982 resultados para continuous emission monitoring
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Background:Amplitude-integrated electroencephalogram (aEEG) is increasingly used for neuromonitoring in preterms. We aimed to quantify the effects of gestational age (GA), postnatal age (PNA), and other perinatal factors on the development of aEEG early after birth in very preterm newborns with normal cerebral ultrasounds.Methods:Continuous aEEG was prospectively performed in 96 newborns (mean GA: 29.5 (range: 24.4-31.9) wk, birth weight 1,260 (580-2,120) g) during the first 96 h of life. aEEG tracings were qualitatively (maturity scores) and quantitatively (amplitudes) evaluated using preestablished criteria.Results:A significant increase in all aEEG measures was observed between day 1 and day 4 and for increasing GA (P < 0.001). The effect of PNA on aEEG development was 6.4- to 11.3-fold higher than that of GA. In multivariate regression, GA and PNA were associated with increased qualitative and quantitative aEEG measures, whereas small-for-GA status was independently associated with increased maximum aEEG amplitude (P = 0.003). Morphine administration negatively affected all aEEG measures (P < .05), and caffeine administration negatively affected qualitative aEEG measures (P = 0.02).Conclusion:During the first few days after birth, aEEG activity in very preterm infants significantly develops and is strongly subjected to the effect of PNA. Perinatal factors may alter the early aEEG tracing and interfere with its interpretation.
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AIM: In type 1 diabetic patients (T1DM), nocturnal hypoglycaemias (NH) are a serious complication of T1DM treatment; self-monitoring of blood glucose (SMBG) is recommended to detect them. However, the majority of NH remains undetected on an occasional SMBG done during the night. An alternative strategy is the Continuous glucose monitoring (CGMS), which retrospectively shows the glycaemic profile. The aims of this retrospective study were to evaluate the true incidence of NH in T1DM, the best SMBG time to predict NH, the relationship between morning hyperglycaemia and NH (Somogyi phenomenon) and the utility of CGMS to reduce NH. METHODS: Eighty-eight T1DM who underwent a CGMS exam were included. Indications for CGMS evaluation, hypoglycaemias and correlation with morning hyperglycaemias were recorded. The efficiency of CGMS to reduce the suspected NH was evaluated after 6-9 months. RESULTS: The prevalence of NH was 67% (32% of them unsuspected). A measured hypoglycaemia at bedtime (22-24 h) had a sensitivity of 37% to detect NH (OR=2.37, P=0.001), while a single measure < or =4 mmol/l at 3-hour had a sensitivity of 43% (OR=4.60, P<0.001). NH were not associated with morning hyperglycaemias but with morning hypoglycaemias (OR=3.95, P<0.001). After 6-9 months, suspicions of NH decreased from 60 to 14% (P<0.001). CONCLUSION: NH were highly prevalent and often undetected. SMBG at bedtime, which detected hypoglycaemia had sensitivity almost equal to that of 3-hour and should be preferred because it is easier to perform. Somogyi phenomenon was not observed. CGMS is useful to reduce the risk of NH in 75% of patients.
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INTRODUCTION: Continuous EEG (cEEG) is increasingly used to monitor brain function in neuro-ICU patients. However, its value in patients with coma after cardiac arrest (CA), particularly in the setting of therapeutic hypothermia (TH), is only beginning to be elucidated. The aim of this study was to examine whether cEEG performed during TH may predict outcome. METHODS: From April 2009 to April 2010, we prospectively studied 34 consecutive comatose patients treated with TH after CA who were monitored with cEEG, initiated during hypothermia and maintained after rewarming. EEG background reactivity to painful stimulation was tested. We analyzed the association between cEEG findings and neurologic outcome, assessed at 2 months with the Glasgow-Pittsburgh Cerebral Performance Categories (CPC). RESULTS: Continuous EEG recording was started 12 ± 6 hours after CA and lasted 30 ± 11 hours. Nonreactive cEEG background (12 of 15 (75%) among nonsurvivors versus none of 19 (0) survivors; P < 0.001) and prolonged discontinuous "burst-suppression" activity (11 of 15 (73%) versus none of 19; P < 0.001) were significantly associated with mortality. EEG seizures with absent background reactivity also differed significantly (seven of 15 (47%) versus none of 12 (0); P = 0.001). In patients with nonreactive background or seizures/epileptiform discharges on cEEG, no improvement was seen after TH. Nonreactive cEEG background during TH had a positive predictive value of 100% (95% confidence interval (CI), 74 to 100%) and a false-positive rate of 0 (95% CI, 0 to 18%) for mortality. All survivors had cEEG background reactivity, and the majority of them (14 (74%) of 19) had a favorable outcome (CPC 1 or 2). CONCLUSIONS: Continuous EEG monitoring showing a nonreactive or discontinuous background during TH is strongly associated with unfavorable outcome in patients with coma after CA. These data warrant larger studies to confirm the value of continuous EEG monitoring in predicting prognosis after CA and TH.
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Introduction: Continuous EEG (cEEG) is increasingly used to monitor brain function in neuro-ICU patients. However, its value in patients with coma after cardiac arrest (CA), particularly in the setting of therapeutic hypothermia (TH), is only beginning to be elucidated. The aim of this study was to examine whether cEEG performed during TH may predict outcome. Methods: From April 2009 to April 2010, we prospectively studied 34 consecutive comatose patients treated with TH after CA who were monitored with cEEG, initiated during hypothermia and maintained after rewarming. EEG background reactivity to painful stimulation was tested. We analyzed the association between cEEG findings and neurologic outcome, assessed at 2 months with the Glasgow-Pittsburgh Cerebral Performance Categories (CPC). Results: Continuous EEG recording was started 12 ± 6 hours after CA and lasted 30 ± 11 hours. Nonreactive cEEG background (12 of 15 (75%) among nonsurvivors versus none of 19 (0) survivors; P < 0.001) and prolonged discontinuous "burst-suppression" activity (11 of 15 (73%) versus none of 19; P < 0.001) were significantly associated with mortality. EEG seizures with absent background reactivity also differed significantly (seven of 15 (47%) versus none of 12 (0); P = 0.001). In patients with nonreactive background or seizures/epileptiform discharges on cEEG, no improvement was seen after TH. Nonreactive cEEG background during TH had a positive predictive value of 100% (95% confidence interval (CI), 74 to 100%) and a false-positive rate of 0 (95% CI, 0 to 18%) for mortality. All survivors had cEEG background reactivity, and the majority of them (14 (74%) of 19) had a favorable outcome (CPC 1 or 2). Conclusions: Continuous EEG monitoring showing a nonreactive or discontinuous background during TH is strongly associated with unfavorable outcome in patients with coma after CA. These data warrant larger studies to confirm the value of continuous EEG monitoring in predicting prognosis after CA and TH.
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OBJECTIVES: To determine the prevalence, predictors, and clinical significance of electrographic seizures (ESz) and other continuous electroencephalographic monitoring findings in critically ill patients with central nervous system infections. DESIGN: Retrospective cohort study. SETTING: Eighteen-bed neurocritical care unit. PATIENTS: We identified 42 consecutive patients with primary central nervous system infection (viral, 27 patients [64%]; bacterial, 8 patients [18%]; and fungal or parasitic, 7 patients [17%]) who underwent continuous electroencephalographic monitoring between January 1, 1996, and February 28, 2007. MAIN OUTCOME MEASURES: Presence of ESz or periodic epileptiform discharges (PEDs). RESULTS: Electrographic seizures were recorded in 14 patients (33%), and PEDs were recorded in 17 patients (40%). Twenty patients (48%) had either PEDs or ESz. Of the 14 patients with ESz, only 5 (36%) had a clinical correlate. Periodic epileptiform discharges (odds ratio=13.4; P=.001) and viral cause (odds ratio=13.0; P=.02) were independently associated with ESz. Both ESz (odds ratio=5.9; P=.02) and PEDs (odds ratio=6.1; P=.01) were independently associated with poor outcome at discharge (severe disability, vegetative state, or death). CONCLUSIONS: In patients with central nervous system infections undergoing continuous electroencephalographic monitoring, ESz and/or PEDs were frequent, occurring in 48% of our cohort. More than half of the ESz had no clinical correlate. Both ESz and PEDs were independently associated with poor outcome. Additional studies are needed to determine whether prevention or treatment of these electrographic findings improves outcome.
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Rapport de synthèse : Hypoglycémies nocturnes chez les patients diabétiques de type 1 : que pouvons-nous apprendre de la mesure de la glycémie en continu ? But : les hypoglycémies nocturnes sont une complication majeure du traitement des patients diabétiques de type 1; des autocontrôles de la glycémie capillaire sont donc recommandés pour les détecter. Cependant, la majorité des hypoglycémies nocturnes ne sont pas décelées par un autocontrôle glycémique durant la nuit. La mesure de la glycémie en continu (CGMS) est une alternative intéressante. Les buts de cette étude rétrospective étaient d'évaluer la véritable incidence des hypoglycémies nocturnes chez des patients diabétiques de type 1, la meilleure période pour effectuer un autocontrôle permettant de prédire une hypoglycémie nocturne, la relation entre les hyperglycémies matinales et les hypoglycémies nocturnes (phénomène de Somogyi) ainsi que l'utilité du CGMS pour réduire les hypoglycémies nocturnes. Méthode : quatre-vingt-huit patients diabétiques de type 1 qui avaient bénéficié d'un CGMS ont été inclus. Les indications au CGMS, les hypoglycémies nocturnes et diurnes ainsi que la corrélation entre les hypoglycémies nocturnes et les hyperglycémies matinales durant le CGMS ont été enregistrées. L'efficacité du CGMS pour réduire les hypoglycémies nocturnes a été évaluée six à neuf mois après. Résultats : la prévalence des hypoglycémies nocturnes était de 67% (32% non suspectées). La sensibilité d'une hypoglycémie à prédire une hypoglycémie nocturne était de 37% (OR = 2,37, P = 0,001) lorsqu'elle survient au coucher (22-24 h) et de 43% lorsqu'elle survient à 3 h (OR = 4,60, P < 0,001). Les hypoglycémies nocturnes n'étaient pas associées à des hyperglycémies matinales, mais à des hypoglycémies matinales (OR = 3.95, P < 0.001). Six à neuf mois après le CGMS, les suspicions cliniques d'hypoglycémies nocturnes ont diminué de 60% à 14% (P < 0.001). Abstract : Aim. - In type 1 diabetic patients (TIDM), nocturnal hypoglycaemias (Nlï) are a serious complication of T1DM treatment; self-monitoring of blood glucose (SMBG) is recommended to detect them. However, the majority of NH remains undetected on an occasional SMBG done during the night. An alternative strategy is the Continuous glucose monitoring (CGMS), which retrospectively shows the glycaemic profile. The aims of this retrospective study were to evaluate the true incidence of NH in TiDM, the bèst SMBG time to predict NH, the relationship between morning hyperglycaemia and N$ (Somogyi phenomenon) and the utility of CGMS to reduce NH. Methods. -Eighty-eight T1DM who underwent a CGMS exam were included. Indications for CGMS evaluarion, hypoglycaemias and correlation with morning hyperglycaemias were recorded. The efficiency of CGMS to reduce the suspected NH was evaluated after 6-9 months. Results. -The prevalence of NH was 67% (32% of them unsuspected). A measured hypoglycaemia at bedtime (22-24 h) had a sensitivity of 37% to detect NH (OR = 2.37, P = 0.001), while a single measure <_ 4 mmol/l at 3-hour had a sensitivity of 43% (OR = 4.60, P < 0.001). NH were not associated with morning hyperglycaemias but with morning hypoglycaemias (OR = 3.95, P < 0.001). After 6-9 months, suspicions of NH decreased from 60 to 14% (P < 0.001). Conclusion. - NH were highly prevalent and often undetected. SMBG at bedtime, which detected hypoglycaemia had sensitivity almost equal to that of 3-hour and should be preferred because it is easier to perform. Somogyi phenomenon was not observed. CGMS is useful to reduce the risk of NH in 75% of patients.
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The effect of continuous emission hypothesis on the two-pion Bose-Einstein correlation is discussed and compared with the corresponding results based on the usual freeze-out ansatz. Sizable differences in the correlation function are observed when comparing these two scenarios of the decoupling process. They could lead to entirely different interpretation of properties of the hot matter formed in high-energy heavy-ion collisions.
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The usual particle emission scenario used in hydrodynamics presupposes that particles instantaneously stop interacting (freeze-out) once they reach some three dimensional surface. Another formalism has been developed recently where particle emission occurs continuously during the whole expansion of thermalized matter. Here we compare both mechanisms in a simplified hydrodynamical framework and show that they lead to a drastically different interpretation of data.
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The effect of the continuous emission hypothesis on the two-pion Bose-Einstein correlation function is discussed and compared with the corresponding results based on the usual freeze-out. Sizable differences in the correlation function appear in these different descriptions of the decoupling process. This means that, when extracting properties of the hot matter formed in high-energy heavy-ion collisions from the data, completely different conclusions may be reached according to the description of the particle emission process adopted.
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Effects of lattice-QCD-inspired equations of state and continuous emission on some observables are discussed, by solving a 3D hydrodynamics. The particle multiplicity as well ν 2 are found to increase in the mid-rapidity. We also discuss the effects of the initial-condition fluctuations. © 2006 American Institute of Physics.
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Background: This pilot study aimed to verify if glycemic control can be achieved in type 2 diabetes patients after acute myocardial infarction (AMI), using insulin glargine (iGlar) associated with regular insulin (iReg), compared with the standard intensive care unit protocol, which uses continuous insulin intravenous delivery followed by NPH insulin and iReg (St. Care). Patients and Methods: Patients (n = 20) within 24 h of AMI were randomized to iGlar or St. Care. Therapy was guided exclusively by capillary blood glucose (CBG), but glucometric parameters were also analyzed by blinded continuous glucose monitoring system (CGMS). Results: Mean glycemia was 141 +/- 39 mg/dL for St. Care and 132 +/- 42 mg/dL for iGlar by CBG or 138 +/- 35 mg/dL for St. Care and 129 +/- 34 mg/dL for iGlar by CGMS. Percentage of time in range (80-180 mg/dL) by CGMS was 73 +/- 18% for iGlar and 77 +/- 11% for St. Care. No severe hypoglycemia (<= 40 mg/dL) was detected by CBG, but CGMS indicated 11 (St. Care) and seven (iGlar) excursions in four subjects from each group, mostly in sulfonylurea users (six of eight patients). Conclusions: This pilot study suggests that equivalent glycemic control without increase in severe hyperglycemia may be achieved using iGlar with background iReg. Data outputs were controlled by both CBG and CGMS measurements in a real-life setting to ensure reliability. Based on CGMS measurements, there were significant numbers of glycemic excursions outside of the target range. However, this was not detected by CBG. In addition, the data indicate that previous use of sulfonylurea may be a potential major risk factor for severe hypoglycemia irrespective of the type of insulin treatment.
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During this work has been developed an innovative methodology for continuous and in situ gas monitoring (24/24 h) of fumarolic and soil diffusive emissions applied to the geothermal and volcanic area of Pisciarelli near Agnano inside the Campi Flegrei caldera (CFc). In literature there are only scattered and in discrete data of the geochemical gas composition of fumarole at Campi Flegrei; it is only since the early ’80 that exist a systematic record of fumaroles with discrete sampling at Solfatara (Bocca Grande and Bocca Nuova fumaroles) and since 1999, even at the degassing areas of Pisciarelli. This type of sampling has resulted in a time series of geochemical analysis with discontinuous periods of time set (in average 2-3 measurements per month) completely inadequate for the purposes of Civil Defence in such high volcanic risk and densely populated areas. For this purpose, and to remedy this lack of data, during this study was introduced a new methodology of continuous and in situ sampling able to continuously detect data related and from its soil diffusive degassing. Due to its high sampling density (about one measurement per minute therefore producing 1440 data daily) and numerous species detected (CO2, Ar, 36Ar, CH4, He, H2S, N2, O2) allowing a good statistic record and the reconstruction of the gas composition evolution of the investigated area. This methodology is based on continuous sampling of fumaroles gases and soil degassing using an extraction line, which after undergoing a series of condensation processes of the water vapour content - better described hereinafter - is analyzed through using a quadrupole mass spectrometer
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Abstract Background and Aims: Data on the influence of calibration on accuracy of continuous glucose monitoring (CGM) are scarce. The aim of the present study was to investigate whether the time point of calibration has an influence on sensor accuracy and whether this effect differs according to glycemic level. Subjects and Methods: Two CGM sensors were inserted simultaneously in the abdomen on either side of 20 individuals with type 1 diabetes. One sensor was calibrated predominantly using preprandial glucose (calibration(PRE)). The other sensor was calibrated predominantly using postprandial glucose (calibration(POST)). At minimum three additional glucose values per day were obtained for analysis of accuracy. Sensor readings were divided into four categories according to the glycemic range of the reference values (low, ≤4 mmol/L; euglycemic, 4.1-7 mmol/L; hyperglycemic I, 7.1-14 mmol/L; and hyperglycemic II, >14 mmol/L). Results: The overall mean±SEM absolute relative difference (MARD) between capillary reference values and sensor readings was 18.3±0.8% for calibration(PRE) and 21.9±1.2% for calibration(POST) (P<0.001). MARD according to glycemic range was 47.4±6.5% (low), 17.4±1.3% (euglycemic), 15.0±0.8% (hyperglycemic I), and 17.7±1.9% (hyperglycemic II) for calibration(PRE) and 67.5±9.5% (low), 24.2±1.8% (euglycemic), 15.5±0.9% (hyperglycemic I), and 15.3±1.9% (hyperglycemic II) for calibration(POST). In the low and euglycemic ranges MARD was significantly lower in calibration(PRE) compared with calibration(POST) (P=0.007 and P<0.001, respectively). Conclusions: Sensor calibration predominantly based on preprandial glucose resulted in a significantly higher overall sensor accuracy compared with a predominantly postprandial calibration. The difference was most pronounced in the hypo- and euglycemic reference range, whereas both calibration patterns were comparable in the hyperglycemic range.