Contribution of health status and prevalent chronic disease to individual risk for workplace injury in the manufacturing environment.

OBJECTIVES: An 'information gap' has been identified regarding the effects of chronic disease on occupational injury risk. We investigated the association of ischaemic heart disease, hypertension, diabetes, depression and asthma with acute occupational injury in a cohort of manufacturing workers from 1 January 1997 through 31 December 2007. METHODS: We used administrative data on real-time injury, medical claims, workplace characteristics and demographics to examine this association. We employed a piecewise exponential model within an Andersen-Gill framework with a frailty term at the employee level to account for inclusion of multiple injuries for each employee, random effects at the employee level due to correlation among jobs held by an employee, and experience on the job as a covariate. RESULTS: One-third of employees had at least one of the diseases during the study period. After adjusting for potential confounders, presence of these diseases was associated with increased hazard of injury: heart disease (HR 1.23, 95% CI 1.11 to 1.36), diabetes (HR 1.17, 95% CI 1.08 to 1.27), depression (HR 1.25, 95% CI 1.12 to 1.38) and asthma (HR 1.14, 95% CI 1.02 to 1.287). Hypertension was not significantly associated with hazard of injury. Associations of chronic disease with injury risk were less evident for more serious reportable injuries; only depression and a summary health metric derived from claims remained significantly positive in this subset. CONCLUSIONS: Our results suggest that chronic heart disease, diabetes and depression confer an increased risk for acute occupational injury.

A predictive model to identify hospitalized cancer patients at risk for 30-day mortality based on admission criteria via the electronic medical record.

BACKGROUND: This study sought to develop a predictive model for 30-day mortality in hospitalized cancer patients, by using admission information available through the electronic medical record. METHODS: Observational cohort study of 3062 patients admitted to the oncology service from August 1, 2008, to July 31, 2009. Matched numbers of patients were in the derivation and validation cohorts (1531 patients). Data were obtained on day 1 of admission and included demographic information, vital signs, and laboratory data. Survival data were obtained from the Social Security Death Index. RESULTS: The 30-day mortality rate of the derivation and validation samples were 9.5% and 9.7% respectively. Significant predictive variables in the multivariate analysis included age (P < .0001), assistance with activities of daily living (ADLs; P = .022), admission type (elective/emergency) (P = .059), oxygen use (P < .0001), and vital signs abnormalities including pulse oximetry (P = .0004), temperature (P = .017), and heart rate (P = .0002). A logistic regression model was developed to predict death within 30 days: Score = 18.2897 + 0.6013*(admit type) + 0.4518*(ADL) + 0.0325*(admit age) - 0.1458*(temperature) + 0.019*(heart rate) - 0.0983*(pulse oximetry) - 0.0123 (systolic blood pressure) + 0.8615*(O2 use). The largest sum of sensitivity (63%) and specificity (78%) was at -2.09 (area under the curve = -0.789). A total of 25.32% (100 of 395) of patients with a score above -2.09 died, whereas 4.31% (49 of 1136) of patients below -2.09 died. Sensitivity and positive predictive value in the derivation and validation samples compared favorably. CONCLUSIONS: Clinical factors available via the electronic medical record within 24 hours of hospital admission can be used to identify cancer patients at risk for 30-day mortality. These patients would benefit from discussion of preferences for care at the end of life.

Hearing effects from intermittent and continuous noise exposure in a study of Korean factory workers and firefighters.

BACKGROUND: South Korea and surrounding countries in East Asia are believed to have the highest proportion in the world of high frequency hearing loss due to occupational noise exposure, yet there has been limited information published in international journals, and limited information for control of noise in local workplaces beyond strategies from western countries. We exploit medical surveillance information from two worker groups to enhance local knowledge about noise-induced hearing loss and explore the possible importance of shift work to risk. METHODS: Four-years of hearing data were evaluated for 81 male farm machine factory workers and 371 male firefighters who had successfully completed a health examination and questionnaires for the duration of the study period. The averages of hearing thresholds at 2, 3, and 4 kHz were used as the primary end-point for comparison. Repeat measure analysis adjusted for age, exposure duration and smoking status was used to measure the difference in hearing threshold between the two groups. RESULTS: Noise levels were measured in the factory at a mean of 82 dBA, with a range of 66-97. No concurrent measurements were taken for the firefighters, but historic comparison values showed a wider range but a similar mean of 76-79 dBA. Although losses during follow-up were negligible, the factory workers had significantly (P < 0.0001) more hearing loss at the baseline of the study than the firefighters in both ears at 2, 3, and 4 kHz, adjusted for age, duration of employment and smoking status. Among those with 10 years of employment, mean losses at these frequencies among the factory workers fell into the impairment range (> 25 dB loss). Firefighters also showed increased losses associated with longer exposure duration, but these were significantly less marked. Losses at lower frequencies (< or = 1 kHz) were negligible in both groups. CONCLUSIONS: Korean work environments with continuous noise exposure in the measured range should consider implementation of a hearing conservation program. Further evaluation of hearing loss in workers exposed to irregular or intermittent high noise levels, such as firefighters, is also warranted.

Process of care compliance is associated with fewer diabetes complications.

OBJECTIVE: To examine the association between processes measures of diabetes care and time to progression for 4 diabetes complications: coronary artery disease (CAD), stroke, heart failure (HF), and renal disease (RD). STUDY DESIGN: This retrospective study followed outcomes from 2003 through 2009 in a cohort of 1797 employees with diabetes who worked for a large US manufacturer and were enrolled in the same health insurance plan. METHODS: Quality of care was measured by consensus standards for testing glycated hemoglobin, lipids, and microalbuminuria. Employees with diabetes who received all 3 measures of care in the baseline year (2003) were compared with those who received less complete testing. Cox proportional hazard regression models were used to assess potential associations between diabetes care and time to complications, controlling for potential confounders. RESULTS: Observed differences between the 2 groups in time to event were significant for 2 of the 4 complications: HF (hazard ratio [HR] = 0.39, 95% confidence interval [CI], 0.19-0.81; P = .0117) and RD (HR = 0.48, 95% CI, 0.24-0.95; P = .0339) and any of the 4 complications (HR = 0.66, 95% CI, 0.48-0.91; P = .0101). Differences in time to complication for CAD (HR = 0.70, 95% CI, 0.49-1.02; P = .0635) and stroke (HR = 0.63, 95% CI, 0.38-1.07; P = .0891) showed the same trend but were not significant. CONCLUSIONS: Employees with diabetes who received all 3 quality measures experienced fewer complications, risk-adjusting for other factors. These results provide support for the importance of care quality.

Systematic review and meta-analysis of opioid antagonists for smoking cessation.

OBJECTIVES: This meta-analysis sought to evaluate the efficacy of opioid antagonists in promoting long-term smoking cessation. Post-treatment abstinence was examined as a secondary outcome and effects on withdrawal symptoms, craving and reduced consumption were also explored. DESIGN: The search strategy for this meta-analysis included clinical trials (published and unpublished data) in the Cochrane Tobacco Addiction Group Specialized Register and MEDLINE. PARTICIPANTS: Adult smokers. INTERVENTIONS: We included randomised trials comparing opioid antagonists to placebo or an alternative therapy for smoking cessation and reported data on abstinence for a minimum of 6 months. PRIMARY AND SECONDARY OUTCOME MEASURES: Outcomes included smoking abstinence at long-term follow-up (primary); abstinence at end of treatment (secondary); and effects on withdrawal, craving and smoking consumption (exploratory). RESULTS: 8 trials with a total of 1213 participants were included. Half the trials examined the benefit of adding naltrexone versus placebo to nicotine replacement therapy (NRT). There was no significant difference between naltrexone and placebo alone (relative risk (RR) 1.00; 95% CI 0.66 to 1.51) or as an adjunct to NRT (RR 0.95; 95% CI 0.70 to 1.30), with an overall pooled estimate of RR 0.97; 95% CI 0.76 to 1.24. Findings for naltrexone effects on withdrawal, craving and reduced smoking were equivocal. CONCLUSIONS: The findings indicate no beneficial effect of naltrexone alone or as an adjunct to NRT on short-term or long-term smoking abstinence. While further trials may narrow the confidence limits, they are unlikely to appreciably alter the conclusion.

Potential reporting bias in fMRI studies of the brain.

BACKGROUND: Functional magnetic resonance imaging (fMRI) studies have reported multiple activation foci associated with a variety of conditions, stimuli or tasks. However, most of these studies used fewer than 40 participants. METHODOLOGY: After extracting data (number of subjects, condition studied, number of foci identified and threshold) from 94 brain fMRI meta-analyses (k = 1,788 unique datasets) published through December of 2011, we analyzed the correlation between individual study sample sizes and number of significant foci reported. We also performed an analysis where we evaluated each meta-analysis to test whether there was a correlation between the sample size of the meta-analysis and the number of foci that it had identified. Correlation coefficients were then combined across all meta-analyses to obtain a summary correlation coefficient with a fixed effects model and we combine correlation coefficients, using a Fisher's z transformation. PRINCIPAL FINDINGS: There was no correlation between sample size and the number of foci reported in single studies (r = 0.0050) but there was a strong correlation between sample size and number of foci in meta-analyses (r = 0.62, p<0.001). Only studies with sample sizes <45 identified larger (>40) numbers of foci and claimed as many discovered foci as studies with sample sizes ≥ 45, whereas meta-analyses yielded a limited number of foci relative to the yield that would be anticipated from smaller single studies. CONCLUSIONS: These results are consistent with possible reporting biases affecting small fMRI studies and suggest the need to promote standardized large-scale evidence in this field. It may also be that small studies may be analyzed and reported in ways that may generate a larger number of claimed foci or that small fMRI studies with inconclusive, null, or not very promising results may not be published at all.