A Two-Flap Combination for Auricular Elevation in Microtia Reconstruction.

BACKGROUND: The aims of this study were to describe and evaluate the effectiveness of combined flaps, a modification of the Nagata technique, for providing a reasonable projection for reconstructed auricles. METHODS: The authors modified the Nagata method for covering the cartilage block by introducing a new combined flap technique, including the temporoparietal skin flap and retroauricular flap. The authors compared the shape, size, and position of the reconstructed ear to the opposite ear, and we evaluated postoperative complications and patient satisfaction levels. They verified the effectiveness of the combined flap by assessing flap necrosis, skin color, thickness, hair in the auricular area, and scars. RESULTS: A total of 38 consecutive patients (39 ears) with microtia, aged 6 to 34 years, underwent reconstruction using the modified method and were followed up for 33.6 months on average. The reconstructed auricle's shape was well defined, with 41.0% having good and 15.4% having excellent results. Most cases achieved good and acceptable levels in size, position, medial longitudinal axis angle, and auriculocephalic angles, and 79.9% of patients/their families were satisfied. The authors observed no cases of flap necrosis or hypertrophic scarring, and there were low rates of flap complications, such as unmatched skin color (7.7%), unacceptable thickness (5.1%), or hair and stretch marks (10.3%). CONCLUSIONS: The modified method's reconstructed ear achieved stable projection, symmetric appearance, and obvious anatomical landmarks with high patient satisfaction. The combined flap method showed certain advantages: high survival rate, less skin contrast, no hypertrophic scars, and fewer complications. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, IV.

Machine Learning-Based Prediction of Drug-Drug Interactions for Histamine Antagonist Using Hybrid Chemical Features.

The requesting of detailed information on new drugs including drug-drug interactions or targets is often unavailable and resource-intensive in assessing adverse drug events. To shorten the common evaluation process of drug-drug interactions, we present a machine learning framework-HAINI to predict DDI types for histamine antagonist drugs using simplified molecular-input line-entry systems (SMILES) combined with interaction features based on CYP450 group as inputs. The data used in our research consisted of approved drugs of histamine antagonists that are connected to 26,344 DDI pairs from the DrugBank database. Various classification algorithms such as Naive Bayes, Decision Tree, Random Forest, Logistic Regression, and XGBoost were used with 5-fold cross-validation to approach a large-scale DDIs prediction among histamine antagonist drugs. The prediction performance shows that our model outperformed previously published works on DDI prediction with the best precision of 0.788, a recall of 0.921, and an F1-score of 0.838 among 19 given DDIs types. An important finding of the study is that our prediction is based solely on the SMILES and CYP450 and thus can be applied at the early stage of drug development.

Health insurance drop-out among adult population: findings from a study in a Health and demographic surveillance system in Northern Vietnam 2006-2013.

The coverage of health insurance as measured by enrollment rates has increased significantly in Vietnam. However, maintaining health insurance to the some groups such as the farmer, the borderline poor and informal workers, etc. has been very challenging. This paper examines the situation of health insurance drop-out among the adult population in sub-rural areas of Northern Vietnam from 2006 to 2013, and analyzes several socio-economic correlates of the health insurance drop-out situation. Data used in this paper were obtained from Health and Demographic Surveillance System located in Chi Linh district, an urbanizing area, in a northern province of Vietnam. Descriptive analyses were used to describe the level and distribution of the health insurance drop-out status. Multiple logistic regressions were used to assess associations between the health insurance drop-out status and the independent variables. A total of 32 561 adults were investigated. We found that the cumulative percentage of health insurance drop-out among the study participants was 21.2%. Health insurance drop-out rates were higher among younger age groups, people with lower education, and those who worked as small trader and other informal jobs, and belonged to the non-poor households. Given the findings, further attention toward health insurance among these special populations is needed.

Clinical diagnosis and assessment of severity of confirmed dengue infections in Vietnamese children: is the world health organization classification system helpful?

Classification of dengue using the current World Health Organization (WHO) system is not straightforward. In a large prospective study of pediatric dengue, no clinical or basic laboratory parameters clearly differentiated between children with and without dengue, although petechiae and hepatomegaly were independently associated with the diagnosis. Among the 712 dengue-infected children there was considerable overlap in the major clinical features. Mucosal bleeding was observed with equal frequency in those with dengue fever and dengue hemorrhagic fever (DHF), and petechiae, thrombocytopenia, and the tourniquet test differentiated poorly between the two diagnostic categories. Fifty-seven (18%) of 310 with shock did not fulfill all four criteria considered necessary for a diagnosis of DHF by the WHO, but use of the WHO provisional classification scheme resulted in considerable over-inflation of the DHF figures. If two separate entities truly exist rather than a continuous spectrum of disease, it is essential that some measure of capillary leak is included in any classification system, with less emphasis on bleeding and a specific platelet count.