Correction: Feasibility of a Pediatric Acute Video Consultation Process Among Health Care Professionals in Primary Care in a Rural Setting: Protocol for a Prospective Validation Study.

[This corrects the article DOI: 10.2196/52946.].

Real-world testing of an artificial intelligence algorithm for the analysis of chest X-rays in primary care settings.

Interpreting chest X-rays is a complex task, and artificial intelligence algorithms for this purpose are currently being developed. It is important to perform external validations of these algorithms in order to implement them. This study therefore aims to externally validate an AI algorithm's diagnoses in real clinical practice, comparing them to a radiologist's diagnoses. The aim is also to identify diagnoses the algorithm may not have been trained for. A prospective observational study for the external validation of the AI algorithm in a region of Catalonia, comparing the AI algorithm's diagnosis with that of the reference radiologist, considered the gold standard. The external validation was performed with a sample of 278 images and reports, 51.8% of which showed no radiological abnormalities according to the radiologist's report. Analysing the validity of the AI algorithm, the average accuracy was 0.95 (95% CI 0.92; 0.98), the sensitivity was 0.48 (95% CI 0.30; 0.66) and the specificity was 0.98 (95% CI 0.97; 0.99). The conditions where the algorithm was most sensitive were external, upper abdominal and cardiac and/or valvular implants. On the other hand, the conditions where the algorithm was less sensitive were in the mediastinum, vessels and bone. The algorithm has been validated in the primary care setting and has proven to be useful when identifying images with or without conditions. However, in order to be a valuable tool to help and support experts, it requires additional real-world training to enhance its diagnostic capabilities for some of the conditions analysed. Our study emphasizes the need for continuous improvement to ensure the algorithm's effectiveness in primary care.

Impact of COVID-19 on the Pediatric Primary Care Model in Catalonia: Analysis of Changes in the Number and Type of Face-to-Face and Remote Visits.

Background: The outbreak of COVID-19 has turned the care model of health systems around the world upside down. The health care crisis has led to opportunities for digital health to deliver quality care, and the system has been redirected toward telemedicine. In Catalonia, Spain, as of March 2020, the pattern of visits in primary care pediatric consultations changed, such that face-to-face visits decreased in favor of non-face-to-face visits. Objective: This study aimed to analyze variations in the types of pediatric visits in primary care centers in Catalonia before and after the onset of COVID-19. Methods: This was a descriptive observational study based on administrative data. The number and type of visits to primary care pediatric services in Catalonia between January 2019 and December 2022 were studied. Results: A drop of more than 80% in face-to-face visits and an increase of up to 15 times in remote visits were observed as of March 2020 compared to the previous year. Subsequently, the face-to-face attendance rate began to recover, although it did not reach the same rate as before COVID-19. Non-face-to-face visits were maintained, representing more than 20% of the total after more than 2 years of the pandemic. Conclusions: COVID-19 has been the trigger for a transition in the types of visits to primary care pediatric services. The COVID-19 pandemic was a clear catalyst for the integration of telemedicine in Catalan pediatric health care. In this context, although face-to-face consultations have recovered in absolute numbers, after the pandemic period, the weight of telemedicine has increased.

Feasibility of a Pediatric Acute Video Consultation Process Among Health Care Professionals in Primary Care in a Rural Setting: Protocol for a Prospective Validation Study.

BACKGROUND: For years, in Catalonia and in the rest of Spain, there has been a deficit and an unequal geographical distribution of health professionals specializing in pediatrics, especially in rural areas. Among the proposals to improve this situation is the promotion of the use of information and communication technologies (ICT) among users and professionals. Moreover, with the outbreak of COVID-19, the use of telehealth has become an essential tool, with an overall increase in non-face-to-face visits, including in primary care pediatrics. In this context, telemedicine, when used in primary care pediatrics, can be an effective means of improving families' access to medical care. Currently, in Catalonia, telemedicine involving patients and health professionals is used in pediatric primary care through telephone consultation and asynchronous teleconsultation (eConsulta). Video consultation is in practice not used, although it could have different applications. OBJECTIVE: The aim of this study is to evaluate the feasibility of a video consultation process with physical examination in acute pediatric pathology in rural areas among primary care professionals. In addition, the level of satisfaction with these remote consultations will be assessed from the perspective of both the users and the health care professionals. METHODS: We will conduct a prospective experimental study to analyze the possibility of using video consultation in pediatric acute care in primary care in central Catalonia (Spain). A minimum of 170 children aged between 0 and 14 years attending the primary care center (PCC) for acute illness for a period of 1 year will be included in the study. Initially, the telemetric visit, including a physical examination, will include a nurse at the patient and family's side and a pediatrician who will participate remotely. Subsequently, the pediatrician will visit the patient in person and the physical examination and diagnosis made during the remote visit will be compared with the physical examination and diagnosis of the face-to-face visit, which is considered the gold standard. RESULTS: Recruitment was planned to begin in the second half of 2023 and continue for at least 1 year. It is anticipated to be a good resource for a variety of acute pediatric conditions in primary care. The evaluation will focus on the feasibility of performing live remote visits and comparing their diagnostic accuracy with that of face-to-face visits. CONCLUSIONS: We believe that this study could provide evidence on the feasibility and diagnostic accuracy of video consultation in pediatric acute primary care in a rural setting, as well as on satisfaction with video consultations among both users and professionals. If proven useful in addressing the acute needs of children in a variety of situations, it could become a digital health tool that improves the overall pediatric primary care service in rural areas, for both families and professionals. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/52946.

Clinical characteristics and degree of cardiovascular risk factor control in patients with newly-diagnosed type 2 diabetes in Catalonia.

Introduction: Women with type 2 diabetes mellitus (T2DM) face a greater risk of cardiovascular disease (CVD) and encounter challenges in managing cardiovascular risk factors (CVRF); however, limited data are available in individuals with newlydiagnosed T2DM. Methods: This study aimed to examine differences between women and men at the onset of T2DM in terms of clinical characteristics, glycaemic status, and CVRF management. This was a retrospective cohort study including subjects with newly-diagnosed T2DM from the System for the Development of Research in Primary Care (SIDIAP) database in Catalonia (Spain). Sex differences (Dif) were assessed at baseline and 1-year post-diagnosis, by calculating the absolute difference of means or proportions. Results: A total of 13,629 subjects with newly-diagnosed T2DM were analyzed. Women were older and had a higher BMI than men. At baseline, women had higher total cholesterol [Dif (95%CI) 10 mg/dL (9.1/10.8)] and low-density lipoprotein cholesterol (LDL-c) [Dif (95%CI) 7 mg/dL (6.3/7.7)], while men had higher rates of smoking and alcohol intake. Lipid target achievement was lower in women, in both primary prevention (LDL-c < 100 mg/dL) [Dif (95%CI) -7.3 mg/dL (-10.5/-4.1)] and secondary prevention (LDL-c < 70 mg/dL) [Dif (95%CI) -8.3 mg/dL (-17.3/0.7)], along with lower statin and antiplatelet prescriptions, especially one year after diagnosis. Changes in clinical and laboratory data one year post-diagnosis revealed that, in the primary prevention group, men experienced greater improvements in total cholesterol, LDL-c and triglycerides, while women had less success in achieving CVRF control targets compared to men. Additionally, cardiovascular events, such as coronary artery disease and peripheral artery disease increased more in men than in women within the first year of diagnosis, especially in primary prevention subjects. Conclusion: Differences between men and women CVRF are already apparent at the onset of T2DM, particularly in primary prevention, with notable differences in lipid profile and target level attainment.

A Sex- and Gender-Based Approach to Chronic Conditions in Central Catalonia (Spain): A Descriptive Cross-Sectional Study.

The growth of chronic conditions worldwide poses a challenge for both health systems and the quality of life of people with these conditions. However, sex- and gender-based approaches are scarce in this field. Adopting this perspective, this study aims to describe the prevalence of chronic conditions in the Bages-Moianès region (Catalonia, Spain), and analyse the associations of chronic conditions with sex and age. This cross-sectional study used data from the population assigned to the Catalan Health Institute primary care settings in this area between 2018 and 2021 (n = 163,024). A total of 26 chronic conditions (grouped into 7 typologies), sex and age were the analysis variables. A total of 75,936 individuals presented at least one chronic condition, representing 46.6% of the analysed population. The prevalence was higher among women and older individuals. Being male was associated with a greater probability of presenting cardiovascular diseases, neurodevelopmental disorders and metabolic diseases and a lower probability of presenting neurodegenerative diseases, chronic pain and mental health disorders. Adjusting by sex, a positive age gradient was observed in most groups, except for respiratory diseases and mental health disorders. Chronic conditions have a high prevalence in the Bages-Moianès region, showing differences in typology, sex and age. Adopting gender perspectives (both in health systems and future research) is crucial when dealing with chronic conditions in order to take into account their differential impact.

eHealth in the Management of Depressive Episodes in Catalonia's Primary Care From 2017 to 2022: Retrospective Observational Study.

BACKGROUND: The reasons for mental health consultations are becoming increasingly relevant in primary care. The Catalan health care system is undergoing a process of digital transformation, where eHealth is becoming increasingly relevant in routine clinical practice. OBJECTIVE: This study aimed to analyze the approach to depressive episodes and the role of eHealth in the Catalan health care system from 2017 to 2022. METHODS: A retrospective observational study was conducted on diagnostic codes related to depressive episodes and mood disorders between 2017 and 2022 using data from the Catalan Institute of Health. The sociodemographic evolution and prevalence of depression and mood disorders in Catalonia were analyzed between 2017 and 2022. Sociodemographic variables were analyzed using absolute frequency and percentage. The prevalence of depressive episodes was calculated, highlighting the year-to-year changes. The use of eHealth for related consultations was assessed by comparing the percentages of eHealth and face-to-face consultations. A comparison of sociodemographic variables based on attendance type was conducted. Additionally, a logistic regression model was used to explore factors influencing face-to-face attendance. The analysis used R software (version 4.2.1), with all differences examined using 95% CIs. RESULTS: From 2017 to 2022, there was an 86.6% increase in the prevalence of depression and mood disorders, with women consistently more affected (20,950/31,197, 67.2% in 2017 and 22,078/33,169, 66.6% in 2022). In 2022, a significant rise in depression diagnoses was observed in rural areas (difference 0.71%, 95% CI 0.04%-1.43%), contrasting with a significant decrease in urban settings (difference -0.7%, 95% CI -1.35% to -0.05%). There was a significant increase in antidepressant use in 2022 compared to 2017 (difference 2.4%, 95% CI 1.87%-3.06%) and the proportion of eHealth visits rose from 4.34% (1240/28,561) in 2017 to 26.3% (8501/32,267) in 2022. Logistic regression analysis indicated that men (odds ratio [OR] 1.06, 95% CI 1.04-1.09) and younger individuals had a higher likelihood of eHealth consultations in 2022. Furthermore, individuals using eHealth consultations were more likely to use antidepressants (OR 1.54, 95% CI 1.50-1.57) and anxiolytics (OR 1.06, 95% CI 1.03-1.09). CONCLUSIONS: The prevalence of depression in Catalonia has significantly increased in the last 6 years, likely influenced by the COVID-19 pandemic. Despite ongoing digital transformation since 2011, eHealth usage remained limited as of 2017. During the lockdown period, eHealth accounted for nearly half of all health care consultations, representing a quarter of consultations by 2022. In the immediate aftermath of the COVID-19 pandemic, emerging evidence suggests a significant role of eHealth in managing depression-related consultations, along with an apparent likelihood of patients being prescribed antidepressants and anxiolytics. Further research is needed to understand the long-term impact of eHealth on diagnostic practices and medication use.

Knowledge and Perception of the Use of AI and its Implementation in the Field of Radiology: Cross-Sectional Study.

BACKGROUND: Artificial Intelligence (AI) has been developing for decades, but in recent years its use in the field of health care has experienced an exponential increase. Currently, there is little doubt that these tools have transformed clinical practice. Therefore, it is important to know how the population perceives its implementation to be able to propose strategies for acceptance and implementation and to improve or prevent problems arising from future applications. OBJECTIVE: This study aims to describe the population's perception and knowledge of the use of AI as a health support tool and its application to radiology through a validated questionnaire, in order to develop strategies aimed at increasing acceptance of AI use, reducing possible resistance to change and identifying possible sociodemographic factors related to perception and knowledge. METHODS: A cross-sectional observational study was conducted using an anonymous and voluntarily validated questionnaire aimed at the entire population of Catalonia aged 18 years or older. The survey addresses 4 dimensions defined to describe users' perception of the use of AI in radiology, (1) "distrust and accountability," (2) "personal interaction," (3) "efficiency," and (4) "being informed," all with questions in a Likert scale format. Results closer to 5 refer to a negative perception of the use of AI, while results closer to 1 express a positive perception. Univariate and bivariate analyses were performed to assess possible associations between the 4 dimensions and sociodemographic characteristics. RESULTS: A total of 379 users responded to the survey, with an average age of 43.9 (SD 17.52) years and 59.8% (n=226) of them identified as female. In addition, 89.8% (n=335) of respondents indicated that they understood the concept of AI. Of the 4 dimensions analyzed, "distrust and accountability" obtained a mean score of 3.37 (SD 0.53), "personal interaction" obtained a mean score of 4.37 (SD 0.60), "efficiency" obtained a mean score of 3.06 (SD 0.73) and "being informed" obtained a mean score of 3.67 (SD 0.57). In relation to the "distrust and accountability" dimension, women, people older than 65 years, the group with university studies, and the population that indicated not understanding the AI concept had significantly more distrust in the use of AI. On the dimension of "being informed," it was observed that the group with university studies rated access to information more positively and those who indicated not understanding the concept of AI rated it more negatively. CONCLUSIONS: The majority of the sample investigated reported being familiar with the concept of AI, with varying degrees of acceptance of its implementation in radiology. It is clear that the most conflictive dimension is "personal interaction," whereas "efficiency" is where there is the greatest acceptance, being the dimension in which there are the best expectations for the implementation of AI in radiology.

Prevalence of Respiratory Infections during the 2018-2020 Period in the Paediatric Population of Primary Care Centres in Central Catalonia.

Following the COVID-19 pandemic, policies such as social distancing, hand washing, and the use of masks were implemented, which could play an important role in the reduction of infectious diseases. An observational, descriptive, cross-sectional study was conducted to observe the prevalence of respiratory infections in children under 15 years of age during the 2018-2020 period in Primary Care centres in Central Catalonia. In 2020, there was a 44.3% decrease in total consultations for respiratory infections compared to 2019. All respiratory infections exhibited a significant decrease except flu-like syndrome; children between the ages of 6 and 12 had the highest prevalence of flu-like syndrome (87.6%), and the SARS-CoV-2-19 infection was most frequent (4%) among those between the ages of 12 and 15. Compared to urban centres, rural centres presented a higher prevalence of all infections except flu-like syndrome and SARS-CoV-2. In conclusion, the COVID-19 pandemic caused a significant decrease in the number of consultations for respiratory infections in the paediatric population, except for flu-like syndrome, which increased in cases in January, February, and March 2020. No differences were found between sexes, although differences were found in the distribution of the different age groups.

Exploring the potential of artificial intelligence in improving skin lesion diagnosis in primary care.

Dermatological conditions are a relevant health problem. Machine learning (ML) models are increasingly being applied to dermatology as a diagnostic decision support tool using image analysis, especially for skin cancer detection and disease classification. The objective of this study was to perform a prospective validation of an image analysis ML model, which is capable of screening 44 skin diseases, comparing its diagnostic accuracy with that of General Practitioners (GPs) and teledermatology (TD) dermatologists in a real-life setting. Prospective, diagnostic accuracy study including 100 consecutive patients with a skin problem who visited a participating GP in central Catalonia, Spain, between June 2021 and October 2021. The skin issue was first assessed by the GPs. Then an anonymised skin disease picture was taken and uploaded to the ML application, which returned a list with the Top-5 possible diagnosis in order of probability. The same image was then sent to a dermatologist via TD for diagnosis, as per clinical practice. The GPs Top-3, ML model's Top-5 and dermatologist's Top-3 assessments were compared to calculate the accuracy, sensitivity, specificity and diagnostic accuracy of the ML models. The overall Top-1 accuracy of the ML model (39%) was lower than that of GPs (64%) and dermatologists (72%). When the analysis was limited to the diagnoses on which the algorithm had been explicitly trained (n = 82), the balanced Top-1 accuracy of the ML model increased (48%) and in the Top-3 (75%) was comparable to the GPs Top-3 accuracy (76%). The Top-5 accuracy of the ML model (89%) was comparable to the dermatologist Top-3 accuracy (90%). For the different diseases, the sensitivity of the model (Top-3 87% and Top-5 96%) is higher than that of the clinicians (Top-3 GPs 76% and Top-3 dermatologists 84%) only in the benign tumour pathology group, being on the other hand the most prevalent category (n = 53). About the satisfaction of professionals, 92% of the GPs considered it as a useful diagnostic support tool (DST) for the differential diagnosis and in 60% of the cases as an aid in the final diagnosis of the skin lesion. The overall diagnostic accuracy of the model in this study, under real-life conditions, is lower than that of both GPs and dermatologists. This result aligns with the findings of few existing prospective studies conducted under real-life conditions. The outcomes emphasize the significance of involving clinicians in the training of the model and the capability of ML models to assist GPs, particularly in differential diagnosis. Nevertheless, external testing in real-life conditions is crucial for data validation and regulation of these AI diagnostic models before they can be used in primary care.

Gender, Mental Health and Socioeconomic Differences in Fibromyalgia: A Retrospective Cohort Study Using Real-World Data from Catalonia.

The main objective of our study was to assess the associated risk between fibromyalgia (FM) and the incidence of the diagnosis of anxiety and depression in the general population during the years 2010-2017 in Catalonia. METHOD: A retrospective cohort study was designed using the Information System for Research Development in Primary Care database. All patients with FM were included (n = 56,098) and matched to the control group in a 1:2 pairing ratio (n = 112,196). The demographic variables studied were sex, age and socio-economic status. RESULTS: Patients with FM have a lower survival rate if they are also diagnosed with anxiety and depression during the entire study period, with the rate being 26.6% lower in FM patients at an 8-year follow-up (0.58, 95%CI: 0.57-0.59 vs. 0.79, 95%CI: 0.78-0.79). There is a 58% reduction in the risk of developing anxiety and/or depression in the control group vs. the FM group (p-value < 0.05), and by 45% in male vs. female sex (p-value < 0.05). CONCLUSIONS: FM is a disease that is associated with anxiety and depression, and men are at lower risk of anxiety and depression after FM diagnosis.

Detection of gender-based violence in primary care in Central Catalonia: a descriptive cross-sectional study.

BACKGROUND: Violence against women is a serious public health problem. Primary care could be one of the ideal places for the detection of gender-based violence (GBV), since women come into contact with PC at some point in their lives to look after their sexual and reproductive health. The increase in initiatives promoted by the health authorities regarding GBV offers the possibility of observing its evolution over the last few years. METHODS: A descriptive cross-sectional study of reported cases of GBV in the region of Central Catalonia, during the period from 2017 to 2021, was carried out. All women of legal age, belonging to the specified health region and suffering episodes of GBV, were included. The variables analysed were age, area of residence, health diagnoses related to GBV, whether or not they were pregnant at the time of the attack, and mental health history. RESULTS: Of the total number of women studied, 1,467 presented some type of diagnosis of GBV, with a total of 3,452 episodes reported. We found an increase in the detection of cases, although it must be noted that there is an underreporting of cases in PC. The prevalence according to the total number of women assigned per year over the period studied was 0.42% in 2017 and 0.48% in 2021. It has also been observed that the average number of episodes per woman increased from 1.03 in 2017 to 1.15 in 2021. During the 5 years analysed, the minimum number of episodes per woman was 1 and the maximum was 10. In reference to the duration of the episodes, the minimum was 1 day, and the maximum was 32 years. The mean age of the women was 42.10 years, the most frequent nationality was Spanish (46.60%), and 54.15% of them lived in rural areas. CONCLUSIONS: Despite the established protocols and procedures, it seems that primary health care is not the most frequent place for its detection. It is necessary to continue working to raise awareness and train professionals, and to ensure coordination among all the parties involved in accompanying women in these processes. TRIAL REGISTRATION: CEIm: 21/278-P.

Recording of Social Determinants in Computerized Medical Records in Primary Care Consultations: Quasi-Experimental Study.

BACKGROUND:  Social determinants of health may be more important than medical or lifestyle choices in influencing people's health. Even so, there is a deficit in recording these in patients' computerized medical histories. The Spanish administration and the World Health Organization are promoting the recording of diagnoses in computerized clinical histories with the aim of benefiting the individual, the professional, and the community. In most cases, professionals tend to record only clinical diagnoses despite evidence in the literature documenting that addressing the social determinants of health can lead to improvements in health and reductions in social disparities in disease. OBJECTIVE:  This study aims to develop and evaluate the effectiveness of a mixed intervention (face-to-face-digital) aimed at improving the quantity and quality of the records of the social determinants of health in computerized medical records at primary care clinics. METHODS:  A quasi-experimental, nonrandomized, controlled, multicenter study with 2 parallel study arms was conducted in the area of Central Catalonia (Spain) with primary care professionals of the Institut Català de la Salut (ICS), working from September 23, 2019, to March 31, 2020. All interested professionals were accepted. In total, 22 basic health areas were involved in the study. In Spain and Catalonia, the International Classification of Diseases is used, in which there is a coding of the social determinants of health. Five social determinants were selected by a physician, a nurse, and a social worker; these professionals had experience in primary care and were experts in community health. The choice was made taking into account the ease of use, benefit, and existing terminology. The intervention, based on the integration of a checklist, was integrated as part of the usual multidisciplinary clinical workflow in primary care consultations to influence the recording of these determinants in the patient's computerized medical record. RESULTS:  After 6 months of implementing the intervention, the volume and quantity of records of 5 social determinants of health were compared, and a significant increase in the median number of pre- and postintervention diagnoses was observed (P≤.001). There was also an increase in the diversity of selected social determinants. Using the linear regression model, the significant mean increase of the experimental group with respect to the control group was estimated with a coefficient of 8.18 (95% CI 5.11-11.26). CONCLUSIONS:  The intervention described in this study is an effective tool for coding the social determinants of health designed by a multidisciplinary team to be incorporated into the workflow of primary care practices. The effectiveness of its usability and the description of the intervention described here should be generalizable to any environment. TRIAL REGISTRATION: ClinicalTrials.gov NCT04151056; https://clinicaltrials.gov/ct2/show/NCT04151056.

Developing an Artificial Intelligence Model for Reading Chest X-rays: Protocol for a Prospective Validation Study.

BACKGROUND: Chest x-rays are the most commonly used type of x-rays today, accounting for up to 26% of all radiographic tests performed. However, chest radiography is a complex imaging modality to interpret. Several studies have reported discrepancies in chest x-ray interpretations among emergency physicians and radiologists. It is of vital importance to be able to offer a fast and reliable diagnosis for this kind of x-ray, using artificial intelligence (AI) to support the clinician. Oxipit has developed an AI algorithm for reading chest x-rays, available through a web platform called ChestEye. This platform is an automatic computer-aided diagnosis system where a reading of the inserted chest x-ray is performed, and an automatic report is returned with a capacity to detect 75 pathologies, covering 90% of diagnoses. OBJECTIVE: The overall objective of the study is to perform validation with prospective data of the ChestEye algorithm as a diagnostic aid. We wish to validate the algorithm for a single pathology and multiple pathologies by evaluating the accuracy, sensitivity, and specificity of the algorithm. METHODS: A prospective validation study will be carried out to compare the diagnosis of the reference radiologists for the users attending the primary care center in the Osona region (Spain), with the diagnosis of the ChestEye AI algorithm. Anonymized chest x-ray images will be acquired and fed into the AI algorithm interface, which will return an automatic report. A radiologist will evaluate the same chest x-ray, and both assessments will be compared to calculate the precision, sensitivity, specificity, and accuracy of the AI algorithm. Results will be represented globally and individually for each pathology using a confusion matrix and the One-vs-All methodology. RESULTS: Patient recruitment was conducted from February 7, 2022, and it is expected that data can be obtained in 5 to 6 months. In June 2022, more than 450 x-rays have been collected, so it is expected that 600 samples will be gathered in July 2022. We hope to obtain sufficient evidence to demonstrate that the use of AI in the reading of chest x-rays can be a good tool for diagnostic support. However, there is a decreasing number of radiology professionals and, therefore, it is necessary to develop and validate tools to support professionals who have to interpret these tests. CONCLUSIONS: If the results of the validation of the model are satisfactory, it could be implemented as a support tool and allow an increase in the accuracy and speed of diagnosis, patient safety, and agility in the primary care system, while reducing the cost of unnecessary tests. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/39536.

Motivation for Vaccination against COVID-19 in Persons Aged between 18 and 60 Years at a Population-Based Vaccination Site in Manresa (Spain).

Our purpose was to identify the reasons why members of the population, aged 18-60 years, are vaccinated against COVID-19 at the mass vaccination point in Bages, Spain. This is 1 of 42 provisional spaces outside of health centres which have been set up in Catalonia in the context of the COVID-19 pandemic, and where people from all over Catalonia could go to be vaccinated by appointment. METHODOLOGY: We performed a cross-sectional study of users attending mass vaccination points in Bages during the months of July, August, and September 2021. RESULTS: A total of 1361 questionnaires were statistically analysed. The most common reasons for vaccination were fear of infecting family (49.52%) and fear of self-infection (39.45%), followed by socialising (31.00%) and travel (30.56%). However, by applying a logistic regression model to each reason for vaccination, it was possible to estimate the associations regarding age, sex, marital status, educational level, production sector, mass vaccination point, previous COVID-19 infection, and COVID-19 infection of a family member. RELEVANCE: The data generated will inform decisions and formulations of appropriate campaigns that will promote vaccination in specific population groups.

Prevalence and Incidence of Patients With Fibromyalgia in Catalonia Between 2010 and 2017: A Descriptive Observational Study.

OBJECTIVE: To measure the prevalence and cumulative incidence of individuals diagnosed with fibromyalgia (FM) in Catalonia between 2010 and 2017. METHODS: A retrospective observational study of the population of Catalonia between 2010 and 2017, both included, was designed to describe the incidence, prevalence, and sociodemographic characteristics of individuals diagnosed with fibromyalgia. A total of 56 098 patients were included in the study. The scope of the study were the 283 Primary Care Teams (PCT), all managed by the Instituto Catalán de la Salud [Catalan Institute of Health] (ICS). RESULTS: The diagnosis of FM is higher in females (95.4%) than males (4.55%), with a mean age of 53.0 [45.0-61.0] years. The prevalence of FM in the total population was 0.4% in 2010 and 1.4% in 2017. The highest prevalence was found in the 55 to 65 age group (1.05% in 2010, and 2.46% in 2017). A relationship was found between the prevalence of FM and the degree of socioeconomic deprivation in urban areas: the greater the deprivation, the greater the prevalence of FM. The cumulative incidence of FM in the population remained constant over time (0.11% in 2010 and 0.10% in 2017), being more prevalent in women than men (0.18% women, 0.01% men in 2017). CONCLUSIONS: Our study confirms that FM is a prevalent disease in Catalonia, with an upward trend in recent years and it is more prevalent in women.

Use of Virtual Reality in the Reduction of Pain After the Administration of Vaccines Among Children in Primary Care Centers: Protocol for a Randomized Clinical Trial.

BACKGROUND: Pain and anxiety caused by vaccination and other medical procedures in childhood can result in discomfort for both patients and their parents. Virtual reality (VR) is a technology that is capable of entertaining and distracting the user. Among its many applications, we find the improvement of pain management and the reduction of anxiety in patients undergoing medical interventions. OBJECTIVE: We aim to publish the protocol of a clinical trial for the reduction of pain and anxiety after the administration of 2 vaccines in children aged 3 to 6 years. METHODS: We will conduct a randomized, parallel, controlled clinical trial with 2 assigned groups. The intervention group will wear VR goggles during the administration of 2 vaccines, while the control group will receive standard care from a primary care center for the procedure. Randomization will be carried out by using the RandomizedR computer system-a randomization tool of the R Studio program. This trial will be an open or unblinded trial; both the subjects and the investigators will know the assigned treatment groups. Due to the nature of the VR intervention, it will be impossible to blind the patients, caregivers, or observers. However, a blind third-party assessment will be carried out. The study population will include children aged 3 to 6 years who are included in the patient registry and cared for in a primary care center of the region of Central Catalonia. They will receive the following vaccines during the Well-Child checkup: the triple viral+varicella vaccine at 3 years of age and the hepatitis A+diphtheria-tetanus-pertussis vaccine at 6 years of age. RESULTS: The study is scheduled to begin in January 2022 and is scheduled to end in January 2023, which is when the statistical analysis will begin. As of March 2022, a total of 23 children have been recruited, of which 13 have used VR during the vaccination process. In addition, all of the guardians have found that VR helps to reduce pain during vaccination. CONCLUSIONS: VR can be a useful tool in pediatric procedures that generate pain and anxiety. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/35910.

Prevalence, Clinical Characteristics, and Management of Episodic Dyspnea in Advanced Lung Cancer Outpatients: A Multicenter Nationwide Study-The INSPIRA-DOS Study.

Background: Episodic dyspnea (ED) is a common problem in patients with advanced lung cancer (LC). However, the prevalence of ED and other related aspects in this patient population is not known. Objectives: To assess and describe the prevalence, clinical features, treatment, and risk factors for ED in outpatients with advanced LC. Design: Multicenter cross-sectional study. Subjects: Consecutive sample of adult outpatients with advanced LC. Measurements: We assessed background dyspnea (BD), the characteristics, triggers, and management of ED. Potential ED risk factors were assessed through multivariate logistic regression. Results: A total of 366 patients were surveyed. Overall, the prevalence of ED was 31.9% (90% in patients reporting BD). Patients reported a median of one episode per day (interquartile range [IQR]: 1-2), with a median intensity of 7/10 (IQR: 5-8.25). ED triggers were identified in 89.9% of patients. ED was significantly associated with chronic obstructive pulmonary disease (p = 0.011), pulmonary vascular disease (p = 0.003), cachexia (p = 0.002), and palliative care (p < 0.001). Continuous oxygen use was associated with higher risk of ED (odds ratio: 9.89; p < 0.001). Opioids were used by 44% patients with ED. Conclusions: ED is highly prevalent and severe in outpatients with advanced LC experiencing BD. The association between intrathoracic comorbidities and oxygen therapy points to alveolar oxygen exchange failure having a potential etiopathogenic role in ED in this population. Further studies are needed to better characterize ED in LC to better inform treatments and trial protocols.

Comparing the Clinical Characteristics and Mortality of Residential and Non-Residential Older People with COVID-19: Retrospective Observational Study.

Nursing homes have accounted for a significant part of SARS-CoV-2 mortality, causing great social alarm. Using data collected from electronic medical records of 1,319,839 institutionalised and non-institutionalised persons ≥ 65 years, the present study investigated the epidemiology and differential characteristics between these two population groups. Our results showed that the form of presentation of the epidemic outbreak, as well as some risk factors, are different among the elderly institutionalised population with respect to those who are not. In addition to a twenty-fold increase in the rate of adjusted mortality among institutionalised individuals, the peak incidence was delayed by approximately three weeks. Having dementia was shown to be a risk factor for death, and, unlike the non-institutionalised group, neither obesity nor age were shown to be significantly associated with the risk of death among the institutionalised. These differential characteristics should be able to guide the actions to be taken by the health administration in the event of a similar infectious situation among institutionalised elderly people.

Study of the sensitivity and specificity of smell and taste disorders as a predictive factor of SARS-CoV-2 infection among primary care healthcare professionals: a retrospective observational study.

BACKGROUND: Among the manifestations of COVID-19 are taste and smell disorders (TSDs). AIM: To evaluate the sensitivity and specificity of TSDs and other associated symptoms to estimate predictive values for determining SARS-CoV-2 infection. DESIGN & SETTING: A retrospective observational study of healthcare professionals in Catalonia, Spain. METHOD: A study of the sensitivity and specificity of TSDs has been carried out using the polymerase chain reaction (PCR) test for the diagnosis of SARS-CoV-2 as the gold standard value. Logistic regressions adjusted for age and sex were performed to identify additional symptoms that might be associated with COVID-19. RESULTS: The results are based on 226 healthcare workers with clinical symptoms suggestive of COVID-19, 116 with positive PCR and 110 with negative PCR. TSDs had an odds ratio (OR) of 12.4 (95% confidence interval [CI] = 6.3 to 26.2), sensitivity 60.3% and specificity 89.1%. In the logistic regression model, the association of TSD, fever or low-grade fever, shivering, dyspnoea, arthralgia, and myalgia obtained an area under the curve (AUC) of 85.7% (95% CI = 80.7 % to 90.7 %), sensitivity 82.8 %, specificity 80.0%, and positive predictive values 81.4% and negative 81.5%. CONCLUSION: TSDs are a strong predictor of COVID-19. The association of TSD, fever, low-grade fever or shivering, dyspnoea, arthralgia, and myalgia correctly predicts 85.7% of the results of the COVID-19 test.