Predictors of Change in Dyspnea Level in Acute Exacerbations of COPD.

The aim of this study was to identify factors related to changes in dyspnoea level in the acute and short-term periods after acute exacerbation of chronic obstructive pulmonary disease. This was a prospective cohort study of patients with symptoms of acute chronic obstructive pulmonary disease exacerbation who attended one of 17 hospitals in Spain between June 2008 and September 2010. Clinical data and patient reported measures (dyspnoea level, health-related quality of life, anxiety and depression levels, capacity to perform physical activity) were collected from arrival to the emergency department up to a week after the visit in discharged patients and to discharge in admitted patients (short term). Main outcomes were time course of dyspnoea over the acute (first 24 hours) and short-term periods, mortality and readmission within 2 months of the index episode. Changes in dyspnoea in both periods were related capacity to perform physical activity as well as clinical variables. Short-term changes in dyspnoea were also related to dyspnoea at 24 hours after the ED visit, and anxiety and depression levels. Dyspnoea worsening or failing to improve over the studied periods was associated with poor clinical outcomes. Patient-reported measures are predictive of changes in dyspnoea level.

The Use of Pulse Oximetry to Determine Hypoxemia in Acute Exacerbations of COPD.

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.

External validity of a prognostic score for acute heart failure based on the Epidemiology of Acute Heart Failure in Emergency Departments registry: the EAHFE-3D scale. / Validación externa de la escala EAHFE-3D para la evaluación del pronóstico en insuficiencia cardiaca aguda.

OBJECTIVES: To validate the EAHFE-3D scale, based on the Acute Heart Failure in Emergency Departments registry, in a cohort of patients attended for acute heart failure. MATERIAL AND METHODS: Study of a multipurpose cohort of patients with acute heart failure in 3 hospitals in the Basque Country between 2011 and 2013. We extracted age, baseline New York Heart Association functional class, systolic blood pressure, baseline arterial oxygen saturation, sodium level in blood, and emergency department treatments (noninvasive mechanical ventilation, use of inotropic agents and vasopressors) in order to calculate each patient's EAHFE-3D score. The main outcome variable was mortality within 3 days of arrival at the emergency department. RESULTS: The patient sample for score validation consisted of 717 patients with complete information. The model's intercept was 0.5 (95% CI, -2.7 to 3.7) and the slope was 1.3 (95% CI, 0.4 to 2.2). The area under the receiver operating characteristic curve was 0.76 (95% CI, 0.58 to 0.94). CONCLUSION: The EAHFE-3D scale's ability to discriminate was good in this patient sample and similar to that reported by the authors who developed the scale; however, calibration was poor. The scale should be studied further before it is applied in clinical practice.

OBJETIVO: Validar la escala pronóstica EAHFE-3D en una cohorte externa de pacientes atendidos por insuficiencia cardiaca aguda (ICA). METODO: Estudio de cohortes multipropósito que incluyó pacientes con ICA en 3 centros hospitalarios del País Vasco entre 2011 y 2013. Se recogieron los datos demográficos (edad), clase funcional basal (New York Heart Association), clínicos (presión arterial sistólica y saturación de oxígeno basal), analíticos (natremia) y terapéuticos (ventilación mecánica no invasiva e inotrópicos y vasopresores) en el servicio de urgencias (SU) necesarios para el cálculo de la escala EAHFE-3D. La variable de resultado principal fue la mortalidad a tres días de la llegada al SU. RESULTADOS: Analizamos 717 pacientes con información completa. El intercepto ß el modelo fue 0,5 (IC95%: ­2,7- 3,7) y la pendiente α fue de 1,3 (IC95%: 0,4-2,2). El área bajo la curva AUC (ROC) fue 0,76 (IC95%: 0,58-0,94). CONCLUSIONES: La escala EAHFE-3D presentó una buena capacidad predictiva en nuestra muestra, no diferente a la obtenida por los autores originales, aunque no ha mostrado buena calibración. Se recomienda continuar con el proceso de validación antes de ser implementada en la práctica clínica.

Creation and validation of the acute heart failure risk score: AHFRS.

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.

Application of appropriateness criteria for hospitalization in COPD exacerbation.

The IRYSS-COPD appropriateness study was developed in 16 hospitals belonging to the Spanish National Health Service from June 2008 to September 2010 (n = 2,877). The objectives were to apply a set of explicit criteria for the appropriateness of hospital admission created by the RAND/UCLA methodology to patients evaluated in the emergency department (ED) for exacerbations of COPD. This is a prospective cohort study. We explored the relationship between appropriateness of admission as defined by the explicit criteria and the final decision to admit or discharge. A total of 2,877 patients were included for analysis; of these, 1,747 (60.7 %) were admitted and 1,130 (39.3 %) were discharged from the ED to home. Among patients classified by the explicit criteria as appropriate for hospital admission, 81.3 % were admitted, compared with 64.81 % of those classified as uncertain and 48.65 % of those classified as inappropriate for admission. Severity of exacerbation was the most influencing variable in the decision. Application of our explicit criteria for appropriate hospital admission among a large sample of patients experiencing an exacerbation of COPD in the ED setting suggests that these criteria could be used as the basis for clinical decision-making and health-care assessment.

Predictors of short-term rehospitalization following discharge of patients hospitalized with community-acquired pneumonia.

BACKGROUND: Among patients hospitalized for community-acquired pneumonia (CAP), the risk factors for short-term hospital readmission after discharge are unknown. METHODS: We conducted a prospective observational study of 1,117 patients who had been discharged alive after hospitalization for CAP. We collected variables associated with CAP severity at hospital admission, in-hospital clinical evolution, clinical instability factors on hospital discharge, therapy employed during hospitalization, and diagnostic bacteriology. We assessed hospital readmission within 30 days after discharge for the index hospitalization. Risk factors independently associated with 30-day hospital readmission were identified using Cox regression models. RESULTS: Of the 81 patients (7.3%) who were readmitted to the hospital within 30 days, 29 (35.8%) were rehospitalized for pneumonia-related causes. Variables associated with pneumonia-related hospital readmission were treatment failure (hazard ratio [HR], 2.9; 95% CI, 1.2 to 6.8), and one or more instability factors on hospital discharge (HR, 2.8; 95% CI, 1.3 to 6.2). The predictive performance of these variables measured by the area under the curve (AUC) of the receiver operating characteristic was 0.65. Variables associated with pneumonia-unrelated hospital readmission were age >or= 65 years (HR, 4.5; 95% CI, 1.4 to 14.7), Charlson comorbidity index >or= 2 (HR, 1.9; 95% CI, 1.0 to 3.4), and decompensated comorbidities during in-hospital evolution (HR, 3.5; 95% CI, 2.0 to 6.3); the AUC for this model was 0.77. Patients with at least two risk factors were at significantly increased risk of 30-day hospital readmission (pneumonia-related CAP: HR, 9.0; 95% CI, 3.2 to 25.3; pneumonia-unrelated CAP: HR, 5.3; 95% CI, 1.6 to 18.1). CONCLUSIONS: Among patients hospitalized for CAP, different risk factors are associated with hospital readmission related to pneumonia or to other causes. The identification of two different groups of patients who were at high risk of hospital readmission raises the possibility that different management strategies could decrease the rate of hospital readmissions.