Bmc Med Res Methodol
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Bmc Med Res Methodol · Jan 2008
Examining intra-rater and inter-rater response agreement: a medical chart abstraction study of a community-based asthma care program.
To assess the intra- and inter-rater agreement of chart abstractors from multiple sites involved in the evaluation of an Asthma Care Program (ACP). ⋯ Though collected by multiple abstractors, the results show high sensitivity and specificity and substantial to excellent inter- and intra-rater agreement, assuring confidence in the use of chart abstraction for evaluating the ACP.
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Bmc Med Res Methodol · Jan 2008
Comparative StudyIndustry-supported meta-analyses compared with meta-analyses with non-profit or no support: differences in methodological quality and conclusions.
Studies have shown that industry-sponsored meta-analyses of drugs lack scientific rigour and have biased conclusions. However, these studies have been restricted to certain medical specialities. We compared all industry-supported meta-analyses of drug-drug comparisons with those without industry support. ⋯ Transparency is essential for readers to make their own judgment about medical interventions guided by the results of meta-analyses. We found that industry-supported meta-analyses are less transparent than meta-analyses with non-profit support or no support.
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Bmc Med Res Methodol · Jan 2008
The changing causal foundations of cancer-related symptom clustering during the final month of palliative care: a longitudinal study.
Symptoms tend to occur in what have been called symptom clusters. Early symptom cluster research was imprecise regarding the causal foundations of the coordinations between specific symptoms, and was silent on whether the relationships between symptoms remained stable over time. This study develops a causal model of the relationships between symptoms in cancer palliative care patients as they approach death, and investigates the changing associations among the symptoms and between those symptoms and well-being. ⋯ Some of the causal forces explaining the variations in, and relationships among, palliative care patients' symptoms changed over the final month of life. This illustrates how investigating the causal foundations of symptom correlation or clustering can provide more detailed understandings that may contribute to improved control of patient comfort, quality of life, and quality of death.
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Bmc Med Res Methodol · Jan 2008
Randomized Controlled TrialUse of the Oxford Handicap Scale at hospital discharge to predict Glasgow Outcome Scale at 6 months in patients with traumatic brain injury.
Traumatic brain injury (TBI) is an important cause of acquired disability. In evaluating the effectiveness of clinical interventions for TBI it is important to measure disability accurately. The Glasgow Outcome Scale (GOS) is the most widely used outcome measure in randomised controlled trials (RCTs) in TBI patients. However GOS measurement is generally collected at 6 months after discharge when loss to follow up could have occurred. The objectives of this study were to evaluate the association and predictive validity between a simple disability scale at hospital discharge, the Oxford Handicap Scale (OHS), and the GOS at 6 months among TBI patients. ⋯ We have shown that the OHS, a simple disability scale available at hospital discharge can predict disability accurately, according to the GOS, at 6 months. OHS could be used to improve the design and analysis of clinical trials in TBI patients and may also provide a valuable clinical tool for physicians to improve communication with patients and relatives when assessing a patient's prognosis at hospital discharge.
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Bmc Med Res Methodol · Jan 2008
Comparative StudyComparison of generalized estimating equations and quadratic inference functions using data from the National Longitudinal Survey of Children and Youth (NLSCY) database.
The generalized estimating equations (GEE) technique is often used in longitudinal data modeling, where investigators are interested in population-averaged effects of covariates on responses of interest. GEE involves specifying a model relating covariates to outcomes and a plausible correlation structure between responses at different time periods. While GEE parameter estimates are consistent irrespective of the true underlying correlation structure, the method has some limitations that include challenges with model selection due to lack of absolute goodness-of-fit tests to aid comparisons among several plausible models. The quadratic inference functions (QIF) method extends the capabilities of GEE, while also addressing some GEE limitations. ⋯ QIF is useful for model selection and provides more efficient parameter estimates than GEE. QIF can help investigators obtain more reliable results when used in conjunction with GEE.