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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.
Subject(s)
Ambulances , COVID-19 , Adult , Humans , Cohort Studies , Prospective Studies , Risk FactorsABSTRACT
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.
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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.
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Objective. To characterize phenotypes of prehospital patients with COVID-19 to facilitate early identification of at-risk groups. 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. Conclusions. 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. Objetivos. Desarrollar un fenotipado prehospitalario de pacientes con COVID-19 que permita una identificación temprana de los grupos de riesgo. Método. 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.
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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.
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Objective. To develop and validate a scale to stratify risk of 2-day mortality based on data collected during calls to an emergency dispatch center from patients with suspected coronavirus disease 2019 (COVID-19). Methods. Retrospective multicenter study of consecutive patients over the age of 18 years with suspected COVID-19 who were transported from home over the course of 3 months after telephone interviews with dispatchers. We analyzed clinical and epidemiologic variables and comorbidities in relation to death within 2 days of the call. Using data from the development cohort, we built a risk model by means of logistic regression analysis of categorical variables that were independently associated with 2-day mortality. The scale was validated first in a validation cohort in the same province and then in a cohort in a different province. Results. A total of 2320 patients were included. The mean age was 79 years, and 49.8% were women. The overall 2-day mortality rate was 22.6% (376 deaths of patients with severe acute respiratory syndrome coronavirus 2 infection). The model included the following factors: age, location (rural location as a protective factor), institutionalization, desaturation, lung sounds (rhonchi), and altered mental status. The area under the receiver operating characteristic curve for death within 2 days was 0.763 (95% CI, 0.725-0.802;P < .001). Mortality in patients at high risk (more than 2.4 points on the scale) was 60%. Conclusions. This risk scale derived from information available to an emergency dispatch center is applicable to patients with suspected COVID-19. It can stratify patients by risk of early death (within 2 days), possibly helping with decision making regarding whether to transport from home or what means of transport to use, and destination. Objetivo. Derivar y validar una escala basada en variables recogidas durante la llamada a un centro coordinador de urgencias (CCU) que permita estratificar el riesgo de mortalidad a 2 días en pacientes con sospecha de enfermedad por COVID-19. Método. Estudio multicéntrico retrospectivo que incluyó a los pacientes consecutivos ≥ 18 años durante 3 meses, catalogados como caso sospechoso de COVID-19 después de la entrevista telefónica del CCU y que precisaron evacuación. Se analizaron variables clínico-epidemiológicas, comorbilidades y resultado de muerte a los 2 días. Se derivó una escala con las variables categóricas asociadas de forma independiente con la mortalidad a 2 días mediante regresión logística, en la cohorte de derivación. La escala se validó mediante una cohorte de validación y otra de revalidación obtenida en una provincia distinta. Resultados. Se incluyeron 2.320 pacientes (edad mediana 79 años, 49,8% mujeres). La mortalidad global fue del 22,6% (376 casos en pacientes con SARS-CoV-2). El modelo incluyó edad, localización (zona rural como variable protectora), institucionalización, desaturación, roncus, taquipnea y alteración del nivel de conciencia. El área bajo la curva (ABC) para la mortalidad a 2 días fue de 0,763 (IC 95%: 0,725-0,802;p < 0,001). La mortalidad en los pacientes de alto riesgo (> 2,4 puntos) fue del 60%. Conclusiones. La escala, derivada a través de información obtenida con datos del CCU, es aplicable a pacientes con sospecha de infección por COVID-19, estratifica el riesgo de mortalidad precoz (menos de 2 días) y puede ser una herramienta que ayude en la toma de decisiones, referidas a su evacuación, destino o vector de transporte.
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Introduction: Prognosis of Coronavirus disease 2019 (Covid-19) patients with vascular risk factors, and certain comorbidities is worse. The impact of chronic neurological disorders (CND) on prognosis is unclear. We evaluated if the presence of CND in Covid-19 patients is a predictor of a higher in-hospital mortality. As secondary endpoints, we analyzed the association between CND, Covid-19 severity, and laboratory abnormalities during admission. Methods: Retrospective cohort study that included all the consecutive hospitalized patients with confirmed Covid-19 disease from March 8th to April 11th, 2020. The study setting was Hospital Clínico, tertiary academic hospital from Valladolid. CND was defined as those neurological conditions causing permanent disability. We assessed demography, clinical variables, Covid-19 severity, laboratory parameters and outcome. The primary endpoint was in-hospital all-cause mortality, evaluated by multivariate cox-regression log rank test. We analyzed the association between CND, covid-19 severity and laboratory abnormalities. Results: We included 576 patients, 43.3% female, aged 67.2 years in mean. CND were present in 105 (18.3%) patients. Patients with CND were older, more disabled, had more vascular risk factors and comorbidities and fewer clinical symptoms of Covid-19. They presented 1.43 days earlier to the emergency department. Need of ventilation support was similar. Presence of CND was an independent predictor of death (HR 2.129, 95% CI: 1.382-3.280) but not a severer Covid-19 disease (OR: 1.75, 95% CI: 0.970-3.158). Frequency of laboratory abnormalities was similar, except for procalcitonin and INR. Conclusions: The presence of CND is an independent predictor of mortality in hospitalized Covid-19 patients. That was not explained neither by a worse immune response to Covid-19 nor by differences in the level of care received by patients with CND.