What is the best time point to identify patients at risk of developing persistent low back pain?

BACKGROUND Early identification of patients at risk of developing persistent low back pain (LBP) is crucial. OBJECTIVE Aim of this study was to identify in patients with a new episode of LBP the time point at which those at risk of developing persistent LBP can be best identified.METHODS: Prospective cohort study of 315 patients presenting to a health practitioner with a first episode of acute LBP. Primary outcome measure was functional limitation. Patients were assessed at baseline, three, six, twelve weeks and six months looking at factors of maladaptive cognition as potential predictors. Multivariate logistic regression analysis was performed for all time points. RESULTS The best time point to predict the development of persistent LBP at six months was the twelve-week follow-up (sensitivity 78%; overall predictive value 90%). Cognitions assessed at first visit to a health practitioner were not predictive. CONCLUSIONS Maladaptive cognitions at twelve weeks appear to be suitable predictors for a transition from acute to persistent LBP. Already three weeks after patients present to a health practitioner with acute LBP cognitions might influence the development of persistent LBP. Therefore, cognitive-behavioral interventions should be considered as early adjuvant LBP treatment in patients at risk of developing persistent LBP.

Saddlepoint Approximations to the Probability of Ruin in Finite Time for the Compound Poisson Risk Process Perturbed by Diffusion

A large deviations type approximation to the probability of ruin within a finite time for the compound Poisson risk process perturbed by diffusion is derived. This approximation is based on the saddlepoint method and generalizes the approximation for the non-perturbed risk process by Barndorff-Nielsen and Schmidli (Scand Actuar J 1995(2):169–186, 1995). An importance sampling approximation to this probability of ruin is also provided. Numerical illustrations assess the accuracy of the saddlepoint approximation using importance sampling as a benchmark. The relative deviations between saddlepoint approximation and importance sampling are very small, even for extremely small probabilities of ruin. The saddlepoint approximation is however substantially faster to compute.

Thrombophilia and risk of VTE recurrence according to the age at the time of first VTE manifestation

BACKGROUND Whether screening for thrombophilia is useful for patients after a first episode of venous thromboembolism (VTE) is a controversial issue. However, the impact of thrombophilia on the risk of recurrence may vary depending on the patient's age at the time of the first VTE. PATIENTS AND METHODS Of 1221 VTE patients (42 % males) registered in the MAISTHRO (MAin-ISar-THROmbosis) registry, 261 experienced VTE recurrence during a 5-year follow-up after the discontinuation of anticoagulant therapy. RESULTS Thrombophilia was more common among patients with VTE recurrence than those without (58.6 % vs. 50.3 %; p = 0.017). Stratifying patients by the age at the time of their initial VTE, Cox proportional hazards analyses adjusted for age, sex and the presence or absence of established risk factors revealed a heterozygous prothrombin (PT) G20210A mutation (hazard ratio (HR) 2.65; 95 %-confidence interval (CI) 1.71 - 4.12; p < 0.001), homozygosity/double heterozygosity for the factor V Leiden and/or PT mutation (HR 2.35; 95 %-CI 1.09 - 5.07, p = 0.030), and an antithrombin deficiency (HR 2.12; 95 %-CI 1.12 - 4.10; p = 0.021) to predict recurrent VTE in patients aged 40 years or older, whereas lupus anticoagulants (HR 3.05; 95%-CI 1.40 - 6.66; p = 0.005) increased the risk of recurrence in younger patients. Subgroup analyses revealed an increased risk of recurrence for a heterozygous factor V Leiden mutation only in young females without hormonal treatment whereas the predictive value of a heterozygous PT mutation was restricted to males over the age of 40 years. CONCLUSIONS Our data do not support a preference of younger patients for thrombophilia testing after a first venous thromboembolic event.

Association of part-time employment and sexual risk-taking behaviors among middle school students

Background. Previous research shows inconsistent results as to the association between part-time employment and sexual behavior among younger teens. Studies of older teens cannot be generalized to younger teens because of the wide differences in types of work performed, nature of work environments, and work intensity. Objective. Examine the relationship between part-time employment and sexual behavior in a cross-sectional sample of public middle school students in Houston, Texas. Methods . The study presents a secondary analysis of data from the It’s Your Game…Keep it Real baseline data collection (11/2004–1/2005). It’s Your Game… is an intervention program for middle school students designed to prevent Sexually Transmitted Infections. Statistical analysis. Univariate and multivariate logistic regression analyses were conducted to examine the association between part-time employment and vaginal intercourse: (a) ever had sex; and (b) current sexual activity. Results. Overall, 13.2% of students worked for pay; male students were 1.5 times as likely as females to be working. Of all the students, 11.0% had had sexual intercourse; students who worked were 3 times more likely to be sexually experienced than those who did not. Among students who were sexually experienced, 67.0% were currently sexually active. After adjusting for the other covariates, Hispanic students were almost 3.6 times more likely to report current sexual activity compared to students in other racial/ethnic groups. In univariate analysis, students who worked 1-5 hrs/week were more likely to be sexually experienced than those not currently employed, and the likelihood increased with number of hours worked. There is a similar pattern in the multivariate model, but the odds ratios are too close for the evidence to be more than suggestive. Of sexually experienced students, students working 1-5 hrs/week were 2.7 times more likely to report current sexual intercourse than those not working; those working >5 hrs/week were 4.7 times more likely. The multivariate model showed a similar increase in likelihood, and adjustment for covariates increased these associations: students who worked 1-5 hrs/week were 3.6 times more likely to report current sexual intercourse, and students who worked >5 hrs/week were 4.5 times more likely, than students not currently employed.^

A comparison of worker risk of injury while working on fully automated side loaders and other residential collection trucks at a large solid waste collection company

The study aim was to determine whether using automated side loader (ASL) trucks in higher proportions compared to other types of trucks for residential waste collection results in lower injury rates (from all causes). The primary hypothesis was that the risk of injury to workers was lower for those who work with ASL trucks than for workers who work with other types of trucks used in residential waste collection. To test this hypothesis, data were collected from one of the nation’s largest companies in the solid waste management industry. Different local operating units (i.e. facilities) in the company used different types of trucks to varying degrees, which created a special opportunity to examine refuse collection injuries and illnesses and the risk reduction potential of ASL trucks.^ The study design was ecological and analyzed end-of-year data provided by the company for calendar year 2007. During 2007, there were a total of 345 facilities which provided residential services. Each facility represented one observation.^ The dependent variable – injury and illness rate, was defined as a facility’s total case incidence rate (TCIR) recorded in accordance with federal OSHA requirements for the year 2007. The TCIR is the rate of total recordable injury and illness cases per 100 full-time workers. The independent variable, percent of ASL trucks, was calculated by dividing the number of ASL trucks by the total number of residential trucks at each facility.^ Multiple linear regression models were estimated for the impact of the percent of ASL trucks on TCIR per facility. Adjusted analyses included three covariates: median number of hours worked per week for residential workers; median number of months of work experience for residential workers; and median age of residential workers. All analyses were performed with the statistical software, Stata IC (version 11.0).^ The analyses included three approaches to classifying exposure, percent of ASL trucks. The first approach included two levels of exposure: (1) 0% and (2) >0 - <100%. The second approach included three levels of exposure: (1) 0%, (2) ≥ 1 - < 100%, and (3) 100%. The third approach included six levels of exposure to improve detection of a dose-response relationship: (1) 0%, (2) 1 to <25%, (3) 25 to <50%, (4) 50 to <75%, (5) 75 to <100%, and (6) 100%. None of the relationships between injury and illness rate and percent ASL trucks exposure levels was statistically significant (i.e., p<0.05), even after adjustment for all three covariates.^ In summary, the present study shows that there is some risk reduction impact of ASL trucks but not statistically significant. The covariates demonstrated a varied yet more modest impact on the injury and illness rate but again, none of the relationships between injury and illness rate and the covariates were statistically significant (i.e., p<0.05). However, as an ecological study, the present study also has the limitations inherent in such designs and warrants replication in an individual level cohort design. Any stronger conclusions are not suggested.^

Motorcycle accident risk could be inflated by a time to arrival illusion

Purpose. Drivers adopt smaller safety margins when pulling out in front of motorcycles compared with cars. This could partly account for why the most common motorcycle/car accident involves a car violating a motorcyclist's right of way. One possible explanation is the size-arrival effect in which smaller objects are perceived to arrive later than larger objects. That is, drivers may estimate the time to arrival of motorcycles to be later than cars because motorcycles are smaller. Methods. We investigated arrival time judgments using a temporal occlusion paradigm. Drivers recruited from the student population (n = 28 and n = 33) saw video footage of oncoming vehicles and had to press a response button when they judged that vehicles would reach them. Results. In experiment 1, the time to arrival of motorcycles was estimated to be significantly later than larger vehicles (a car and a van) for different approach speeds and viewing times. In experiment 2, we investigated an alternative explanation to the size-arrival effect: that the smaller size of motorcycles places them below the threshold needed for observers to make an accurate time to arrival judgment using tau. We found that the motorcycle/car difference in arrival time estimates was maintained for very short occlusion durations when tau could be estimated for both motorcycles and cars. Conclusions. Results are consistent with the size-arrival effect and are inconsistent with the tau threshold explanation. Drivers estimate motorcycles will reach them later than cars across a range of conditions. This could have safety implications.

The effects of varying time under tension and volume load on acute neuromuscular responses

The purpose of this study was to examine the effects of different methods of measuring training volume, controlled in different ways, on selected variables that reflect acute neuromuscular responses. Eighteen resistance-trained males performed three fatiguing protocols of dynamic constant external resistance exercise, involving elbow flexors, that manipulated either time-under-tension (TUT) or volume load (VL), defined as the product of training load and repetitions. Protocol A provided a standard for TUT and VL. Protocol B involved the same VL as Protocol A but only 40% concentric TUT; Protocol C was equated to Protocol A for TUT but only involved 50% VL. Fatigue was assessed by changes in maximum voluntary isometric contraction (MVIC), interpolated doublet (ID), muscle twitch characteristics (peak twitch, time to peak twitch, 0.5 relaxation time, and mean rates of force development and twitch relaxation). All protocols produced significant changes (P

Project time risk analysis through simulation

An inherent weakness in the management of large scale projects is the failure to achieve the scheduled completion date. When projects are planned with the objective of time achievement, the initial planning plays a vital role in the successful achievement of project deadlines. Cost and quality are additional priorities when such projects are being executed. This article proposes a methodology for achieving time duration of a project through risk analysis with the application of a Monte Carlo simulation technique. The methodology is demonstrated using a case application of a cross-country petroleum pipeline construction project.

Handling varying amounts of missing data when classifying mental-health risk levels

One of the main challenges of classifying clinical data is determining how to handle missing features. Most research favours imputing of missing values or neglecting records that include missing data, both of which can degrade accuracy when missing values exceed a certain level. In this research we propose a methodology to handle data sets with a large percentage of missing values and with high variability in which particular data are missing. Feature selection is effected by picking variables sequentially in order of maximum correlation with the dependent variable and minimum correlation with variables already selected. Classification models are generated individually for each test case based on its particular feature set and the matching data values available in the training population. The method was applied to real patients' anonymous mental-health data where the task was to predict the suicide risk judgement clinicians would give for each patient's data, with eleven possible outcome classes: zero to ten, representing no risk to maximum risk. The results compare favourably with alternative methods and have the advantage of ensuring explanations of risk are based only on the data given, not imputed data. This is important for clinical decision support systems using human expertise for modelling and explaining predictions.

Sensitivity Analysis of the Risk of Forecasting for Autoregressive Time Series with Missing Values

2000 Mathematics Subject Classification: 62M20, 62M10, 62-07.