Molecular evolution of primate immunodeficiency viruses and hepatitis delta virus

Primate immunodeficiency viruses, or lentiviruses (HIV-1, HIV-2, and SIV), and hepatitis delta virus (HDV) are RNA viruses characterized by rapid evolution. Infection by primate immunodeficiency viruses usually results in the development of acquired immunodeficiency syndrome (AIDS) in humans and AIDS-like illnesses in Asian macaques. Similarly, hepatitis delta virus infection causes hepatitis and liver cancer in humans. These viruses are heterogeneous within an infected patient and among individuals. Substitution rates in the virus genomes are high and vary in different lineages and among sites. Methods of phylogenetic analysis were applied to study the evolution of primate lentiviruses and the hepatitis delta virus. The following results have been obtained: (1) The substitution rate varies among sites of primate lentivirus genes according to the two parameter gamma distribution, with the shape parameter $\alpha$ being close to 1. (2) Primate immunodeficiency viruses fall into species-specific lineages. Therefore, viral transmissions across primate species are not as frequent as suggested by previous authors. (3) Primate lentiviruses have acquired or lost their pathogenicity several times in the course of evolution. (4) Evidence was provided for multiple infections of a North American patient by distinct HIV-1 strains of the B subtype. (5) Computer simulations indicate that the probability of committing an error in testing HIV transmission depends on the number of virus sequences and their length, the divergence times among sequences, and the model of nucleotide substitution. (6) For future investigations of HIV-1 transmissions, using longer virus sequences and avoiding the use of distant outgroups is recommended. (7) Hepatitis delta virus strains are usually related according to the geographic region of isolation. (8) Evolution of HDV is characterized by the rate of synonymous substitution being lower than the nonsynonymous substitution rate and the rate of evolution of the noncoding region. (9) There is a strong preference for G and C nucleotides at the third codon positions of the HDV coding region. ^

Nurse likelihood to report a pediatric medication error: Examination of the "pre-reporting" period

Each year, hospitalized patients experience 1.5 million preventable injuries from medication errors and hospitals incur an additional $3.5 billion in cost (Aspden, Wolcott, Bootman, & Cronenwatt; (2007). It is believed that error reporting is one way to learn about factors contributing to medication errors. And yet, an estimated 50% of medication errors go unreported. This period of medication error pre-reporting, with few exceptions, is underexplored. The literature focuses on error prevention and management, but lacks a description of the period of introspection and inner struggle over whether to report an error and resulting likelihood to report. Reporting makes a nurse vulnerable to reprimand, legal liability, and even threat to licensure. For some nurses this state may invoke a disparity between a person‘s belief about him or herself as a healer and the undeniable fact of the error.^ This study explored the medication error reporting experience. Its purpose was to inform nurses, educators, organizational leaders, and policy-makers about the medication error pre-reporting period, and to contribute to a framework for further investigation. From a better understanding of factors that contribute to or detract from the likelihood of an individual to report an error, interventions can be identified to help the nurse come to a psychologically healthy resolution and help increase reporting of error in order to learn from error and reduce the possibility of future similar error.^ The research question was: "What factors contribute to a nurse's likelihood to report an error?" The specific aims of the study were to: (1) describe participant nurses' perceptions of medication error reporting; (2) describe participant explanations of the emotional, cognitive, and physical reactions to making a medication error; (3) identify pre-reporting conditions that make it less likely for a nurse to report a medication error; and (4) identify pre-reporting conditions that make it more likely for a nurse to report a medication error.^ A qualitative research study was conducted to explore the medication error experience and in particular the pre-reporting period from the perspective of the nurse. A total of 54 registered nurses from a large private free-standing not-for-profit children's hospital in the southwestern United States participated in group interviews. The results describe the experience of the nurse as well as the physical, emotional, and cognitive responses to the realization of the commission of a medication error. The results also reveal factors that make it more and less likely to report a medication error.^ It is clear from this study that upon realization that he or she has made a medication error, a nurse's foremost concern is for the safety of the patient. Fear was also described by each group of nurses. The nurses described a fear of several things including physician reaction, manager reaction, peer reaction, as well as family reaction and possible lack of trust as a result. Another universal response was the description of a struggle with guilt, shame, imperfection, blaming oneself, and questioning one's competence.^

A simulation study of the effects of small center enrollment in multi -center clinical trials

Multi-center clinical trials are very common in the development of new drugs and devices. One concern in such trials, is the effect of individual investigational sites enrolling small numbers of patients on the overall result. Can the presence of small centers cause an ineffective treatment to appear effective when treatment-by-center interaction is not statistically significant?^ In this research, simulations are used to study the effect that centers enrolling few patients may have on the analysis of clinical trial data. A multi-center clinical trial with 20 sites is simulated to investigate the effect of a new treatment in comparison to a placebo treatment. Twelve of these 20 investigational sites are considered small, each enrolling less than four patients per treatment group. Three clinical trials are simulated with sample sizes of 100, 170 and 300. The simulated data is generated with various characteristics, one in which treatment should be considered effective and another where treatment is not effective. Qualitative interactions are also produced within the small sites to further investigate the effect of small centers under various conditions.^ Standard analysis of variance methods and the "sometimes-pool" testing procedure are applied to the simulated data. One model investigates treatment and center effect and treatment-by-center interaction. Another model investigates treatment effect alone. These analyses are used to determine the power to detect treatment-by-center interactions, and the probability of type I error.^ We find it is difficult to detect treatment-by-center interactions when only a few investigational sites enrolling a limited number of patients participate in the interaction. However, we find no increased risk of type I error in these situations. In a pooled analysis, when the treatment is not effective, the probability of finding a significant treatment effect in the absence of significant treatment-by-center interaction is well within standard limits of type I error. ^