5, CCR4, and CXCR4 (trafficking) and CD69 and CD127 (activation). PMNs and monocytes were analyzed by FACS. The data were analyzed using the T-test and Mann-Whitney's U-test for contrasts and principal component and Fuzzy C means analyses for clustering, with p < 0.05 considered significant. RESULTS: Compared to the low-risk group, the binge group showed higher CCR5 expression on PMNs, decreases in the CD69 percentage and positive PMNs per microliter, and decreased CXCR4 expression on monocytes. Six immunophenotypical clusters were identified, all of which were distributed following the CCR5 and CXCR4 main vectors. CONCLUSION: Young adult binge drinkers have differential PMN trafficking and activation immunophenotypes, which could be related to the initial onset of alcoholic liver disease and a systemic inflammatory state in response to their alcohol consumption pattern. These findings could lead to the future development of an early diagnostic tool.