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.

Spanish vs USA cohort comparison of prehospital trauma scores to predict short-term mortality.

BACKGROUND: This study aimed to evaluate three prehospital early warning scores (EWSs): RTS, MGAP and MREMS, to predict short-term mortality in acute life-threatening trauma and injury/illness by comparing United States (US) and Spanish cohorts. METHODS: A total of 8,854 patients, 8,598/256 survivors/nonsurvivors, comprised the unified cohort. Datasets were randomly divided into training and test sets. Training sets were used to analyse the discriminative power of the scores in terms of the area under the curve (AUC), and the score performance was assessed in the test set in terms of sensitivity (SE), specificity (SP), accuracy (ACC) and balanced accuracy (BAC). RESULTS: The three scores showed great discriminative power with AUCs>0.90, and no significant differences between cohorts were found. In the test set, RTS/MREMS/MGAP showed SE/SP/ACC/BAC values of 86.0/89.9/89.6/87.1%, 91.0/86.9/87.5/88.5%, and 87.7/82.9/83.4/85.2%, respectively. CONCLUSIONS: All EWSs showed excellent ability to predict the risk of short-term mortality, independent of the country.

Utility of non-invasive monitoring of exhaled carbon dioxide and perfusion index in adult patients in the emergency department.

BACKGROUND: Several noninvasive solutions are available for the assessment of patients at risk of deterioration. Capnography, in the form of end-tidal exhaled CO2 (ETCO2) and perfusion index (PI), could provide relevant information about patient prognosis. The aim of the present project was to determine the association of ETCO2 and PI with mortality of patients admitted to the emergency department (ED). METHODS: Multicenter, prospective, cohort study of adult patients with acute disease who needed continuous monitoring in the ED. The study included two tertiary hospitals in Spain between October 2022 and June 2023. The primary outcome of the study was in-hospital mortality (all-cause). Demographics, vital signs, ETCO2 and PI were collected. RESULTS: A total of 687 patients were included in the study. The in-hospital mortality rate was 6.8%. The median age was 79 years (IQR: 69-86), and 63.3% were males. The median ETCO2 value was 30 mmHg (26-35) in survivors and 23 mmHg (16-30) in nonsurvivors (p = 0.001). For the PI, the medians were 4.7% (2.8-8.1) for survivors and 2.5% (0.98-4-4) for nonsurvivors (p < 0.001). The model that presented the best AUC was age (odds ratio (OR): 1.02 (1.00-1.05)), the respiratory rate (OR: 1.06 (1.02-1.11)), and the PI (OR: 0.83 (0.75-0.91)), with a result of 0.840 (95% CI: 0.795-0.886); the model with the respiratory rate (OR: 1.05 (1.01-1.10)), the PI (OR: 0.84 (0.76-0.93)), and the ETCO2 (no statistically significant OR), with an AUC of 0.838 (95% CI: 0.787-0.889). CONCLUSIONS: The present study showed that the PI and respiratory rate are independently associated with in-hospital mortality. Both the PI and ETCO2 are predictive parameters with improved prognostic performance compared with that of standard vital signs.

Comparison of eight prehospital early warning scores in life-threatening acute respiratory distress: a prospective, observational, multicentre, ambulance-based, external validation study.

BACKGROUND: A myriad of early warning scores (EWSs) exist, yet there is a need to identify the most clinically valid score to be used in prehospital respiratory assessments to estimate short-term and midterm mortality, intensive-care unit admission, and airway management in life-threatening acute respiratory distress. METHODS: This is a prospective, observational, multicentre, ambulance-based, external validation study performed in 44 ambulance services and four hospitals across three Spanish provinces (ie, Salamanca, Segovia, and Valladolid). We identified adults (ie, those aged 18 years and older) discharged to the emergency department with suspected acute respiratory distress. The primary outcome was 2-day all-cause in-hospital mortality, for all the patients or according to prehospital respiratory conditions, including dyspnoea, chronic obstructive pulmonary disease (COPD), COVID-19, other infections, and other conditions (asthma exacerbation, haemoptysis, and bronchoaspirations). 30-day mortality, intensive-care unit admission, and invasive and non-invasive mechanical ventilation were secondary outcomes. Eight EWSs, namely, the National Early Warning Score 2, the Modified Rapid Emergency Medicine Score, the Rapid Acute Physiology Score, the Quick Sequential Organ Failure Assessment Score, the CURB-65 Severity Score for Community-Acquired Pneumonia, the BAP-65 Score for Acute Exacerbation of COPD, the Quick COVID-19 Severity Index, and the Modified Sequential Organ Failure Assessment (mSOFA), were explored to determine their predictive validity through calibration, clinical net benefit as determined through decision curve analysis, and discrimination analysis (area under the curve of the receiver operating characteristic [AUROC], compared with Delong's test). FINDINGS: Between Jan 1, 2020, and Nov 31, 2022, 902 patients were enrolled. The global 2-day mortality rate was 87 (10%); in proportion to various respiratory conditions, the rates were 35 (40%) for dyspnoea, nine (10%) for COPD, 13 (15%) for COVID-19, 28 (32%) for other infections, and two (2%) for others conditions. mSOFA showed the best calibration, a higher net benefit, and the best discrimination (AUROC 0·911, 95% CI 0·86-0·95) for predicting 2-day mortality, and its discrimination was statistically significantly more accurate (p<0·0001) compared with the other scores. The performance of mSOFA for predicting 2-day mortality was higher than the other scores when considering the prehospital respiratory conditions, and was also higher for the secondary outcomes, except for non-invasive mechanical ventilation. INTERPRETATION: Our results showed that mSOFA outperformed other EWSs. The inclusion of mSOFA in prehospital decision making will entail a quick identification of patients in acute respiratory distress at high risk of deterioration, allowing prioritisation of resources and patient care. FUNDING: Gerencia Regional de Salud, Public Health System of Castilla y León (GRS Spain). TRANSLATION: For the Spanish translation of the abstract see Supplementary Materials section.

Prehospital acute life-threatening cardiovascular disease in elderly: an observational, prospective, multicentre, ambulance-based cohort study.

OBJECTIVE: The aim was to explore the association of demographic and prehospital parameters with short-term and long-term mortality in acute life-threatening cardiovascular disease by using a hazard model, focusing on elderly individuals, by comparing patients under 75 years versus patients over 75 years of age. DESIGN: Prospective, multicentre, observational study. SETTING: Emergency medical services (EMS) delivery study gathering data from two back-to-back studies between 1 October 2019 and 30 November 2021. Six advanced life support (ALS), 43 basic life support and five hospitals in Spain were considered. PARTICIPANTS: Adult patients suffering from acute life-threatening cardiovascular disease attended by the EMS. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was in-hospital mortality from any cause within the first to the 365 days following EMS attendance. The main measures included prehospital demographics, biochemical variables, prehospital ALS techniques used and syndromic suspected conditions. RESULTS: A total of 1744 patients fulfilled the inclusion criteria. The 365-day cumulative mortality in the elderly amounted to 26.1% (229 cases) versus 11.6% (11.6%) in patients under 75 years old. Elderly patients (≥75 years) presented a twofold risk of mortality compared with patients ≤74 years. Life-threatening interventions (mechanical ventilation, cardioversion and defibrillation) were also related to a twofold increased risk of mortality. Importantly, patients suffering from acute heart failure presented a more than twofold increased risk of mortality. CONCLUSIONS: This study revealed the prehospital variables associated with the long-term mortality of patients suffering from acute cardiovascular disease. Our results provide important insights for the development of specific codes or scores for cardiovascular diseases to facilitate the risk of mortality characterisation.

Prehospital lactate-glucose interaction in acute life-threatening illnesses: metabolic response and short-term mortality.

BACKGROUND AND IMPORTANCE: Lactate is an already recognized biomarker for short-term mortality. However, how glycemia and diabetes affect the predictive ability of lactate needs to be revealed. OBJECTIVE: To determine how hypoglycemia, normoglycemia, and hyperglycemia modify the predictive ability of lactate for short-term mortality (3 days). The secondary objective was to evaluate the predictive ability of lactate in diabetic patients. DESIGN, SETTINGS AND PARTICIPANTS: Prospective, observational study performed between 26 October 2018 and 31 December 2022. Multicenter, EMS-delivery, ambulance-based study, considering 38 basic life support units and 5 advanced life support units referring to four tertiary care hospitals (Spain). Eligible patients were adults recruited from among all phone requests for emergency assistance who were later evacuated to emergency departments. OUTCOMES MEASURE AND ANALYSIS: The primary outcome was in-hospital mortality from any cause within the third day following EMS attendance. The main predictors considered were lactate, blood glucose levels and previous diabetes. MAIN RESULTS: A total of 6341 participants fulfilled the inclusion criteria. 68 years (IQR: 51-80); 41.4% were female. The 3-day in-hospital mortality rate was 3.5%. The predictive capacity of lactate for 3-day mortality was only significantly different between normo-glycemia and hyperglycemia. The best predictive result was for normo-glycemia - AUC = 0.897 (95% CI: 0.881-0.913) - then hyperglycemia - AUC = 0.819 (95% CI: 0.770-0.868) and finally, hypoglycemia - AUC = 0.703 (95% CI: 0.422-0.983). The stratification according to diabetes presented no statistically significant difference, and the predictive results were AUC = 0.924 (95% CI: 0.892-0.956), AUC = 0.906 (95% CI: 0.884-0.928), and AUC = 0.872 (95% CI: 0.817-0.927) for nondiabetes, uncomplicated cases, and end-organ damage diabetes, respectively. CONCLUSION: Our results demonstrated that glycemia, but not diabetes, alters the predictive ability of lactate. Therefore, hyperglycemia should be considered when interpreting lactate, since this could improve screening to detect cryptic shock conditions.

Prehospital mSOFA Score for Quick Prediction of Life-Saving Interventions and Mortality in Trauma Patients: A Prospective, Multicenter, Ambulance-based, Cohort Study.

Background: Prehospital emergency medical services (EMS) are the main gateway for trauma patients. Recent advances in point-of-care testing and the development of early warning scores have allowed EMS to improve patient classification. We aimed to identify patients presenting with major trauma involving life-saving interventions (LSI) using the modified Sequential Organ Failure Assessment (mSOFA) score in the prehospital scenario, and to compare these results with those of other trauma scores. Methods: This was a prospective, ambulance-based, multicenter, training-validation study in trauma patients who were treated in a prehospital setting and subsequently transported to a hospital. The study involved six Advanced Life Support units, 38 Basic Life Support units, and four hospitals. The primary outcome was LSI performed at the scene or en route and intensive care unit (ICU) admission and all-cause two-day in-hospital mortality. We collected epidemiological variables, creatinine, lactate, base excess, international normalized ratio, and vital signs. Discriminative power (area under the receiver operating characteristic curve [AUC]), calibration (observed vs predicted outcome agreement), and decision-curve analysis (DCA, clinical utility) were used to assess the reliability of the mSOFA in comparison to other scores. Results: Between January 1, 2020-April 30, 2022, a total of 763 patients were selected. The mSOFA score's AUC was 0.927 (95% confidence interval [CI] 0.898-0.957) for LSI, 0.845 (95% CI 0.808-0.882) for ICU admission, and 0.979 (95% CI 0.966-0.991) for two-day mortality. Conclusion: The mSOFA score outperformed the other scores, allowing a quick identification of high-risk patients. The routine implementation in EMS of mSOFA could provide critical support in the decision-making process in time-dependent trauma injuries.

Head-to-head comparison of six warning scores to predict mortality and clinical impairment in COVID-19 patients in emergency department.

The aim was to evaluate the ability of six risk scores (4C, CURB65, SEIMC, mCHOSEN, QuickCSI, and NEWS2) to predict the outcome of patients with COVID-19 during the sixth pandemic wave in Spain. A retrospective observational study was performed to review the electronic medical records in patients ≥ 18 years of age who consulted consecutively in an emergency department with COVID-19 diagnosis throughout 2 months during the sixth pandemic wave. Clinical-epidemiological variables, comorbidities, and their respective outcomes, such as 30-day in-hospital mortality and clinical deterioration risk (a combined outcome considering: mechanical ventilation, intensive care unit admission, and/or 30-day in-hospital mortality), were calculated. The area under the curve for each risk score was calculated, and the resulting curves were compared by the Delong test, concluding with a decision curve analysis. A total of 626 patients (median age 79 years; 49.8% female) fulfilled the inclusion criteria. Two hundred and ninety-three patients (46.8%) had two or more comorbidities. Clinical deterioration risk criteria were present in 10.1% (63 cases), with a 30-day in-hospital mortality rate of 6.2% (39 cases). Comparison of the results showed that score 4C presented the best results for both outcome variables, with areas under the curve for mortality and clinical deterioration risk of 0.931 (95% CI 0.904-0.957) and 0.871 (95% CI 0.833-0.910) (both p < 0.001). The 4C Mortality Score proved to be the best score for predicting mortality or clinical deterioration risk among patients with COVID-19 attended in the emergency department in the following 30 days.

Long-Term Mortality in Patients Transferred by Emergency Medical Services: Prospective Cohort Study.

OBJECTIVE: This study aimed to determine the long-term mortality (one-year follow-up) associated with patients transferred by Emergency Medical Services (EMS), and to reveal the determinants (causes and risk factors). METHODS: This was a multicenter, prospective, observational, controlled, ambulance-based study of adult patients transferred by ambulance to emergency departments (EDs) from October 2019 through July 2021 for any cause. A total of six Advanced Life Support (ALS) units, 38 Basic Life Support (BLS) units, and five hospitals from Spain were included. Physiological, biochemical, demographic, and reasons for transfer variables were collected. A longitudinal analysis was performed to determine the factors associated to long-term mortality (any cause). RESULTS: The final cohort included 1,406 patients. The one-year mortality rate was 21.6% (n = 304). Mortality over the first two days reached 5.2% of all the patients; between Day 2 and Day 30, reached 5.3%; and between Day 31 and Day 365, reached 11.1%. Low Glasgow values, elevated lactate levels, elevated blood urea nitrogen (BUN) levels, low oxygen saturation, high respiratory rate, as well as being old and suffering from circulatory diseases and neurological diseases were risk factors for long-term mortality. CONCLUSION: The quick identification of patients at risk of long-term worsening could provide an opportunity to customize care through specific follow-up.

Prehospital seizures: Short-term outcomes and risk stratification based in point-of-care testing.

BACKGROUND: Information for treatment or hospital derivation of prehospital seizures is limited, impairing patient condition and hindering patients risk assessment by the emergency medical services (EMS). This study aimed to determine the associated factors to clinical impairment, and secondarily, to determine risk factors associated to cumulative in-hospital mortality at 2, 7 and 30 days, in patients presenting prehospital seizures. METHODS: Prospective, multicentre, EMS-delivery study involving adult subjects with prehospital seizures, including five advanced life support units, 27 basic life support units and four emergency departments in Spain. All bedside variables: including demographic, standard vital signs, prehospital laboratory tests and presence of intoxication or traumatic brain injury (TBI), were analysed to construct a risk model using binary logistic regression and internal validation methods. RESULTS: A total of 517 patients were considered. Clinical impairment was present in 14.9%, and cumulative in-hospital mortality at 2, 7 and 30-days was 3.4%, 4.6% and 7.7%, respectively. The model for the clinical impairment indicated that respiratory rate, partial pressure of carbon dioxide, blood urea nitrogen, associated TBI or stroke were risk factors; higher Glasgow Coma Scale (GCS) scores mean a lower risk of impairment. Age, potassium, glucose, prehospital use of mechanical ventilation and concomitant stroke were risk factors associated to mortality; and oxygen saturation, a high score in GCS and haemoglobin were protective factors. CONCLUSION: Our study shows that prehospital variables could reflect the clinical impairment and mortality of patients suffering from seizures. The incorporation of such variables in the prehospital decision-making process could improve patient outcomes.

Derivation and validation of a blood biomarker score for 2-day mortality prediction from prehospital care: a multicenter, cohort, EMS-based study.

Identifying potentially life-threatening diseases is a key challenge for emergency medical services. This study aims at examining the role of different prehospital biomarkers from point-of-care testing to derive and validate a score to detect 2-day in-hospital mortality. We conducted a prospective, observational, prehospital, ongoing, and derivation-validation study in three Spanish provinces, in adults evacuated by ambulance and admitted to the emergency department. A total of 23 ambulance-based biomarkers were collected from each patient. A biomarker score based on logistic regression was fitted to predict 2-day mortality from an optimum subset of variables from prehospital blood analysis, obtained through an automated feature selection stage. 2806 cases were analyzed, with a median age of 68 (interquartile range 51-81), 42.3% of women, and a 2-day mortality rate of 5.5% (154 non-survivors). The blood biomarker score was constituted by the partial pressure of carbon dioxide, lactate, and creatinine. The score fitted with logistic regression using these biomarkers reached a high performance to predict 2-day mortality, with an AUC of 0.933 (95% CI 0.841-0.973). The following risk levels for 2-day mortality were identified from the score: low risk (score < 1), where only 8.2% of non-survivors were assigned to; medium risk (1 ≤ score < 4); and high risk (score ≥ 4), where the 2-day mortality rate was 57.6%. The novel blood biomarker score provides an excellent association with 2-day in-hospital mortality, as well as real-time feedback on the metabolic-respiratory patient status. Thus, this score can help in the decision-making process at critical moments in life-threatening situations.

Comparison of seven prehospital early warning scores to predict long-term mortality: a prospective, multicenter, ambulance-based study.

METHODS: A prospective, multicenter, ambulance-based study of adult patients with an acute illness involving six advanced life support units and 38 basic life support units, referring to five emergency departments in Spain. RESULTS: The primary outcome was long-term mortality with a 1-year follow-up. The compared scores included: National Early Warning Score 2, VitalPAC early warning score, modified rapid emergency medicine score (MREMS), Sepsis-related Organ Failure Assessment, Cardiac Arrest Risk Triage Score, Rapid Acute Physiology Score, and Triage Early Warning Score. Discriminative power [area under the receiver operating characteristic curve (AUC)] and decision curve analysis (DCA) were used to compare the scores. Additionally, a Cox regression and Kaplan-Meier method were used. Between 8 October 2019, and 31 July 2021, a total of 2674 patients were selected. The MREMS presented the highest AUC of 0.77 (95% confidence interval, 0.75-0.79), significantly higher than those of the other EWS. It also exhibited the best performance in the DCA and the highest hazard ratio for 1-year mortality [3.56 (2.94-4.31) for MREMS between 9 and 18 points, and 11.71 (7.21-19.02) for MREMS > 18]. CONCLUSION: Among seven tested EWS, the use of the MREMS presented better characteristics to predict 1-year mortality; however, all these scores present moderate performances.

Modified Sequential Organ Failure Assessment Score vs. Early Warning Scores in Prehospital Care to Predict Major Adverse Cardiac Events in Acute Cardiovascular Disease.

(1) Background: The Modified Sequential Organ Failure Assessment (mSOFA) is an Early Warning Score (EWS) that has proven to be useful in identifying patients at high risk of mortality in prehospital care. The main objective of this study was to evaluate the predictive validity of prehospital mSOFA in estimating 2- and 90-day mortality (all-cause) in patients with acute cardiovascular diseases (ACVD), and to compare this validity to that of four other widely-used EWS. (2) Methods: We conducted a prospective, observational, multicentric, ambulance-based study in adults with suspected ACVD who were transferred by ambulance to Emergency Departments (ED). The primary outcome was 2- and 90-day mortality (all-cause in- and out-hospital). The discriminative power of the predictive variable was assessed and evaluated by the area under the curve (AUC) of the receiver operating characteristic (ROC). (3) Results: A total of 1540 patients met the inclusion criteria. The 2- and 90-day mortality rates were 5.3% and 12.7%, respectively. The mSOFA showed the highest AUC of all the evaluated scores for both 2- and 90-day mortality, AUC = 0.943 (0.917-0.968) and AUC = 0.874 (0.847-0.902), respectively. (4) Conclusions: The mSOFA is a quick and easy-to-use EWS with an excellent ability to predict mortality at both 2 and 90 days in patients treated for ACVD, and has proved to be superior to the other EWS evaluated in this study.

Development of a prehospital lactic acidosis score for early-mortality. A prospective, multicenter, ambulance-based, cohort study.

BACKGROUND: Lactic acidosis is a clinical status related to clinical worsening. Actually, higher levels of lactate is a well-established trigger of emergency situations. The aim of this work is to build-up a prehospital early warning score to predict 2-day mortality and intensive care unit (ICU) admission, constructed with other components of the lactic acidosis besides the lactate. METHODS: Prospective, multicenter, observational, derivation-validation cohort study of adults evacuated by ambulance and admitted to emergency department with acute diseases, between January 1st, 2020 and December 31st, 2021. Including six advanced life support, thirty-eight basic life support units, referring to four hospitals (Spain). The primary and secondary outcome of the study were 2-day all-cause mortality and ICU-admission. The prehospital lactic acidosis (PLA) score was derived from the analysis of prehospital blood parameters associated with the outcome using a logistic regression. The calibration, clinical utility, and discrimination of PLA were determined and compared to the performance of each component of the score alone. RESULTS: A total of 3334 patients were enrolled. The final PLA score included: lactate, pCO2, and pH. For 2-day mortality, the PLA showed an AUC of 0.941 (95%CI: 0.914-0.967), a better performance in calibration, and a higher net benefit as compared to the other score components alone. For the ICU admission, the PLA only showed a better performance for AUC: 0.75 (95%CI: 0.706-0.794). CONCLUSIONS: Our results showed that PLA predicts 2-day mortality better than other lactic acidosis components alone. Including PLA score in prehospital setting could improve emergency services decision-making.

Prehospital Respiratory Early Warning Score for airway management in-ambulance: A score comparison.

BACKGROUND: Prehospital Respiratory Early Warning Scores to estimate the requirement for advanced respiratory support is needed. To develop a prehospital Respiratory Early Warning Score to estimate the requirement for advanced respiratory support. METHODS: Multicentre, prospective, emergency medical services (EMS)-delivered, longitudinal cohort derivationvalidation study carried out in 59 ambulances and five hospitals across five Spanish provinces. Adults with acute diseases evaluated, supported and discharged to the Emergency Department with high priority were eligible. The primary outcome was the need for invasive or non-invasive respiratory support (NIRS or IRS) in the prehospital scope at the first contact with the patient. The measures included the following: epidemiological endpoints, prehospital vital signs (respiratory rate, pulse oximetry saturation, fraction of inspired oxygen, systolic and diastolic mean blood pressure, heart rate, tympanic temperature and consciousness level by the GCS). RESULTS: Between 26 Oct 2018 and 26 Oct 2021, we enrolled 5793 cases. For NIRS prediction, the final model of the logistic regression included respiratory rate and pulse oximetry saturation/fraction of inspired oxygen ratio. For the IRS case, the motor response from the Glasgow Coma Scale was also included. The REWS showed an AUC of 0.938 (95% CI: 0.918-0.958), a calibration-in-large of 0.026 and a higher net benefit as compared with the other scores. CONCLUSIONS: Our results showed that REWS is a remarkably aid for the decision-making process in the management of advanced respiratory support in prehospital care. Including this score in the prehospital scenario could improve patients' care and optimise the resources' management.

Derivation and validation of new prehospital phenotypes for adults with COVID-19. / Derivación y validación de nuevos fenotipos prehospitalarios en pacientes adultos con enfermedad por COVID-19.

OBJECTIVES: To characterize phenotypes of prehospital patients with COVID-19 to facilitate early identification of at-risk groups. MATERIAL AND METHODS: Multicenter observational noninterventional study of a retrospective cohort of 3789 patients, analyzing 52 prehospital variables. The main outcomes were 4 clusters of prehospital variables describing the phenotypes. Secondary outcomes were hospitalization, mechanical ventilation, admission to an intensive care unit, and cumulative mortality inside or outside the hospital on days 1, 2, 3, 7, 14, 21, and 28 after hospitalization and after start of prehospital care. RESULTS: We used a principal components multiple correspondence analysis (factor analysis) followed by decomposition into 4 clusters as follows: cluster 1, 1090 patients (28.7%); cluster 2, 1420 (37.4%); cluster 3, 250 (6.6%), and cluster 4, 1029 (27.1%). Cluster 4 was comprised of the oldest patients and had the highest frequencies of residence in group facilities and low arterial oxygen saturation. This group also had the highest mortality (44.8% at 28 days). Cluster 1 was comprised of the youngest patients and had the highest frequencies of smoking, fever, and requirement for mechanical ventilation. This group had the most favorable prognosis and the lowest mortality. CONCLUSION: Patients with COVID-19 evaluated by emergency medical responders and transferred to hospital emergency departments can be classified into 4 phenotypes with different clinical, therapeutic, and prognostic characteristics. The phenotypes can help health care professionals to quickly assess a patient's future risk, thus informing clinical decisions.

OBJETIVO: Desarrollar un fenotipado prehospitalario de pacientes con COVID-19 que permita una identificación temprana de los grupos de riesgo. METODO: Estudio observacional de cohorte retrospectivo multicéntrico, sin intervención con 3.789 pacientes y 52 variables prehospitalarias. Las variables de resultado principal fueron las cuatro agrupaciones prehospitalarios obtenidos, #1, #2, #3 y #4. Los resultados secundarios fueron: ingreso hospitalario, ventilación mecánica, ingreso en unidad de cuidados intensivos y mortalidad acumulada a los 1, 2, 3, 7, 14, 21 y 28 días desde el ingreso hospitalario (hospitalaria y extrahospitalaria). RESULTADOS: Por medio de una descomposición en componentes principales/correspondencia múltiple de datos mixtos (continuos y categóricos), seguido de una descomposición en agrupaciones, se obtuvo cuatro agrupaciones/fenotipos #1, #2, #3 y #4 de 1.090 (28,7%), 1.420 (37,4%), 250 (6,6%) y 1.029 (27,1%) pacientes, respectivamente. El grupo #4, compuesto por los pacientes de mayor edad, baja saturación de oxígeno e institucionalización es el que presenta la mayor mortalidad (44,8% de mortalidad a 28 días). El grupo #1, compuesto de pacientes de menor edad, con mayor porcentaje de tabaquismo, fiebre y necesidades de ventilación mecánica, es el de pronóstico más favorable con la menor tasa de mortalidad. CONCLUSIONES: Los pacientes con COVID-19 valorados por los servicios médicos de emergencias y transferidos al servicio de urgencias hospitalario se pueden clasificar en 4 fenotipos con diferentes consideraciones clínicas, terapéuticas y de pronóstico, y permite a los profesionales sanitarios discriminar rápidamente el nivel de riesgo futuro del paciente y ayuda por lo tanto en el proceso de toma de decisiones.

Role of prehospital point-of-care N-terminal pro-brain natriuretic peptide in acute life-threatening cardiovascular disease.

INTRODUCTION: The evidence about the use of natriuretic peptides (NP) to predict mortality in the pre-hospital setting is limited. The main objective of this study is to assess the ability of point-of-care testing (POCT) N-terminal portion of B-type natriuretic peptide (NT-proBNP) to predict 2-day in-hospital mortality of acute cardiovascular diseases (ACVD). METHODS: We conducted a multicentric, prospective, observational study in adults with ACVD transferred by ambulance to emergency departments (ED). The primary outcome was 2-day in-hospital mortality. The discrimination capacity of the NT-proBNP was performed through a prediction model trained using a derivation cohort and evaluated by the area under the curve (AUC) of the receiver operating characteristic on a validation cohort. RESULTS: A total of 1006 patients were recruited. The median age was 75 (IQR 63-84) years and 421 (41.85%) were females. The 2-day in-hospital mortality was 5.8% (58 cases). The predictive validity of NT-proBNP, for 2-day mortality reached the following AUC: 0.823 (95%CI: 0.758-0.889, p < 0.001), and the optimal specificity and sensitivity were 73.1 and 82.7. Predictive power of NT-proBNP obtained an AUC 0.549 (95%CI: 0.432-0.865, p 0.215) for acute heart failure, AUC 0.893 (95%CI: 0.617-0.97, p < 0.001) for ischemic heart disease, AUC 0.714 (95%CI: 0.55-0.87, p = 0.0069) for arrhythmia and AUC 0.927 (95%CI: 0.877-0.978, p < 0,001) for syncope. CONCLUSION: POCT NT-proBNP has proven to be a strong predictor of early mortality in ACVD, showing an excellent predictive capacity in cases of syncope. However, this biomarker does not appear to be useful for predicting outcome in patients with acute heart failure.

Novel Prehospital Phenotypes and Outcomes in Adult-Patients with Acute Disease.

An early identification of prehospital phenotypes may allow health care workers to speed up and improve patients' treatment. To determine emergency phenotypes by exclusively using prehospital clinical data, a multicenter, prospective, and observational ambulance-based study was conducted with a cohort of 3,853 adult patients treated consecutively and transferred with high priority from the scene to the hospital emergency department. Cluster analysis determined three clusters with highly different outcome scores and pathological characteristics. The first cluster presented a 30-day mortality after the index event of 45.9%. The second cluster presented a mortality of 26.3%, while mortality of the third cluster was 5.1%. This study supports the detection of three phenotypes with different risk stages and with different clinical, therapeutic, and prognostic considerations. This evidence could allow adapting treatment to each phenotype thereby helping in the decision-making process.

COVID-19 as a risk factor for long-term mortality in patients managed by the emergency medical system: A prospective, multicenter, ambulance-based cohort study.

Introduction: COVID-19 has initially been studied in terms of an acute-phase disease, although recently more attention has been given to the long-term consequences. In this study, we examined COVID-19 as an independent risk factor for long-term mortality in patients with acute illness treated by EMS (emergency medical services) who have previously had the disease against those who have not had the disease. Methods: A prospective, multicenter, ambulance-based, ongoing study was performed with adult patients with acute disease managed by EMS and transferred with high priority to the emergency department (ED) as study subjects. The study involved six advanced life support units, 38 basic life support units, and five emergency departments from Spain. Sociodemographic inputs, baseline vital signs, pre-hospital blood tests, and comorbidities, including COVID-19, were collected. The main outcome was long-term mortality, which was classified into 1-year all-cause mortality and 1-year in- and out-of-hospital mortality. To compare both the patients with COVID-19 vs. patients without COVID-19 and to compare survival vs non-survival, two main statistical analyses were performed, namely, a longitudinal analysis (Cox regression) and a logistic regression analysis. Results: Between 12 March 2020 and 30 September 2021, a total of 3,107 patients were included in the study, with 2,594 patients without COVID-19 and 513 patients previously suffering from COVID-19. The mortality rate was higher in patients with COVID-19 than in patients without COVID-19 (31.8 vs. 17.9%). A logistic regression showed that patients previously diagnosed with COVID-19 presented higher rates of nursing home residency, a higher number of breaths per minute, and suffering from connective disease, dementia, and congestive heart failure. The longitudinal analysis showed that COVID-19 was a risk factor for mortality [hazard ratio 1.33 (1.10-1.61); p < 0.001]. Conclusion: The COVID-19 group presented an almost double mortality rate compared with the non-COVID-19 group. The final model adjusted for confusion factors suggested that COVID-19 was a risk factor for long-term mortality.