A ntipsychotic medications are disproportionately used in elderly populations and have been prescribed to over a quarter of US Medicare beneficiaries in nursing homes.1-3 Reasons for their use include dementia, delirium, psychosis, agitation and affective disorders, but much use is outside approved indications. 4 In addition, there have been rapid shifts away from first-generation conventional agents (e.g., chlorpromazine, haloperidol and loxapine) to more actively marketed second-generation atypical agents (e.g., clozapine, olanzapine, quetiapine and risperidone). 5In a public health advisory issued on June 15, 2005, Health Canada warned that, compared with placebo, atypical antipsychotic medications increased the risk of death by 60% in a pooled analysis of 17 short-term randomized controlled trials involving elderly patients with dementia.6 Health Canada requested that "all manufacturers of these drugs include a warning and description of this risk in the safety information sheet for each drug." The advisory did not extend to conventional antipsychotic medications, although the US Food and Drug Administration (FDA) noted that this is an important issue to study in the future. 7,8In the absence of data on the risk of death posed by conventional antipsychotic medications, there is mounting concern that clinicians may switch their elderly patients to these older agents, 9 particularly since their replacement by the newer drugs occurred so rapidly and recently.5 On the basis of extrapolations mainly from younger populations, some have suggested that the conventional formulations could, in theory, pose risks equal to or greater than those associated with the newer, atypical drugs in elderly populations.10-13 A cohort study involving US Medicare patients eligible for statefunded low-income pharmacy assistance programs showed a 37% increase in the 180-day mortality associated with the use of conventional antipsychotic medications compared with atypical ones.14 However, patients enrolled in state-funded pharmacy assistance programs are not representative of the general elderly population, since on average they have lower incomes and higher morbidity and mortality.We conducted a population-based cohort study involving all elderly people in British Columbia to compare the shortterm mortality between those prescribed a conventional antipsychotic medication and those prescribed an atypical antipsychotic medication. We also examined whether the risk of death differed by dose or duration of drug use and by dementia status and residence in a nursing home. MethodsWe conducted a cohort study involving all British Columbia residents aged 65 years or more who filled a first-recorded (index) prescription for an oral antipsychotic medication between Risk of death associated with the use of conventional versus atypical antipsychotic drugs among elderly patients Background: Public health advisories have warned that the use of atypical antipsychotic medications increases the risk of death among elderly patients. We assessed the shor...

Among critically ill adults with sepsis, resuscitation with balanced fluids was associated with a lower risk of in-hospital mortality. If confirmed in randomized trials, this finding could have significant public health implications, as crystalloid resuscitation is nearly universal in sepsis.

BACKGROUND: Although many patient, physician, and payment predictors of adherence have been described, knowledge of their relative strength and overall ability to explain adherence is limited.OBJECTIVES: To measure the contributions of patient, physician, and payment predictors in explaining adherence to statins RESEARCH DESIGN: Retrospective cohort study using administrative data SUBJECTS: 14,257 patients insured by Horizon Blue Cross Blue Shield of New Jersey (BCBSNJ) who were newly prescribed a statin cholesterol-lowering medication MEASURES: Adherence to statin medication was measured during the year after the initial prescription, based on proportion of days covered (PDC). The impact of patient, physician, and payment predictors of adherence were evaluated using multivariate logistic regression. The explanatory power of these models was evaluated with C statistics, a measure of the goodness of fit.RESULTS: Overall, 36.4% of patients were fully adherent. Older patient age, male gender, lower neighborhood percent black composition, higher median income, and fewer number of emergency department (ED) visits were significant patient predictors of adherence. Having a statin prescribed by a cardiologist, a patient's primary care physician, or a US medical graduate were significant physician predictors of adherence. Lower copayments also predicted adherence. All of our models had low explanatory power. Multivariate models including patient covariates only had greater explanatory power (C = 0.613) than models with physician variables only (C = 0.566) or copayments only (C = 0.543). A fully specified model had only slightly more explanatory power (C = 0.633) than the model with patient characteristics alone.CONCLUSIONS: Despite relatively comprehensive claims data on patients, physicians, and out-ofpocket costs, our overall ability to explain adherence remains poor. Administrative data likely do not capture many complex mechanisms underlying adherence.

Summary. Instrumental variable (IV) methods are popular in non-experimental studies to estimate the causal effects of medical interventions. These approaches allow for the consistent estimation of treatment effects even if important confounding factors are unobserved. Despite the increasing use of these methods, there have been few extensions of IV methods to censored data problems. In this article, we discuss challenges in applying IV techniques to the proportional hazards model and demonstrate the utility of the additive hazards formulation for IV analyses with censored data. Assuming linear structural equation models for the hazard function, we develop a closed-form, two-stage estimator for the causal effect in the additive hazard model. The methods permit both continuous and discrete exposures, and enable the estimation of causal relative survival measures. The asymptotic properties of the estimators are derived and the resulting inferences are shown to perform well in simulation studies and in an application to a data set on the effectiveness of a novel chemotherapeutic agent for colon cancer.

KOLOTKIN, RONETTE L, SUSAN HEAD, ALAN BROOKHART. Construct validity of the Impact of Weight on Quality of Life questionnaire. Obes Res. 1997; 54-41. The Impact of Weight on Quality of Life questionnaire (IWQOL) is a 74-item self-report, condition-specific instrument that (1) assesses the effect of weight on quality of life in eight key areas, and (2) may be used as a treatment outcome measure and/or an evaluation tool for healthcare policy makers and third-party payers. This study explores IWQOL construct validity and provides new information on internal consistency, treatment effects, and differences between men and women. IWQOL total scores correlated highly with other measures of overall quality of life, and subscale scores correlated well with counterparts in the assessment battery. Internal consistency estimates for the IWQOL scales generally were high. For the women, 4-week participants, and the total sample, pretreatment-posttreatment differences were significant for all IWQOL scales and total score. For men, treatment differences were significant for the total score and all subscales except for Work and Mobility. Treatment differences for 2-week participants were significant for all scales except for Work. Consistent with previous JWQOL study results, the Comfort With Food scale scores reflected more discomfort at posttreatment as compared with pretreatment. The IWQOL, already translated into French and Italian, currently is demonstrating clinical and research utility as a quality-of-life outcome measure for clinical trials of antiobesity drugs and surgical treatments for patients with obesity. (15), such that we now warehouse (9) and index (3) these measures. Furthermore, measures of quality of life increasingly are being used by policy analysts and healthcare providers to compare costs and benefits of different health care services and to make decisions about healthcare policy and third-party payments (16).The three well-known health-related quality-of-life instruments mentioned above are generic measures of quality of life. Generic measures are used in general populations to assess functional health across a wide range of domains, health states, and diseases and are particularly useful for comparing the relative burden of different diseases or the relative benefit of different treatments (11). On the other hand, disease-specific instruments, which focus on the domains most relevant to the diseasekondition under study and the characteristics of patients in whom the conditions are most prevalent, are particularly useful in clinical trials in which specific therapeutic interventions for spec$c diseaseskonditions are being evaluated (1 1,15). Diseasespecific outcome measures have been developed for use in numerous medical populations, including human immunodeficiency virus, respiratory diseases, diabetes, and cancer.With respect to obesity, a serious condition with associated health risks, the gold standard for successful treatment outcome typically has been weight loss itself. Although clinici...