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OBJECTIVE - The objective of this systematic literature review was to evaluate the incidences and risks for adverse events (AEs) associated with oral and parenteral corticosteroids. An assessment was performed to estimate the costs of such AEs.
METHODS - A systematic review of literature published from 2007 to 2009 was conducted to identify the incidence rates and risk ratios of corticosteroid-related AEs. The review protocol was developed according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The literature search was expanded to include additional search terms for psychiatric conditions, infections, and peptic ulcers. Costs obtained from a separate narrative literature review were applied to AEs likely to affect third-party payers in the United States.
RESULTS - A total of 357 publications were identified from the primary (n = 323) and secondary (n = 34) searches. Of these, 310 were excluded because they did not evaluate AEs related to corticosteroids, were an excluded publication type, or for other reasons. A final list of 47 studies were used for data extraction. Across patient populations, the most frequently reported corticosteroid-associated AEs were psychiatric events, infections, gastric conditions, and fractures. Corticosteroid-associated AEs reported to occur at an incidence >30% were sleep disturbances, lipodystrophy, adrenal suppression, metabolic syndrome, weight gain, and hypertension. Vertebral fractures were reported at an incidence of 21% to 30%. Dose-response relationships were documented for fractures, acute myocardial infarction, hypertension, and peptic ulcer. The costs of managing AEs that may occur with corticosteroids can be substantial. The literature reported 1-year per-patient costs of up to $26,471.80 for nonfatal myocardial infarction, and per-event costs as high as $18,357.90 for fracture. The findings from the present review should be interpreted cautiously due to several limitations, including the retrospective design of most of the studies identified, risk for confounding due to underlying disease activity or patient population, and the relatively small number of studies that reported each AE association. As this cost analysis was preliminary, a comprehensive pharmacoeconomic analysis should be undertaken to confirm the findings.
CONCLUSION - Based on the findings from this review, systemic corticosteroids are a common cause of AEs that may be costly to payers.
Copyright © 2011 Elsevier HS Journals, Inc. All rights reserved.
The lipid-lowering agent pravastatin and the antidepressant paroxetine are among the most widely prescribed drugs in the world. Unexpected interactions between them could have important public health implications. We mined the US Food and Drug Administration's (FDA's) Adverse Event Reporting System (AERS) for side-effect profiles involving glucose homeostasis and found a surprisingly strong signal for comedication with pravastatin and paroxetine. We retrospectively evaluated changes in blood glucose in 104 patients with diabetes and 135 without diabetes who had received comedication with these two drugs, using data in electronic medical record (EMR) systems of three geographically distinct sites. We assessed the mean random blood glucose levels before and after treatment with the drugs. We found that pravastatin and paroxetine, when administered together, had a synergistic effect on blood glucose. The average increase was 19 mg/dl (1.0 mmol/l) overall, and in those with diabetes it was 48 mg/dl (2.7 mmol/l). In contrast, neither drug administered singly was associated with such changes in glucose levels. An increase in glucose levels is not a general effect of combined therapy with selective serotonin reuptake inhibitors (SSRIs) and statins.
OBJECTIVE - To describe the effect of different exposure classification strategies for disease-modifying antirheumatic drugs (DMARDs) on drug-outcome associations.
METHODS - We studied the association between DMARD initiation and all-cause hospitalizations in patients with rheumatoid arthritis (RA), 1995-2005. Initiators of DMARDs and oral glucocorticoids were followed for < or =180 days. We compared 2 strategies for exposure classification: a persistent exposure required (PER) approach, in which followup stopped when the regimen changed; and a persistent exposure ignored (PEI) approach, in which followup continued despite regimen changes. For PEI, adherence was assessed using the medication possession ratio. All-cause hospitalization risk was compared among RA regimen initiators using Cox models and methotrexate as the reference.
RESULTS - We identified 28,906 episodes of medication initiation. In PER analyses, tumor necrosis factor alpha antagonists did not increase hospitalization risk compared with methotrexate, whereas leflunomide did (hazard ratio [HR] 1.36, 95% confidence interval [95% CI] 1.1-1.67). Glucocorticoids increased hospitalization risk (HR 1.29, 1.54, and 2.03 for low, medium, and high doses, respectively). PEI results were similar to PER except that infliximab initiation increased the risk of hospitalization compared with methotrexate (HR 1.46, 95% CI 1.19-1.8), and most other effects were closer to the null. In PEI, adherence ranged from 73% for etanercept to 6% for glucocorticoids and adherence to methotrexate was 59%.
CONCLUSION - Compared with methotrexate initiation, leflunomide or glucocorticoid initiation consistently increased all-cause hospitalizations in the first 180 days of use. Most PER and PEI estimates were similar; observed differences in risk between these methods were likely due to differences in adherence.
PURPOSE - Specific patient and clinical characteristics associated with an increased risk of sustaining an adverse event (AE) were identified.
METHODS - AE reports for patients in a 658-bed tertiary care medical center between January 1, 2000, and June 30, 2002, were analyzed. The data collected from each report included medical record number, patient sex, patient age, clinical service, date of occurrence, diagnoses, type of error, suspected medication, and severity of the AE. A three-stage logistic regression model with high-risk indicators was used to evaluate key indicators of the most vulnerable patient populations.
RESULTS - The number of control patients and those with AEs totaled 60,206. This population was then randomly split into two equal groups of patients: the training data set (n = 30,103) and the validation data set (n = 30,103). AEs occurred in a higher percentage of patients who were age <1 year, 1-15, 47-59, and > or =60 years than in other groups. A higher percentage of AEs were reported in men than women, but the groups were not significantly different when comparing those with an AE and those without an AE. Asian Indian patients demonstrated a high rate of AEs, but this may be a statistical artifact, reflecting their very small percentage in the study. Evaluation of admission sources revealed that doctors' offices, clinic referrals, and local hospital transfers accounted for higher rates of AEs than other sources.
CONCLUSION - Certain age groups, diagnoses, admission sources, types of insurance, and the use of specific medications or medication classes were associated with increased AE rates at a tertiary care medical center.
CONTEXT - Although patient safety is a major problem, most health care organizations rely on spontaneous reporting, which detects only a small minority of adverse events. As a result, problems with safety have remained hidden. Chart review can detect adverse events in research settings, but it is too expensive for routine use. Information technology techniques can detect some adverse events in a timely and cost-effective way, in some cases early enough to prevent patient harm.
OBJECTIVE - To review methodologies of detecting adverse events using information technology, reports of studies that used these techniques to detect adverse events, and study results for specific types of adverse events.
DESIGN - Structured review.
METHODOLOGY - English-language studies that reported using information technology to detect adverse events were identified using standard techniques. Only studies that contained original data were included.
MAIN OUTCOME MEASURES - Adverse events, with specific focus on nosocomial infections, adverse drug events, and injurious falls.
RESULTS - Tools such as event monitoring and natural language processing can inexpensively detect certain types of adverse events in clinical databases. These approaches already work well for some types of adverse events, including adverse drug events and nosocomial infections, and are in routine use in a few hospitals. In addition, it appears likely that these techniques will be adaptable in ways that allow detection of a broad array of adverse events, especially as more medical information becomes computerized.
CONCLUSION - Computerized detection of adverse events will soon be practical on a widespread basis.