Predicting the potential for lightning activity in mediterranean storms based on the WRF model dynamic and microphysical fields

A new parameter is introduced: the lightning potential index (LPI), which is a measure of the potential for charge generation and separation that leads to lightning flashes in convective thunderstorms. The LPI is calculated within the charge separation region of clouds between 0 C and 20 C, where the noninductive mechanism involving collisions of ice and graupel particles in the presence of supercooled water is most effective. As shown in several case studies using the Weather Research and Forecasting (WRF) model with explicit microphysics, the LPI is highly correlated with observed lightning. It is suggested that the LPI may be a useful parameter for predicting lightning as well as a tool for improving weather forecasting of convective storms and heavy rainfall.

Enhanced radar precipitation estimates using a combined clutter and beam blockage correction technique

Weather radar observations are currently the most reliable method for remote sensing of precipitation. However, a number of factors affect the quality of radar observations and may limit seriously automated quantitative applications of radar precipitation estimates such as those required in Numerical Weather Prediction (NWP) data assimilation or in hydrological models. In this paper, a technique to correct two different problems typically present in radar data is presented and evaluated. The aspects dealt with are non-precipitating echoes - caused either by permanent ground clutter or by anomalous propagation of the radar beam (anaprop echoes) - and also topographical beam blockage. The correction technique is based in the computation of realistic beam propagation trajectories based upon recent radiosonde observations instead of assuming standard radio propagation conditions. The correction consists of three different steps: 1) calculation of a Dynamic Elevation Map which provides the minimum clutter-free antenna elevation for each pixel within the radar coverage; 2) correction for residual anaprop, checking the vertical reflectivity gradients within the radar volume; and 3) topographical beam blockage estimation and correction using a geometric optics approach. The technique is evaluated with four case studies in the region of the Po Valley (N Italy) using a C-band Doppler radar and a network of raingauges providing hourly precipitation measurements. The case studies cover different seasons, different radio propagation conditions and also stratiform and convective precipitation type events. After applying the proposed correction, a comparison of the radar precipitation estimates with raingauges indicates a general reduction in both the root mean squared error and the fractional error variance indicating the efficiency and robustness of the procedure. Moreover, the technique presented is not computationally expensive so it seems well suited to be implemented in an operational environment.

Phytochrome interacting factors 4 and 5 redundantly limit seedling de-etiolation in continuous far-red light.

Phytochromes are red/far-red photosensors that regulate numerous developmental programs in plants. Among them, phytochrome A (phyA) is essential to enable seedling de-etiolation under continuous far-red (FR) light, a condition that mimics the environment under a dense canopy. The ecological relevance of this response is demonstrated by the high mortality rate of phyA mutant plants that germinate in deep vegetational shade. phyA signaling involves direct interaction of the photoreceptor with phytochrome-interacting factors PIF1 and PIF3, members of the bHLH transcription factor family. Here we investigated the involvement of PIF4 and PIF5 in phyA signaling, and found that they redundantly control de-etiolation in FR light. The pif4 pif5 double mutant is hypersensitive to low fluence rates of FR light. This phenotype is dependent on FR light perception by phyA, but does not rely on alterations in the phyA level. Our microarray analysis shows that PIF4 and PIF5 are part of an inhibitory mechanism that represses the expression of some light-responsive genes in the dark, and that they are also needed for full expression of several growth-related genes in the light. Unlike PIF1 and PIF3, PIF4 and PIF5 are not degraded in response to FR light, indicating that they are light-regulated by a different mechanism. Our genetic analysis suggests that this is achieved through sequestration of these PIFs by the closely related bHLH transcription factor HFR1 (long hypocotyl in FR light).

Three-dimensional ordered-subset expectation maximization iterative protocol for evaluation of left ventricular volumes and function by quantitative gated SPECT: a dynamic phantom study.

The purposes of this study were to characterize the performance of a 3-dimensional (3D) ordered-subset expectation maximization (OSEM) algorithm in the quantification of left ventricular (LV) function with (99m)Tc-labeled agent gated SPECT (G-SPECT), the QGS program, and a beating-heart phantom and to optimize the reconstruction parameters for clinical applications. METHODS: A G-SPECT image of a dynamic heart phantom simulating the beating left ventricle was acquired. The exact volumes of the phantom were known and were as follows: end-diastolic volume (EDV) of 112 mL, end-systolic volume (ESV) of 37 mL, and stroke volume (SV) of 75 mL; these volumes produced an LV ejection fraction (LVEF) of 67%. Tomographic reconstructions were obtained after 10-20 iterations (I) with 4, 8, and 16 subsets (S) at full width at half maximum (FWHM) gaussian postprocessing filter cutoff values of 8-15 mm. The QGS program was used for quantitative measurements. RESULTS: Measured values ranged from 72 to 92 mL for EDV, from 18 to 32 mL for ESV, and from 54 to 63 mL for SV, and the calculated LVEF ranged from 65% to 76%. Overall, the combination of 10 I, 8 S, and a cutoff filter value of 10 mm produced the most accurate results. The plot of the measures with respect to the expectation maximization-equivalent iterations (I x S product) revealed a bell-shaped curve for the LV volumes and a reverse distribution for the LVEF, with the best results in the intermediate range. In particular, FWHM cutoff values exceeding 10 mm affected the estimation of the LV volumes. CONCLUSION: The QGS program is able to correctly calculate the LVEF when used in association with an optimized 3D OSEM algorithm (8 S, 10 I, and FWHM of 10 mm) but underestimates the LV volumes. However, various combinations of technical parameters, including a limited range of I and S (80-160 expectation maximization-equivalent iterations) and low cutoff values (< or =10 mm) for the gaussian postprocessing filter, produced results with similar accuracies and without clinically relevant differences in the LV volumes and the estimated LVEF.

PPARγ Agonist-Induced Fluid Retention Depends on αENaC Expression in Connecting Tubules.

BACKGROUND/AIMS: Thiazolidinediones (TZDs, like rosiglitazone (RGZ)) are peroxisome proliferator-activated receptor γ (PPARγ) agonists used to treat type 2 diabetes. Clinical limitations include TZD-induced fluid retention and body weight (BW) increase, which are inhibited by amiloride, an epithelial-sodium channel (ENaC) blocker. RGZ-induced fluid retention is maintained in mice with αENaC knockdown in the collecting duct (CD). Since ENaC in the connecting tubule (CNT) rather than in CD appears to be critical for normal NaCl retention, we aimed to further explore the role of ENaC in CNT in RGZ-induced fluid retention. METHODS: Mice with conditional inactivation of αENaC in both CNT and CD were used (αENaC lox/lox AQP2-Cre; 'αENaC-CNT/CD-KO') and compared with littermate controls (αENaC lox/lox mice; 'WT'). BW was monitored and total body water (TBW) and extracellular fluid volume (ECF) were determined by bioelectrical impedance spectroscopy (BIS) before and after RGZ (320 mg/kg diet for 10 days). RESULTS: On regular NaCl diet, αENaC-CNT/CD-KO had normal BW, TBW, ECF, hematocrit, and plasma Na(+), K(+), and creatinine, associated with an increase in plasma aldosterone compared with WT. Challenging αENaC-CNT/CD-KO with a low NaCl diet unmasked impaired NaCl and K homeostasis, consistent with effective knockdown of αENaC. In WT, RGZ increased BW (+6.1%), TBW (+8.4%) and ECF (+10%), consistent with fluid retention. These changes were significantly attenuated in αENaC-CNT/CD-KO (+3.4, 1.3, and 4.3%). CONCLUSION: Together with the previous studies, the current results are consistent with a role of αENaC in CNT in RGZ-induced fluid retention, which dovetails with the physiological relevance of ENaC in this segment. © 2014 S. Karger AG, Basel.

Creatine and guanidinoacetate transport at blood-brain and blood-cerebrospinal fluid barriers.

While it was thought that most of cerebral creatine is of peripheral origin, AGAT and GAMT are well expressed in CNS where brain cells synthesize creatine. While the creatine transporter SLC6A8 is expressed by microcapillary endothelial cells (MCEC) at blood-brain barrier (BBB), it is absent from their surrounding astrocytes. This raised the concept that BBB has a limited permeability for peripheral creatine, and that the brain supplies a part of its creatine by endogenous synthesis. This review brings together the latest data on creatine and guanidinoacetate transport through BBB and blood-CSF barrier (BCSFB) with the clinical evidence of AGAT-, GAMT- and SLC6A8-deficient patients, in order to delineate a clearer view on the roles of BBB and BCSFB in the transport of creatine and guanidinoacetate between periphery and CNS, and on brain synthesis and transport of creatine. It shows that in physiological conditions, creatine is taken up by CNS from periphery through SLC6A8 at BBB, but in limited amounts, and that CNS also needs its own creatine synthesis. No uptake of guanidinoacetate from periphery occurs at BBB except under GAMT deficiency, but a net exit of guanidinoacetate seems to occur from CSF to blood at BCSFB, predominantly through the taurine transporter TauT.

Time-lapse and probabilistic inversion strategies for plane-wave electromagnetic data.

L'utilisation efficace des systèmes géothermaux, la séquestration du CO2 pour limiter le changement climatique et la prévention de l'intrusion d'eau salée dans les aquifères costaux ne sont que quelques exemples qui démontrent notre besoin en technologies nouvelles pour suivre l'évolution des processus souterrains à partir de la surface. Un défi majeur est d'assurer la caractérisation et l'optimisation des performances de ces technologies à différentes échelles spatiales et temporelles. Les méthodes électromagnétiques (EM) d'ondes planes sont sensibles à la conductivité électrique du sous-sol et, par conséquent, à la conductivité électrique des fluides saturant la roche, à la présence de fractures connectées, à la température et aux matériaux géologiques. Ces méthodes sont régies par des équations valides sur de larges gammes de fréquences, permettant détudier de manières analogues des processus allant de quelques mètres sous la surface jusqu'à plusieurs kilomètres de profondeur. Néanmoins, ces méthodes sont soumises à une perte de résolution avec la profondeur à cause des propriétés diffusives du champ électromagnétique. Pour cette raison, l'estimation des modèles du sous-sol par ces méthodes doit prendre en compte des informations a priori afin de contraindre les modèles autant que possible et de permettre la quantification des incertitudes de ces modèles de façon appropriée. Dans la présente thèse, je développe des approches permettant la caractérisation statique et dynamique du sous-sol à l'aide d'ondes EM planes. Dans une première partie, je présente une approche déterministe permettant de réaliser des inversions répétées dans le temps (time-lapse) de données d'ondes EM planes en deux dimensions. Cette stratégie est basée sur l'incorporation dans l'algorithme d'informations a priori en fonction des changements du modèle de conductivité électrique attendus. Ceci est réalisé en intégrant une régularisation stochastique et des contraintes flexibles par rapport à la gamme des changements attendus en utilisant les multiplicateurs de Lagrange. J'utilise des normes différentes de la norme l2 pour contraindre la structure du modèle et obtenir des transitions abruptes entre les régions du model qui subissent des changements dans le temps et celles qui n'en subissent pas. Aussi, j'incorpore une stratégie afin d'éliminer les erreurs systématiques de données time-lapse. Ce travail a mis en évidence l'amélioration de la caractérisation des changements temporels par rapport aux approches classiques qui réalisent des inversions indépendantes à chaque pas de temps et comparent les modèles. Dans la seconde partie de cette thèse, j'adopte un formalisme bayésien et je teste la possibilité de quantifier les incertitudes sur les paramètres du modèle dans l'inversion d'ondes EM planes. Pour ce faire, je présente une stratégie d'inversion probabiliste basée sur des pixels à deux dimensions pour des inversions de données d'ondes EM planes et de tomographies de résistivité électrique (ERT) séparées et jointes. Je compare les incertitudes des paramètres du modèle en considérant différents types d'information a priori sur la structure du modèle et différentes fonctions de vraisemblance pour décrire les erreurs sur les données. Les résultats indiquent que la régularisation du modèle est nécessaire lorsqu'on a à faire à un large nombre de paramètres car cela permet d'accélérer la convergence des chaînes et d'obtenir des modèles plus réalistes. Cependent, ces contraintes mènent à des incertitudes d'estimations plus faibles, ce qui implique des distributions a posteriori qui ne contiennent pas le vrai modèledans les régions ou` la méthode présente une sensibilité limitée. Cette situation peut être améliorée en combinant des méthodes d'ondes EM planes avec d'autres méthodes complémentaires telles que l'ERT. De plus, je montre que le poids de régularisation des paramètres et l'écart-type des erreurs sur les données peuvent être retrouvés par une inversion probabiliste. Finalement, j'évalue la possibilité de caractériser une distribution tridimensionnelle d'un panache de traceur salin injecté dans le sous-sol en réalisant une inversion probabiliste time-lapse tridimensionnelle d'ondes EM planes. Etant donné que les inversions probabilistes sont très coûteuses en temps de calcul lorsque l'espace des paramètres présente une grande dimension, je propose une stratégie de réduction du modèle ou` les coefficients de décomposition des moments de Legendre du panache de traceur injecté ainsi que sa position sont estimés. Pour ce faire, un modèle de résistivité de base est nécessaire. Il peut être obtenu avant l'expérience time-lapse. Un test synthétique montre que la méthodologie marche bien quand le modèle de résistivité de base est caractérisé correctement. Cette méthodologie est aussi appliquée à un test de trac¸age par injection d'une solution saline et d'acides réalisé dans un système géothermal en Australie, puis comparée à une inversion time-lapse tridimensionnelle réalisée selon une approche déterministe. L'inversion probabiliste permet de mieux contraindre le panache du traceur salin gr^ace à la grande quantité d'informations a priori incluse dans l'algorithme. Néanmoins, les changements de conductivités nécessaires pour expliquer les changements observés dans les données sont plus grands que ce qu'expliquent notre connaissance actuelle des phénomenès physiques. Ce problème peut être lié à la qualité limitée du modèle de résistivité de base utilisé, indiquant ainsi que des efforts plus grands devront être fournis dans le futur pour obtenir des modèles de base de bonne qualité avant de réaliser des expériences dynamiques. Les études décrites dans cette thèse montrent que les méthodes d'ondes EM planes sont très utiles pour caractériser et suivre les variations temporelles du sous-sol sur de larges échelles. Les présentes approches améliorent l'évaluation des modèles obtenus, autant en termes d'incorporation d'informations a priori, qu'en termes de quantification d'incertitudes a posteriori. De plus, les stratégies développées peuvent être appliquées à d'autres méthodes géophysiques, et offrent une grande flexibilité pour l'incorporation d'informations additionnelles lorsqu'elles sont disponibles. -- The efficient use of geothermal systems, the sequestration of CO2 to mitigate climate change, and the prevention of seawater intrusion in coastal aquifers are only some examples that demonstrate the need for novel technologies to monitor subsurface processes from the surface. A main challenge is to assure optimal performance of such technologies at different temporal and spatial scales. Plane-wave electromagnetic (EM) methods are sensitive to subsurface electrical conductivity and consequently to fluid conductivity, fracture connectivity, temperature, and rock mineralogy. These methods have governing equations that are the same over a large range of frequencies, thus allowing to study in an analogous manner processes on scales ranging from few meters close to the surface down to several hundreds of kilometers depth. Unfortunately, they suffer from a significant resolution loss with depth due to the diffusive nature of the electromagnetic fields. Therefore, estimations of subsurface models that use these methods should incorporate a priori information to better constrain the models, and provide appropriate measures of model uncertainty. During my thesis, I have developed approaches to improve the static and dynamic characterization of the subsurface with plane-wave EM methods. In the first part of this thesis, I present a two-dimensional deterministic approach to perform time-lapse inversion of plane-wave EM data. The strategy is based on the incorporation of prior information into the inversion algorithm regarding the expected temporal changes in electrical conductivity. This is done by incorporating a flexible stochastic regularization and constraints regarding the expected ranges of the changes by using Lagrange multipliers. I use non-l2 norms to penalize the model update in order to obtain sharp transitions between regions that experience temporal changes and regions that do not. I also incorporate a time-lapse differencing strategy to remove systematic errors in the time-lapse inversion. This work presents improvements in the characterization of temporal changes with respect to the classical approach of performing separate inversions and computing differences between the models. In the second part of this thesis, I adopt a Bayesian framework and use Markov chain Monte Carlo (MCMC) simulations to quantify model parameter uncertainty in plane-wave EM inversion. For this purpose, I present a two-dimensional pixel-based probabilistic inversion strategy for separate and joint inversions of plane-wave EM and electrical resistivity tomography (ERT) data. I compare the uncertainties of the model parameters when considering different types of prior information on the model structure and different likelihood functions to describe the data errors. The results indicate that model regularization is necessary when dealing with a large number of model parameters because it helps to accelerate the convergence of the chains and leads to more realistic models. These constraints also lead to smaller uncertainty estimates, which imply posterior distributions that do not include the true underlying model in regions where the method has limited sensitivity. This situation can be improved by combining planewave EM methods with complimentary geophysical methods such as ERT. In addition, I show that an appropriate regularization weight and the standard deviation of the data errors can be retrieved by the MCMC inversion. Finally, I evaluate the possibility of characterizing the three-dimensional distribution of an injected water plume by performing three-dimensional time-lapse MCMC inversion of planewave EM data. Since MCMC inversion involves a significant computational burden in high parameter dimensions, I propose a model reduction strategy where the coefficients of a Legendre moment decomposition of the injected water plume and its location are estimated. For this purpose, a base resistivity model is needed which is obtained prior to the time-lapse experiment. A synthetic test shows that the methodology works well when the base resistivity model is correctly characterized. The methodology is also applied to an injection experiment performed in a geothermal system in Australia, and compared to a three-dimensional time-lapse inversion performed within a deterministic framework. The MCMC inversion better constrains the water plumes due to the larger amount of prior information that is included in the algorithm. The conductivity changes needed to explain the time-lapse data are much larger than what is physically possible based on present day understandings. This issue may be related to the base resistivity model used, therefore indicating that more efforts should be given to obtain high-quality base models prior to dynamic experiments. The studies described herein give clear evidence that plane-wave EM methods are useful to characterize and monitor the subsurface at a wide range of scales. The presented approaches contribute to an improved appraisal of the obtained models, both in terms of the incorporation of prior information in the algorithms and the posterior uncertainty quantification. In addition, the developed strategies can be applied to other geophysical methods, and offer great flexibility to incorporate additional information when available.

Dynamic changes in brain functional connectivity during concurrent dual-task performance.

This study investigated the spatial, spectral, temporal and functional proprieties of functional brain connections involved in the concurrent execution of unrelated visual perception and working memory tasks. Electroencephalography data was analysed using a novel data-driven approach assessing source coherence at the whole-brain level. Three connections in the beta-band (18-24 Hz) and one in the gamma-band (30-40 Hz) were modulated by dual-task performance. Beta-coherence increased within two dorsofrontal-occipital connections in dual-task conditions compared to the single-task condition, with the highest coherence seen during low working memory load trials. In contrast, beta-coherence in a prefrontal-occipital functional connection and gamma-coherence in an inferior frontal-occipitoparietal connection was not affected by the addition of the second task and only showed elevated coherence under high working memory load. Analysis of coherence as a function of time suggested that the dorsofrontal-occipital beta-connections were relevant to working memory maintenance, while the prefrontal-occipital beta-connection and the inferior frontal-occipitoparietal gamma-connection were involved in top-down control of concurrent visual processing. The fact that increased coherence in the gamma-connection, from low to high working memory load, was negatively correlated with faster reaction time on the perception task supports this interpretation. Together, these results demonstrate that dual-task demands trigger non-linear changes in functional interactions between frontal-executive and occipitoparietal-perceptual cortices.

Dynamic and Regulated Association of Caveolin with Lipid Bodies: Modulation of Lipid Body Motility and Function by a Dominant Negative Mutant

Caveolins are a crucial component of caveolae but have also been localized to the Golgi complex, and, under some experimental conditions, to lipid bodies (LBs). The physiological relevance and dynamics of LB association remain unclear. We now show that endogenous caveolin-1 and caveolin-2 redistribute to LBs in lipid loaded A431 and FRT cells. Association with LBs is regulated and reversible; removal of fatty acids causes caveolin to rapidly leave the lipid body. We also show by subcellular fractionation, light and electron microscopy that during the first hours of liver regeneration, caveolins show a dramatic redistribution from the cell surface to the newly formed LBs. At later stages of the regeneration process (when LBs are still abundant), the levels of caveolins in LBs decrease dramatically. As a model system to study association of caveolins with LBs we have used brefeldin A (BFA). BFA causes rapid redistribution of endogenous caveolins to LBs and this association was reversed upon BFA washout. Finally, we have used a dominant negative LB-associated caveolin mutant (cavDGV) to study LB formation and to examine its effect on LB function. We now show that the cavDGV mutant inhibits microtubule-dependent LB motility and blocks the reversal of lipid accumulation in LBs.

Cholesterol and Fatty Acids Regulate Dynamic Caveolin Trafficking through the Golgi Complex and between the Cell Surface and Lipid Bodies

Caveolins are a crucial component of plasma membrane (PM) caveolae but have also been localized to intracellular compartments, including the Golgi complex and lipid bodies. Mutant caveolins associated with human disease show aberrant trafficking to the PM and Golgi accumulation. We now show that the Golgi pool of mainly newly synthesized protein is detergent-soluble and predominantly in a monomeric state, in contrast to the surface pool. Caveolin at the PM is not recognized by specific caveolin antibodies unless PM cholesterol is depleted. Exit from the Golgi complex of wild-type caveolin-1 or -3, but not vesicular stomatitis virus-G protein, is modulated by changing cellular cholesterol levels. In contrast, a muscular dystrophy-associated mutant of caveolin-3, Cav3P104L, showed increased accumulation in the Golgi complex upon cholesterol treatment. In addition, we demonstrate that in response to fatty acid treatment caveolin can follow a previously undescribed pathway from the PM to lipid bodies and can move from lipid bodies to the PM in response to removal of fatty acids. The results suggest that cholesterol is a rate-limiting component for caveolin trafficking. Changes in caveolin flux through the exocytic pathway can therefore be an indicator of cellular cholesterol and fatty acid levels.

One minute of grief: Emotional processing in short-term dynamic psychotherapy for adjustment disorder.

OBJECTIVE: Depth of emotional processing has shown to be related to outcome across approaches to psychotherapy. Moreover, a specific emotional sequence has been postulated and tested in several studies on experiential psychotherapy (Pascual-Leone & Greenberg, 2007). This process-outcome study aims at reproducing the sequential model of emotional processing in psychodynamic psychotherapy for adjustment disorder and linking these variables with ultimate therapeutic outcome. METHOD: In this study, 32 patients underwent short-term dynamic psychotherapy. On the basis of reliable clinical change statistics, a subgroup (n = 16) presented with good outcome and another subgroup (n = 16) had a poor outcome in the end of treatment. The strongest alliance session of each case was rated using the observer-rated system Classification of Affective Meaning States. Reliability coefficients for the measure were excellent (κ = .82). RESULTS: Using 1 min as the fine-grained unit of analysis, results showed that the experience of fundamentally adaptive grief was more common in the in-session process of patients with good outcome, compared with those with poor outcomes (χ2 = 6.56, p = .01, d = 1.23). This variable alone predicted 19% of the change in depressive symptoms as measured by the Beck Depression Inventory at the end of treatment. Moreover, sequences of the original model were supported and related to outcome. CONCLUSIONS: These results are discussed within the framework of the sequential model of emotional processing and its possible relevance for psychodynamic psychotherapy. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Numerical analysis of wave-induced fluid flow effects on seismic data: Application to monitoring of CO2 storage at the Sleipner Field

In this work we analyze how patchy distributions of CO2 and brine within sand reservoirs may lead to significant attenuation and velocity dispersion effects, which in turn may have a profound impact on surface seismic data. The ultimate goal of this paper is to contribute to the understanding of these processes within the framework of the seismic monitoring of CO2 sequestration, a key strategy to mitigate global warming. We first carry out a Monte Carlo analysis to study the statistical behavior of attenuation and velocity dispersion of compressional waves traveling through rocks with properties similar to those at the Utsira Sand, Sleipner field, containing quasi-fractal patchy distributions of CO2 and brine. These results show that the mean patch size and CO2 saturation play key roles in the observed wave-induced fluid flow effects. The latter can be remarkably important when CO2 concentrations are low and mean patch sizes are relatively large. To analyze these effects on the corresponding surface seismic data, we perform numerical simulations of wave propagation considering reservoir models and CO2 accumulation patterns similar to the CO2 injection site in the Sleipner field. These numerical experiments suggest that wave-induced fluid flow effects may produce changes in the reservoir's seismic response, modifying significantly the main seismic attributes usually employed in the characterization of these environments. Consequently, the determination of the nature of the fluid distributions as well as the proper modeling of the seismic data constitute important aspects that should not be ignored in the seismic monitoring of CO2 sequestration problems.

Intrathecal analgesia and restrictive perioperative fluid management within enhanced recovery pathway: hemodynamic implications.

BACKGROUND: Intrathecal analgesia and avoidance of perioperative fluid overload are key items within enhanced recovery pathways. Potential side effects include hypotension and renal dysfunction. STUDY DESIGN: From January 2010 until May 2010, all patients undergoing colorectal surgery within enhanced recovery pathways were included in this retrospective cohort study and were analyzed by intrathecal analgesia (IT) vs none (noIT). Primary outcomes measures were systolic and diastolic blood pressure, mean arterial pressure, and heart rate for 48 hours after surgery. Renal function was assessed by urine output and creatinine values. RESULTS: One hundred and sixty-three consecutive colorectal patients (127 IT and 36 noIT) were included in the analysis. Both patient groups showed low blood pressure values within the first 4 to 12 hours and a steady increase thereafter before return to baseline values after about 24 hours. Systolic and diastolic blood pressure and mean arterial pressure were significantly lower until 16 hours after surgery in patients having IT compared with the noIT group. Low urine output (<0.5 mL/kg/h) was reported in 11% vs 29% (IT vs noIT; p = 0.010) intraoperatively, 20% vs 11% (p = 0.387), 33% vs 22% (p = 0.304), and 31% vs 21% (p = 0.478) for postanesthesia care unit and postoperative days 1 and 2, respectively. Only 3 of 127 (2.4%) IT and 1 of 36 (2.8%) noIT patients had a transitory creatinine increase >50%; no patients required dialysis. CONCLUSIONS: Postoperative hypotension affects approximately 10% of patients within an enhanced recovery pathway and is slightly more pronounced in patients with IT. Hemodynamic depression persists for <20 hours after surgery; it has no measurable negative impact and therefore cannot justify detrimental postoperative fluid overload.