INTRODUCTIONThe exposed section of a traditional nasogastric (NG) tube can interfere with patients' social activities and thereby result in distress. This study was conducted to evaluate the feasibility and safety of a novel two-piece NG tube for patients with dysphagia.

METHODSTen patients with dysphagia were recruited between November 2011 and May 2012. Patients who were unconscious or in critical condition, had a traditional NG tube < 50 cm or > 60 cm in fixed length, or were unable to follow instructions or sign consent forms were excluded. The two-piece NG tube, which was placed in the patients for one week, comprised a removable external tube that can be joined to an internal tube via a T-connector, which was placed close to the naris. Events related to safety (e.g. nasal pressure sores, number of unplanned extubation, displacement and spontaneous migration of the NG tube, other unpredictable injuries) and effectiveness (e.g. liquid food spills, tube obstruction, perfusion rate, other adverse circumstances) were assessed daily.

RESULTSAll patients received feeding without complication using the two-piece NG tube and none experienced premature removal of the tube. No serious NG tube complications or malfunctions were observed.

CONCLUSIONThe results of this study indicate that the two-piece NG feeding tube is a feasible option for patients with dysphagia. Future improvements to the connector may help enhance its performance. A rigorous randomised controlled trial to examine the effects of the two-piece NG tube on patients' quality of life and quality of medical care is being planned.

Aged ; Aged, 80 and over ; Deglutition Disorders ; therapy ; Enteral Nutrition ; instrumentation ; methods ; Equipment Design ; Female ; Humans ; Intubation, Gastrointestinal ; adverse effects ; methods ; Male ; Middle Aged

Objectives: This study aimed to present the Asia-Pacific consensus on long-term and sequential therapy for osteoporosis, offering evidence-based recommendations for the effective management of this chronic condition.The primary focus is on achieving optimal fracture prevention through a comprehensive, individualized approach. Methods: A panel of experts convened to develop consensus statements by synthesizing the current literature and leveraging clinical expertise. The review encompassed long-term anti-osteoporosis medication goals, first-line treatments for individuals at very high fracture risk, and the strategic integration of anabolic and anti resorptive agents in sequential therapy approaches. Results: The panelists reached a consensus on 12 statements. Key recommendations included advocating for anabolic agents as the first-line treatment for individuals at very high fracture risk and transitioning to anti resorptive agents following the completion of anabolic therapy. Anabolic therapy remains an option for in dividuals experiencing new fractures or persistent high fracture risk despite antiresorptive treatment. In cases of inadequate response, the consensus recommended considering a switch to more potent medications. The consensus also addressed the management of medication-related complications, proposing alternatives instead of discontinuation of treatment. Conclusions This consensus provides a comprehensive, cost-effective strategy for fracture prevention with an emphasis on shared decision-making and the incorporation of country-specific case management systems, such as fracture liaison services. It serves as a valuable guide for healthcare professionals in the Asia-Pacific region, contributing to the ongoing evolution of osteoporosis management.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.