Clinical assessments of photodamage are based upon a subjective evaluation of characteristic features such as wrinkling and pigmentary change, and are influenced by inter-observer differences in grading criteria. In an effort to standardize the grading of photodamage severity, we have developed a six-point photographic scale in which each of the six grades of overall photodamage severity is depicted by three photographs. The use of three photographs to portray each grade illustrates the diversity and range of manifestations within each grade. This photographic scale was tested by two groups of dermatologists, who used it on two occasions to grade the overall photodamage severity of a single group of female Caucasian subjects. Results indicate high inter-observer agreement, with chance-corrected agreement ranging from 0.44 to 0.63 and from 0.54 to 0.76 on the first and second occasions, respectively. Intra-observer repeatability was high, with chance-corrected agreement ranging from 0.56 to 0.78. Inter- and intra-observer differences were within one category in nearly all cases. Similar grades were assigned by dermatologists with and without experience in treating photodamaged patients. We conclude that application of this scale results in consistent and reproducible clinical evaluations of overall photodamage severity in Caucasian subjects. The scale may be useful in categorizing subjects for epidemiological studies, or in selecting patients for clinical trials.

Composite measurement scales (CMS) are increasingly used in medicine to measure complex phenomena or concepts such as disease risk and severity, physical and psychological functioning and quality of life. To investigate the methodology currently used in the construction of CMS, we examined 46 studies recently published in six major medical and epidemiological journals. Important measurement properties such as measurement level, content and construct validity and reliability are often neglected. Statistical methods, particularly multivariate methods are frequently misused; verifications of model relevance and assumptions, and cross-validations to avoid overfitting are seldom performed. We propose recommendations for the construction and the presentation of CMS, to help authors and investigators to report and choose, respectively, measurement instruments for a complex phenomenon.

Heart disease in patients with progressive systemic sclerosis may be due in part to myocardial ischemia caused by a disturbance of the coronary microcirculation. To determine whether abnormalities of myocardial perfusion in this disorder are potentially reversible, we evaluated the effect of the coronary vasodilator nifedipine on myocardial perfusion assessed by thallium-201 scanning in 20 patients. Thallium-201 single-photon-emission computerized tomography was performed under control conditions and 90 minutes after 20 mg of oral nifedipine. The mean (+/- SD) number of left ventricular segments with perfusion defects decreased from 5.3 +/- 2.0 to 3.3 +/- 2.2 after nifedipine (P = 0.0003). Perfusion abnormalities were quantified by a perfusion score (0 to 2.0) assigned to each left ventricular segment and by a global perfusion score (0 to 18) for the entire left ventricle. The mean perfusion score in segments with resting defects increased from 0.97 +/- 0.24 to 1.26 +/- 0.44 after nifedipine (P less than 0.00001). The mean global perfusion score increased from 11.2 +/- 1.7 to 12.8 +/- 2.4 after nifedipine (P = 0.003). The global perfusion score increased by at least 2.0 in 10 patients and decreased by at least 2.0 in only 1. These observations reveal short-term improvement in thallium-201 myocardial perfusion with nifedipine in patients with progressive systemic sclerosis. The results are consistent with a potentially reversible abnormality of coronary vasomotion in this disorder, but the long-term therapeutic effects of nifedipine remain to be determined.

Background: Many medication errors are encountered in drug prescriptions, which would not occur if practitioners could remember the drug properties. They can refer to drug monographs to find these properties, however drug monographs are long and tedious to read during consultation. We propose a two-step approach for facilitating access to drug monographs. The first step, presented here, is the design of a graphical language, called VCM.

Computerised queries in spontaneous reporting systems for pharmacovigilance require reliable and reproducible coding of adverse drug reactions (ADRs). The aim of the Medical Dictionary for Regulatory Activities (MedDRA) terminology is to provide an internationally approved classification for efficient communication of ADR data between countries. Several studies have evaluated the domain completeness of MedDRA and whether encoded terms are coherent with physicians' original verbatim descriptions of the ADR. MedDRA terms are organised into five levels: system organ class (SOC), high level group terms (HLGTs), high level terms (HLTs), preferred terms (PTs) and low level terms (LLTs). Although terms may belong to different SOCs, no PT is related to more than one HLT within the same SOC. This hierarchical property ensures that terms cannot be counted twice in statistical studies, though it does not allow appropriate semantic grouping of PTs. For this purpose, special search categories (SSCs) [collections of PTs assembled from various SOCs] have been introduced in MedDRA to group terms with similar meanings. However, only a small number of categories are currently available and the criteria used to construct these categories have not been clarified. The objective of this work is to determine whether MedDRA contains the structural and terminological properties to group semantically linked adverse events in order to improve the performance of spontaneous reporting systems. Rossi Mori classifies terminological systems in three categories: first-generation systems, which represent terms as strings; second-generation systems, which dissect terminological phrases into a set of simpler terms; and third-generation systems, which provide advanced features to automatically retrieve the position of new terms in the classification and group sets of meaning-related terms. We applied Cimino's desiderata to show that MedDRA is not compatible with the properties of third-generation systems. Consequently, no tool can help for the automated positioning of new terms inside the hierarchy and SSCs have to be entered manually rather than automatically using the MedDRA files. One solution could be to link MedDRA to a third-generation system. This would allow the current MedDRA structure to be kept to ensure that end users have a common view on the same data and the addition of new computational properties to MedDRA.

The interface designed according to usability principles was perceived to be more usable and inspired greater confidence among physicians than the guided navigation interface. Consideration of usability principles in the construction of an interface--in particular 'effective information presentation', 'consistency', 'efficient interactions', 'effective use of language', and 'minimizing cognitive load'--seemed to improve perceived usability and confidence in the system.

BackgroundClinical guidelines carry medical evidence to the point of practice. As evidence is not always available, many guidelines do not provide recommendations for all clinical situations encountered in practice. We propose an approach for identifying knowledge gaps in guidelines and for exploring physicians' therapeutic decisions with data mining techniques to fill these knowledge gaps. We demonstrate our method by an example in the domain of type 2 diabetes.MethodsWe analyzed the French national guidelines for the management of type 2 diabetes to identify clinical conditions that are not covered or those for which the guidelines do not provide recommendations. We extracted patient records corresponding to each clinical condition from a database of type 2 diabetic patients treated at Avicenne University Hospital of Bobigny, France. We explored physicians' prescriptions for each of these profiles using C5.0 decision-tree learning algorithm. We developed decision-trees for different levels of detail of the therapeutic decision, namely the type of treatment, the pharmaco-therapeutic class, the international non proprietary name, and the dose of each medication. We compared the rules generated with those added to the guidelines in a newer version, to examine their similarity.ResultsWe extracted 27 rules from the analysis of a database of 463 patient records. Eleven rules were about the choice of the type of treatment and thirteen rules about the choice of the pharmaco-therapeutic class of each drug. For the choice of the international non proprietary name and the dose, we could extract only a few rules because the number of patient records was too low for these factors. The extracted rules showed similarities with those added to the newer version of the guidelines.ConclusionOur method showed its usefulness for completing guidelines recommendations with rules learnt automatically from physicians' prescriptions. It could be used during the development of guidelines as a complementary source from practice-based knowledge. It can also be used as an evaluation tool for comparing a physician's therapeutic decisions with those recommended by a given set of clinical guidelines. The example we described showed that physician practice was in some ways ahead of the guideline.

A quantitative method of skin healing assessment using true color image processing is presented. The method was developed during a clinical trial using healthy volunteers, the goal of which was to study a drug for accelerating healing. Photographic images of the skin were sequentially acquired between day 1 and day 12 after pure painless epidermal wounds. The images were digitized in controlled conditions using a color video camera connected to a computer system. A color threshold based segmentation was developed to provide an operator-independent delineation of the wound. Two healing indexes were built measuring, the wound area and the wound color. The method was implemented in a software system allowing a fully automated determination of the healing indexes. The method provides a new quantitative global assessment of healing kinetics. It is noninvasive and well suited for multicentric clinical trials.