Association of ambient air pollution and pesticide mixtures on respiratory inflammatory markers in agricultural communities.

Air pollution exposure is associated with adverse respiratory health outcomes. Evidence from occupational and community-based studies also suggests agricultural pesticides have negative health impacts on respiratory health. Although populations are exposed to multiple inhalation hazards simultaneously, multidomain mixtures (e.g. environmental and chemical pollutants of different classes) are rarely studied. We investigated the association of ambient air pollution-pesticide exposure mixtures with urinary leukotriene E4 (LTE4), a respiratory inflammation biomarker, for 75 participants in four Central California communities over two seasons. Exposures included three criteria air pollutants estimated via the Community Multiscale Air Quality model (fine particulate matter, ozone, and nitrogen dioxide) and urinary metabolites of organophosphate (OP) pesticides (total dialkyl phosphates (DAPs), total diethyl phosphates (DE), and total dimethyl phosphates (DM)). We implemented multiple linear regression models to examine associations in single pollutant models adjusted for age, sex, asthma status, occupational status, household member occupational status, temperature, and relative humidity, and evaluated whether associations changed seasonally. We then implemented Bayesian kernel machine regression (BKMR) to analyse these criteria air pollutants, DE, and DM as a mixture. Our multiple linear regression models indicated an interquartile range (IQR) increase in total DAPs was associated with an increase in urinary LTE4 in winter (ß: 0.04, 95% CI: [0.01, 0.07]). Similarly, an IQR increase in total DM was associated with an increase in urinary LTE4 in winter (ß:0.03, 95% CI: [0.004, 0.06]). Confidence intervals for all criteria air pollutant effect estimates included the null value. BKMR analysis revealed potential non-linear interactions between exposures in our air pollution-pesticide mixture, but all confidence intervals contained the null value. Our analysis demonstrated a positive association between OP pesticide metabolites and urinary LTE4 in a low asthma prevalence population and adds to the limited research on the joint effects of ambient air pollution and pesticides mixtures on respiratory health.

THE ROLE OF IMMUNOMODULATORY THERAPY WITH OXIRIS IN COVID 19 WITH RENAL FAILURE AND IMMUNE DYSFUNCTION.

INTRODUCTION: The main objective of this study is to evaluate the impact of hemoadsorption on the elimination of inflammatory mediators. METHODS: A prospective, bicenter, observational cohort study was conducted between March 2020 and February 2022 to explore the immunomodulatory response, demographic and clinical characteristics of individuals with COVID-19 admitted to the ICU with severe acute respiratory failure and in need of CRRT with Oxiris® with or without AKI. RESULTS: 64 patients were analyzed. Statistically significant differences were observed between exposed and unexposed groups, regarding levels of D-dimer -15614 (24848.9) vs -4136.5(9913.47) (p .031, d:1.59, 95% CI -21830, -1126). An increase in PCT was observed 0.47(2.08) vs -0.75(2.3) (p .044 95% CI 0.03,2.44). No differences were found in a decrease in CRP -4.21(7.29) vs -1.6(9.02) (p .22) nor in the rest of inflammatory parameters fibrinogen, IL-6, ferritin, lymphocytes, and neutrophils. Subgroup analysis in patients exposed to therapy also showed a significant decrease in D-Dimer of 55% from baseline; 6000 (1984.5-277750) pre-therapy vs 2700 (2119.5-6145) (95% CI -23000, -2489) post-therapy with a strong effect size (p .001, d:0.65). CONCLUSION: The hemoadsorptive therapy in COVID 19 was associated with a significant decrease in D-dimer parameters without showing decreases in the rest of the clinical, inflammatory parameters and severity scales analyzed.

Effects of PEEP on intracranial pressure in patients with acute brain injury: An observational, prospective and multicenter study.

OBJECTIVE: To analyze the impact of positive end-expiratory pressure (PEEP) changes on intracranial pressure (ICP) dynamics in patients with acute brain injury (ABI). DESIGN: Observational, prospective and multicenter study (PEEP-PIC study). SETTING: Seventeen intensive care units in Spain. PATIENTS: Neurocritically ill patients who underwent invasive neuromonitorization from November 2017 to June 2018. INTERVENTIONS: Baseline ventilatory, hemodynamic and neuromonitoring variables were collected immediately before PEEP changes and during the following 30 min. MAIN VARIABLES OF INTEREST: PEEP and ICP changes. RESULTS: One-hundred and nine patients were included. Mean age was 52.68 (15.34) years, male 71 (65.13%). Traumatic brain injury was the cause of ABI in 54 (49.54%) patients. Length of mechanical ventilation was 16.52 (9.23) days. In-hospital mortality was 21.1%. PEEP increases (mean 6.24-9.10 cmH2O) resulted in ICP increase from 10.4 to 11.39 mmHg, P < .001, without changes in cerebral perfusion pressure (CPP) (P = .548). PEEP decreases (mean 8.96 to 6.53 cmH2O) resulted in ICP decrease from 10.5 to 9.62 mmHg (P = .052), without changes in CPP (P = .762). Significant correlations were established between the increase of ICP and the delta PEEP (R = 0.28, P < .001), delta driving pressure (R = 0.15, P = .038) and delta compliance (R = -0.14, P = .052). ICP increment was higher in patients with lower baseline ICP. CONCLUSIONS: PEEP changes were not associated with clinically relevant modifications in ICP values in ABI patients. The magnitude of the change in ICP after PEEP increase was correlated with the delta of PEEP, the delta driving pressure and the delta compliance.

Age and growth of the blue shark Prionace glauca (Linnaeus, 1758) in the Ecuadorian Pacific: Bayesian multi-models.

The blue shark Prionace glauca plays a critical role as a predator in marine ecosystems but is threatened by by-catch. To obtain more precise biological data, a Bayesian approach was used, and 536 vertebrae samples collected during 1 year at the landing stage called "Playita Mía" Manta, Ecuador, were analysed. The objective was to estimate the age and growth parameters of the species. The size of the specimens varied between 116 and 310 cm in total length (TL). Using a Bayesian approach based on the Markov Chain Monte Carlo (MCMC) method, growth parameters were evaluated. The von Bertalanffy model was the one that best fitted the data and provided more adequate estimates (females: L ∞ = 325.50 cm, L 0 = 53.23 cm, and k = 0.12 years; males: L ∞ = 331.47 cm, L 0 = 51.59 cm, k = 0.12 years -1; combined sexes: L ∞ = 329.65 cm, L 0 = 53.64 cm, k = 0.11 year-1). The results indicated that females and males have a similar growth, and that the species has a slow growth. Further studies using multi-model Bayesian approaches and covering a broader range of sizes in the Pacific Ocean are suggested. These studies will provide crucial information for the management and conservation of this species.

Current perspectives on the use of artificial intelligence in critical patient safety.

Intensive Care Units (ICUs) have undergone enhancements in patient safety, and artificial intelligence (AI) emerges as a disruptive technology offering novel opportunities. While the published evidence is limited and presents methodological issues, certain areas show promise, such as decision support systems, detection of adverse events, and prescription error identification. The application of AI in safety may pursue predictive or diagnostic objectives. Implementing AI-based systems necessitates procedures to ensure secure assistance, addressing challenges including trust in such systems, biases, data quality, scalability, and ethical and confidentiality considerations. The development and application of AI demand thorough testing, encompassing retrospective data assessments, real-time validation with prospective cohorts, and efficacy demonstration in clinical trials. Algorithmic transparency and explainability are essential, with active involvement of clinical professionals being crucial in the implementation process.

Evaluation of mango residues to produce hyaluronic acid by Streptococcus zooepidemicus.

Mango processing generates significant amounts of residues (35-65%) that may represent environmental problems owed to improper disposal. The use of mango byproducts as substrates to produce hyaluronic acid (HA) is an attractive alternative to reduce the cost of substrate. In this study, we evaluated the potential of hydrolyzates from mango peels and seeds to produce HA by Streptococcus equi. subsp. zooepidemicus. The physicochemical characterization of mango residues showed that the seeds contain a higher amount of holocellulose (cellulose and hemicellulose), which amounts 54.2% (w/w) whereas it only represents 15.5% (w/w) in the peels. Mango peels, however, are composed mainly of hot water-extractives (62% w/w, that include sucrose, fructose, glucose and organic acids). A higher concentration of monosaccharides (39.8 g/L) was obtained from the enzymatic hydrolysis (with Macerex) of peels as compared to seeds (24.8 g/L with Celuzyme). From mango peels, hydrolyzates were obtained 0.6 g/L HA, while 0.9 g/L HA were obtained with hydrolyzates from mango seeds. These results demonstrate that mango byproducts have the potential to be used for production of HA.

¿Podrían ayudarnos los algoritmos de machine learning en la predicción de hemorragia masiva a nivel prehospitalario? / Could machine learning algorithms help us in predicting massive hemorrhage at the prehospital level?

Objetivo: Comparación de la capacidad predictiva de diferentes algoritmos de machine learning (AML) respecto a escalas tradicionales de predicción de hemorragia masiva en pacientes con enfermedad traumática grave (ETG). Diseño: Sobre una base de datos de una cohorte retrospectiva con variables clínicas prehospitalarias y de resultado de hemorragia masiva se realizó un tratamiento de la base de datos para poder aplicar los AML, obteniéndose un conjunto total de 473 pacientes (80% entrenamiento, 20% validación). Para la modelización se realizó imputación proporcional y validación cruzada. El poder predictivo se evaluó con la métrica ROC y la importancia de las variables mediante los valores Shapley. Ámbito: Atención extrahospitalaria del paciente con ETG. Pacientes: Pacientes con ETG atendidos en el medio extrahospitalario por un servicio médico extrahospitalario desde enero de 2010 hasta diciembre de 2015 y trasladados a un centro de trauma en Madrid. Intervenciones: Ninguna. Variables de interés principales: Obtención y comparación de la métrica ROC de 4 AML: random forest, support vector machine, gradient boosting machine y neural network con los resultados obtenidos con escalas tradicionales de predicción. Resultados: Los diferentes AML alcanzaron valores ROC superiores al 0,85, teniendo medianas cercanas a 0,98. No encontramos diferencias significativas entre los AML. Cada AML ofrece un conjunto de variables diferentes, pero con predominancia de las variables hemodinámicas, de reanimación y de deterioro neurológico. Conclusiones: Los AML podrían superar a las escalas tradicionales de predicción en la predicción de hemorragia masiva. (AU)

Objective: Comparison of the predictive ability of various machine learning algorithms (MLA) versus traditional prediction scales for massive hemorrhage in patients with severe traumatic injury (ETG). Design: On a database of a retrospective cohort with prehospital clinical variables and massive hemorrhage outcome, a treatment of the database was performed to be able to apply the different MLA, obtaining a total set of 473 patients (80% training and 20% validation). For modeling, proportional imputation and cross validation were performed. The predictive power was evaluated with the ROC metric and the importance of the variables using the Shapley values. Setting: Out-of-hospital care of patients with ETG. Participants: Patients with ETG treated out-of-hospital by a prehospital medical service from January 2010 to December 2015 and transferred to a trauma center in Madrid. Interventions: None. Main variables of interest: Obtaining and comparing the ROC curve metric of 4 MLAs: random forest, support vector machine, gradient boosting machine and neural network with the results obtained with traditional prediction scales. Results: The different MLA reached ROC values higher than 0.85, having medians close to 0.98. We found no significant differences between MLAs. Each MLA offers a different set of more important variables with a predominance of hemodynamic, resuscitation variables and neurological impairment. Conclusions: MLA may be helpful in patients with massive hemorrhage by outperforming traditional prediction scales. (AU)

Could machine learning algorithms help us predict massive bleeding at prehospital level?

OBJECTIVE: Comparison of the predictive ability of various machine learning algorithms (MLA) versus traditional prediction scales (TPS) for massive hemorrhage (MH) in patients with severe traumatic injury (STI). DESIGN: On a database of a retrospective cohort with prehospital clinical variables and MH outcome, a treatment of the database was performed to be able to apply the different AML, obtaining a total set of 473 patients (80% training, 20% validation). For modeling, proportional imputation and cross validation were performed. The predictive power was evaluated with the ROC metric and the importance of the variables using the Shapley values. SETTING: Out-of-hospital care of patients with STI. PARTICIPANTS: Patients with STI treated out-of-hospital by a out-of-hospital medical service from January 2010 to December 2015 and transferred to a trauma center in Madrid. INTERVENTIONS: None. MAIN VARIABLES OF INTEREST: Obtaining and comparing the "Receiver Operating Characteristic curve" (ROC curve) metric of four MLAs: "random forest" (RF), "vector support machine" (SVM), "gradient boosting machine" (GBM) and "neural network" (NN) with the results obtained with TPS. RESULTS: The different AML reached ROC values higher than 0.85, having medians close to 0.98. We found no significant differences between AMLs. Each AML offers a different set of more important variables with a predominance of hemodynamic, resuscitation variables and neurological impairment. CONCLUSIONS: MLA may be helpful in patients with HM by outperforming TPS.

Retos de hoy en Medicina Intensiva: diversidad, equidad e inclusión. Posicionamiento de género de la Sociedad Española de Medicina Intensiva, Crítica y Unidades Coronarias (SEMICYUC) / Challenges in intensive medicine: Diversity, equity and inclusion. Gender statement of the Spanish Society of Intensive and Critical Medicine and Coronary Units (SEMICYUC)

El género es un determinante social que impacta en el ámbito de la salud y genera desigualdades a todos los niveles; repercute en los pacientes y en la patología crítica, en los profesionales y en el desarrollo de la carrera profesional y las sociedades científicas, desde una perspectiva de justicia social. Todas las sociedades científicas internacionales de medicina intensiva comprometidas en aportar una perspectiva de género coinciden en la necesidad de un compromiso formal por parte de las instituciones. La Sociedad de Medicina Intensiva y Unidades Coronarias (SEMICYUC) se compromete a velar por la equidad, la inclusión y la representatividad de sus profesionales y combatir la brecha de género en el ámbito de la medicina intensiva (AU)

Gender is a social determinant that impacts on health and generates inequities at all levels; it has an impact on patients and critical pathology, professionals and professional career development, and scientific societies, from a social justice perspective. All the international scientific societies of Intensive Care Medicine committed to contributing a gender perspective agree on the need for a formal positioning by the institutions. The Society of Intensive Medicine and Coronary Units (SEMICYUC) is committed to ensuring the equity, inclusion and representativeness of its professionals and combating the gender gap in the field of Intensive Medicine (AU)

[Prevalence of persistent hypogammaglobulinemia in patients with autoimmune rheumatic disease who received treatment with Rituximab in a national medical center in Mexico]. / Prevalencia de hipogammaglobulinemia persistente en pacientes con enfermedad autoinmune que reciben rituximab en un centro de referencia nacional en México.

OBJECTIVE: To describe the prevalence of persistent hypogammaglobulinemia in patients receiving Rituximab as a treatment for autoimmune rheumatological diseases. METHODS: A transversal, retrospective and unicentric study, carried out in patients with autoimmune rheumatic diseases who were admitted to the Rheumatology service of the Hospital de Especialidades Dr. Antonio Fraga Mouret, Centro Médico Nacional La Raza, Mexico City, to receive treatment with rituximab between January 2013 and January 2018. Descriptive and inferential statistics of serum levels of immunoglobulins, clinical-demographic characteristics, diagnosis, and treatment received were performed. RESULTS: from 262 patients with autoimmune rheumatological disease who received treatment with Rituximab; We identified 8 patients with persistent hypogammaglobulinemia (6 women and 2 men), this is a prevalence of 3.1%. No associated factors with the development of hypogammaglobulinemia were identified. CONCLUSIONS: Until now, no associated prognostic or predictive factors have been identified with persistent hypogammaglobulinemia. Additional prospective studies are required to understand more precisely the implications of persistent hypogammaglobulinemia in patients with autoimmune diseases.

OBJECTIVO: Determinar la prevalencia de hipogammaglobulinemia persistente en pacientes con enfermedades reumatológicas autoinmunes que reciben rituximab. MÉTODOS: Estudio trasversal, retrospectivo y unicéntrico, emprendido en pacientes con enfermedades reumatológicas autoinmunes, que acudieron a la Consulta externa del servicio de Reumatología del Hospital de Especialidades Dr. Antonio Fraga Mouret, Centro Médico Nacional La Raza, Ciudad de México, entre enero de 2013 y enero de 2018, para recibir tratamiento con rituximab. El análisis de los datos se efectuó con estadística descriptiva e inferencial, para la evaluación de las concentraciones séricas de inmunoglobulinas, características clínico demográficas, diagnóstico y tratamiento. RESULTADOS: Estudio trasversal, retrospectivo y unicéntrico, emprendido en pacientes con enfermedades reumatológicas autoinmunes, que acudieron a la Consulta externa del servicio de Reumatología del Hospital de Especialidades Dr. Antonio Fraga Mouret, Centro Médico Nacional La Raza, Ciudad de México, entre enero de 2013 y enero de 2018, para recibir tratamiento con rituximab. El análisis de los datos se efectuó con estadística descriptiva e inferencial, para la evaluación de las concentraciones séricas de inmunoglobulinas, características clínico demográficas, diagnóstico y tratamiento. CONCLUSIONES: Hasta el momento no se han identificado factores asociados, pronósticos o predictivos, con hipogammaglobulinemia persistente. Se requieren estudios prospectivos adicionales para conocer con mayor precisión las implicaciones de la hipogammaglobulinemia persistente en pacientes con enfermedades autoinmunes.

Challenges in intensive medicine: Diversity, equity and inclusion. Gender statement of the Spanish Society of Intensive and Critical Medicine and Coronary Units (SEMICYUC).

Gender is a social determinant that impacts health and generates inequalities at all levels. It has impacts patients and critical conditions, health professionals and professional career development, and scientific societies from a perspective of social justice. All the International scientific societies of Intensive Care Medicine committed to contributing a gender perspective agree on the institutional need for achieving a formal positioning standpoint. The Spanish Society of Intensive and Critical Medicine and Coronary Units (SEMICYUC) is committed to ensuring the equality, inclusion and representativeness of its health professionals to fight the existing gender gap in the field of Intensive Medicine.

Programa de Mentoría: acompañando tus primeros pasos hacia la excelencia científica / Mentoring Programme: Guiding your first steps towards scientific excellence

El primer Programa de Mentoría de SEMICYUC tiene como objetivo apoyar la carrera investigadora de los miembros más jóvenes de la Sociedad. Como beneficios añadidos está la adquisición de nuevas capacidades de investigación y/o clínicas, incrementar la capacidad de reflexión y fomentar el desarrollo de la próxima generación de líderes en la investigación. Este proyecto no sería posible sin el equipo excepcional de mentores o expertos investigadores dispuestos a emprender el viaje con los jóvenes aprendices. El presente artículo expone las bases de dicho programa, además de proponer futuros cambios en haz de una mejora continua (AU)

SEMICYUC's first Mentoring Programme aims to support the research careers of the Society's youngest members. Added benefits include acquiring new research and/or clinical skills, increasing the ability of critical thought, and fostering the development of the next generation of research leaders. This project would not be possible without the exceptional team of mentors or research experts willing to embark on the journey with the young trainees. This article sets out the foundations of such a programme and proposes future changes for continuous improvement (AU)

Factors affecting urinary organophosphate pesticide metabolite levels among Californian agricultural community members.

Organophosphate (OP) pesticides are widely used in California for agricultural pest and weed control despite their well-documented adverse health effects among infants, children, and adults. We sought to identify factors affecting urinary OP metabolites among families living in high-exposure communities. Our study included 80 children and adults who lived within 61 m (200 ft) of agricultural fields in the Central Valley of California in January and June 2019, which are pesticide non-spraying and spraying seasons, respectively. We collected one urine sample per participant during each visit to measure dialkyl phosphate (DAP) metabolites; these were coupled with in-person surveys to identify health, household, sociodemographic, pesticide exposure, and occupational risk factors. We used a data-driven, best subsets regression approach to identify key factors that influenced urinary DAPs. Participants were mostly Hispanic/Latino(a) (97.5 %), over half were female (57.5 %), and most households reported having a member who worked in agriculture (70.6 %). Among the 149 urine samples suitable for analysis, DAP metabolites were detected in 48.0 % and 40.5 % of samples during January and June, respectively. Total diethyl alkylphosphates (EDE) were only detected in 4.7 % (n = 7) of samples, but total dimethyl alkylphosphates (EDM) were detected in 41.6 % (n = 62) of samples. No differences were observed in urinary DAP levels by visit month or by occupational exposure to pesticides. Best subsets regression identified several individual- and household-level variables that influenced both urinary EDM and total DAPs: the number of years spent living at the current address, household use of chemical products to control mice/rodents, and seasonal employment status. Among adults only, we identified educational attainment (for total DAPs) and age category (for EDM) as significant factors. Our study found consistent urinary DAP metabolites among participants, regardless of spraying season, and identified potential mitigating factors that members of vulnerable populations can implement to protect their health against OP exposure.

Associated Risk Factors and Impact in Clinical Outcomes of Multiorgan Failure in Patients with TBI.

BACKGROUND: Individual extracerebral organ dysfunction is common after severe traumatic brain injury (TBI) and impacts outcomes. However, multiorgan failure (MOF) has received less attention in patients with isolated TBI. Our objective was to analyze the risk factors associated with the development of MOF and its impact in clinical outcomes in patients with TBI. METHODS: This was an observational, prospective, multicenter study using data from a nationwide registry that currently includes 52 intensive care units (ICUs) in Spain (RETRAUCI). Isolated significant TBI was defined as Abbreviated Injury Scale (AIS) ≥ 3 in the head area with no AIS ≥ 3 in any other anatomical area. Multiorgan failure was defined using the Sequential-related Organ Failure Assessment as the alteration of two or more organs with a score of ≥ 3. We analyzed the contribution of MOF to crude and adjusted mortality (age and AIS head) by using logistic regression analysis. A multiple logistic regression analysis was performed to analyze the risk factors associated with the development of MOF in patients with isolated TBI. RESULTS: A total of 9790 patients with trauma were admitted to the participating ICUs. Of them, 2964 (30.2%) had AIS head ≥ 3 and no AIS ≥ 3 in any other anatomical area, and these patients constituted the study cohort. Mean age was 54.7 (19.5) years, 76% of patients were men, and ground-level falls were the main mechanism of injury (49.1%). In-hospital mortality was 22.2%. Up to 185 patients with TBI (6.2%) developed MOF during their ICU stay. Crude and adjusted (age and AIS head) mortality was higher in patients who developed MOF (odds ratio 6.28 [95% confidence interval 4.58-8.60] and odds ratio 5.20 [95% confidence interval 3.53-7.45]), respectively. The logistic regression analysis showed that age, hemodynamic instability, the need of packed red blood cells concentrates in the initial 24 h, the severity of brain injury, and the need for invasive neuromonitoring were significantly associated with MOF development. CONCLUSIONS: MOF occurred in 6.2% of patients with TBI admitted to the ICU and was associated with increased mortality. MOF was associated with age, hemodynamic instability, the need of packed red blood cells concentrates in the initial 24 h, the severity of brain injury, and the need for invasive neuromonitoring.