External validation of a prognostic model predicting time of death after withdrawal of life support in neurocritical patients

Department of Intensive Care, Center for Medical Decision Making, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.
Critical care medicine (Impact Factor: 6.15). 09/2011; 40(1):233-8. DOI: 10.1097/CCM.0b013e31822f0633
Source: PubMed

ABSTRACT The ability to predict the time of death after withdrawal of life support is of specific interest for organ donation after cardiac death. We aimed to externally validate a previously developed model to predict the probability of death within the time constraint of 60 mins after withdrawal of life-sustaining measures.
The probability to die within 60 mins for each patient in this validation sample was calculated based on the model developed by Yee et al, which includes four variables (absent corneal reflex, absent cough reflex, extensor or absent motor response, and an oxygenation index >4.2). Analyses included logistic regression modeling with bootstrapping to adjust for overoptimism. Performance was assessed by calibration (agreement between observed and predicted outcomes) and discrimination (distinction of those patients who die within 60 mins from those who do not, expressed by the area under the receiver operating characteristic curve).
Mixed intensive care unit in The Netherlands.
We analyzed data from 152 patients who died as a result of a neurologic condition between 2007 and 2009.
A total of 82 patients had sufficient data. Fifty (61%) died within 60 mins. Univariable and multivariable odds ratios of the predictors were very similar between the development and validation sample. The prediction model showed good discrimination with an area under the receiver operating characteristic curve of 0.75 (95% confidence interval [CI] 0.63-0.87) but calibration was modest. The mean predicted probability was 80%, overestimating the 61% overall observed risk of death within 60 mins. Modeling oxygenation index as a linear term led to an improved version of the Mayo NICU model. (area under the receiver operating characteristic curve [95% CI] = 0.774 [0.69-0.90], bootstrap-validated area under the receiver operating characteristic curve [95% CI] = 0.74 [0.66-0.87]).
The model discriminated well between patients who died within 60 mins after withdrawal of life support and those who did not. Further prospective validation is needed.

  • [Show abstract] [Hide abstract]
    ABSTRACT: A persistant shortage of available organs for transplantation has driven French medical authorities to focus on organ retrieval from patients who die following the withdrawal of life-sustaining therapy. This study was designed to assess the theoretical eligibility of patients who have died in French intensive care units (ICUs) after a decision to withhold or withdraw life-sustaining therapy to organ donation. This was an observational multi-center study in which data were collected on all consecutive patients admitted to any of the 43 participating ICUs during the study period who qualified for a withholding/withdrawal procedure according to French law. The theoretical organ donor eligibility of the patients once deceased was determined a posteriori according to current medical criteria for graft selection, as well as according to the withholding/withdrawal measures implemented and their impact on the time of death. A total of 5,589 patients were admitted to the ICU during the study period, of whom 777 (14 %) underwent withholding/withdrawal measures. Of the 557 patients who died following a foreseeable circulatory arrest, 278 (50 %) presented a contraindication ruling out organ retrieval. Of the 279 patients who would have been eligible as organ donors regardless of measures implemented, cardiopulmonary support was withdrawn in only 154 of these patients, 70 of whom died within 120 min of the withdrawal of life-sustaining treatment. Brain-injured patients accounted for 29 % of all patients who qualified for the withholding/withdrawal of treatment, and 57 % of those died within 120 min of the withdrawal/withholding of treatment. A significant number of patients who died during the study period in French ICUs under withholding/withdrawal conditions would have been eligible for organ donation. Brain-injured patients were more likely to die in circumstances which would have been compatible with such practice.
    Intensive Care Medicine 08/2014; 40(9). DOI:10.1007/s00134-014-3409-2 · 5.54 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Brain injury is well established as a cause of early mortality after out-of-hospital cardiac arrest (OHCA), but postresuscitation shock also contributes to these deaths. This study aims to describe the respective incidence, risk factors, and relation to mortality of post-cardiac arrest (CA) shock and brain injury. Retrospective analysis of an observational cohort. 24-bed medical intensive care unit (ICU) in a French university hospital. All consecutive patients admitted following OHCA were considered for analysis. Post-CA shock was defined as a need for infusion of vasoactive drugs after resuscitation. Death related to brain injury included brain death and care withdrawal for poor neurological evolution. None. Between 2000 and 2009, 1,152 patients were admitted after OHCA. Post-CA shock occurred in 789 (68 %) patients. Independent factors associated with its onset were high blood lactate and creatinine levels at ICU admission. During the ICU stay, 269 (34.8 %) patients died from post-CA shock and 499 (65.2 %) from neurological injury. Age, raised blood lactate and creatinine values, and time from collapse to restoration of spontaneous circulation increased the risk of ICU mortality from both shock and brain injury, whereas a shockable rhythm was associated with reduced risk of death from these causes. Finally, bystander cardiopulmonary resuscitation (CPR) decreased the risk of death from neurological injury. Brain injury accounts for the majority of deaths, but post-CA shock affects more than two-thirds of OHCA patients. Mortality from post-CA shock and brain injury share similar risk factors, which are related to the quality of the rescue process.
    European Journal of Intensive Care Medicine 08/2013; 39(11). DOI:10.1007/s00134-013-3043-4 · 5.17 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Summary - The aim of this study was to develop and validate a clinical tool to calculate the probabilities of asystole following withdrawal of life-sustaining treatment (WLST) in potential donation after circulatory death (DCD) donors in the United Kingdom, which is imperative to shared decision-making. A two-stage prospective observational cohort study was undertaken in multi-centre mixed and neurological adult intensive care units in the United Kingdom. One hundred and sixty three potential DCD donors who underwent WLST were included in this study between 2010-2011. An asystole prediction-scoring (APS) tool incorporating clinical variables, assimilated to a score on the basis of derived severity was validated. Data were collected at two time points: initial referral and 60 minutes prior to WLST. Cox regression analysis determined overall probabilities of asystole following WLST. Cox regression demonstrated statistically significant (p<0.05) probabilities of asystole using the APS tool. Probabilities of asystole were produced for time points between 0 and 240 minutes. Lower scores have a low probability of asystole occurring within 180 minutes while higher scores have a high probability of asystole occurring at all time points. Potential donors with APS total scores greater than 30 all died within 180 minutes of WLST. The APS tool provides important information on the likelihood of asystole within defined time lines. This ability to predict time lines could be used by clinicians in decision-making in referring potential DCD donors, and through sharing probabilities of donation occurring with family members thereby facilitating shared decision-making to underpin informed consent.
    Cells Tissues Organs 01/2013; 16(3):189-197. · 1.96 Impact Factor


Available from
Jun 5, 2014