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.

Synergistic impact of N-antigenemia profiled by a rapid antigen test and low anti-S1 antibodies on the risk of hospitalization in COVID-19.

OBJECTIVES: Identifying patients with COVID-19 who are at risk of poor evolution is key to early decide on their hospitalization. We evaluated the combined impact of nucleocapsid (N)-antigenemia profiled by a rapid test and antibodies against the S1 subunit of the SARS-CoV S protein (S1) on the hospitalization risk of patients with COVID-19. METHODS: N-antigenemia and anti-S1 antibodies were profiled at admission to the emergency department in 146 patients with COVID-19 using the Panbio® antigen Rapid Test and the SARS-CoV-2 immunoglobulin G II Quant/SARS-CoV-2 immunoglobulin G assay from Abbott. A multivariable analysis was used to evaluate the impact of these factors on hospitalization. RESULTS: Patients with a positive N-antigen test in plasma and anti-S1 levels <2821 arbitrary units/mL needed hospitalization more frequently (20 of 23, 87%). A total of 20 of 71 (28.2%) of those showing a negative N-antigen test and anti-S1 ≥2821 arbitrary units/mL were hospitalized for 18 of 52 (34.6%) of the patients with only one of these conditions. Patients with a positive N-antigen test and low antibody levels showed an odds ratio, 95% confidence interval, and P-value for hospitalization of 18.21, 2.74-121.18, and 0.003, respectively, and exhibited the highest mortality (30.4%). CONCLUSIONS: Simultaneous profiling of a rapid N-antigen test in plasma and anti-S1 levels could help to early identify patients with COVID-19 needing hospitalization.

Decalogue to promote the implementation and improvement of recommendations for the early diagnosis of HIV in Emergency Departments.

Early diagnosis of HIV is still a challenge. Emergency Departments (EDs) suppose ideal settings for the early detection of HIV, since patients with high prevalence of hidden HIV infection are frequently attending those services. In 2020, the Spanish Society of Emergency and Emergency Medicine (SEMES) published a series of recommendations for the early diagnosis of patients with suspected HIV infection and their referral and follow-up in the EDs as part of its "Deja tu huella" program. However, the application of these recommendations has been very heterogeneous in our country. Considering this, the working group of the HIV hospital network led by the SEMES has motivated the drafting of a decalogue, with the aim of promoting the implementation and improvement of protocols for the early diagnosis of HIV in Spanish EDs.

Utilidad del modelo 5MPB-Toledo para predecir bacteriemia en el paciente anciano / Usefulness of the 5MPB-Toledo model to predict bacteremia in the elderly patient

Resumen Objetivo: Analizar la utilidad del modelo predictivo de bacteriemia (5MPB-Toledo) en los mayores de 65 años atendidos por infección en el servicio de urgencias (SU). Material y Método: Estudio observacional prospectivo y multicéntrico de los hemocultivos (HC) obtenidos en pacientes mayores de 65 años atendidos por infección en 66 SU españoles desde el 1 de diciembre de 2019 hasta el 30 de abril de 2020. Se analizó la capacidad predictiva del modelo con el área bajo la curva (ABC) de la característica operativa del receptor (COR) y se calculó el rendimiento diagnóstico de los puntos de corte (PC) del modelo elegido con los cálculos de la sensibilidad, la especificidad, el valor predictivo positivo y el valor predictivo negativo. Resultados: Se incluyeron 2.401 episodios de HC extraídos. De ellos, se consideró como bacteriemia verdadera a 579 (24,11%) y como HC negativo a 1.822 (75,89%). Entre los negativos, 138 (5,74%) se consideraron contaminados. Se categorizó a los pacientes en bajo (0-2 puntos), moderado (3-5 puntos) y alto (6-8 puntos) riesgo, con una probabilidad de bacteriemia de 1,2%, 18,1% y 80,7%, respectivamente. El ABC-COR del modelo tras remuestreo fue de 0,908 (IC 95%: 0,897-0,924). El rendimiento diagnóstico del modelo, considerando un PC ≥ 5 puntos, obtiene una sensibilidad de 94% (IC 95%:92-96), especificidad de 77% (IC 95%:76-79) y un valor predictivo negativo de 97% (IC 95%:96-98). Conclusión: El modelo 5MPB-Toledo es de utilidad para predecir bacteriemia en los mayores de 65 años atendidos en el SU por un episodio de infección.

Abstract Objective: To analyse a risk score to predict bacteremia (MPB5-Toledo) in the patients aged older 65 years seen in the emergency departments (ED) due to infections. Patients and Methods: Prospective and multicenter observational cohort study of the blood cultures (BC) ordered in 66 Spanish ED for patients aged older 65 years seen from December 1, 2019, to April 30, 2020. The predictive ability of the model was analyzed with the area under the Receiver Operating Characteristic curve (AUC-ROC). The prognostic performance for true bacteremia was calculated with the cut-off values chosen for getting the sensitivity, specificity, positive predictive value and negative predictive value. Results: A total of 2.401 blood samples wered cultured. True cases of bacteremia were confirmed in 579 (24.11%). The remaining 1.822 cultures (75.89%) wered negative. And, 138 (5.74%) were judged to be contaminated. Low risk for bacteremia was indicated by a score of 0 to 2 points, intermediate risk by 3 to 5 points, and high risk by 6 to 8 points. Bacteremia in these 3 risk groups was predicted for 1.2%, 18.1%, and 80.7%, respectively. The model´s area under the receiver ope rating characteristic curve was 0.908 (95% CI, 0.897-0.924). The prognostic performance with a model´s cut-off value of ≥ 5 points achieved 94% (95% CI: 92-96) sensitivity, 77% (95% CI: 76-79) specificity, and negative predictive value of 97% (95% CI: 96-98). Conclusion: The 5MPB-Toledo score is useful for predicting bacteremia in the patients aged older 65 years seen in the emergency departments due to infections.

Validation of a predictive model for bacteraemia (MPB5-Toledo) in the patients seen in emergency departments due to infections.

OBJECTIVE: To validate a simple risk score to predict bacteremia (MPB5-Toledo) in patients seen in the emergency departments (ED) due to infections. METHODS: Prospective and multicenter observational cohort study of the blood cultures (BC) ordered in 74 Spanish ED for adults (aged 18 or older) seen from October 1, 2019, to February 29, 2020. The predictive ability of the model was analyzed with the area under the Receiver Operating Characteristic curve (AUC-ROC). The prognostic performance for true bacteremia was calculated with the cut-off values chosen for getting the sensitivity, specificity, positive predictive value and negative predictive value. RESULTS: A total of 3.843 blood samples wered cultured. True cases of bacteremia were confirmed in 839 (21.83%). The remaining 3.004 cultures (78.17%) were negative. Among the negative, 172 (4.47%) were judged to be contaminated. Low risk for bacteremia was indicated by a score of 0-2 points, intermediate risk by 3-5 points, and high risk by 6-8 points. Bacteremia in these 3 risk groups was predicted for 1.5%, 16.8%, and 81.6%, respectively. The model's area under the receiver operating characteristic curve was 0.930 (95% CI, 0.916-0.948). The prognostic performance with a model's cut-off value of ≥5 points achieved 94.76% (95% CI: 92.97-96.12) sensitivity, 81.56% (95% CI: 80.11-82.92) specificity, and negative predictive value of 98.24% (95% CI: 97.62-98.70). CONCLUSION: The 5MPB-Toledo score is useful for predicting bacteremia in patients attended in hospital emergency departments for infection.

A bacteraemia risk prediction model: development and validation in an emergency medicine population.

OBJECTIVE: Design a risk model to predict bacteraemia in patients attended in emergency departments (ED) for an episode of infection. METHODS: This was a national, prospective, multicentre, observational cohort study of blood cultures (BC) collected from adult patients (≥ 18 years) attended in 71 Spanish EDs from October 1 2019 to March 31, 2020. Variables with a p value < 0.05 were introduced in the univariate analysis together with those of clinical significance. The final selection of variables for the scoring scale was made by logistic regression with selection by introduction. The results obtained were internally validated by dividing the sample in a derivation and a validation cohort. RESULTS: A total of 4,439 infectious episodes were included. Of these, 899 (20.25%) were considered as true bacteraemia. A predictive model for bacteraemia was defined with seven variables according to the Bacteraemia Prediction Model of the INFURG-SEMES group (MPB-INFURG-SEMES). The model achieved an area under the curve-receiver operating curve of 0.924 (CI 95%:0.914-0.934) in the derivation cohort, and 0.926 (CI 95%: 0.910-0.942) in the validation cohort. Patients were then split into ten risk categories, and had the following rates of risk: 0.2%(0 points), 0.4%(1 point), 0.9%(2 points), 1.8%(3 points), 4.7%(4 points), 19.1% (5 points), 39.1% (6 points), 56.8% (7 points), 71.1% (8 points), 82.7% (9 points) and 90.1% (10 points). Findings were similar in the validation cohort. The cut-off point of five points provided the best precision with a sensitivity of 95.94%, specificity of 76.28%, positive predictive value of 53.63% and negative predictive value of 98.50%. CONCLUSION: The MPB-INFURG-SEMES model may be useful for the stratification of risk of bacteraemia in adult patients with infection in EDs, together with clinical judgement and other variables independent of the process and the patient.

Validation of a predictive model for bacteraemia (MPB5-Toledo) in the patients seen in emergency departments due to infections. / Validación del modelo predictivo de bacteriemia (5MPB-Toledo) en los pacientes atendidos en el servicio de urgencias por infección.

OBJECTIVE: To validate a simple risk score to predict bacteremia (MPB5-Toledo) in patients seen in the emergency departments (ED) due to infections. METHODS: Prospective and multicenter observational cohort study of the blood cultures (BC) ordered in 74 Spanish ED for adults (aged 18 or older) seen from from October 1, 2019, to February 29, 2020. The predictive ability of the model was analyzed with the area under the Receiver Operating Characteristic curve (AUC-ROC). The prognostic performance for true bacteremia was calculated with the cut-off values chosen for getting the sensitivity, specificity, positive predictive value and negative predictive value. RESULTS: A total of 3.843 blood samples wered cultured. True cases of bacteremia were confirmed in 839 (21.83%). The remaining 3.004 cultures (78.17%) were negative. Among the negative, 172 (4.47%) were judged to be contaminated. Low risk for bacteremia was indicated by a score of 0 to 2 points, intermediate risk by 3 to 5 points, and high risk by 6 to 8 points. Bacteremia in these 3 risk groups was predicted for 1.5%, 16.8%, and 81.6%, respectively. The model's area under the receiver operating characteristic curve was 0.930 (95% CI, 0.916-0.948). The prognostic performance with a model's cut-off value of ≥ 5 points achieved 94.76% (95% CI: 92.97-96.12) sensitivity, 81.56% (95% CI: 80.11-82.92) specificity, and negative predictive value of 98.24% (95% CI: 97.62-98.70). CONCLUSION: The 5MPB-Toledo score is useful for predicting bacteremia in patients attended in hospital emergency departments for infection.

Usefulness of infection biomarkers for diagnosing bacteremia in patients with a sepsis code in the emergency department.

The objective of this study was to assess the usefulness of the biomarkers lactate, C-reactive protein (CPR) and procalcitonin for the diagnosis of bacteremia in patients with suspected sepsis in the emergency department (ED) and according to the focus of infection. We conducted a retrospective study among patients included in the sepsis code of our ED between November 2013 and December 2017. We analyzed demographic variables, co-morbidity according to the Charlson Index and focus of infection, blood cultures and classification according to Gram staining. We determined the diagnostic performance of the biomarkers quantitatively and calculated the area under the curve (AUC) for global bacteremia and as a function of the focus of infection. We included 653 patients with a median age of 79 years (interquartile range: 66-86), of whom 287 (44.0% were women. The most frequent infectious focus was respiratory (36.1%]. Blood cultures were requested in 87.5% (569 cases). Of the tested samples, 31.3% were positive, of which 63.5% revealed Gram-negative (GN) bacteria. Procalcitonin obtained globally the best AUC 0.70 (95% CI: 0.65-0.75). The values with the best sensitivity and specificity were 2.54 ng/mL for procalcitonin, 4.1 mmol/L for lactate and 156 mg/L for CRP. We found an association between the median procalcitonin value and GN bacteria (6.02; IQR: 1.39-39.40) and Gram-positive bacteria (1.74; IQR: 0.22-15.61). Procalcitonin is the biomarker with the greatest capacity to diagnose bacteremia, particularly in GN infection. Stratification by focus is important since not all biomarkers discriminate in the same way.

A multidrug-resistant microorganism infection risk prediction model: development and validation in an emergency medicine population.

The aim was to develop a predictive model of infection by multidrug-resistant microorganisms (MDRO). A national, retrospective cohort study was carried out including all patients attended for an infectious disease in 54 Spanish Emergency Departments (ED), in whom a microbiological isolation was available from a culture obtained during their attention in the ED. A MDRO infection prediction model was created in a derivation cohort using backward logistic regression. Those variables significant at p < 0.05 assigned an integer score proportional to the regression coefficient. The model was then internally validated by k-fold cross-validation and in the validation cohort. A total of 5460 patients were included; 1345 (24.6%) were considered to have a MDRO infection. Twelve independent risk factors were identified in the derivation cohort and were combined into an overall score, the ATM (assessment of threat for MDRO) score. The model achieved an area under the curve-receiver operating curve of 0.76 (CI 95% 0.74-0.78) in the derivation cohort and 0.72 (CI 95% 0.70-0.75) in the validation cohort (p = 0.0584). Patients were then split into 6 risk categories and had the following rates of risk: 7% (0-2 points), 16% (3-5 points), 24% (6-9 points), 33% (10-14 points), 47% (15-21 points), and 71% (> 21 points). Findings were similar in the validation cohort. Several patient-specific factors were independently associated with MDRO infection risk. When integrated into a clinical prediction rule, higher risk scores and risk classes were related to an increased risk for MDRO infection. This clinical prediction rule could be used by providers to identify patients at high risk and help to guide antibiotic strategy decisions, while accounting for clinical judgment.

First case of imported Zika virus infection in Spain.

We report a case of Zika virus (ZIKV) infection in a patient with diarrhea, fever, synovitis, non-purulent conjunctivitis, and with discreet retro-orbital pain, after returning from Colombia in January 2016. The patient referred several mosquito bites. Presence of ZIKV was detected by PCR (polymerase chain reaction) in plasma. Rapid microbiological diagnosis of ZIKV infection is needed in European countries with circulation of its vector, in order to avoid autochthonous circulation. The recent association of ZIKV infection with abortion and microcephaly, and a Guillain-Barré syndrome highlights the need for laboratory differentiation of ZIKV from other virus infection. Women with potential risk for Zika virus infection who are pregnant or planning to become pregnant must mention that fact during prenatal visits in order to be evaluated and properly monitored.

Epidemiological Characteristics of Renal Colic and Climate-Related Causes in a Continental Area in Spain.

PURPOSE: The aim of this study was to analyze the incidence of renal colic (RC) in a northwestern area of Spain and its relationship with seasonal and meteorological characteristics. MATERIALS AND METHODS: We examined 700,257 cases that presented at the emergency room (ER) between 2005 and 2013. We reviewed data such as age, gender, arrival at ER, tests performed and destination after ER. Monthly data regarding temperature, humidity and hours of daylight were taken into account. The Student t-test, the Mann-Whitney test and the Chi-square test were used for the statistical analysis. RC visits were correlated with meteorological characteristics using the Pearson correlation coefficients. RESULTS: A total of 9,330 cases were diagnosed as RC episodes (1.41% of total cases presented). The age range was 14-100 years and mean age was 47 years. Prevalence in men was higher (55.6%) than in women (44.4%). After the seasonal decomposition analysis by month, a significant increase in RC incidence was observed in the months of June, July, August and December (107-114%). There is a statistically significant correlation between mean monthly temperature and RC visit rate (R 0.33, p < 0.001). CONCLUSION: The incidence of RC in our region is slightly higher than the one described in the literature. A significant increase in RCs is observed in the summer months, as well as a significant correlation between incidence and temperature.