How Startups and Entrepreneurs Survived in Times of Pandemic Crisis: Implications and Challenges for Managing Uncertainty

The recent pandemic crisis has greatly impacted startups, and some changes are expected to be long-lasting. Small businesses usually have fewer resources and are more vulnerable to losing customers and investors, especially during crises. This study investigates how startups' business processes were affected and how entrepreneurs managed this sudden change brought by the COVID-19 outbreak. Data were analyzed using qualitative research methods through in-depth interviews with the co-founders of eighteen startups. Results show that the three core business processes affected by the COVID-19 crisis were marketing and sales, logistics and operations, and organizational support. The way to succeed is to be flexible, agile, and adaptable, with technological knowledge focusing on digital channels to find novel opportunities and innovate. Additionally, resilience, self-improvement, education, technology readiness and adoption, close relationship with customers and other stakeholders, and incubation experience seem to shield startups against pandemic crisis outbreaks. © 2023, Small Business Institute. All rights reserved.

CLINICAL CHARACTERISTICS OF PEDIATRIC PATIENTS WITH RHEUMATIC DISEASES UNDER TREATMENT WITH BIOLOGICAL THERAPY: INFORMATION FROM BIOBADAMEX

BackgroundThe advent of biologic treatment (bDMARD) in childhood rheumatic diseases (RD) has changed their evolution and prognosis. Evidence is robust for diseases such as juvenile idiopathic arthritis (JIA) and systemic lupus erythematosus (SLE), but in other diseases we still have to learn which is the ideal therapy, time to discontinuation and the potential adverse events (AE) in short and long term.ObjectivesIdentify the clinical and treatment characteristics of pediatric patients with rheumatic diseases with bDMARD treatment and describe the development of AE.MethodsBIOBADAMEX is a prospective ongoing cohort of Mexican patients with RD using bDMARDs since 2016. We included all patients younger than 18 years of age registered in BIOBADAMEX. Descriptive statistics were used for the baseline characteristics and the Chi-square test to analyze the differences between the characteristics of the groups in relation to the development of AE.ResultsA total of 45 patients were included, 31 (69%) of them female, mean age of 13.3 (±3.6) years. (Table 1).The most frequent diagnosis was JIA 25 (56%), followed by SLE 9 (20%), uveitis 5 (11%), polymyositis/dermatomyositis and hidradenitis 2 (4%) respectively;systemic sclerosis and CINCA 1 patient (2%) respectively. The mean duration disease in years was 4.67 (±2.1). Nine patients (20%) used a biologic prior to the current;23 (51%) patients had comorbidities.The most frequent bDMARDs used was Adalimumab (ADA) in 17 (38%) patients followed by Rituximab in 15 (33%) and Tocilizumab in 10 (22%), Infliximab, Abatacept and Canakinumab were used in one patient respectively.When compared by groups, ADA and Tocilizumab were the most used bDMARDs in JIA, Rituximab the only one used in SLE and PM/DM, and ADA the only one for uveitis.15 patients discontinued biological treatment, 4 (27%) due to AE. 82% used an additional synthetic DMARD, being methotrexate the most used in 48% of patients. Steroids were used by 21 (47%) of the patients with a median dose of 10mg (IQR 5 - 25).Fifteen AEs were recorded: 7 (47%) were infections, 5 of these (71%) were COVID;allergies and neutropenia in 2 (13%) patients respectively. By disease infections were more frequent in patients with JIA and Uveitis;neutropenia only occurred in patients with JIA (p 0.95). 87% of the AEs were non-serious, 1 patient with JIA presented a severe AE and one patient with SLE a fatal AE associated with COVID (p 0.93), with no statistically significant difference between groups.ConclusionJIA is the most frequent indication to use bDMARD as worldwide reported. The AE in this analysis are similar to previous registries in terms of the prevalence of infections, in our group the most frequent infectious complication was COVID, being fatal in one patient related with rituximab in SLE. Our study did not find statistically significant differences in the development of AE between diseases;however, they will continue to be reported and the number of patients in the registry will increase.References[1] Sterba,Y.et al. Curr Rheumatol Rep 2016;18,45[2] Fuhlbrigge RC, et al. 2021;47(4):531-543.Table 1.Baseline CharacteristicsBaseline characteristics (n = 45)n%Female, n(%)3168.9Age, media (SD)13.3 (±3.6)Index Body Mass, media (SD)19.6 (±4.9)Dx n(%)n %- JIA25 55.6- SLE9 20- PM/DM2 4.4- Uveitis5 11.1- Hidradenitis2 4.4- Systemic sclerosis1 2.2- CINCA1 2.2Disease duration(years) media (IQR)4.67±2.1Current treatment n(%)n %- Infliximab1 2.2- Adalimumab17 37.8- Rituximab15 33.3- Abatacept1 2.2- Tocilizumab10 22.2- Canakinumab1 2.2Treatment duration (months) median (IQR)4.5 (0.56 – 36.9)Treatment suspension, n(%)15 (33.2)Months to suspension, median (IQR)0.66 (0.46 – 1)Discontinue cause, n(%)n %- Inefficacy1 6.6- Remission1 6.6- Side effects4 26.6- Others5 33.3- Unknown4 26.6Steroids use, n(%):21 46.7Steroids dose (mg), median (IQR)10 5 – 25DMARDs use n(%):37 82.2AE, n(%):15 33.3By disease:AE TypeInfectionAllergyNeutropeniaOtherChi2JIA31230.95SLE1101Uveitis3000Acknowledgements:NIL.Disclosure of InterestsSamara Mendieta: None declare , Alfonso Torres: None declared, Fedra Irazoque-Palazuelos: None declared, Sandra Sicsik: None declared, Iris Jazmin Colunga-Pedraza: None declared, Daniel Xavier Xibille Friedmann: None declared, Deshire Alpizar-Rodriguez Employee of: Scientific advisor in GSK-Mexico, VIJAYA RIVERA TERAN: None declared.

Machine Learning Applied to COVID-19: A Review of the Initial Pandemic Period

Diagnostic and decision-making processes in the 2019 Coronavirus treatment have combined new standards using patient chest images, clinical and laboratory data. This work presents a systematic review aimed at studying the Artificial Intelligence (AI) approaches to the patients' diagnosis or evolution with Coronavirus 2019. Five electronic databases were searched, from December 2019 to October 2020, considering the beginning of the pandemic when there was no vaccine influencing the exploration of Artificial Intelligence-based techniques. The first search collected 839 papers. Next, the s were reviewed, and 138 remained after the inclusion/exclusion criteria was performed. After thorough reading and review by a second group of reviewers, 64 met the study objectives. These papers were carefully analyzed to identify the AI techniques used to interpret the images, clinical and laboratory data, considering a distribution regarding two variables: (i) diagnosis or outcome and (ii) the type of data: clinical, laboratory, or imaging (chest computed tomography, chest X-ray, or ultrasound). The data type most used was chest CT scans, followed by chest X-ray. The chest CT scan was the only data type that was used for diagnosis, outcome, or both. A few works combine Clinical and Laboratory data, and the most used laboratory tests were C-reactive protein. AI techniques have been increasingly explored in medical image annotation to overcome the need for specialized manual work. In this context, 25 machine learning (ML) techniques with a highest frequency of usage were identified, ranging from the most classic ones, such as Logistic Regression, to the most current ones, such as those that explore Deep Learning. Most imaging works explored convolutional neural networks (CNN), such as VGG and Resnet. Then transfer learning which stands out among the techniques related to deep learning has the second highest frequency of use. In general, classification tasks adopted two or three datasets. COVID-19 related data is present in all papers, while pneumonia is the most common non-COVID-19 class among them.

Outcomes of Sars-Cov-2 Infection in Patients with Anca Associated Vasculitis. Data from the National Sar-Covid Registry

Objectives: To describe the clinical characteristics and outcomes of SARSCoV-2 infection in patients with systemic vasculitis. Method(s): Observational, multicenter, cross-sectional analytical study in patients 18 or older diagnosed with systemic vasculitis with confirmed SARSCoV-2 infection (RT-PCR or serology) included in the SAR-COVID registry. Patients were evaluated from July 2020 to February 2022. Patients diagnosed with ANCA-associated vasculitis (AAV), other systemic vasculitides (Giant cell arteritis, Takayasu), and a control group of patients with other rheumatological diseases matched by age, sex, comorbidities, and date of SARS-CoV-2 infection. The survival curve of the groups was studied by Kaplan-Meier and compared through the Log-Rank Test. A Cox regression model will be performed to adjust survival for different variables (sex, age, treatments for underlying disease, treatments for viral infection, smoking, obesity, d-dimer level, and disease activity). Result(s): A total of 282 out of 2694 patients in the SAR-COVID registry were included, 57.4%women with a mean age of 55.7 years (SD 14.1). Fifty-four patients in the AAV group, 32 in the other vasculitis group, and 196 controls were studied. Hospitalization was required in 53.7% of the AAV group, 37.5% in other vasculitides, and 26.2% in the control group. 5.6% of patients in the control group presented acute respiratory distress syndrome (ARDS), 15.6% in the other vasculitis group, and 22.2% in the AAV group (p alpha 0.001). Complete recovery was observed in 82.3% of patients in the control group, 75%in the other vasculitis group, and 63%in the AAV group.We observed that 5.7% of the patients in the control group died from COVID-19, 9.4%from other vasculitides, and 27.8% in the AAV group (p alpha 0.001). We found a lower survival in the AAV group compared to the control group (p alpha 0.005). In the multivariate Cox regression model, older age (HR:1.05 IC95%1.01-1.09 p = 0.01), BMI > 40 (HR:13.2 IC95% 2.1-83.2 p = 0.01), and high activity of the underlying disease (HR:16 95% CI 3.7-69.4 p alpha 0.005) were associated with lower survival. Conclusion(s): In conclusion, patients diagnosed with AAV presented a worse disease course during SARS-CoV-2 infection with a more frequent requirement for invasive mechanical ventilation. Likewise, these patients showed lower survival compared to patients with other autoimmune diseases.

Noninvasive Mechanical Ventilation and Conventional Oxygen Therapy

COVID-19 pneumonia often presents with severely impaired oxygenation. In patients presenting with hypoxemic acute respiratory failure (ARF), one of the most important goals is to avoid invasive mechanical ventilation. Therefore, in this chapter, we will review the current evidence and rationale for using noninvasive oxygenation and ventilation strategies in patients presenting with COVID-19 and hypoxemic ARF. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Derivation and validation of clinical phenotypes and associated treatment responses in critically ill COVID-19 patients

Introduction: Due to variability in the host response, a uniform treatment strategy for severe COVID-19 may be inadequate. We applied unsupervised clustering methods to large cohorts of COVID-19 ICU patients to derive and validate clinical phenotypes, and to explore treatment responses in these phenotypes. Method(s): Phenotypes were derived in 13.279 critically ill COVID-19 patients admitted to 82 Dutch ICUs from September 2020 to February 2022. Twenty-one features were selected from clinical characteristics measured within 24 h after ICU admission. Phenotypes were assigned using consensus k means clustering. External validation was performed in 6225 critically ill COVID-19 patients admitted to 55 Spanish ICUs from February 2020 to December 2021. Individual patient data on corticosteroids therapy enabled us to investigate phenotype-specific responses in this cohort. Result(s): Three distinct clinical phenotypes were derived (Fig. 1A). Patients with phenotype 1 (43%) were younger, had lower APACHE IV scores, higher BMI as well as a lower P/F ratio and 90-day in-hospital mortality (18%, Fig. 1A). Phenotype 2 patients (37%) were older and had slightly higher APACHE IV scores compared with phenotype 1, a lower BMI, and higher mortality compared to phenotype 1 (24%, p = 2.95e-07). Phenotype 3 (20%) included the oldest patients with the most comorbidities and highest APACHE IV scores, severe renal and metabolic impairment, and the worst outcome (47% mortality, p = 6.6e-16 and p = 6.6e-16 versus phenotypes 1 and 2, respectively). Phenotype distribution and outcome were very similar in the validation cohort (Fig. 1B). This cohort also revealed that corticosteroid therapy only benefited phenotype 3 (65% vs. 54% mortality, p = 2.5e-03, Fig. 1C). Conclusion(s): COVID-19 ICU phenotypes based on clinical data are related to outcome and treatment responses. This can inform treatment decisions as well as randomized trials employing precision medicine approaches.

COVID-19: Pandemic in Ecuador: a health disparities perspective.

BACKGROUND: The global COVID-19 pandemic initiated in Ecuador with the patient zero in February 2020 and since more than 40,000 persons have been tested positive to the virus, leaving some 3,500 deceased, while approximately about 10,500 persons above annual average numbers died within March to May. A strict lockdown was applied by mid-March, which resulted to a severe economic crisis in the country. Although during the lockdown. OBJECTIVE: Our study postulates, that persons who are most likely to be infected during such secondary wave will be people who have already health issues to which we count besides the known ones, especially those who are already suffer by the distribution of volcanic ashes, as such pyroclastic material is known to affect lunges and thyroids. occurred a notable decrease in the number of new cases, the spread of the infection was already massive, untechnical, political and economic decisions will certainly lead to continuous wave of infections for months. METHODS: A descriptive ecological study of information related to COVID-19 infection at a national level using official data from the Minister of Public Health and volcanic ash fall by geographical area in Ecuador. RESULTS: The mortality rate per canton indicated that those with lower attack rates are the ones with highest mortality rate. For instance, Portovelo (21.3/100,000), Playas (18.4/100,000), Santa Rosa (15.8/100,000), Suscal (15.3/100,000) and Penipe (14.3/100,000) reported the highest mortality rate per 100,000 people. The main distribution of such volcanic material is within the central to northern area of the Highlands and Inter-Andean Valley of Ecuador, due to the analysis of some 7394 satellite images of the last 21 years. CONCLUSIONS: We conclude that areas with high vulnerabilities are also most susceptible to develop COVID-19. Such areas with their respective populations will be affected above average and shall be protected in particular within the presently starting during possible second wave of infection.

Proteomic determinants of disease, mortality and sequelae in COVID-19 patients requiring invasive mechanical ventilation

Introduction: The molecular mechanisms linked to the pathology of severe COVID-19 and its outcomes are poorly described. Aim(s): To analyze the proteomic profile of bronchial aspirates (BAS) samples from critically ill COVID-19 patients in order to identify factors associated with the disease and its prognosis. Method(s): Multicenter study including 74 critically ill non-COVID-19 and COVID-19 patients. BAS was obtained by bronchoaspiration after invasive mechanical ventilation (IMV) initiation. Proximity extension assay (PEA) technology was used for proteomic profiling. Random forest (RF) statistical models were used to predict the variable importance. Result(s): After adjusting for confounding factors, CST5, NADK, SRPK2 and TGF-alpha showed differences between COVID-19 and non-COVID-19 patients. Reduced levels of ENTPD2 and PTN were observed in non-survivors, even after adjustment. AGR2, NQO2, IL-1alpha, OSM and TRAIL, were the top five strongest predictors for ICU mortality and were used to build a prediction model. PTN (HR=4.00) ENTPD2 (HR=2.14) and the prediction model (HR=6.25) were associated with higher risk of death. In survivors, FCRL1, NTF4 and THOP1 correlated with lung function (DLCO levels) 3-months after hospital discharge. Similar findings were observed for Flt3L and THOP1 and radiological features (TSS). The proteins identified are expressed in immune and non-immune lung cells. A poor control of viral infectivity and an inappropriate reparative response seems to be linked to the disease and fatal outcomes, respectively. Conclusion(s): In critically ill COVID-19 patients, specific proteomic profiles are associated with the pathology, mortality and lung sequelae.

One year overview of follow-up in a post-covid consultation of critical patients with covid-19

Introduction: Long-term clinical management and evolution of a cohort of critical COVID-19 survivors has not been well described. Method(s): We report a prospective observational study of COVID-19 patients admitted to ICU between March to August 2020. The follow-up comprised symptoms, pulmonary function test, 6-minute walking test (6MWT, and chest computed tomography (CT). Additionally, questionnaires to evaluate the prevalence of post-covid19 syndrome was performed at 1-year. Result(s) and Conclusion(s): A total of 181 patients were admitted at the ICU during the study period. They were predominantly middle-aged (median [IQR] of 61 [52;67] years old) male (66.9%) with a median of ICU stay of 9 (5- 24.2) days. Twenty percent of them died in the hospital and 39 were not able to be included, a final cohort of 105 patients initiated the follow-up. At one year, 32.2% persist with respiratory alterations and needed to continue the follow-up. 10% still had severe lung diffusing (DLCO) involvement (<60%) and 53.7% had a fibrotic pattern on CT. Moreover, patients had a mean (SD) of symptoms of 5.77 (4.66) and 61.3% meet criteria for post-covid syndrome at one-year. During the follow-up 46 patients were discharge and 16 were transfer to others consultations. Other conditions such as emphysema (21.6%), COPD (8.2%), severe neurocognitive disorders (4.1%) and lung cancer (1%) have been identified. A high use of healthcare resources is observed in the first year of these critical survivors after hospital discharge.

Proteomic profiling of severe lung diffusion impairment in the recovery stage of COVID-19-induced ARDS

Background: Around 80% of patients who developed COVID-19-driven ARDS present lung ailment. There is a lack of knowledge of the mechanisms that mediate the pulmonary outcomes. Aim(s): To characterize the factors linked to diffusion impairment in survivors of severe COVID-19. Method(s): Prospective cohort study including 87 COVID-19-induced ARDS survivors. A complete pulmonary evaluation was performed 3 months after hospital discharge. 364 proteins were quantified using the proximity extension assay (PEA). Partial least square-discriminant analysis (PLS-DA) and random forest (RF) were used for multivariable analyses. Result(s): Moderate to severe diffusion impairment (DLCO<60% predicted) was observed in the 30% of the cohort. 15 proteins were differentially detected [false discovery rate (FDR)<0.05] in the univariate analysis. Pleiotrophin showed the highest differences (fold change=2.22 and FDR=0.001). In continuous analysis, proteins were inversely and independently associated with DLCO, and in some cases showed a robust dose-response relationship. PLS-DA and RF identified proteomic profiles related to the severity of diffusion capacity. Clusters identified were enriched in mediators of cell proliferation and differentiation, tissue remodeling, angiogenesis, coagulation, inflammation, immune response and fibrosis. Proteins are expressed in immune and non-immune lung cells. Conclusion(s): In survivors of COVID-19-driven ARDS, lung dysfunction is linked to plasma factors involved in injury and repair mechanisms. The host proteomic profile provides a novel understanding of post-acute sequelae and may be source of therapeutic strategies and biomarkers.

Identification of highly immunogenic epitopes in the SARS-CoV-2 Spike protein to produce monoclonal antibodies

Background: In outpatients, monoclonal antibodies to Spike protein reduce viral load and improve outcomes, with a greater effect in serum antibody-negative at baseline. The aim of this study was to find epitope candidates to produce neutralizing monoclonal antibodies (mAb) for COVID-19 treatment. Method(s): IgG COVID-19 patients (N=500) against SARS-CoV-2 was confirmed. Epitope mapping was performed by Luminex technology. A computational pipeline based in predictive models was designed to predict S protein epitopes most likely to be recognized by mAb from COVID-19 convalescent patients. Result(s): Validation Screening: 29 epitopes of the SARS-CoV-2 S protein were predicted by our pipeline and included in the Luminex panel. 40 serum samples from convalescent COVID-19 patients and 126 pre-pandemia negative controls were included in the validation screening. Epitope mapping: 500 serum samples were tested against the 8 epitopes selected in the validation screening. The two epitopes with the highest IgG of participants above the seropositivity cut-offs were selected. The two most immunogenic epitopes were screened in phage library containing 109 clones of antibodies anti-SARS-CoV-2 to produce mAbs by phage display technology. Conclusion(s): The two epitopes with the highest IgG reactivity validated against serum samples from 500 COVID-19 convalescent patients and phage library are good candidates for the production of new neutralizing mAbs against SARS-CoV-2 S protein.

Risk factors for mortality in COPD patients with COVID19 admitted to Intensive Care Unit

Background and aim: Patients with Chronic obstructive pulmonary disease (COPD) and COVID-19 have increased risk of hospitalization and Instensive Care Unit (ICU) admission (1). Aims and objectives: To indentify risk factors for intrahospital mortality in COPD patients with COVID-19 admitted to Spanish ICUs. Method(s): Demographic and clinical data during ICU admission were recorded using REDCap on all patients hospitalized for COVID-19 in 70 Spanish ICUs (2). We described the baseline clinical characteristics of COPD compared to other chronic respiratory disease (CRD) and to the overall population. We identified the risk factors for intrahospital mortality of COPD patients receiving invasive mechanical ventilation (IMV) and for those COPD receiving noninvasive respiratory support (NIRS). Result(s): Two hundred and sixty-eight ICU patients (5%) had COPD out of 5196 included. No differences were found between COPD, CRD or the overall population in the rates of IMV (76-78%) vs NIRS (22-24%). COPD intrahospital mortality was much higher in the IMV subgroup (58%). Independent risk factors for intrahospital mortality in the COPD+IMV or COPD+NIRS were: age and chronic Kidney disease or hypertension, respectively. Previous NIRS in COPD+IMV group was protective for intrahospital mortality (Figure). Conclusion(s): New strategies are needed to reduce the high intrahospital and 90-days mortality of COPD COVID-19 patients admitted to ICU.

Administration in private higher education institutions through virtual platforms in Honduras

The main goal of this research was to analyze the education in universities through virtual platforms in Honduras caused by COVID.19. A quantitative approach was used, with an exploratory-descriptive research level;in addition, questionnaires were used with a reliability level of 0.847 Cronbach's Alpha. The sample consisted of five private universities represented by sixty teachers. It was found that a fast adaptation to virtuality was achieved, which reflected a high level of satisfaction of the teachers. It is concluded that private institutions at the higher education develop new strategies to maintain the fluency of classes by having programs and platforms for virtual teaching

Risk factors associated with mortality among elderly patients with COVID-19: Data from 55 intensive care units in Spain.

INTRODUCTION AND OBJECTIVES: Critically-ill elderly ICU patients with COVID-19 have poor outcomes. We aimed to compare the rates of in-hospital mortality between non-elderly and elderly critically-ill COVID-19 ventilated patients, as well as to analyze the characteristics, secondary outcomes and independent risk factors associated with in-hospital mortality of elderly ventilated patients. PATIENTS AND METHODS: We conducted a multicentre, observational cohort study including consecutive critically-ill patients admitted to 55 Spanish ICUs due to severe COVID-19 requiring mechanical ventilation (non-invasive respiratory support [NIRS; include non-invasive mechanical ventilation and high-flow nasal cannula] and invasive mechanical ventilation [IMV]) between February 2020 and October 2021. RESULTS: Out of 5,090 critically-ill ventilated patients, 1,525 (27%) were aged ≥70 years (554 [36%] received NIRS and 971 [64%] received IMV. In the elderly group, median age was 74 years (interquartile range 72-77) and 68% were male. Overall in-hospital mortality was 31% (23% in patients <70 years and 50% in those ≥70 years; p<0.001). In-hospital mortality in the group ≥70 years significantly varied according to the modality of ventilation (40% in NIRS vs. 55% in IMV group; p<0.001). Factors independently associated with in-hospital mortality in elderly ventilated patients were age (sHR 1.07 [95%CI 1.05-1.10], p<0.001); previous admission within the last 30 days (sHR 1.40 [95%CI 1.04-1.89], p = 0.027); chronic heart disease (sHR 1.21 [95%CI 1.01-1.44], p = 0.041); chronic renal failure (sHR 1.43 [95%CI 1.12- 1.82], p = 0.005); platelet count (sHR 0.98 [95% CI 0.98-0.99], p<0.001); IMV at ICU admission (sHR 1.41 [95% CI 1.16- 1.73], p<0.001); and systemic steroids (sHR 0.61 [95%CI 0.48- 0.77], p<0.001). CONCLUSIONS: Amongst critically-ill COVID-19 ventilated patients, those aged ≥70 years presented significantly higher rates of in-hospital mortality than younger patients. Increasing age, previous admission within the last 30 days, chronic heart disease, chronic renal failure, platelet count, IMV at ICU admission and systemic steroids (protective) all comprised independent factors for in-hospital mortality in elderly patients.

Comparative analysis of risk factors for COVID-19 mortality before, during and after the vaccination programme in Mexico.

OBJECTIVES: The purpose of this study was to compare case fatality rates (CFRs) and odds for mortality by risk factors of patients with COVID-19 in Mexico, before, during and after the implementation of the national COVID-19 vaccination programme. STUDY DESIGN: A large database including COVID-19 monitoring cases was used to perform an observational retrospective study. METHODS: The Chi-squared test and multivariate logistic regression analyses were applied to data from COVID-19-positive patients in Mexico. Data were analysed over 3 years, 2020, 2021 and 2022, corresponding with pre-, during and post-vaccination periods. The unadjusted odds ratios and 95% confidence interval were used to estimate the risk factors for COVID-19 mortality in each of the years. RESULTS: Statistically significant differences in CFR and odds ratio were found in the studied years, favouring postvaccination period. Significant changes in CFR by age, sex and main comorbidities indicated changes in the epidemic dynamics after the implementation of the COVID-19 vaccination campaign. The likelihood of death increased for hospitalised cases and for patients who were middle-aged or older in 2021 and 2022, whereas the odds of death associated with sex and comorbidities remained similar or reduced over the 3 years. CONCLUSIONS: Implementation of the COVID-19 vaccination programme during 2021 showed positive consequences on CFR. The increased odds of dying in hospitalised patients are likely to be due to the unvaccinated proportion of patients.

Outdoor recreation alters terrestrial vertebrate scavenger assemblage and carrion removal in a protected Mediterranean wetland

Outdoor recreation has increased in recent decades, with an intensification after the COVID-19 lockdown. Previous studies have shown that disturbances from this activity may affect species behaviour and fitness, but its effect on ecological processes has been overlooked. Here, we test the impact of outdoor recreation on terrestrial vertebrate scavenger assemblage and scavenging patterns in El Hondo Natural Park, a Mediterranean wetland located in south-eastern Spain. We placed 185 carcasses monitored with camera traps between February 2020 and May 2021 in two areas: 'public access area', where visitors can freely access and carry out outdoor recreation, and 'restricted area', where visitors are not allowed. Our results showed that outdoor recreation altered the scavenger assemblage composition, especially affecting large species such as raptors. Non-native species scavenged almost four times more often on carcasses in public access areas than in the restricted areas, showing that human activities promote the presence of non-native species. Furthermore, vertebrates completely consumed 68.2% of the carcasses in the restricted area, decreasing to 46.7% in the public access area. In the restricted area, consumption time was shorter (111.8 vs. 157.5 h) and consumed biomass by vertebrate scavengers was larger (73.9 vs. 52.2%) than in public access area, evidencing that outdoor recreation also affects scavenging processes. Our study shows that outdoor recreation profoundly alters not only the scavenger assemblage but also key ecological processes such as carrion removal. This highlights the urgency of regulating tourism and maintaining restricted areas to preserve biodiversity and ecological processes, especially in highly anthropized landscapes.

Risks of adverse outcomes in COVID-19 patients and vaccination status in a secondary hospital in Spain

Introduction: In December 2020, vaccination against SARS-CoV-2 started in Spain. Until March 2022, 91.1% of the target population was vaccinated. The objective of the study is to describe the characteristics of patients with SARS-CoV-2 infection, the risk of serious outcomes and their vaccination status. Material and methods: Retrospective longitudinal analytical observational study. Demographic characteristics and outcomes of COVID-19 infections and vaccination history from 01/01/2021–08/10/2021 were collected from electronic medical records and the Unified Vaccination Registry. Data analysis was performed with Excel and Stata 16. Results: 4161 COVID-19 cases were detected;of which 185 (4.5%) had received a complete vaccination schedule. The most affected age group was 80–89 years (34.1%). 1697 patients were hospitalized, of whom 78 (4.6%) had been vaccinated against SARS-CoV-2. No patient admitted to the ICU had a history of vaccination. The mean hospitalization time in unvaccinated patients was 11 days (95% CI -41.54–63.54) compared to 8.5 days (95% CI 7.04–9.96) in vaccinated patients. The relative risk of hospitalization in vaccinated patients compared to unvaccinated patients for the age group 40 to 59 years was 0.29 (95% CI 0.11–0.72) and 0.77 (95% CI 0.67–0). 0.90) for people over 60 years of age. Conclusions: The risk of hospitalization and death was lower in vaccinated patients compared to unvaccinated patients in the age groups 40–59 and older than 60 years. This finding supports current clinical evidence.