Background:

Coronary atherosclerosis develops slowly over decades but is frequently characterized clinically by sudden unstable episodes. Patients who present with unstable coronary disease, such as acute myocardial infarction, may systematically differ from patients who present with relatively stable coronary disease, such as exertional angina.

Objective:

To examine whether medication use or patient characteristics influence the mode of initial clinical presentation of coronary disease.

Design:

Case-control study.

Setting:

Large integrated health care delivery system in northern California.

Patients:

Adults whose first clinical presentation of coronary disease was either acute myocardial infarction (n = 916) or stable exertional angina (n = 468).

Measurements:

Use of cardiac medications before the event from pharmacy databases and demographic, lifestyle, and clinical characteristics from self-report and clinical and administrative databases.

Results:

Compared with patients with incident stable exertional angina, patients with incident acute myocardial infarction were more likely to be men, smokers, physically inactive, and hypertensive but were less likely to have a parental history of coronary disease. Patients presenting with myocardial infarction were much less likely to have received statins (19.3% vs. 40.4%; P 0.001) and ß-blockers (19.0% vs. 47.7%; P 0.001) than patients presenting with exertional angina. After adjustment for potential confounders, recent use of statins (adjusted odds ratio, 0.45 [95% CI, 0.32 to 0.62]) and ß-blockers (adjusted odds ratio, 0.26 [CI, 0.19 to 0.35]) was associated with lower likelihoods of presenting with an acute myocardial infarction than with stable angina.

Limitations:

This observational study did not have information on all possible confounding factors, including use of aspirin therapy.

Conclusion:

Statin and ß-blocker use was associated with lower odds of presenting with an acute myocardial infarction than with stable angina. Additional studies are needed to confirm that these therapies protect against unstable, higher-risk clinical presentations of coronary disease.

Background:

Mortality from inhalational anthrax during the 2001 U.S. attack was substantially lower than that reported historically.

Purpose:

To systematically review all published inhalational anthrax case reports to evaluate the predictors of disease progression and mortality.

Data Sources:

MEDLINE (1966-2005), 14 selected journal indexes (1900-1966), and bibliographies of all retrieved articles.

Study Selection:

Case reports (in any language) between 1900 and 2005 that met predefined criteria.

Data Extraction:

Two authors (1 author for non-English-language reports) independently abstracted patient data.

Data Synthesis:

The authors found 106 reports of 82 cases of inhalational anthrax. Mortality was statistically significantly lower for patients receiving antibiotics or anthrax antiserum during the prodromal phase of disease, multidrug antibiotic regimens, or pleural fluid drainage. Patients in the 2001 U.S. attack were less likely to die than historical anthrax case-patients (45% vs. 92%; P < 0.001) and were more likely to receive antibiotics during the prodromal phase (64% vs. 13%; P < 0.001), multidrug regimens (91% vs. 50%; P = 0.027), or pleural fluid drainage (73% vs. 11%; P < 0.001). Patients who progressed to the fulminant phase had a mortality rate of 97% (regardless of the treatment they received), and all patients with anthrax meningoencephalitis died.

Limitations:

This was a retrospective case review of previously published heterogeneous reports.

Conclusions:

Despite advances in supportive care, fulminant-phase inhalational anthrax is usually fatal. Initiation of antibiotic or anthrax antiserum therapy during the prodromal phase is associated with markedly improved survival, although other aspects of care, differences in clinical circumstances, or unreported factors may contribute to this observed reduction in mortality. Efforts to improve early diagnosis and timely initiation of appropriate antibiotics are critical to reducing mortality.

This report documents the work undertaken in Phase I of a two-phase process to develop the Pediatric Quality Indicators as part of the Agency for Healthcare Research and Quality (AHRQ) contract, "Support for Quality Indicators II" under subcontract with

Battelle Memorial Institute by Stanford University and the University of California at

Davis. This work was initiated in response to a charge to develop indicators of children's health care utilizing inpatient administrative data. These indicators examine both the quality of inpatient care, as well as the quality of outpatient care that can be inferred from inpatient data, such as potentially preventable hospitalizations.

The report contains three main sections:

1. The introduction section launches the actual technical report and provides background

regarding pediatric indicator development and the current effort to develop an indicator

set based on administrative data.

2. The methods section outlines the approach used to gather evidence to identify and

evaluate potential patient safety indicators, including the literature review, empirical

analyses, and clinician panel review, as well as the operationalization of indicators and

evaluation of risk adjustment approaches.

3. The results section is divided into two parts. The first part highlights general themes

and summarizes the overall results. The second part provides detailed results for each

AHRQ QI examined.

Several appendixes provide additional detail regarding methods and results.

Outcomes research often requires estimating the impact of a binary treatment on a binary outcome in a non-randomized setting, such as the effect of taking a drug on mortality. The data often come from self-selected samples, leading to a spurious correlation between the treatment and outcome when standard binary dependent variable techniques, like logit or probit, are used. Intuition suggests that a two-step procedure (analogous to two-stage least squares) might be sufficient to deal with this problem if variables are available that are correlated with the treatment choice but not the outcome.

This paper demonstrates the limitations of such a two-step procedure. We show that such estimators will not generally be consistent. We conduct a Monte Carlo exercise to compare the performance of the two-step probit estimator, the two-stage least squares linear probability model estimator, and the multivariate probit. The results from this exercise argue in favour of using the multivariate probit rather than the two-step or linear probability model estimators, especially when there is more than one treatment, when the average probability of the dependent variable is close to 0 or 1, or when the data generating process is not normal. We demonstrate how these different methods perform in an empirical example examining the effect of private and public insurance coverage on the mortality of HIV+ patients.

We sought to understand how diagnosis with HIV affects health-related quality of life. We assessed health-related quality of life using utility-based measures in a Department of Veterans Affairs (VA) clinic and a University-based clinic. Respondents assessed health-related quality of life regarding their current health, and retrospectively assessed their health 1 month prior to and 2 months after diagnosis with HIV infection. Sixty-six patients completed the study. The overall mean utilities for health 1 month before and 2 months after diagnosis were 0.87 (standard error 0.037), and 0.80 (0.043) (p0.005 by rank sign test), but the effect of diagnosis differed between the two clinics, with a substantial decrease in the university clinic and a small non-significant decrease in the VA clinic. The overall mean utility for current health was 0.85 (0.034), assessed on average 7.5 years after diagnosis. When asked directly whether diagnosis of HIV decreased health-related quality of life, 47% agreed, but 35% stated that HIV diagnosis positively affected health-related quality of life. Diagnosis with HIV decreased health-related quality of life at 2 months on average, but this effect diminished over time, and differed among patient populations. Years after diagnosis, although half of the patients believed that diagnosis reduced health-related quality of life, one-third reported improved health-related quality of life.