External validation of a prediction model and decision tree for sickness absence due to mental disorders

Purpose: A previously developed prediction model and decision tree were externally validated for their ability to identify occupational health survey participants at increased risk of long-term sickness absence (LTSA) due to mental disorders. Methods: The study population consisted of N = 3415 employees in mobility services who were invited in 2016 for an occupational health survey, consisting of an online questionnaire measuring the health status and working conditions, followed by a preventive consultation with an occupational health provider (OHP). The survey variables of the previously developed prediction model and decision tree were used for predicting mental LTSA (no = 0, yes = 1) at 1-year follow-up. Discrimination between survey participants with and without mental LTSA was investigated with the area under the receiver operating characteristic curve (AUC). Results: A total of n = 1736 (51%) non-sick-listed employees participated in the survey and 51 (3%) of them had mental LTSA during follow-up. The prediction model discriminated (AUC = 0.700; 95% CI 0.628–0.773) between participants with and without mental LTSA during follow-up. Discrimination by the decision tree (AUC = 0.671; 95% CI 0.589–0.753) did not differ significantly (p = 0.62) from discrimination by the prediction model. Conclusion: At external validation, the prediction model and the decision tree both poorly identified occupational health survey participants at increased risk of mental LTSA. OHPs could use the decision tree to determine if mental LTSA risk factors should be explored in the preventive consultation which follows after completing the survey questionnaire

Development of Prediction Models for Sickness Absence Due to Mental Disorders in the General Working Population

PurposeThis study investigated if and how occupational health survey variables can be used to identify workers at risk of long-term sickness absence (LTSA) due to mental disorders.MethodsCohort study including 53,833 non-sicklisted participants in occupational health surveys between 2010 and 2013. Twenty-seven survey variables were included in a backward stepwise logistic regression analysis with mental LTSA at 1-year follow-up as outcome variable. The same variables were also used for decision tree analysis. Discrimination between participants with and without mental LTSA during follow-up was investigated by using the area under the receiver operating characteristic curve (AUC); the AUC was internally validated in 100 bootstrap samples.Results30,857 (57%) participants had complete data for analysis; 450 (1.5%) participants had mental LTSA during follow-up. Discrimination by an 11-predictor logistic regression model (gender, marital status, economic sector, years employed at the company, role clarity, cognitive demands, learning opportunities, co-worker support, social support from family/friends, work satisfaction, and distress) was AUC = 0.713 (95% CI 0.692-0.732). A 3-node decision tree (distress, gender, work satisfaction, and work pace) also discriminated between participants with and without mental LTSA at follow-up (AUC = 0.709; 95% CI 0.615-0.804).ConclusionsAn 11-predictor regression model and a 3-node decision tree equally well identified workers at risk of mental LTSA. The decision tree provides better insight into the mental LTSA risk groups and is easier to use in occupational health care practice

Framingham score and work-related variables for predicting cardiovascular disease in the working population

Background: The Framingham score is commonly used to estimate the risk of cardiovascular disease (CVD). This study investigated whether work-related variables improve Framingham score predictions of sickness absence due to CVD. Methods: Eleven occupational health survey variables (descent, marital status, education, work type, work pace, cognitive demands, supervisor support, co-worker support, commitment to work, intrinsic work motivation and distress) and the Framingham Point Score (FPS) were combined into a multi-variable logistic regression model for CVD sickness absence during 1-year follow-up of 19 707 survey participants. The Net Reclassification Index (NRI) was used to investigate the added value of work-related variables to the FPS risk classification. Discrimination between participants with and without CVD sickness absence during follow-up was investigated by the area under the receiver operating characteristic curve (AUC). Results: A total of 129 (0.7%) occupational health survey participants had CVD sickness absence during 1-year follow-up. Manual work and high cognitive demands, but not the other work-related variables contributed to the FPS predictions of CVD sickness absence. However, work type and cognitive demands did not improve the FPS classification for risk of CVD sickness absence [NRI = 2.3%; 95% confidence interval (CI) -2.7 to 9.5%; P = 0.629]. The FPS discriminated well between participants with and without CVD sickness absence (AUC = 0.759; 95% CI 0.724-0.794). Conclusion: Work-related variables did not improve predictions of CVD sickness absence by the FPS. The non-laboratory Framingham score can be used to identify health survey participants at risk of CVD sickness absence

The UV Dose Used for Disinfection of Drinking Water in Sweden Inadequately Inactivates Enteric Virus with Double-Stranded Genomes

Irradiation with ultraviolet light (UV) at 254 nm is effective in inactivating a wide range of human pathogens. In Sweden, a UV dose of 400 J/m2 is often used for the treatment of drinking water. To investigate its effect on virus inactivation, enteric viruses with different genomic organizations were irradiated with three UV doses (400, 600, and 1000 J/m2), after which their viability on cell cultures was examined. Adenovirus type 2 (double-stranded DNA), simian rotavirus 11 (double-stranded RNA), and echovirus 30 (single-stranded RNA) were suspended in tap water and pumped into a laboratory-scale Aquada 1 UV reactor. Echovirus 30 was reduced by 3.6-log10 by a UV dose of 400 J/m2. Simian rotavirus 11 and adenovirus type 2 were more UV resistant with only 1-log10 reduction at 400 J/m2 and needed 600 J/m2 for 2.9-log10 and 3.1-log10 reductions, respectively. There was no significant increase in the reduction of viral viability at higher UV doses, which may indicate the presence of UV-resistant viruses. These results show that higher UV doses than those usually used in Swedish drinking water treatment plants should be considered in combination with other barriers to disinfect the water when there is a risk of fecal contamination of the water

Molecular and Phylogenetic Analyses Suggest an Additional Hepatitis B Virus Genotype “I”

A novel hepatitis B virus (HBV) strain (W29) was isolated from serum samples in the northwest of China. Phylogenetic and distance analyses indicate that this strain is grouped with a series of distinct strains discovered in Vietnam and Laos that have been proposed to be a new genotype I. TreeOrderScan and GroupScan methods were used to study the intergenotype recombination of this special group. Recombination plots and tree maps of W29 and these putative genotype I strains exhibit distinct characteristics that are unexpected in typical genotype C strains of HBV. The amino acids of P gene, S gene, X gene, and C gene of all genotypes (including subtypes) were compared, and eight unique sites were found in genotype I. In vitro and in vivo experiments were also conducted to determine phenotypic characteristics between W29 and other representative strains of different genotypes obtained from China. Secretion of HBsAg in Huh7 cells is uniformly abundant among genotypes A, B, C, and I (W29), but not genotype D. HBeAg secretion is low in genotype I (W29), whose level is close to genotype A and much lower than genotypes B, C, and D. Results from the acute hydrodynamic injection mouse model also exhibit a similar pattern. From an overview of the results, the viral markers of W29 (I1) in Huh7 cells and mice had a more similar level to genotype A than genotype C, although the latter was closer to W29 in distance analysis. All evidence suggests that W29, together with other related strains found in Vietnam and Laos, should be classified into a new genotype

Large-scale extrusion processing and characterization of hybrid nylon-6/SiO2 nanocomposites

Solution impregnations, pulltrusion and film stacking are widely used methods to prepare thermoplastic composite materials. Extruders are used to melt the polymer and to incorporate fibers into the polymer in order to modify physical properties. In this article, the compounding of colloidal silica nanoparticles filled polyamide-6 (PA-6) is achieved using a twin-screw extruder, which has a significant market share due to its low cost and easy maintenance. The experiments were performed at 250 rpm and the bulk throughput was 6 kg h(-1) with a pump pressure of 30 bars. The composites were characterized with nuclear magnetic resonance (NMR), wide angle X-ray diffraction (WAXD), differential scanning calorimetry (DSC) and transmission electron microscopy (TEM). As determined by WAXD, the PA-6 showed higher amounts of gamma-phase when compared to other synthesis methods such as in situ polymerization. TEM pictures showed that the silica particles aggregated nevertheless, upon addition of 14% (w/w) silica the E-modulus increased from 2.7 to 3.9 GPa indicating that an effective mechanical coupling with the polymer was achieved. The behavior, illustrated with dynamic mechanical analysis (DMA) curves, indicated that in general when a filled system is compared to unfilled material, the values of the moduli (E' and E") increased and tan 6 decreased. Determination of molecular mass distribution of the samples by means of size exclusion chromatography (SEC) coupled to a refractive index (RI), viscosity (DV) and light scattering (LS) detector revealed that the addition of silica did not decrease the average molecular weight of the polymer matrix, which is of importance for composite applications. Copyright (C) 2004 John Wiley Sons, Ltd.</p