Blood eosinophil count correlates with severity of respiratory failure in life-threatening asthma and predicts risk of subsequent exacerbations.

BACKGROUND: An elevated blood eosinophil count when asthma is stable predicts exacerbations and therapeutic response to corticosteroids or biologics targeting eosinophils. Few studies have examined the prognostic value of blood eosinophils measured at exacerbation. AIM: To elucidate the relationship between a spot blood eosinophil count-measured at the onset of a life-threatening asthma exacerbation-with indices of exacerbation severity and risk of subsequent exacerbations. METHODS: Real-world, retrospective review of all life-threatening asthma cases admitted at 4 public hospitals in Singapore between 2011-2015. We assessed the trends and correlations between blood eosinophil count on admission with arterial blood gas values, duration of mechanical ventilation, and risk of death, hypoxic ischemic encephalopathy or respiratory arrest. Risk of future exacerbations among survivors was modelled using Cox regression and survival curves. RESULTS: There were 376 index life-threatening exacerbations with median blood eosinophil count (5-95th percentiles) of 0.270 × 109 /L (0-1.410 × 109 /L). Arterial pH decreased and PCO2 increased with increasing eosinophil count. Duration of mechanical ventilation and risk of death, hypoxic ischaemic encephalopathy or respiratory arrest did not vary with eosinophils. Among 329 survivors who were followed-up over a median of 52 months, blood eosinophils ≥1.200 × 109 /L was associated with an increased hazard of emergency visits and/or admissions for asthma (hazard ratio 1.8, 95% confidence interval 1.1-2.9, P = .02). CONCLUSION: In this study of life-threatening asthma, we found that a spot blood eosinophil count correlates with severity of respiratory failure and predicts risk of subsequent exacerbations.

A review of psychological dysfunction in asthma: affective, behavioral and cognitive factors.

BACKGROUND: The research on psychological dysfunction in asthma is extensive but heterogeneous. We undertook a narrative review about the effects of psychological dysfunction on asthma. METHODS: Electronic searches of MEDLINE, EMBASE, CINAHL and the Cochrane Library were conducted, supplemented by hand-searching bibliographies and seeking expert opinion. RESULTS: The impact of psychological factors on asthma can be classified according to dysfunction in the domains of affect, behavior and cognition. Affective or emotional disturbance may lead to poor asthma control by directly modulating disease activity. Maladaptive behaviors may occur in asthma patients. These include maladaptive breathing behaviors, such as impaired voluntary drive to breathe and dysfunctional breathing, as well as impaired asthma health behaviors, that is, a coordinated range of activities performed to maintain good disease control. Dysfunctional cognitions (thoughts and beliefs) about asthma and impaired cognitive processing of the perception of dyspnea are associated with poorly controlled disease and asthma deaths, respectively. The three domains of psychological dysfunction are often closely intertwined, leading to vicious circles. CONCLUSIONS: We have conceptualized psychological dysfunction in asthma using a framework consisting of affect, behavior and cognition. Their influences are intertwined and complex. Future research should focus on the formulation of a psychological assessment tool based on this framework and evaluating its efficacy in improving asthma outcomes.

Evaluation of multi-component interventions for prevention of nosocomial pneumonia in older adults: a randomized, controlled trial.

AIMS: To evaluate the efficacy of multi-component interventions for prevention of hospital-acquired pneumonia in older patients hospitalized in geriatric wards. METHODS: A randomized, parallel-group, controlled trial was undertaken in patients aged 65 and above who were admitted to a tertiary hospital geriatric unit from January 1, 2016 to June 30, 2018 for an acute non-respiratory illness. Participants were randomized by to receive either a multi-component intervention (consisting of reverse Trendelenburg position, dysphagia screening, oral care and vaccinations), or usual care. The outcome measures were the proportion of patients who developed hospital-acquired pneumonia during hospitalisation, and mean time from randomization to the next hospitalisation due to respiratory infections in 1 year. RESULTS: A total of 123 participants (median age, 85; 43.1% male) were randomized, (n = 59) to intervention group and (n = 64) to control group. The multi-component interventions did not significantly reduce the incidence of hospital-acquired pneumonia but did increase the mean time to next hospitalisation due to respiratory infection (11.5 months vs. 9.5 months; P = 0.049), and reduced the risk of hospitalisation in 1 year (18.6% vs. 34.4%; P = 0.049). Implementation of multi-component interventions increased diagnoses of oropharyngeal dysphagia (35.6% vs. 20.3%; P < 0.001) and improved the influenza (54.5% vs 17.2%; P < 0.001) and pneumococcal vaccination rates (52.5% vs. 20.3%; P < 0.001). CONCLUSIONS: The nosocomial pneumonia multi-component intervention did not significantly reduce the incidence of hospital-acquired pneumonia during hospitalisation but reduce subsequent hospitalisations for respiratory infections. CLINICAL TRIAL REGISTRATION: ClinicalTrial.gov, NCT04347395.

A clinical prediction model for hospitalized COPD exacerbations based on "treatable traits".

Background: Assessing risk of future exacerbations is an important component in COPD management. History of exacerbation is a strong and independent predictor of future exacerbations, and the criterion of ≥2 nonhospitalized or ≥1 hospitalized exacerbation is often used to identify high-risk patients in whom therapy should be intensified. However, other factors or "treatable traits" also contribute to risk of exacerbation. Objective: The objective of the study was to develop and externally validate a novel clinical prediction model for risk of hospitalized COPD exacerbations based on both exacerbation history and treatable traits. Patients and methods: A total of 237 patients from the COPD Registry of Changi General Hospital, Singapore, aged 75±9 years and with mean post-bronchodilator FEV1 60%±20% predicted, formed the derivation cohort. Hospitalized exacerbation rate was modeled using zero-inflated negative binomial regression. Calibration was assessed by graphically comparing the agreement between predicted and observed annual hospitalized exacerbation rates. Predictive (discriminative) accuracy of the model for identifying high-risk patients (defined as experiencing ≥1 hospitalized exacerbations) was assessed with area under the curve (AUC) and receiver operating characteristics analyses, and compared to other existing risk indices. We externally validated the prediction model using a multicenter dataset comprising 419 COPD patients. Results: The final model included hospitalized exacerbation rate in the previous year, history of acute invasive/noninvasive ventilation, coronary artery disease, bronchiectasis, and sputum nontuberculous mycobacteria isolation. There was excellent agreement between predicted and observed annual hospitalized exacerbation rates. AUC was 0.789 indicating good discriminative accuracy, and was significantly higher than the AUC of the Global Initiative for Chronic Obstructive Lung Disease (GOLD) risk assessment criterion (history of ≥1 hospitalized exacerbation in the previous year) and the age, dyspnea, and obstruction index. When applied to the independent multicenter validation cohort, the model was well-calibrated and discrimination was good. Conclusion: We have derived and externally validated a novel risk prediction model for COPD hospitalizations which outperforms several other risk indices. Our model incorporates several treatable traits which can be targeted for intervention to reduce risk of future hospitalized exacerbations.