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Abstract Emergency medical services (EMSs) face critical situations that require patient risk classification based on analytical and vital signs. We aimed to establish clustering-derived phenotypes based on prehospital analytical and vital signs that allow risk stratification. This was a prospective, multicenter, EMS-delivered, ambulance-based cohort study considering six advanced life support units, 38 basic life support units, and four tertiary hospitals in Spain. Adults with unselected acute diseases managed by the EMS and evacuated with discharge priority to emergency departments were considered between January 1, 2020, and June 30, 2023. Prehospital point-of-care testing and on-scene vital signs were used for the unsupervised machine learning method (clustering) to determine the phenotypes. Then phenotypes were compared with the primary outcome (cumulative mortality (all-cause) at 2, 7, and 30 days). A total of 7909 patients were included. The median (IQR) age was 64 (51–80) years, 41% were women, and 26% were living in rural areas. Three clusters were identified: alpha 16.2% (1281 patients), beta 28.8% (2279), and gamma 55% (4349). The mortality rates for alpha, beta and gamma at 2 days were 18.6%, 4.1%, and 0.8%, respectively; at 7 days, were 24.7%, 6.2%, and 1.7%; and at 30 days, were 33%, 10.2%, and 3.2%, respectively. Based on standard vital signs and blood test biomarkers in the prehospital scenario, three clusters were identified: alpha (high-risk), beta and gamma (medium- and low-risk, respectively). This permits the EMS system to quickly identify patients who are potentially compromised and to proactively implement the necessary interventions.

Objective To compare the predictive value of the quick COVID-19 Severity Index (qCSI) and the National Early Warning Score (NEWS) for 90-day mortality amongst COVID-19 patients. Methods Multicenter retrospective cohort study conducted in adult patients transferred by ambulance to an emergency department (ED) with suspected COVID-19 infection subsequently confirmed by a SARS-CoV-2 test (polymerase chain reaction). We collected epidemiological data, clinical covariates (respiratory rate, oxygen saturation, systolic blood pressure, heart rate, temperature, level of consciousness and use of supplemental oxygen) and hospital variables. The primary outcome was cumulative all-cause mortality during a 90-day follow-up, with mortality assessment monitoring time points at 1, 2, 7, 14, 30 and 90 days from ED attendance. Comparison of performances for 90-day mortality between both scores was carried out by univariate analysis. Results From March to November 2020, we included 2,961 SARS-CoV-2 positive patients (median age 79 years, IQR 66–88), with 49.2% females. The qCSI score provided an AUC ranging from 0.769 (1-day mortality) to 0.749 (90-day mortality), whereas AUCs for NEWS ranging from 0.825 for 1-day mortality to 0.777 for 90-day mortality. At all-time points studied, differences between both scores were statistically significant (p

BackgroundNowadays, 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.MethodsProspective, 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.ResultsThe 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.ConclusionThe use of mSOFA could provide and extra insight regarding the short-term mortality and sepsis diagnostic, backing its recommendation in the prehospital scenario.

IntroductionCOVID-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.MethodsA 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.ResultsBetween 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].ConclusionThe 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.

(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.

Introduction The aim of the study was to compare the Quick Sequential Organ Failure Assessment tools (qSOFA), and Quick Sequential Organ Failure Assessment-Lactate (LqSOFA) to detect pre-hospital sepsis among patients with or without suspicion of infection. Material and methods Multicenter prospective cohort study in non-traumatic patients attended by Advanced Life Support in the prehospital environment and transferred to the hospital. We collected demographic, physiological, clinical, and analytical variables, main diagnosis, hospital admission and clinical diagnosis of sepsis. Primary outcome was the clinical diagnosis of sepsis in the hospital. Results Between March 1, 2018 and March 31, 2019, we included in our study 1548 participants of whom 82 (5.3%) received a final hospital diagnosis of sepsis. The qSOFA presented an area under the receiver operating characteristic curve (AUROC) to detect sepsis in patients with suspicion and without suspicion of infection of 0.757 (95% CI: 0.65–0.81), compared to LqSOFA with an AUROC to detect sepsis of 0.784 (95% CI: 0.72–0.84). In the group of patients with suspected infection, the LqSOFA for a 2-point cut-off presented an AUROC of 0.773 (95% CI: 0.69–0.85), with an excellent sensitivity of 92.6% (95% CI: 83.9–96.8) and an odds ratio of 8.23 (95% CI: 3.09–21.92). Conclusions An appropriate strategy for reducing the morbidity and mortality from sepsis must necessarily include the prompt identification of this time-dependent pathology by using all the tools at our disposal. The qSOFA and LqSOFA can be used in the prehospital environment and help the diagnosis of suspected sepsis in patients with medical pathology, highlighting the predictive capacity of LqSOFA in the group of patients with suspected infection.

The ability of COVID-19 to compromise the respiratory system has generated a substantial proportion of critically ill patients in need of invasive mechanical ventilation (IMV). The objective of this paper was to analyze the prognostic ability of the pulse oximetry saturation/fraction of inspired oxygen ratio (SpO2/FiO2) and the ratio of SpO2/FiO2 to the respiratory rate–ROX index–as predictors of IMV in an emergency department in confirmed COVID-19 patients. A multicenter, retrospective cohort study was carried out in four provinces of Spain between March and November 2020. The discriminative power of the predictive variable was assessed through a prediction model trained using a derivation sub-cohort and evaluated by the area under the curve (AUC) of the receiver operating characteristic (ROC) on the validation sub-cohort. A total of 2040 patients were included in the study. The IMV rate was 10.1%, with an in-hospital mortality rate of 35.3%. The performance of the SpO2/FiO2 ratio was better than the ROX index–AUC = 0.801 (95% CI 0.746–0.855) and AUC = 0.725 (95% CI 0.652–0.798), respectively. In fact, a direct comparison between AUCs resulted in significant differences (p = 0.001). SpO2 to FiO2 ratio is a simple and promising non-invasive tool for predicting risk of IMV in patients infected with COVID-19, and it is realizable in emergency departments.

One of the challenges in the emergency department (ED) is the early identification of patients with a higher risk of clinical deterioration. The objective is to evaluate the prognostic capacity of ΔLA (correlation between prehospital lactate (pLA) and hospital lactate (hLA)) with respect to in-hospital two day mortality. We conducted a pragmatic, multicentric, prospective and blinded-endpoint study in adults who consecutively attended and were transported in advanced life support with high priority from the scene to the ED. The corresponding area under the receiver operating characteristics curve (AUROC) was obtained for each of the outcomes. In total, 1341 cases met the inclusion criteria. The median age was 71 years (interquartile range: 54–83 years), with 38.9% (521 cases) females. The total 2 day mortality included 106 patients (7.9%). The prognostic precision for the 2 day mortality of pLA and hLA was good, with an AUROC of 0.800 (95% CI: 0.74–0.85; p < 0.001) and 0.819 (95% CI: 0.76–0.86; p < 0.001), respectively. Of all patients, 31.5% (422 cases) had an ΔLA with a decrease of

Background: Chronic non-cancer pain (CNCP) is one of the leading causes of disability. The use of strong opioids (SOs) in the management of CNCP is increasing, although evidence supporting their use remains limited. Primary care (PC) plays a key role in this context. Objectives: Our objectives were to determine the prevalence and profile of patients using SOs for CNCP in PC consultations in Valladolid in 2022, and to describe the consumption of SO prescribed for CNCP from 2020 to 2023. Methods: We conducted a descriptive and retrospective study using data extracted from the Pharmaceutical Consumption Information System of Castilla y León. Patients in Valladolid with SO use for more than three months due to CNCP were analyzed. Sociodemographic and clinical characteristics of these patients in 2022 were described. The number of defined daily doses (nº DDDs) and costs from 2020 to 2023 were analyzed. Results: A total of 3642 patients were included (0.7% of the population of Valladolid), 71.8% of whom were women. Of the patients, 62.4% were aged 70 or older, 39.8% lived in rural areas, and 9.9% resided in nursing homes. The most frequently prescribed SOs in nº DDDs were fentanyl and tapentadol. The highest consumption in nº DDDs was in patients who lived in nursing homes, were over 70 years old and were resident in rural areas. The number of DDDs from 2020 to 2023 for SOs in DCNO increased by 41%. Conclusions: In total, 0.7% of the population of Valladolid consumes SOs for CNCP, mostly women and people over 70 years old. The consumption of strong opioids in DDDs grew by 41% from 2020 to 2023.

Aim of the Study. To evaluate the ability of the prehospital National Early Warning Score 2 scale (NEWS2) to predict early mortality (within 48 hours) after the index event based on the triage priority assigned for any cause in the emergency department. Methods. This is a multicenter longitudinal observational cohort study on patients attending Advanced Life Support units and transferred to the emergency department of their reference hospital. We collected demographic, physiological, and clinical variables, main diagnosis, and hospital triage level as well as mortality. The main outcome variable was mortality from any cause within two days of the index event. Results. Between April 1 and November 30, 2018, a total of 1054 patients were included in our study. Early mortality within the first 48 hours after the index event affected 55 patients (5.2%), of which 23 cases (41.8%) had causes of cardiovascular origin. In the stratification by triage levels, the AUC of the NEWS2 obtained for short-term mortality varied between 0.77 (95% CI: 0.65-0.89) for level I and 0.94 (95% CI: 0.79-1) for level III. Conclusions. The Prehospital Emergency Medical Services should evaluate the implementation of the NEWS2 as a routine evaluation, which, together with the structured hospital triage system, effectively serves to predict early mortality and detect high-risk patients.

Introduction. Certain professions, such as those related to emergency services, have usually been performed by men, progressively incorporating women into these professions. The main objective of our study was to determine, according to gender, how the use of level D biohazard personal protection equipment (PPE) affects emergency professionals during the performance of resuscitation. Materials and Methods. An uncontrolled quasi-experimental study was performed on 96 volunteers selected by means of random sampling stratified by gender. Baseline and final vital signs of the assessment activity were analyzed. This activity involves volunteers performing a simulated resuscitation in a controlled environment whilst wearing personal protective suits in a biohazard situation. Results. Analyzing the physiological tolerance pattern parameter by parameter, and according to gender, through a univariate model, we can observe that there is no interaction between tolerance and gender; that is, having good or bad tolerance does not depend on gender. Conclusion. This specialized skilled work can be performed by any properly trained professional.