Brominated flame retardant (BFRs) and Dechlorane Plus (DP) in paired human serum and segmented hair.

Brominated flame retardants (BFRs) and Dechlorane Plus (DP) were measured in both human hair and paired serum samples from a cohort of university students in South China. Segmental analysis was conducted to explore gender difference and the relationships between the hair and serum. The concentrations of total PBDEs in the hair and serum samples were in a range of 0.28-34.1ng/g dry weight (dw) and 0.16-156ng/g lipid weight (lw), respectively. Concentrations of ∑DPs (sum of the syn-DP and anti-DP isomers) in all hair samples ranged from nd-5.45ng/g dry weight. Concentrations of most PBDEs and decabromodiphenylethane (DBDPE) in distal segments (5-10cm from the scalp) were higher than those in the proximal segments (0-5cm from the scalp) (t-test, p < 0.05), which could be due to the longer exposure time of distal segments. The proximal segments exhibited a unique congener profile, more close to that in the serum rather than the distal segments of hair. An obvious gender difference was found in the levels of ∑PBDEs using integrated hair samples, while the difference disappeared when considering alone the proximal segments of hair (0-5cm from scalp) for both genders. This paper provides supplement to the current knowledge on sources of BFRs and DPs in hair and declares the importance of segmental analysis.

A proposed prognostic 7-day survival formula for patients with terminal cancer.

BACKGROUND: The ability to identify patients for hospice care results in better end-of-life care. To develop a validated prognostic scale for 7-day survival prediction, a prospective observational cohort study was made of patients with terminal cancer. METHODS: Patient data gathered within 24 hours of hospital admission included demographics, clinical signs and symptoms and their severity, laboratory test results, and subsequent survival data. Of 727 patients enrolled, data from 374 (training group) was used to develop a prognostic tool, with the other 353 serving as the validation group. RESULTS: Five predictors identified by multivariate logistic regression analysis included patient's cognitive status, edema, ECOG performance status, BUN and respiratory rate. A formula of the predictor model based on those five predictors was constructed. When probability was >0.2, death within 7 days was predicted in the training group and validation group, with sensitivity of 80.9% and 71.0%, specificity of 65.9% and 57.7%, positive predictive value of 42.6% and 26.8%, and negative predictive value (NPV) of 91.7% and 90.1%, respectively. CONCLUSION: This predictor model showed a relatively high sensitivity and NPV for predicting 7-day survival among terminal cancer patients, and could increase patient satisfaction by improving end-of-life care.