Methods: This study enrolled 241 patients to evaluate systemic iodine absorption after exposure to conjunctival and/or periorbital 1.25% and 10% PVP-I compared to an iodine-free antiseptic.

Results: All patients who received the 10% PVP-I regardless of the application site showed a 1.2-1.5-fold increase in urinary iodine excretion after 24 h (p = 0.01). In 17 out of 110 (15.5%) patients in NSC 707544 whom 10% PVP-I was used, the critical threshold of urinary iodine

excretion as defined by WHO (>300 mu g/L) was exceeded. In contrast, no significant ioduria was observed with the use of 1.25% PVP-I except in patients after 48 h (p = 0.01) and with a concurrent conjunctival and periorbital application. The proportion of the excreted iodine in urine ranged from 0.24% to 1.77%. No correlation was found between the total applied concentration of iodine and the amount excreted in urine.

Conclusion: Based on our findings, we believe that the use of 10% PVP-I as preoperative ophthalmic antiseptic should undergo further clinical evaluation in regard to its impact on thyroid function. Conjunctival or periorbital application of 1.25% PVP-I does not result in significant ioduria.”
“Objectives: To recommend methodological standards in the prevention and handling of missing data for primary patient-centered outcomes research (PCOR).

Study Design and Setting: We searched VX770 National Library of Medicine Bookshelf and Catalog

as well as regulatory agencies’ and organizations’ Web sites in January 2012 for guidance documents that had formal recommendations regarding learn more missing data. We extracted the characteristics

of included guidance documents and recommendations. Using a two-round modified Delphi survey, a multidisciplinary panel proposed mandatory standards on the prevention and handling of missing data for PCOR.

Results: We identified 1,790 records and assessed 30 as having relevant recommendations. We proposed 10 standards as mandatory, covering three domains. First, the single best approach is to prospectively prevent missing data occurrence. Second, use of valid statistical methods that properly reflect multiple sources of uncertainty is critical when analyzing missing data. Third, transparent and thorough reporting of missing data allows readers to judge the validity of the findings.

Conclusion: We urge researchers to adopt rigorous methodology and promote good science by applying best practices to the prevention and handling of missing data. Developing guidance on the prevention and handling of missing data for observational studies and studies that use existing records is a priority for future research. (C) 2014 Elsevier Inc. All rights reserved.”
“Laser hair removal is a relatively effective method for thick hair. Despite the risk for induction of fine hair growth, application of laser for fine dark hair is sometimes inevitable.