IntroductionThe COPD bacteriome associates with disease severity, exacerbations, and mortality. While COPD patients are susceptible to fungal sensitisation, the role of the fungal mycobiome remains uncertain.MethodsWe report the largest multicenter evaluation of the COPD airway mycobiome to date including participants from Asia (Singapore and Malaysia) and the United Kingdom (Scotland) when stable (n=337) and during exacerbations (n=66) as well as non-diseased controls (n=47). Longitudinal mycobiome analyses performed during and following COPD exacerbations (n=34) were examined in terms of exacerbation frequency, two-year mortality, and the occurrence of serum specific-IgE against selected fungi.ResultsA distinct mycobiome profile is observed in COPD compared to controls evidenced by increased alpha diversity (Shannon-index) (p<0.001). Significant airway mycobiome differences including greater inter-fungal interaction (by co-occurrence) characterise very frequent COPD exacerbators (≥3 exacerbations per year) (PERMANOVA, adjusted p<0.001). Longitudinal analyses during exacerbations and following treatment with antibiotics and corticosteroids did not reveal any significant change in airway mycobiome profile. Unsupervised clustering resulted in two clinically distinct COPD groups, (1) with increased symptoms (CAT score) and Saccharomyces dominance and (2) with very frequent exacerbations and higher mortality characterised by Aspergillus, Penicillium and Curvularia with a concomitant increase in serum specific IgE levels against the same fungi. During acute exacerbations of COPD, lower fungal diversity associates with higher two-year mortality.ConclusionThe airway mycobiome in COPD is characterised by specific fungal genera associated with exacerbations and increased mortality.

IntroductionAllergic sensitisation to fungi such as Aspergillus are associated to poor clinical outcomes in asthma, bronchiectasis and cystic fibrosis, however, clinical relevance in COPD remains unclear.MethodsPatients with stable COPD (n=446) and non-diseased controls (n=51) were prospectively recruited across three countries (Singapore, Malaysia and Hong Kong) and screened against a comprehensive allergen panel including house dust mites, pollens, cockroach and fungi. For the first time, using a metagenomics approach, we assess outdoor and indoor environmental allergen exposure in COPD. We identify key fungi in outdoor air and develop specific-IgE assays against the top culturable fungi, linking sensitisation responses to COPD outcomes. Indoor air and surface allergens were prospectively evaluated by metagenomics in the homes of n=11 COPD patients and linked to clinical outcome.ResultsHigh frequencies of sensitisation to a broad range of allergens occurs in COPD. Fungal sensitisation associates with frequent exacerbations, and, unsupervised clustering reveals a “highly sensitised fungal predominant” sub-group demonstrating significant symptomatology, frequent exacerbations and poor lung function. Outdoor and indoor environments serve as important reservoirs of fungal allergen exposure in COPD, and, promote a sensitisation response to outdoor air fungi. Indoor (home) environments with high fungal allergens associate with greater COPD symptoms and poorer lung function illustrating the importance of environmental exposures on clinical outcomes in COPD.ConclusionFungal sensitisation is prevalent in COPD and associates with frequent exacerbations representing a potential treatable trait. Outdoor and indoor (home) environments represent a key source of fungal allergen exposure, amenable to intervention, in “sensitised” COPD.

Dexmedetomidine can ameliorate the postoperative cognitive functions of elder patients who received the laparoscopic ovarian cystectomy under general anesthesia, and effectively decrease the incidence rate of POCD without any obvious or severe adverse reaction. Thus, it can serve as a kind of adjuvant drug for general anesthesia in clinical practice.

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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 FEV 1 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.