970 resultados para Sleep Quality
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BACKGROUND Several studies in recent years have evaluated Health Related Quality of Life (HRQoL) of patients with primary hyperparathyroidism (PHPT). No disease specific questionnaires are available to assess the impact of the disease. The aim of this research is to describe the development of a new disease specific Quality of Life (QoL) questionnaire for use specifically with PHPT patients. METHODS A conceptual model was developed describing the impact of the disease and its symptoms on QoL domains. A literature review was conducted to identify the most relevant domains. A focus group with experts was used to validate the domains; 24 patients were also interviewed to complement the information from the patient's perspective. A content analysis of the interviews was performed to identify items related with the impact of the disease, leading to PHPQoL-V.1 which was presented to a sample of 67 patients. Reliability was assessed by Cronbach's coefficient alpha and item-total score correlations. Validity was assessed by a factor analysis performed to determine the number of domains. Rasch analysis was carried out in order to refine the questionnaire items. RESULTS 259 items were extracted from the interviews that were subsequently reduced to 34 items. Cronbach's coefficient alpha was 0.92. The factor analysis extracted two domains (physical and emotional). After Rasch analysis the questionnaire PHPQoL-V.2 kept 16 items (9 physical and 7 emotional). The questionnaire was developed in a Spanish population and the final version was translated to English through translation and back-translation. CONCLUSION The first disease specific HRQoL questionnaire for PHPT patients (PHPQoL-16) has been developed. Validation studies designed to assess measurement properties of this tool are currently underway.
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Introduction: Obstructive sleep apnea (OSA) is associated with an increased risk of cardiovascular diseases. Endothelial dysfunction is believed to be one of the pathophysiological mechanism underlying this association. Our aim was to compare endothelial dependent coronary vasoreactivity in obstructive sleep apnea (OSA) patients and controls by quantifying myocardial blood flow (MBF) response to cold pressure testing (CPT) with 82Rb cardiac PET/CT. Methods: Twenty-four OSA patients (2W/22M, mean age 58 yo, mean BMI 28.6 kg/m2) with an apnea-hypopnea index (AHI) >30/h and 9 healthy volunteers (AHI <10/h) underwent a full night sleep recording (PSG) and a dynamic 82 Rb cardiac PET/CT scan at rest, during CPT and adenosine stress. In OSA patients the same measurements (PSG and PET/CT) were respeated 6 weeks after initiating continuous positive airway pressure (autoCPAP) treatment. To reflect differences in baseline cardiac work, values were normalized according to ratepressure product (RPP). Results: At baseline, untreated OSA patients had a mean AHI of 48.8/h and showed a lower MBF response to CPT than controls (1.1 ± 0.2 mL/min/g vs. 1.3 ± 0.4 mL/min/g, P = 0.048). When treated with CPAP, CPT-MBF was not different between controls and well-treated OSA patients (1.2 ± 0.3 mL/min/g vs 1.3 ± 0.4 mL/min/g, P = 0.68), but it was significantly lower for insufficiently treated patients (n = 10) with a residual AHI >10/h (0.9 ± 0.2 mL/min/g vs 1.3 ± 0.4 mL/min/g, P = 0.03). There was also a trend toward a difference in CPT-MBF between insufficiently and well-treated OSA patients (1.2 ± 0.3 mL/min/g vs 0.9 ± 0.2 mL/min/g, P = 0.15). Conclusion: Untreated OSA patients have an impaired coronary endothelial function as measured by MBF response to CPT compared to control subjects. This difference disappears after 6 weeks of autoCPAP therapy but only in OSA patients showing a good response to CPAP (AHI <10/h). Further studies are needed to determine by which mechanism OSA and CPAP treatment influence coronary vasoreactivity.
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Aims: To evaluate the impact on glycemic control and quality of life of a bolus calculator. Methods: Multicentre randomized prospective crosssectional study. Patients were randomized to control phase (3 months; calculation of prandial insulin according to insulinto-carbohydrate ratio and insulin sensitivity factor using a single strip meter) or intervention phase (3 months; calculation of prandial insulin with a bolus advisor), with a washout period (3 months). Patients wore a continuous glucosensor (7 days) and answered a quality of life questionnaire at the beginning and at the end of each phase. A questionnaire of satisfaction was obtained at the end of both phases. Inclusion criteria: Adults; T1DM> 1 year, HbA1c > 7.5%, basal-bolus therapy with insulin analogs, experience with carbohydrate Results: Data from the first 32 subjects with at least 1 ended phase (27 females, age 38 – 11 years, diabetes duration 16.8 – 7.5 years). Basal characteristics were comparable independently of the starting phase. No differences were found between phases in terms of mean blood glucose, standard deviation (from meter neither from sensor) and satisfaction. Conclusions: The use of a bolus calculator improves glycemic control and quality of life of T1DM subjects.
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BACKGROUND The rate of avoidable caesarean sections (CS) could be reduced through multifaceted strategies focusing on the involvement of health professionals and compliance with clinical practice guidelines (CPGs). Quality improvements for CS (QICS) programmes (QICS) based on this approach, have been implemented in Canada and Spain. OBJECTIVES Their objectives are as follows: 1) Toto identify clusters in each setting with similar results in terms of cost-consequences, 2) Toto investigate whether demographic, clinical or context characteristics can distinguish these clusters, and 3) Toto explore the implementation of QICS in the 2 regions, in order to identify factors that have been facilitators in changing practices and reducing the use of obstetric intervention, as well as the challenges faced by hospitals in implementing the recommendations. METHODS Descriptive study with a quantitative and qualitative approach. 1) Cluster analysis at patient level with data from 16 hospitals in Quebec (Canada) (n = 105,348) and 15 hospitals in Andalusia (Spain) (n = 64,760). The outcome measures are CS and costs. For the cost, we will consider the intervention, delivery and complications in mother and baby, from the hospital perspective. Cluster analysis will be used to identify participants with similar patterns of CS and costs based, and t tests will be used to evaluate if the clusters differed in terms of characteristics: Hospital level (academic status of hospital, level of care, supply and demand factors), patient level (mother age, parity, gestational age, previous CS, previous pathology, presentation of the baby, baby birth weight). 2) Analysis of in-depth interviews with obstetricians and midwives in hospitals where the QICS were implemented, to explore the differences in delivery-related practices, and the importance of the different constructs for positive or negative adherence to CPGs. Dimensions: political/management level, hospital level, health professionals, mothers and their birth partner. DISCUSSION This work sets out a new approach for programme evaluation, using different techniques to make it possible to take into account the specific context where the programmes were implemented.
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Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.
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One third of the population is affected by a sleep disorder with a major social, medical, and economic impact. Although very little is known about the genetics of normal sleep, familial and twin studies indicate an important influence of genetic factors. Most sleep disorders run in families and in several of them the contribution of genetic factors is increasingly recognised. With recent advances in the genetics of narcolepsy and the role of the hypocretin/orexin system, the possibility that other gene defects may contribute to the pathophysiology of major sleep disorders is worth indepth investigation.
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BACKGROUND Health-related quality of life (HRQoL) is gaining importance as a valuable outcome measure in oral cancer area. The aim of this study was to assess the general and oral HRQoL of oral and oropharyngeal cancer patients 6 or more months after treatment and compare them with a population free from this disease. METHODS A cross-sectional study was carried out with patients treated for oral cancer at least 6 months post-treatment and a gender and age group matched control group. HRQoL was measured with the 12-Item Short Form Health Survey (SF-12); oral HRQoL (OHRQoL) was evaluated using the Oral Health Impact Profile (OHIP-14) and the Oral Impacts on Daily Performances (OIDP). Multivariable regression models assessed the association between the outcomes (SF-12, OHIP-14 and OIDP) and the exposure (patients versus controls), adjusting for sex, age, social class, functional tooth units and presence of illness. RESULTS For patients (n = 142) and controls (n = 142), 64.1% were males. The mean age was 65.2 (standard deviation (sd): 12.9) years in patients and 67.5 (sd: 13.7) years in controls. Patients had worse SF-12 Physical Component Summary scores than controls even in fully the adjusted model [β-coefficient = -0.11 (95% CI: -5.12-(-0.16)]. The differences in SF-12 Mental Component Summary were not statistically significant. Regarding OHRQoL patients had 11.63 (95% CI: 6.77-20.01) higher odds for the OHIP-14 and 21.26 (95% CI: 11.54-39.13) higher odds for OIDP of being in a worse category of OHRQoL compared to controls in the fully adjusted model. CONCLUSION At least 6 months after treatment, oral cancer patients had worse OHRQoL, worse physical HRQoL and similar psychological HRQoL than the general population.
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A low arousal threshold is believed to predispose to breathing instability during sleep. The present authors hypothesised that trazodone, a nonmyorelaxant sleep-promoting agent, would increase the effort-related arousal threshold in obstructive sleep apnoea (OSA) patients. In total, nine OSA patients, mean+/-sd age 49+/-9 yrs, apnoea/hypopnoea index 52+/-32 events.h(-1), were studied on 2 nights, one with trazodone at 100 mg and one with a placebo, in a double blind randomised fashion. While receiving continuous positive airway pressure (CPAP), repeated arousals were induced: 1) by increasing inspired CO(2) and 2) by stepwise decreases in CPAP level. Respiratory effort was measured with an oesophageal balloon. End-tidal CO(2 )tension (P(ET,CO(2))) was monitored with a nasal catheter. During trazodone nights, compared with placebo nights, the arousals occurred at a higher P(ET,CO(2)) level (mean+/-sd 7.30+/-0.57 versus 6.62+/-0.64 kPa (54.9+/-4.3 versus 49.8+/-4.8 mmHg), respectively). When arousals were triggered by increasing inspired CO(2) level, the maximal oesophageal pressure swing was greater (19.4+/-4.0 versus 13.1+/-4.9 cm H(2)O) and the oesophageal pressure nadir before the arousals was lower (-5.1+/-4.7 versus -0.38+/-4.2 cm H(2)O) with trazodone. When arousals were induced by stepwise CPAP drops, the maximal oesophageal pressure swings before the arousals did not differ. Trazodone at 100 mg increased the effort-related arousal threshold in response to hypercapnia in obstructive sleep apnoea patients and allowed them to tolerate higher CO(2) levels.
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Monitor a distribution network implies working with a huge amount of data coining from the different elements that interact in the network. This paper presents a visualization tool that simplifies the task of searching the database for useful information applicable to fault management or preventive maintenance of the network