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BackgroundGastroesophageal reflux disease (GERD) is one of the most common causes of chronic cough and a potential risk factor for exacerbation of chronic obstructive pulmonary disease (COPD). The aim of this study was to investigate the prevalence and risk factors of GERD in patients with COPD and association between GERD and COPD exacerbation.MethodsData were collected from the National Health Insurance Database of Korea. The subjects were 40 years old and older, who had COPD as primary or secondary diagnosis codes and utilized health care resource to receive prescriptions of COPD medication at least twice in 2009. Univariate logistic regression was performed to understand the relationship between COPD and GERD, and multiple logistic regression analysis was performed with adjustment for several confounding factors.ResultsThe prevalence of GERD in COPD patients was 28% (39,987/141,057). Old age, female gender, medical aid insurance type, hospitalization, and emergency room (ER) visit were associated with GERD. Most of COPD medications except inhaled muscarinic antagonists were associated with GERD. The logistic regression analysis showed that the presence of GERD was associated with increased risk of hospitalization (OR 1.54, CI 1.50 to 1.58, p<0.001) and frequent ER visits (OR 1.55, CI 1.48 to 1.62, p<0.001).ConclusionsThe prevalence of GERD in patients with COPD was high. Old age, female gender, medical aid insurance type, and many COPD medications except inhaled muscarinic antagonists were associated with GERD. The presence of GERD was associated with COPD exacerbation.

Highlights 1 • Reports a large 3D benchmark study of pore-scale modeling methods 2 • Codes and methods varied widely in complexity and computational 3 demand 4 • Both macroscopic and local measures of flow and solute transport were 5 evaluated 6 • Comparisons were generally favorable among the various methods 7 • Differences observed support method selection depending on problem 8 context 9 Abstract 21Multiple numerical approaches have been developed to simulate porous media fluid flow and solute transport at the pore scale. These include 1) methods that explicitly model the three-dimensional geometry of pore spaces and 2) methods that conceptualize the pore space as a topologically consistent set of stylized pore bodies and pore throats. In previous work we validated a model of the first type, using computational fluid dynamics (CFD) codes employing standard finite volume method (FVM), against magnetic resonance velocimetry (MRV) measurements of pore-scale velocities. Here we expand that validation to include additional models of the first type based on the lattice Boltzmann method (LBM) and smoothed particle hydrodynamics (SPH), as well as a model of the second type, a pore-network model (PNM).The PNM approach used in the current study was recently improved and demonstrated to accurately simulate solute transport in a two-dimensional experiment. While the PNM approach is computationally much less demanding than direct numerical simulation methods, the effect of conceptualizing complex three-dimensional pore geometries on solute transport in the manner of PNMs has not been fully determined. We apply all four approaches (FVM-based CFD, LBM, SPH and PNM) to simulate pore-scale velocity distributions and (for capable codes) nonreactive solute transport, and intercompare the model results. Comparisons are drawn both in terms of macroscopic variables (e.g., permeability, solute breakthrough curves) and microscopic variables (e.g., local velocities and concentrations). Generally good agreement was achieved among the various approaches, but some differences were observed depending on the model context. The intercomparison work was challenging because of variable capabilities of the codes, and inspired some code enhancements to allow consistent comparison of flow and transport simulations across the full suite of methods. This study provides support for confidence in a variety of pore-scale modeling methods, and motivates further development and application of pore-scale simulation methods.

The purposes of this study were to assess hospital foodservice quality and to identify causes of quality problems and improvement strategies. Based on the review of literature, hospital foodservice quality was defined and the Hospital Foodservice Quality model was presented. The study was conducted in two steps. In Step 1, nutritional standards specified on diet manuals and nutrients of planned menus, served meals, and consumed meals for regular, diabetic, and low-sodium diets were assessed in three general hospitals. Quality problems were found in all three hospitals since patients consumed less than their nutritional requirements. Considering the effects of four gaps in the Hospital Foodservice Quality model, Gaps 3 and 4 were selected as critical control points (CCPs) for hospital foodservice quality management. In Step 2, the causes of the gaps and improvement strategies at CCPs were labeled as "quality hazards" and "corrective actions", respectively and were identified using a case study. At Gap 3, inaccurate forecasting and a lack of control during production were identified as quality hazards and corrective actions proposed were establishing an accurate forecasting system, improving standardized recipes, emphasizing the use of standardized recipes, and conducting employee training. At Gap 4, quality hazards were menus of low preferences, inconsistency of menu quality, a lack of menu variety, improper food temperatures, and patients' lack of understanding of their nutritional requirements. To reduce Gap 4, the dietary departments should conduct patient surveys on menu preferences on a regular basis, develop new menus, especially for therapeutic diets, maintain food temperatures during distribution, provide more choices, conduct meal rounds, and provide nutrition education and counseling. The Hospital Foodservice Quality Model was a useful tool for identifying causes of the foodservice quality problems and improvement strategies from a holistic point of view.

BackgroundPreserved ratio impaired spirometry (PRISm) is an incompletely understood respiratory condition. We investigated the incidence and significant predictive factors of chronic obstructive pulmonary disease (COPD) in PRISm patients.MethodsFrom 11,922 subjects registered in the Korea National Health and Nutrition Examination Survey, never or light smokers, young subjects, and those already medically diagnosed with COPD (defined by ICD-10 code and prescribed medication) were excluded. The 2666 remaining subjects were categorized into PRISm (normal forced expiratory volume in the first second [FEV1]/force vital capacity [FVC] [≥ 0.7] and low FEV1 (< 80%); n = 313); normal (n = 1666); and unrevealed COPD groups (FEV1/FVC ratio <  0.7; n = 687). These groups were compared using matched Health Insurance Review and Assessment Service data over a 3-year follow-up.ResultsCOPD incidence in PRISm patients (17/1000 person-year [PY]) was higher than that in normal subjects (4.3/1000 PY; P <  0.001), but lower than that in unrevealed COPD patients (45/1000 PY; P < 0.001). PRISm patients visited hospitals, took COPD medication, and incurred hospitalization costs more frequently than normal subjects, but less frequently than unrevealed COPD patients. In the overall sample, age, FVC, FEV1, dyspnea, and wheezing were significant predictors of COPD, but in PRISm patients, only age (OR, 1.14; P = 0.002) and wheezing (OR, 4.56; P = 0.04) were significant predictors.ConclusionPRISm patients are likely to develop COPD, and should be monitored carefully, especially older patients and those with wheezing, regardless of lung function.