Study Objectives: Sleep deprivation is known to be associated with insulin resistance and diabetes risk. This study investigated whether 2-week sleep extension in chronically sleep-deprived individuals would improve glucose metabolism. Methods: A crossover study was conducted in volunteers without diabetes who reported sleeping ≤ 6 h/night. They were randomized to maintain their habitual sleep or extend sleep time for 2 weeks, then crossed over after a washout period. Sleep was monitored by actigraphy. Oral glucose tolerance tests (75 g) with insulin levels was performed at the end of each period. Mixed-effect linear regression analysis, adjusting for sequence and period effects, was applied. Results: A total of 21 participants (19 females) with mean (standard deviation) age of 33.1 (6.1) years completed the protocol. Mean sleep duration during habitual sleep was 318.7 (44.3) minutes and the participants extended their sleep by 36.0 (45.2) minutes during sleep extension. The average washout period was 21 (11) days. There were no significant effects of sleep extension on any metabolic parameters. The per-protocol analysis included eight participants who could sleep more than 6 hours during sleep extension (mean sleep duration 396 [25] minutes, extended by 60.1 [28.5] minutes). Among these individuals, sleep extension improved Homeostatic Model Assessment of Insulin Resistance (adjusted mean difference −0.50 [95% confidence interval [CI] −0.89, −0.11, P = .013]), early insulin secretion (insulinogenic index; mean difference 0.39 [95% CI 0.15, 0.63, P = .001]), and β-cell function (disposition index, mean difference 1.07 [95% CI 0.17, 1.97, P = .02]). Conclusions: Sleep extension in chronically sleep-deprived individuals improved glucose metabolism in only those who could objectively extend their sleep to more than 6 h/night. Our findings suggest that a critical amount of sleep is needed to benefit metabolic outcomes.

the correlation between the %CSA<5 and the radionuclide uptake rate visualized by pulmonary perfusion scintigraphy.Results: The %CSA<5 in the obstructed side of the lung after treatment displayed significant improvements after intervention (p = 0.04). Among the 5 cases that underwent pulmonary perfusion scintigraphy before and after the treatment, the radionuclide uptake rate of the obstructed side improved in all patients, whereas the %CSA<5 improved in 4 of the 5 patients.Conclusion: Measurement of the %CSA<5 might be useful to assess the outcome of interventional bronchoscopy. AP384Background and Aim: The diagnostic bronchoscopy in acute hypoxemic patients might result in profound hypoxemia requiring intubation. We aimed to study the effectiveness of non-invasive ventilation (NIV) compared with high-flow nasal cannula (HFNC) in those patients requiring the diagnostic bronchoscopy. The primary end point was the lowest oxygen saturation during the procedure.

Although tracheostomy is a well-accepted procedure for airway management, some early and late complications may occur. Fracture of the tracheostomy tube (TT) is a rare complication, particularly in a patient with long-term use. Herein we report a case of fractured metallic TT migrating into the tracheobronchial tree. Rigid bronchoscopy was performed through the tracheostomy stoma and the fractured tube was successfully removed by a balloon catheter. Appropriate cleaning, routine careful examination, and scheduled replacement of the TT may help prevent this complication.

Background Ventilator-associated pneumonia (VAP) is a common nocosomial infection in intensive care unit (ICU). Local microbiological surveillance of pathogens and resistance patterns for early-onset VAP (EOVAP) and late-onset VAP (LOVAP) will help to choose appropriate empiric antibiotics. Objective To compare the multi-drug resistant (MDR) pathogens, treatment outcomes, and factors associated with hospital mortality of VAP. Method A cross-sectional study between 1 January 2015 and 31 December 2017 at Srinagarind hospital, Khon Kaen University was conducted. The demographic data, causative pathogens, hospital length of stay (LOS), ICU LOS, mechanical ventilator (MV) days, and hospital mortality were retrospectively reviewed. Results One hundred and ninety patients were enrolled; 42 patients (22%) were EOVAP and 148 patients (78%) were LOVAP. Acinetobacter baumannii was the most common pathogen in both groups (50% EOVAP vs 52.7% LOVAP). MDR pathogens were significant greater in LOVAP (81.8%) than EOVAP (61.9%) (p = 0.007). The EOVAP had a significantly better ICU LOS [median (interquartile range, IQR) 20.0 (11.0, 30.0) vs. 26.5 (17.0, 43.0) days], hospital LOS [median (IQR) 26.5 (15.0, 44.0) vs. 35.5 (24.0, 56.0) days] shorter MV days [median (IQR) 14.0 (10.0, 29.0) vs. 23.0 (14.0, 35.5) days] and lower hospital mortality (16.7% vs 35.1%) than LOVAP (p < 0.05). The factor associated with hospital mortality was having simplified acute physiology (SAP) II score ≥ 40 with an adjusted odds ratio (aOR) of 2.22 [95% confidence interval (CI), 1.08–4.54, p = 0.02]. Conclusion LOVAP had significantly higher MDR pathogens, MV days, ICU LOS, hospital LOS and hospital mortality than EOVAP. A broad-spectrum antibiotic to cover MDR pathogens should be considered in LOVAP. The factor associated with hospital mortality of VAP was a SAPII score ≥ 40.

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Frailty is an aging-associated state that increases patients’ vulnerability to disease, and can lead to various adverse outcomes. It is classified as either physical frailty alone or physical frailty in combination with cognitive impairment (cognitive frailty). There are currently limited data available regarding the prevalence and adverse outcomes of frailty in Thailand. This was a cross-sectional study aimed at determining the prevalence of physical and cognitive frailty and their effects on hospitalization and quality of life. Participants were older patients who attended an internal medicine outpatient clinic. Frailty was diagnosed using the Thai Frailty Index. The Thai version of the MoCA was used to evaluate cognitive status. Univariate and multivariate analyses were performed to compare adverse outcomes in terms of poor quality of life and history of admission to hospital between patients with frailty and non-frail patients, and among patients with physical frailty, cognitive frailty, cognitive impairment, and robust (non-frail and non-cognitively impaired) patients. We enrolled 198 participants. The prevalence of physical and cognitive frailty was 28.78% and 20.70%, respectively. When compared with non-frail patients, frailty was associated with hospitalization (adjusted OR 3.01, p = 0.002) but was not significantly related to quality of life (adjusted OR = 1.98, p = 0.09). However, physical and cognitive frailty were associated with fair quality of life when compared with normal patients (adjusted OR = 4.34, p = 0.04 and adjusted OR = 4.28, p = 0.03, respectively). The prevalence of frailty—particularly cognitive frailty—was high. Frailty was associated with adverse outcomes in terms of hospitalization and quality of life.

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