Introduction Community‐acquired pneumonia (CAP) severity scores perform well in predicting mortality of CAP patients, but their applicability in influenza pneumonia is powerless. Objectives The aim of our research was to test the efficiency of PO2/FiO2 and CAP severity scores in predicting mortality and intensive care unit (ICU) admission with influenza pneumonia patients. Methods We reviewed all patients with positive influenza virus RNA detection in Beijing Chao‐Yang Hospital during the 2009–2014 influenza seasons. Outpatients, inpatients with no pneumonia and incomplete data were excluded. We used receiver operating characteristic curves (ROCs) to verify the accuracy of severity scores or indices as mortality predictors in the study patients. Results Among 170 hospitalized patients with influenza pneumonia, 30 (17.6%) died. Among those who were classified as low‐risk (predicted mortality 0.1%–2.1%) by pneumonia severity index (PSI) or confusion, urea, respiratory rate, blood pressure, age ≥65 year (CURB‐65), the actual mortality ranged from 5.9 to 22.1%. Multivariate logistic regression indicated that hypoxia (PO2/FiO2 ≤ 250) and lymphopenia (peripheral blood lymphocyte count <0.8 × 109/L) were independent risk factors for mortality, with OR value of 22.483 (95% confidence interval 4.927–102.598) and 5.853 (95% confidence interval 1.887–18.152), respectively. PO2/FiO2 combined lymphocyte count performed well for mortality prediction with area under the curve (AUC) of 0.945, which was significantly better than current CAP severity scores of PSI, CURB‐65 and confusion, respiratory rate, blood pressure, age ≥65 years for mortality prediction (P < 0.001). The scores or indices for ICU admission prediction to hospitalized patients with influenza pneumonia confirmed a similar pattern and PO2/FiO2 combined lymphocyte count was also the best predictor for predicting ICU admission. Conclusion In conclusion, we found that PO2/FiO2 combined lymphocyte count is simple and reliable predictor of hospitalized patients with influenza pneumonia in predicting mortality and ICU admission. When PO2/FiO2 ≤ 250 or peripheral blood lymphocyte count <0.8 × 109/L, the clinician should pay great attention to the possibility of severe influenza pneumonia.

Surface acoustic wave (SAW) devices have been widely used in different fields and will continue to be of great importance in the foreseeable future. These devices are compact, cost efficient, easy to fabricate, and have a high performance, among other advantages. SAW devices can work as filters, signal processing units, sensors and actuators. They can even work without batteries and operate under harsh environments. In this review, the operating principles of SAW sensors, including temperature sensors, pressure sensors, humidity sensors and biosensors, will be discussed. Several examples and related issues will be presented. Technological trends and future developments will also be discussed.

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Aims: This study aimed to identify potential, non-invasive biomarkers for diagnosis and monitoring of the progress in multiple myeloma (MM) patients.Methods: MM patients and age-matched healthy controls (HC) were recruited in Discovery phase and Validation phase, respectively. MM patients were segregated into active group (AG) and responding group (RG). Serum samples were collected were conducted to non-targeted metabolomics analyses. Metabolites which were significantly changed (SCMs) among groups were identified in Discovery phase and was validated in Validation phase. The signaling pathways of these SCMs were enriched. The ability of SCMs to discriminate among groups in Validation phase was analyzed through receiver operating characteristic curve. The correlations between SCMs and clinical features, between SCMs and survival period of MM patients were analyzed.Results: Total of 23 SCMs were identified in AG compared with HC both in Discovery phase and Validation phase. Those SCMs were significantly enriched in arginine and proline metabolism and glycerophospholipid metabolism. 4 SCMs had the discriminatory ability between MM patients and healthy controls in Validation phase. Moreover, 12 SCMs had the ability to discriminate between the AG patients and RG patients in Validation phase. 10 out of 12 SCMs correlated with advanced features of MM. Moreover, 8 out of 12 SCMs had the negative impact on the survival of MM. 5′-Methylthioadenosine may be the only independent prognostic factor in survival period of MM.Conclusion: 10 SCMs identified in our study, which correlated with advanced features of MM, could be potential, novel, non-invasive biomarkers for active disease in MM.

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