Radio Frequency Nonionizing Radiation in a Community Exposed to Radio and Television Broadcasting

Exposure to radio frequency (RF) nonionizing radiation from telecommunications is pervasive in modern society. Elevated disease risks have been observed in some populations exposed to radio and television transmissions, although findings are inconsistent. This study quantified RF exposures among 280 residents living near the broadcasting transmitters for Denver, Colorado. RF power densities outside and inside each residence were obtained, and a global positioning system (GPS) identified geographic coordinates and elevations. A viewshed model within a geographic information system (GIS) characterized the average distance and percentage of transmitters visible from each residence. Data were collected at the beginning and end of a 2.5-day period, and some measurements were repeated 8–29 months later. RF levels logged at 1-min intervals for 2.5 days varied considerably among some homes and were quite similar among others. The greatest differences appeared among homes within 1 km of the transmitters. Overall, there were no differences in mean residential RF levels compared over 2.5 days. However, after a 1- to 2-year follow-up, only 25% of exterior and 38% of interior RF measurements were unchanged. Increasing proximity, elevation, and line-of-sight visibility were each associated with elevated RF exposures. At average distances from > 1–3 km, exterior RF measurements were 13–30 times greater among homes that had > 50% of the transmitters visible compared with homes with ≤ 50% visibility at those distances. This study demonstrated that both spatial and temporal factors contribute to residential RF exposure and that GPS/GIS technologies can improve RF exposure assessment and reduce exposure misclassification

RF power densities recorded at 1-min intervals for homes ≤ 1 km (), 1–2 km (), or 2–3 km () from the transmitters

<p><b>Copyright information:</b></p><p>Taken from "Radio Frequency Nonionizing Radiation in a Community Exposed to Radio and Television Broadcasting"</p><p>Environmental Health Perspectives 2005;114(2):248-253.</p><p>Published online 20 Sep 2005</p><p>PMCID:PMC1367839.</p><p>This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original DOI.</p> Each time series was collected from a stationary location within a single home on a different day. Results have been superimposed so that the time of day coincides among traces. Time 0.0 corresponds to 13:40. A flat line designates times before or after the recording period (i.e., no data collection)

Measurement of spatial and temporal variation in volatile hazardous air pollutants in Tacoma, Washington, using a mobile membrane introduction mass spectrometry (MIMS) system

<div><p>The objective of this study was to use membrane introduction mass spectrometry (MIMS), implemented on a mobile platform, in order to provide real-time, fine–scale, temporally and spatially resolved measurements of several hazardous air pollutants. This work is important because there is now substantial evidence that fine-scale spatial and temporal variations of air pollutant concentrations are important determinants of exposure to air pollution and adverse health outcomes. The study took place in Tacoma, WA during periods of impaired air quality in the winter and summer of 2008 and 2009. Levels of fine particles were higher in winter compared to summer, and were spatially uniform across the study area. Concentrations of vapor phase pollutants measured by membrane introduction mass spectrometry (MIMS), notably benzene and toluene, had relatively uniform spatial distributions at night, but exhibited substantial spatial variation during the day—daytime levels were up to 3-fold higher at traffic-impacted locations compared to a reference site. Although no direct side-by-side comparison was made between the MIMS system and traditional fixed site monitors, the MIMS system typically reported higher concentrations of specific VOCs, particularly benzene, ethylbenzene and naphthalene, compared to annual average concentrations obtained from SUMA canisters and gas chromatographic analysis at the fixed sites.</p></div

A Machine Learning Algorithm to Identify Patients at Risk of Unplanned Subsequent Surgery After Intramedullary Nailing for Tibial Shaft Fractures

Objectives: In the SPRINT trial, 18% of patients with a tibial shaft fracture (TSF) treated with intramedullary nailing (IMN) had one or more unplanned subsequent surgical procedures. It is clinically relevant for surgeon and patient to anticipate unplanned secondary procedures, other than operations that can be readily expected such as reconstructive procedures for soft tissue defects. Therefore, the objective of this study was to develop a machine learning (ML) prediction model using the SPRINT data that can give individual patients and their care team an estimate of their particular probability of an unplanned second surgery. Methods: Patients from the SPRINT trial with unilateral TSFs were randomly divided into a training set (80%) and test set (20%). Five ML algorithms were trained in recognizing patterns associated with subsequent surgery in the training set based on a subset of variables identified by random forest algorithms. Performance of each ML algorithm was evaluated and compared based on (1) area under the ROC curve, (2) calibration slope and intercept, and (3) the Brier score. Results: Total data set comprised 1198 patients, of whom 214 patients (18%) underwent subsequent surgery. Seven variables were used to train ML algorithms: (1) Gustilo-Anderson classification, (2) Tscherne classification, (3) fracture location, (4) fracture gap, (5) polytrauma, (6) injury mechanism, and (7) OTA/AO classification. The best-performing ML algorithm had an area under the ROC curve, calibration slope, calibration intercept, and the Brier score of 0.766, 0.954, -0.002, and 0.120 in the training set and 0.773, 0.922, 0, and 0.119 in the test set, respectively. Conclusions: An ML algorithm was developed to predict the probability of subsequent surgery after IMN for TSFs. This ML algorithm may assist surgeons to inform patients about the probability of subsequent surgery and might help to identify patients who need a different perioperative plan or a more intensive approach.Orthopaedics, Trauma Surgery and Rehabilitatio

Critical care usage after major gastrointestinal and liver surgery: a prospective, multicentre observational study

Background Patient selection for critical care admission must balance patient safety with optimal resource allocation. This study aimed to determine the relationship between critical care admission, and postoperative mortality after abdominal surgery. Methods This prespecified secondary analysis of a multicentre, prospective, observational study included consecutive patients enrolled in the DISCOVER study from UK and Republic of Ireland undergoing major gastrointestinal and liver surgery between October and December 2014. The primary outcome was 30-day mortality. Multivariate logistic regression was used to explore associations between critical care admission (planned and unplanned) and mortality, and inter-centre variation in critical care admission after emergency laparotomy. Results Of 4529 patients included, 37.8% (n=1713) underwent planned critical care admissions from theatre. Some 3.1% (n=86/2816) admitted to ward-level care subsequently underwent unplanned critical care admission. Overall 30-day mortality was 2.9% (n=133/4519), and the risk-adjusted association between 30-day mortality and critical care admission was higher in unplanned [odds ratio (OR): 8.65, 95% confidence interval (CI): 3.51–19.97) than planned admissions (OR: 2.32, 95% CI: 1.43–3.85). Some 26.7% of patients (n=1210/4529) underwent emergency laparotomies. After adjustment, 49.3% (95% CI: 46.8–51.9%, P<0.001) were predicted to have planned critical care admissions, with 7% (n=10/145) of centres outside the 95% CI. Conclusions After risk adjustment, no 30-day survival benefit was identified for either planned or unplanned postoperative admissions to critical care within this cohort. This likely represents appropriate admission of the highest-risk patients. Planned admissions in selected, intermediate-risk patients may present a strategy to mitigate the risk of unplanned admission. Substantial inter-centre variation exists in planned critical care admissions after emergency laparotomies

Body mass index and complications following major gastrointestinal surgery: A prospective, international cohort study and meta-analysis

Aim Previous studies reported conflicting evidence on the effects of obesity on outcomes after gastrointestinal surgery. The aims of this study were to explore the relationship of obesity with major postoperative complications in an international cohort and to present a metaanalysis of all available prospective data. Methods This prospective, multicentre study included adults undergoing both elective and emergency gastrointestinal resection, reversal of stoma or formation of stoma. The primary end-point was 30-day major complications (Clavien–Dindo Grades III–V). A systematic search was undertaken for studies assessing the relationship between obesity and major complications after gastrointestinal surgery. Individual patient meta-analysis was used to analyse pooled results. Results This study included 2519 patients across 127 centres, of whom 560 (22.2%) were obese. Unadjusted major complication rates were lower in obese vs normal weight patients (13.0% vs 16.2%, respectively), but this did not reach statistical significance (P = 0.863) on multivariate analysis for patients having surgery for either malignant or benign conditions. Individual patient meta-analysis demonstrated that obese patients undergoing surgery formalignancy were at increased risk of major complications (OR 2.10, 95% CI 1.49–2.96, P < 0.001), whereas obese patients undergoing surgery for benign indications were at decreased risk (OR 0.59, 95% CI 0.46–0.75, P < 0.001) compared to normal weight patients. Conclusions In our international data, obesity was not found to be associated with major complications following gastrointestinal surgery. Meta-analysis of available prospective data made a novel finding of obesity being associated with different outcomes depending on whether patients were undergoing surgery for benign or malignant disease