Model for predicting short-term mortality of severe sepsis

International audienceABSTRACT: INTRODUCTION: To establish a prognostic model for predicting 14-day mortality in ICU patients with severe sepsis overall and according to place of infection acquisition and to sepsis episode number. METHODS: In this prospective multicentre observational study on a multicentre database (OUTCOMEREA) including data from 12 ICUs, 2268 patients with 2737 episodes of severe sepsis were randomly divided into a training cohort (n=1458) and a validation cohort (n=810). Up to four consecutive severe sepsis episodes per patient occurring within the first 28 ICU days were included. We developed a prognostic model for predicting death within 14 days after each episode, based on patient data available at sepsis onset. RESULTS: Independent predictors of death were logistic organ dysfunction (OR, 1.22 per point, p<10-4), septic shock (OR, 1.40; p=0.01), rank of severe sepsis episode (1 reference, 2: OR, 1.26; p=0.10 [greater than or equal to]3: OR, 2.64 ;10-3), multiple sources of infection (OR; 1.45, p=0.03), simplified acute physiology score II (OR, 1.02 per point; p<10-4), McCabe score ([greater than or equal to]2)(OR, 1.96; p<10-4), and number of chronic co-morbidities (1: OR, 1.75; p=10-3, [greater than or equal to]2: OR, 2.24, p= 10-3). Validity of the model was good in whole cohorts (AUC-ROC, 0.76; 95%CI [0.74; 0.79] and HL Chi-square: 15.3 (p=0.06) for all episodes pooled). CONCLUSIONS: In ICU patients, a prognostic model based on a few easily obtained variables is effective in predicting death within 14 days after the first to fourth episode of severe sepsis complicating community-, hospital-, or ICU-acquired infection

Norepinephrine weaning in septic shock patients by closed loop control based on fuzzy logic

International audienceABSTRACT: INTRODUCTION: The rate of weaning of vasopressors drugs is usually an empirical choice made by the treating in critically ill patients. We applied fuzzy logic principles to modify intravenous norepinephrine (noradrenaline) infusion rates during norepinephrine infusion in septic patients in order to reduce the duration of shock. METHODS: Septic patients were randomly assigned to norepinephrine infused either at the clinician's discretion (control group) or under closed-loop control based on fuzzy logic (fuzzy group). The infusion rate changed automatically after analysis of mean arterial pressure in the fuzzy group. The primary end-point was time to cessation of norepinephrine. The secondary end-points were 28-day survival, total amount of norepinephine infused and duration of mechanical ventilation. RESULTS: Nineteen patients were randomly assigned to fuzzy group and 20 to control group. Weaning of norepinephrine was achieved in 18 of the 20 control patients and in all 19 fuzzy group patients. Median (interquartile range) duration of shock was significantly shorter in the fuzzy group than in the control group (28.5 [20.5 to 42] hours versus 57.5 [43.7 to 117.5] hours; P < 0.0001). There was no significant difference in duration of mechanical ventilation or survival at 28 days between the two groups. The median (interquartile range) total amount of norepinephrine infused during shock was significantly lower in the fuzzy group than in the control group (0.6 [0.2 to 1.0] mug/kg versus 1.4 [0.6 to 2.7] mug/kg; P < 0.01). CONCLUSIONS: Our study has shown a reduction in norepinephrine weaning duration in septic patients enrolled in the fuzzy group. We attribute this reduction to fuzzy control of norepinephrine infusion. TRIAL REGISTRATION: Trial registration: Clinicaltrials.gov NCT00763906

Multiple-center evaluation of mortality associated with acute kidney injury in critically ill patients: a competing risks analysis

International audienceINTRODUCTION: In this study, we aimed to assess the association between acute kidney injury (AKI) and mortality in critically ill patients using an original competing risks approach. METHODS: Unselected patients admitted between 1997 and 2009 to 13 French medical or surgical intensive care units were included in this observational cohort study. AKI was defined according to the RIFLE criteria. The following data were recorded: baseline characteristics, daily serum creatinine level, daily Sequential Organ Failure Assessment (SOFA) score, vital status at hospital discharge and length of hospital stay. Patients were classified according to the maximum RIFLE class reached during their ICU stay. The association of AKI with hospital mortality with "discharge alive" considered as a competing event was assessed according to the Fine and Gray model. RESULTS: Of the 8,639 study patients, 32.9% had AKI, of whom 19.1% received renal replacement therapy. Patients with AKI had higher crude mortality rates and longer lengths of hospital stay than patients without AKI. In the Fine and Gray model, independent risk factors for hospital mortality were the RIFLE classes Risk (sub-hazard ratio (SHR) 1.58 and 95% confidence interval (95% CI) 1.32 to 1.88; P < 0.0001), Injury (SHR 3.99 and 95% CI 3.43 to 4.65; P < 0.0001) and Failure (SHR 4.12 and 95% CI 3.55 to 4.79; P < 0.0001); nonrenal SOFA score (SHR 1.19 per point and 95% CI 1.18 to 1.21; P < 0.0001); McCabe class 3 (SHR 2.71 and 95% CI 2.34 to 3.15; P < 0.0001); and respiratory failure (SHR 3.08 and 95% CI 1.36 to 7.01; P < 0.01). CONCLUSIONS: By using a competing risks approach, we confirm in this study that AKI affecting critically ill patients is associated with increased in-hospital mortality

The future sea-level contribution of the Greenland ice sheet: A multi-model ensemble study of ISMIP6

The Greenland ice sheet is one of the largest contributors to global mean sea-level rise today and is expected to continue to lose mass as the Arctic continues to warm. The two predominant mass loss mechanisms are increased surface meltwater run-off and mass loss associated with the retreat of marine-terminating outlet glaciers. In this paper we use a large ensemble of Greenland ice sheet models forced by output from a representative subset of the Coupled Model Intercomparison Project (CMIP5) global climate models to project ice sheet changes and sea-level rise contributions over the 21st century. The simulations are part of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6).We estimate the sea-level contribution together with uncertainties due to future climate forcing, ice sheet model formulations and ocean forcing for the two greenhouse gas concentration scenarios RCP8.5 and RCP2.6. The results indicate that the Greenland ice sheet will continue to lose mass in both scenarios until 2100, with contributions of 90-50 and 32-17mm to sea-level rise for RCP8.5 and RCP2.6, respectively. The largest mass loss is expected from the south-west of Greenland, which is governed by surface mass balance changes, continuing what is already observed today. Because the contributions are calculated against an unforced control experiment, these numbers do not include any committed mass loss, i.e. mass loss that would occur over the coming century if the climate forcing remained constant. Under RCP8.5 forcing, ice sheet model uncertainty explains an ensemble spread of 40 mm, while climate model uncertainty and ocean forcing uncertainty account for a spread of 36 and 19 mm, respectively. Apart from those formally derived uncertainty ranges, the largest gap in our knowledge is about the physical understanding and implementation of the calving process, i.e. the interaction of the ice sheet with the ocean. © Author(s) 2020

The future sea-level contribution of the Greenland ice sheet: a multi-model ensemble study of ISMIP6

The Greenland ice sheet is one of the largest contributors to global mean sea-level rise today and is expected to continue to lose mass as the Arctic continues to warm. The two predominant mass loss mechanisms are increased surface meltwater run-off and mass loss associated with the retreat of marine-terminating outlet glaciers. In this paper we use a large ensemble of Greenland ice sheet models forced by output from a representative subset of the Coupled Model Intercomparison Project (CMIP5) global climate models to project ice sheet changes and sea-level rise contributions over the 21st century. The simulations are part of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6). We estimate the sea-level contribution together with uncertainties due to future climate forcing, ice sheet model formulations and ocean forcing for the two greenhouse gas concentration scenarios RCP8.5 and RCP2.6. The results indicate that the Greenland ice sheet will continue to lose mass in both scenarios until 2100, with contributions of 90±50 and 32±17 mm to sea-level rise for RCP8.5 and RCP2.6, respectively. The largest mass loss is expected from the south-west of Greenland, which is governed by surface mass balance changes, continuing what is already observed today. Because the contributions are calculated against an unforced control experiment, these numbers do not include any committed mass loss, i.e. mass loss that would occur over the coming century if the climate forcing remained constant. Under RCP8.5 forcing, ice sheet model uncertainty explains an ensemble spread of 40 mm, while climate model uncertainty and ocean forcing uncertainty account for a spread of 36 and 19 mm, respectively. Apart from those formally derived uncertainty ranges, the largest gap in our knowledge is about the physical understanding and implementation of the calving process, i.e. the interaction of the ice sheet with the ocean

Future Sea Level Change Under Coupled Model Intercomparison Project Phase 5 and Phase 6 Scenarios From the Greenland and Antarctic Ice Sheets

Projections of the sea level contribution from the Greenland and Antarctic ice sheets (GrIS and AIS) rely on atmospheric and oceanic drivers obtained from climate models. The Earth System Models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6) generally project greater future warming compared with the previous Coupled Model Intercomparison Project phase 5 (CMIP5) effort. Here we use four CMIP6 models and a selection of CMIP5 models to force multiple ice sheet models as part of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6). We find that the projected sea level contribution at 2100 from the ice sheet model ensemble under the CMIP6 scenarios falls within the CMIP5 range for the Antarctic ice sheet but is significantly increased for Greenland. Warmer atmosphere in CMIP6 models results in higher Greenland mass loss due to surface melt. For Antarctica, CMIP6 forcing is similar to CMIP5 and mass gain from increased snowfall counteracts increased loss due to ocean warming

MODÈLE À RISQUES COMPÉTITIFS ET ANALYSE DE PROPENSION APPLIQUÉS À L'ATTEINTE RÉNALE AIGUË EN RÉANIMATION

Acute kidney injury (AKI) is commonly encountered in critically ill patients. Although it has been extensively studied so far, may key issues remain unresolved. This aim of this thesis is to bring a new insight in the field through rigorous and original methodological approaches. In the first part, the prognostic impact of AKI is assessed through the Fine and Gray competing risks model. In the second part, the efficacy of renal replacement therapy (RRT) is evaluated by the propensity score technique. Finally, concerns about contrast-induced AKI, which has been surprisingly under investigated in the intensive care unit, are addressed in the third part. Results emphasize the poor outcome associated with AKI, cast some doubt on RRT efficacy and stress the need for urgent validation of early and sensitive diagnostic markers, and standardization of AKI management.L'atteinte rénale aiguë (ARA) est une pathologie fréquente en réanimation. La littérature actuelle sur le sujet est riche mais globalement hétérogène et confuse. Ainsi, plusieurs questions clés restent à ce jour sans réponse claire. Le but de cette thèse est d'apporter des éléments nouveaux dans le domaine dans un souci de rigueur et d'originalité méthodologiques. La première partie est consacrée à l'appréciation précise de l'impact pronostique de l'ARA par le modèle à risques compétitifs de Fine et Gray. La deuxième est dédiée à l'évaluation de l'efficacité de l'épuration extra-rénale (EER) par la technique du score de propension. La troisième, enfin, s'intéresse à l'ARA induite par les produits de contraste iodés, cas particulier potentiellement grave mais étonnamment peu étudié jusqu'alors en réanimation. Les résultats soulignent le pronostic sombre associé à la survenue d'une ARA, l'efficacité incertaine de l'EER et la nécessité urgente d'uniformisation des pratiques en termes de diagnostic et de thérapeutique

Incidence and outcome of contrast-associated acute kidney injury in a mixed medical-surgical ICU population: a retrospective study.

International audienceABSTRACT: BACKGROUND: Contrast-enhanced radiographic examinations carry the risk of contrast-associated acute kidney injury (CA-AKI). While CA-AKI is a well-known complication outside the intensive care unit (ICU) setting, data on CA-AKI in ICU patients are scarce. Our aim was to assess the incidence and short-term outcome of CA-AKI in a mixed medical-surgical ICU population. METHODS: We conducted a single-center retrospective analysis between September 2006 and December 2008 on adult patients who underwent a contrast-enhanced computed tomography for urgent diagnostic purposes. CA-AKI was defined as either a relative increment in serum creatinine of >= 25% or an absolute increment in serum creatinine of >= 0.3 mg/dL within 48 hrs after contrast administration. ICU mortality rates of patients with and without CA-AKI were compared in univariate and multivariate analyses. The need for renal replacement therapy (RRT) was also recorded. RESULTS: CA-AKI occurred in 24/143 (16.8%) patients. Coexisting risk factors for kidney injury, such as sepsis, nephrotoxic drugs and hemodynamic failure were commonly observed in patients who developed CA-AKI. ICU mortality was significantly higher in patients with than in those without CA-AKI (50% vs 21%, p = 0.004). In multivariate logistic regression, CA-AKI remained associated with ICU mortality (odds ratio: 3.48, 95% confidence interval: 1.10-11.46, p = 0.04). RRT was required in 7 (29.2%) patients with CA-AKI. CONCLUSIONS: In our cohort, CA-AKI was a frequent complication. It was associated with a poor short-term outcome and seemed to occur mainly when multiple risk factors for kidney injury were present. Administration of ICM should be considered as a potential high-risk procedure and not as a routine innocuous practice in ICU patients

A rapidly converging initialisation method to simulate the present-day Greenland ice sheet using the GRISLI ice sheet model (version 1.3)

International audienceProviding reliable projections of the ice sheet contribution to future sea-level rise has become one of the main challenges of the ice sheet modelling community. To increase confidence in future projections, a good knowledge of the present-day state of ice flow dynamics, which is critically dependent on basal conditions, is strongly needed. The main difficulty is tied to the scarcity of observations at the ice-bed interface at the scale of the whole ice sheet, resulting in poorly constrained parameterisations in ice sheet models. To circumvent this drawback, inverse modelling approaches can be developed to infer initial conditions for ice sheet models that best reproduce available data. Most often such approaches allow for a good representation of the mean present-day state of the ice sheet but are accompanied with unphys-ical trends. Here, we present an initialisation method for the Greenland ice sheet using the thermo-mechanical hybrid GRISLI (GRenoble Ice Shelf and Land Ice) ice sheet model. Our approach is based on the adjustment of the basal drag coefficient that relates the sliding velocities at the ice-bed interface to basal shear stress in unfrozen bed areas. This method relies on an iterative process in which the basal drag is periodically adjusted in such a way that the simulated ice thickness matches the observed one. The quality of the method is assessed by computing the root mean square errors in ice thickness changes. Because the method is based on an adjustment of the sliding velocities only, the results are discussed in terms of varying ice flow enhancement factors that control the deformation rates. We show that this factor has a strong impact on the minimisation of ice thickness errors and has to be chosen as a function of the internal thermal state of the ice sheet (e.g. a low enhancement factor for a warm ice sheet). While the method performance slightly increases with the duration of the minimisation procedure, an ice thickness root mean square error (RMSE) of 50.3 m is obtained in only 1320 model years. This highlights a rapid convergence and demonstrates that the method can be used for computation-ally expensive ice sheet models