Les analyses en clusters ont identifié un certain nombre de phénotypes cliniques chez les patients atteints de BPCO mais leurs résultats sont difficiles à utiliser en pratique clinique quotidienne. Notre objectif était de développer un algorithme utilisable en pratique clinique pour classer individuellement les patients dans les phénotypes. Les données cliniques de 2409 patients atteints de BPCO recrutés dans 3 cohortes françaises et belges ont été analysées à l’aide d’une analyse en cluster pour données mixtes, et les phénotypes identifiés ont été validés en utilisant la mortalité toutes causes confondues à 3 ans. Un arbre décisionnel simple permettant de classer les patients dans les phénotypes a été construit par une analyse de type classification and regression trees (CART). Cet arbre décisionnel a été testé dans une cohorte indépendante de 3651 patients atteints de BPCO issus de l’initiative 3CIA, un regroupement international de cohortes. L’analyse en cluster a permis l’identification de 5 phénotypes qui ont été validés du fait de différences dans la survie à 3 ans et l’âge de décès. Un arbre décisionnel comprenant les comorbidités cardiovasculaires et/ou le diabète, le VEMS, l’échelle mMRC, l’indice de masse corporelle et l’âge (mais pas les exacerbations) a permis la classification d’environ 80 % des patients dans le phénotype approprié. Cet arbre décisionnel a été appliqué sur les patients issus de la cohorte 3CIA et a permis l’identification de patients ayant des caractéristiques cliniques et un pronostic différent, permettant une validation externe. Un algorithme simple, fondé sur des données facilement disponibles en pratique clinique quotidienne permet l’identification de phénotypes de BPCO. Cet algorithme pourrait servir de base à une nouvelle classification de la BPCO pour inclure les patients dans des essais thérapeutiques ou pour analyser des cohortes observationnelles disposant de biomarqueurs (imagerie, marqueurs biologiques). Ces analyses ont été financées à l’aide d’une subvention inconditionnelle de Boehringer Ingelheim France.

RATIONALE: Panic disorder (PD) has been shown to be associated with worse asthma outcomes in individuals with asthma, but the psychophysiological mechanisms underlying this association remain unclear.Some theories suggest that asthmatics with PD have worse underlying asthma severity and some argue that they simply report more symptoms based on their tendency to catastrophize bodily sensations.METHODS: A total of 39 patients (19 with and 20 without PD) with physician-diagnosed asthma underwent standard metacholine challenge testing (MCT).Demographic and medical/asthma history information was collected at baseline.Pre and post MCT patients completed the Panic symptom scale (PSS), the Modified Borg Scale (MBS), and the Subjective distress visual analogue scale (SD-VAS).Heart rate (HR), systolic, and diastolic blood pressure (SBP/DBP) were recorded pre, during, and post MCT.RESULTS: There were no differences in PC20 values between asthmatics with and without PD (F=0.21,p=0.652).PD patients had a higher number of panic symptoms (from the PSS) at post-test compared to those without PD ([M (SD)] PD pre = 2.21 (2.42), PD post = 5.00 (3.32); non-PD pre = 0.75 (1.07), non-PD post = 2.25 (1.89): F=5.05, p=0.031).There were no differences in MBS (F=0.70,p=0.407),SD-VAS anxiety (F=0.36,p=0.554),SD-VAS worry (F=0.84,p=0.366),HR (F=0.06,p=0.805),SBP (F=0.49,p=0.487), or DBP (F=0.01,p=0.942) between PD and non-PD patients.CONCLUSIONS: Results suggest that having PD is associated with increased subjective responses during MCT, with no impact on objective measures of asthma.Future research should focus on the potential impact of these increased panic attack-like symptoms on long-term asthma care and if intervening on them influences outcomes such as emergency room visits.

We studied the validity of a recently introduced, handheld, electronic loading device in providing automatically processed information on external inspiratory work, power and breathing pattern during loaded breathing tasks in patients with COPD. Thirty-five patients with moderate to severe COPD performed an endurance breathing task against a fixed resistive inspiratory load that corresponded to 55 ± 13% of their maximal inspiratory pressure. Flow and pressure signals during this task were sampled and processed at 500 Hz by the handheld loading device and at 100 Hz with an external, laboratory system that provided the "gold standard" reference data. Intra Class Correlations between methods were 0.97 for average mean inspiratory power, 0.98 for average mean pressure, 0.98 for average duty cycle, and 0.99 for total work (all p < 0.0001). We conclude that the handheld device provides automatically processed and valid estimates of physical units of energy during loaded breathing tasks. This enables health care providers to quantify the load on inspiratory muscles during these tests in daily clinical practice.

Background: This study explores spirometry quality and reproducibility in the Understanding Potential Long-term Impacts on Function with Tiotropium (UPLIFT (R)) trial.Methods: Four-year, randomized, double-blind, placebo-controlled, multicenter trial in 5993 patients with chronic obstructive pulmonary disease. Within-test variability of pre- and post-bronchodilator forced expiratory volume in 1 s (FEV1) was compared across study visits. Between-test variability of best pre- or post-FEV1 values between two visits 6 months apart was compared at the start, middle and end of the trial.Results: Three or more acceptable maneuvers were obtained in 93% of visits. Within-test variability of pre- and post-FEV1 (mean standard deviation: 0.092 and 0.098 L) decreased during the trial. Between-test variability also decreased: pre-FEV1 (visit 3-5 = 0.141 +/- 0.138 L; visit 9-11 = 0.129 +/- 0.121 L; visit 17-19 = 0.121 +/- 0.122 L); post-FEV1 (0.139 +/- 0.140, 0.126 +/- 0.123, 0.121 +/- 0.122 L, respectively), and was dependent on age, sex, smoking status and disease stage, but not on bronchodilator response or study treatment.Conclusion: Spirometry quality in UPLIFT (R) was good and improved during the trial. Between-test variability across patient subgroups suggests that relevant cut-offs for individual disease monitoring are difficult to establish. Trial registration number: NCT00144339. (C) 2013 Elsevier Ltd. All rights reserved.