Simple and Low-cost Fiber-optic Sensors for Detection of UV Radiation

In this paper two simple and low-cost fiberoptic sensors for detection of UV radiation are presented. A U-shaped sensor covered with an UV marker for UV radiation detection and a fiber-optic sensor with one end covered with powder from a mercury lamp are produced and described in details. Both sensors are made of large-core PMMA plastic optical fibers. As UV sources, a solar simulator and four different UV lamps are used. The light spectrum on the fiber output is measured by using an USB spectrometer. Dependence of output light intensity on the distance of end-type sensor with powder from a mercury lamp from UV lamp is investigated as well. On the output of the sensor covered with powder from a mercury lamp are obtained peaks of fluorescent emission at approximately 616 nm and 620 nm wavelengths

Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.

BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700

Development and validation of a prediction score for postoperative acute renal failure following liver resection

OBJECTIVE: To develop and validate a score to predict postoperative acute renal failure (ARF) after liver resection. BACKGROUND: Postoperative ARF after major surgery is associated with morbidity and mortality. Early identification of patients at risk of ARF is important in order to provide protective kidney treatment. METHODS: Postoperative ARF was prospectively assessed in consecutive patients undergoing liver resection. In randomly selected two-third of the total number of patients, multivariate logistic regression analysis was used to develop a new prediction score (including a full and a reduced model), based on the preoperative parameters of age, gender, preexisting chronic renal dysfunction, cardiovascular disease, diabetes, bilirubin, and alanine aminotransferase (ALT) levels. In the remaining last third of the patients, the new score was validated by calibrating the accuracy of the score (ClinicalTrials.gov NCT 00743132). RESULTS: Postoperative ARF occurred in 15.1% (86 of 569 consecutive patients) from 2002 to 2007 and was highly associated with mortality (22.5% vs. 0.8% without ARF, P < 0.001). In the 380 (two-third of the population) patients selected for the development of the prediction score, preoperatively elevated ALT, preexisting cardiovascular disease, chronic renal failure, and diabetes were the strongest predictors of ARF. Validating the full prediction model (0-22 points) to the remaining 189 patients (one-third of the population), the risk could be predicted accurately (mean predicted risk of 11.5% vs. an observed risk of 14.8%) without significant differences between predicted and observed risks across different risk categories (P = 0.98). Prediction with the reduced model including the 4 strongest predictors (0-7 points) was almost as accurate as with the full model (11.4% predicted vs. 14.8% observed) and also without significant differences across different risk categories (P = 0.75). CONCLUSIONS: The new prediction score (the full as well as the reduced model) accurately predicted postoperative ARF after liver resection. The use of these scores allows early identification of patients at high risk of ARF, and may support decision making for protective kidney interventions perioperatively