Bmc Med Res Methodol
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Bmc Med Res Methodol · Jan 2008
Comparative StudyResponsiveness of five condition-specific and generic outcome assessment instruments for chronic pain.
Changes of health and quality-of-life in chronic conditions are mostly small and require specific and sensitive instruments. The aim of this study was to determine and compare responsiveness, i.e. the sensitivity to change of five outcome instruments for effect measurement in chronic pain. ⋯ The MPI was most responsive in all comparable domains followed by the SF-36. The pain-specific MPI and the generic SF-36 can be recommended for comprehensive and specific bio-psycho-social effect measurement of health and quality-of-life in chronic pain.
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Bmc Med Res Methodol · Jan 2008
ReviewNegative pressure wound therapy: potential publication bias caused by lack of access to unpublished study results data.
Negative pressure wound therapy (NPWT) is widely applied, although the evidence base is weak. Previous reviews on medical interventions have shown that conclusions based on published data alone may no longer hold after consideration of unpublished data. The main objective of this study was to identify unpublished randomised controlled trials (RCTs) on NPWT within the framework of a systematic review. ⋯ Multi-source comprehensive searches identify unpublished RCTs. However, lack of access to unpublished study results data raises doubts about the completeness of the evidence base on NPWT.
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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
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.