Modelo de riesgo de mortalidad a largo plazo en pacientes con infección atendidos por servicios de emergencias prehospitalarios / Long-term risk of death in patients with infection attended by prehospital emergency services

Objetivo: Diseñar y validar un modelo de riesgo con variables determinadas a nivel prehospitalario para predecir el riesgo de mortalidad a largo plazo (1 año) en pacientes con infección. Métodos: Estudio multicéntrico, observacional prospectivo, sin intervención, en pacientes adultos con sospecha infección atendidos por unidades de soporte vital avanzado y trasladados a 4 hospitales españoles entre el 1 de junio de 2020 y el 30 de junio de 2022. Se recogieron variables demográficas, fisiológicas, clínicas y analíticas. Se construyó y validó un modelo de riesgo para la mortalidad a un año usando una regresión de Cox.Resultados: Se incluyeron 410 pacientes, con una tasa de mortalidad acumulada al año del 49%. La tasa de diagnóstico de sepsis (infección e incremento sobre el SOFA basal $ 2 puntos) fue del 29,2% en supervivientes frente a un 56,7% en no supervivientes. El modelo predictivo obtuvo un área bajo la curva de la característica operativa del receptor para la mortalidad a un año fue de 0,89, e incluyó: edad, institucionalización, índice de comorbilidad de Charlson ajustado por edad, presión parcial de dióxido de carbono, potasio, lactato, nitrógeno ureico en sangre, creatinina, saturación en relación con fracción inspirada de oxígeno y diagnóstico de sepsis.Conclusiones: El modelo desarrollado con variables epidemiológicas, analíticas y clínicas mostró una excelente capacidad predictiva, y permitió identificar desde el primer contacto del paciente con el sistema sanitario, a modo de evento centinela, casos de alto riesgo.(AU)

Objectives: To develop and validate a risk model for 1-year mortality based on variables available from earlyprehospital emergency attendance of patients with infection. Methods: Prospective, observational, noninterventional multicenter study in adults with suspected infection transferred to 4 Spanish hospitals by advanced life-support ambulances from June 1, 2020, through June 30, 2022. We collected demographic, physiological, clinical, and analytical data. Cox regression analysis was used to develop and validate a risk model for 1-year mortality. Results: Four hundred ten patients were enrolled (development cohort, 287; validation cohort, 123). Cumulative mortality was 49% overall. Sepsis (infection plus a Sepsis-related Organ Failure Assessment score of 2 or higher) was diagnosed in 29.2% of survivors vs 56.7% of nonsurvivors. The risk model achieved an area under the receiver operating characteristic curve of 0.89 for 1-year mortality. The following predictors were included in the model: age; institutionalization; age-adjusted Charlson comorbidity index; PaCO2; potassium, lactate, urea nitrogen, and creatinine levels; fraction of inspired oxygen; and diagnosed sepsis. Conclusions: The model showed excellent ability to predict 1-year mortality based on epidemiological, analytical, andclinical variables, identifying patients at high risk of death soon after their first contact with the health care system.(AU)

Long-term risk of death in patients with infection attended by prehospital emergency services. / Modelo de riesgo de mortalidad a largo plazo en pacientes con infección atendidos por servicios de emergencias prehospitalarios.

OBJECTIVES: To develop and validate a risk model for 1-year mortality based on variables available from early prehospital emergency attendance of patients with infection. MATERIAL AND METHODS: Prospective, observational, noninterventional multicenter study in adults with suspected infection transferred to 4 Spanish hospitals by advanced life-support ambulances from June 1, 2020, through June 30, 2022. We collected demographic, physiological, clinical, and analytical data. Cox regression analysis was used to develop and validate a risk model for 1-year mortality. RESULTS: Four hundred ten patients were enrolled (development cohort, 287; validation cohort, 123). Cumulative mortality was 49% overall. Sepsis (infection plus a Sepsis-related Organ Failure Assessment score of 2 or higher) was diagnosed in 29.2% of survivors vs 56.7% of nonsurvivors. The risk model achieved an area under the receiver operating characteristic curve of 0.89 for 1-year mortality. The following predictors were included in the model: age; institutionalization; age-adjusted Charlson comorbidity index; PaCO2; potassium, lactate, urea nitrogen, and creatinine levels; fraction of inspired oxygen; and diagnosed sepsis. CONCLUSION: The model showed excellent ability to predict 1-year mortality based on epidemiological, analytical, and clinical variables, identifying patients at high risk of death soon after their first contact with the health care system.

OBJETIVO: Diseñar y validar un modelo de riesgo con variables determinadas a nivel prehospitalario para predecir el riesgo de mortalidad a largo plazo (1 año) en pacientes con infección. METODO: Estudio multicéntrico, observacional prospectivo, sin intervención, en pacientes adultos con sospecha infección atendidos por unidades de soporte vital avanzado y trasladados a 4 hospitales españoles entre el 1 de junio de 2020 y el 30 de junio de 2022. Se recogieron variables demográficas, fisiológicas, clínicas y analíticas. Se construyó y validó un modelo de riesgo para la mortalidad a un año usando una regresión de Cox. RESULTADOS: Se incluyeron 410 pacientes, con una tasa de mortalidad acumulada al año del 49%. La tasa de diagnóstico de sepsis (infección e incremento sobre el SOFA basal $ 2 puntos) fue del 29,2% en supervivientes frente a un 56,7% en no supervivientes. El modelo predictivo obtuvo un área bajo la curva de la característica operativa del receptor para la mortalidad a un año fue de 0,89, e incluyó: edad, institucionalización, índice de comorbilidad de Charlson ajustado por edad, presión parcial de dióxido de carbono, potasio, lactato, nitrógeno ureico en sangre, creatinina, saturación en relación con fracción inspirada de oxígeno y diagnóstico de sepsis. CONCLUSIONES: El modelo desarrollado con variables epidemiológicas, analíticas y clínicas mostró una excelente capacidad predictiva, y permitió identificar desde el primer contacto del paciente con el sistema sanitario, a modo de evento centinela, casos de alto riesgo.

Prehospital qSOFA, mSOFA, and NEWS2 performance for sepsis prediction: A prospective, multi-center, cohort study.

Background: Nowadays, there is no gold standard score for prehospital sepsis and sepsis-related mortality identification. The aim of the present study was to analyze the performance of qSOFA, NEWS2 and mSOFA as sepsis predictors in patients with infection-suspected in prehospital care. The second objective is to study the predictive ability of the aforementioned scores in septic-shock and in-hospital mortality. Methods: Prospective, ambulance-based, and multicenter cohort study, developed by the emergency medical services, among patients (n = 535) with suspected infection transferred by ambulance with high-priority to the emergency department (ED). The study enrolled 40 ambulances and 4 ED in Spain between 1 January 2020, and 30 September 2021. All the variables used in the scores, in addition to socio-demographic data, standard vital signs, prehospital analytical parameters (glucose, lactate, and creatinine) were collected. For the evaluation of the scores, the discriminative power, calibration curve and decision curve analysis (DCA) were used. Results: The mSOFA outperformed the other two scores for mortality, presenting the following AUCs: 0.877 (95%CI 0.841-0.913), 0.761 (95%CI 0.706-0.816), 0.731 (95%CI 0.674-0.788), for mSOFA, NEWS, and qSOFA, respectively. No differences were found for sepsis nor septic shock, but mSOFA's AUCs was higher than the one of the other two scores. The calibration curve and DCA presented similar results. Conclusion: The use of mSOFA could provide and extra insight regarding the short-term mortality and sepsis diagnostic, backing its recommendation in the prehospital scenario.

Combination of Prehospital NT-proBNP with qSOFA and NEWS to Predict Sepsis and Sepsis-Related Mortality.

BACKGROUND: The aim of this study was to assess the role of prehospital point-of-care N-terminal probrain natriuretic peptide to predict sepsis, septic shock, or in-hospital sepsis-related mortality. METHODS: A prospective, emergency medical service-delivered, prognostic, cohort study of adults evacuated by ambulance and admitted to emergency department between January 2020 and May 2021. The discriminative power of the predictive variable was assessed through a prediction model trained using the derivation cohort and evaluated by the area under the curve of the receiver operating characteristic on the validation cohort. RESULTS: A total of 1,360 patients were enrolled with medical disease in the study. The occurrence of sepsis, septic shock, and in-hospital sepsis-related mortality was 6.4% (67 cases), 4.2% (44 cases), and 6.1% (64 cases). Prehospital National Early Warning Score 2 had superior predictive validity than quick Sequential Organ Failure Assessment and N-terminal probrain natriuretic peptide for detecting sepsis and septic shock, but N-terminal probrain natriuretic peptide outperformed both scores in in-hospital sepsis-related mortality estimation. Application of N-terminal probrain natriuretic peptide to subgroups of the other two scores improved the identification of sepsis, septic shock, and sepsis-related mortality in the group of patients with low-risk scoring. CONCLUSIONS: The incorporation of N-terminal probrain natriuretic peptide in prehospital care combined with already existing scores could improve the identification of sepsis, septic shock, and sepsis-related mortality.

Comorbidity-adjusted NEWS predicts mortality in suspected patients with COVID-19 from nursing homes: Multicentre retrospective cohort study.

AIMS: To assess the prognostic accuracy of comorbidity-adjusted National Early Warning Score in suspected Coronavirus disease 2019 patients transferred from nursing homes by the Emergency Department. DESIGN: Multicentre retrospective cohort study. METHODS: Patients transferred by high-priority ambulances from nursing homes to Emergency Departments with suspected severe acute respiratory syndrome coronavirus 2 infection, from March 12 to July 31 2020, were considered. Included variables were: clinical covariates (respiratory rate, oxygen saturation, systolic blood pressure, heart rate, temperature, level of consciousness and supplemental oxygen use), the presence of comorbidities and confirmatory analytical diagnosis of severe acute respiratory syndrome coronavirus 2 infection. The primary outcome was a 2-day mortality rate. The discriminatory capability of the National Early Warning Score was assessed by the area under the receiver operating characteristic curve in two different cohorts, the validation and the revalidation, which were randomly selected from the main cohort. RESULTS: A total of 337 nursing homes, 10 advanced life support units, 51 basic life support units and 8 hospitals in Spain entailing 1,324 patients (median age 87 years) was involved in this study. Two-day mortality was 11.5% (152 cases), with a positivity rate of severe acute respiratory syndrome coronavirus 2 of 51.2%, 77.7% of hospitalization from whom 1% was of intensive care unit admission. The National Early Warning Score results for the revalidation cohort presented an AUC of 0.771, and of 0.885, 0.778 and 0.730 for the low-, medium- and high-level groups of comorbidities. CONCLUSION: The comorbidity-adjusted National Early Warning Score provides a good short-term prognostic criterion, information that can help in the decision-making process to guide the best strategy for each older adult, under the current pandemic. IMPACT: What problem did the study address? Under the current coronavirus disease 2019 pandemic, targeting older adults at high risk of deterioration in nursing homes remains challenging. What were the main findings? Comorbidity-adjusted National Early Warning Score helps to forecast the risk of clinical deterioration more accurately. Where and on whom will the research have impact? A high NEWS, with a low level of comorbidity is associated with optimal predictive performance, making these older adults likely to benefit from continued follow up and potentially hospital referral under the current coronavirus disease 2019 pandemic.

Impacto en el consumo de antibióticos del test de diagnóstico rápido de Streptococcus pyogenes en Atención Primaria / Impact of the rapid diagnostic test of Streptococcus pyogenes on the consumption of antibiotics in Primary Care

OBJETIVOS: analizar el empleo de los test de detección rápida de antígeno estreptocócico en Pediatría de Atención Primaria (AP), su impacto en la prescripción de antibióticos y la reducción de costes del tratamiento antibiótico. MATERIAL Y MÉTODOS: estudio descriptivo transversal, en menores de 15 años atendidos en AP, en 24 centros de salud, desde abril de 2017 hasta febrero de 2018. Se elaboró un protocolo de utilización del test de detección rápida de antígeno estreptocócico (TDRS). Se incluyeron pacientes con escala Centor mayor o igual a 2 puntos. Se extrajeron del sistema de facturación de recetas datos del número de dosis diaria definida (DDD) e importe de antibióticos en dicha temporada, comparándose con el gasto en los 12 meses previos. RESULTADOS: se realizaron 819 TDRS. Resultaron positivos 250 (30,5%), negativos 557 (68%) y 12 no valorables (1,5%). Se prescribió antibiótico al 33% de los pacientes (todos los positivos, 18 negativos, 3 no valorables). En 539 pacientes (97%) con resultado negativo no se instauró antibiótico. El número de DDD total disminuyó en 21 960 (12%), de las cuales 19 023 (86,6%) corresponden a los antibióticos más utilizados (penicilinas, amoxicilina, amoxicilina-clavulánico y azitromicina). La reducción económica fue de 11 320 € (12,5%) y el gasto en TDRS fue de 991 €, lo que supone un ahorro de 10 329€. CONCLUSIONES: la introducción del TDRS en consultas de Pediatría de AP ha permitido que se eviten un elevado número de tratamientos antibióticos. Su utilización ha demostrado ser eficiente en la optimización del consumo de antibióticos, consiguiendo reducir su utilización, evitar efectos adversos y reducir el gasto farmacéutico innecesario

OBJECTIVE: the aim of the study was to analyse the use of the rapid Streptococcus antigen detection test in primary care paediatrics, its impact on antibiotic prescription of and the associated decrease in antibiotic treatment costs. MATERIAL AND METHODS: we conducted a cross-sectional descriptive study in children aged less than 15 years managed in 24 primary care centres between April 2017 and February 2018. We developed a protocol for the use of the rapid strep test (RST). We included patients with a Centor score equal to or greater than 2 points. We collected data on the number of daily defined doses (DDDs) and amount antibiotics prescribed in the study period from the prescription billing system and compared it with the costs corresponding to the previous 12-month period. RESULTS: 819 TDRS were performed. The results were positive in 250 (30.5%), negative in 557 (68%) and inconclusive in 12 (1.5%). Antibiotics were prescribed to 33% of the patients (all patients with a positive test, 18 with a negative test and 3 with an inconclusive test). Antibiotherapy was not prescribed to 539 of the patients with a negative result (97%). The total number of prescribed DDDs decreased by 21 960 (12%), of which 19 023 (86.6%) corresponded to the most frequently prescribed antibiotics (penicillins, amoxicillin, amoxicillin-clavulanic acid and azithromycin). We found a reduction of €11 320 in antibiotherapy costs (12.5%), while the total cost of rapid testing was € 991, corresponding to total savings of €10 329. CONCLUSIONS: the introduction of the RST in primary care paediatrics has achieved a reduction in the frequency of antibiotherapy. Its use has proven effective in optimising antibiotic use, reducing antibiotic prescription and therefore preventing associated adverse events and reducing unnecessary pharmacotherapy costs