ObjectiveAlthough there is accumulating evidence regarding multimorbidity in Western countries, this information is very limited in Asian countries. This study aimed to estimate population-based, age-specific and gender-specific prevalence and trends of multimorbidity in the Taiwanese population.DesignThis was a cross-sectional study based on claims data (National Health Insurance Research Database, Taiwan).ParticipantsThe participants included a subset of the National Health Insurance Research Database, which contains claims data for two million randomly selected beneficiaries (~10% of the total population) under Taiwan’s mandatory National Health Insurance system.Outcome measurementsThe prevalence of multimorbidity in different age groups and in both sexes in 2003 and 2013 was reported. We analysed data on the prevalence of 20 common diseases in each age group and for both sexes. To investigate the clustering effect, we used graphical displays to analyse the likelihood of co-occurrence with one, two, three, and four or more other diseases for each selected disease in 2003 and 2013.ResultsThe prevalence of multimorbidity (two or more diseases) was 20.07% in 2003 and 30.44% in 2013. In 2013, the prevalence varied between 5.21% in patients aged 20–29 years and 80.96% in those aged 80–89 years. In patients aged 50–79 years, the prevalence of multimorbidity was higher in women than in men. In men, the prevalence of chronic pulmonary disease and cardiovascular-related diseases was predominant, while in women the prevalence of osteoporosis, arthritis, cancer and psychosomatic disorders was predominant. Co-occurring diseases varied across different age and gender groups.ConclusionsThe burden of multimorbidity is increasing and becoming more complex in Taiwan, and it was found to vary across different age and gender groups. Fulfilling the needs of individuals with multimorbidity requires collaborative work between healthcare providers and needs to take the age and gender disparities of multimorbidity into account.

End-tidal carbon dioxide pressure (PetCO(2)) was measured in the neonatal intensive care unit (NICU) to assess its reliability and accuracy in predicting arterial partial pressure of carbon dioxide (PaCO(2)). Arterial blood was drawn for gas analysis and compared with exhaled CO(2) measured by mainstream capnography. In total, 130 PetCO(2)/PaCO(2) comparisons were obtained from 61 patients (20 term and 41 preterm infants). PetCO(2) was significantly different from PaCO(2) (PetCO(2) = 42.3 +/- 10.5 mmHg vs. PaCO(2) = 45.8 +/- 12.3 mmHg, P < 0.001, mean +/- SD). The overall PetCO(2) bias (mean +/- SD) was 3.5 +/- 7.1 mmHg. There was a positive correlation between PetCO(2) and PaCO(2) (n = 130, r = 0.818, P < 0.001) in both term (n = 44, r = 0.779, P < 0.001) and preterm infants (n = 86, r = 0.849, P < 0.001). The PetCO(2) biases (95% CI) were 3.5 +/- 9.0 mmHg (0.8-6.2) in the term group and 3.4 +/- 6.0 mmHg (2.2-4.7) in the preterm group. Therefore, PetCO(2) was a valid and reliable method for monitoring PaCO(2) in neonates, especially preterm infants. This method decreases blood loss and prevents complications associated with arterial catheters. In conclusion, we recommend using mainstream capnography to monitor PetCO(2) instead of measuring PaCO(2) in the NICU.

1. The study provides the evidence that a novel lncRNA IL6-AS1 is highly expressed in COPD and is associated with inflammation. 2. IL6-AS1 acts as the competitive endogenous RNA (ceRNA) to competitively bind to hsa-miR-149-5p to regulate IL-6 expression. 3. IL6-AS1 acts as a guide to promote the gene expression via recruiting EBF1 to the region of the IL-6 promoter.

Background: Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease and its clinically relevant subtypes are not well understood. Which clinical characteristics are more likely to be present among individuals who develop COPD remains to be studied in depth. Therefore, we designed a prospective observational cohort study, entitled the Early Chronic Obstructive Pulmonary Disease (ECOPD) study, to fill this evidence gap. The ECOPD study has four specific aims: (I) identification of characteristics, parameters, and biomarkers that may predict the development of airflow obstruction and annual decline in lung function with normal spirometry; (II) identification of clinically relevant early COPD subtypes; (III) identification of characteristics, parameters, and biomarkers that may predict disease progression in these early COPD subtypes; (IV) development and validation of machine learning models to predict development of airflow obstruction and disease progression.Methods: We will recruit approximately 2,000 participants aged 40-80 years, including approximately 1,000 with COPD [post-bronchodilator forced expiratory volume in 1 second (FEV1)/forced vital capacity (FVC) <0.7] and approximately 1,000 without COPD, using a population-based survey for COPD. We will assess all participants using standard respiratory epidemiological questionnaires, pulmonary function tests [pre-bronchodilator and post-bronchodilator spirometry, and impulse oscillometry (IOS)], health outcomes [modified British Medical Research Council (mMRC) dyspnea scale, COPD assessment test (CAT), COPD clinical questionnaire (CCQ)], inspiratory and expiratory chest computed tomography (CT), and biomarker measurements (blood and urine), as well as satellite remote sensing pollutant exposure measures. Subgroup will additionally complete induced sputum, exercise capacity tests [6-minute walk test (6MWT) and cardiopulmonary exercise testing (CPET)] and home monitoring/personal sampling as pollutant exposure measures. Study procedures will be performed at baseline and every 1 year thereafter. Discussion: The ECOPD study will provide insight into many aspects of early COPD and improve our understanding of COPD development, which may facilitate therapeutic interventions with the potential to ^ ORCID: 0000-0001-6651-634X.