ABSTRACT
BACKGROUND: Different variables are playing a role in prognosis of acute heart failure. OBJECTIVES: Our purpose was to create and validate a risk score to predict mortality in patients with a first episode of acute heart failure during the first 2 months after the first hospitalization. DESIGN: This was a prospective cohort study. PARTICIPANTS: We recruited patients diagnosed with a first episode of acute heart failure. MAIN MEASURES: We collected data on sociodemographic characteristics; medical history; symptoms; precipitating factors; signs and symptoms of congestion; echocardiographic parameters; aetiology; vital signs and laboratory findings; and response to initial treatment (yes/no). A Cox proportional hazard regression model was built with mortality during the first 2 months after the index episode as the dependent variable. A risk score is presented. KEY RESULTS: The mortality rate during the first 2 months after a first episode of heart failure was 5%. Age, systolic blood pressure, serum sodium, ejection fraction and blood urea nitrogen were selected in the internal validation, as was right ventricular failure. A risk score was developed. Both the model and the score showed good discrimination and calibration properties when applied to an independent cohort. CONCLUSIONS: Our ESSIC-FEHF risk score showed excellent properties in the derivation cohort and also in a cohort from a different time period. This score is expected to help decision making in patients diagnosed with heart failure for the first time.
Subject(s)
Heart Failure , Hospitalization , Humans , Prognosis , Prospective Studies , Risk Assessment , Risk FactorsABSTRACT
Objetivo. Comparar la evolución de las infecciones del tracto urinario superior (ITUS) atendidas en urgencias que se derivan y tratan en hospitalización a domicilio (HAD) frente a las que ingresan en hospitalización convencional (HC). Método. Estudio prospectivo, cuasiexperimental de pacientes con ITUS atendidos en tres hospitales de Osakidetza-Sistema Vasco de Salud (SVS) entre enero de 2012 y junio de 2013. Los pacientes se dividieron en 2 grupos según destino (ingresados en HAD en HC). Se recogieron datos sociodemográficos, antecedentes nefrourológicos, comorbilidades, factores de riesgo de infección complicada, forma de presentación en urgencias, pruebas diagnósticas realizadas y tratamientos prescritos. La variable de resultado principal fue la mala evolución (complicaciones locales durante el ingreso, recurrencia de la infección o reingreso relacionado con la infección). Se realizó un modelo multivariable de regresión logística para analizar la mala evolución, que incluyó el ingreso en HAD como la variable independiente principal. Resultados. Los pacientes derivados a HAD incluyen una mayor proporción de mujeres (70,6% frente a 57,1%, p = 0,04), con menos ingresos previos (2,4% frente a 9,5%, p = 0,03) y menos criterios de presentar ITUS complicadas (58,7% frente a 83,3%, p < 0,001), en relación a los ingresados en HC. No hubo diferencias en complicaciones entre los dos grupos, excepto en la frecuencia de síndrome confusional que fue inferior en el grupo HAD (8,3% frente a 0,8%, p = 0,007). No se encontraron diferencias en las variables de mala evolución entre los que ingresaron en HC y en HAD. Conclusiones. No hay diferencias en la evolución de los pacientes con ITUS ingresados en HAD comparados con los ingresados en HC (AU)
Objective. To compare outcomes of urinary tract infections (UTIs) in patients referred to a home hospitalization program or admitted to a conventional ward after initial management in the emergency department. Methods. Prospective, quasi-experimental study of patients with UTIs attended in 3 hospital emergency departments in the public health system of the Basque Country, Spain, between January 2012 and June 2013. Patients were assigned to 2 groups according to site of treatment (home or hospital ward) after discharge from the emergency department. We collected sociodemographic data, history of kidney or urologic symptoms, concomitant diseases, risk for complicated UTI, presentation on admission to the emergency department, diagnostic findings, and prescribed treatments. The main outcome was poor clinical course (local complications during hospital or home care, recurrence, or readmission related to UTI. Multivariate logistic modeling was used to analyze factors related to poor clinical course. Home hospitalization was the main independent variable of interest. Results. Patients referred to home hospitalization were more often women (70.6% vs 57.1% men, P=.04). Fewer cases of prior admission were recorded in the group treated at home (2.4% vs 9.5% of hospitalized patients, P=.03). Likewise, fewer home-hospitalization patients had risk factors for complicated UTI (58.7% vs 83.3% in the hospitalized group, P<,001). The only significant difference in complications between the 2 groups was a lower rate of acute confusional state in patients assigned to home hospitalization (0.8% vs 8.3% in hospitalized patients, P=.007). The frequency of poor clinical course was similar in home-hospitalized and ward-admitted patients. Conclusion. The clinical course of UTI is similar whether patients are hospitalized after emergency department management or discharged to a home hospitalization program (AU)
Subject(s)
Humans , Male , Female , Middle Aged , Aged , Urinary Tract Infections/therapy , Hospitalization/trends , Ambulatory Care/methods , Emergency Medical Services/methods , Clinical Evolution/methods , Drug Resistance, Multiple , Evaluation of the Efficacy-Effectiveness of Interventions , Comorbidity , Prospective Studies , Analysis of Variance , Risk FactorsABSTRACT
Our aims were to create and validate a clinical decision rule to assess severity in acute heart failure. We conducted a prospective cohort study of patients with symptoms of acute heart failure who attended the emergency departments (EDs) of three hospitals between April 2011 and April 2013. The following data were collected on arrival to or during the stay in the ED: baseline severity of symptoms; presence of decompensated comorbidities; number of hospital admissions/visits to EDs for acute heart failure during the previous 24 months; triggers of the exacerbation; clinical signs and symptoms; results of ancillary tests requested in the ED; treatments prescribed; and response to the initial treatment in the ED. The main outcome was poor course during the acute phase, in-hospital for admitted patients and during the first week following the ED visit for discharged patients, this being a composite endpoint that included death, admission to an intensive care unit, need for invasive mechanical ventilation, cardiac arrest and use of non-invasive mechanical ventilation. Multivariate logistic regression models were developed. Predictors of poor course in acute heart failure were oedema on chest radiography, visits to the ED and/or admissions in the previous two years, and levels of glycemia and blood urea nitrogen (areas under the curve of 0.83 in the derivation sample, and 0.82 in the validation sample). Four clinical predictors available in the ED can be used to create a simple score to predict poor course in acute heart failure.Clinical Trials.gov ID: NCT02437058.
Subject(s)
Heart Failure/diagnosis , Prognosis , Risk Assessment/methods , Risk Assessment/standards , Aged , Aged, 80 and over , Cohort Studies , Emergency Service, Hospital/organization & administration , Emergency Service, Hospital/statistics & numerical data , Female , Hospitalization/statistics & numerical data , Humans , Intensive Care Units/statistics & numerical data , Logistic Models , Male , Odds Ratio , Patient Outcome Assessment , Prospective Studies , Spain , Validation Studies as TopicABSTRACT
BACKGROUND: There is little evidence that the guideline-recommended oxygen saturation of 92% is the best cut-off point for detecting hypoxemia in COPD exacerbations. OBJECTIVE: To detect and validate pulse oximetry oxygen saturation cut-off values likely to detect hypoxemia in patients with aeCOPD, to explore the correlation between oxygen saturation measured by pulse oximetry and hypoxemia or hypercapnic respiratory failure. METHODOLOGY: Cross-sectional study nested in the IRYSS-COPD study with 2,181 episodes of aeCOPD recruited between 2008 and 2010 in 16 hospitals belonging to the Spanish Public Health System. Data collected include determination of oxygen saturation by pulse oximetry upon arrival in the emergency department (ED), first arterial blood gasometry values, sociodemographic information, background medical history and clinical variables upon ED arrival. Logistic regression models were performed using as the dependent variables hypoxemia (PaO2 < 60 mmHg) and hypercapnic respiratory failure (PaO2 < 60 mmHg and PaCO2 > 45). Optimal cut-off points were calculated. RESULTS: The correlation coefficient between oxygen saturation and pO2 measured by arterial blood gasometry was 0.89. The area under the curve (AUC) for the hypoxemia model was 0.97 (0.96-0.98) and the optimal cut-off point for hypoxemia was an oxygen saturation of 90%. The AUC for hypercapnic respiratory failure was 0.90 (0.87-0.92) and the optimal cut-off point was an oxygen saturation of 88%. CONCLUSIONS: Our results support current recommendations for ordering blood gasometry based on pulse oximetry oxygen saturation cut-offs for hypoxemia. We also provide easy to use formulae to calculate pO2 from oxygen saturation measured by pulse oximetry.
