975 resultados para Clinical validation
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The purpose of the study is: (1) to describe how nursing students' experienced their clinical learning environment and the supervision given by staff nurses working in hospital settings; and (2) to develop and test an evaluation scale of Clinical Learning Environment and Supervision (CLES). The study has been carried out in different phases. The pilot study (n=163) explored the association between the characteristics of a ward and its evaluation as a learning environment by students. The second version of research instrument (which was developed by the results of this pilot study) were tested by an expert panel (n=9 nurse teachers) and test-retest group formed by student nurses (n=38). After this evaluative phase, the CLES was formed as the basic research instrument for this study and it was tested with the Finnish main sample (n=416). In this phase, a concurrent validity instrument (Dunn & Burnett 1995) was used to confirm the validation process of CLES. The international comparative study was made by comparing the Finnish main sample with a British sample (n=142). The international comparative study was necessary for two reasons. In the instrument developing process, there is a need to test the new instrument in some other nursing culture. Other reason for comparative international study is the reflecting the impact of open employment markets in the European Union (EU) on the need to evaluate and to integrate EU health care educational systems. The results showed that the individualised supervision system is the most used supervision model and the supervisory relationship with personal mentor is the most meaningful single element of supervision evaluated by nursing students. The ward atmosphere and the management style of ward manager are the most important environmental factors of the clinical ward. The study integrates two theoretical elements - learning environment and supervision - in developing a preliminary theoretical model. The comparative international study showed that, Finnish students were more satisfied and evaluated their clinical placements and supervision with higher scores than students in the United Kingdom (UK). The difference between groups was statistical highly significant (p= 0.000). In the UK, clinical placements were longer but students met their nurse teachers less frequently than students in Finland. Arrangements for supervision were similar. This research process has produced the evaluation scale (CLES), which can be used in research and quality assessments of clinical learning environment and supervision in Finland and in the UK. CLES consists of 27 items and it is sub-divided into five sub-dimensions. Cronbach's alpha coefficient varied from high 0.94 to marginal 0.73. CLES is a compact evaluation scale and user-friendliness makes it suitable for continuing evaluation.
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INTRODUCTION: A clinical decision rule to improve the accuracy of a diagnosis of influenza could help clinicians avoid unnecessary use of diagnostic tests and treatments. Our objective was to develop and validate a simple clinical decision rule for diagnosis of influenza. METHODS: We combined data from 2 studies of influenza diagnosis in adult outpatients with suspected influenza: one set in California and one in Switzerland. Patients in both studies underwent a structured history and physical examination and had a reference standard test for influenza (polymerase chain reaction or culture). We randomly divided the dataset into derivation and validation groups and then evaluated simple heuristics and decision rules from previous studies and 3 rules based on our own multivariate analysis. Cutpoints for stratification of risk groups in each model were determined using the derivation group before evaluating them in the validation group. For each decision rule, the positive predictive value and likelihood ratio for influenza in low-, moderate-, and high-risk groups, and the percentage of patients allocated to each risk group, were reported. RESULTS: The simple heuristics (fever and cough; fever, cough, and acute onset) were helpful when positive but not when negative. The most useful and accurate clinical rule assigned 2 points for fever plus cough, 2 points for myalgias, and 1 point each for duration <48 hours and chills or sweats. The risk of influenza was 8% for 0 to 2 points, 30% for 3 points, and 59% for 4 to 6 points; the rule performed similarly in derivation and validation groups. Approximately two-thirds of patients fell into the low- or high-risk group and would not require further diagnostic testing. CONCLUSION: A simple, valid clinical rule can be used to guide point-of-care testing and empiric therapy for patients with suspected influenza.
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Summary Background: We previously derived a clinical prognostic algorithm to identify patients with pulmonary embolism (PE) who are at low-risk of short-term mortality who could be safely discharged early or treated entirely in an outpatient setting. Objectives: To externally validate the clinical prognostic algorithm in an independent patient sample. Methods: We validated the algorithm in 983 consecutive patients prospectively diagnosed with PE at an emergency department of a university hospital. Patients with none of the algorithm's 10 prognostic variables (age >/= 70 years, cancer, heart failure, chronic lung disease, chronic renal disease, cerebrovascular disease, pulse >/= 110/min., systolic blood pressure < 100 mm Hg, oxygen saturation < 90%, and altered mental status) at baseline were defined as low-risk. We compared 30-day overall mortality among low-risk patients based on the algorithm between the validation and the original derivation sample. We also assessed the rate of PE-related and bleeding-related mortality among low-risk patients. Results: Overall, the algorithm classified 16.3% of patients with PE as low-risk. Mortality at 30 days was 1.9% among low-risk patients and did not differ between the validation and the original derivation sample. Among low-risk patients, only 0.6% died from definite or possible PE, and 0% died from bleeding. Conclusions: This study validates an easy-to-use, clinical prognostic algorithm for PE that accurately identifies patients with PE who are at low-risk of short-term mortality. Low-risk patients based on our algorithm are potential candidates for less costly outpatient treatment.
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Le "Chest wall syndrome" (CWS) est défini comme étant une source bénigne de douleurs thoraciques, localisées sur la paroi thoracique antérieure et provoquées par une affection musculosquelettique. Le CWS représente la cause la plus fréquente de douleurs thoraciques en médecine de premier recours. Le but de cette étude est de développer et valider un score de prédiction clinique pour le CWS. Une revue de la littérature a d'abord été effectuée, d'une part pour savoir si un tel score existait déjà, et d'autre part pour retrouver les variables décrites comme étant prédictives d'un CWS. Le travail d'analyse statistique a été effectué avec les données issues d'une cohorte clinique multicentrique de patients qui avaient consulté en médecine de premier recours en Suisse romande avec une douleur thoracique (59 cabinets, 672 patients). Un diagnostic définitif avait été posé à 12 mois de suivi. Les variables pertinentes ont été sélectionnées par analyses bivariées, et le score de prédiction clinique a été développé par régression logistique multivariée. Une validation externe de ce score a été faite en utilisant les données d'une cohorte allemande (n= 1212). Les analyses bivariées ont permis d'identifier 6 variables caractérisant le CWS : douleur thoracique (ni rétrosternale ni oppressive), douleur en lancées, douleur bien localisée, absence d'antécédent de maladie coronarienne, absence d'inquiétude du médecin et douleur reproductible à la palpation. Cette dernière variable compte pour 2 points dans le score, les autres comptent pour 1 point chacune; le score total s'étend donc de 0 à 7 points. Dans la cohorte de dérivation, l'aire sous la courbe sensibilité/spécificité (courbe ROC) est de 0.80 (95% de l'intervalle de confiance : 0.76-0.83). Avec un seuil diagnostic de > 6 points, le score présente 89% de spécificité et 45% de sensibilité. Parmi tous les patients qui présentaient un CWS (n = 284), 71% (n = 201) avaient une douleur reproductible à la palpation et 45% (n= 127) sont correctement diagnostiqués par le score. Pour une partie (n = 43) de ces patients souffrant de CWS et correctement classifiés, 65 investigations complémentaires (30 électrocardiogrammes, 16 radiographies du thorax, 10 analyses de laboratoire, 8 consultations spécialisées, et une tomodensitométrie thoracique) avaient été réalisées pour parvenir au diagnostic. Parmi les faux positifs (n = 41), on compte trois angors stables (1.8% de tous les positifs). Les résultats de la validation externe sont les suivants : une aire sous la courbe ROC de 0.76 (95% de l'intervalle de confiance : 0.73-0.79) avec une sensibilité de 22% et une spécificité de 93%. Ce score de prédiction clinique pour le CWS constitue un complément utile à son diagnostic, habituellement obtenu par exclusion. En effet, pour les 127 patients présentant un CWS et correctement classifiés par notre score, 65 investigations complémentaires auraient pu être évitées. Par ailleurs, la présence d'une douleur thoracique reproductible à la palpation, bien qu'étant sa plus importante caractéristique, n'est pas pathognomonique du CWS.
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BACKGROUND: A 70-gene signature was previously shown to have prognostic value in patients with node-negative breast cancer. Our goal was to validate the signature in an independent group of patients. METHODS: Patients (n = 307, with 137 events after a median follow-up of 13.6 years) from five European centers were divided into high- and low-risk groups based on the gene signature classification and on clinical risk classifications. Patients were assigned to the gene signature low-risk group if their 5-year distant metastasis-free survival probability as estimated by the gene signature was greater than 90%. Patients were assigned to the clinicopathologic low-risk group if their 10-year survival probability, as estimated by Adjuvant! software, was greater than 88% (for estrogen receptor [ER]-positive patients) or 92% (for ER-negative patients). Hazard ratios (HRs) were estimated to compare time to distant metastases, disease-free survival, and overall survival in high- versus low-risk groups. RESULTS: The 70-gene signature outperformed the clinicopathologic risk assessment in predicting all endpoints. For time to distant metastases, the gene signature yielded HR = 2.32 (95% confidence interval [CI] = 1.35 to 4.00) without adjustment for clinical risk and hazard ratios ranging from 2.13 to 2.15 after adjustment for various estimates of clinical risk; clinicopathologic risk using Adjuvant! software yielded an unadjusted HR = 1.68 (95% CI = 0.92 to 3.07). For overall survival, the gene signature yielded an unadjusted HR = 2.79 (95% CI = 1.60 to 4.87) and adjusted hazard ratios ranging from 2.63 to 2.89; clinicopathologic risk yielded an unadjusted HR = 1.67 (95% CI = 0.93 to 2.98). For patients in the gene signature high-risk group, 10-year overall survival was 0.69 for patients in both the low- and high-clinical risk groups; for patients in the gene signature low-risk group, the 10-year survival rates were 0.88 and 0.89, respectively. CONCLUSIONS: The 70-gene signature adds independent prognostic information to clinicopathologic risk assessment for patients with early breast cancer.
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Background: A patient's chest pain raises concern for the possibility of coronary heart disease (CHD). An easy to use clinical prediction rule has been derived from the TOPIC study in Lausanne. Our objective is to validate this clinical score for ruling out CHD in primary care patients with chest pain. Methods: This secondary analysis used data collected from a oneyear follow-up cohort study attending 76 GPs in Germany. Patients attending their GP with chest pain were questioned on their age, gender, duration of chest pain (1-60 min), sternal pain location, pain increases with exertion, absence of tenderness point at palpation, cardiovascular risks factors, and personal history of cardiovascular disease. Area under the curve (ROC), sensitivity and specificity of the Lausanne CHD score were calculated for patients with full data. Results: 1190 patients were included. Full data was available for 509 patients (42.8%). Missing data was not related to having CHD (p = 0.397) or having a cardiovascular risk factor (p = 0.275). 76 (14.9%) were diagnosed with a CHD. Prevalence of CHD were respectively of 68/344 (19.8%), 2/62 (3.2%), 6/103 (5.8%) in the high, intermediate and low risk category. ROC was of 72.9 (CI95% 66.8; 78.9). Ruling out patients with low risk has a sensitivity of 92.1% (CI95% 83.0; 96.7) and a specificity of 22.4% (CI95% 18.6%; 26.7%). Conclusion: The Lausanne CHD score shows reasonably good sensitivity and can be used to rule out coronary events in patients with chest pain. Patients at risk of CHD for other rarer reasons should nevertheless also be investigated.
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BACKGROUND: Genotypes obtained with commercial SNP arrays have been extensively used in many large case-control or population-based cohorts for SNP-based genome-wide association studies for a multitude of traits. Yet, these genotypes capture only a small fraction of the variance of the studied traits. Genomic structural variants (GSV) such as Copy Number Variation (CNV) may account for part of the missing heritability, but their comprehensive detection requires either next-generation arrays or sequencing. Sophisticated algorithms that infer CNVs by combining the intensities from SNP-probes for the two alleles can already be used to extract a partial view of such GSV from existing data sets. RESULTS: Here we present several advances to facilitate the latter approach. First, we introduce a novel CNV detection method based on a Gaussian Mixture Model. Second, we propose a new algorithm, PCA merge, for combining copy-number profiles from many individuals into consensus regions. We applied both our new methods as well as existing ones to data from 5612 individuals from the CoLaus study who were genotyped on Affymetrix 500K arrays. We developed a number of procedures in order to evaluate the performance of the different methods. This includes comparison with previously published CNVs as well as using a replication sample of 239 individuals, genotyped with Illumina 550K arrays. We also established a new evaluation procedure that employs the fact that related individuals are expected to share their CNVs more frequently than randomly selected individuals. The ability to detect both rare and common CNVs provides a valuable resource that will facilitate association studies exploring potential phenotypic associations with CNVs. CONCLUSION: Our new methodologies for CNV detection and their evaluation will help in extracting additional information from the large amount of SNP-genotyping data on various cohorts and use this to explore structural variants and their impact on complex traits.
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BACKGROUND: The Marburg Heart Score (MHS) aims to assist GPs in safely ruling out coronary heart disease (CHD) in patients presenting with chest pain, and to guide management decisions. AIM: To investigate the diagnostic accuracy of the MHS in an independent sample and to evaluate the generalisability to new patients. DESIGN AND SETTING: Cross-sectional diagnostic study with delayed-type reference standard in general practice in Hesse, Germany. METHOD: Fifty-six German GPs recruited 844 males and females aged ≥ 35 years, presenting between July 2009 and February 2010 with chest pain. Baseline data included the items of the MHS. Data on the subsequent course of chest pain, investigations, hospitalisations, and medication were collected over 6 months and were reviewed by an independent expert panel. CHD was the reference condition. Measures of diagnostic accuracy included the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, likelihood ratios, and predictive values. RESULTS: The AUC was 0.84 (95% confidence interval [CI] = 0.80 to 0.88). For a cut-off value of 3, the MHS showed a sensitivity of 89.1% (95% CI = 81.1% to 94.0%), a specificity of 63.5% (95% CI = 60.0% to 66.9%), a positive predictive value of 23.3% (95% CI = 19.2% to 28.0%), and a negative predictive value of 97.9% (95% CI = 96.2% to 98.9%). CONCLUSION: Considering the diagnostic accuracy of the MHS, its generalisability, and ease of application, its use in clinical practice is recommended.
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ABSTRACT: BACKGROUND: Chest wall syndrome (CWS), the main cause of chest pain in primary care practice, is most often an exclusion diagnosis. We developed and evaluated a clinical prediction rule for CWS. METHODS: Data from a multicenter clinical cohort of consecutive primary care patients with chest pain were used (59 general practitioners, 672 patients). A final diagnosis was determined after 12 months of follow-up. We used the literature and bivariate analyses to identify candidate predictors, and multivariate logistic regression was used to develop a clinical prediction rule for CWS. We used data from a German cohort (n = 1212) for external validation. RESULTS: From bivariate analyses, we identified six variables characterizing CWS: thoracic pain (neither retrosternal nor oppressive), stabbing, well localized pain, no history of coronary heart disease, absence of general practitioner's concern, and pain reproducible by palpation. This last variable accounted for 2 points in the clinical prediction rule, the others for 1 point each; the total score ranged from 0 to 7 points. The area under the receiver operating characteristic (ROC) curve was 0.80 (95% confidence interval 0.76-0.83) in the derivation cohort (specificity: 89%; sensitivity: 45%; cut-off set at 6 points). Among all patients presenting CWS (n = 284), 71% (n = 201) had a pain reproducible by palpation and 45% (n = 127) were correctly diagnosed. For a subset (n = 43) of these correctly classified CWS patients, 65 additional investigations (30 electrocardiograms, 16 thoracic radiographies, 10 laboratory tests, eight specialist referrals, one thoracic computed tomography) had been performed to achieve diagnosis. False positives (n = 41) included three patients with stable angina (1.8% of all positives). External validation revealed the ROC curve to be 0.76 (95% confidence interval 0.73-0.79) with a sensitivity of 22% and a specificity of 93%. CONCLUSIONS: This CWS score offers a useful complement to the usual CWS exclusion diagnosing process. Indeed, for the 127 patients presenting CWS and correctly classified by our clinical prediction rule, 65 additional tests and exams could have been avoided. However, the reproduction of chest pain by palpation, the most important characteristic to diagnose CWS, is not pathognomonic.
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Chaque jour, le médecin utilise dans sa pratique des scores cliniques. Ces scores sont souvent des aides à la décision médicale. Les étapes de validation des scores cliniques sont par contre souvent méconnues du médecin. Cette revue rappelle les bases théoriques de la validation d'un score clinique et propose des exercices pratiques. [Abstract] Physicians are using clinical scores on a regular basis. These scores are generally helpful in making medical decisions. However, the process of validation of clinical scores is often unknown to the physicians. This paper reviews the theory of validation of clinical scores and proposes practical exercises.
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The current study aimed to explore the validity of an adaptation into French of the self-rated form of the Health of the Nation Outcome Scales for Children and Adolescents (F-HoNOSCA-SR) and to test its usefulness in a clinical routine use. One hundred and twenty nine patients, admitted into two inpatient units, were asked to participate in the study. One hundred and seven patients filled out the F-HoNOSCA-SR (for a subsample (N=17): at two occasions, one week apart) and the strengths and difficulties questionnaire (SDQ). In addition, the clinician rated the clinician-rated form of the HoNOSCA (HoNOSCA-CR, N=82). The reliability (assessed with split-half coefficient, item response theory (IRT) models and intraclass correlations (ICC) between the two occasions) revealed that the F-HoNSOCA-SR provides reliable measures. The concurrent validity assessed by correlating the F-HoNOSCA-SR and the SDQ revealed a good convergent validity of the instrument. The relationship analyses between the F-HoNOSCA-SR and the HoNOSCA-CR revealed weak but significant correlations. The comparison between the F-HoNOSCA-SR and the HoNOSCA-CR with paired sample t-tests revealed a higher score for the self-rated version. The F-HoNSOCA-SR was reported to provide reliable measures. In addition, it allows us to measure complementary information when used together with the HoNOSCA-CR.
Severity score system for progressive myelopathy: development and validation of a new clinical scale
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Progressive myelopathies can be secondary to inborn errors of metabolism (IEM) such as mucopolysaccharidosis, mucolipidosis, and adrenomyeloneuropathy. The available scale, Japanese Orthopaedic Association (JOA) score, was validated only for degenerative vertebral diseases. Our objective is to propose and validate a new scale addressing progressive myelopathies and to present validating data for JOA in these diseases. A new scale, Severity Score System for Progressive Myelopathy (SSPROM), covering motor disability, sphincter dysfunction, spasticity, and sensory losses. Inter- and intra-rater reliabilities were measured. External validation was tested by applying JOA, the Expanded Disability Status Scale (EDSS), the Barthel index, and the Osame Motor Disability Score. Thirty-eight patients, 17 with adrenomyeloneuropathy, 3 with mucopolysaccharidosis I, 3 with mucopolysaccharidosis IV, 2 with mucopolysaccharidosis VI, 2 with mucolipidosis, and 11 with human T-cell lymphotropic virus type-1 (HTLV-1)-associated myelopathy participated in the study. The mean ± SD SSPROM and JOA scores were 74.6 ± 11.4 and 12.4 ± 2.3, respectively. Construct validity for SSPROM (JOA: r = 0.84, P < 0.0001; EDSS: r = -0.83, P < 0.0001; Barthel: r = 0.56, P < 0.002; Osame: r = -0.94, P < 0.0001) and reliability (intra-rater: r = 0.83, P < 0.0001; inter-rater: r = 0.94, P < 0.0001) were demonstrated. The metric properties of JOA were similar to those found in SSPROM. Several clinimetric requirements were met for both SSPROM and JOA scales. Since SSPROM has a wider range, it should be useful for follow-up studies on IEM myelopathies.
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Afin d’adresser la variabilité interindividuelle observée dans la réponse pharmacocinétique à de nombreux médicaments, nous avons créé un panel de génotypage personnalisée en utilisant des méthodes de conception et d’élaboration d’essais uniques. Celles-ci ont pour but premier de capturer les variations génétiques présentent dans les gènes clés impliqués dans les processus d'absorption, de distribution, de métabolisme et d’excrétion (ADME) de nombreux agents thérapeutiques. Bien que ces gènes et voies de signalement sont impliqués dans plusieurs mécanismes pharmacocinétiques qui sont bien connues, il y a eu jusqu’à présent peu d'efforts envers l’évaluation simultanée d’un grand nombre de ces gènes moyennant un seul outil expérimental. La recherche pharmacogénomique peut être réalisée en utilisant deux approches: 1) les marqueurs fonctionnels peuvent être utilisés pour présélectionner ou stratifier les populations de patients en se basant sur des états métaboliques connus; 2) les marqueurs Tag peuvent être utilisés pour découvrir de nouvelles corrélations génotype-phénotype. Présentement, il existe un besoin pour un outil de recherche qui englobe un grand nombre de gènes ADME et variantes et dont le contenu est applicable à ces deux modèles d'étude. Dans le cadre de cette thèse, nous avons développé un panel d’essais de génotypage de 3,000 marqueurs génétiques ADME qui peuvent satisfaire ce besoin. Dans le cadre de ce projet, les gènes et marqueurs associés avec la famille ADME ont été sélectionnés en collaboration avec plusieurs groupes du milieu universitaire et de l'industrie pharmaceutique. Pendant trois phases de développement de cet essai de génotypage, le taux de conversion pour 3,000 marqueurs a été amélioré de 83% à 97,4% grâce à l'incorporation de nouvelles stratégies ayant pour but de surmonter les zones d'interférence génomiques comprenant entre autres les régions homologues et les polymorphismes sous-jacent les régions d’intérêt. La précision du panel de génotypage a été validée par l’évaluation de plus de 200 échantillons pour lesquelles les génotypes sont connus pour lesquels nous avons obtenu une concordance > 98%. De plus, une comparaison croisée entre nos données provenant de cet essai et des données obtenues par différentes plateformes technologiques déjà disponibles sur le marché a révélé une concordance globale de > 99,5%. L'efficacité de notre stratégie de conception ont été démontrées par l'utilisation réussie de cet essai dans le cadre de plusieurs projets de recherche où plus de 1,000 échantillons ont été testés. Nous avons entre autre évalué avec succès 150 échantillons hépatiques qui ont été largement caractérisés pour plusieurs phénotypes. Dans ces échantillons, nous avons pu valider 13 gènes ADME avec cis-eQTL précédemment rapportés et de découvrir et de 13 autres gènes ADME avec cis eQTLs qui n'avaient pas été observés en utilisant des méthodes standard. Enfin, à l'appui de ce travail, un outil logiciel a été développé, Opitimus Primer, pour aider pour aider au développement du test. Le logiciel a également été utilisé pour aider à l'enrichissement de cibles génomiques pour d'expériences séquençage. Le contenu ainsi que la conception, l’optimisation et la validation de notre panel le distingue largement de l’ensemble des essais commerciaux couramment disponibles sur le marché qui comprennent soit des marqueurs fonctionnels pour seulement un petit nombre de gènes, ou alors n’offre pas une couverture adéquate pour les gènes connus d’ADME. Nous pouvons ainsi conclure que l’essai que nous avons développé est et continuera certainement d’être un outil d’une grande utilité pour les futures études et essais cliniques dans le domaine de la pharmacocinétique, qui bénéficieraient de l'évaluation d'une longue liste complète de gènes d’ADME.
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Pre-publication drafts are reproduced with permission and copyright © 2013 of the Journal of Orthopaedic Trauma [Mutch J, Rouleau DM, Laflamme GY, Hagemeister N. Accurate Measurement of Greater Tuberosity Displacement without Computed Tomography: Validation of a method on Plain Radiography to guide Surgical Treatment. J Orthop Trauma. 2013 Nov 21: Epub ahead of print.] and copyright © 2014 of the British Editorial Society of Bone and Joint Surgery [Mutch JAJ, Laflamme GY, Hagemeister N, Cikes A, Rouleau DM. A new morphologic classification for greater tuberosity fractures of the proximal humerus: validation and clinical Implications. Bone Joint J 2014;96-B:In press.]
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Background: Despite the focus on facial photoaging ratings, there are few classifications developed for forearm skin aging assessment.Objective: To develop and validate a clinical scale for the evaluation of forearm skin aging.Methods: Three clinical dermatology faculty members selected, discussed, and appraised the main signs of forearm photoaging. The validation of the resulting scale was performed by 5 assessors who were previously trained to classify 102 photographs of forearms with different degrees of aging. Retests were performed in 15 days.Results: There was significant correlation between the selected variables and the subjective global aging scale. The developed scale showed high internal consistency (Cronbach's alpha = 0.87) and high correlation with the global photoaging scale (rho = 0.92). Inter- and intraobserver final scores showed high agreement.Conclusion: A validated clinical photoaging scale for forearms with internal consistency, reliability, and validity was developed.